identifier
stringlengths
11
32
pdf_url
stringlengths
17
4.62k
lang
stringclasses
120 values
error
stringclasses
1 value
title
stringlengths
2
500
source_name
stringlengths
1
435
publication_year
float64
1.9k
2.02k
license
stringclasses
3 values
word_count
int64
0
1.64M
text
stringlengths
1
9.75M
https://openalex.org/W2581422350
https://europepmc.org/articles/pmc5260126?pdf=render
English
null
On the cytokine/chemokine network during Plasmodium vivax malaria: new insights to understand the disease
Malaria journal
2,017
cc-by
8,367
*Correspondence: llbueno@icb.ufmg.br †Natália Satchiko Hojo-Souza and Dhelio Batista Pereira contributed equally to this work 1 Departamento de Parasitologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil Full list of author information is available at the end of the article Abstract Background:  The clinical outcome of malaria depends on the delicate balance between pro-inflammatory and immunomodulatory cytokine responses triggered during infection. Despite the numerous reports on characteriza‑ tion of plasma levels of cytokines/chemokines, there is no consensus on the profile of these mediators during blood stage malaria. The identification of acute phase biomarkers might contribute to a better understanding of the disease, allowing the use of more effective therapeutic approaches to prevent the progression towards severe disease. In the present study, the plasma levels of cytokines and chemokines and their association with parasitaemia and number of previous malaria episodes were evaluated in Plasmodium vivax-infected patients during acute and convalescence phase, as well as in healthy donors. Methods:  Samples of plasma were obtained from peripheral blood samples from four different groups: P. vivax- infected, P. vivax-treated, endemic control and malaria-naïve control. The cytokine (IL-6, IL-10, IL-17, IL-27, TGF-β, IFN-γ and TNF) and chemokine (MCP-1/CCL2, IP-10/CXCL10 and RANTES/CCL5) plasma levels were measured by CBA or ELISA. The network analysis was performed using Spearman correlation coefficient. Results:  Plasmodium vivax infection induced a pro-inflammatory response driven by IL-6 and IL-17 associated with an immunomodulatory profile mediated by IL-10 and TGF-β. In addition, a reduction was observed of IFN-γ plasma levels in P. vivax group. A lower level of IL-27 was observed in endemic control group in comparison to malaria-naïve control group. No significant results were found for IL-12p40 and TNF. It was also observed that P. vivax infection promoted higher levels of MCP-1/CCL2 and IP-10/CXCL10 and lower levels of RANTES/CCL5. The plasma level of IL-10 was elevated in patients with high parasitaemia and with more than five previous malaria episodes. Furthermore, association profile between cytokine and chemokine levels were observed by correlation network analysis indicating signature patterns associated with different parasitaemia levels. Conclusions:  The P. vivax infection triggers a balanced immune response mediated by IL-6 and MCP-1/CCL2, which is modulated by IL-10. In addition, the results indicated that IL-10 plasma levels are influenced by parasitaemia and number of previous malaria episodes. Keywords:  Plasmodium vivax, Malaria, Cytokines, Chemokines © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. On the cytokine/chemokine network during Plasmodium vivax malaria: new insights to understand the disease Natália Satchiko Hojo‑Souza1†, Dhelio Batista Pereira2†, Fernanda Sumika Hojo de Souza3, Tiago Antônio de Oliveira Mendes4, Mariana Santos Cardoso1, Mauro Shugiro Tada2, Graziela Maria Zanini5, Daniella Castanheira Bartholomeu1, Ricardo Toshio Fujiwara1 and Lilian Lacerda Bueno1* © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Hojo‑Souza et al. Malar J (2017) 16:42 DOI 10.1186/s12936-017-1683-5 Hojo‑Souza et al. Malar J (2017) 16:42 DOI 10.1186/s12936-017-1683-5 Malaria Journal Open Access Abstract The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Hojo‑Souza et al. Malar J (2017) 16:42 Page 2 of 10 Page 2 of 10 Background levels of pro- and anti-inflammatory cytokines and some chemokines were measured in this work during the acute phase of P. vivax naturally infected individuals. Samples were also obtained of some patients after anti-malarial drugs treatment to detect possible changes in the host immunological response after treatment and to identify biomarkers of active infection. Finally, analyses of cor- relation among cytokines/chemokines levels, degree of parasitaemia and number of infections were performed to evaluate whether variations in clinical manifestations are associated with activated or suppressed cytokine/ chemokine networks. Malaria is caused by a protozoan of the genus Plas- modium and is responsible for high morbidity rates (besides the cases of mortality, especially among chil- dren), resulting in serious impact on the socio-economic development in endemic regions. In the Brazilian Ama- zon region, Plasmodium vivax is the main species caus- ing malaria, being responsible for 82% of the cases [1]. Malaria is a complex disease involving genetic factors inherent to the parasite and to the host, geographical and environmental aspects that favour its occurrence and the difficulty of its eradication [2]. fi During infection, both the antibody-mediated and the cell-mediated immunity play an important role for achieving clinical immunity [3]. Several studies suggest that successful resolution of malaria infection depends on the ability of the host in inducing adequate levels of pro-inflammatory and regulatory cytokines during key stages of the infection. Thus, the fine-tuning between inflammatory and anti-inflammatory response appears to be a determinant factor in the clinical outcome of the disease [3–5]. Study participants and blood sample collection Study participants and blood sample collection Plasmodium vivax naturally infected individuals with uncomplicated symptomatic malaria (P. vivax group, n  =  75), P.vivax naturally infected individuals after 25  days of treatment with chloroquine and primaquine (P. vivax-treated group, n  =  10) and non-infected sub- jects with previous episodes of malaria (endemic control group, n = 10) were recruited at the Centro de Pesquisa em Medicina Tropical (Porto Velho, Rondônia, Brazil). In addition, 15 healthy donors (malaria-naïve control group) with no previous malaria exposure were recruited from a non-endemic area (Belo Horizonte, Minas Ger- ais, Brazil). The demographic, parasitological and clini- cal parameters of the subjects are shown in Table 1. The parasitological demonstration of P. vivax infection was performed by well-trained microscopists from the Cen- tro de Pesquisa em Medicina Tropical using thick smears and it was further confirmed by nested polymerase chain reaction (PCR) as previously described [16]. Peripheral venous blood was collected in heparin-containing tubes and centrifuged to obtain plasma. Samples were stored at −80 °C until performing the cytokine and chemokine assays. Although the mechanisms involved in host immuno- logical response during human malaria are still poorly understood, accumulating data suggest that malaria infection induces pro-inflammatory cytokines that elim- inate the parasite or promote the removal of red blood cells infected by the parasite [6]. This response is sup- pressed in turn by anti-inflammatory cytokines, and the clearance of remaining parasites as well as the preven- tion of recrudescence or re-infection, are mediated by anti-parasite antibodies [6]. However, depending on fac- tors such as genetic variability of host and parasite, age, number of infections and co-infections, the inflammatory response may be unregulated and, if excessive, it can lead to immunopathology.i Several studies have focused on the profile of plasma cytokines and chemokines in vivax malaria infection, comparing the repertoire of cytokines/chemokines elic- ited between P. vivax and Plasmodium falciparum infec- tion [7–11] and further association with disease severity, determined by clinical symptoms, or immunological profile after treatment with anti-malarial drugs [8–15]. Overall the profile of cytokine/chemokine production is still contradictory due to differences in study population, degree of endemicity in the region, among other factors, requiring further investigations.h Cytokine and chemokine plasma levels assays Cytokine and chemokine plasma levels assays Measurements of IL-6, IL-10, IL-17, MCP-1/CCL2, RANTES/CCL5 and IP-10/IP-10/CXCL10 in the plasma samples were conducted using cytometric bead assay (CBA) (BD Biosciences, USA) according to manufactur- er’s instructions. The data were collected using a FAC- SCan flow cytometer (BD Biosciences, USA) and the results were analysed in FCAP Array software (Soft Flow). The limit of detection for each assay was: IL-6 = 2.4 pg/ mL, IL-10  =  4.5  pg/mL, IL-17  =  18.9  pg/mL, MCP-1/ CCL2  =  2.7  pg/mL, RANTES/CCL5  =  1.0  pg/mL and IP-10/CXCL10  =  2.8  pg/mL. The upper-range lim- its of detection for the assays were 5000.0  pg/mL for chemokines (MCP-1/CCL2, RANTES/CCL5 and IP-10/ CXCL10), and 2500.0  pg/mL for cytokines (IL-6, IL-10 The characterization of immune responses elicited during vivax malaria and correlations with the clinical symptoms can reveal important aspects for understand- ing the pathogenesis of the disease and provide insights for the development of more effective vaccines and even new therapeutic approaches. Because of this, the plasma Hojo‑Souza et al. Malar J (2017) 16:42 Page 3 of 10 Table 1  Demographic, parasitological and  symptomato- logical parameters of the study population The parasitaemia and symptoms in the P. vivax-treated group refers to acute phase. The n for symptoms were: P. vivax group (n = 68) and P. vivax-treated group (n = 8) Parameters Value for group Control (n = 15) Endemic Control (n = 10) P. vivax (n = 75) P. Statistical analysis Statistical analyses were conducted using the Prism soft- ware 5.0 for Windows (GraphPad Inc, USA). Initially, Grubb’s test was applied to detect possible outliers and the Kolmogorov-Smirnoff test was used to verify the data distribution. Comparisons among groups were per- formed using Kruskal–Wallis test followed by Dunn’s Post-hoc test or Mann–Whitney U test. The paired t test and Wilcoxon test were also applied, according to data distribution. Statistical differences were considered sig- nificant when p values were less or equal to 0.05. Results were corrected for multiple comparisons as needed. Correlation networks were generated by the analysis of relationship among cytokine and chemokine plasma level datasets. Initially, pair-wise Spearman correlation coefficients were calculated using a scientific computing library (SciPy) and python programming language. Along with the Spearman rank-order correlation coefficient, the p value to test for non-correlation was evaluated using p ≤ 0.05 as a cut-off. The correlation strength was sepa- rated into three ranges: weak (0.2 ≤ r < 0.5), moderate (0.5 ≤ r < 0.7) and strong (0.7 ≤ r ≤ 1.0). Cytokine and chemokine plasma levels assays vivax- treated (n = 10) Age [median(range)] 27 (19–35) 38 (21–49) 37 (20–80) 42 (21–50) Gender [n(%)]  Male 10 (66.7) 6 (60.0) 57 (76.0) 6 (60.0)  Female 5 (33.3) 4 (40.0) 18 (24.0) 4 (40.0) Parasitaemia (parasites/mm3), [n = (%)]  ≤500 – – 34 (45.3) –  501–10,000 – – 26 (34.7) –  10,001–100,000 – – 8 (10.7) –  Without informa‑ tion – – 7 (9.3) – Nº of previous malaria episodes [n(%)]  First malaria – 3 (30.0) 10 (13.3) 1 (10.0)  ≤5 – 2 (20.0) 24 (32) 2 (20.0)  >5 – 5 (50.0) 33 (44.0) 6 (60.0)  Without informa‑ tion 0 (0.0) 8 (10.7) 1 (10.0) Symptoms [n(%)]  Fever – – 66 (97.1) –  Headache – – 66 (97.1) –  Myalgia – – 61 (89.7) –  Chills – – 60 (88.2) –  Sweating – – 51 (75.0) –  Arthralgia – – 49 (72.1) –  Nausea – – 36 (52.9) –  Vomiting – – 20 (29.4) – Table 1  Demographic, parasitological and  symptomato- logical parameters of the study population for IL-12p40, 31.2 pg/mL for TGF-β, and15.6 pg/mL for IFN-γ and TNF. The upper-range limits of detection for the assays were 10,000.0 pg/mL for IL-27, 4000.0 pg/mL for IL-12p40, 2000.0  pg/mL for TGF-β, and 1000.0  pg/ mL for IFN-γ and TNF. Dilution of samples was per- formed whenever necessary to ensure the obtained val- ues fell within the range of the generated standard curve. for IL-12p40, 31.2 pg/mL for TGF-β, and15.6 pg/mL for IFN-γ and TNF. The upper-range limits of detection for the assays were 10,000.0 pg/mL for IL-27, 4000.0 pg/mL for IL-12p40, 2000.0  pg/mL for TGF-β, and 1000.0  pg/ mL for IFN-γ and TNF. Dilution of samples was per- formed whenever necessary to ensure the obtained val- ues fell within the range of the generated standard curve. Plasmodium vivax infection triggers a marked pro‑inflammatory cytokine responsehl Plasmodium vivax infection triggers a marked pro‑inflammatory cytokine responsehl The parasitaemia and symptoms in the P. vivax-treated group refers to acute phase. The n for symptoms were: P. vivax group (n = 68) and P. vivax-treated group (n = 8) The parasitaemia and symptoms in the P. vivax-treated group refers to acute phase. The n for symptoms were: P. vivax group (n = 68) and P. vivax-treated group (n = 8) The circulating levels of pro-inflammatory cytokines such as IL-6, IL-17, IL-12p40, and TNF were prominent in P. vivax naturally infected individuals when compared to plasma levels observed in other groups (malaria-naïve, endemic and P. vivax-treated) (Fig. 1a–d), although sig- nificant differences to control groups were observed only for IL-6 and IL-17 (p < 0.0001 and p = 0.0051, respec- tively) (Fig. 1a, b). Conversely, the P. vivax infection resulted in a significant reduction of IFN-γ plasma levels when compared to control groups (p < 0.0001) (Fig. 1e), with circulating levels of IFN-γ detected in only 20% of the samples from P. vivax group. and IL-17) detection. Dilution of samples was performed whenever necessary to ensure the obtained values fell within the range of the generated standard curve. Enzyme-linked immunosorbent assay (ELISA) was performed for the measurement of IL-12p40, IL-27, IFN- γ, TNF and TGF-β (R&D Systems, USA), according to manufacturer’s instructions. Biotin-labeled antibodies were used for detection and the assay was revealed with streptavidin-HRP (Amersham Biosciences, USA) using OPD (o-Phenylenediamine dihydrochloride) substrate system (Sigma, USA). The colorimetric reaction was read using an automated ELISA microplate reader (Versa- max, Molecular Devices, USA) at 492 nm. The cytokine concentration was calculated from the standard curve using seven-parameter curve fitting software (SOFT- maxPro 5.3, Molecular Devices). The limit of detection for each assay was 156.0  pg/mL for IL-27, 62.5  pg/mL After treatment, production of IL-6, IL-12p40, TNF and IFN-γ were restored to baseline levels (p < 0.001 for IL-6 and p < 0.05 for IFN-γ, only), in contrast to plasma levels of IL-17, which were similar to those presented by infected individuals before treatment. In addition, it was also observed a significant decrease of IL-6 after treat- ment during a paired analysis (Fig. 1f). Hojo‑Souza et al. Malar J (2017) 16:42 Page 4 of 10 Fig. 1  Inflammatory cytokine plasma levels. Higher levels of IL‑10 and TGF‑β were also induced during Plasmodium vivax infection Higher levels of IL‑10 and TGF‑β were also induced during Plasmodium vivax infection and P. vivax-treated individuals). However, significant differences were observed only between the malaria- naïve control (median = 1257.0 pg/mL) and endemic control (median = 105.3 pg/mL) groups (p = 0.0389, Fig. 3). Production of IL-10 was only observed in the P. vivax group, being present in 94.4% of the plasma samples (median  =  186.1  pg/mL). After treatment, the IL-10 level returned to basal levels, equivalent to levels observed in control groups (p < 0.001) (Fig. 2a). Similar result was observed for the paired analysis comparing the cytokine levels before and after treatment (Fig. 2b). Moreover, samples from P. vivax group presented sig- nificant higher levels of TGF-β (median  =  42.8  pg/ mL) when compared to malaria-naïve control group (median  =  10.3  pg/mL) (p  =  0.0353) but similar pro- duction of this cytokine when compared to endemic control (median  =  48.9  pg/mL) and P. vivax-treated (median = 43.7 pg/mL) groups (Fig. 2c). No significant differences in the TGF-β production was observed for the paired analysis comparing the cytokine level before and after treatment (p = 0.7344). Plasmodium vivax infection induced higher levels of MCP‑1/CCL2 and IP‑10/CXCL10 and lower levels of RANTES/CCL5h The plasma levels of MCP-1/CCL2 were increased in P. vivax-infected individuals (median  =  770.6  pg/ mL) when compared to malaria-naïve control group (median  =  97.3  pg/mL) and endemic con- trol group (median  =  76.0  pg/mL) (Fig. 4a), with fur- ther re-establishment to basal levels after treatment (median  =  104.5  pg/mL) (p  <  0.0001). Plasma samples from P. vivax-infected donors also presented higher lev- els of IP-10/CXCL10 in comparison to control groups (p  <  0.0001) but, similarly to MCP-1/CCL2, the IP-10/ CXCL10 plasma level in treated individuals presented a baseline production that is equivalent to control indi- viduals (p  <  0.001) (Fig. 4b). On the other hand, lower RANTES/CCL5 plasma levels were observed in individ- uals with P. vivax infection when compared to endemic control group (p = 0.0010) (Fig. 4c). Plasmodium vivax infection triggers a marked pro‑inflammatory cytokine responsehl Comparative analysis of IL-6 (a), IL-17 (b), IL-12p40 (c), TNF (d) and IFN-γ production among malaria- naïve control group (n = 15), endemic control group (n = 10), P. vivax group (n = 75) and P. vivax-treated group (n = 10) were performed using Kruskal–Wallis test followed by Dunn Post-hoc. The dotted lines (—) represent the detection limit of the assay. IL-6 levels in acute-phase and conva‑ lescence period from P. vivax-infected patients (e) was compared between P. vivax group (n = 10) and P. vivax-treated group using Paired t-test or Wilcoxon test, according to data distribution. A p value <0.05 was considered significant. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 Fig. 1  Inflammatory cytokine plasma levels. Comparative analysis of IL-6 (a), IL-17 (b), IL-12p40 (c), TNF (d) and IFN-γ production among malaria- naïve control group (n = 15), endemic control group (n = 10), P. vivax group (n = 75) and P. vivax-treated group (n = 10) were performed using Kruskal–Wallis test followed by Dunn Post-hoc. The dotted lines (—) represent the detection limit of the assay. IL-6 levels in acute-phase and conva‑ lescence period from P. vivax-infected patients (e) was compared between P. vivax group (n = 10) and P. vivax-treated group using Paired t-test or Wilcoxon test, according to data distribution. A p value <0.05 was considered significant. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 Immune response mediators established a complex network during Plasmodium vivax infection During P. vivax infection, the triggering of several plasma mediators might result in a complex interaction network, which may render a weak, moderate or strongly correla- tion among themselves. The network profiles observed in the P. vivax group, as well as the sub-groups classified according to the parasite load, are shown in Fig. 6. Inter- estingly, high parasitaemia network includes practically all correlation observed in the network of all infected patients (Fig. 6a) highlighting the importance of parasite numbers to host immune stimulation. The correlation network between plasma mediators is less connected in low (Fig. 6b) than high parasitaemia (Fig 6c). Fig. 3  Plasma levels of IL-27 during vivax malaria. Comparative analy‑ sis of IL-27 among malaria-naïve control group (n = 15), endemic control group (n = 10), P. vivax group (n = 75) and P. vivax-treated group (n = 10) were performed using Kruskal–Wallis test followed by Dunn Post-hoc. A p value <0.05 (*) was considered significant. The dotted lines (—) represent the detection limit of the assay Fig. 3  Plasma levels of IL-27 during vivax malaria. Comparative analy‑ sis of IL-27 among malaria-naïve control group (n = 15), endemic control group (n = 10), P. vivax group (n = 75) and P. vivax-treated group (n = 10) were performed using Kruskal–Wallis test followed by Dunn Post-hoc. A p value <0.05 (*) was considered significant. The dotted lines (—) represent the detection limit of the assay The comparison between plasma levels for both MCP-1/CCL2 and IP-10/CXCL10, before and after treat- ment (paired analysis), also showed significant differ- ences (p = 0.0048 and p = 0.0012, respectively) (Fig. 4d, e). Despite the absence of significant result between P. vivax group and P. vivax-treated group due probably to high variability of chemokine levels and differences of sample number, a significant increase was observed in the plasma level of RANTES/CCL5 in the paired t-test after the treatment when following the same individuals (Fig. 4f). Plasmodium vivax-infected patients presented a strong correlation between IL-6 and MCP-1/CCL2 (r  =  0.82, p  <  0.0001). Furthermore, moderate correlations were observed between IL-6 and IL-10 (r = 0.60, p < 0.0001) and between IL-12p40 and TNF-a (r = 0.54, p < 0.0001). Several weak correlations were observed among other cytokines and chemokines (Fig. 6a). Plasmodium vivax patients were further separated into two sub-groups according to parasitaemia: low (≤500 parasites/cu mm) and high (>501 parasites/cu mm). IL‑27 in vivax malaria IL-27 is a pleiotropic cytokine that can induce either a pro-inflammatory or immunoregulatory response. The production of IL-27 was reduced in individuals living in endemic areas (endemic control, P. vivax-infected Hojo‑Souza et al. Malar J (2017) 16:42 Page 5 of 10 Fig. 2  Regulatory cytokine plasma levels. Comparative analysis of IL-10 (a total production; b paired analysis between infected and treated individu‑ als) and TGF-β among malaria-naïve control group (n = 15), endemic control group (n = 10), P. vivax group (n = 75) and P. vivax-treated group (n = 10) were performed using Kruskal–Wallis test followed by Dunn Post-hoc. A p value <0.05 was considered significant. The dotted lines (—) represent the detection limit of the assay. Paired analysis was performed between P. vivax group (n = 10) and P. vivax-treated group using Paired t-test or Wilcoxon test, according to data distribution. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 Fig. 2  Regulatory cytokine plasma levels. Comparative analysis of IL-10 (a total production; b paired analysis between infected and treated individu‑ als) and TGF-β among malaria-naïve control group (n = 15), endemic control group (n = 10), P. vivax group (n = 75) and P. vivax-treated group (n = 10) were performed using Kruskal–Wallis test followed by Dunn Post-hoc. A p value <0.05 was considered significant. The dotted lines (—) represent the detection limit of the assay. Paired analysis was performed between P. vivax group (n = 10) and P. vivax-treated group using Paired t-test or Wilcoxon test, according to data distribution. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 Fig. 3  Plasma levels of IL-27 during vivax malaria. Comparative analy‑ sis of IL-27 among malaria-naïve control group (n = 15), endemic control group (n = 10), P. vivax group (n = 75) and P. vivax-treated group (n = 10) were performed using Kruskal–Wallis test followed by Dunn Post-hoc. A p value <0.05 (*) was considered significant. The dotted lines (—) represent the detection limit of the assay cu mm denominated as low parasitaemia and >501 par- asites/cu mm as high parasitaemia (Fig. 5a). Patients with low parasitaemia presented reduced levels of IL-10 (median = 56.2 pg/mL) in comparison to patients with high parasitaemia (median = 366.1 pg/mL) (p < 0.0134). Furthermore, higher number of previous malaria epi- sodes was associated with higher IL-10 plasma levels (p < 0.0242) (Fig. 5b). Immune response mediators established a complex network during Plasmodium vivax infection Patients with low para- sitaemia presented moderate/strong correlations among inflammatory mediators (IL-6/IFN-γand MCP-1/CCL2). On the other hand, only a weak correlation between nd number of previous malaria episodes *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 IL-6/IL-10 and IL-12p40/TNF was observed in this sub- population (Fig. 6b). Furthermore, patients with high parasitaemia presented moderate correlations between IL-6 and IP-10/CXCL10 (r  =  0.56, p  <  0.001), IL-10 and MCP-1/CCL2 (r  =  0.62, p  <  0.001), MCP-1/CCL2 and IP-10/CXCL10 (r = 0.55, p < 0.001) and IL-6/TNF (r = 0.55, p < 0.001) (Fig. 6c). Discussion While some studies have investigated cytokines/ chemokines plasma levels during P. vivax infection [7–15, 17–19], there is still no agreement regarding the produc- tion of cytokines/chemokines and protection. It is well established that a pro-inflammatory response is required for parasite elimination, but an immunomodulatory IL-6/IL-10 and IL-12p40/TNF was observed in this sub- population (Fig. 6b). Furthermore, patients with high parasitaemia presented moderate correlations between IL-6 and IP-10/CXCL10 (r  =  0.56, p  <  0.001), IL-10 and MCP-1/CCL2 (r  =  0.62, p  <  0.001), MCP-1/CCL2 and IP-10/CXCL10 (r = 0.55, p < 0.001) and IL-6/TNF (r = 0.55, p < 0.001) (Fig. 6c). IL-6/IL-10 and IL-12p40/TNF was observed in this sub- population (Fig. 6b). Furthermore, patients with high parasitaemia presented moderate correlations between IL-6 and IP-10/CXCL10 (r  =  0.56, p  <  0.001), IL-10 and MCP-1/CCL2 (r  =  0.62, p  <  0.001), MCP-1/CCL2 and IP-10/CXCL10 (r = 0.55, p < 0.001) and IL-6/TNF (r = 0.55, p < 0.001) (Fig. 6c). nd number of previous malaria episodes Plasmodium vivax-infected patients were separated into two groups according to parasitaemia:  ≤500 parasites/ Hojo‑Souza et al. Malar J (2017) 16:42 Page 6 of 10 Fig. 4  Chemokine plasma levels. Comparative analysis of MCP-1/CCL2 (a), IP-10/CXCL10 (b), and RANTES/CCL5 (c) production among malaria-naïve control group (n = 15), endemic control group (n = 10), P. vivax group (n = 75) and P. vivax-treated group (n = 10) were performed using Kruskal– Wallis test followed by Dunn Post-hoc. The dotted lines (—) represent the detection limit of the assay. Levels of MCP-1/CCL2 (D), IP-10/CXCL10 (e) and RANTES/CCL5 (f) in acute-phase and convalescence period from P. vivax infected patients were determined from P. vivax group (n = 10) and P. vivax-treated group using Paired t-test or Wilcoxon test, according to data distribution. A p value <0.05 was considered significant. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 Fig. 4  Chemokine plasma levels. Comparative analysis of MCP-1/CCL2 (a), IP-10/CXCL10 (b), and RANTES/CCL5 (c) production among malaria-naïve control group (n = 15), endemic control group (n = 10), P. vivax group (n = 75) and P. vivax-treated group (n = 10) were performed using Kruskal– Wallis test followed by Dunn Post-hoc. The dotted lines (—) represent the detection limit of the assay. Levels of MCP-1/CCL2 (D), IP-10/CXCL10 (e) and RANTES/CCL5 (f) in acute-phase and convalescence period from P. vivax infected patients were determined from P. vivax group (n = 10) and P. vivax-treated group using Paired t-test or Wilcoxon test, according to data distribution. A p value <0.05 was considered significant. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 Fig. 4  Chemokine plasma levels. Comparative analysis of MCP-1/CCL2 (a), IP-10/CXCL10 (b), and RANTES/CCL5 (c) production among malaria-naïve control group (n = 15), endemic control group (n = 10), P. vivax group (n = 75) and P. vivax-treated group (n = 10) were performed using Kruskal– Wallis test followed by Dunn Post-hoc. The dotted lines (—) represent the detection limit of the assay. Levels of MCP-1/CCL2 (D), IP-10/CXCL10 (e) and RANTES/CCL5 (f) in acute-phase and convalescence period from P. vivax infected patients were determined from P. vivax group (n = 10) and P. vivax-treated group using Paired t-test or Wilcoxon test, according to data distribution. A p value <0.05 was considered significant. Discussion The association between IL-10 plasma levels and high parasitaemia could reflect a self-regulation mecha- nism to protect the excessive inflammatory response because of high antigen stimulation. Fig. 5  IL-10 plasma levels and their associations. a Parasitaemia: high vs low number of parasites. Comparison between high (>500 parasites/cu mm, n = 33) and low (≤500 parasites/cu mm, n = 32) number of parasites was performed using Mann–Whitney test. b Number of previous malaria episodes. Comparisons among first malaria (n = 10), ≤5 episodes (n = 24) and >5 episodes (n = 32) were performed using Kruskal–Wallis test followed by Dunn Post-hoc. A p value <0.05 was considered significant. *p < 0.05. The dotted lines (—) represent the detection limit of the assay During acute episode of vivax malaria, several stud- ies have reported high plasma levels of IFN-γ [7, 10, 12, 15, 19]. In the present study, IFN-γ plasma levels were only observed in 20% of P. vivax patient samples. On the other hand, the majority of patients of this group pre- sented higher production of IL-17. However, reports on IL-17 production in the human malarial infection are poorly described [9, 11] and further investigations are required. It is important to highlight that IL-17 may be produced by macrophages, dendritic cells, NK, NKT, γdT cells, CD8+ and Th17 [23, 24] and the source of this cytokine during P. vivax infection needs more investiga- tion. A previous study showed that CD4+ T cells pro- ducing IL-17 were increased during vivax malaria [25]. The higher plasma levels of TGF-β and IL-6 in the acute phase could suggest the induction of IL-17, since naïve CD4+ T cells require stimulation by IL-6 and TGF-β, and possibly IL-1b, to differentiate in Th17 and to secrete IL-17 [23, 26, 27]. Th17 cells induced by IL-6 and TGF-β also produce IL-10, presenting a regulatory function [28]. It is important to highlight that the low levels of IFN-γ observed in P. vivax group could contribute to high levels response is also needed to prevent immunopathology [6]. In the present study, it was shown that P. vivax infec- tion induced increased levels of IL-6 and, after treatment, the plasma levels were restored. Discussion While some studies have investigated cytokines/ chemokines plasma levels during P. vivax infection [7–15, 17–19], there is still no agreement regarding the produc- tion of cytokines/chemokines and protection. It is well established that a pro-inflammatory response is required for parasite elimination, but an immunomodulatory Hojo‑Souza et al. Malar J (2017) 16:42 Page 7 of 10 Fig. 5  IL-10 plasma levels and their associations. a Parasitaemia: high vs low number of parasites. Comparison between high (>500 parasites/cu mm, n = 33) and low (≤500 parasites/cu mm, n = 32) number of parasites was performed using Mann–Whitney test. b Number of previous malaria episodes. Comparisons among first malaria (n = 10), ≤5 episodes (n = 24) and >5 episodes (n = 32) were performed using Kruskal–Wallis test followed by Dunn Post-hoc. A p value <0.05 was considered significant. *p < 0.05. The dotted lines (—) represent the detection limit of the assay induces higher levels of IL-10 during acute phase of vivax malaria [7, 8, 10–13, 15, 17–19] and that the cytokine levels were restored to baseline after treatment [8, 10, 11, 14]. Indeed, a previous study demonstrated that CD4+CD25+ T cells producing IL-10 play a significant role during Plasmodium infection, possibly controlling the pro-inflammatory cytokines IFN-γ and TNF [6]. Of note, previous studies also demonstrated the increased number of circulating Treg cells (CD4+CD25+Foxp3+) during P. vivax infection [20, 21]. Regarding the asso- ciation between IL-10 plasma levels with parasitaemia and number of previous malaria episodes, in the pre- sent study, it was observed higher IL-10 plasma levels in patients with high parasitaemia (>501 parasites/cu mm) and with more than five previous malaria episodes. Similar result was observed for the association with par- asitaemia, but not with number of previous malaria epi- sodes [18]. The significance of IL-6 and IL-10 has been highlighted during vivax  malaria. High levels of these cytokines were observed in uncomplicated cases [18, 22], while low IL-6 levels were observed in patients with complicated malaria [22]. In addition, a positive correla- tion between IL-6 and IL-10 has also been observed in P. vivax infection [10, 18, 22]. Likewise, in the present study correlation analysis between IL-6 and IL-10 demon- strated a positive correlation (r = 0.60) in P. vivax group, suggesting the acquisition of a more immunomodulatory profile. Discussion vivax sub-group with high parasitaemia (> 500 parasites/cu mm) (n = 34). The correlation analyses were evaluated by Spearman correlation test. A p value <0.05 was considered significant of IL-17 once IFN-γ negatively regulates the generation of IL-17-producing cells [29]. accentuated in severe cases [33]. Thus, the IL-27 role in vivax malaria needs further investigation. Despite the high TGF-β plasma levels observed during P. vivax infection, there was no consensus about these findings [8, 10, 15]. TGF-β is a potent inductor of Treg cells [30], which may have contributed to the high IL-10 plasma levels observed. Although high IL-17 plasma lev- els were observed in P. vivax group, only a weak nega- tive correlation was detected between IL-17 and TGF-β by the network analysis approach. This connection was also found in low parasite load sub-group. Therefore, the IL-17 and TGF-β roles during P. vivax infection require additional investigations. Regarding IL-12p40 and TNF, no significant results were observed in the present study. However, differences in literature findings occur for both cytokines in acute phase [7, 8, 10–13, 15, 17–19] and convalescence period [8, 10, 11, 13, 14]. MCP-1/CCL2, known as Monocyte Chemoattract- ant Protein-1, is a powerful attractant of monocytes, T cells and dendritic cells to inflammatory sites. This chemokine is produced by several cell types, such as  epithelial, endothelial, smooth muscle, fibroblasts, astrocytes, monocytes, and microglial cells, and can be induced by TNF, IL-1 and endotoxins [34]. In the present study, high plasma levels of MCP-1/CCL2 were observed during P. vivax infection. Similar result was previous described during P. vivax infection [7]. The pro-inflam- matory IL-6 cytokine induced the mRNA expression and MCP-1 secretion by peripheral blood mononuclear cells [35]. During blood stage of P. vivax infection both IL-6 and MCP-1/CCL2 were significantly elevated. The  net- work analysis revealed a strong correlation between IL-6 and MCP-1/CCL2, regardless of parasite load, suggest- ing that these mediators were induced by the infection itself. These findings support the hypothesis that IL-6 and MCP-1/CCL2 pathway plays a central role in response to P. vivax infection. Interestingly, the network analyses for the high and low parasitaemia groups have shown that individuals with high parasitaemia exhibit moder- ate/strong correlation between IL-6/IL-10 and MCP-1/ CCL2. However, patients with low parasitaemia exhib- ited weak correlation between IL-6 and IL-10, losing the IL-27 is a pleiotropic cytokine with both pro- and anti- inflammatory actions. Discussion These findings were in agreement with previous studies during acute phase [11, 15, 17, 18] although the controversial data in the litera- ture with reduction [10, 14] or increase [11] of IL-6 after the treatment, which might be attributed to convales- cence period range (7–45 days) in the different studies [8, 10, 11, 13, 14].l Higher levels of some pro-inflammatory mediators such as IL-6, MCP-1/CCL2 and IP-10/CXCL10 were observed in P. vivax-infected patients, which were re-established after anti-malarial treatment, suggesting that the parasite infection triggered an inflammatory response. Concomi- tantly, it seems to be a consensus that P. vivax infection Hojo‑Souza et al. Malar J (2017) 16:42 Page 8 of 10 Fig. 6  Plasma mediators network. Correlations among 11 mediators during P. vivax infection were plotted in network graphs. Each circle represents a cytokine or chemokine and the connecting lines represent significant correlations between two mediators. Solid and dotted lines, respectively, represent positive and negative correlations. The line thickness represents the significance degree. a P. vivax group (n = 73). b P. vivax sub-group with low parasitaemia (≤500 parasites/cu mm) (n = 34). c P. vivax sub-group with high parasitaemia (> 500 parasites/cu mm) (n = 34). The correlation analyses were evaluated by Spearman correlation test. A p value <0.05 was considered significant Fig. 6  Plasma mediators network. Correlations among 11 mediators during P. vivax infection were plotted in network graphs. Each circle represents a cytokine or chemokine and the connecting lines represent significant correlations between two mediators. Solid and dotted lines, respectively, represent positive and negative correlations. The line thickness represents the significance degree. a P. vivax group (n = 73). b P. vivax sub-group with low parasitaemia (≤500 parasites/cu mm) (n = 34). c P. vivax sub-group with high parasitaemia (> 500 parasites/cu mm) (n = 34). The correlation analyses were evaluated by Spearman correlation test. A p value <0.05 was considered significant Fig. 6  Plasma mediators network. Correlations among 11 mediators during P. vivax infection were plotted in network graphs. Each circle represents a cytokine or chemokine and the connecting lines represent significant correlations between two mediators. Solid and dotted lines, respectively, represent positive and negative correlations. The line thickness represents the significance degree. a P. vivax group (n = 73). b P. vivax sub-group with low parasitaemia (≤500 parasites/cu mm) (n = 34). c P. Authors’ contributions NSHS, DBP, FSHS, TAOM, MSC, RTF, and LLB conceived and designed the exper‑ iments; NSHS and DBP performed the experiments; NSHS, DBP, FSHS, MSC, TAOM, RTF and LLB analysed the data; NSHS, DBP, FSHS, TAOM, MSC, GMZ, DCB, RTF and LLB contributed reagents/materials/analysis tools; NSHS, DBP, FSHS, TAOM, MSC, DCB, RTF, and LLB wrote the paper; DBP and MST assisted with patient care and case identification. All authors read and approved the final manuscript. References 1. WHO. World malaria report 2014. Geneva: World Health Organiza‑ tion; 2014. http://www.who.int/malaria/publications/world_malaria_ report_2014/en/. Accessed 15 Nov 2014. 2. Struik SS, Riley EM. Does malaria suffer from lack of memory? Immunol Rev. 2004;201:268–90. 3. Artavanis-Tsakonas K, Tongren JE, Riley EM. The war between the malaria parasite and the immune system: immunity, immunoregulation and immunonopathology. Clin Exp Immunol. 2003;133:145–52. 4. Finney OC, Riley EM, Walther M. Regulatory T cells in malaria—friend or foe? Trends Immunol. 2010;31:63–70. 5. Hansen DS, Schofield L. Natural regulatory T cells in malaria: host or parasite allies? PLoS Pathog. 2010;6:e1000771. 6. Riley EM. Regulating immunity to malaria. Parasite Immunol. 2006;28:35–49. 1. WHO. World malaria report 2014. Geneva: World Health Organiza‑ tion; 2014. http://www.who.int/malaria/publications/world_malaria_ report_2014/en/. Accessed 15 Nov 2014. Discussion This cytokine is a potent inhibitor of Th17 cell development and of IL-17 induction [31, 32]. In the present study, low IL-27 levels were observed in endemic control group compared to malaria-naïve con- trol group. However, no difference was observed regard- ing to IL-17 between the control groups. In children infected with P. falciparum, IL-27 plasma levels were decreased during uncomplicated malaria in compari- son to endemic control group. This reduction was more Hojo‑Souza et al. Malar J (2017) 16:42 Page 9 of 10 P. vivax acute infection. IL-6, MCP-1/CCL2 and IL-10 could be recognized as biomarkers of acute phase of P. vivax infection. These results provide new insights into the complex relationship among mediators that are trig- gered during P. vivax clinical malaria. interaction between IL-10 andMCP-1/CCL2. These data associated with the positive correlation between IL-6/ IFN-γ reinforce the significance of the IL-6/MCP-1/ IFN-γ axis in controlling parasitaemia, which could con- tribute to the lower parasite load observed. IP-10/CXCL10 (IFN-inducible protein 10) is another chemokine that is induced by IFN-γ [36] as well as by IL-17 [37] in different cell types. This chemokine is involved in inflammatory processes, being capable of attracting macrophages, dendritic cells, NK cells and activated CD4+ and CD8+ T cells towards inflamed tis- sues [36]. In the present study, P. vivax infected patients presented elevated IP-10/CXCL10 plasma levels, but only weak positive correlation with IFN-γ. No correlation was observed between IP-10/CXCL10 and IL-17, although both mediators were elevated during P. vivax infection. However, when patients were separated according to the parasite load, this connection was lost, and moder- ate correlation was established between IP-10/CXCL10 and IL-6, only in patients with high parasitaemia. In  P. falciparum infection, IP-10/CXCL10 has been identified as biomarker (in serum and cerebrospinal fluid) associ- ated with elevated risk of fatal cerebral malaria [38]. On the other hand, higher IP-10/CXCL10 plasma levels, as well as IFN-γ and IL-10, were observed in vivax malaria patients with mild anaemia in comparison to no anaemia [12]. Availability of data and materials All data and materials are available upon request. Availability of data and materials All data and materials are available upon request. RANTES/CCL5, known as Regulated upon Activation Normal T cell Expressed and Secreted, is an inflamma- tory chemokine attractant of T cells, basophils, eosino- phils, and dendritic cells to inflammatory site [39]. RANTES/CCL5 is produced predominantly by CD8+ T cells, epithelial cells, fibroblasts, and platelets [40]. In children infected by  falciparum  malaria low mRNA and RANTES protein levels were associated with severe malaria [41]. Lower RANTES levels were also found in children with cerebral malaria and a strong positive correlation was verified between RANTES levels and platelets count [42]. In the present study, vivax malaria patients have shown significant low RANTES/CCL5 lev- els, but just weakly associated with IL-6, IL-12p40, IFN-γ or MCP-1/CCL2. The lower levels of RANTES/CCL5 could be explained by the CD8+ T cells reduction [43– 45] and thrombocytopaenia [8, 10, 11, 44–46] observed during vivax malaria. A study carried out with children infected with P. falciparum observed an association between thrombocytopaenia and lower RANTES plasma levels [47]. Author details 1 Departamento de Parasitologia, Instituto de Ciências Biológicas, Universi‑ dade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil. 2 Centro de Pesquisa em Medicina Tropical, Porto, Velho, Rondônia, Brazil. 3 Departamento de Ciência da Computação, Universidade Federal de São João del-Rei, São João del‑Rei, Minas Gerais, Brazil. 4 Departamento de Bioquímica e Biologia Molecular, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil. 5 Insti‑ tuto de Pesquisa Clínica Evandro Chagas, Fundação Oswaldo Cruz, Rio de Janeiro, Rio de Janeiro, Brazil. Funding h k g This work was financially supported by Conselho Nacional de Desenvolvi‑ mento Científico e Tecnológico/CNPq (Grant #478379/2013-7), FAPEMIG (Grant # APQ-00814-15) and Pró-Reitoria de Pesquisa of Universidade Federal de Minas Gerais. Received: 8 November 2016 Accepted: 5 January 2017 Received: 8 November 2016 Accepted: 5 January 2017 Ethics approval and consent to participate The present study was approved by the Ethics Committee of the Centro de Pesquisa em Medicina Tropical (CAAEs: 0008.0.046.000-11, 0449.0.203.000-09) and the Ethics Committee of the Universidade Federal de Minas Gerais (CAAE: 27466214.0.0000.5149). Written informed consent was obtained from each participant. Acknowledgements S S d b NSH-S was supported by a doctoral degree fellowship from CNPq/Brazil. RF and DB are supported by Brazilian National Research Council (CNPq) fellowships. e e e ces 1. WHO. World malaria report 2014. Geneva: World Health Organiza‑ tion; 2014. http://www.who.int/malaria/publications/world_malaria_ report_2014/en/. Accessed 15 Nov 2014. 2. Struik SS, Riley EM. Does malaria suffer from lack of memory? Immunol Rev. 2004;201:268–90. 3. Artavanis-Tsakonas K, Tongren JE, Riley EM. The war between the malaria parasite and the immune system: immunity, immunoregulation and immunonopathology. Clin Exp Immunol. 2003;133:145–52. 4. Finney OC, Riley EM, Walther M. Regulatory T cells in malaria—friend or foe? Trends Immunol. 2010;31:63–70. 5. Hansen DS, Schofield L. Natural regulatory T cells in malaria: host or parasite allies? PLoS Pathog. 2010;6:e1000771. 6. Riley EM. Regulating immunity to malaria. Parasite Immunol. 2006;28:35–49. Competing interests Th h d l h Competing interests The authors declare that they have no competing interests. Competing interests The authors declare that they have no competing interests. Competing interests The authors declare that they have no competing interests. p g The authors declare that they have no competing interests 2. Struik SS, Riley EM. Does malaria suffer from lack of memory? Immunol Rev. 2004;201:268–90. Conclusion Taken together, the multiple analyses performed in the present study allowed the identification of an immuno- logical signature from plasma mediators associated with Hojo‑Souza et al. Malar J (2017) 16:42 Page 10 of 10 Page 10 of 10 7. Fernandes AAM, Carvalho LJM, Zanini GM, Ventura AMRS, Souza JM, Cotias PM, et al. Similar cytokine responses and degrees of anemia in patients with Plasmodium falciparum and Plasmodium vivax infections in the Brazilian Amazon region. Clin Vaccine Imunol. 2008;15:650–8. 7. Fernandes AAM, Carvalho LJM, Zanini GM, Ventura AMRS, Souza JM, Cotias PM, et al. Similar cytokine responses and degrees of anemia in patients with Plasmodium falciparum and Plasmodium vivax infections in the Brazilian Amazon region. Clin Vaccine Imunol. 2008;15:650–8. 27. Awasthi A, Kuchroo VK. Th17 cells: from precursors to players in inflam‑ mation and infection. Int Immunol. 2009;21:489–98. 28. McGeachy MJ, Bak-Jensen KS, Chen Y, Tato CM, Blumenschein W, McCla‑ nahan T, Cua DJ. TGF-beta and IL-6 drive the production of IL-17 and IL-10 by T cells and restrain TH-17 cell-mediates pathology. Nat Immunol. 2007;8:1390–7. 8. Gonçalves RM, Salmazi KC, Santos BAN, Bastos MS, Rocha SC, Boscardin SB, et al. CD4+CD25+Foxp3+ regulatory T cells, dendritic cells, and circu‑ lating cytokines in uncomplicated malaria: do different parasite species elicit similar host responses? Infect Immun. 2010;78:4763–72. 29. Park H, Li Z, Yang XO, Chang SH, Nurjeva R, Wang YH, et al. A distinct line‑ age of CD4 T cells regulates tissue inflammation by producing interleukin 17. Nat Immunol. 2005;6:1133–41. 9. Cox-Singh J, Singh B, Daneshvar C, Planche T, Parker-Williams J, Krishna S. Anti-inflammatory cytokines predominate in acute human Plasmodium knowlesi infections. PLoS ONE. 2011;6:e20541. 9. Cox-Singh J, Singh B, Daneshvar C, Planche T, Parker-Williams J, Krishna S. Anti-inflammatory cytokines predominate in acute human Plasmodium knowlesi infections. PLoS ONE. 2011;6:e20541. 30. Betelli E, Carrier Y, Gao W, Korn T, Strom TB, Oukka M, et al. Reciprocal developmental pathways for the generation of pathogenic effector TH17 and regulatory T cells. Nature. 2006;441:235–8. 10. Gonçalves RM, Scopel KKG, Bastos MS, Ferreira MU. Cytokine balance in human malaria: does Plasmodium vivax elicit more inflammatory responses than Plasmodium falciparum? PLoS ONE. 2012;7:e44394. g y 31. Stumhofer SJ, Hunter CA. Advances in understanding the anti-inflamma‑ tory properties of IL-27. Immunol Lett. 2008;117:123–30. tory properties of IL-27. Immunol Lett. 2008;117:123–30. 32. Murugaiyan G, Mittal A, Lopez-Diego R, Maier LM, Anderson DE, Weiner HL. Conclusion 2014;5:491. 17. Zeyrek FY, Kurcer MA, Zeyrek D, Simsek Z. Parasite density and serum cytokine levels in Plasmodium vivax malaria in Turkey. Parasite Immunol. 2006;28:201–7. 40. Appay V, Rowland-Jones SL. RANTES: a versatile and controversial chemokine. Trends Immunol. 2001;22:83–7. 18. Costa AG, Antonelli LRV, Costa PAC, Pimentel JPD, Garcia NP, Tarragô AM, et al. The robust and modulated biomarker network elicited by the Plasmodium vivax infection is mainly mediated by the IL-6/IL-10 axis and is associated with the parasite load. J Immunol Res. 2014;2014:318250. 41. Ochiel DO, Awandare GA, Keller CC, Hittner JB, Kremsner PG, Weinberg JB, et al. Differential regulation of beta-chemokines in children with Plasmo- dium falciparum malaria. Infect Immun. 2005;73:4190–7. 42. John CC, Opika-Opoka R, Byarugaba J, Idro R, Boivin MJ. Low levels of RANTES are associated with mortality in children with cerebral malaria. J Infect Dis. 2006;194:837–45. 19. Medina TS, Costa SPT, Oliveira MD, Ventura AM, Souza JM, Gomes TF, et al. Increased interleukin-10 and interferon-γ levels in Plasmodium vivax malaria suggest a reciprocal regulation which is not altered by IL-10 gene promoter polymorphism. Malar J. 2011;10:264. 43. Kassa D, Petros B, Mesele T, Hailu E, Wolday D. Characterization of peripheral blood lymphocyte subsets in patients with acute Plasmodium falciparum and P. vivax malaria infections at Wonji Sugar Estate, Ethiopia. Clin Vaccine Immunol. 2006;13:376–9. 20. Jangpatarapongsa K, Chootong P, Sattabongkot J, Chotivanich K, Siri‑ chaisinthop J, Tungpradabkul S, et al. Plasmodium vivax parasites alter the balance of myeloid and plasmacytoid dendritic cells and the induction of regulatory T cells. Eur J Immunol. 2008;38:2697–705. 44. Borges QI, Fontes CJF, Damazo AS. Analysis of lymphocytes in patients with Plasmodium vivax malaria and its relation to the annexin-A1 and IL-10. Malar J. 2013;12:455. 21. Bueno LL, Morais CG, Araújo FF, Gomes JAS, Corrêa-Oliveira R, Soares IS, et al. Plasmodium vivax: induction of CD4+CD25+FoxP3+ regulatory T cells during infection are directly associated with level of circulating parasites. PLoS ONE. 2010;5:e9623. 45. Hojo-Souza NS, Pereira DB, Passos LS, Gazzinelli-Guimarães PH, Cardoso MS, Tada MS, et al. Phenotypic profiling of CD8+ T cells during Plasmo- dium vivax blood-stage infection. BMC Infect Dis. 2015;15:35. 22. Raza A, Ghanchi NK, Raheem A, Nizami S, Beg MA. Tumor necrosis factor-a, interleukin-10, intercellular and vascular adhesion molecules are possible biomarkers of disease severity in complicated Plasmodium vivax isolates from Pakistan. PLoS ONE. 2013;8:e81363. 46. Conclusion IL-27 is a key regulator of IL-10 and IL-17 production by human CD4 + T Cells. J Immunol. 2009;183:2435–43. 11. Rodrigues-da-Silva RN, Lima-Junior JC, Fonseca BPF, Antas PRZ, Baldez A, Storer FL, et al. Alterations in cytokines and haematological parameters during the acute and convalescent phases of Plasmodium falciparum and Plasmodium vivax infections. Mem Inst Oswaldo Cruz. 2014;109:154–62. 33. Ayimba E, Hegewald J, Ségbéna AY, Gantin RG, Lechner CJ, Agossou A, et al. Proinflammatory and regulatory cytokines and chemokines in infants with uncomplicated and severe Plasmodium falciparum malaria. Clin Exp Immunol. 2011;166:218–26. 12. Jain V, Singh PP, Silawat N, Patel R, Saxena A, Bharti PK, et al. A prelimi‑ nary study on pro- and anti-inflammatory cytokine profiles in Plas- modium vivax malaria patients from central zone of India. Acta Trop. 2010;113:263–8. 34. Yadav A, Saini V, Arora S. MCP-1: chemoattractant with a role beyond immunity: a review. Clin Chim Acta. 2010;411:1570–9. 13. Andrade BB, Reis-Filho A, Souza-Neto SM, Clarêncio J, Camargo LMA, Bar‑ ral A, et al. Severe Plasmodium vivax malaria exhibits marked inflamma‑ tory imbalance. Malar J. 2010;9:13. 35. Biswas P, Delfanti F, Bernasconi S, Mengozzi M, Cota M, Polentarutti N, et al. Interleukin-6 induces monocyte chemotactic protein-1 in peripheral blood mononuclear cells in the U937 cell line. Blood. 1998;91:258–65. y 14. Leoratti FMS, Trevelin SC, Cunha FQ, Rocha BC, Costa PAC, Gravina HD, et al. Neutrophil paralysis in Plasmodium vivax malaria. PLoS Negl Trop Dis. 2012;6:e1710. 36. Liu M, Guo S, Hibbert JM, Jain V, Singh N, Wilson NO, Stiles JK. IP-10/ CXCL10/IP-10 in infectious disease pathogenesis and potential therapeu‑ tic implications. Cytokine Growth Factor Rev. 2011;22:121–30. 15. Mendonça VRR, Queiroz ATL, Lopes FM, Andrade BB, Barral-Neto M. Net‑ working the host immune response in Plasmodium vivax malaria. Malar J. 2013;12:69. 37. Weaver CT, Hatton RD, Mangan PR, Harrington LE. IL-17 family cytokines and the expanding diversity of effector T cell lineages. Annu Rev Immu‑ nol. 2007;25:821–52. 16. Snounou G, Viriyakosol S, Zhu XP, Jarra W, Pinheiro L, Rosário VE, et al. High sensitivity of detection of human malaria parasites by the use of nested polymerase chain reaction. Mol Biochem Parasitol. 1993;61:315–20. 38. Armah HB, Wilson NO, Sarfo BY, Powell MD, Bond VC, Anderson W, et al. Cerebrospinal fluid and serum biomarkers of cerebral malaria mortality in Ghanaian children. Malar J. 2007;6:147. 39. Arango Duque G, Descoteaux A. Macrophage cytokines: involvement in immunity and infectious disease. Front Immunol. Hojo‑Souza et al. Malar J (2017) 16:42 Conclusion Hojo-Souza NS, Pereira DB, Mendes TA, Passos LS, Gazzinelli-Guimarães AC, Gazzinelli-Guimarães PH, et al. CD4+ T cells apoptosis in Plasmodium vivax infection is mediated by activation of both intrinsic and extrinsic pathways. Malar J. 2015;14:5. 23. Onishi RM, Gaffen SL. Interleukin-17 and its target genes: mechanisms of interleukin-17 function in disease. Immunology. 2010;129:311–21. 47. Were T, Hittner JB, Ouma C, Otieno RO, Orago AS, Ong’echa JM, et al. Suppression of RANTES in children with Plasmodium falciparum malaria. Haematologica. 2006;91:1396–9. 24. Xu S, Cao X. Interleukin-17 and its expanding biological functions. Cell Mol Immunol. 2010;7:164–74. 25. Bueno LL, Morais CG, Lacerda MV, Fujiwara RT, Braga EM. Interleukin-17 producing T helper cells are increased during natural Plasmodium vivax infection. Acta Trop. 2012;123:53–7. 26. Romagnani S. Human Th17 cells. Arthritis Res Ther. 2008;10:206.
https://openalex.org/W4327855691
https://tc.copernicus.org/preprints/tc-2022-265/tc-2022-265.pdf
English
null
Comment on tc-2022-265
null
2,023
cc-by
29,929
Modes of Antarctic tidal grounding line migration revealed by ICESat-2 laser altimetry ICESat-2 laser altimetry Bryony I. D. Freer1,2, Oliver J. Marsh1, Anna E. Hogg2, Helen Amanda Fricker3, Laurie Padman Bryony I. D. Freer1,2, Oliver J. Marsh1, Anna E. Hogg2, Helen Amanda Fricker3, Laurie Padman4 Bryony I. D. Freer1,2, Oliver J. Marsh1, Anna E. Hogg2, Helen Amanda Fricker3, eer1,2, Oliver J. Marsh1, Anna E. Hogg2, Helen Amanda Fricker3, Laurie Padman4 1British Antarctic Survey, Cambridge, CB3 0ET, UK 2School of Earth and Environment, University of Leeds, LS2 9JT, UK 5 3Scripps Polar Center, Scripps Institution of Oceanography, UC San Diego, California, USA 4Earth and Space Research, Corvallis, OR, USA 1British Antarctic Survey, Cambridge, CB3 0ET, UK 2School of Earth and Environment, University of Leeds, LS2 9JT, UK 5 3Scripps Polar Center, Scripps Institution of Oceanography, UC San Diego, California, USA 4Earth and Space Research, Corvallis, OR, USA Correspondence to: Bryony I. D. Freer (breer90@bas.ac.uk) Abstract. Short-term tidal grounding line (GL) migration in Antarctica can impact ice dynamics at the ice sheet margins and 10 obscures assessments of long-term GL advance or retreat. However, the magnitude of tidally-induced GL migration is poorly known, and the spatial pattern and modes of variability are not well characterised. Here we develop and apply a technique that uses ICESat-2 repeat-track laser altimetry to locate the inland limit of tidal ice shelf flexure for each sampled tide, enabling the magnitude and temporal variability of tidal GL migration to be resolved. We demonstrate its application at an ice plain Abstract. Short-term tidal grounding line (GL) migration in Antarctica can impact ice dynamics at the ice sheet margins and 10 obscures assessments of long-term GL advance or retreat. However, the magnitude of tidally-induced GL migration is poorly known, and the spatial pattern and modes of variability are not well characterised. Here we develop and apply a technique that uses ICESat-2 repeat-track laser altimetry to locate the inland limit of tidal ice shelf flexure for each sampled tide, enabling the magnitude and temporal variability of tidal GL migration to be resolved. We demonstrate its application at an ice plain north of Bungenstockrücken, in a region of the southern Ronne Ice Shelf subject to large ocean tides. We observe a 1,300 km2 15 area of ephemeral grounding over which the GL migrates by up to 15 km between low and high tide, and identify four distinct modes of migration: “linear”, “asymmetric”, “threshold” and “hysteresis”. The short-term movement of the GL dominates any long-term migration signal in this location, and the distribution of GL positions and modes contains information about spatial variability in the ice-bed interface. We discuss the impact of extreme tidal GL migration on ice shelf-ocean-subglacial systems in Antarctica and make recommendations for how GLs should be more precisely defined and documented in future by the 20 community. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. Modes of Antarctic tidal grounding line migration revealed by ICESat-2 laser altimetry Bryony I. D. Freer1,2, Oliver J. Marsh1, Anna E. Hogg2, Helen Amanda Fricker3, Laurie Padman 1British Antarctic Survey, Cambridge, CB3 0ET, UK 2School of Earth and Environment, University of Leeds, LS2 9JT, UK 5 3Scripps Polar Center, Scripps Institution of Oceanography, UC San Diego, California, USA 4E th d S R h C lli OR USA 1 Introduction Prior satellite observations have shown that the extent of this short-term tidal GL migration can range from a few hundred metres to several kilometres (Hogg et al., 2016; Brunt et al., 2011; Milillo et al., 2017), with the magnitude of this migration controlled by the tide amplitude, local bed topography and the thickness and 45 strength of the ice. The short-term tidal GL migration signal is superimposed on top of the long-term signal of GL migration associated with ice dynamic change, which is traditionally calculated by comparing sparsely sampled, individual measurements of GL position through time (e.g. Rignot et al., 2014). Therefore, in order to increase confidence in measurements of long-term GL migration rates, we must improve our knowledge of the spatially variable pattern of short- 2017), with the magnitude of this migration controlled by the tide amplitude, local bed topography and the thickness and 45 strength of the ice. The short-term tidal GL migration signal is superimposed on top of the long-term signal of GL migration associated with ice dynamic change, which is traditionally calculated by comparing sparsely sampled, individual measurements of GL position through time (e.g. Rignot et al., 2014). Therefore, in order to increase confidence in measurements of long-term GL migration rates, we must improve our knowledge of the spatially variable pattern of short- term tidal GL migration 50 Despite the importance of understanding tidal GL migration there is currently no Antarctic-wide assessment of its extent or variability. This is mostly because there is a lack of acquired or suitable satellite data in the historical archive with sufficient spatial and temporal resolution. We currently also have a limited understanding of the mechanisms of tidal ice shelf flexure and GL migration. Various representations of tidal flexure have been modelled using elastic and viscoelastic frameworks (Holdsworth, 1969; Vaughan, 1995; Schmeltz et al., 2002; Walker et al., 2013), some of which allow for tidal GL migration 55 (Sayag and Worster, 2013; Tsai and Gudmundsson, 2015) but results vary considerably and the choice of representation of these processes can have a large impact on results of modelling studies (e.g. Mosbeux et al., 2022). Whilst some localised in situ measurements of tidal flexure have been made to examine these processes (Smith, 1991; Vaughan, 1995), there are very few satellite observations with high enough tidal sampling to test and validate these models. 1 Introduction The location of the GL and change in its position over time is, therefore, a sensitive indicator of ice sheet stability and local environmental forcing, with sustained ice thinning causing GL retreat, and thickening causing GL advance (Joughin et al., 2010, 2012; Dutrieux et al., 2014), and it has been identified 35 as an Essential Climate Variable (Bojinski et al., 2014) Several satellite-based techniques have been used to map features in the grounding zone (GZ), the 1-10 km-wide region spanning the GL (Vaughan, 1995), with the primary goal to monitor long-term change in GL position (Sect. 2). The GL is typically located by identifying the inland limit of ice shelf flexure, but this is complicated by the effect of short-term sea Several satellite-based techniques have been used to map features in the grounding zone (GZ), the 1-10 km-wide region spanning the GL (Vaughan, 1995), with the primary goal to monitor long-term change in GL position (Sect. 2). The GL is typically located by identifying the inland limit of ice shelf flexure, but this is complicated by the effect of short-term sea level variations, primarily driven by ocean tides, which can cause GL migration on hourly to daily timescales. During a 40 rising tide, increased buoyancy causes more of the ice shelf to lift off the bed and the GL temporarily migrates inland, returning to its most seaward position at low tide (Brancato et al., 2020), with some slight time lag due to the viscoelastic effects of the ice (Reeh et al., 2003). Prior satellite observations have shown that the extent of this short-term tidal GL migration can range from a few hundred metres to several kilometres (Hogg et al., 2016; Brunt et al., 2011; Milillo et al., level variations, primarily driven by ocean tides, which can cause GL migration on hourly to daily timescales. During a 40 rising tide, increased buoyancy causes more of the ice shelf to lift off the bed and the GL temporarily migrates inland, returning to its most seaward position at low tide (Brancato et al., 2020), with some slight time lag due to the viscoelastic effects of the ice (Reeh et al., 2003). 1 Introduction Recent mass loss from the Antarctic Ice Sheet has been attributed to changes in the floating ice shelves that fringe 74% of its margins (Gudmundsson et al., 2019; Joughin et al., 2012) and buttress upstream grounded ice (Dupont and Alley, 2005). 25 Accurate representation of the ice sheet in coupled Earth system models is essential to predict its evolution and the magnitude and rate of its future contribution to sea level rise. This requires knowledge of ice sheet processes and boundary conditions, including the configuration and behaviour of ice shelves. One important parameter for ice sheet monitoring and 25 1 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. modelling is the location of the grounding line (GL), which marks the boundary between the grounded ice sheet and floating ice shelf (Thomas, 1979). As the ice detaches from the underlying bed, ice flow transitions from a regime dominated by 30 vertical shear and basal drag to that of primarily buoyancy-driven flow dominated by longitudinal stretching and lateral shear with no basal drag (Schoof, 2007). There are high rates of basal melt at the GL as ocean water comes into contact with the base of the ice shelf (Jenkins et al., 2006; Depoorter et al., 2013). The location of the GL and change in its position over time is, therefore, a sensitive indicator of ice sheet stability and local environmental forcing, with sustained ice thinning causing GL retreat, and thickening causing GL advance (Joughin et al., 2010, 2012; Dutrieux et al., 2014), and it has been identified 35 as an Essential Climate Variable (Bojinski et al., 2014) ice shelf (Thomas, 1979). As the ice detaches from the underlying bed, ice flow transitions from a regime dominated by 30 vertical shear and basal drag to that of primarily buoyancy-driven flow dominated by longitudinal stretching and lateral shear with no basal drag (Schoof, 2007). There are high rates of basal melt at the GL as ocean water comes into contact with the base of the ice shelf (Jenkins et al., 2006; Depoorter et al., 2013). 1 Introduction We show that with ICESat-2 repeat-track laser altimetry (RTLA) it is possible to monitor the time-varying GZ structure at the Bungenstockrücken ice plain in unprecedented detail, and we identify four distinct modes of tidal GL migration. We discuss the implications both for long- unprecedented detail, and we identify four distinct modes of tidal GL migration. We discuss the implications both for long- term GL monitoring and how these findings inform our process understanding of tidal flexure and GL migration mechanisms 75 in Antarctica. term GL monitoring and how these findings inform our process understanding of tidal flexure and GL migration mechanisms 75 in Antarctica. 1 Introduction Furthermore, modelled 2 projections of future mass loss from West Antarctica are very sensitive to the amount of basal melt and ice flux at the GL 60 2 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. (Arthern and Williams, 2017; Goldberg et al., 2019), yet most numerical ice sheet models typically assume a fixed or slowly moving GL determined by flotation conditions alone with zero basal melt (Milillo et al., 2017; Favier et al., 2014). This is an over-simplification in areas subject to extreme tidal variability, where short-term GL migration is likely to impact both ice dynamics through rapid variations in basal shear stress, and basal melt rate through changes in cavity geometry enhancing tidal mixing. Quantifying the extent and influence of tidal GL migration around the margin of Antarctica is valuable for 65 these processes to be more accurately parameterised in ice sheet models. In this study we present a new approach to observe tidal GL migration, that takes advantage of the high along-track resolution and repeat-track configuration of the Ice, Cloud and land Elevation (ICESat-2) satellite laser altimeter mission to improve temporal sampling of tidal ice flexure and GL migration. We apply the method to the ice plain north of the Bungenstockrücken ice rise, on the southern Ronne Ice Shelf. An ice plain is defined as an area of low surface slope close to 70 the GZ where the ice is close to flotation (Alley et al., 1989), and which can sometimes experience “ephemeral grounding” between high and low tide (Schmeltz et al., 2001; Brunt et al., 2011). We show that with ICESat-2 repeat-track laser altimetry (RTLA) it is possible to monitor the time-varying GZ structure at the Bungenstockrücken ice plain in unprecedented detail, and we identify four distinct modes of tidal GL migration. We discuss the implications both for long- Bungenstockrücken ice rise, on the southern Ronne Ice Shelf. An ice plain is defined as an area of low surface slope close to 70 the GZ where the ice is close to flotation (Alley et al., 1989), and which can sometimes experience “ephemeral grounding” between high and low tide (Schmeltz et al., 2001; Brunt et al., 2011). 2.1 Features of the grounding zone The grounding zone (GZ) is a region between the seaward limit of the ice sheet and the landward limit of the ice shelf, typically 1-10 km wide, over which the ice transitions from being in constant contact with the bed to floating in hydrostatic 80 equilibrium with the ocean. Ice in the GZ is supported by both the hydrostatic pressure from the underlying ocean and internal stresses, and undergoes tidal flexure (Vaughan, 1995). The true GL location, Point G, refers to the point at which the ice base first detaches from the bed as it flows from the ice sheet. As a subglacial feature within the GZ, Point G can only be directly observed using ground-based radar (MacGregor et al., 2011; Catania et al., 2010) or using remotely-operated 80 vehicles deployed from the shelf edge or through boreholes (Schmidt et al., 2023). However, there are a number of 85 observable surface features in the GZ that relate to the location of Point G, which can be more readily detected in situ or in satellite data and used as GL proxies (Fig. 1). Point F is the landward limit of tidal flexure, and is often located slightly inland of Point G (on the order of hundreds of metres) due the elastic properties of the ice (Padman et al., 2018; Rignot et al., 2011). Point H is the seaward limit of tidal flexure and inland limit of hydrostatic equilibrium. The break-in-slope, Point Ib, k th h d ti i f l th t d t th b t h i b l h t th GL d i 90 vehicles deployed from the shelf edge or through boreholes (Schmidt et al., 2023). However, there are a number of 85 observable surface features in the GZ that relate to the location of Point G, which can be more readily detected in situ or in satellite data and used as GL proxies (Fig. 1). Point F is the landward limit of tidal flexure, and is often located slightly inland of Point G (on the order of hundreds of metres) due the elastic properties of the ice (Padman et al., 2018; Rignot et al., 2011). Point H is the seaward limit of tidal flexure and inland limit of hydrostatic equilibrium. 2.1 Features of the grounding zone The break-in-slope, Point Ib, marks the sharp reduction in surface slope that occurs due to the abrupt change in basal shear stress across the GL, and in 90 3 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. typical GZs it is located slightly seaward of Point G (Schoof, 2011). However, where a GZ has an ice plain, Point Ib has been observed several kilometres inland of Point G (Corr et al., 2001). We show the locations of the key GZ surface proxies as they relate to Point G for an idealised ice plain in Fig. 1(a), and in Fig. 1(b) we depict how Point F can migrate by several kilometres across the tide cycle at an ice plain experiencing ephemeral grounding. 5 Figure 1: (a) Idealised cross section of an ice plain GZ, showing the location of typical satellite-derived GZ proxies: Point Ib, the first break-in-slope; Point F, the inland limit of tidal flexure (represented here as approximately equal to Point G, the true GL); Point H, the inshore limit of hydrostatic equilibrium. (b) Idealised cross section of an ice plain GZ experiencing tidal GL migration, showing the difference in position of the ice shelf and migration of Point F between high tide (Fmax) and low tide (Fmin), across 24 hours of a simplified ~12 h semidiurnal tide cycle. 0 95 Figure 1: (a) Idealised cross section of an ice plain GZ, showing the location of typical satellite-derived GZ proxies: Point Ib, the first break-in-slope; Point F, the inland limit of tidal flexure (represented here as approximately equal to Point G, the true GL); Point H, the inshore limit of hydrostatic equilibrium. (b) Idealised cross section of an ice plain GZ experiencing tidal GL migration, showing the difference in position of the ice shelf and migration of Point F between high tide (Fmax) and low tide (Fmin), across 24 hours of a simplifie ~12 h semidiurnal tide cycle. 100 95 95 Figure 1: (a) Idealised cross section of an ice plain GZ, showing the location of typical satellite-derived GZ proxies: Point Ib, the first break-in-slope; Point F, the inland limit of tidal flexure (represented here as approximately equal to Point G, the true GL); Point H, the inshore limit of hydrostatic equilibrium. ~12 h semidiurnal tide cycle. 2.1 Features of the grounding zone (b) Idealised cross section of an ice plain GZ experiencing tidal GL migration, showing the difference in position of the ice shelf and migration of Point F between high tide (Fmax) and low tide (Fmin), across 24 hours of a simplified ~12 h semidiurnal tide cycle. 00 100 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. 2.2 Methods for detecting the grounding zone GZ surface proxies can be measured in situ using instruments such as tiltmeters and GNSS (Stephenson et al., 1979; Smith, 1991; Vaughan, 1995), or using satellite techniques to obtain more widespread measurements (Rignot, 1996; Friedl et al., 105 2020). Static satellite methods identify the break-in-slope, Point Ib, either from shadows in a single-epoch optical satellite image (Scambos et al., 2007; Bindschadler et al., 2011) or single-epoch elevation profiles from radar and laser satellite altimetry (Hogg et al., 2018; Brunt et al., 2010a; Li et al., 2022a). Dynamic satellite methods use data acquired at two or more distinct phases of the tidal cycle to locate the limits of tidal flexure, Points F and H. CryoSat-2 radar altimetry has been 105 used to map Point F by applying a pseudo-crossover method to detect tidal flexure (Dawson and Bamber, 2017, 2020). This 110 provides good spatial coverage by assimilating large data volumes over a multi-year record, but cannot be used to detect short-term GL migration between specific tides. Differential Interferometric Synthetic Aperture Radar (DInSAR) is one of the most commonly used dynamic satellite methods, and can produce quasi-continuous maps of Points F and H from double- differenced interferograms produced from three or four SAR images acquired at different times in the tidal cycle (Rignot, used to map Point F by applying a pseudo-crossover method to detect tidal flexure (Dawson and Bamber, 2017, 2020). This 110 provides good spatial coverage by assimilating large data volumes over a multi-year record, but cannot be used to detect short-term GL migration between specific tides. Differential Interferometric Synthetic Aperture Radar (DInSAR) is one of the most commonly used dynamic satellite methods, and can produce quasi-continuous maps of Points F and H from double- differenced interferograms produced from three or four SAR images acquired at different times in the tidal cycle (Rignot, 1996). However, the temporal sampling and spatial coverage of DInSAR in Antarctica is limited, in part due to its reliance 115 on a short repeat-time between acquisitions to retain interferometric coherence. 2.2 Methods for detecting the grounding zone Recent studies using data from the COSMO- SkyMed (CSK) constellation, with a short repeat-period of 1, 3, 4 or 8 days and up to 3 m spatial resolution, have improved DInSAR sampling of tidal GL migration in specific locations (Milillo et al., 2017; Minchew et al., 2017), but are still complicated by the fact that interferograms are produced from oblique imagery from at least three different tide times. 1996). However, the temporal sampling and spatial coverage of DInSAR in Antarctica is limited, in part due to its reliance 115 on a short repeat-time between acquisitions to retain interferometric coherence. Recent studies using data from the COSMO- SkyMed (CSK) constellation, with a short repeat-period of 1, 3, 4 or 8 days and up to 3 m spatial resolution, have improved DInSAR sampling of tidal GL migration in specific locations (Milillo et al., 2017; Minchew et al., 2017), but are still complicated by the fact that interferograms are produced from oblique imagery from at least three different tide times. Moreover, while the relatively short-repeat period of CSK enables interferometric coherence to be maintained on faster 120 floating ice streams, the spatial coverage of coherent SAR image pairs is still limited, constraining the period where continent-wide studies can be performed. Moreover, while the relatively short-repeat period of CSK enables interferometric coherence to be maintained on faster 120 floating ice streams, the spatial coverage of coherent SAR image pairs is still limited, constraining the period where continent-wide studies can be performed. An alternative dynamic satellite technique is repeat-track satellite laser altimetry (RTLA), which was first introduced for GZ detection by Fricker and Padman (2006). For this method, comparison of repeat tracks of ice shelf elevation profiles sampled at different tidal states identifies elevation anomalies that relate to Points F and H along discrete ground tracks. RTLA was 125 pioneered using data from the Geoscience Laser Altimeter System instrument on board the Ice, Cloud and Land Elevation Satellite (ICESat) that was in orbit from 2003 to 2009. However, ICESat only had a single ground track that only repeated to about ±100 m, which led to unrecoverable topographic biases across GZs (Fricker et al., 2009). In contrast, the Advanced Topographic Laser Altimeter System (ATLAS) that launched on board ICESat-2 in 2018 has a six-beam design with more at different tidal states identifies elevation anomalies that relate to Points F and H along discrete ground tracks. 3.1 Datasets CATS2008 is an update of the model described by (Padman et al., 2002) that is widely considered the best performing tidal no significant differences between ‘weak’ and ‘strong’ beams in the ATL06 product, therefore we included all beams in our 150 analysis. We obtained coincident tide amplitudes at the most seaward point of each ICESat-2 ground track per cycle from the circum- Antarctic inverse tide model CATS2008 (Howard et al., 2019) using the pyTMD software (Sutterley et al., 2019). CATS2008 is an update of the model described by (Padman et al., 2002) that is widely considered the best performing tidal We obtained coincident tide amplitudes at the most seaward point of each ICESat-2 ground track per cycle from the circum- Antarctic inverse tide model CATS2008 (Howard et al., 2019) using the pyTMD software (Sutterley et al., 2019). model in the region, in part due to its assimilation of ICESat altimetry data over large ice shelves (King et al., 2011). We 155 selected three locations 35 – 40 km seaward of Bungenstockrücken (Fig. 2a) to extract a time series of tide heights over a single year (centred on 01/01/2020), which are used to calculate annual tide distributions across the width of the region. model in the region, in part due to its assimilation of ICESat altimetry data over large ice shelves (King et al., 2011). We 155 selected three locations 35 – 40 km seaward of Bungenstockrücken (Fig. 2a) to extract a time series of tide heights over a single year (centred on 01/01/2020), which are used to calculate annual tide distributions across the width of the region. 2.2 Methods for detecting the grounding zone RTLA was 125 pioneered using data from the Geoscience Laser Altimeter System instrument on board the Ice, Cloud and Land Elevation Satellite (ICESat) that was in orbit from 2003 to 2009. However, ICESat only had a single ground track that only repeated to about ±100 m, which led to unrecoverable topographic biases across GZs (Fricker et al., 2009). In contrast, the Advanced Topographic Laser Altimeter System (ATLAS) that launched on board ICESat-2 in 2018 has a six-beam design with more accurate pointing, which reduces across-track deviation from the reference ground track (RGT), providing better spatial 130 sampling of the GZ. Only two repeat measurements are required to locate Point F using RTLA, providing an advantage over DInSAR which requires at least three repeats, and allows us to attribute the migration of Point F to individual tidal states. Li et al. (2022c) has used these data to locate a single Point F, H and Ib (Fig. 1a) along most ICESat-2 ground tracks around 5 5 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. Antarctica. Here, we extend the Li et al. (2022c) record at Bungenstockrücken to locate multiple Point F positions along each ICESat-2 ground track as it migrates over the tide cycle (Fig. 1b), providing novel observations of tidal GZ behaviour. 135 3.1 Datasets The ATLAS instrument onboard ICESat-2 is the first spaceborne photon-counting laser altimeter (Markus et al., 2017). It samples 11 m diameter footprints (Magruder et al., 2021) estimating surface heights every 0.7 m along its 1387 RGTs. ATLAS transmits a single beam of 532 nm (green) laser light pulsing at 10 kHz along each RGT, which is split into six 140 beams organised into three pairs, each separated by 3.3 km. The beams in each pair, one ‘weak’ and one ‘strong’, are separated by 90 m across-track, and each beam follows its own ground track (GT1L, GT1R, GT2R…to GT3L), although the mapping of the weak/strong beams to each ground track per pair switches roughly twice per year as ICESat-2 switches orientation to maximise solar illumination of solar panels. The system operates in a 91-day exact repeat orbit, providing repeat surface height measurements along each ground track about four times per year (Neumann et al., 2019). We obtained 145 data from version 5 of the Land Ice Height (ATL06) product along all ground tracks crossing the Bungenstockrücken GL (Fig. 2b). This included data from repeat cycles 3 to 15 (April 2019 to May 2022; Smith et al., 2021), with cycles 1 and 2 omitted due to instrument off-pointing at the start of the mission. ATL06 provides surface height measurements every 20 m along-track, calculated by averaging the L2 geolocated photon data over 40 m segments (Smith et al., 2019). We observed repeat surface height measurements along each ground track about four times per year (Neumann et al., 2019). We obtained 145 data from version 5 of the Land Ice Height (ATL06) product along all ground tracks crossing the Bungenstockrücken GL (Fig. 2b). This included data from repeat cycles 3 to 15 (April 2019 to May 2022; Smith et al., 2021), with cycles 1 and 2 omitted due to instrument off-pointing at the start of the mission. ATL06 provides surface height measurements every 20 m along-track, calculated by averaging the L2 geolocated photon data over 40 m segments (Smith et al., 2019). We observed no significant differences between ‘weak’ and ‘strong’ beams in the ATL06 product, therefore we included all beams in our 150 analysis. We obtained coincident tide amplitudes at the most seaward point of each ICESat-2 ground track per cycle from the circum- Antarctic inverse tide model CATS2008 (Howard et al., 2019) using the pyTMD software (Sutterley et al., 2019). 3.2 Repeat-track laser altimetry RTLA is a dynamic method for GL estimation that uses repeat measurements made at different phases of the tidal cycle to estimate the temporal change in the surface elevation of the ice shelf caused by ocean tides to identify the limits of tidal 160 flexure (Points F and H) as proxies for GL location (Fricker and Padman, 2006). This method typically involves three steps: 6 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. (i) Data preparation; (ii) Define a reference elevation profile; (iii) Locate the limits of tidal flexure by calculating elevation anomalies relative to the reference profile. In this study we present updates to steps (ii) and (iii) that allow us to improve the temporal sampling of short-term tidal GL migration. We describe each of these steps below. (i) Data preparation; (ii) Define a reference elevation profile; (iii) Locate the limits of tidal flexure by calculating elevation anomalies relative to the reference profile. In this study we present updates to steps (ii) and (iii) that allow us to improve the temporal sampling of short-term tidal GL migration. We describe each of these steps below. 165 3.2.1 Data preparation We obtained ATL06 surface height data along all ICESat-2 ground tracks in the study area (Smith et al., 2021; Scheick and others, 2019). We removed poor quality measurements caused by cloud cover, blowing snow or background photon 170 clustering using the ATL06_quality_summary parameter. We rejected all values either without a valid associated across- track-slope measurement and/or where the minimum segment difference exceeds 1, which is calculated as the minimum absolute difference between each segment’s endpoints and those of its two neighbours (Arendt et al., 2020). Following the method described in Li et al. (2020), we applied a cross-track slope correction to minimise the effects of rough terrain (Smith We obtained ATL06 surface height data along all ICESat-2 ground tracks in the study area (Smith et al., 2021; Scheick and others, 2019). We removed poor quality measurements caused by cloud cover, blowing snow or background photon 170 clustering using the ATL06_quality_summary parameter. We rejected all values either without a valid associated across- track-slope measurement and/or where the minimum segment difference exceeds 1, which is calculated as the minimum absolute difference between each segment’s endpoints and those of its two neighbours (Arendt et al., 2020). Following the method described in Li et al. (2020), we applied a cross-track slope correction to minimise the effects of rough terrain (Smith et al., 2019), and for each ground track omitted repeat cycles with fewer than 50% valid measurements along-track, as they 175 are deemed unreliable for GZ calculation. We then performed RTLA analysis along each ground track using the remaining high quality repeat cycles, as described in Sects. 3.2.2 and 3.2.3. 7 8 Figure 2: Method used to define three types of reference profile for elevation anomaly calculations along ICESat-2 ground tracks, as illustrated for RGT 559 GT3L at the Bungenstockrücken ice plain. (a) Location of Bungenstockrücken on the Ronne Ice Shelf. Red diamonds show the locations used to calculate annual tide distributions. (b) ICESat-2 ground tracks crossing the MEaSUREs and ASAI GLs in the study area (Rignot et al., 2016; Bindschadler and Choi, 2011). (c-e) Repeat surface elevation profiles and anomalies of RGT 559 GT3L, each using a different reference profile: (c) mean profile of cycles 4, 6, 8, 9, 11, 12, 13; (d) neutral profile of cycle 13; (e) lowest-sampled tide profile of cycle 9. 3.2.1 Data preparation The reference profile at zero-elevation anomaly is shown as a black dashed line, and the latitude the derived Point F positions for each cycle along-track as coloured circles along the x-axis. Dashed coloured lines show the modelled t height at the time of each cycle at the most seaward point along-track (in (e) these are differenced from the tide of cycle 9). (f) Histogra of CATS2008 modelled tide heights experienced over a single year, centred on 01/01/2020 (Howard et al., 2019), with vertical coloure dashed lines showing the tide height at each repeat cycle. (g) Tidal time series showing tide height, velocity and phase during the 24 ho period before and after the ICESat-2 overpass for each repeat cycle at RGT 559 GT3L. 8 Figure 2: Method used to define three types of reference profile for elevation anomaly calculations along ICESat-2 ground tracks, as illustrated for RGT 559 GT3L at the Bungenstockrücken ice plain. (a) Location of Bungenstockrücken on the Ronne Ice Shelf. Red 180 diamonds show the locations used to calculate annual tide distributions. (b) ICESat-2 ground tracks crossing the MEaSUREs and ASAID GLs in the study area (Rignot et al., 2016; Bindschadler and Choi, 2011). (c-e) Repeat surface elevation profiles and anomalies of RGT 559 GT3L, each using a different reference profile: (c) mean profile of cycles 4, 6, 8, 9, 11, 12, 13; (d) neutral profile of cycle 13; (e) lowest-sampled tide profile of cycle 9. The reference profile at zero-elevation anomaly is shown as a black dashed line, and the latitude of the derived Point F positions for each cycle along-track as coloured circles along the x-axis. Dashed coloured lines show the modelled tide 185 height at the time of each cycle at the most seaward point along-track (in (e) these are differenced from the tide of cycle 9). (f) Histogram of CATS2008 modelled tide heights experienced over a single year, centred on 01/01/2020 (Howard et al., 2019), with vertical coloured dashed lines showing the tide height at each repeat cycle. (g) Tidal time series showing tide height, velocity and phase during the 24 hour period before and after the ICESat-2 overpass for each repeat cycle at RGT 559 GT3L. 8 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. 3.2.2 Defining the reference elevation profile 190 This particularly affects areas experiencing large tidal GL migration, as can be seen clearly in Fig. 2(c), where the anomalies for cycles 6 and 13 fall below zero between -80.96° S and -80.88° S. This might incorrectly suggest that tidal flexure extends this far inland, when in fact it reflects the skew of the mean reference profile caused by GL migration further inland at higher tides (cycles 4 and 12). Given that we locate Point F along- track where the anomaly gradient for each cycle first deviates from 0, this would lead us to incorrectly locate just 210 two Point Fs along this ground track: one for cycle 4 at ~-80.99° S and one for all other cycles together at ~-81.96° S (Fig. 2c). As a result, we see a systematic inland bias in the derived GL position when using the mean reference profile, leading to a large underestimation of the total extent of tidal GL migration along this ground track. (i) Mean profile (Fig. 2c): The mean elevation profile is calculated as the mean of the interpolated profiles per repeat cycle along each ground track. However, this reference profile does not represent the true “mean” ice shelf surface corresponding to zero (“neutral”) tide. Instead, it gives us the along-track mean of the ice shelf surfaces at the tide phases sampled by ICESat-2. This can introduce an observation bias; for example, the mean reference elevation profile would be biased high if most sampled repeats of a single RGT are acquired at positive tides, or during one or 205 two extreme high tides. This particularly affects areas experiencing large tidal GL migration, as can be seen clearly in Fig. 2(c), where the anomalies for cycles 6 and 13 fall below zero between -80.96° S and -80.88° S. This might incorrectly suggest that tidal flexure extends this far inland, when in fact it reflects the skew of the mean reference profile caused by GL migration further inland at higher tides (cycles 4 and 12). Given that we locate Point F along- track where the anomaly gradient for each cycle first deviates from 0, this would lead us to incorrectly locate just 210 two Point Fs along this ground track: one for cycle 4 at ~-80.99° S and one for all other cycles together at ~-81.96° S (Fig. 2c). 3.2.2 Defining the reference elevation profile 190 The reference profile is important for identifying the limits of tidal flexure, as it is used as a baseline from which to calculate elevation anomalies for each ICESat-2 repeat sampled at different tidal states. The mean elevation profile has been used as the reference profile in all previous RTLA studies (Fricker and Padman, 2006; Fricker et al., 2009; Brunt et al., 2010b, 2011; Li et al., 2020, 2022a, b), but here we propose two alternative approaches: using a reference profile sampled at a neutral tide or at the lowest-sampled tide. These are illustrated for RGT 559 GT3L in Figure 2. Before selecting one of these approaches for 195 our study, we first evaluated the results from each and considered the situations for which each would be appropriate. To test each approach, we fitted a cubic B-spline approximation to the valid repeat surface elevation profiles per ground track, using a smoothing parameter of 0.7. The use of an interpolated profile rather than the raw data points is more robust, providing a method for handling small along-track data gaps in individual profiles, which can be consistently applied across all repeat tracks. 200 at the lowest-sampled tide. These are illustrated for RGT 559 GT3L in Figure 2. Before selecting one of these approaches for 195 our study, we first evaluated the results from each and considered the situations for which each would be appropriate. To test each approach, we fitted a cubic B-spline approximation to the valid repeat surface elevation profiles per ground track, using a smoothing parameter of 0.7. The use of an interpolated profile rather than the raw data points is more robust, providing a method for handling small along-track data gaps in individual profiles, which can be consistently applied across all repeat tracks. 200 (i) Mean profile (Fig. 2c): The mean elevation profile is calculated as the mean of the interpolated profiles per repeat cycle along each ground track. However, this reference profile does not represent the true “mean” ice shelf surface corresponding to zero (“neutral”) tide. Instead, it gives us the along-track mean of the ice shelf surfaces at the tide phases sampled by ICESat-2. This can introduce an observation bias; for example, the mean reference elevation profile would be biased high if most sampled repeats of a single RGT are acquired at positive tides, or during one or 205 two extreme high tides. 3.2.2 Defining the reference elevation profile 190 As a result, we see a systematic inland bias in the derived GL position when using the mean reference profile, leading to a large underestimation of the total extent of tidal GL migration along this ground track. (i) (ii) Neutral tide profile (Fig. 2d): To more closely represent the true “mean” ice shelf surface, we can use the elevation profile from a single cycle sampled at a neutral tide as the reference profile. Ideally, this would use the profile 215 sampled close to a 0 m tide during the neap phase, such as cycle 13 on Bungenstockrücken RGT 559 GT3L (Fig. 2g). Using the neutral tide profile removes the effect of the skewed mean in the inner regions of the GZ and improves our interpretation of flexure between tides, as we are now directly comparing the surface profiles between two individual tidal states for each cycle. However, it still raises the same issue that for all tides below “neutral”, we would locate Point F too far inland, where anomalies first deviate from 0 (e.g. cycles 9 and 11 in Fig. 2d). We 220 (ii) Neutral tide profile (Fig. 2d): To more closely represent the true “mean” ice shelf surface, we can use the elevation profile from a single cycle sampled at a neutral tide as the reference profile. Ideally, this would use the profile 215 sampled close to a 0 m tide during the neap phase, such as cycle 13 on Bungenstockrücken RGT 559 GT3L (Fig. 2g). Using the neutral tide profile removes the effect of the skewed mean in the inner regions of the GZ and improves our interpretation of flexure between tides, as we are now directly comparing the surface profiles between two individual tidal states for each cycle. However, it still raises the same issue that for all tides below “neutral”, we would locate Point F too far inland, where anomalies first deviate from 0 (e.g. cycles 9 and 11 in Fig. 2d). We 220 (ii) 9 9 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. are also unable locate Point F for cycles sampled close to the neutral tide as there is no deviation in elevation from the reference profile (cycle 6 and 13 in Fig. 2d). Again, this would mean we would underestimate the total extent of tidal GL migration, by overlooking migration that occurs at tides below neutral. 3.2.2 Defining the reference elevation profile 190 Moreover, many ICESat-2 RGTs have not sampled a nearly “neutral” tide, so it would not be possible to apply this approach consistently across multiple ground tracks. are also unable locate Point F for cycles sampled close to the neutral tide as there is no deviation in elevation from the reference profile (cycle 6 and 13 in Fig. 2d). Again, this would mean we would underestimate the total extent of tidal GL migration, by overlooking migration that occurs at tides below neutral. Moreover, many ICESat-2 RGTs have not sampled a nearly “neutral” tide, so it would not be possible to apply this approach consistently across multiple ground tracks. 225 (iii) (iii) Lowest-sampled tide profile (Fig. 2e): Alternatively, we propose that the elevation profile of the repeat cycle sampled at the lowest coincident tide can be used as the reference profile. This also overcomes the issue of the mean reference profile being skewed by inland flexure at higher tides, but with the additional advantage that it can be applied consistently across RGTs, enabling automation. Most importantly, it allows us to locate Point F for cycles sampled at lower tides that are missed when using both the mean and neutral reference profiles. For RGT 559 230 GT3L we identify five individual Point Fs using the lowest-sampled reference profile (Fig. 2e) as opposed to two with the mean (Fig. 2c) or four using the neutral (Fig. 2d). By locating the most seaward Point F (from cycle 11 in Fig. 2e) it gives us a more realistic baseline for the low tide GL position against which to quantify the extent of migration at each higher sampled tide. Note that we cannot locate Point F for the lowest-sampled tide itself (i.e. cycle 9 in Fig. 2e) as there is no lower profile to compare to. 235 The choice of reference profile (mean / neutral / lowest-sampled tide) to calculate elevation anomalies ultimately depends on the scientific question being posed and the tidal sampling by the ICESat-2 RGTs. We must also consider the impact of signals in the repeat elevation profiles that are not associated with tidal displacement, which can be especially prominent where there are large time gaps between repeat cycles. 3.2.3 Locating the limits of flexure in regions of ephemeral grounding 250 3.2.3 Locating the limits of flexure in regions of ephemeral grounding 250 Most previous GZ studies using RTLA located a single Point F per track (Fricker and Padman, 2006; Fricker et al., 2009; Brunt et al., 2010b; Li et al., 2020, 2022a, b). However, with our method using the lowest-sampled tide as the reference profile, it is possible to locate multiple Point F positions along each ICESat-2 ground track, each sampled at a different tidal state. To achieve this, we calculated the elevation anomalies per repeat cycle against the reference profile for each ground Most previous GZ studies using RTLA located a single Point F per track (Fricker and Padman, 2006; Fricker et al., 2009; Brunt et al., 2010b; Li et al., 2020, 2022a, b). However, with our method using the lowest-sampled tide as the reference profile, it is possible to locate multiple Point F positions along each ICESat-2 ground track, each sampled at a different tidal state. To achieve this, we calculated the elevation anomalies per repeat cycle against the reference profile for each ground track, as is shown for RGT 559 GT3L in Fig. 3. The region where the elevation anomaly is close to zero is interpreted as 255 fully grounded ice, and where it is close to the modelled tide prediction with zero gradient as freely floating ice in hydrostatic equilibrium. We compared this with modelled tide predictions from CATS2008 to distinguish the tidal signal from other causes of elevation change, including surface mass balance and ice dynamics. We then located Point F for each repeat cycle using an automated technique adapted from Li et al. (2022). First, we applied a low-pass Butterworth filter to track, as is shown for RGT 559 GT3L in Fig. 3. The region where the elevation anomaly is close to zero is interpreted as 255 fully grounded ice, and where it is close to the modelled tide prediction with zero gradient as freely floating ice in hydrostatic equilibrium. We compared this with modelled tide predictions from CATS2008 to distinguish the tidal signal from other causes of elevation change, including surface mass balance and ice dynamics. We then located Point F for each repeat cycle using an automated technique adapted from Li et al. (2022). 3.2.2 Defining the reference elevation profile 190 For example, in regions of fast flowing ice, elevation gradients will advect through the GZ between repeat passes, or alternatively surface mass balance or long-term ice dynamic thickness 240 change could alter the repeat track elevation profiles and obscure the tidal signal. These issues could be addressed by using shorter-sub-sections of the whole time series to define the choice of reference profile. The choice of reference profile (mean / neutral / lowest-sampled tide) to calculate elevation anomalies ultimately depends on the scientific question being posed and the tidal sampling by the ICESat-2 RGTs. We must also consider the impact of signals in the repeat elevation profiles that are not associated with tidal displacement, which can be especially prominent where there are large time gaps between repeat cycles. For example, in regions of fast flowing ice, elevation gradients will The choice of reference profile (mean / neutral / lowest-sampled tide) to calculate elevation anomalies ultimately depends on the scientific question being posed and the tidal sampling by the ICESat-2 RGTs. We must also consider the impact of signals in the repeat elevation profiles that are not associated with tidal displacement, which can be especially prominent where there are large time gaps between repeat cycles. For example, in regions of fast flowing ice, elevation gradients will advect through the GZ between repeat passes, or alternatively surface mass balance or long-term ice dynamic thickness 240 change could alter the repeat track elevation profiles and obscure the tidal signal. These issues could be addressed by using shorter-sub-sections of the whole time series to define the choice of reference profile. 10 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. 3.2.3 Locating the limits of flexure in regions of ephemeral grounding 250 First, we applied a low-pass Butterworth filter to the elevation anomalies per cycle, using a normalised cut-off frequency of 0.016 and an order 5, to remove the high- 260 frequency noise whilst retaining the shape of each anomaly curve. From this, we located Point F where the anomaly gradient first deviates from zero and the 2nd derivative of the anomaly peaks (Fig. 3b-g). To ensure the correct estimation of Point F, we restricted the choice of peak to where anomaly values <0.25 m and then manually adjusted any choice of peak where it was still visibly incorrect. For each Point F we then extracted the latitude and longitude as well as the coincident tide height and phase at the time of ICESat-2 overpass from CATS2008, which allows us to map the migration of Point F across the tide 265 cycle (Fig. 3h). Finally, to investigate modes of tidal GL migration along each ground track we plotted the distance between Point F and the location of the furthest seaward Point F against the coincident tide height for each repeat cycle, distinguishing between those sampled during rising vs falling tides (Fig. 3i). and phase at the time of ICESat-2 overpass from CATS2008, which allows us to map the migration of Point F across the tide 265 cycle (Fig. 3h). Finally, to investigate modes of tidal GL migration along each ground track we plotted the distance between Point F and the location of the furthest seaward Point F against the coincident tide height for each repeat cycle, distinguishing between those sampled during rising vs falling tides (Fig. 3i). 11 11 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. hod used to locate Point F per repeat cycle from ICESat-2 elevation anomalies, as illustrated for RGT 559 GT3L. (a) malies for repeat cycles 4, 6, 8, 11, 12 and 13, each calculated against the lowest-sampled tide reference profile of cycle 9. ed lines indicate the CATS2008 modelled tide height per cycle, differenced from the cycle 9 tide (Howard et al., 2019). (b- elevation anomalies for each repeat cycle, with the low-pass-filtered anomalies in black and the 2nd derivative of the filtered reen. 3.2.3 Locating the limits of flexure in regions of ephemeral grounding 250 Vertical dashed lines shows the along-track latitude where Point F has been located from the peak(s) of the second Map showing the derived position of Point F per repeat cycle along RGT 559 GT3L. (h) Along-track migration distance of cle for RGT 559 GT3L as a function of coincident tide height, overlain on the histogram of tide heights experienced over a ntred on 01/01/2020). Figure 3: Method used to locate Point F per repeat cycle from ICESat-2 elevation anomalies, as illustrated for RGT 559 GT3L. (a) 270 Elevation anomalies for repeat cycles 4, 6, 8, 11, 12 and 13, each calculated against the lowest-sampled tide reference profile of cycle 9. Dashed coloured lines indicate the CATS2008 modelled tide height per cycle, differenced from the cycle 9 tide (Howard et al., 2019). (b- g) Individual elevation anomalies for each repeat cycle, with the low-pass-filtered anomalies in black and the 2nd derivative of the filtered anomalies in green. Vertical dashed lines shows the along-track latitude where Point F has been located from the peak(s) of the second derivative. (g) Map showing the derived position of Point F per repeat cycle along RGT 559 GT3L. (h) Along-track migration distance of 275 Point F per cycle for RGT 559 GT3L as a function of coincident tide height, overlain on the histogram of tide heights experienced over a single year (centred on 01/01/2020). 12 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. 3.3 Study region 13 We tested our updated RTLA methodology along all ICESat-2 ground tracks crossing a 220km section of GL at the ice plain north of Bungenstockrücken, located on the southern Ronne Ice Shelf in between the Institute and Möller ice streams (Fig. 280 2). This is an ideal location to study tidal GL migration for four reasons: (1) Large tidal range with ephemeral grounding: The southern Ronne experiences predominantly semidiurnal tides with a 7-8 m total tidal range, one of the largest in Antarctica (Padman et al., 2018). Ephemeral grounding has already been identified over this ice plain in earlier ICESat studies (Brunt et al., 2011); (2) ICESat-2 sampling: The high latitude location, GZ orientation and low cloud cover leads to a high density of 285 unobstructed ICESat-2 tracks crossing normal to the GL (67 RGTs, each with six separate ground tracks); (3) Low ice velocity: Ice flows across the GL at ~5 m a-1 (Rignot et al., 2017), resulting in little advection of surface features between repeat profiles over the three year study period, which could otherwise affect the success of RTLA; (4) Evidence for past change: There is evidence that this region has undergone significant GL retreat in the past, and as the upstream ice sheet is currently grounded over a >1.5 km deep basin with a retrograde slope it is potentially 290 susceptible to future ice loss (Ross et al., 2012; Siegert et al., 2013). In general, ice plains are a good location to monitor early signs of change as they are highly sensitive to small perturbations in ice dynamics, sea level, surface mass balance, basal melt and sediment deposition (Brunt et al., 2011; Horgan et al., 2013b). We use five existing GL datasets at Bungenstockrücken to compare to our results, as summarised in Table 1. Table 1: Existing grounding line datasets used in this study to compare to our ICESat-2 RTLA results. 295 Grounding Line Dataset Continuous Line / Discrete Points Satellite(s) Method Acquisition Date Reference MEaSUREs Point F Line RADARSAT-2 DInSAR 2009 Rignot et al. (2016) ICESat Point F Points ICESat RTLA 2003-2009 Brunt et al., (2010a) ICESat Point “F2” (The maximum inland flexure limit at high tide along eight individual ICESat ground tracks at Bungenstockrücken) Points ICESat RTLA 2003-2009 Brunt et al. (2011) ICESat-2 Point F Points ICESat-2 RTLA March 2019 – September 2020 Li et al. 3.3 Study region (2022c) ASAID Point Ib (Antarctic Surface Accumulation and Ice Discharge Project) Line Landsat-7 ICESat Photoclinometry and laser altimetry Landsat-7: 1999- 2003 ICESat: 2003-2009 Bindschadler and Choi (2011) ICESat-2 Point Ib Points ICESat-2 Laser altimetry March 2019 – September 2020 Li et al. (2022c) We tested our updated RTLA methodology along all ICESat-2 ground tracks crossing a 220km section of GL at the ice plain north of Bungenstockrücken, located on the southern Ronne Ice Shelf in between the Institute and Möller ice streams (Fig. 280 2). This is an ideal location to study tidal GL migration for four reasons: We tested our updated RTLA methodology along all ICESat-2 ground tracks crossing a 220km section of GL at the ice plain north of Bungenstockrücken, located on the southern Ronne Ice Shelf in between the Institute and Möller ice streams (Fig. 80 2). This is an ideal location to study tidal GL migration for four reasons: (1) Large tidal range with ephemeral grounding: The southern Ronne experiences predominantly semidiurnal tides with a 7-8 m total tidal range, one of the largest in Antarctica (Padman et al., 2018). Ephemeral grounding has already been identified over this ice plain in earlier ICESat studies (Brunt et al., 2011); (2) ICESat-2 sampling: The high latitude location, GZ orientation and low cloud cover leads to a high density of 285 unobstructed ICESat-2 tracks crossing normal to the GL (67 RGTs, each with six separate ground tracks); (3) Low ice velocity: Ice flows across the GL at ~5 m a-1 (Rignot et al., 2017), resulting in little advection of surface features between repeat profiles over the three year study period, which could otherwise affect the success of RTLA; (4) Evidence for past change: There is evidence that this region has undergone significant GL retreat in the past, and as the upstream ice sheet is currently grounded over a >1.5 km deep basin with a retrograde slope it is potentially 290 susceptible to future ice loss (Ross et al., 2012; Siegert et al., 2013). In general, ice plains are a good location to monitor early signs of change as they are highly sensitive to small perturbations in ice dynamics, sea level, surface mass balance, basal melt and sediment deposition (Brunt et al., 2011; Horgan et al., 2013b). 3.3 Study region We use five existing GL datasets at Bungenstockrücken to compare to our results, as summarised We use five existing GL datasets at Bungenstockrücken to compare to our results, as summarised in Table 1. We use five existing GL datasets at Bungenstockrücken to compare to our results, as summarised in Table 1. Table 1: Existing grounding line datasets used in this study to compare to our ICESat-2 RTLA results. 95 Grounding Line Dataset Continuous Line / Discrete Points Satellite(s) Method Acquisition Date Reference MEaSUREs Point F Line RADARSAT-2 DInSAR 2009 Rignot et al. (2016) ICESat Point F Points ICESat RTLA 2003-2009 Brunt et al., (2010a) ICESat Point “F2” (The maximum inland flexure limit at high tide along eight individual ICESat ground tracks at Bungenstockrücken) Points ICESat RTLA 2003-2009 Brunt et al. (2011) ICESat-2 Point F Points ICESat-2 RTLA March 2019 – September 2020 Li et al. (2022c) ASAID Point Ib (Antarctic Surface Accumulation and Ice Discharge Project) Line Landsat-7 ICESat Photoclinometry and laser altimetry Landsat-7: 1999- 2003 ICESat: 2003-2009 Bindschadler and Choi (2011) ICESat-2 Point Ib Points ICESat-2 Laser altimetry March 2019 – September 2020 Li et al. (2022c) able 1: Existing grounding line datasets used in this study to compare to our ICESat-2 RTLA results. 13 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. 4.1 Extent of tidal grounding line migration at Bungenstockrücken 4b,c), where we observe Point F migrating progressively further inland as tides increase, totalling 10.4 km of GL migration across the ~4.5 m sampled tide range (90.3% of total tide range). At the highest sampled tide of +2.08 m (cycle 4), Point F reaches as far inland as Point Ib, but since 7% of tides experienced in the region exceed +2.08 m, it is possible that flexure extends even further inland at these higher tides. In Area B, we observe two main In Area A and across the central section we observe a fairly consistent migration of Point F with the tide. This is exemplified 305 by the pattern of RGT 559 GT3L (Fig. 4b,c), where we observe Point F migrating progressively further inland as tides increase, totalling 10.4 km of GL migration across the ~4.5 m sampled tide range (90.3% of total tide range). At the highest sampled tide of +2.08 m (cycle 4), Point F reaches as far inland as Point Ib, but since 7% of tides experienced in the region exceed +2.08 m, it is possible that flexure extends even further inland at these higher tides. In Area B, we observe two main In Area A and across the central section we observe a fairly consistent migration of Point F with the tide. This is exemplified 305 by the pattern of RGT 559 GT3L (Fig. 4b,c), where we observe Point F migrating progressively further inland as tides increase, totalling 10.4 km of GL migration across the ~4.5 m sampled tide range (90.3% of total tide range). At the highest sampled tide of +2.08 m (cycle 4), Point F reaches as far inland as Point Ib, but since 7% of tides experienced in the region exceed +2.08 m, it is possible that flexure extends even further inland at these higher tides. In Area B, we observe two main clusters of Point F, possibly indicating the presence of two stable GL locations (one landward and one seaward) depending 310 on the tide. This pattern can be seen in the surface and anomaly profiles of RGT 574 GT3L (Fig. 4d,e), which show a ~11.5 km separation between the seaward GL position near -81.45° S and the landward GL position near -81.55° S. 4.1 Extent of tidal grounding line migration at Bungenstockrücken Our results reveal the spatial pattern of tidal GL migration at Bungenstockrücken across a ~1,300 km2 zone of ephemeral grounding (Fig. 4). Across the central part of the study area (between Areas A and B), we observe the inland limit of tide p p g g p grounding (Fig. 4). Across the central part of the study area (between Areas A and B), we observe the inland limit of tide flexure (Point F) to migrate by 5 to 15 km across the GZ, although the total migration distance may be greater in regions 300 where the full tide range has not yet been sampled by ICESat-2. In this central region, Point F measured at the highest tides consistently reaches several kilometres further inland than the MEaSUREs GL, and as far inland as the ICESat-2 break-in- slope. The spatial pattern of short-term tidal GL migration is not consistent across the region, with the most migration observed in Areas A and B (Fig. 4a). flexure (Point F) to migrate by 5 to 15 km across the GZ, although the total migration distance may be greater in regions 300 where the full tide range has not yet been sampled by ICESat-2. In this central region, Point F measured at the highest tides consistently reaches several kilometres further inland than the MEaSUREs GL, and as far inland as the ICESat-2 break-in- slope. The spatial pattern of short-term tidal GL migration is not consistent across the region, with the most migration observed in Areas A and B (Fig. 4a). flexure (Point F) to migrate by 5 to 15 km across the GZ, although the total migration distance may be greater in regions 300 where the full tide range has not yet been sampled by ICESat-2. In this central region, Point F measured at the highest tides consistently reaches several kilometres further inland than the MEaSUREs GL, and as far inland as the ICESat-2 break-in- slope. The spatial pattern of short-term tidal GL migration is not consistent across the region, with the most migration observed in Areas A and B (Fig. 4a). 300 In Area A and across the central section we observe a fairly consistent migration of Point F with the tide. This is exemplified 305 by the pattern of RGT 559 GT3L (Fig. 4.1 Extent of tidal grounding line migration at Bungenstockrücken Similarly to RGT 559 GT3L, the landward GL position at the highest sampled tide for RGT 574 GT3L coincides with the ICESat-2 Point Ib, just inland of the large surface undulation visible in the elevation profile (Fig. 4d). We note that in parts of Area B the clusters of Point F, possibly indicating the presence of two stable GL locations (one landward and one seaward) depending 310 on the tide. This pattern can be seen in the surface and anomaly profiles of RGT 574 GT3L (Fig. 4d,e), which show a ~11.5 km separation between the seaward GL position near -81.45° S and the landward GL position near -81.55° S. Similarly to RGT 559 GT3L, the landward GL position at the highest sampled tide for RGT 574 GT3L coincides with the ICESat-2 Point Ib, just inland of the large surface undulation visible in the elevation profile (Fig. 4d). We note that in parts of Area B the landward GL position extends up to 5 km further inland than the ASAID Point Ib, up to 3 km beyond the ICESat-2 Point Ib, 315 and is positioned around the prominent surface undulations visible in the ice surface topography. landward GL position extends up to 5 km further inland than the ASAID Point Ib, up to 3 km beyond the ICESat-2 Point Ib, 315 and is positioned around the prominent surface undulations visible in the ice surface topography. In the areas west of Area A and east of Area B, Point F is consistently located just inland (<2 km) of the ASAID and ICESat- 2 break-in-slope with little tidal migration. This is consistent with the surface features of a typical GZ (i.e. non-ice plain) (Schoof, 2011), indicating that these regions are beyond the edges of the ice plain. In the areas west of Area A and east of Area B, Point F is consistently located just inland (<2 km) of the ASAID and ICESat- 2 break-in-slope with little tidal migration. This is consistent with the surface features of a typical GZ (i.e. non-ice plain) (Schoof, 2011), indicating that these regions are beyond the edges of the ice plain. 14 20 Figure 4: Tidal GL migration at Bungenstockrücken, measured by ICESat-2 RTLA. 4.1 Extent of tidal grounding line migration at Bungenstockrücken The two areas with the largest observed GL migration are highlighted A A d d h l i f G 9 G 3 3 G 3 d 4 G 3 h (b ) h l i fil d 325 y p g y g ( ) MEaSUREs GL (Rignot et al., 2016), ASAID break-in-slope GL (Bindschadler and Choi, 2011), and the most recent ICESat-2 derived break-in-slope (Point Ib) along each ground track (Li et al., 2022c). The two areas with the largest observed GL migration are highlighted as Areas A and B, and the locations for RGT 559 GT3L, 537 GT3L and 574 GT3L are shown. (b-c) The repeat elevation profiles and 325 anomalies of RGT 559 GT3L, with repeat cycles coloured by tide (as % of maximum tide height) and labelled in (c). The location of ICESat-2 Point Ib is marked with a vertical dashed line (Li et al., 2022b). (d-e) The equivalent repeat elevation profiles and anomalies for RGT 574 GT3L. 4.1 Extent of tidal grounding line migration at Bungenstockrücken (a) The location of Point F at every sampled repeat cycle per ICESat-2 ground track is coloured by % of maximum tide height, overlain on the REMA 8m DEM (Howat et al., 2018), MEaSUREs GL (Rignot et al., 2016), ASAID break-in-slope GL (Bindschadler and Choi, 2011), and the most recent ICESat-2 derived break-in-slope (Point Ib) along each ground track (Li et al., 2022c). The two areas with the largest observed GL migration are highlighted as Areas A and B, and the locations for RGT 559 GT3L, 537 GT3L and 574 GT3L are shown. (b-c) The repeat elevation profiles and 25 anomalies of RGT 559 GT3L, with repeat cycles coloured by tide (as % of maximum tide height) and labelled in (c). The location of ICESat-2 Point Ib is marked with a vertical dashed line (Li et al., 2022b). (d-e) The equivalent repeat elevation profiles and anomalies for RGT 574 GT3L. 320 Figure 4: Tidal GL migration at Bungenstockrücken, measured by ICESat-2 RTLA. (a) The location of Point F at every sampled repeat cycle per ICESat-2 ground track is coloured by % of maximum tide height, overlain on the REMA 8m DEM (Howat et al., 2018), MEaSUREs GL (Rignot et al., 2016), ASAID break-in-slope GL (Bindschadler and Choi, 2011), and the most recent ICESat-2 derived break-in-slope (Point Ib) along each ground track (Li et al., 2022c). The two areas with the largest observed GL migration are highlighted as Areas A and B, and the locations for RGT 559 GT3L, 537 GT3L and 574 GT3L are shown. (b-c) The repeat elevation profiles and 325 anomalies of RGT 559 GT3L, with repeat cycles coloured by tide (as % of maximum tide height) and labelled in (c). The location of Figure 4: Tidal GL migration at Bungenstockrücken, measured by ICESat-2 RTLA. (a) The location of Point F at every sampled repeat cycle per ICESat-2 ground track is coloured by % of maximum tide height, overlain on the REMA 8m DEM (Howat et al., 2018), MEaSUREs GL (Rignot et al., 2016), ASAID break-in-slope GL (Bindschadler and Choi, 2011), and the most recent ICESat-2 derived break-in-slope (Point Ib) along each ground track (Li et al., 2022c). 4.2 Long-term grounding zone change at Bungenstockrücken 15 To assess if there has been any long-term GZ change in our study region, we compared our results to previous GL datasets 330 (Fig. 5). By locating multiple Point Fs along each ground track between high and low tide, we have been able to assess almost the entire width of the zone of ephemeral grounding at Bungenstockrücken for the first time. It is difficult to make a direct comparison to other GL products (Fig. 5a,b) which only locate a single Point F position (Rignot et al., 2016; Brunt et al., 2010a; Li et al., 2022c). Nonetheless, we see that across the central section of Bungenstockrücken, the ICESat-2 derived 15 To assess if there has been any long-term GZ change in our study region, we compared our results to previous GL datasets 330 (Fig. 5). By locating multiple Point Fs along each ground track between high and low tide, we have been able to assess almost the entire width of the zone of ephemeral grounding at Bungenstockrücken for the first time. It is difficult to make a direct comparison to other GL products (Fig. 5a,b) which only locate a single Point F position (Rignot et al., 2016; Brunt et al., 2010a; Li et al., 2022c). Nonetheless, we see that across the central section of Bungenstockrücken, the ICESat-2 derived 15 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. Point Fs for the highest ~60% of tides are located consistently inland of the MEaSUREs GL, by ~2-10 km (Fig. 5a). The 335 ICESat derived Point Fs are mostly located towards the middle of the band of our ICESat-2 derived Point Fs (Fig. 5a), although the maximum inland Point “F2s” (Brunt et al., 2011) match our ICESat-2 derived Point Fs at high tide more closely. There has been little long-term change in the position of Point Ib between ICESat/ASAID and ICESat-2, apart from a few locations in Areas A and B where we observe several kilometres of landward migration (Fig. 5c). 340 Figure 5: (a) Comparison of the ICESat-2 derived Point Fs at Bungenstockrücken to: (i) the ICESat-derived Point F (Brunt et al., 2010a), (ii) the ICESat-derived maximum inland Point “F2” (Brunt et al., 2011), and (iii) the MEaSUREs GL (Rignot et al., 2016), derived from 2009 RADARSAT-2 data. 4.2 Long-term grounding zone change at Bungenstockrücken (b) Co pa so o t e C Sat de ved o t s pe epeat cyc e o t s study, to t e C Sat de ved o t F dataset from Li et al. (2022c) that locates a single Point F per ground track. (c) Comparison between the Point Ib from ASAID (Bindschadler and Choi (2011); derived from Landsat-7 and ICESat), ICESat (Brunt et al., 2010a) and ICESat-2 (Li et al., 2022c). 345 F dataset from Li et al. (2022c) that locates a single Point F per ground track. (c) Comparison bet (Bindschadler and Choi (2011); derived from Landsat-7 and ICESat), ICESat (Brunt et al., 2010a 345 4.2 Long-term grounding zone change at Bungenstockrücken (b) Comparison of the ICESat-2 derived Point Fs per repeat cycle from this study, to the ICESat-2 derived Point F dataset from Li et al. (2022c) that locates a single Point F per ground track. (c) Comparison between the Point Ib from ASAID (Bindschadler and Choi (2011); derived from Landsat-7 and ICESat), ICESat (Brunt et al., 2010a) and ICESat-2 (Li et al., 2022c). 345 4 3 M d f tid l di li i ti 340 Figure 5: (a) Comparison of the ICESat-2 derived Point Fs at Bungenstockrücken to: (i) the ICESat-derived Point F (Brunt et al., 2010a), (ii) the ICESat-derived maximum inland Point “F2” (Brunt et al., 2011), and (iii) the MEaSUREs GL (Rignot et al., 2016), derived from 2009 RADARSAT-2 data. (b) Comparison of the ICESat-2 derived Point Fs per repeat cycle from this study, to the ICESat-2 derived Point F dataset from Li et al. (2022c) that locates a single Point F per ground track. (c) Comparison between the Point Ib from ASAID (Bindschadler and Choi (2011); derived from Landsat-7 and ICESat), ICESat (Brunt et al., 2010a) and ICESat-2 (Li et al., 2022c). 345 Figure 5: (a) Comparison of the ICESat-2 derived Point Fs at Bungenstockrücken to: (i) the ICESat-derived Point F (Brunt et al., 2010a), (ii) the ICESat-derived maximum inland Point “F2” (Brunt et al., 2011), and (iii) the MEaSUREs GL (Rignot et al., 2016), derived from 2009 RADARSAT-2 data. (b) Comparison of the ICESat-2 derived Point Fs per repeat cycle from this study, to the ICESat-2 derived Point F dataset from Li et al (2022c) that locates a single Point F per ground track (c) Comparison between the Point Ib from ASAID Figure 5: (a) Comparison of the ICESat-2 derived Point Fs at Bungenstockrücken to: (i) the ICESat-derived Point F (Brunt et al., 2010a), (ii) the ICESat-derived maximum inland Point “F2” (Brunt et al., 2011), and (iii) the MEaSUREs GL (Rignot et al., 2016), derived from 2009 RADARSAT-2 data. (b) Comparison of the ICESat-2 derived Point Fs per repeat cycle from this study, to the ICESat-2 derived Point F dataset from Li et al. (2022c) that locates a single Point F per ground track. (c) Comparison between the Point Ib from ASAID (Bindschadler and Choi (2011); derived from Landsat-7 and ICESat), ICESat (Brunt et al., 2010a) and ICESat-2 (Li et al., 2022c). 345 009 S data. 4.3 Modes of tidal grounding line migration We investigated the relationship between modelled tide height, tide phase and GL migration distance for the ICESat-2 ground tracks at Bungenstockrücken, and identified four distinct modes of tidal GL migration (Fig. 6). We manually classified these modes based on visual assessment of the most dominant behaviour. To increase confidence in the classification, we included only tracks where > 2 m of the tide range was sampled and with a total tidal GL migration 350 distance > 1 km. This removes tracks where small uncertainties in GL position associated with tide phase, basal properties and long-term surface change are sufficient to obscure the detail in the patterns of GL migration required for this type of classification. We investigated the relationship between modelled tide height, tide phase and GL migration distance for the ICESat-2 ground tracks at Bungenstockrücken, and identified four distinct modes of tidal GL migration (Fig. 6). We manually classified these modes based on visual assessment of the most dominant behaviour. To increase confidence in the We investigated the relationship between modelled tide height, tide phase and GL migration distance for the ICESat-2 ground tracks at Bungenstockrücken, and identified four distinct modes of tidal GL migration (Fig. 6). We manually classified these modes based on visual assessment of the most dominant behaviour. To increase confidence in the classification, we included only tracks where > 2 m of the tide range was sampled and with a total tidal GL migration 350 classification, we included only tracks where > 2 m of the tide range was sampled and with a total tidal GL migration 350 distance > 1 km. This removes tracks where small uncertainties in GL position associated with tide phase, basal properties and long-term surface change are sufficient to obscure the detail in the patterns of GL migration required for this type of classification. 350 16 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. Figure 6: Four modes of tidal grounding line migration observed along ICESat-2 ground tracks at Bungenstockrücken. 4.3 Modes of tidal grounding line migration 6a-c): In this mode we observe a linear relationship between tide height and GL migration distance. 365 Within the sampled tide range, the GL migrates by 2.2 km with every metre of tidal change (a-b), and by 1.7 km/m in (c). Considering a simplified semidiurnal spring tide regime where the tide rises from minimum (-3 m) to maximum (+3 m) within 6 hours, this could translate to an average GL retreat rate of about 2 km/h. We observe little difference between GL positions sampled at rising vs falling tides. However, we note that, for RGT 781 GT1R (b) there is only one F point measured during falling tide, and for all ground tracks we cannot determine whether the linear response 370 extends out to the most extreme tides. The linear mode of tidal GL migration is seen on ground tracks across the study area, but particularly clustered east of Area A (Fig. 6m). (1) Linear (Fig. 6a-c): In this mode we observe a linear relationship between tide height and GL migration distance. 365 Within the sampled tide range, the GL migrates by 2.2 km with every metre of tidal change (a-b), and by 1.7 km/m in (c). Considering a simplified semidiurnal spring tide regime where the tide rises from minimum (-3 m) to maximum (+3 m) within 6 hours, this could translate to an average GL retreat rate of about 2 km/h. We observe little difference between GL positions sampled at rising vs falling tides. However, we note that, for RGT 781 GT1R (b) there is only one F point measured during falling tide, and for all ground tracks we cannot determine whether the linear response 370 extends out to the most extreme tides. The linear mode of tidal GL migration is seen on ground tracks across the study area, but particularly clustered east of Area A (Fig. 6m). 370 (2) Asymmetric (Fig. 6d-f): In this mode there is an asymmetric relationship between tide height and GL migration, with a large increase in the GL migration rate observed at higher tides. For tides below about +0.5 m in (d) and below 0 m in (e) and (f), Point Fs are clustered close together, indicating that there is little tidal GL migration within the lower 5 tidal range. 4.3 Modes of tidal grounding line migration However, as the tide increases beyond this point the rates of GL migration increases sharply to linear rates of +2.5 km/m in (d), +1.8 km/m in (e) and +4.1 km/m in (f). Again, outside of the sampled tide range the magnitudes and modes of GL migration are unknown. Ground tracks with asymmetric tidal GL migration mode are mainly clustered in Area A and just west of Area B (Fig. 6m). (3) Threshold (Fig. 6g-i): In this mode there is little GL migration up to a certain tide threshold, beyond which the GL 380 migrates significantly with just a small increase in tide. The tide threshold in (g) is at ~+0.7 m, and at ~+0.4 m in (h), and in both examples a <0.3 m rise of the tide across the threshold causes the GL to migrate inland by over 10km. At peak spring tide (across the full 6m tide range) this could feasibly occur within 18 minutes, translating to a possible maximum GL migration rate exceeding 30 km/h. Either side of the threshold in (g) and (i), further tide change does not cause much more GL migration. This supports the interpretation that in some locations two fairly stable GL 385 positions (landward and seaward) can exist, as observed in Area B (Fig. 4). Considering the histogram of tide distributions, we can infer from this that the GL is at the landward position ~26% of the time in (g), ~38% in (h) and ~22% in (i). The majority of ground tracks with threshold tidal GL migration mode are located in Area B (Fig. 6m). (3) (4) Hysteresis (Fig. 6j-l): In this mode there is a hysteresis between tidal forcing and GL migration, related to the phase of the sampled tide at each measurement of Point F. This means we observe a different GL migration behaviour 0 between rising and falling tides. For example, along RGT 34 GT1R (j) we note a landward and seaward cluster of Point F positions separated by about 15 km, similar to the threshold pattern seen in (g-i). However, instead of a single tidal threshold that defines if the GL is in the landward or seaward position, in (j) we observe two different thresholds for the rising and falling tide phases. 4.3 Modes of tidal grounding line migration Three examples 355 are shown per mode, which are classified from top to bottom as: (a-c) Linear, with a linear relationship between tide height and GL migration distance; (d-f) Asymmetric, with higher tides causing an increased rate of GL migration; (g-i) Threshold, with a sharp tide threshold above which there is significant GL migration; (j-l) Hysteresis, with a difference in the impact of tidal variability on GL migration during the rising vs falling tide phase. In each example we show the along-track migration distance between each Point F and the Point F measured at the lowest-sampled tide as a function of coincident tide height from CATS2008 (Howard et al., 2019). Note the 360 variable y axis scale between ground tracks. The orientation of the triangle indicates whether the repeat cycle was sampled during a rising or falling tide phase. Histograms show the distribution of tide heights experienced across a single year, centred on 01/01/2020. (m) Map of Bungenstockrücken showing ICESat-2 ground tracks coloured by migration mode (excluding tracks with <1 km tidal migration or <2 m tide range sampled). Figure 6: Four modes of tidal grounding line migration observed along ICESat-2 ground tracks at Bungenstockrücken. Three examples 355 are shown per mode, which are classified from top to bottom as: (a-c) Linear, with a linear relationship between tide height and GL migration distance; (d-f) Asymmetric, with higher tides causing an increased rate of GL migration; (g-i) Threshold, with a sharp tide threshold above which there is significant GL migration; (j-l) Hysteresis, with a difference in the impact of tidal variability on GL migration during the rising vs falling tide phase. In each example we show the along-track migration distance between each Point F and the Point F measured at the lowest-sampled tide as a function of coincident tide height from CATS2008 (Howard et al., 2019). Note the 360 variable y axis scale between ground tracks. The orientation of the triangle indicates whether the repeat cycle was sampled during a rising or falling tide phase. Histograms show the distribution of tide heights experienced across a single year, centred on 01/01/2020. (m) Map of Bungenstockrücken showing ICESat-2 ground tracks coloured by migration mode (excluding tracks with <1 km tidal migration or <2 m tide range sampled). 17 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. (1) Linear (Fig. 4.3 Modes of tidal grounding line migration The extra bump further inland in the anomalies for cycle 12 (between -81.5° S and -81.57° S; Fig. 7g) indicates that the ice shelf surface between the seaward and landward GLs has not yet fully recovered from its high tide position. We discuss the 410 potential causes and implications of this in Section 5. surface between the seaward and landward GLs has not yet fully recovered from its high tide position. We discuss the 410 potential causes and implications of this in Section 5. We note that the four tidal GL migration modes described here are not necessarily discrete categories. This is highlighted in Fig. 6(h), which shows that along RGT 1016 GT3R we observe both linear and threshold behaviours in different parts of the tidal cycle. Hysteresis may also be superimposed on top of the other modes, as is arguably visible in Fig. 6(a), but will We note that the four tidal GL migration modes described here are not necessarily discrete categories. This is highlighted in Fig. 6(h), which shows that along RGT 1016 GT3R we observe both linear and threshold behaviours in different parts of the tidal cycle. Hysteresis may also be superimposed on top of the other modes, as is arguably visible in Fig. 6(a), but will become much clearer to identify as more repeats are acquired by ICESat-2. Uncertainty is also introduced where there are 415 gaps in the sampling of certain tidal ranges, for example above +0.5 m in Fig. 6(h, k), and there is subjectivity introduced by the manual classification of modes. This could explain the overlap between tracks with different modes in Fig. 6(m), and particularly those with hysteresis. Our ability to understand and identify these different tidal behaviours will greatly improve as ICESat-2 collects an increasing volume of repeat measurements over the GZ, which should sample more of the tide range. become much clearer to identify as more repeats are acquired by ICESat-2. Uncertainty is also introduced where there are 415 gaps in the sampling of certain tidal ranges, for example above +0.5 m in Fig. 6(h, k), and there is subjectivity introduced by the manual classification of modes. This could explain the overlap between tracks with different modes in Fig. 6(m), and particularly those with hysteresis. 4.3 Modes of tidal grounding line migration From this we infer that at the lowest tides the GL is located in the seaward position, but as the tide rises and crosses some threshold between +0.5 m and +1.2 m there is enough buoyant uplift 5 (4) 18 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. force to unground the ice. This then causes ocean water to intrude into the GZ cavity and, due to the likely very flat bed, allows the GL to migrate by up to 15 km to its landward position. As the tide rises beyond +1.2 m, the GL does not migrate any further within the sampled tide range. However, as the tide turns and falls below +0.5 m there is not an immediate re-advance of the GL to its seaward position. Instead, the GL is observed to remain at its landward position until the tide has fallen beneath some secondary threshold at about -0.8 m. A similar, if less pronounced, hysteresis mode is observed in (k) and (l). Hysteresis is observed on ground tracks across the study area, but particularly in Areas A and B and close to ground tracks with asymmetric and threshold modes (Fig. 6m). 400 RGT 537 GT3L reveal more detail about the hysteresis mechanism that is observed in this region (Fig. 7d-g). Along this 405 ground track, cycles 9 and 12 are sampled at a very similar absolute tide height (~0.25 m higher at cycle 9 vs 12), but their elevation anomaly profiles look very different (Fig. 7f-g). This can be explained by comparing the coincident tide phases, which shows that cycle 9 was sampled during a rising tide, whereas cycle 12 was sampled during a falling tide. The extra bump further inland in the anomalies for cycle 12 (between -81.5° S and -81.57° S; Fig. 7g) indicates that the ice shelf RGT 537 GT3L reveal more detail about the hysteresis mechanism that is observed in this region (Fig. 7d-g). Along this 405 ground track, cycles 9 and 12 are sampled at a very similar absolute tide height (~0.25 m higher at cycle 9 vs 12), but their elevation anomaly profiles look very different (Fig. 7f-g). This can be explained by comparing the coincident tide phases, which shows that cycle 9 was sampled during a rising tide, whereas cycle 12 was sampled during a falling tide. 4.3 Modes of tidal grounding line migration Inset panels show the time-series of tide heights for the 24 hours before and after the time of ICESat-2 overpass at each cycle, showing the coincident tide phase and velocity. Figure 7: (a) The spatial pattern of tidal GL migration observed in Area B, Bungenstockrücken. Point F identified for every repeat cycle of each ICESat-2 ground track is coloured by % of maximum tide height. (b-c) Schematics depicting the flow of water in between the seaward and landward GL positions inferred from ICESat-2 RTLA results in Area B, during the rising and falling tide phase. (d-e) The repeat elevation profiles and anomalies of RGT 537 GT3L, calculated using the lowest-sampled tide reference profile from cycle 4. Repeat cycles are coloured by tide (as % of maximum tide height), and the cycle numbers are labelled in (e) alongside the CATS2008 modelled 425 tide heights, differenced from the tide at cycle 4. (f-g) The individual elevation anomalies for cycles 9 and 12 against the lowest-sampled tide profile of cycle 4. Inset panels show the time-series of tide heights for the 24 hours before and after the time of ICESat-2 overpass at each cycle, showing the coincident tide phase and velocity. 4.3 Modes of tidal grounding line migration Our ability to understand and identify these different tidal behaviours will greatly improve as ICESat-2 collects an increasing volume of repeat measurements over the GZ, which should sample more of the tide range. 19 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. 420 Figure 7: (a) The spatial pattern of tidal GL migration observed in Area B, Bungenstockrücken. Point F identified for every repeat cycle of each ICESat-2 ground track is coloured by % of maximum tide height. (b-c) Schematics depicting the flow of water in between the seaward and landward GL positions inferred from ICESat-2 RTLA results in Area B, during the rising and falling tide phase. (d-e) The repeat elevation profiles and anomalies of RGT 537 GT3L, calculated using the lowest-sampled tide reference profile from cycle 4. Repeat cycles are coloured by tide (as % of maximum tide height), and the cycle numbers are labelled in (e) alongside the CATS2008 modelled 425 tide heights, differenced from the tide at cycle 4. (f-g) The individual elevation anomalies for cycles 9 and 12 against the lowest-sampled tide profile of cycle 4. Inset panels show the time-series of tide heights for the 24 hours before and after the time of ICESat-2 overpass at each cycle, showing the coincident tide phase and velocity. 420 Figure 7: (a) The spatial pattern of tidal GL migration observed in Area B, Bungenstockrücken. Point F identified for every repeat cycle of each ICESat-2 ground track is coloured by % of maximum tide height. (b-c) Schematics depicting the flow of water in between the seaward and landward GL positions inferred from ICESat-2 RTLA results in Area B, during the rising and falling tide phase. (d-e) The repeat elevation profiles and anomalies of RGT 537 GT3L, calculated using the lowest-sampled tide reference profile from cycle 4. Repeat cycles are coloured by tide (as % of maximum tide height), and the cycle numbers are labelled in (e) alongside the CATS2008 modelled 425 tide heights, differenced from the tide at cycle 4. (f-g) The individual elevation anomalies for cycles 9 and 12 against the lowest-sampled tide profile of cycle 4. 5.1 Advantages of our ICESat-2 RTLA method for monitoring tidal grounding line behaviour The number of valid measurements per ground track (of a maximum possible 13) largely depends on the number of repeats obscured by 455 cloud cover. As more cycles of ICESat-2 data are acquired in the future, the temporal sampling of tidal GZ behaviour will continue to increase. valid measurements per ground track (of a maximum possible 13) largely depends on the number of repeats obscured by 455 cloud cover. As more cycles of ICESat-2 data are acquired in the future, the temporal sampling of tidal GZ behaviour will continue to increase. 5 Discussion The improved repeat-track sampling capabilities of ICESat-2 together with our updated RTLA methodology offers several 430 advantages over other satellite-based techniques for monitoring tidal GZ behaviour. Using this approach, our observation of widespread short-term tidal GL migration at Bungenstockrücken has implications for how long-term change is assessed and The improved repeat-track sampling capabilities of ICESat-2 together with our updated RTLA methodology offers several 430 advantages over other satellite-based techniques for monitoring tidal GZ behaviour. Using this approach, our observation of widespread short-term tidal GL migration at Bungenstockrücken has implications for how long-term change is assessed and 20 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. interpreted, and for how the GL is represented in models. Furthermore, monitoring the dynamic movement of the GL provides an independent satellite method to illuminate bed characteristics and processes that can influence stability in the GZ region. We expand on each of these implications below. interpreted, and for how the GL is represented in models. Furthermore, monitoring the dynamic movement of the GL provides an independent satellite method to illuminate bed characteristics and processes that can influence stability in the GZ region. We expand on each of these implications below. 435 5.1 Advantages of our ICESat-2 RTLA method for monitoring tidal grounding line behaviour ICESat-2 coverage also extends to 88° S, which is further south than most 445 spaceborne SAR, meaning there is no available coincident DInSAR coverage at Bungenstockrücken during the ICESat-2 period. Second, the use of our updated RTLA technique improves the temporal sampling of tidal GL behaviour. Most previous RTLA h i h b h ICES d ICES 2 f fil d i i l P i F k (F i k altimetry (Dawson and Bamber, 2017). ICESat-2 coverage also extends to 88° S, which is further south than most 445 spaceborne SAR, meaning there is no available coincident DInSAR coverage at Bungenstockrücken during the ICESat-2 period. altimetry (Dawson and Bamber, 2017). ICESat-2 coverage also extends to 88° S, which is further south than most 445 spaceborne SAR, meaning there is no available coincident DInSAR coverage at Bungenstockrücken during the ICESat-2 period. Second, the use of our updated RTLA technique improves the temporal sampling of tidal GL behaviour. Most previous RTLA approaches with both ICESat and ICESat-2 use a mean reference profile to derive a single Point F per track (Fricker and Padman, 2006; Fricker et al., 2009; Brunt et al., 2010b; Li et al., 2020, 2022a, b). Our method, by using the lowest- 450 sampled tide as the reference profile, allows us to locate multiple positions of Point F along each ground track as it migrates with the tide. This produces GL measurements at fine temporal resolution, which enables a closer investigation of tidal GZ processes that occur over hourly to daily timescales. Within the time period of this study, we locate up to 11 Point Fs per ground track, each sampled at a different tide, totalling 2402 measurements across the 402 ground tracks. The number of and Padman, 2006; Fricker et al., 2009; Brunt et al., 2010b; Li et al., 2020, 2022a, b). Our method, by using the lowest- 450 sampled tide as the reference profile, allows us to locate multiple positions of Point F along each ground track as it migrates with the tide. This produces GL measurements at fine temporal resolution, which enables a closer investigation of tidal GZ processes that occur over hourly to daily timescales. Within the time period of this study, we locate up to 11 Point Fs per ground track, each sampled at a different tide, totalling 2402 measurements across the 402 ground tracks. 5.1 Advantages of our ICESat-2 RTLA method for monitoring tidal grounding line behaviour First, the use of ICESat-2 itself offers several advantages that improve the spatial sampling of tidal GL behaviour compared to other satellites. Its track spacing and six-beam pattern greatly increases the density of measurements compared to ICESat, with 402 separate ground tracks crossing the Bungenstockrücken GZ (using the six beams from 67 ICESat-2 RGTs), to other satellites. Its track spacing and six-beam pattern greatly increases the density of measurements compared to ICESat, with 402 separate ground tracks crossing the Bungenstockrücken GZ (using the six beams from 67 ICESat-2 RGTs), compared to 23 ICESat tracks. There is also an improvement in along-track sampling, with ATL06 surface height 440 measurements calculated every 20m along-track (averaged from 40m overlapping segments), compared to a spacing of 172m with ICESat (Schutz et al., 2005). This allows us to better resolve finer-scale details of the shape and configuration of the GL and observe how these may be affected by the tide. Furthermore, its repeat-track configuration and sensitivity to small amplitude tidal variations allow us to attribute GL migration to specific tides, which is not possible with CryoSat-2 radar compared to 23 ICESat tracks. There is also an improvement in along-track sampling, with ATL06 surface height 440 measurements calculated every 20m along-track (averaged from 40m overlapping segments), compared to a spacing of 172m with ICESat (Schutz et al., 2005). This allows us to better resolve finer-scale details of the shape and configuration of the GL and observe how these may be affected by the tide. Furthermore, its repeat-track configuration and sensitivity to small amplitude tidal variations allow us to attribute GL migration to specific tides, which is not possible with CryoSat-2 radar compared to 23 ICESat tracks. There is also an improvement in along-track sampling, with ATL06 surface height 440 measurements calculated every 20m along-track (averaged from 40m overlapping segments), compared to a spacing of 172m with ICESat (Schutz et al., 2005). This allows us to better resolve finer-scale details of the shape and configuration of the GL and observe how these may be affected by the tide. Furthermore, its repeat-track configuration and sensitivity to small amplitude tidal variations allow us to attribute GL migration to specific tides, which is not possible with CryoSat-2 radar altimetry (Dawson and Bamber, 2017). 5.2 Implications for grounding line monitoring Therefore, when assessing long-term 22 be uc s a e at ost ta ct c G s (depe d g o t de a ge a d bed p ope t es, c ud g s ope a d ct o coefficient), even at an order of magnitude less may still be sufficient to obscure early signs of long-term retreat in response to ice shelf thinning (Milillo et al., 2017; Li et al., 2022b) and to impact ice dynamics. Therefore, when assessing long-term GL migration rates from sparse observations of GL location through time, we must consider the tidal state associated with 480 each measurement epoch. Ideally, long-term GL location estimates should be made at the same tidal state or tide difference; however, given the scarcity of GL measurements in most locations, this has historically not been feasible. In lieu of this, our updated ICESat-2 RTLA methodology could be applied around the ice sheet margin to provide a constraint on the expected tidal range and mechanisms of GL movement. This will enable better evaluation of the impact of tides on previously-derived estimates of GL position, and ultimately improve the confidence with which we can assess long-term GL change. 485 The identification of different modes of tidal GL migration using ICESat-2 RTLA (Fig. 6) could be used to identify regions that are particularly sensitive to ice thickness changes, similar to Schmeltz et al. (2001) who showed that areas of ephemeral grounding can reveal subtle changes in ice thickness. In regions with a “threshold” or “hysteresis” mode of tidal GL migration, an observed decrease in the tide threshold that defines whether the GL is located in the landward or seaward position could indicate a retreat of the GL and signal dynamic ice thinning. Conversely, if the tide threshold rises it could 490 signal GL advance and ice thickening. We suggest that Area B at Bungenstockrücken (Fig. 7) would be an ideal place to monitor this, with its wide zone of ephemeral grounding (up to 15 km) and numerous ICESat-2 tracks exhibiting either threshold or hysteresis GL migration modes. Monitoring ephemeral grounding in this way could enable us to discriminate between inferred thickness changes due to changing firn-air content, and true ice thickness change (Moholdt et al., 2014). GL migration rates from sparse observations of GL location through time, we must consider the tidal state associated with 480 each measurement epoch. 5.2 Implications for grounding line monitoring Our observation of up to 15 km of tidal GL migration across the Bungenstockrücken ice plain is t Our observation of up to 15 km of tidal GL migration across the Bungenstockrücken ice plain is the largest signal reported anywhere in Antarctica. The signal is an order of magnitude higher than the fastest annual average GL retreat of 1.8 km yr-1 460 observed at Pine Island Glacier between 1992 and 2011 (Park et al., 2013) and several orders of magnitude higher than average long-term Antarctic GL migration rates (Konrad et al., 2018). For comparison, the highest estimated deglaciation anywhere in Antarctica. The signal is an order of magnitude higher than the fastest annual average GL retreat of 1.8 km yr-1 460 observed at Pine Island Glacier between 1992 and 2011 (Park et al., 2013) and several orders of magnitude higher than average long-term Antarctic GL migration rates (Konrad et al., 2018). For comparison, the highest estimated deglaciation 21 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. retreat rates from palaeo-records are >2.1 km yr-1 and >10 km yr-1 for Thwaites and Larsen A, respectively (Dowdeswell et al., 2020; Graham et al., 2022). Therefore, to accurately measure long-term GZ change it is necessary to isolate the spatially variable pattern of tidal GL migration. At Bungenstockrücken, the observed difference between the MEaSUREs GL and the 465 ICESat-2 derived Point F values (Fig. 5a) could either suggest that there has been up to 10 km of GL retreat since 2009, or no change, depending on whether the MEaSUREs GL was produced from data sampled at high or low tides. This shows the value of providing a precise time stamp in addition to the acquisition date when producing a GL data product, as the tide amplitude at the time of measurement will inform our interpretation about whether a short-term, temporary tidal fluctuation 465 or a longer-term dynamic change has occurred. Similarly, in this particular location, it is also difficult to quantify any long- 470 term GL migration between the ICESat and ICESat-2 records (Fig. 5a) because the signal is dominated by tidal variability and different methods have been used to derive Point F. The fact that the small number of ICESat-derived maximum inland Point “F2s” from Brunt et al. 5.2 Implications for grounding line monitoring (2011) are broadly consistent with our highest tide ICESat-2 Point Fs, suggests that there has not been significant retreat of the maximum inland flexure limit over the past 10 to 15 years. or a longer-term dynamic change has occurred. Similarly, in this particular location, it is also difficult to quantify any long- 470 term GL migration between the ICESat and ICESat-2 records (Fig. 5a) because the signal is dominated by tidal variability and different methods have been used to derive Point F. The fact that the small number of ICESat-derived maximum inland Point “F2s” from Brunt et al. (2011) are broadly consistent with our highest tide ICESat-2 Point Fs, suggests that there has not been significant retreat of the maximum inland flexure limit over the past 10 to 15 years. Bungenstockrücken provides a reasonable upper bound for rates of tidal GL migration around the ice sheet, as it is located in 475 an ice plain region with low bed slopes and one of the highest tide ranges in Antarctica. Although tidal migration is likely to be much smaller at most Antarctic GLs (depending on tide range and bed properties, including slope and friction coefficient), even at an order of magnitude less may still be sufficient to obscure early signs of long-term retreat in response to ice shelf thinning (Milillo et al., 2017; Li et al., 2022b) and to impact ice dynamics. Therefore, when assessing long-term Bungenstockrücken provides a reasonable upper bound for rates of tidal GL migration around the ice sheet, as it is located in 475 an ice plain region with low bed slopes and one of the highest tide ranges in Antarctica. Although tidal migration is likely to be much smaller at most Antarctic GLs (depending on tide range and bed properties, including slope and friction coefficient), even at an order of magnitude less may still be sufficient to obscure early signs of long-term retreat in response to ice shelf thinning (Milillo et al., 2017; Li et al., 2022b) and to impact ice dynamics. 5.3 Implications for modelling tidal ice shelf flexure and grounding line migration Our results at Bungenstockrücken show that the use of ICESat-2 RTLA to map Point F across the tide cycle can improve our g p y p understanding of the relationship between short-term GL migration and the long-term ice sheet surface profile. We observe 510 that Point F is located seaward of Point Ib for most of the tidal cycle, but see that at the highest tides it consistently migrates as far inland as Point Ib (Fig. 4). As the break-in-slope (Ib) is one of the key surface signatures of the change in basal shear stress at the GL (Schoof, 2011), these observations imply that from a stress-balance perspective the ice sheet geometry is controlled by the furthest inland position that Point F reaches at the highest tides. Although the ice shelf re-grounds seaward of the break-in-slope at low tides, the variable stresses over the ice plain area do not appear to substantially affect the surface 515 profile. There are substantial deviations between flexure-derived GLs and those derived from break-in-slope, which may therefore be partly explained by sampling of GL positions at either mean or non-maximum tides. We propose that the information derived from ICESat-2 RTLA, by better constraining the extent and pattern of tidal GL migration, could be used to better inform the choice of GL in models where observations are used. of the break-in-slope at low tides, the variable stresses over the ice plain area do not appear to substantially affect the surface 515 profile. There are substantial deviations between flexure-derived GLs and those derived from break-in-slope, which may therefore be partly explained by sampling of GL positions at either mean or non-maximum tides. We propose that the information derived from ICESat-2 RTLA, by better constraining the extent and pattern of tidal GL migration, could be used to better inform the choice of GL in models where observations are used. Our results provide observational validations for different numerical models of tidal ice flexure and GL migration. The 520 existence of different modes of tidal GL migration within a region experiencing similar tidal forcing indicates that there is a spatial heterogeneity in local bed properties. 5.2 Implications for grounding line monitoring Ideally, long-term GL location estimates should be made at the same tidal state or tide difference; however, given the scarcity of GL measurements in most locations, this has historically not been feasible. In lieu of this, our updated ICESat-2 RTLA methodology could be applied around the ice sheet margin to provide a constraint on the expected tidal range and mechanisms of GL movement. This will enable better evaluation of the impact of tides on previously-derived estimates of GL position, and ultimately improve the confidence with which we can assess long-term GL change. 485 GL migration rates from sparse observations of GL location through time, we must consider the tidal state associated with 480 each measurement epoch. Ideally, long-term GL location estimates should be made at the same tidal state or tide difference; however, given the scarcity of GL measurements in most locations, this has historically not been feasible. In lieu of this, our updated ICESat-2 RTLA methodology could be applied around the ice sheet margin to provide a constraint on the expected tidal range and mechanisms of GL movement. This will enable better evaluation of the impact of tides on previously-derived estimates of GL position, and ultimately improve the confidence with which we can assess long-term GL change. 485 22 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. This is useful for detecting early signs of ice sheet change, particularly as the accuracy with which altimeters can measure 495 long-term ice thickness change at the GL is limited by our lack of knowledge about the flotation state of the ice across the GZ (further complicated by tidal GL migration). This is useful for detecting early signs of ice sheet change, particularly as the accuracy with which altimeters can measure 495 long-term ice thickness change at the GL is limited by our lack of knowledge about the flotation state of the ice across the GZ (further complicated by tidal GL migration). 5.3 Implications for modelling tidal ice shelf flexure and grounding line migration The representation of GZ processes in ice sheet models strongly impacts projections of future ice (Arthern and Williams, 2017). The 15 km observed tidal GL migration at Bungenstockrücken is much larger than standard 500 model grid spacing at the GL, particularly when mesh refinement occurs (e.g. Durand et al., 2009). Similarly, the time step of an ice sheet model is generally much longer than one day; therefore, prescribing a sub-daily change in GL position is not generally possible. It is beyond the scope of this study to parameterise tidal GL effects in ice sheet models at dissimilar scales, but any “short-term fixed” GL derived from observations must be applied in a consistent manner, whether this is (Arthern and Williams, 2017). The 15 km observed tidal GL migration at Bungenstockrücken is much larger than standard 500 model grid spacing at the GL, particularly when mesh refinement occurs (e.g. Durand et al., 2009). Similarly, the time step of an ice sheet model is generally much longer than one day; therefore, prescribing a sub-daily change in GL position is not generally possible. It is beyond the scope of this study to parameterise tidal GL effects in ice sheet models at dissimilar scales, but any “short-term fixed” GL derived from observations must be applied in a consistent manner, whether this is (Arthern and Williams, 2017). The 15 km observed tidal GL migration at Bungenstockrücken is much larger than standard 500 model grid spacing at the GL, particularly when mesh refinement occurs (e.g. Durand et al., 2009). Similarly, the time step of an ice sheet model is generally much longer than one day; therefore, prescribing a sub-daily change in GL position is not generally possible. It is beyond the scope of this study to parameterise tidal GL effects in ice sheet models at dissimilar scales, but any “short-term fixed” GL derived from observations must be applied in a consistent manner, whether this is using the highest, lowest or “mean” tide position. This choice of a consistent GL is complicated by the fact that different 505 satellite-derived GL products use different surface proxies (i.e. Points F vs Ib), each of which relate differently to the sharp basal stress boundary, which is the parameter that we generally want to represent in models. Moreover, the extent to which tidal GL migration can blur the basal stress boundary in areas of ephemeral grounding is largely unknown. 5.3 Implications for modelling tidal ice shelf flexure and grounding line migration We observe a similar linear mode of GL migration within the sampled tide range along numerous ICESat-2 ground tracks at Bungenstockrücken (Fig. 6a-c). In contrast, Tsai and Gudmundsson (2015) modelled the GL as an elastic fracture problem forced by the tidally-induced increase in ocean water pressure, concluding that tidally- induced GL migration in areas with prograde bed slopes is asymmetric, with the GL migrating up to 9 times further inland at high tide than it migrates seaward at low tide. Along several ICESat-2 ground tracks at Bungenstockrücken we observe a 530 similar kind of asymmetry in the mode of tidal GL migration (Fig. 6d-f). It is likely that the shape and stiffness of the bed exert strong controls over the mode of GL migration (Sayag and Worster, 2013), but independent bed information is generally not high enough resolution to further inform our interpretation of the flexure patterns observed by our ICESat-2 RTLA method. high tide than it migrates seaward at low tide. Along several ICESat-2 ground tracks at Bungenstockrücken we observe a 530 similar kind of asymmetry in the mode of tidal GL migration (Fig. 6d-f). It is likely that the shape and stiffness of the bed exert strong controls over the mode of GL migration (Sayag and Worster, 2013), but independent bed information is generally not high enough resolution to further inform our interpretation of the flexure patterns observed by our ICESat-2 RTLA method. 530 Our ICESat-2 observations can also inform the representation of elastic and viscous stresses in these models of tidal flexure 535 and GL migration. Both the Sayag and Worster (2013) and Tsai and Gudmundsson (2015) models use purely elastic frameworks, justified due to the short timescales (<12 h) over which the forcing acts. In reality, ice deforms viscoelastically (Reeh et al., 2003) and so these models overlook any time-dependent viscoelastic deformation that follows the initial elastic response to tides. The hysteresis mode of tidal GL migration observed at Bungenstockrücken (Figs. 5j-l and 6) reveals a time delay between the response of the ice shelf surface (and perhaps also the subglacial till) to tidal forcing. 5.3 Implications for modelling tidal ice shelf flexure and grounding line migration Therefore, in regions like Bungenstockrücken that experience large tidal GL migration, models of tide flexure that do not allow for movement of the GL (Holdsworth, 1969; Schmeltz et al., 2002; Walker et al., 2013) cannot produce realistic representations of the basal stress or GL velocity change. Sayag and Worster (2013) developed an elastic beam model coupled to an elastically deforming bed that allows the GL to migrate 525 23 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. proportionally with tidal forcing. We observe a similar linear mode of GL migration within the sampled tide range along numerous ICESat-2 ground tracks at Bungenstockrücken (Fig. 6a-c). In contrast, Tsai and Gudmundsson (2015) modelled the GL as an elastic fracture problem forced by the tidally-induced increase in ocean water pressure, concluding that tidally- induced GL migration in areas with prograde bed slopes is asymmetric, with the GL migrating up to 9 times further inland at proportionally with tidal forcing. We observe a similar linear mode of GL migration within the sampled tide range along numerous ICESat-2 ground tracks at Bungenstockrücken (Fig. 6a-c). In contrast, Tsai and Gudmundsson (2015) modelled the GL as an elastic fracture problem forced by the tidally-induced increase in ocean water pressure, concluding that tidally- induced GL migration in areas with prograde bed slopes is asymmetric, with the GL migrating up to 9 times further inland at proportionally with tidal forcing. We observe a similar linear mode of GL migration within the sampled tide range along numerous ICESat-2 ground tracks at Bungenstockrücken (Fig. 6a-c). In contrast, Tsai and Gudmundsson (2015) modelled the GL as an elastic fracture problem forced by the tidally-induced increase in ocean water pressure, concluding that tidally- induced GL migration in areas with prograde bed slopes is asymmetric, with the GL migrating up to 9 times further inland at high tide than it migrates seaward at low tide. Along several ICESat-2 ground tracks at Bungenstockrücken we observe a 530 similar kind of asymmetry in the mode of tidal GL migration (Fig. 6d-f). It is likely that the shape and stiffness of the bed exert strong controls over the mode of GL migration (Sayag and Worster, 2013), but independent bed information is generally not high enough resolution to further inform our interpretation of the flexure patterns observed by our ICESat-2 RTLA method. proportionally with tidal forcing. 5.3 Implications for modelling tidal ice shelf flexure and grounding line migration Similar observations 540 in Greenland have shown a difference in the surface deflection profile between rising and falling tides, and have been well described by viscoelastic beam models that capture this lag between the change in the tide and the ice shelf response (Reeh et al., 2000, 2003; Wild et al., 2017). Currently no models of tidal flexure exist that use both a viscoelastic framework and allow for migration of the GL, but this may be necessary to better represent these kinds of processes in GZs subject to high tidal variability and could account for the discrepancies between model predictions and observations. 545 Modes of tidal GL migration and why they differ spatially, can also provide insights into the underlying bed topography. As a specific example, we expect that the threshold mode of GL migration (Fig. 6g-i) is likely to only exist in regions with a very flat bed where the ice is very close to flotation, whereby a small increase in tide across this threshold can provide enough buoyant force to unground the ice and cause large GL migration. Area B at Bungenstockrücken is likely grounded tidal variability and could account for the discrepancies between model predictions and observations. 545 Modes of tidal GL migration and why they differ spatially, can also provide insights into the underlying bed topography. As a specific example, we expect that the threshold mode of GL migration (Fig. 6g-i) is likely to only exist in regions with a very flat bed where the ice is very close to flotation, whereby a small increase in tide across this threshold can provide enough buoyant force to unground the ice and cause large GL migration. Area B at Bungenstockrücken is likely grounded over a very flat bed, as we observe a cluster of ground tracks with a threshold tidal GL migration mode (Fig. 6m). While 550 Brunt et al. (2011) presented a method to calculate bed slopes from tidal GL migration along ICESat tracks based on a hydrostatic assumption, this assumed a linear relationship between migration distance and tide height, which, as our findings prove, is not necessarily valid in the GZ. Our results therefore support the conclusion of Tsai and Gudmundsson (2015) in urging caution when quantitatively inferring bed slopes from measurements of tidal GL migration. 5.3 Implications for modelling tidal ice shelf flexure and grounding line migration over a very flat bed, as we observe a cluster of ground tracks with a threshold tidal GL migration mode (Fig. 6m). While 550 Brunt et al. (2011) presented a method to calculate bed slopes from tidal GL migration along ICESat tracks based on a hydrostatic assumption, this assumed a linear relationship between migration distance and tide height, which, as our findings prove, is not necessarily valid in the GZ. Our results therefore support the conclusion of Tsai and Gudmundsson (2015) in urging caution when quantitatively inferring bed slopes from measurements of tidal GL migration. The distribution of tidal GL migration modes as well as the width and rate of tidal GL migration around Antarctic GZs is 555 valuable to inform the choice of parameterisation of tidal flexure mechanisms, basal shear stress and/or basal melt in larger- The distribution of tidal GL migration modes as well as the width and rate of tidal GL migration around Antarctic GZs is 555 valuable to inform the choice of parameterisation of tidal flexure mechanisms, basal shear stress and/or basal melt in larger- The distribution of tidal GL migration modes as well as the width and rate of tidal GL migration around Antarctic GZs is 555 valuable to inform the choice of parameterisation of tidal flexure mechanisms, basal shear stress and/or basal melt in larger- 24 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. scale ice sheet models. For example, Mosbeux et al. (2022) considered different GL migration parameterisations to assess the impact of seasonal sea surface height variability on ice velocities over the Ross Ice Shelf. The first considered an asymmetric treatment of GL migration with elastic fracture mechanics introduced by Tsai and Gudmundsson (2015)) and a constant bed slope, and the second defined migration using hydrostatic equilibrium of the GL with BedMap2 bed slopes. 560 They found that the asymmetric treatment led to larger modelled ice shelf velocity variability that more closely matched GNSS observations. Given that the mechanism of migration varies spatially, even across relatively small distances (as we have demonstrated), then obtaining reliable observations of the spatial distribution of these GL migration modes around Antarctica is needed to inform the parameterisation of GL processes in larger ice sheet modelling studies. 5.3 Implications for modelling tidal ice shelf flexure and grounding line migration Our study at B t k ü k h f ll d t t d h ICES t 2 RTLA b d fi t t t d thi 565 Bungenstockrücken has successfully demonstrated how ICESat-2 RTLA can be used as a first step towards this. 565 5.4 Insights into tidal processes in the ice shelf-ocean-subglacial system The cyclical, twice-daily ungrounding and tidal flushing of ocean water up to 15 km into the GZ has implications for several processes contributing to the net dynamics of this system (Fig. 8). Many of these processes are poorly understood with few observations, and so the use of ICESat-2 RTLA to study tidal GL behaviour in settings like Bungenstockrücken could provide important new insights and constraints. 570 25 Figure 8: Schematic summarising impacts of tidal flexure and GL migration on the ice shelf-ocean-subglacial system. These include impacts on: Ice velocity (Gudmundsson, 2007; Thompson et al., 2014; Robel et al., 2017, 2022; Mosbeux et al., 2022); GZ surface profile (e.g. Schoof, 2011); Inland seawater incursion (Warburton et al., 2020; Robel et al., 2022); Variations in subglacial water pressure (Rosier et al., 2015; Begeman et al., 2020); Formation of estuarine features in the GZ (Horgan et al., 2013a); Enhanced basal melt (Makinson et 75 al., 2011; Mueller et al., 2012); Basal shear stress (Anandakrishnan et al., 2003); Till compaction, leading to changes in basal lubrication (Walker et al., 2013; Christianson et al., 2013; Sayag and Worster, 2013); Formation of tidal seabed ridges (Dowdeswell et al., 2020; Graham et al., 2022); Ocean circulation through tidal mixing. The landward and seaward tidal GL positions are labelled as Fmax and Fmin. 25 Figure 8: Schematic summarising impacts of tidal flexure and GL migration on the ice shelf-ocean-subglacial system. These include impacts on: Ice velocity (Gudmundsson, 2007; Thompson et al., 2014; Robel et al., 2017, 2022; Mosbeux et al., 2022); GZ surface profile (e.g. Schoof, 2011); Inland seawater incursion (Warburton et al., 2020; Robel et al., 2022); Variations in subglacial water pressure (Rosier et al., 2015; Begeman et al., 2020); Formation of estuarine features in the GZ (Horgan et al., 2013a); Enhanced basal melt (Makinson et al., 2011; Mueller et al., 2012); Basal shear stress (Anandakrishnan et al., 2003); Till compaction, leading to changes in basal lubrication (Walker et al., 2013; Christianson et al., 2013; Sayag and Worster, 2013); Formation of tidal seabed ridges (Dowdeswell et al., 2020; Graham et al., 2022); Ocean circulation through tidal mixing. The landward and seaward tidal GL positions are labelled as Fmax and Fmin. 575 25 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. 5.4 Insights into tidal processes in the ice shelf-ocean-subglacial system Little is known about the oceanography close to most of the Antarctic GZ, but the ability to observe the tidal variability of cavity geometry with ICESat-2 RTLA will allow us to model the potential melt rates in these anomalous regions. At 580 Bungenstockrücken, our results indicate that an additional ~1,300 km2 of ice ungrounds twice-daily between low and high tide (Fig. 4), allowing the relatively warm ocean water to reach deeper into the GZ cavity and exposing this additional area to basal melt. The cold High Salinity Shelf Water (HSSW) beneath the Ronne Ice Shelf causes relatively low basal melt rates (compared to warmer regions like the Amundsen Sea that are affected by Circumpolar Deep Water), but depression of the seawater freezing point under pressure means it still has the capacity to melt ice at the GL (Nicholls and Østerhus, 2004; 585 Makinson et al., 2011; Naughten et al., 2021). The very shallow water column (<100m) immediately seaward of Bungenstockrücken (Johnson and Smith, 1997) suggests that tidal mixing would be strong here, and is likely to be enhanced as water is “pumped” in and out of the cavity as the GL migrates with the tides. Short-term tidal fluctuations in melt rate and tidal mixing have been shown to impact long-term GL retreat in less stable regions (Graham et al., 2022). Given that seawater freezing point under pressure means it still has the capacity to melt ice at the GL (Nicholls and Østerhus, 2004; 585 Makinson et al., 2011; Naughten et al., 2021). The very shallow water column (<100m) immediately seaward of Bungenstockrücken (Johnson and Smith, 1997) suggests that tidal mixing would be strong here, and is likely to be enhanced as water is “pumped” in and out of the cavity as the GL migrates with the tides. Short-term tidal fluctuations in melt rate and tidal mixing have been shown to impact long-term GL retreat in less stable regions (Graham et al., 2022). Given that projections of future ice sheet mass loss are highly sensitive to basal melt at the GL (Arthern and Williams, 2017; Goldberg 590 et al., 2019; Adusumilli et al., 2020), the type of information about tidal GZ behaviour that we can derive from ICESat-2 RTLA will be valuable to improve melt parameterisations in ice sheet models. 5.4 Insights into tidal processes in the ice shelf-ocean-subglacial system projections of future ice sheet mass loss are highly sensitive to basal melt at the GL (Arthern and Williams, 2017; Goldberg 590 et al., 2019; Adusumilli et al., 2020), the type of information about tidal GZ behaviour that we can derive from ICESat-2 RTLA will be valuable to improve melt parameterisations in ice sheet models. Variation in basal stresses in the GZ caused by tidal flexure and GL migration can also impact the flow of upstream and downstream ice. Grounding and ungrounding of the ice shelf throughout the tidal cycle has several effects: it changes the area affected by basal drag; modifies the driving stress through changes in surface slope (e.g. Makinson et al., 2012; 595 Mosbeux et al., 2022); modulates hydrostatic and flexural stresses (e.g. Rosier and Gudmundsson, 2016); and impacts buttressing (e.g. Robel et al., 2017). Rosier and Gudmundsson (2020) concluded that the presence of tides enhances ice flow across the entire Filchner-Ronne Ice Shelf by 21%. Since ice velocities across the Bungenstockrücken GL do not exceed ~5 m a-1 (Rignot et al., 2017), the impact of tidal GL migration on absolute flow speed here is likely to be low, but it may be more significant in faster flowing regions such as the Rutford Ice Stream (Minchew et al 2017) 600 Our results have implications for testing models and hypotheses in subglacial hydrology. It has been suggested that tidal ice shelf flexure acts to “pump” ocean water upstream of the GL into the subglacial hydrological system, with implications for basal lubrication, basal melt and till compaction (Christianson et al., 2013; Horgan et al., 2013a; Sayag and Worster, 2013; Walker et al., 2013; Drews et al., 2017; Robel et al., 2022). Airborne radar data indicate the possible presence of brackish water several kilometres inland of the Bungenstockrücken GL (Corr, 2021), which may provide evidence for upstream 605 seawater incursion driven by tidal GL migration. Modelling of this process by Warburton et al. (2020) indicated that water is pumped upstream into the subglacial environment much faster during a rising tide than it drains as the tide falls. The hysteresis mode of GL migration observed at Bungenstockrücken (Figs. 6j-l and 7) suggests there is a similar lag in the response of the ice shelf surface to tidal forcing between rising and falling phases, which could provide observational support for this theory. For example, the pattern observed in Area B (Fig. 6 Summary and outlook We have presented an updated method for determining Antarctic ice shelf grounding line (GL) location from ICESat-2 repeat track laser altimetry (RTLA). We show that, by using the elevation profile at the lowest-sampled tide as the reference profile for calculating anomalies, it is possible to locate the inland limit of tidal flexure at different stages of the tidal cycle. 620 This temporal resolution provides insights into grounding zone (GZ) processes on tidal timescales that are difficult to observe with other methods. We have applied the technique to the GZ of an ice plain north of Bungenstockrücken on the southern Ronne Ice Shelf, where we observe >15 km of tidal GL migration. This is the largest reported distance of ephemeral grounding anywhere in Antarctica and demonstrates the necessity of accounting for short-term tidal GL migration to accurately measure long-term migration. It also calls into question the use of a fixed or slowly moving GL boundary in ice 625 sheet models, which does not represent the full range of GL migration behaviour. Our updated ICESat-2 RTLA technique also allows us to observe different modes of tidal GL migration, and we classify four modes at the Bungenstockrücken ice plain: “linear”, “asymmetric”, “threshold” and “hysteresis”. This can provide observational validation for models of tidal ice shelf flexure, GL migration and subglacial hydrology at the GZ, and offers a tool for future explorations of bed to accurately measure long-term migration. It also calls into question the use of a fixed or slowly moving GL boundary in ice 625 sheet models, which does not represent the full range of GL migration behaviour. Our updated ICESat-2 RTLA technique also allows us to observe different modes of tidal GL migration, and we classify four modes at the Bungenstockrücken ice plain: “linear”, “asymmetric”, “threshold” and “hysteresis”. This can provide observational validation for models of tidal ice shelf flexure, GL migration and subglacial hydrology at the GZ, and offers a tool for future explorations of bed characteristics, basal melt and basal shear stress in these sensitive parts of the ice sheet. We suggest that monitoring the 630 change in extent and modes of tidal GL migration around Antarctica could provide vital early indications of wider ice sheet change. 5.4 Insights into tidal processes in the ice shelf-ocean-subglacial system 7) is likely to indicate that a subglacial channel or 610 26 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. cavity exists in between the seaward and landward GL positions that fills with water at high tide (above a certain threshold). As the tide falls, the water drains away more slowly and the ice around the seaward GL position (a possible topographic high) re-grounds before the landward cavity has fully emptied, forcing the water to be flushed out from this channel to the east (Fig. 7b,c). This could be a similar pattern to tidal beach drainage, and supports the idea of “estuary” type features at the ice sheet margins (Horgan et al., 2013a). Knowledge of the modes of tidal GL migration around the coast derived from ICESat-2 RTLA will be useful for constraining such regional models. cavity exists in between the seaward and landward GL positions that fills with water at high tide (above a certain threshold). As the tide falls, the water drains away more slowly and the ice around the seaward GL position (a possible topographic high) re-grounds before the landward cavity has fully emptied, forcing the water to be flushed out from this channel to the east (Fig. 7b,c). This could be a similar pattern to tidal beach drainage, and supports the idea of “estuary” type features at the ice sheet margins (Horgan et al., 2013a). Knowledge of the modes of tidal GL migration around the coast derived from ICESat-2 RTLA will be useful for constraining such regional models. 615 Code Availability. The code developed for this study can be provided by the corresponding authors upon request and will be made available at a DOI tbc. Code Availability. The code developed for this study can be provided by the corresponding authors upon request and will be made available at a DOI tbc. Data Availability. The ICESat-2 ATL06 data, ICESat-2 grounding zone products and the MEaSUREs grounding line 650 product used in this study are available from the National Snow and Ice Data Center (NSIDC). The ASAID grounding line and ICESat-derived grounding zone products are available from the U.S. Antarctic Program Data Center. Author Contribution. BF and OM planned the research; BF conducted the data analysis and wrote the manuscript. All authors provided insights in the interpretation of data, and reviewed and edited the manuscript. Author Contribution. BF and OM planned the research; BF conducted the data analysis and wrote the manuscript. All authors provided insights in the interpretation of data, and reviewed and edited the manuscript. Competing interests. The authors declare that they have no conflict of interest. 655 Acknowledgements. This work was led by BF at British Antarctic Survey (BAS) and the School of Earth and Environment at the University of Leeds. BF was supported by the Natural Environment Research Council (NERC) SENSE Centre for Doctoral Training (NE/T00939X/1). AEH was supported by the NERC DeCAdeS project (NE/T012757/1) and the ESA Polar+ Ice Shelves project (ESA-IPL-POE-EF-cb-LE-2019-834). HAF was supported by NASA grant 80NSSC20K0977. LP was supported by the ESR ICESat-2 grant 80NSSC21K0911. The authors gratefully acknowledge the National Aeronautics 660 d S Ad i i t ti f i i th ICES t 2 t llit d t was supported by the ESR ICESat-2 grant 80NSSC21K0911. The authors gratefully acknowledge the National Aeronautics 660 and Space Administration for acquiring the ICESat-2 satellite data. Alley, R. B., Blankenship, D. D., Rooney, S. T., and Bentley, C. R.: Sedimentation beneath ice shelves — the view from ice 665 stream B, Marine Geology, 85, 101–120, https://doi.org/10.1016/0025-3227(89)90150-3, 1989. Adusumilli, S., Fricker, H. A., Medley, B., Padman, L., and Siegfried, M. R.: Interannual variations in meltwater input to the Southern Ocean from Antarctic ice shelves, Nat. Geosci., 13, 616–620, https://doi.org/10.1038/s41561-020-0616-z, 2020. 6 Summary and outlook Based on the findings of this study, we make four recommendations for future work: (1) Any future satellite-derived measurement of GL position should be accompanied with a timestamp (at least to the closest hour), ideally also with coincident tide height and phase. For DInSAR this information should be provided per image, and for RTLA for both the reference and repeat cycle tides. This will allow a more robust assessment of the impact of tidal processes on individual measurements of the GL position. 635 (2) Future studies should scale this analysis up across Antarctica to derive a continent-wide dataset of the extent and mode of tidal GL migration. This could be used to improve confidence in long-term records of GL migration. (2) Future studies should scale this analysis up across Antarctica to derive a continent-wide dataset of the extent and mode of tidal GL migration. This could be used to improve confidence in long-term records of GL migration. 27 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. (3) Targeted ground-based surveys in regions subject to extreme tidal variability would be valuable to better understand 640 the link between these surface observations and the processes taking place within and beneath the ice in GZs on tidal timescales. We suggest that Bungenstockrücken would be a suitable location, due to its high tidal signal, low ice velocity and crevassing, and current long-term stability which isolates the tidal signal from long-term change. (4) The observations presented here have only been possible to obtain using ICESat-2. Therefore, it is crucial that we extend our satellite-based repeat-track sampling of ice sheet surface elevation beyond this satellite mission to 45 continue this valuable record as ice sheets continue to respond to the changing climate. (4) The observations presented here have only been possible to obtain using ICESat-2. Therefore, it is crucial that we extend our satellite-based repeat-track sampling of ice sheet surface elevation beyond this satellite mission to 45 continue this valuable record as ice sheets continue to respond to the changing climate. Code Availability. The code developed for this study can be provided by the corresponding authors upon request and will be made available at a DOI tbc. Code Availability. The code developed for this study can be provided by the corresponding authors upon request and will be made available at a DOI tbc. References and Choi, H.: High-resolution Image-derived Grounding and Hydrostatic Lines for the Antarctic Ice Sheet, U.S. Antarctic Program (USAP) Data Center [data set], https://doi.org/10.7265/N56T0JK2, 2011. Bindschadler, R., Choi, H., Wichlacz, A., Bingham, R., Bohlander, J., Brunt, K., Corr, H., Drews, R., Fricker, H., Hall, M., 680 Hindmarsh, R., Kohler, J., Padman, L., Rack, W., Rotschky, G., Urbini, S., Vornberger, P., and Young, N.: Getting around Antarctica: new high-resolution mappings of the grounded and freely-floating boundaries of the Antarctic ice sheet created for the International Polar Year, The Cryosphere, 5, 569–588, https://doi.org/10.5194/tc-5-569-2011, 2011. Bojinski, S., Verstraete, M., Peterson, T. C., Richter, C., Simmons, A., and Zemp, M.: The Concept of Essential Climate Variables in Support of Climate Research, Applications, and Policy, Bulletin of the American Meteorological Society, 95, 685 1431–1443, https://doi.org/10.1175/BAMS-D-13-00047.1, 2014. Bojinski, S., Verstraete, M., Peterson, T. C., Richter, C., Simmons, A., and Zemp, M.: The Concept of Essential Climate Variables in Support of Climate Research, Applications, and Policy, Bulletin of the American Meteorological Society, 95, 685 1431–1443, https://doi.org/10.1175/BAMS-D-13-00047.1, 2014. Brancato, V., Rignot, E., Milillo, P., Morlighem, M., Mouginot, J., An, L., Scheuchl, B., Jeong, S., Rizzoli, P., Bueso Bello, J. L., and Prats‐Iraola, P.: Grounding Line Retreat of Denman Glacier, East Antarctica, Measured With COSMO‐SkyMed Radar Interferometry Data, Geophys. Res. Lett., 47, https://doi.org/10.1029/2019GL086291, 2020. Brancato, V., Rignot, E., Milillo, P., Morlighem, M., Mouginot, J., An, L., Scheuchl, B., Jeong, S., Rizzoli, P., Bueso Bello, J. L., and Prats‐Iraola, P.: Grounding Line Retreat of Denman Glacier, East Antarctica, Measured With COSMO‐SkyMed Radar Interferometry Data, Geophys. Res. Lett., 47, https://doi.org/10.1029/2019GL086291, 2020. Brunt, K. M., Fricker, H. A., Padman, L., and O’Neel, S.: ICESat-Derived Grounding Zone for Antarctic Ice Shelves, U.S. 690 Antarctic Program (USAP) Data Center [data set], https://doi.org/10.7265/N5CF9N19, 2010a. Brunt, K. M., Fricker, H. A., Padman, L., Scambos, T. A., and O’Neel, S.: Mapping the grounding zone of the Ross Ice Shelf, Antarctica, using ICESat laser altimetry, Ann. Glaciol., 51, 71–79, https://doi.org/10.3189/172756410791392790, 2010b. Brunt, K. M., Fricker, H. A., Padman, L., and O’Neel, S.: ICESat-Derived Grounding Zone for Antarctic Ice Shelves, U.S. 690 Antarctic Program (USAP) Data Center [data set], https://doi.org/10.7265/N5CF9N19, 2010a. Brunt, K. M., Fricker, H. A., Padman, L., Scambos, T. A., and O’Neel, S.: Mapping the grounding zone of the Ross Ice Shelf, Antarctica, using ICESat laser altimetry, Ann. Glaciol., 51, 71–79, https://doi.org/10.3189/172756410791392790, 2010b. Brunt, K. M., Fricker, H. References Adusumilli, S., Fricker, H. A., Medley, B., Padman, L., and Siegfried, M. R.: Interannual variations in meltwater input to the Southern Ocean from Antarctic ice shelves, Nat. Geosci., 13, 616–620, https://doi.org/10.1038/s41561-020-0616-z, 2020. Alley, R. B., Blankenship, D. D., Rooney, S. T., and Bentley, C. R.: Sedimentation beneath ice shelves — the view from ice 665 stream B, Marine Geology, 85, 101–120, https://doi.org/10.1016/0025-3227(89)90150-3, 1989. 28 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. Anandakrishnan, S., Voigt, D. E., Alley, R. B., and King, M. A.: Ice stream D flow speed is strongly modulated by the tide beneath the Ross Ice Shelf, Geophys. Res. Lett., 30, https://doi.org/10.1029/2002GL016329, 2003. Arendt, A., Scheick, J., Shean, D., Buckley, Ellen, Grigsby, Shane, Haley, Charley, Heagy, Lindsey, Mohajerani, Yara, 670 Neumann, Tom, Nilsson, Johan, Markus, Thorsten, Paolo, Fernando S., Perez, Fernando, Petty, Alek, Schweiger, Axel, 670 Smith, Benjamin, Steiker, Amy, Alvis, Sebastian, Henderson, Scott, Holschuh, Nick, Liu, Zheng, and Sutterly, Tyler: 2020 ICESat-2 Hackweek Tutorials, Zenodo [code] , https://doi.org/10.5281/ZENODO.3966463, 2020. Arthern, R. J. and Williams, C. R.: The sensitivity of West Antarctica to the submarine melting feedback, Geophys. Res. Lett., 44, 2352–2359, https://doi.org/10.1002/2017GL072514, 2017. ICESat-2 Hackweek Tutorials, Zenodo [code] , https://doi.org/10.5281/ZENODO.3966463, 2020. Arthern, R. J. and Williams, C. R.: The sensitivity of West Antarctica to the submarine melting feedback, Geophys. Res. Lett., 44, 2352–2359, https://doi.org/10.1002/2017GL072514, 2017. thern, R. J. and Williams, C. R.: The sensitivity of West Antarctica to the submarine melting feedback, Geophys. Res. tt., 44, 2352–2359, https://doi.org/10.1002/2017GL072514, 2017. Begeman, C. B., Tulaczyk, S., Padman, L., King, M., Siegfried, M. R., Hodson, T. O., and Fricker, H. A.: Tidal 675 Pressurization of the Ocean Cavity Near an Antarctic Ice Shelf Grounding Line, J. Geophys. Res. Oceans, 125, https://doi.org/10.1029/2019JC015562, 2020. Bindschadler, R. and Choi, H.: High-resolution Image-derived Grounding and Hydrostatic Lines for the Antarctic Ice Sheet, U.S. Antarctic Program (USAP) Data Center [data set], https://doi.org/10.7265/N56T0JK2, 2011. Begeman, C. B., Tulaczyk, S., Padman, L., King, M., Siegfried, M. R., Hodson, T. O., and Fricker, H. A.: Tidal 675 Pressurization of the Ocean Cavity Near an Antarctic Ice Shelf Grounding Line, J. Geophys. Res. Oceans, 125, https://doi.org/10.1029/2019JC015562, 2020. https://doi.org/10.1029/2019JC015562, 2020. Bindschadler, R. and Choi, H.: High-resolution Image-derived Grounding and Hydrostatic Lines for the Antarctic Ice Sheet, U.S. Antarctic Program (USAP) Data Center [data set], https://doi.org/10.7265/N56T0JK2, 2011. Bindschadler, R. References L.: Measuring the location and width of the Antarctic grounding zone using CryoSat-2, The Corr, H. F. J., Doake, C. S. M., Jenkins, A., and Vaughan, D. G.: Investigations of an “ice plain” in the mouth of Pine Island 705 Glacier, Antarctica, J. Glaciol., 47, 51–57, https://doi.org/10.3189/172756501781832395, 2001. Dawson G J and Bamber J L : Antarctic Grounding Line Mapping From CryoSat-2 Radar Altimetry Geophys Res Lett Corr, H. F. J., Doake, C. S. M., Jenkins, A., and Vaughan, D. G.: Investigations of an ice plain in the mouth of Pine Island 705 Glacier, Antarctica, J. Glaciol., 47, 51–57, https://doi.org/10.3189/172756501781832395, 2001. Dawson, G. J. and Bamber, J. L.: Antarctic Grounding Line Mapping From CryoSat-2 Radar Altimetry, Geophys. Res. Lett., 44, 11886-11893, https://doi.org/10.1002/2017GL075589, 2017. Dawson, G. J. and Bamber, J. L.: Antarctic Grounding Line Mapping From CryoSat-2 Radar Altimetry, Geophys. Res. Lett., 44, 11886-11893, https://doi.org/10.1002/2017GL075589, 2017. Dawson, G. J. and Bamber, J. L.: Measuring the location and width of the Antarctic grounding zone using CryoSat-2, The Cryosphere, 14, 2071–2086, https://doi.org/10.5194/tc-14-2071-2020, 2020. Dawson, G. J. and Bamber, J. L.: Measuring the location and width of the Antarctic grounding zone using CryoSat-2, The Cryosphere 14 2071 2086 https://doi org/10 5194/tc 14 2071 2020 2020 710 Cryosphere, 14, 2071–2086, https://doi.org/10.5194/tc-14-2071-2020, 2020. 710 Depoorter, M. A., Bamber, J. L., Griggs, J. A., Lenaerts, J. T. M., Ligtenberg, S. R. M., van den Broeke, M. R., and Moholdt, G.: Calving fluxes and basal melt rates of Antarctic ice shelves, Nature, 502, 89–92, https://doi.org/10.1038/nature12567, 2013. Depoorter, M. A., Bamber, J. L., Griggs, J. A., Lenaerts, J. T. M., Ligtenberg, S. R. M., van den Broeke, M. R., and Moholdt, G.: Calving fluxes and basal melt rates of Antarctic ice shelves, Nature, 502, 89–92, https://doi.org/10.1038/nature12567, 2013. Dowdeswell, J. A., Batchelor, C. L., Montelli, A., Ottesen, D., Christie, F. D. W., Dowdeswell, E. K., and Evans, J.: Delicate seafloor landforms reveal past Antarctic grounding-line retreat of kilometers per year, Science, 368, 1020–1024, 715 https://doi.org/10.1126/science.aaz3059, 2020. Dowdeswell, J. A., Batchelor, C. L., Montelli, A., Ottesen, D., Christie, F. D. W., Dowdeswell, E. K., and Evans, J.: Delicate seafloor landforms reveal past Antarctic grounding-line retreat of kilometers per year, Science, 368, 1020–1024, 715 https://doi.org/10.1126/science.aaz3059, 2020. Drews, R., Pattyn, F., Hewitt, I. J., Ng, F. S. References L., Berger, S., Matsuoka, K., Helm, V., Bergeot, N., Favier, L., and Neckel, N.: Actively evolving subglacial conduits and eskers initiate ice shelf channels at an Antarctic grounding line, Nat. Commun., 8, 15228, https://doi.org/10.1038/ncomms15228, 2017. Drews, R., Pattyn, F., Hewitt, I. J., Ng, F. S. L., Berger, S., Matsuoka, K., Helm, V., Bergeot, N., Favier, L., and Neckel, N.: Actively evolving subglacial conduits and eskers initiate ice shelf channels at an Antarctic grounding line, Nat. Commun., 8, 15228, https://doi.org/10.1038/ncomms15228, 2017. Dupont, T. K. and Alley, R. B.: Assessment of the importance of ice-shelf buttressing to ice-sheet flow, Geophys. Res. Lett., 720 32, L04503, https://doi.org/10.1029/2004GL022024, 2005. Dupont, T. K. and Alley, R. B.: Assessment of the importance of ice-shelf buttressing to ice-sheet flow, Geophys. Res. Lett., 720 32, L04503, https://doi.org/10.1029/2004GL022024, 2005. Durand, G., Gagliardini, O., de Fleurian, B., Zwinger, T., and Le Meur, E.: Marine ice sheet dynamics: Hysteresis and Dupont, T. K. and Alley, R. B.: Assessment of the importance of ice-shelf buttressing to ice-sheet flow, Geophys. Res. Lett., 720 32, L04503, https://doi.org/10.1029/2004GL022024, 2005. Durand, G., Gagliardini, O., de Fleurian, B., Zwinger, T., and Le Meur, E.: Marine ice sheet dynamics: Hysteresis and neutral equilibrium, J. Geophys. Res., 114, F03009, https://doi.org/10.1029/2008JF001170, 2009. Durand, G., Gagliardini, O., de Fleurian, B., Zwinger, T., and Le Meur, E.: Marine ice sheet dynamics: Hysteresis and neutral equilibrium, J. Geophys. Res., 114, F03009, https://doi.org/10.1029/2008JF001170, 2009. Dutrieux, P., De Rydt, J., Jenkins, A., Holland, P. R., Ha, H. K., Lee, S. H., Steig, E. J., Ding, Q., Abrahamsen, E. P., and Schroder, M.: Strong Sensitivity of Pine Island Ice-Shelf Melting to Climatic Variability, Science, 343, 174–178, 725 https://doi.org/10.1126/science.1244341, 2014. Favier, L., Durand, G., Cornford, S. L., Gudmundsson, G. H., Gagliardini, O., Gillet-Chaulet, F., Zwinger, T., Payne, A. J., and Le Brocq, A. M.: Retreat of Pine Island Glacier controlled by marine ice-sheet instability, Nat. Clim. Change, 4, 117– Dutrieux, P., De Rydt, J., Jenkins, A., Holland, P. R., Ha, H. K., Lee, S. H., Steig, E. J., Ding, Q., Abrahamsen, E. P., and Schroder, M.: Strong Sensitivity of Pine Island Ice-Shelf Melting to Climatic Variability, Science, 343, 174–178, 725 https://doi.org/10.1126/science.1244341, 2014. Schroder, M.: Strong Sensitivity of Pine Island Ice-Shelf Melting to Climatic Variability, Science, 343, 174–178, 725 https://doi.org/10.1126/science.1244341, 2014. Favier, L., Durand, G., Cornford, S. L., Gudmundsson, G. H., Gagliardini, O., Gillet-Chaulet, F., Zwinger, T., Payne, A. J., and Le Brocq, A. References A., and Padman, L.: Analysis of ice plains of the Filchner–Ronne Ice Shelf, Antarctica, using 695 ICESat laser altimetry, J. Glaciol., 57, 965–975, https://doi.org/10.3189/002214311798043753, 2011. Catania, G., Hulbe, C., and Conway, H.: Grounding-line basal melt rates determined using radar-derived internal stratigraphy, J. Glaciol., 56, 545–554, https://doi.org/10.3189/002214310792447842, 2010. Brunt, K. M., Fricker, H. A., and Padman, L.: Analysis of ice plains of the Filchner–Ronne Ice Shelf, Antarctica, using 695 ICESat laser altimetry, J. Glaciol., 57, 965–975, https://doi.org/10.3189/002214311798043753, 2011. Catania, G., Hulbe, C., and Conway, H.: Grounding-line basal melt rates determined using radar-derived internal stratigraphy, J. Glaciol., 56, 545–554, https://doi.org/10.3189/002214310792447842, 2010. Christianson, K., Parizek, B. R., Alley, R. B., Horgan, H. J., Jacobel, R. W., Anandakrishnan, S., Keisling, B. A., Craig, B. D., and Muto, A.: Ice sheet grounding zone stabilization due to till compaction, Geophys. Res. Lett., 40, 5406–5411, 700 https://doi.org/10.1002/2013GL057447, 2013. D., and Muto, A.: Ice sheet grounding zone stabilization due to till compaction, Geophys. Res. Lett., 40, 5406–5411, 700 https://doi.org/10.1002/2013GL057447, 2013. 29 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. Corr, H.: Processed airborne radio-echo sounding data from the GRADES-IMAGE survey covering the Evans and Rutford Ice Streams, and ice rises in the Ronne Ice Shelf, West Antarctica (2006/2007) (1.0), NERC EDS UK Polar Data Centre [data set], https://doi.org/10.5285/C7EA5697-87E3-4529-A0DD-089A2ED638FB, 2021. Corr, H.: Processed airborne radio-echo sounding data from the GRADES-IMAGE survey covering the Evans and Rutford Ice Streams, and ice rises in the Ronne Ice Shelf, West Antarctica (2006/2007) (1.0), NERC EDS UK Polar Data Centre [data set], https://doi.org/10.5285/C7EA5697-87E3-4529-A0DD-089A2ED638FB, 2021. Corr, H. F. J., Doake, C. S. M., Jenkins, A., and Vaughan, D. G.: Investigations of an “ice plain” in the mouth of Pine Island Glacier, Antarctica, J. Glaciol., 47, 51–57, https://doi.org/10.3189/172756501781832395, 2001. Corr, H. F. J., Doake, C. S. M., Jenkins, A., and Vaughan, D. G.: Investigations of an “ice plain” in the mouth of Pine Island Glacier, Antarctica, J. Glaciol., 47, 51–57, https://doi.org/10.3189/172756501781832395, 2001. Corr, H. F. J., Doake, C. S. M., Jenkins, A., and Vaughan, D. G.: Investigations of an “ice plain” in the mouth of Pine Island 705 Glacier, Antarctica, J. Glaciol., 47, 51–57, https://doi.org/10.3189/172756501781832395, 2001. Dawson, G. J. and Bamber, J. L.: Antarctic Grounding Line Mapping From CryoSat-2 Radar Altimetry, Geophys. Res. Lett., 44, 11886-11893, https://doi.org/10.1002/2017GL075589, 2017. Dawson, G. J. and Bamber, J. References B.: Sediment deposition at the modern grounding zone of Whillans Ice Stream, West Antarctica, Geophys. Res. Lett., 40, 3934–3939, 755 https://doi.org/10.1002/grl.50712, 2013b. Howard, S. L., Padman, L., and Erofeeva, S. Y.: CATS2008: Circum-Antarctic Tidal Simulation version 2008 (1), U.S. Antarctic Program (USAP) Data Center [code], https://doi.org/10.15784/601235, 2019. Howat, I., Morin, P., Porter, C., and Noh, M.-J.: The Reference Elevation Model of Antarctica, Version 1, Harvard Dataverse [data set], https://doi.org/10.7910/DVN/SAIK8B, 2018. 760 Horgan, H. J., Alley, R. B., Christianson, K., Jacobel, R. W., Anandakrishnan, S., Muto, A., Beem, L. H., and Siegfried, M. R.: Estuaries beneath ice sheets, Geology, 41, 1159–1162, https://doi.org/10.1130/G34654.1, 2013a. Horgan, H. J., Christianson, K., Jacobel, R. W., Anandakrishnan, S., and Alley, R. B.: Sediment deposition at the modern grounding zone of Whillans Ice Stream, West Antarctica, Geophys. Res. Lett., 40, 3934–3939, 755 https://doi.org/10.1002/grl.50712, 2013b. Howard, S. L., Padman, L., and Erofeeva, S. Y.: CATS2008: Circum-Antarctic Tidal Simulation version 2008 (1), U.S. Antarctic Program (USAP) Data Center [code], https://doi.org/10.15784/601235, 2019. Horgan, H. J., Alley, R. B., Christianson, K., Jacobel, R. W., Anandakrishnan, S., Muto, A., Beem, L. H., and Siegfried, M. R.: Estuaries beneath ice sheets, Geology, 41, 1159–1162, https://doi.org/10.1130/G34654.1, 2013a. Horgan, H. J., Christianson, K., Jacobel, R. W., Anandakrishnan, S., and Alley, R. B.: Sediment deposition at the modern grounding zone of Whillans Ice Stream, West Antarctica, Geophys. Res. Lett., 40, 3934–3939, 755 https://doi.org/10.1002/grl.50712, 2013b. Howard, S. L., Padman, L., and Erofeeva, S. Y.: CATS2008: Circum-Antarctic Tidal Simulation version 2008 (1), U.S. Antarctic Program (USAP) Data Center [code], https://doi.org/10.15784/601235, 2019. Howat, I., Morin, P., Porter, C., and Noh, M.-J.: The Reference Elevation Model of Antarctica, Version 1, Harvard Dataverse [data set], https://doi.org/10.7910/DVN/SAIK8B, 2018. 760 Howat, I., Morin, P., Porter, C., and Noh, M.-J.: The Reference Elevation Model of Antarctica, Version 1, Harvard Dataverse [data set] https://doi org/10 7910/DVN/SAIK8B 2018 60 Jenkins, A., Corr, H. F. J., Nicholls, K. W., Stewart, C. L., and Doake, C. S. M.: Interactions between ice and ocean observed with phase-sensitive radar near an Antarctic ice-shelf grounding line, J. Glaciol., 52, 325–346, https://doi.org/10.3189/172756506781828502, 2006. Johnson, M. R. and Smith, A. M.: Seabed topography under the southern and western Ronne Ice Shelf, derived from seismic surveys, Antarct. Sci., 9, 201–208, https://doi.org/10.1017/S0954102097000254, 1997. 765 Johnson, M. R. and Smith, A. References A.: Instantaneous Antarctic ice- sheet mass loss driven by thinning ice shelves. Geophys. Res. Lett., 46, 13903– 13909. https://doi.org/10.1029/2019GL085027, 2019. 745 Hogg, A. E., Shepherd, A., Gourmelen, N., and Engdahl, M.: Grounding line migration from 1992 to 2011 on Petermann Glacier, North-West Greenland, J. Glaciol., 62, 1104–1114, https://doi.org/10.1017/jog.2016.83, 2016. Hogg, A. E., Shepherd, A., Gilbert, L., Muir, A., and Drinkwater, M. R.: Mapping ice sheet grounding lines with CryoSat-2, Adv. Space Res., 62, 1191–1202, https://doi.org/10.1016/j.asr.2017.03.008, 2018. Gudmundsson, G. H.: Tides and the flow of Rutford Ice Stream, West Antarctica, J. Geophys. Res., 112, F04007, https://doi.org/10.1029/2006JF000731, 2007. Gudmundsson, G. H., Paolo, F. S., Adusumilli, S., and Fricker, H. A.: Instantaneous Antarctic ice- sheet mass loss driven by thinning ice shelves. Geophys. Res. Lett., 46, 13903– 13909. https://doi.org/10.1029/2019GL085027, 2019. 45 , , , , , , , y thinning ice shelves. Geophys. Res. Lett., 46, 13903– 13909. https://doi.org/10.1029/2019GL085027, 2019. 745 Hogg, A. E., Shepherd, A., Gourmelen, N., and Engdahl, M.: Grounding line migration from 1992 to 2011 on Petermann Glacier, North-West Greenland, J. Glaciol., 62, 1104–1114, https://doi.org/10.1017/jog.2016.83, 2016. Hogg, A. E., Shepherd, A., Gilbert, L., Muir, A., and Drinkwater, M. R.: Mapping ice sheet grounding lines with CryoSat-2, Adv. Space Res., 62, 1191–1202, https://doi.org/10.1016/j.asr.2017.03.008, 2018. Hogg, A. E., Shepherd, A., Gourmelen, N., and Engdahl, M.: Grounding line migration from 1992 to 2011 on Petermann Glacier, North-West Greenland, J. Glaciol., 62, 1104–1114, https://doi.org/10.1017/jog.2016.83, 2016. Hogg, A. E., Shepherd, A., Gourmelen, N., and Engdahl, M.: Grounding line migration from 1992 to 2011 on Petermann Glacier, North-West Greenland, J. Glaciol., 62, 1104–1114, https://doi.org/10.1017/jog.2016.83, 2016. Hogg, A. E., Shepherd, A., Gilbert, L., Muir, A., and Drinkwater, M. R.: Mapping ice sheet grounding lines with CryoSat-2, Adv. Space Res., 62, 1191–1202, https://doi.org/10.1016/j.asr.2017.03.008, 2018. Hogg, A. E., Shepherd, A., Gilbert, L., Muir, A., and Drinkwater, M. R.: Mapping ice sheet grounding lines with CryoSat-2, Adv. Space Res., 62, 1191–1202, https://doi.org/10.1016/j.asr.2017.03.008, 2018. Holdsworth, G.: Flexure of a Floating Ice Tongue, J. Glaciol., 8, 385–397, https://doi.org/10.3189/S0022143000026976, 750 1969. Holdsworth, G.: Flexure of a Floating Ice Tongue, J. Glaciol., 8, 385–397, https://doi.org/10.3189/S0022143000026976, 750 1969. Horgan, H. J., Alley, R. B., Christianson, K., Jacobel, R. W., Anandakrishnan, S., Muto, A., Beem, L. H., and Siegfried, M. R.: Estuaries beneath ice sheets, Geology, 41, 1159–1162, https://doi.org/10.1130/G34654.1, 2013a. Horgan, H. J., Christianson, K., Jacobel, R. W., Anandakrishnan, S., and Alley, R. References M.: Retreat of Pine Island Glacier controlled by marine ice-sheet instability, Nat. Clim. Change, 4, 117– 121, https://doi.org/10.1038/nclimate2094, 2014. Favier, L., Durand, G., Cornford, S. L., Gudmundsson, G. H., Gagliardini, O., Gillet-Chaulet, F., Zwinger, T., Payne, A. J., and Le Brocq, A. M.: Retreat of Pine Island Glacier controlled by marine ice-sheet instability, Nat. Clim. Change, 4, 117– 121, https://doi.org/10.1038/nclimate2094, 2014. Fricker, H. A. and Padman, L.: Ice shelf grounding zone structure from ICESat laser altimetry, Geophys. Res. Lett., 33, 730 https://doi.org/10.1029/2006GL026907, 2006. Fricker H A Coleman R Padman L Scambos T A Bohlander J and Brunt K M : Mapping the grounding zone of Fricker, H. A. and Padman, L.: Ice shelf grounding zone structure from ICESat laser altimetry, Geophys. Res. Lett., 33, 730 https://doi.org/10.1029/2006GL026907, 2006. Fricker, H. A., Coleman, R., Padman, L., Scambos, T. A., Bohlander, J., and Brunt, K. M.: Mapping the grounding zone of the Amery Ice Shelf, East Antarctica using InSAR, MODIS and ICESat, Antarct. Sci., 21, 515–532, https://doi.org/10.1017/S095410200999023X, 2009. Fricker, H. A., Coleman, R., Padman, L., Scambos, T. A., Bohlander, J., and Brunt, K. M.: Mapping the grounding zone of the Amery Ice Shelf, East Antarctica using InSAR, MODIS and ICESat, Antarct. Sci., 21, 515–532, https://doi.org/10.1017/S095410200999023X, 2009. Friedl, P., Weiser, F., Fluhrer, A., and Braun, M. H.: Remote sensing of glacier and ice sheet grounding lines: A review, 735 Earth-Sci. Rev., 201, 102948, https://doi.org/10.1016/j.earscirev.2019.102948, 2020. Goldberg, D. N., Gourmelen, N., Kimura, S., Millan, R., and Snow, K.: How Accurately Should We Model Ice Shelf Melt Rates?, Geophys. Res. Lett., 46, 189–199, https://doi.org/10.1029/2018GL080383, 2019. 30 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. Graham, A. G. C., Wåhlin, A., Hogan, K. A., Nitsche, F. O., Heywood, K. J., Totten, R. L., Smith, J. A., Hillenbrand, C.-D., Simkins, L. M., Anderson, J. B., Wellner, J. S., and Larter, R. D.: Rapid retreat of Thwaites Glacier in the pre-satellite era, 0 Nat. Geosci., https://doi.org/10.1038/s41561-022-01019-9, 2022. Simkins, L. M., Anderson, J. B., Wellner, J. S., and Larter, R. D.: Rapid retreat of Thwaites Glacier in the pre-satellite era, 740 Nat. Geosci., https://doi.org/10.1038/s41561-022-01019-9, 2022. Gudmundsson, G. H.: Tides and the flow of Rutford Ice Stream, West Antarctica, J. Geophys. Res., 112, F04007, https://doi.org/10.1029/2006JF000731, 2007. Gudmundsson, G. H., Paolo, F. S., Adusumilli, S., and Fricker, H. References L.: Mapping the grounding zone of Larsen C Ice Shelf, Antarctica, from 775 ICESat-2 laser altimetry, The Cryosphere, 14, 3629–3643, https://doi.org/10.5194/tc-14-3629-2020, 2020. Li, T., Dawson, G. J., Chuter, S. J., and Bamber, J. L.: Mapping the grounding zone of Larsen C Ice Shelf, Antarctica, from 775 ICESat-2 laser altimetry, The Cryosphere, 14, 3629–3643, https://doi.org/10.5194/tc-14-3629-2020, 2020. Li, T., Dawson, G. J., Chuter, S. J., and Bamber, J. L.: A high-resolution Antarctic grounding zone product from ICESat-2 laser altimetry, Earth Syst. Sci. Data, 14, 535–557, https://doi.org/10.5194/essd-14-535-2022, 2022a. Li, T., Dawson, G. J., Chuter, S. J., and Bamber, J. L.: Grounding line retreat and tide-modulated ocean channels at Moscow University and Totten Glacier ice shelves, East Antarctica, The Cryosphere Discuss. [preprint], 1–32, 780 https://doi.org/10.5194/tc-2022-129, in review, 2022b. Li, T., Dawson, Geoffrey J., Chuter, Stephen J., and Bamber, Jonathan L.: ICESat-2 L3 Grounding Zone for Antarctic Ice Shelves, Version 1, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi org/10 5067/RI67B92708M9 2022c Li, T., Dawson, G. J., Chuter, S. J., and Bamber, J. L.: A high-resolution Antarctic grounding zone product from ICESat-2 laser altimetry, Earth Syst. Sci. Data, 14, 535–557, https://doi.org/10.5194/essd-14-535-2022, 2022a. Li, T., Dawson, G. J., Chuter, S. J., and Bamber, J. L.: Grounding line retreat and tide-modulated ocean channels at Moscow University and Totten Glacier ice shelves, East Antarctica, The Cryosphere Discuss. [preprint], 1–32, 780 https://doi.org/10.5194/tc-2022-129, in review, 2022b. Li, T., Dawson, G. J., Chuter, S. J., and Bamber, J. L.: Grounding line retreat and tide-modulated ocean channels at Moscow University and Totten Glacier ice shelves, East Antarctica, The Cryosphere Discuss. [preprint], 1–32, 780 https://doi.org/10.5194/tc-2022-129, in review, 2022b. Li, T., Dawson, Geoffrey J., Chuter, Stephen J., and Bamber, Jonathan L.: ICESat-2 L3 Grounding Zone for Antarctic Ice Shelves, Version 1, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/RI67B92708M9, 2022c. Li, T., Dawson, Geoffrey J., Chuter, Stephen J., and Bamber, Jonathan L.: ICESat-2 L3 Grounding Zone for Antarctic Ice Shelves, Version 1, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/RI67B92708M9, 2022c. MacGregor, J. A., Anandakrishnan, S., Catania, G. A., and Winebrenner, D. P.: The grounding zone of the Ross Ice Shelf, 785 West Antarctica, from ice-penetrating radar, J. Glaciol., 57, 917–928, https://doi.org/10.3189/002214311798043780, 2011. MacGregor, J. A., Anandakrishnan, S., Catania, G. A., and Winebrenner, D. References M.: Seabed topography under the southern and western Ronne Ice Shelf, derived from seismic s r e s Antarct Sci 9 201 208 https://doi org/10 1017/S0954102097000254 1997 765 , , p g p y , surveys, Antarct. Sci., 9, 201–208, https://doi.org/10.1017/S0954102097000254, 1997. 765 Joughin, I., Smith, B. E., and Holland, D. M.: Sensitivity of 21st century sea level to ocean-induced thinning of Pine Island Glacier, Antarctica, Geophys. Res. Lett., 37, L20502, https://doi.org/10.1029/2010GL044819, 2010. Joughin, I., Alley, R. B., and Holland, D. M.: Ice-Sheet Response to Oceanic Forcing, Science, 338, 1172–1176, https://doi.org/10.1126/science.1226481, 2012. y , , , , p g , Joughin, I., Smith, B. E., and Holland, D. M.: Sensitivity of 21st century sea level to ocean-induced thinning of Pine Island Glacier, Antarctica, Geophys. Res. Lett., 37, L20502, https://doi.org/10.1029/2010GL044819, 2010. Joughin, I., Smith, B. E., and Holland, D. M.: Sensitivity of 21st century sea level to ocean-induced thinning of Pine Island Glacier, Antarctica, Geophys. Res. Lett., 37, L20502, https://doi.org/10.1029/2010GL044819, 2010. Joughin, I., Alley, R. B., and Holland, D. M.: Ice-Sheet Response to Oceanic Forcing, Science, 338, 1172–1176, https://doi.org/10.1126/science.1226481, 2012. Joughin, I., Alley, R. B., and Holland, D. M.: Ice-Sheet Response to Oceanic Forcing, Science, 338, 1172–1176, https://doi.org/10.1126/science.1226481, 2012. King, M. A., Padman, L., Nicholls, K., Clarke, P. J., Gudmundsson, G. H., Kulessa, B., and Shepherd, A.: Ocean tides in the 770 Weddell Sea: New observations on the Filchner-Ronne and Larsen C ice shelves and model validation, J. of Geophys. Res- Oceans, 116, https://doi.org/10.1029/2011JC006949, 2011. King, M. A., Padman, L., Nicholls, K., Clarke, P. J., Gudmundsson, G. H., Kulessa, B., and Shepherd, A.: Ocean tides in the 770 Weddell Sea: New observations on the Filchner-Ronne and Larsen C ice shelves and model validation, J. of Geophys. Res- Oceans, 116, https://doi.org/10.1029/2011JC006949, 2011. Konrad, H., Shepherd, A., Gilbert, L., Hogg, A. E., McMillan, M., Muir, A., and Slater, T.: Net retreat of Antarctic glacier grounding lines, Nat. Geosci., 11, 258–262, https://doi.org/10.1038/s41561-018-0082-z, 2018. Konrad, H., Shepherd, A., Gilbert, L., Hogg, A. E., McMillan, M., Muir, A., and Slater, T.: Net retreat of Antarctic glacier grounding lines, Nat. Geosci., 11, 258–262, https://doi.org/10.1038/s41561-018-0082-z, 2018. 31 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. Li, T., Dawson, G. J., Chuter, S. J., and Bamber, J. References P.: The grounding zone of the Ross Ice Shelf, 785 West Antarctica, from ice-penetrating radar, J. Glaciol., 57, 917–928, https://doi.org/10.3189/002214311798043780, 2011. Magruder, L., Brunt, K., Neumann, T., Klotz, B., and Alonzo, M.: Passive Ground‐Based Optical Techniques for Monitoring the On‐Orbit ICESat‐2 Altimeter Geolocation and Footprint Diameter, Earth and Space Science, 8, https://doi.org/10.1029/2020EA001414, 2021. Magruder, L., Brunt, K., Neumann, T., Klotz, B., and Alonzo, M.: Passive Ground‐Based Optical Techniques for Monitoring the On‐Orbit ICESat‐2 Altimeter Geolocation and Footprint Diameter, Earth and Space Science, 8, https://doi.org/10.1029/2020EA001414, 2021. Makinson, K., Holland, P. R., Jenkins, A., Nicholls, K. W., and Holland, D. M.: Influence of tides on melting and freezing 790 beneath Filchner-Ronne Ice Shelf, Antarctica, Geophys. Res. Lett., 38, L06601, https://doi.org/10.1029/2010GL046462, 2011. Makinson, K., King, M. A., Nicholls, K. W., and Hilmar Gudmundsson, G.: Diurnal and semidiurnal tide-induced lateral movement of Ronne Ice Shelf, Antarctica, Geophys. Res. Lett., 39, L06601, https://doi.org/10.1029/2012GL051636, 2012. Makinson, K., Holland, P. R., Jenkins, A., Nicholls, K. W., and Holland, D. M.: Influence of tides on melting and freezing 790 beneath Filchner-Ronne Ice Shelf, Antarctica, Geophys. Res. Lett., 38, L06601, https://doi.org/10.1029/2010GL046462, 2011. Makinson, K., King, M. A., Nicholls, K. W., and Hilmar Gudmundsson, G.: Diurnal and semidiurnal tide-induced lateral movement of Ronne Ice Shelf, Antarctica, Geophys. Res. Lett., 39, L06601, https://doi.org/10.1029/2012GL051636, 2012. Markus, T., Neumann, T., Martino, A., Abdalati, W., Brunt, K., Csatho, B., Farrell, S., Fricker, H., Gardner, A., Harding, D., 795 Jasinski, M., Kwok, R., Magruder, L., Lubin, D., Luthcke, S., Morison, J., Nelson, R., Neuenschwander, A., Palm, S., Popescu, S., Shum, C., Schutz, B. E., Smith, B., Yang, Y., and Zwally, J.: The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2): Science requirements, concept, and implementation, Remote Sens. of Environ., 190, 260–273, https://doi.org/10.1016/j.rse.2016.12.029, 2017. Milillo, P., Rignot, E., Mouginot, J., Scheuchl, B., Morlighem, M., Li, X., and Salzer, J. T.: On the Short-term Grounding 800 Zone Dynamics of Pine Island Glacier, West Antarctica, Observed With COSMO-SkyMed Interferometric Data: PIG Grounding Line Dynamics, Geophys. Res. Lett., 44, 10,436-10,444, https://doi.org/10.1002/2017GL074320, 2017. Minchew, B. M., Simons, M., Riel, B., and Milillo, P.: Tidally induced variations in vertical and horizontal motion on Rutford Ice Stream, West Antarctica, inferred from remotely sensed observations, J. Geophys. Res-Earth, 122, 167–190, Milillo, P., Rignot, E., Mouginot, J., Scheuchl, B., Morlighem, M., Li, X., and Salzer, J. References J., Markus, T., Bae, S., Bock, M. R., Brenner, A. C., Brunt, K. M., Cavanaugh, J., Fernandes, S. T., Hancock, D. W., Harbeck, K., Lee, J., Kurtz, N. T., Luers, P. J., Luthcke, S. B., Magruder, L., Pennington, T. A., Ramos-Izquierdo, L., Rebold, T., Skoog, J., and Thomas, T. C.: The Ice, Cloud, and Land Elevation Satellite – 2 mission: A global geolocated photon product derived from the Advanced Topographic Laser Altimeter System, Remote Sens. of 820 Environ., 233, 111325, https://doi.org/10.1016/j.rse.2019.111325, 2019. Nicholls, K. W. and Østerhus, S.: Interannual variability and ventilation timescales in the ocean cavity beneath Filchner- Ronne Ice Shelf, Antarctica, J. Geophys. Res., 109, C04014, https://doi.org/10.1029/2003JC002149, 2004. Padman, L., Fricker, H. A., Coleman, R., Howard, S., and Erofeeva, L.: A new tide model for the Antarctic ice shelves and A f Gl i l 34 247 254 htt //d i /10 3189/172756402781817752 2002 825 Ramos Izquierdo, L., Rebold, T., Skoog, J., and Thomas, T. C.: The Ice, Cloud, and Land Elevation Satellite 2 mission: A global geolocated photon product derived from the Advanced Topographic Laser Altimeter System, Remote Sens. of 820 Environ., 233, 111325, https://doi.org/10.1016/j.rse.2019.111325, 2019. Nicholls, K. W. and Østerhus, S.: Interannual variability and ventilation timescales in the ocean cavity beneath Filchner- Ronne Ice Shelf, Antarctica, J. Geophys. Res., 109, C04014, https://doi.org/10.1029/2003JC002149, 2004. Padman, L., Fricker, H. A., Coleman, R., Howard, S., and Erofeeva, L.: A new tide model for the Antarctic ice shelves and seas, Ann. of Glaciol., 34, 247–254, https://doi.org/10.3189/172756402781817752, 2002. 825 seas, Ann. of Glaciol., 34, 247–254, https://doi.org/10.3189/172756402781817752, 2002. 825 Padman, L., Siegfried, M. R., and Fricker, H. A.: Ocean Tide Influences on the Antarctic and Greenland Ice Sheets, Rev. Geophys., 56, 142–184, https://doi.org/10.1002/2016RG000546, 2018. Park, J. W., Gourmelen, N., Shepherd, A., Kim, S. W., Vaughan, D. G., and Wingham, D. J.: Sustained retreat of the Pine Island Glacier, Geophys. Res. Lett., 40, 2137–2142, https://doi.org/10.1002/grl.50379, 2013. Padman, L., Siegfried, M. R., and Fricker, H. A.: Ocean Tide Influences on the Antarctic and Greenland Ice Sheets, Rev. Geophys., 56, 142–184, https://doi.org/10.1002/2016RG000546, 2018. Park, J. W., Gourmelen, N., Shepherd, A., Kim, S. W., Vaughan, D. G., and Wingham, D. J.: Sustained retreat of the Pine Island Glacier, Geophys. Res. Lett., 40, 2137–2142, https://doi.org/10.1002/grl.50379, 2013. Reeh, N., Mayer, C., Olesen, O. B., Christensen, E. L., and Thomsen, H. H.: Tidal movement of Nioghalvfjerdsfjorden 830 glacier, northeast Greenland: observations and modelling, Ann. Glaciol., 31, 111–117, https://doi.org/10.3189/172756400781820408, 2000. References T.: On the Short-term Grounding 800 Zone Dynamics of Pine Island Glacier, West Antarctica, Observed With COSMO-SkyMed Interferometric Data: PIG Grounding Line Dynamics, Geophys. Res. Lett., 44, 10,436-10,444, https://doi.org/10.1002/2017GL074320, 2017. https://doi.org/10.1002/2016JF003971, 2017. 805 Moholdt, G., Padman, L., and Fricker, H. A.: Basal mass budget of Ross and Filchner-Ronne ice shelves, Antarctica, derived from Lagrangian analysis of ICESat altimetry: Ice shelf basal melting from altimetry, J. Geophys. Res-Earth, 119, 2361– 2380, https://doi.org/10.1002/2014JF003171, 2014. Mosbeux, C., Padman, L., Klein, E., Bromirski, P. B., and Fricker, H. A.: Seasonal variability in Antarctic ice shelf velocities forced by sea surface height variations, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2022-153, 810 in review, 2022. https://doi.org/10.1002/2016JF003971, 2017. 805 Moholdt, G., Padman, L., and Fricker, H. A.: Basal mass budget of Ross and Filchner-Ronne ice shelves, Antarctica, derived from Lagrangian analysis of ICESat altimetry: Ice shelf basal melting from altimetry, J. Geophys. Res-Earth, 119, 2361– 2380, https://doi.org/10.1002/2014JF003171, 2014. Mosbeux, C., Padman, L., Klein, E., Bromirski, P. B., and Fricker, H. A.: Seasonal variability in Antarctic ice shelf velocities forced by sea surface height variations, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2022-153, 810 in review, 2022. 32 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. Mueller, R. D., Padman, L., Dinniman, M. S., Erofeeva, S. Y., Fricker, H. A., and King, M. A.: Impact of tide-topography interactions on basal melting of Larsen C Ice Shelf, Antarctica, J. Geophys. Res., 117, C05005, https://doi.org/10.1029/2011JC007263, 2012. 815 Naughten, K. A., De Rydt, J., Rosier, S. H. R., Jenkins, A., Holland, P. R., and Ridley, J. K.: Two-timescale response of a large Antarctic ice shelf to climate change, Nat. Commun., 12, 1991, https://doi.org/10.1038/s41467-021-22259-0, 2021. Naughten, K. A., De Rydt, J., Rosier, S. H. R., Jenkins, A., Holland, P. R., and Ridley, J. K.: Two-timescale response of a 815 large Antarctic ice shelf to climate change, Nat. Commun., 12, 1991, https://doi.org/10.1038/s41467-021-22259-0, 2021. Neumann, T. A., Martino, A. J., Markus, T., Bae, S., Bock, M. R., Brenner, A. C., Brunt, K. M., Cavanaugh, J., Fernandes, S. T., Hancock, D. W., Harbeck, K., Lee, J., Kurtz, N. T., Luers, P. J., Luthcke, S. B., Magruder, L., Pennington, T. A., Ramos-Izquierdo, L., Rebold, T., Skoog, J., and Thomas, T. C.: The Ice, Cloud, and Land Elevation Satellite – 2 mission: A Neumann, T. A., Martino, A. References J.: Steep reverse bed slope at the grounding line of the Weddell Sea sector in West Antarctica, Nat. 860 Geosci., 5, 393–396, https://doi.org/10.1038/ngeo1468, 2012. Sayag, R. and Worster, M. G.: Elastic dynamics and tidal migration of grounding lines modify subglacial lubrication and melting, Geophys. Res. Lett., 40, 5877–5881, https://doi.org/10.1002/2013GL057942, 2013. Scambos, T. A., Haran, T. M., Fahnestock, M. A., Painter, T. H., and Bohlander, J.: MODIS-based Mosaic of Antarctica (MOA) data sets: Continent-wide surface morphology and snow grain size, Remote Sens. of Environ., 111, 242–257, 865 https://doi.org/10.1016/j.rse.2006.12.020, 2007. Scambos, T. A., Haran, T. M., Fahnestock, M. A., Painter, T. H., and Bohlander, J.: MODIS-based Mosaic of Antarctica (MOA) data sets: Continent-wide surface morphology and snow grain size, Remote Sens. of Environ., 111, 242–257, 865 https://doi.org/10.1016/j.rse.2006.12.020, 2007. Scheick, J. et al., (2019). icepyx: Python tools for obtaining and working with ICESat-2 data [data set], https://github.com/icesat2py/icepyx., 2019. S h l M Ri E d M A l D R E h l di i l f i h lf h J Gl i l 47 71 77 Scambos, T. A., Haran, T. M., Fahnestock, M. A., Painter, T. H., and Bohlander, J.: MODIS based Mosaic of Antarctica (MOA) data sets: Continent-wide surface morphology and snow grain size, Remote Sens. of Environ., 111, 242–257, 865 https://doi.org/10.1016/j.rse.2006.12.020, 2007. p g j , Scheick, J. et al., (2019). icepyx: Python tools for obtaining and working with ICESat-2 data [data set], https://github.com/icesat2py/icepyx., 2019. Schmeltz, M., Rignot, E., and MacAyeal, D. R.: Ephemeral grounding as a signal of ice-shelf change, J. Glaciol., 47, 71–77, https://doi.org/10.3189/172756501781832502, 2001. 870 , , g , , y , p g g g g , , , , https://doi.org/10.3189/172756501781832502, 2001. 870 Schmeltz, M., Rignot, E., and MacAyeal, D.: Tidal flexure along ice-sheet margins: comparison of InSAR with an elastic- plate model, Ann. Glaciol., 34, 202–208, https://doi.org/10.3189/172756402781818049, 2002. Schmidt, B. E., Washam, P., Davis, P. E. D., Nicholls, K. W., Holland, D. M., Lawrence, J. D., Riverman, K. L., Smith, J. A., Spears, A., Dichek, D. J. G., Mullen, A. D., Clyne, E., Yeager, B., Anker, P., Meister, M. R., Hurwitz, B. C., Quartini, E. Schmeltz, M., Rignot, E., and MacAyeal, D.: Tidal flexure along ice-sheet margins: comparison of InSAR with an elastic- plate model, Ann. Glaciol., 34, 202–208, https://doi.org/10.3189/172756402781818049, 2002. Schmidt, B. E., Washam, P., Davis, P. E. D., Nicholls, K. W., Holland, D. M., Lawrence, J. D., Riverman, K. References Reeh, N., Mayer, C., Olesen, O. B., Christensen, E. L., and Thomsen, H. H.: Tidal movement of Nioghalvfjerdsfjorden 830 glacier, northeast Greenland: observations and modelling, Ann. Glaciol., 31, 111–117, https://doi.org/10.3189/172756400781820408, 2000. Reeh, N., Christensen, E. L., Mayer, C., and Olesen, O. B.: Tidal bending of glaciers: a linear viscoelastic approach, Ann. Glaciol., 37, 83–89, https://doi.org/10.3189/172756403781815663, 2003. Reeh, N., Christensen, E. L., Mayer, C., and Olesen, O. B.: Tidal bending of glaciers: a linear viscoelastic approach, Ann. Glaciol., 37, 83–89, https://doi.org/10.3189/172756403781815663, 2003. Rignot, E.: Tidal motion, ice velocity and melt rate of Petermann Gletscher, Greenland, measured from radar interferometry, 835 J. Glaciol., 42, 476–485, https://doi.org/10.3189/S0022143000003464, 1996. Rignot, E.: Tidal motion, ice velocity and melt rate of Petermann Gletscher, Greenland, measured from radar interferometry, 835 J. Glaciol., 42, 476–485, https://doi.org/10.3189/S0022143000003464, 1996. Rignot, E., Mouginot, J., and Scheuchl, B.: Antarctic grounding line mapping from differential satellite radar interferometry, Geophys. Res. Lett., 38, https://doi.org/10.1029/2011GL047109, 2011. Rignot, E., Mouginot, J., and Scheuchl, B.: Antarctic grounding line mapping from differential satellite radar interferometry, Geophys. Res. Lett., 38, https://doi.org/10.1029/2011GL047109, 2011. Rignot, E., Mouginot, J., Morlighem, M., Seroussi, H., and Scheuchl, B.: Widespread, rapid grounding line retreat of Pine Island, Thwaites, Smith, and Kohler glaciers, West Antarctica, from 1992 to 2011, Geophys. Res. Lett., 41, 3502–3509, 840 https://doi.org/10.1002/2014GL060140, 2014. Ri t E M i t J i d S h hl B ME SURE A t ti G di Li f Diff ti l S t llit R d Rignot, E., Mouginot, J., Morlighem, M., Seroussi, H., and Scheuchl, B.: Widespread, rapid grounding line retreat of Pine Island, Thwaites, Smith, and Kohler glaciers, West Antarctica, from 1992 to 2011, Geophys. Res. Lett., 41, 3502–3509, 840 https://doi.org/10.1002/2014GL060140, 2014. Rignot, E., Mouginot, Jeremie, and Scheuchl, B.: MEaSUREs Antarctic Grounding Line from Differential Satellite Radar Interferometry, Version 2, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/IKBWW4RYHF1Q, 2016. Rignot, E., Mouginot, Jeremie, and Scheuchl, B.: MEaSUREs Antarctic Grounding Line from Differential Satellite Radar Interferometry, Version 2, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/IKBWW4RYHF1Q, 2016. Rignot, E., Mouginot, Jeremie, and Scheuchl, B.: MEaSUREs InSAR-Based Antarctica Ice Velocity Map, Version 2, 845 NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/D7GK8F5J8M8R, 2017. 33 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. References CC BY 4.0 License. Robel, A. A., Tsai, V. C., Minchew, B., and Simons, M.: Tidal modulation of ice shelf buttressing stresses, Ann. Glaciol., 58, 12–20, https://doi.org/10.1017/aog.2017.22, 2017. Robel, A. A., Wilson, E., and Seroussi, H.: Layered seawater intrusion and melt under grounded ice, The Cryosphere, 16, 0 451–469, https://doi.org/10.5194/tc-16-451-2022, 2022. Robel, A. A., Wilson, E., and Seroussi, H.: Layered seawater intrusion and melt under grounded ice, The Cryosphere, 16, 850 451–469, https://doi.org/10.5194/tc-16-451-2022, 2022. Rosier, S. H. R. and Gudmundsson, G. H.: Tidal controls on the flow of ice streams, Geophys. Res. Lett., 43, 4433–4440, https://doi.org/10.1002/2016GL068220, 2016. Rosier, S. H. R. and Gudmundsson, G. H.: Tidal controls on the flow of ice streams, Geophys. Res. Lett., 43, 4433–4440, https://doi.org/10.1002/2016GL068220, 2016. Rosier, S. H. R. and Gudmundsson, G. H.: Exploring mechanisms responsible for tidal modulation in flow of the Filchner– Ronne Ice Shelf, The Cryosphere, 14, 17–37, https://doi.org/10.5194/tc-14-17-2020, 2020. 855 Ronne Ice Shelf, The Cryosphere, 14, 17–37, https://doi.org/10.5194/tc-14-17-2020, 2020. 855 Rosier, S. H. R., Gudmundsson, G. H., and Green, J. A. M.: Temporal variations in the flow of a large Antarctic ice stream controlled by tidally induced changes in the subglacial water system, The Cryosphere, 9, 1649–1661, https://doi.org/10.5194/tc-9-1649-2015, 2015. Rosier, S. H. R., Gudmundsson, G. H., and Green, J. A. M.: Temporal variations in the flow of a large Antarctic ice stream controlled by tidally induced changes in the subglacial water system, The Cryosphere, 9, 1649–1661, https://doi.org/10.5194/tc-9-1649-2015, 2015. Ross, N., Bingham, R. G., Corr, H. F. J., Ferraccioli, F., Jordan, T. A., Le Brocq, A., Rippin, D. M., Young, D., Blankenship, D. D., and Siegert, M. J.: Steep reverse bed slope at the grounding line of the Weddell Sea sector in West Antarctica, Nat. 860 Geosci., 5, 393–396, https://doi.org/10.1038/ngeo1468, 2012. Ross, N., Bingham, R. G., Corr, H. F. J., Ferraccioli, F., Jordan, T. A., Le Brocq, A., Rippin, D. M., Young, D., Blankenship, D. D., and Siegert, M. J.: Steep reverse bed slope at the grounding line of the Weddell Sea sector in West Antarctica, Nat. 860 Geosci., 5, 393–396, https://doi.org/10.1038/ngeo1468, 2012. Sayag, R. and Worster, M. G.: Elastic dynamics and tidal migration of grounding lines modify subglacial lubrication and melting, Geophys. Res. Lett., 40, 5877–5881, https://doi.org/10.1002/2013GL057942, 2013. , , g , , , , , , , , q, , pp , , g, , p, D. D., and Siegert, M. References M.: The use of tiltmeters to study the dynamics of Antarctic ice-shelf grounding lines, J. Glaciol., 37, 51–58, https://doi.org/10.3189/S0022143000042799, 1991. Smith, B., Fricker, H. A., Holschuh, N., Gardner, A. S., Adusumilli, S., Brunt, K. M., Csathó, B., Harbeck, K., Huth, A., Neumann, T., Nilsson, J., and Siegfried, M. R.: Land ice height-retrieval algorithm for NASA’s ICESat-2 photon-counting laser altimeter, Remote Sens. of Environ., 233, 111352, https://doi.org/10.1016/j.rse.2019.111352, 2019. 890 S i h i k A G d A Si f i d Ad illi S C hó l h h il l Smith, A. M.: The use of tiltmeters to study the dynamics of Antarctic ice-shelf grounding lines, J. Glaciol., 37, 51–58, https://doi.org/10.3189/S0022143000042799, 1991. Smith, A. M.: The use of tiltmeters to study the dynamics of Antarctic ice-shelf grounding lines, J. Glaciol., 37, 51–58, https://doi.org/10.3189/S0022143000042799, 1991. Smith B Fricker H A Holschuh N Gardner A S Adusumilli S Brunt K M Csathó B Harbeck K Huth A Smith, B., Fricker, H. A., Holschuh, N., Gardner, A. S., Adusumilli, S., Brunt, K. M., Csathó, B., Harbeck, K., Huth, A., Neumann, T., Nilsson, J., and Siegfried, M. R.: Land ice height-retrieval algorithm for NASA’s ICESat-2 photon-counting laser altimeter, Remote Sens. of Environ., 233, 111352, https://doi.org/10.1016/j.rse.2019.111352, 2019. 90 890 , , , , p g j , Smith, B., Fricker, H. A., Gardner, A., Siegfried, M. R., Adusumilli, S., Csathó, B. M., Holschuh, N., Nilsson, J., Paolo, F. S., and the ICESat-2 Science Team: ATLAS/ICESat-2 L3A Land Ice Height, Version 5. Boulder Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/ATLAS/ATL06.005, 2021. Stephenson, S. N., Doake, C. S. M., and Horsfall, J. A. C.: Tidal flexure of ice shelves measured by tiltmeter, Nature, 282, 895 496–497, https://doi.org/10.1038/282496a0, 1979. Sutterley, T. C., Markus, T., Neumann, T. A., van den Broeke, M., van Wessem, J. M., and Ligtenberg, S. R. M.: Antarctic ice shelf thickness change from multimission lidar mapping, The Cryosphere, 13, 1801–1817, https://doi.org/10.5194/tc-13- 1801-2019, 2019. Stephenson, S. N., Doake, C. S. M., and Horsfall, J. A. C.: Tidal flexure of ice shelves measured by tiltmeter, Nature, 282, 895 496–497, https://doi.org/10.1038/282496a0, 1979. Sutterley, T. C., Markus, T., Neumann, T. A., van den Broeke, M., van Wessem, J. M., and Ligtenberg, S. R. M.: Antarctic ice shelf thickness change from multimission lidar mapping, The Cryosphere, 13, 1801–1817, https://doi.org/10.5194/tc-13- 1801-2019, 2019. Thomas, R. References L., Smith, J. A., Spears, A., Dichek, D. J. G., Mullen, A. D., Clyne, E., Yeager, B., Anker, P., Meister, M. R., Hurwitz, B. C., Quartini, E. S., Bryson, F. E., Basinski-Ferris, A., Thomas, C., Wake, J., Vaughan, D. G., Anandakrishnan, S., Rignot, E., Paden, J., and 875 Makinson, K.: Heterogeneous melting near the Thwaites Glacier grounding line, Nature, 614, 471–478, https://doi.org/10.1038/s41586-022-05691-0, 2023. Schoof, C.: Ice sheet grounding line dynamics: Steady states, stability, and hysteresis, J. Geophys. Res., 112, F03S28, https://doi.org/10.1029/2006JF000664, 2007. Schoof, C.: Ice sheet grounding line dynamics: Steady states, stability, and hysteresis, J. Geophys. Res., 112, F03S28, https://doi.org/10.1029/2006JF000664, 2007. Schoof, C.: Marine ice sheet dynamics. Part 2. A Stokes flow contact problem, J. Fluid Mech., 679, 122–155, 880 https://doi.org/10.1017/jfm.2011.129, 2011. Schoof, C.: Marine ice sheet dynamics. Part 2. A Stokes flow contact problem, J. Fluid Mech., 679, 122–155, 880 https://doi.org/10.1017/jfm.2011.129, 2011. Schutz, B. E., Zwally, H. J., Shuman, C. A., Hancock, D., and DiMarzio, J. P.: Overview of the ICESat Mission, Geophys. Res. Lett., 32, L21S01, https://doi.org/10.1029/2005GL024009, 2005. Schutz, B. E., Zwally, H. J., Shuman, C. A., Hancock, D., and DiMarzio, J. P.: Overview of the ICESat Mission, Geophys. Res. Lett., 32, L21S01, https://doi.org/10.1029/2005GL024009, 2005. 34 https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. https://doi.org/10.5194/tc-2022-265 Preprint. Discussion started: 24 February 2023 c⃝Author(s) 2023. CC BY 4.0 License. Siegert, M., Ross, N., Corr, H., Kingslake, J., and Hindmarsh, R.: Late Holocene ice-flow reconfiguration in the Weddell Sea sector of West Antarctica, Quaternary Sci. Rev., 78, 98–107, https://doi.org/10.1016/j.quascirev.2013.08.003, 2013. 885 sector of West Antarctica, Quaternary Sci. Rev., 78, 98 107, https://doi.org/10.1016/j.quascirev.2013.08.003, 2013. 885 Smith, A. M.: The use of tiltmeters to study the dynamics of Antarctic ice-shelf grounding lines, J. Glaciol., 37, 51–58, https://doi.org/10.3189/S0022143000042799, 1991. Smith, B., Fricker, H. A., Holschuh, N., Gardner, A. S., Adusumilli, S., Brunt, K. M., Csathó, B., Harbeck, K., Huth, A., Neumann, T., Nilsson, J., and Siegfried, M. R.: Land ice height-retrieval algorithm for NASA’s ICESat-2 photon-counting laser altimeter, Remote Sens. of Environ., 233, 111352, https://doi.org/10.1016/j.rse.2019.111352, 2019. 890 Smith, B., Fricker, H. A., Gardner, A., Siegfried, M. R., Adusumilli, S., Csathó, B. M., Holschuh, N., Nilsson, J., Paolo, F. S., and the ICESat-2 Science Team: ATLAS/ICESat-2 L3A Land Ice Height, Version 5. Boulder Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], Smith, A. References H.: The Dynamics of Marine Ice Sheets, J. Glaciol., 24, 167–177, https://doi.org/10.1017/S0022143000014726, 900 1979. Thompson, J., Simons, M., and Tsai, V. C.: Modeling the elastic transmission of tidal stresses to great distances inland in channelized ice streams, The Cryosphere, 8, 2007–2029, https://doi.org/10.5194/tc-8-2007-2014, 2014. T i V C d G d d G H A i d d l f tid ll d l t d di li i ti J Gl i l 61 Thomas, R. H.: The Dynamics of Marine Ice Sheets, J. Glaciol., 24, 167–177, https://doi.org/10.1017/S0022143000014726, 900 1979. 1979. Thompson, J., Simons, M., and Tsai, V. C.: Modeling the elastic transmission of tidal stresses to great distances inland in channelized ice streams, The Cryosphere, 8, 2007–2029, https://doi.org/10.5194/tc-8-2007-2014, 2014. Thompson, J., Simons, M., and Tsai, V. C.: Modeling the elastic transmission of tidal stresses to great distances inland in channelized ice streams, The Cryosphere, 8, 2007–2029, https://doi.org/10.5194/tc-8-2007-2014, 2014. Tsai, V. C. and Gudmundsson, G. H.: An improved model for tidally modulated grounding-line migration, J. Glaciol., 61, 216–222, https://doi.org/10.3189/2015JoG14J152, 2015. 905 , , p y g g g , , , 216–222, https://doi.org/10.3189/2015JoG14J152, 2015. 905 Vaughan, D. G.: Tidal flexure at ice shelf margins, J. Geophys. Res-Sol Ea., 100, 6213–6224, https://doi.org/10.1029/94JB02467, 1995. Walker, R. T., Parizek, B. R., Alley, R. B., Anandakrishnan, S., Riverman, K. L., and Christianson, K.: Ice-shelf tidal flexure and subglacial pressure variations, Earth Planet. Sc. Lett., 361, 422–428, https://doi.org/10.1016/j.epsl.2012.11.008, 2013. Vaughan, D. G.: Tidal flexure at ice shelf margins, J. Geophys. Res-Sol Ea., 100, 6213–6224, https://doi.org/10.1029/94JB02467, 1995. Walker, R. T., Parizek, B. R., Alley, R. B., Anandakrishnan, S., Riverman, K. L., and Christianson, K.: Ice-shelf tidal flexure and subglacial pressure variations, Earth Planet. Sc. Lett., 361, 422–428, https://doi.org/10.1016/j.epsl.2012.11.008, 2013. Warburton, K. L. P., Hewitt, D. R., and Neufeld, J. A.: Tidal Grounding‐Line Migration Modulated by Subglacial 910 Hydrology, Geophys. Res. Lett., 47, https://doi.org/10.1029/2020GL089088, 2020. Wild, C. T., Marsh, O. J., and Rack, W.: Viscosity and elasticity: a model intercomparison of ice-shelf bending in an Antarctic grounding zone, J. Glaciol., 63, 573–580, https://doi.org/10.1017/jog.2017.15, 2017. Warburton, K. L. P., Hewitt, D. R., and Neufeld, J. A.: Tidal Grounding‐Line Migration Modulated by Subglacial 910 Hydrology, Geophys. Res. Lett., 47, https://doi.org/10.1029/2020GL089088, 2020. Wild, C. T., Marsh, O. J., and Rack, W.: Viscosity and elasticity: a model intercomparison of ice-shelf bending in an Antarctic grounding zone, J. Glaciol., 63, 573–580, https://doi.org/10.1017/jog.2017.15, 2017. 35
https://openalex.org/W2997366554
https://link.springer.com/content/pdf/10.1007/s12035-019-01860-x.pdf
English
null
Phenotypic Characterization of Larval Zebrafish (Danio rerio) with Partial Knockdown of the cacna1a Gene
Molecular neurobiology
2,019
cc-by
9,758
Abstract The CACNA1A gene encodes the pore-forming α1 subunit of voltage-gated P/Q type Ca2+ channels (Cav2.1). Mutations in this gene, among others, have been described in patients and rodents suffering from absence seizures and episodic ataxia type 2 with/ without concomitant seizures. In this study, we aimed for the first time to assess phenotypic and behavioral alterations in larval zebrafish with partial cacna1aa knockdown, placing special emphasis on changes in epileptiform-like electrographic discharges in larval brains. Whole-mount in situ hybridization analysis revealed expression of cacna1aa in the optic tectum and medulla oblongata of larval zebrafish at 4 and 5 days post-fertilization. Next, microinjection of two antisense morpholino oligomers (individually or in combination) targeting all splice variants of cacna1aa into fertilized zebrafish eggs resulted in dose-dependent mortality and decreased or absent touch response. Over 90% knockdown of cacna1aa on protein level induced epileptiform-like discharges in the optic tectum of larval zebrafish brains. Incubation of morphants with antiseizure drugs (sodium valproate, ethosuximide, lamotrigine, topiramate) significantly decreased the number and, in some cases, cumulative duration of epileptiform-like discharges. In this context, sodium valproate seemed to be the least effective. Carbamazepine did not affect the number and duration of epileptiform-like discharges. Altogether, our data indicate that cacna1aa loss-of-function zebrafish may be considered a new model of absence epilepsy and may prove useful both for the investigation of Cacna1a-mediated epileptogenesis and for in vivo drug screening. Keywords Zebrafish . CACNA1A gene . Loss of function . Epilepsy . Touch response . Antiseizure drugs Keywords Zebrafish . CACNA1A gene . Loss of function . Epilepsy . Touch response . Antiseizure drug Phenotypic Characterization of Larval Zebrafish (Danio rerio) with Partial Knockdown of the cacna1a Gene Kinga Gawel1,2 & Waldemar A. Turski2 & Wietske van der Ent1 & Benan J. Mathai3 & Karolina J. Kirstein-Smardzewska1 & Anne Simonsen3 & Camila V. Esguerra1,4 Kinga Gawel1,2 & Waldemar A. Turski2 & Wietske van der Ent1 & Benan J. Mathai3 & Karolina J. Kirstein-Smardzewska1 & Anne Simonsen3 & Camila V. Esguerra1,4 Received: 16 August 2019 /Accepted: 15 December 2019 /Published online: 26 December 2019 # The Author(s) 2019 Molecular Neurobiology (2020) 57:1904–1916 https://doi.org/10.1007/s12035-019-01860-x Molecular Neurobiology (2020) 57:1904–1916 https://doi.org/10.1007/s12035-019-01860-x Introduction CACNA1A encodes the pore-forming α1 subunit of voltage- gated P/Q type Ca2+ channels (Cav2.1) [1]. These channels are most abundantly located on presynaptic terminals, especially in Purkinje cells of the cerebellum where they control neuro- transmitter release [2–5]. However, high expression of P/Q calcium channels has also been found in the frontal cortex and the CA1 region of the hippocampus [2, 6], the brain struc- tures involved in generation, maintenance and spread of dis- charges in generalized epilepsy [7]. Mutations in CACNA1A have been described in patients suffering from autosomal- dominant diseases: familial hemiplegic migraine type 1, spinocerebellar ataxia type 6, and episodic ataxia type 2 (reviewed by [8]). Wietske van der Ent and Benan J. Mathai equally contributing authors Wietske van der Ent and Benan J. Mathai equally contributing authors Electronic supplementary material The online version of this article (https://doi.org/10.1007/s12035-019-01860-x) contains supplementary material, which is available to authorized users. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s12035-019-01860-x) contains supplementary material, which is available to authorized users. * Camila V. Esguerra c.v.esguerra@ncmm.uio.no 4 School of Pharmacy, Faculty of Mathematics and Natural Sciences, University of Oslo, Sem Sælandsvei 24, 0371 Oslo, Norway * Camila V. Esguerra c.v.esguerra@ncmm.uio.no 1 Chemical Neuroscience Group, Centre for Molecular Medicine Norway, Faculty of Medicine, University of Oslo, Gaustadalléen 21, Forskningsparken, 0349 Oslo, Norway 2 Department of Experimental and Clinical Pharmacology, Medical University of Lublin, Jaczewskiego St. 8b, 20-090 Lublin, Poland Although the type of mutation in the CACNA1A gene de- termines, at least partially, the disease phenotype, mutation carriers still exhibit a diverse range of symptoms, which mod- erately overlap. It is believed that predominantly nonsense mutations or deletions of the gene determine the clinical 3 Faculty of Medicine, Institute of Basic Medical Sciences and Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, University of Oslo, 1112 Blindern, 0317 Oslo, Norway 4 School of Pharmacy, Faculty of Mathematics and Natural Sciences, University of Oslo, Sem Sælandsvei 24, 0371 Oslo, Norway Mol Neurobiol (2020) 57:1904–1916 1905 manifestations in episodic ataxia type 2 patients [9, 10]. However, missense mutations in CACNA1A resulting in loss of P/Q type Ca2+ channel activity were described in infantile epilepsy with myoclonus [11]. Apart from recurrent ataxia, incoordination, slurring of speech, vertigo, and/or nystagmus, some patients present absence [12], myoclonic [13, 14], or febrile seizures [13, 15]. Moreover, early-onset epileptic en- cephalopathy has been described in humans [9, 10, 16]. Additionally, CACNA1A mutations have been detected in ro- dents [17–19] and humans suffering from absence seizures with/without cerebellar ataxia [13, 20, 21]. sequenced and annotated and exhibits approximately 70% similarity with the human genome [33]. Of note, during the process of evolution, some genes were duplicated in zebrafish [34]. The cacna1a gene in zebrafish is duplicated, with 72.01% (cacna1aa) and 71.28% (cacna1ab) homology with human CACNA1A (https://zfin.org/), the former having three splice variants in zebrafish. Although, there are good models of absence epilepsy in rodents, including the well-established and pharmacologically validated GAERS and WAG/Rij rats, spike-wave discharges in these models start appearing relatively late during develop- ment (2–3 months of age, which corresponds to the juvenile stage in humans). This is not consistent with the fact that absence epilepsy in humans typically manifests itself early during development (childhood). Moreover, although WAG/ Rij rats exhibit absence seizures, the mutation leading to the epilepsy phenotype has not been identified to date [35]. In case of GAERS rats, it is believed that mutations in Cacna1h lead to epilepsy [36]. In this context, the zebrafish model of absence epilepsy may offer another advantage. * Camila V. Esguerra c.v.esguerra@ncmm.uio.no Thus, in this study, we aimed for the first time to assess whether larval zebrafish may suffer from cacna1a-mediated absence seizures. Given that there is a lack of data about cacn1aa- related zebrafish phenotypes, we therefore aimed to describe all phenotypic defects in this study. Toward this end, we first assessed the expression of cacna1aa in the larval zebrafish brain using in situ hybridization analysis. Next, the combina- tion of two antisense morpholino oligomers (MOs) targeting ATG codons of all splice variants was used to achieve partial knockdown of cacna1aa. Using this approach, we assessed whether the partial loss-of-function (LOF) of cacna1aa could induce an epileptic-like phenotype in larval zebrafish, both on the behavioral and electroencephalographic (EEG) levels. To further examine the character of cacna1aa epileptiform-like discharges, we assessed the activity of four antiseizure drugs (ASDs) effective in the treatment of human absence seizures (i.e., sodium valproate (VPA), ethosuximide (ETX), lamotrigine (LTG), and topiramate (TPR)) and one drug (i.e., carbamazepine (CBZ)) that is contraindicated for this type of seizure. [ ] In the last decade, zebrafish (Danio rerio) has emerged as a new, attractive species for modeling human brain disorders. With regard to epilepsy research, the utility of zebrafish to mimic aspects of this human disorder has been demonstrated for Dravet syndrome (i.e., SCN1A mutations) [22, 23], pyridoxine-dependent epilepsy (ALDH7A1 and PLPBP) [24, 25], focal seizures (DEPDC5) [26], or in CHD2-mediated epileptic encephalopathies [27, 28]. More recently, Samarut et al. [29], using CRISPR/Cas9 technology, generated a new gabra1−/−mutant zebrafish line in order to unravel the epilep- togenic mechanisms underlying gabra1 deficiency and this study undoubtedly confirmed the potential of zebrafish for elucidating mechanisms underlying the process of epileptogenesis. Additionally, drug screening in zebrafish lar- vae has also been performed in genetic epilepsy models. Baraban et al. [30] took advantage of the epileptic phenotype of scn1lab−/−mutant zebrafish larvae and were able to identify clemizole as a potential new drug candidate by using a large- scale screening program in scn1lab−/−mutant zebrafish. Zhang et al. [22] demonstrated that another zebrafish model of Dravet syndrome responded to a drug lead in the same manner as human patients. They showed for the first time the anti-seizure effect of fenfluramine in scn1lab knockdown zebrafish larvae. * Camila V. Esguerra c.v.esguerra@ncmm.uio.no Interestingly, fenfluramine, which showed success in phase III trials for the management of Dravet syn- drome, did not exhibit any activity in the equivalent rodent models, highlighting the utility of zebrafish for identifying and/or validating new drug leads. More recently, Sourbron et al. [31] performed a drug-repurposing screen, by assessing the response of scn1lab−/−mutant larvae to three different drugs targeting the serotonergic system. In this preliminary study, lisuride (anti-parkinson’s drug, 5-HT2A, types 2 and 3 dopamine receptor agonist) emerged as a new drug candidate for Dravet syndrome patients. Table 1 Sequences of antisense MOs and primer sequences for cacna1aa sense and antisense probes Drugs The following ASDs were used: CBZ (100 μM), ETX (10 mM), LTG (200 μM), TPR (100 μM), and VPA (100 μM). All drugs, except for VPA (Sanofi Aventis), were purchased from Sigma-Aldrich. The doses of drugs were cho- sen on the basis of previous literature [22, 37] and preliminary tests. All ASDs were dissolved in DMSO and diluted in em- bryo medium to achieve a final concentration of DMSO of 0.5% v/v. Embryo medium, prepared with DMSO in a final concentration of 0.5% v/v, served as a vehicle (Veh). Zebrafish Maintenance With regard to developmental stages, 3-day post-fertiliza- tion (dpf) in zebrafish (i.e., day of hatching) corresponds to the time of human birth, while every successive day thereafter corresponds to 3 months of age in humans (i.e., 4, 5, 6, and 7 dpf are the equivalent to 3, 6, 9, and 12 months of age in children, respectively). The zebrafish is also a favorable alter- native to rodents in the context of genetic manipulation (de- scribed in detail by [32]). The zebrafish genome has been fully Adult zebrafish (Danio rerio) stocks of the AB strain (kind gift from Ana Carolina Sulen Tavara, Norwegian University of Life Sciences, Oslo, Norway) were maintained at standard aquaculture conditions (i.e., 28.5 °C, 14/10 h light/dark cycle). Fertilized eggs were collected via natural spawning. Embryos were reared under constant light conditions in embryo medi- um, i.e., Danieau’s buffer: 1.5-mM Hepes, pH 7.6, 17.4-mM 1906 Mol Neurobiol (2020) 57:1904–1916 mounted axiocam color camera. The experiment was replicat- ed twice, with n = 6–8/group. NaCl, 0.21-mM KCl, 0.12-mM MgSO4, and 0.18-mM Ca(NO3)2. All embryos and larvae were kept in an incubator, at 28.5 °C. All experimental protocols and housing conditions were carried out according to the National Institute of Health Guidelines for the Care and Use of Laboratory Animals, the European Community Council Directive of November 2010 for Care and Use of Laboratory Animals (Directive 2010/63/ EU), and the ARRIVE guidelines. All experiments were ap- proved by the Norwegian Food Safety Authority experimental animal administration’s supervisory and application system (FOTS-18/106800-1). Western Blot Analysis The anti-CACNA1A antibody was generated using a synthet- ic peptide from human CACNA1A amino acids 2050–2150. Using Clustal Omega, alignment of this region showed 89% and 50% homology between human CACNA1A and zebrafish cacna1aa and human CACNA1A and zebrafish cacna1ab, respectively. Microinjection of Antisense MOs Antisense MOs were designed and synthesized by Gene Tools, LLC (Philomath, OR, USA). The sequences of MO were plotted in Table 1. The targets for partial knockdown were ATG codons of cacna1aa transcripts, i.e., cacna1aa- 201 and cacna1aa-202 & cacna1aa-203, herein referred to as MO1 and MO2, respectively. A random sequence standard control MO (Ctrl-MO) and p53 MO (4 ng), suppressing p53 mRNA, were used to assess the specificity of the observed phenotype. All MOs, individually or in combination, were injected into the yolk of one- or two-cell stage embryos, in a total volume of 1.5 nl/embryo. EEG Analysis In order to detect epileptiform-like discharges in zebrafish larvae, the EEG recordings were conducted according to the method described previously [39]. The EEG recordings were obtained from zebrafish larval optic tectum at 4 dpf. Larvae were immobilized in a thin layer of 2% low-melting-point agarose, and the glass electrode (resistance 1–5 MΩ) filled with artificial cerebrospinal fluid (124 mM NaCl, 2 mM KCl, 2 mM MgSO4, 2 Mm CaCl2, 1.25 mM KH2PO4, 26 mM NaHCO3, 10 mM glucose) was placed into the optic Effect of ASDs on EEG Mortality of eggs and larvae injected with Ctrl-MO and cacna1aa MO (individually and in combination) was assessed 4 h post-fertilization (hpf) and 24 hpf. Larvae were visually inspected for severe malformations (e.g., pericardial edema, body axis curvature, hemorrhage) from 1 to 5 dpf. For docu- mentation, cacna1aa and Ctrl-MO morphants were photographed at 4 dpf, using a Leica MZ10F stereomicro- scope equipped with a DFC310 FX digital camera. Freely swimming 4 dpf Ctrl-MO and cacna1aa morphants were incubated with ASDs or Veh, within 2 h before EEG analysis. EEG recordings were conducted as described above. Number of epileptiform-like discharges, cumulative duration of events, and mean duration of events were determined. Touch-Evoked Response At 4 dpf, the touch-evoked response was evaluated in 48-well plates. Larvae were lightly touched on the tail with the tip of metal tweezers and their response was scored as follows: (1) “absent”—the larva does not move at all after several tactile stimuli given, (2) “decreased”—the larva performs a move- ment after several stimuli, (3) “normal”—the larva moves immediately after a single stimulus. Whole-Mount In Situ Hybridization Prestained molecular weight protein marker (Presicion Plus Protein™Dual Color Standars; Bio-Rad) was used to deter- mine the molecular weight of each detected band and to con- firm antibody target specificity. Total protein level was nor- malized relative to ß-actin protein level. Expression Pattern of cacna1aa in the Brain At 4 dpf, cacn1aa morphants as well as Ctrl-MO zebrafish larvae were placed in a 48-well plate (one larva per well) filled with 300 μl of embryo medium, and habituated to the auto- mated tracking device (ZebraBox, Viewpoint, Lyon, France) for 10 min in light, followed by 10 min in dark phase. Subsequently, the distance covered in millimeters by each larva was recorded for a total period of 10 min, with the fol- lowing intervals: (1) 5 min in light phase and (2) 5 min in dark phase. Two independent experiments were done, and the data were pooled together. Since the expression of cacna1aa was previously described by Thisse and Thisse [38] during early stages of zebrafish development, we focused on analyzing cacna1aa mRNA ex- pression at the stages when behavioral and EEG experiments were performed. Both dorsal and lateral views of the head, in whole-mount in situ hybridization, for wild type 4 and 5 dpf zebrafish revealed prominent cacna1aa mRNA expression in the midbrain and hindbrain, but low expression in the fore- brain and retina (Fig. 1). High expression of cacna1aa mRNA at 4 dpf larvae was detected in the optic tectum and even higher expression in the medulla oblongata. The staining was even more pronounced at 5 dpf. No detectable expression was observed in 5 dpf sense control larvae (Fig. 1). Statistical Analysis Mortality and touch-evoked response were analyzed using two-sided Fisher’s exact test. Locomotor activity and EEG data were analyzed by one-way analysis of variance (ANOVA), followed by Tukey’s post-hoc test. P values less than 0.05 were considered statistically significant. For a pur- pose of statistical analysis, GraphPad Prism 7.05 version (San Diego, CA, USA) was used. For figures generation, GraphPad Prism 7.05 or ImageJ (https://imagej.nih.gov/ij/) were used. Whole-Mount In Situ Hybridization Four-day-old Ctrl-MO and cacna1aa morphants were col- lected (25 larvae/sample, n = 3–4/group), placed in 100 μl of RIPA buffer (Sigma Aldrich), immediately boiled at 95 °C for 10 min and kept at −80 °C until further analysis. Total protein was separated on a 12% SDS-polyacrylamide gel and trans- ferred electrophoretically to a nitrocellulose membrane. Next, the membrane was blocked for 1 h with 5% skim milk (Sigma- Aldrich, USA) in PBS containing 0.1% Tween-20 and again incubated overnight with rabbit monoclonal anti-CACNA1A antibody (ab181371, 1:2000; Abcam) or rabbit monoclonal anti-ß-actin antibody (ab8226, 1:2000; Abcam) that served as primary antibodies. Goat anti-rabbit (31460, 1:2500; Thermo Fisher) horseradish peroxidase-conjugated secondary antibody was used to detect the primary antibodies, and the Whole-mount in situ hybridization analysis for cacna1aa was performed as previously described [38] using digoxigenin- labeled riboprobes. Primer sequences for cacna1aa sense and antisense probes are plotted in Table 1. Embryos were fixed at 4 or 5 dpf in 4% paraformaldehyde in 1 × PBS. Digoxigenin (DIG) UTP–labeled RNA riboprobes were made from linearized constructs using the mMESSAGE mMACHINE™SP6 Transcription Kit, mMESSAGE mMACHINE™T7 Transcription Kit (Thermo Scientific Fisher), and DIG RNA labeling Mix (Roche). Sense and an- tisense RNA probe-stained 4 dpf and 5 dpf larvae were im- aged on a Stemi 508 DOC Zeiss stereomicroscope with Morpholino name Morpholino sequence Primer sequences for probes cacna1aa MO1 5’-TGTACTCAAATGGAGTGAGA ATCAT-3’ f: 5’CCTTGACCTATGATTCTCAC TCC3’ cacna1aa MO2 5’-TCATCTCCGAACCGAGCCAT TCTAT-3’ r: 5’GCACTCCCTGCAGCATCATT GCT3’ Ctrl-MO 5’-CCTCTTACCTCAGTTACAAT TTATA-3’ p53 MO 5’-GCGCCATTGCTTTGCAAGAATTG −3’ f, forward; r, reverse Mol Neurobiol (2020) 57:1904–1916 1907 resulting signal was measured with the SIGMAFAST™DAB with Metal Enhancer (SLBP7387V; Sigma Aldrich). Prestained molecular weight protein marker (Presicion Plus Protein™Dual Color Standars; Bio-Rad) was used to deter- mine the molecular weight of each detected band and to con- firm antibody target specificity. Total protein level was nor- malized relative to ß-actin protein level. tectum (MultiClamp 700B amplifier, Digidata 1550 digitizer, Axon instruments, USA). Single recordings for each larva were performed for a period of 20 min. The threshold for detection of epileptiform-like discharges was set at 3× back- ground noise and 150 ms. The data were analyzed with the aid of the Clampfit 10.2 software (Molecular Devices Corporation, USA) and custom-written R script for Windows. resulting signal was measured with the SIGMAFAST™DAB with Metal Enhancer (SLBP7387V; Sigma Aldrich). Morphological and Behavioral Assessment of cacna1aa Morphants Administration of cacna1aa MO1 at 7.5 ng also did not affect mortality rate of embryos and larvae as well, but a higher dose of 9 ng significantly enhanced mortality (P < 0.05). Similarly, a second MO, cacna1aa MO2, did not influ- ence mortality at both tested time points at the same dose of 9 ng, but slightly increased mortality of embryos and larvae at 12 ng by 4 hpf (P < 0.05). Simultaneous administration of cacna1aa MO1 + MO2 at combined doses of 2.5 ng + 2.5 ng resulted in no increase in mortality. However, a signif- icant increase in mortality to 60% was evoked by simulta- neous administration of cacna1aa MO1 + MO2 at combined doses of 4.5 ng + 4.5 ng after 24 hpf (Table 2). Visual inspection of cacna1aa morphants (9 or 12 ng, single dose) that survived until 4 dpf revealed profound morpholog- ical malformations (curved body axis, small heads, tiny eyes, pericardial edema, yolk sac malformations) (data not shown). On the other hand, visual inspection of cacna1aa morphants (doses 2.5 ng + 2.5 ng) revealed that at 4 and 5 dpf, larvae were slightly hyperpigmented in comparison with Ctrl-MO counterparts (Fig. 2b). In addition, at 4 dpf, the majority of cacna1aa morphant larvae (i.e., 84.4% (38/45) vs. 4.2% (1/24) of Ctrl-MO injected larvae) did not inflate their swim bladder (see Fig. 2b). Measurements taken at 4 dpf revealed that cacna1aa morphants had a shorter body length (P < 0.05) compared with Ctrl-MO larvae (3.51 mm ± 0.15, n = 11 vs 3.73 mm ± 0.12, n = 9, respectively) (data not shown). There were no observable signs of necrosis, hemorrhage, pericardial edema, or axis truncation. The simultaneous administration of cacna1aa MOs and p53 MO (4 ng) indicated that the ob- served morphological changes were likely specific to cacna1aa partial knockdown and not due to off-target effects of the MO itself (see Supp. Fig 2). With regard to larval touch response, administration of cacna1aa MO1 at tested doses of 7.5 ng and 9 ng or of cacna1aa MO2 at doses of 9 ng and 12 ng hampered larval touch response significantly. Simultaneous administration of cacna1aa MO1 + MO2 at doses of 2.5 ng + 2.5 ng did not influence touch response, whereas combined doses of 4.5 ng + 4.5 ng resulted in a moderate decrease in the touch-evoked response (Table 3). Mortality Rate and Touch Response of cacna1aa Morphants Microinjected Ctrl-MO affected neither mortality rate of em- bryos and larvae, assessed at 4 hpf and 24 hpf, nor larval touch response as determined at 4 dpf (Tables 2 and 3). 1908 Mol Neurobiol (2020) 57:1904–1916 Fig. 1 Representative wild type larva in situ hybridization with cacna1aa antisense and sense probes. Dpf, days post- fertilization; MeO, medulla oblongata; TeO, optic tectum Morphological and Behavioral Assessment of cacna1aa Morphants Based on these results, the simultaneous administration of cacna1aa MO1 + MO2 at doses of 2.5 ng + 2.5 ng was chosen for further experiments. The western blot analysis revealed that these doses reduced cacn1aa protein levels to 10% rela- tive to the control (Fig. 2a and Supp. Fig 1). To investigate the impact of partial cacna1aa LOF on behavior, larval locomotor activity of cacna1aa morphants Fig. 1 Representative wild type larva in situ hybridization with cacna1aa antisense and sense probes. Dpf, days post- fertilization; MeO, medulla oblongata; TeO, optic tectum Fig. 1 Representative wild type larva in situ hybridization with cacna1aa antisense and sense probes. Dpf, days post- fertilization; MeO, medulla oblongata; TeO, optic tectum 1909 Mol Neurobiol (2020) 57:1904–1916 Treatment Dose Death after 4 hpf (%) Death after 24 hpf (%) (n/N) (n/N) Wild type Uninjected 5.29 7.20 (25/472) (34/472) Ctrl-MO 5 ng 2.63 7.89 (4/152) (12/152) cacna1aa MO1 7.5 ng 4.33 11.41 (11/254) (29/254) 9 ng 9.39* 43.19* (20/213) (92/213) cacna1aa MO2 9 ng 4.69 11.18% (21/447) (50/447) 12 ng 10.56* 12.19 (13/123) (15/123) cacna1aa MO1 + MO2 2.5 ng + 2.5 ng 4.14 8.03 (16/386) (31/386) 4.5 ng + 4.5 ng 4.69 60.40* (7/149) (90/149) n, number of dead larvae; N, total number of larvae; Hpf, hours post-fertilization Statistical analysis was performed using two-sided Fisher’s exact test *P < 0.05 vs respective Ctrl-MO group Table 2 Mortality of zebrafish cacna1aa knockdown larvae n, number of dead larvae; N, total number of larvae; Hpf, hours post-fertilization Statistical analysis was performed using two-sided Fisher’s exact test *P < 0.05 vs respective Ctrl-MO group activity was observed in cacna1aa morphants when compared with Ctrl-MO siblings in both analyzed phases (Light: P < 0. 05, Dark: P < 0.05; Fig. 3). Rapid switching from light to dark phase did not increase locomotor activity of morphants (P > 0. 05). activity was observed in cacna1aa morphants when compared with Ctrl-MO siblings in both analyzed phases (Light: P < 0. 05, Dark: P < 0.05; Fig. 3). Rapid switching from light to dark phase did not increase locomotor activity of morphants (P > 0. 05). and Ctrl-MO was evaluated at 4 dpf. One-way ANOVA re- vealed a statistically significant differences between groups of animals (F(3,180) = 21.84, P < 0.05, n = 44–48/group; Fig. 3). We observed that the switch from light to dark phase increased activity of Ctrl-MO (P < 0.05). *P < 0.05 vs respective Ctrl-MO group Statistical analysis was performed using two-sided Fisher’s exact test Morphological and Behavioral Assessment of cacna1aa Morphants In seizure- positive cacna1aa morphants, a mean frequency of events was 7 events/20-min recording, compared with 0.5 events/ 20-min recording in Ctrl-MO counterparts (Fig. 5a). In cacna1aa morphants, the mean and cumulative duration of EEG discharges was 503 and 3164 ms/20 min, respec- tively (Fig. 5b–c). One-way ANOVA revealed statistically significant differences between the tested groups in the number of epileptiform-like discharges (F(6.94) = 9.16, P < 0.05; n = 9–25/group; Fig. 5a), mean duration of events (F(6.94) = 5.64, P < 0.05; n = 9–25/group; Fig. 5b), and cumulative duration of events (F(6.94) = 9.17, P < 0.05; n = 9–25/group; Fig. 5c). Tukey’s post-hoc test revealed that 2-h incubation of cacna1aa morphants with ASDs indicated for the treat- ment of absence seizure in humans prior to EEG assess- ment decreased the number of epileptiform like dis (P > 0.05; Fig. 5b) and decrease the cumulative duration of events (P < 0.05; Fig. 5c). Differently, VPA tended to increase the mean duration of events (P > 0.05; Fig. 5b) while decreasing cumulative duration of events, but re- sults did not reach statistical significance (P > 0.05; Fig. 5c). CBZ, which is contraindicated in human patients with absence seizures, did not decrease any of the parameters when compared with cacna1aa morphants incubated with Veh (P > 0.05; Fig. 5a–c). Incubation of Ctrl-MO larvae with all ASDs did not induce any changes in their EEG Fig. 2 a Representative western blot of 4 dpf cacna1aa and Ctrl- MO larvae (left panel) and quan- tification of all samples (right panel). b Dorsal and side views of representative 4 dpf Ctrl-MO and cacna1aa MOs larvae Assessment of EEG Discharges in cacna1aa Morphants and Ctrl-MO Larvae and Effect of ASDs (P > 0.05; Fig. 5b) and decrease the cumulative duration of events (P < 0.05; Fig. 5c). Differently, VPA tended to Fig. 2 a Representative western blot of 4 dpf cacna1aa and Ctrl- MO larvae (left panel) and quan- tification of all samples (right panel). b Dorsal and side views of representative 4 dpf Ctrl-MO and cacna1aa MOs larvae Assessment of EEG Discharges in cacna1aa Morphants and Ctrl-MO Larvae and Effect of ASDs (P > 0.05; Fig. 5b) and decrease the cumulative duration of events (P < 0.05; Fig. 5c). Differently, VPA tended to increase the mean duration of events (P > 0.05; Fig. Morphological and Behavioral Assessment of cacna1aa Morphants However, reduced locomotor and Ctrl-MO was evaluated at 4 dpf. One-way ANOVA re- vealed a statistically significant differences between groups of animals (F(3,180) = 21.84, P < 0.05, n = 44–48/group; Fig. 3). We observed that the switch from light to dark phase increased activity of Ctrl-MO (P < 0.05). However, reduced locomotor Treatment Dose Normal (%) Decreased (%) Absent (%) (n/N) (n/N) (n/N) Wild type Uninjected 97.22 2.78 0 (35/36) (1/36) (0/36) Ctrl-MO 5 ng 98.07 1.92 0 (51/52) (1/52) (0/52) cacna1aa MO1 7.5 ng 73.37* 18.51* 11.11* (38/54) (10/54) (6/54) 9 ng 0* 16.66* 83.33* (0/24) (4/24) (20/24) cacna1aa MO2 9 ng 52* 13.79* 36.20* (29/58) (8/58) (21/58) 12 ng 0* 5.71 94.28* (0/35) (2/35) (33/35) cacna1aa MO1 + MO2 2.5 ng + 2.5 ng 96.82 3.17 0 (61/63) (2/63) (0/63) 4.5 ng + 4.5 ng 50* 20.83* 29.16* (12/24) (5/24) (7/24) n, number of animals with a defined (i.e., absent, decreased, or normal) response; N, total number of animals i i l l i f d i id d i h Table 3 Touch-evoked response of zebrafish cacna1aa knockdown larvae Treatment Dose Normal (%) Decreased (%) Absent (%) (n/N) (n/N) (n/N) Wild type Uninjected 97.22 2.78 0 (35/36) (1/36) (0/36) Ctrl-MO 5 ng 98.07 1.92 0 (51/52) (1/52) (0/52) cacna1aa MO1 7.5 ng 73.37* 18.51* 11.11* (38/54) (10/54) (6/54) 9 ng 0* 16.66* 83.33* (0/24) (4/24) (20/24) cacna1aa MO2 9 ng 52* 13.79* 36.20* (29/58) (8/58) (21/58) 12 ng 0* 5.71 94.28* (0/35) (2/35) (33/35) cacna1aa MO1 + MO2 2.5 ng + 2.5 ng 96.82 3.17 0 (61/63) (2/63) (0/63) 4.5 ng + 4.5 ng 50* 20.83* 29.16* (12/24) (5/24) (7/24) n, number of animals with a defined (i.e., absent, decreased, or normal) response; N, total number of animals Statistical analysis was performed using two-sided Fisher’s exact test *P < 0.05 vs respective Ctrl-MO group Table 3 Touch-evoked response of zebrafish cacna1aa knockdown larvae Mol Neurobiol (2020) 57:1904–1916 1910 Assessment of EEG Discharges in cacna1aa Morphants and Ctrl-MO Larvae and Effect of ASDs In 2 out of 19 (10.5%) control morphants, single short- duration epileptiform-like events were observed (Fig. 4a). Spontaneous epileptiform-like events in the form of abrupt high-voltage spikes, spike-wave complexes, and polyspike-wave discharges (Fig. 4b–f) occurred in 24 out of 26 (92%) cacna1aa morphants. Fig. 2 a Representative western blot of 4 dpf cacna1aa and Ctrl- MO larvae (left panel) and quan- tification of all samples (right panel). b Dorsal and side views of representative 4 dpf Ctrl-MO and cacna1aa MOs larvae Morphological and Behavioral Assessment of cacna1aa Morphants 5b) while decreasing cumulative duration of events, but re- sults did not reach statistical significance (P > 0.05; Fig. 5c). CBZ, which is contraindicated in human patients with absence seizures, did not decrease any of the parameters when compared with cacna1aa morphants incubated with Veh (P > 0.05; Fig. 5a–c). Incubation of Ctrl-MO larvae with all ASDs did not induce any changes in their EEG In 2 out of 19 (10.5%) control morphants, single short- duration epileptiform-like events were observed (Fig. 4a). Spontaneous epileptiform-like events in the form of abrupt high-voltage spikes, spike-wave complexes, and polyspike-wave discharges (Fig. 4b–f) occurred in 24 out of 26 (92%) cacna1aa morphants. In seizure- positive cacna1aa morphants, a mean frequency of events was 7 events/20-min recording, compared with 0.5 events/ 20-min recording in Ctrl-MO counterparts (Fig. 5a). In cacna1aa morphants, the mean and cumulative duration of EEG discharges was 503 and 3164 ms/20 min, respec- tively (Fig. 5b–c). One-way ANOVA revealed statistically significant differences between the tested groups in the number of epileptiform-like discharges (F(6.94) = 9.16, P < 0.05; n = 9–25/group; Fig. 5a), mean duration of events (F(6.94) = 5.64, P < 0.05; n = 9–25/group; Fig. 5b), and cumulative duration of events (F(6.94) = 9.17, P < 0.05; n = 9–25/group; Fig. 5c). Fig. 3 Locomotor activity of 4 dpf cacna1aa and Ctrl-MO larvae. Larvae were habituated to the apparatus 20 min (10 min light, 10 min in dark) before experiment, and total locomotor activity was tracked within 10 min. The data were pooled from 2 independent experiments. The results were analyzed using one-way ANOVA, followed by Tukey’s post-hoc test. Dots represent individual measurements, the central hori- zontal mark is the mean, and error bars represent standard deviation (SD) (n = 44–48/group). *P < 0.05 vs Ctrl-MO group in relevant phase, #P < 0.05 vs Ctrl-MO group in light phase. Dpf, days post-fertilization 4 Representative electroencephalographic recording illustrating the epileptiform-like discharges recorded in zebrafish Ctrl-MO larvae and cacna1aa morphants (2.5 ng + 2.5 ng). The EEG recordings were obtain- ed from zebrafish larval optic tectum at 4 dpf. a Five-minute-long frag- ment of representative recording from Ctrl-MO larvae. b Five-minute lasting continuous recording from cacna1aa morphant demonstrating the background and ictal activity. Small letters (c–f) correspond to respec- tive ictal events depicted on traces b–e. c–f Epileptiform-like discharges, high-voltage spikes, spike-wave complexes, and polyspike-wave discharges Mol Neurobiol (2020) 57:1904 1916 1911 m 0 1 0.1 mV 10 s 0.1 mV 10 s activity, compared with Ctrl-MO larvae incubated with Veh only (P > 0.05; n = 7–25; Supp. Fig 3 A–C). i i 0.1 mV 100 ms 100 ms 0.1 mV 0 . 1 0 0.1 mV 100 ms activity, compared with Ctrl-MO larvae incubated with 0 0.1 mV 100 ms . m V 0.1 mV 100 ms 0.1 mV 100 ms Fig. 4 Representative electroencephalographic recording illustrating the epileptiform-like discharges recorded in zebrafish Ctrl-MO larvae and cacna1aa morphants (2.5 ng + 2.5 ng). The EEG recordings were obtain- ed from zebrafish larval optic tectum at 4 dpf. a Five-minute-long frag- ment of representative recording from Ctrl-MO larvae. b Five-minute lasting continuous recording from cacna1aa morphant demonstrating the background and ictal activity. Small letters (c–f) correspond to respec- tive ictal events depicted on traces b–e. c–f Epileptiform-like discharges, high-voltage spikes, spike-wave complexes, and polyspike-wave discharges activity, compared with Ctrl-MO larvae incubated with Veh only (P > 0.05; n = 7–25; Supp. Fig 3 A–C). Tukey’s post-hoc test revealed that 2-h incubation of cacna1aa morphants with ASDs indicated for the treat- ment of absence seizure in humans prior to EEG assess- ment decreased the number of epileptiform-like dis- charges substantially, compared with cacna1aa morphants incubated with Veh (Fig. 5a). Herein, VPA, ETX, LTG, and TPR were equally potent (P < 0.05). However, analy- sis of mean and cumulative duration of events revealed that ETX and TPR were the most effective in decreasing the duration of these parameters, when compared with Veh-treated cacna1aa morphants (P < 0.05; Fig. 5 b and c). LTG tended to decrease mean duration of events Fig. 3 Locomotor activity of 4 dpf cacna1aa and Ctrl-MO larvae. Larvae were habituated to the apparatus 20 min (10 min light, 10 min in dark) before experiment, and total locomotor activity was tracked within 10 min. The data were pooled from 2 independent experiments. The results were analyzed using one-way ANOVA, followed by Tukey’s post-hoc test. Dots represent individual measurements, the central hori- zontal mark is the mean, and error bars represent standard deviation (SD) (n = 44–48/group). *P < 0.05 vs Ctrl-MO group in relevant phase, #P < 0.05 vs Ctrl-MO group in light phase. Dpf, days post-fertilization 100 ms 0.1 mV 0.1 mV 100 ms 0 . 1 0 . m V 0.1 mV 100 ms 0.1 mV 100 ms 0.1 Fig. 4 Representative electroencephalographic recording illu epileptiform-like discharges recorded in zebrafish Ctrl-MO cacna1aa morphants (2.5 ng + 2.5 ng). The EEG recordings w ed from zebrafish larval optic tectum at 4 dpf. a Five-minute ment of representative recording from Ctrl-MO larvae. b F lasting continuous recording from cacna1aa morphant dem the background and ictal activity. Small letters (c–f) correspon tive ictal events depicted on traces b–e. c–f Epileptiform-like high-voltage spikes, spike-wave complexes, and polys discharges Mol Neurobiol (2020) 57:1904–1916 Mol Neurobiol (2020) 57:1904–1916 1911 activity, compared with Ctrl-MO larvae incubated with Veh only (P > 0.05; n = 7–25; Supp. Fig 3 A–C). Discussion Our study revealed that partial cacna1aa LOF in larval zebrafish results in profound behavioral impairment and 100 ms 0.1 mV 0.1 mV 100 ms 0 . 1 0 . m V 0.1 mV 100 ms 0.1 mV 100 ms m 0 1 0.1 mV 10 s 0.1 mV 10 s Fig. Discussion Peripheral effects of cacna1aa LOF (2.5 ng + 2.5 ng) were evidenced by changes in morphology of morphants, i.e., slight hyperpigmentation, lack of swim bladder, and shorter body length—phenotypes also observed in other zebrafish models of epilepsy [22, 40]. Notably, cacna1aa mRNA in zebrafish embryos is maternally contrib- uted [41, 42], possibly accounting for the higher mortality rate at 24 h than 4 h after injection. Saito et al. [43] revealed that knockdown of Cacna1a to 28% of baseline Cav2.1 induced severe ataxia, while reduction to 14% dramatically shortened the lifespan of mice. Similarly, conditional ablation of Cav2.1 channels leading to Cacna1a gene LOF in mice resulted in ataxia and dystonia starting at around postnatal days 10–12 and death at postnatal days 21–22 [44]. In our experimental setting, the cause of mortality is partially related to morphol- ogy abnormalities. However, lethal/deleterious effects on brain function cannot be ruled out, especially since our study was based on analyzing behavioral and EEG changes at lower, non-lethal doses of MOs. In this study, we observed that spontaneous epileptiform- like events in the form of abrupt high-voltage spikes, spike- wave complexes, and polyspike-wave discharges occurred in 92% of cacna1aa morphants. Previous studies indicated that chemicals (e.g., pentylentetrazole or allylglycine) [37, 39, 53] as well as mutations in different genes (e.g., scn1lab, aldh7a1) [22, 24] increase locomotor activity in zebrafish larvae remi- niscent of tonic-clonic-like seizures. Indeed, tonic-clonic-like seizures have been described both in genetic and pharmaco- logical models of epilepsy in zebrafish [22, 54]. The number and frequency of EEG discharges correlated with behavioral outcome, i.e., a dramatic increase in locomotor activity with rapid “whirlpool-like” circling followed by loss of posture. cacna1aa morphants did not display this kind of behavior (thus ruling out tonic-clonic-like seizures), and the frequency of epileptiform-like discharges was lower than in all above- mentioned models. Notably, our data are more in line with the phenotype reported for zebrafish tsc−/−mutants (model of tu- berous sclerosis complex) [51], with regard to seizure duration and frequency. In this study however, the authors did not draw any final conclusion as to what type of seizures were observed in tsc−/−mutants. The behavioral impairments observed in cacna1a morphants indicate defects of neuronal origin. The decreased/absent reflex to the touch stimulus may depend on disruption of the spinal reflex mechanism since the touch- evoked locomotor activity response allows assessment of muscle performance in zebrafish. Discussion Our study revealed that partial cacna1aa LOF in larval zebrafish results in profound behavioral impairment and 1912 Mol Neurobiol (2020) 57:1904–1916 disturbed touch-evoked activation of motor neurons, the third neuron of the reflex arc [50]. ƒFig. 5 Effect of ASDs on epileptiform-like discharges recorded from the optic tectum of 4 dpf cacna1aa and Ctrl-MO morphants. Larvae were incubated (2 h) with different ASDs. Results are presented as a number of events, b mean duration of events (msec), and c cumulative duration of events (msec) during 20 min of recording. Statistical analysis was per- formed using one-way ANOVA with Tukey’s post-hoc test. Dots repre- sent individual measurements, the central horizontal mark is the mean, and error bars represent SD (n = 9–25). Symbols represent following comparisons: *P < 0.05 vs Ctrl-MO group incubated with Veh, #P < 0.05 vs cacna1aa MOs group incubated with Veh. CBZ, carbamaz- epine (100 μM); ETX, ethosuximide (10 mM), LTG, lamotrigine (200 μM), TPR, topiramate (100 μM), VPA, sodium valproate (100 μM) Although cacna1aa morphants did not inflate their swim bladder at 4 dpf, other reports have indicated that this defect does not necessarily interfere significantly with total distance traveled, but only affects slow movements associated with maintaining balance [22, 51]. Thus, the lack of an inflated swim bladder can likely be ruled out as a cause for reduced locomotor activity. Reduced locomotor activity in morphants was similar in both light and dark phases. It has been repeatedly demonstrat- ed that abrupt switching from light to dark induces a rapid increase in locomotor activity of zebrafish larvae, which de- creases to baseline after a few (5–10) minutes [51, 52]. A similar uniform reduction in motility may indicate the reduc- tion of skeletal muscle reactivity or muscle relaxation due to decreased activity of P/Q calcium channels [47, 48]. On the other hand, Samarut et al. [29] observed reduced locomotor activity in gabra1−/−zebrafish mutants. Although rapid switching of light to dark induced a very quick and transient increase in their activity, this was followed by profound hypolocomotion [29]. irregular repeated epileptiform-like discharges as measured by EEG. cacna1aa LOF in larval zebrafish leads to mortality, even when individual splice variants are targeted. The cause of mortality may be attributable to defects in the brain, periph- eral effects, or both. Discussion ETX is believed to selectively inhibit T-type calcium channels, while VPA has broader spectrum activity and apart from calcium channel inhibi- tion, also exerts its effect through sodium channel inhibition and activation of GABA-ergic neurotransmission. LTG is a broad- spectrum blocker of calcium and sodium channels, increasing GABA levels, while TPR additionally increases the affinity of GABA to GABAA receptors (for review see [65]). CBZ, also a sodium channel blocker, did not affect the number of EEG dis- charges in cacna1aa morphants. It was reported that CBZ might exaggerate absence seizures in Cacna1a mutation carriers, both in humans and rodents [66, 67]. Similarly, CBZ exaggerated the incidence of EEG discharges in WAG/Rij rats [63]. On the other hand, phenytoin, another sodium channel blocker, did not affect seizure incidence in Cacna1a models of absence seizures [17, 18, 59]. Although, CBZ did not increase the number of EEG dis- charges in cacna1aa morphants, it cannot be excluded that the time of incubation (2 h) was not long enough to enhance EEG discharges. equivalent to 3 months post-birth in humans. This larval zebrafish model is also amenable to large-scale drug screen- ing, opening up the possibility for the discovery of new ther- apeutic compounds to treat the 30% of absence epilepsy pa- tients that are drug resistant. Furthermore, although absence epilepsy is categorized as a relatively benign form of epilepsy compared with other genetic generalized epilepsy syndromes, it is still often accompanied by comorbidities that can persist even after seizure freedom is achieved. Moreover, drugs used to treat absence epilepsy, such as ETX and VPA, are often not well tolerated or are ineffective. Thus, this zebrafish model can also be used to test for potential disease-modifying activ- ity of drugs with regard to effective treatment of comorbidities (e.g., learning and memory deficits, attention deficit hyperac- tivity disorder, and anxiety) associated with absence epilepsy. Funding Information KG received a mobility grant from the Polish Ministry of Science and Higher Education within the “Mobilność Plus V” program (decision nr 1649/1/MOB/V/17/2018/0; 01.01.2018- 31.12.2018). KG has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie (grant agreement no. 798703-GEMZ-H2020- MSCA-IF-2017). Discussion This work was partially supported by start-up funds from the Centre for Molecular Medicine Norway (for CVE) and the Research Council of Norway through its Centres of Excellence funding scheme (project number 262652) and FRIPRO grant (project number 221831 for BJM and AS). Compliance with Ethical Standards All experiments were approved by the Norwegian Food Safety Authority experimental animal administration’s supervisory and application system (FOTS-18/106800-1). Conflict of Interest The authors declare that they have no conflict of interest. Compliance with Ethical Standards All experiments were approved by the Norwegian Food Safety Authority experimental animal administration’s supervisory and application system (FOTS-18/106800-1). Conflict of Interest The authors declare that they have no conflict of interest. Conflict of Interest The authors declare that they have no conflict of interest. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. In summary, our study describes for the first time, the phe- notypic profile of reduced cacna1aa function in larval zebrafish, which causes significant locomotor impairment and even lethality. The described behavioral phenotype is ac- companied by irregular, repeated epileptiform-like discharges as recorded by EEG. In addition, the pharmacological profil- ing data further support the validation of this new model for the study of absence seizures. Given that absence epilepsy is most common in children, the use of a developmental model such as the zebrafish allows for the study of epileptogenesis mechanisms (e.g., observed differences in cortical interneuron populations) [68] in the brain at relevant life stages when absence seizures are most likely to occur. Our analysis of the cacna1aa LOF in zebrafish was performed at 4 dpf, which is Discussion Touch stimuli, e.g., touch of the zebrafish tail tip with a needle, results in muscle con- traction accompanied with burst swim [45]. P/Q calcium channels in mammals are abundantly expressed in neuromus- cular junctions where they control presynaptic acetylcholine release [46] and are considered to mediate fast neuromuscular neurotransmission also in zebrafish [47, 48]. To the best of our knowledge, cacna1aa expression in muscles and the spinal cord has not been investigated, but cacna1ab, the paralog to cacna1aa, was proposed as a mediator of locomotor behavior and touch-evoked motor response as indicated in fakir mu- tants [49, 50]. The high expression of cacna1ab was found in sensory neurons, but MO knockdown of cacna1ab In humans and rodents, absence seizures occur as bilateral, synchronous slow-wave discharges (typically 3 Hz or 5–7 Hz, respectively) [12, 17, 19–21, 55]. Although we could not clearly distinguish this pattern of discharges in cacna1aa morphants, we cannot rule out that species differences may determine the EEG pattern of absence seizures in zebrafish. Our study revealed that all four drugs recommended in the management of absence seizures significantly dimin- ished the number of epileptiform-like events in 4-dpf 1913 Mol Neurobiol (2020) 57:1904–1916 cacna1aa morphants and were equally potent. Noteworthy, VPA did not affect mean and cumulative duration of events, with the tendency to even increase the latter. Interestingly, the International League Against Epilepsy (ILAE) guidelines recommend VPA as the drug of choice for the treatment of absence epilepsy (class I) in children [56]. On the other hand, we observed that TPR was equally potent when compared with ETX, a class I–indicated drug for absence seizures. Although, ILAE guidelines do not include recommen- dations for TPR, it is commonly used to treat absence seizures in humans as a second-choice therapy [57, 58]. LTG belongs to class III (i.e., possibly effective) ASDs for absence seizures in patients. In our model, LTG significantly reduced the cumulative duration of EEG discharges and exhibited a tendency to decrease mean duration of events. In rodents with Cacna1a LOF, both ETX and VPA efficacy were observed [17, 18, 59] with less consistent data for other drugs, i.e., LTG and TPR [60, 61]. ETX also decreased the incidence of EEG discharges in WAG/ Rij rats [62–64]. Nevertheless, taking our data into consideration, it is possible that differences in ASD modes of action might account for differences in our observations. 2. Hillman D, Chen S, Aung TT, Cherksey B, Sugimori M, Llinás RR (1991) Localization of P-type calcium channels in the central ner- vous system. Proc Natl Acad Sci U S A 88:7076–7080. https://doi. org/10.1073/pnas.88.16.7076 References Pena IA, Roussel Y, Daniel K, Mongeon K, Johnstone D, Weinschutz Mendes H, Bosma M, Saxena V et al (2017) Pyridoxine-dependent epilepsy in zebrafish caused by Aldh7a1 de- ficiency. Genetics 207:1501–1518. https://doi.org/10.1534/ genetics.117.300137 8. Jen JC, Wan J (2018) Episodic ataxias. Handb Clin Neurol 155: 205–215. https://doi.org/10.1016/B978-0-444-64189-2.00013-5 9. Damaj L, Lupien-Meilleur A, Lortie A, Riou É, Ospina LH, Gagnon L, Vanasse C, Rossignol E (2015) CACNA1A haploinsufficiency causes cognitive impairment, autism and epilep- tic encephalopathy with mild cerebellar symptoms. Eur J Hum Genet 23:1505–1512. https://doi.org/10.1038/ejhg.2015.21 25. Zabinyakov N, Bullivant G, Cao F, Fernandez Ojeda M, Jia ZP, Wen XY, Dowling JJ, Salomons GS et al (2017) Characterization of the first knock-out aldh7a1 zebrafish model for pyridoxine- dependent epilepsy using CRISPR-Cas9 technology. PLoS One 12:e0186645. https://doi.org/10.1371/journal.pone.0186645 10. Reinson K, Õiglane-Shlik E, Talvik I, Vaher U, Õunapuu A, Ennok M, Teek R, Pajusalu S et al (2016) Biallelic CACNA1A mutations cause early onset epileptic encephalopathy with progressive cere- bral, cerebellar, and optic nerve atrophy. Am J Med Genet A 170: 2173–2176. https://doi.org/10.1002/ajmg.a.37678 26. de Calbiac H, Dabacan A, Marsan E, Tostivint H, Devienne G, Ishida S, Leguern E, Baulac S et al (2018) Depdc5 knockdown causes mTOR-dependent motor hyperactivity in zebrafish. Ann Clin Transl Neurol 5:510–523. https://doi.org/10.1002/acn3.542 11. Balck A, Hanssen H, Hellenbroich Y, Lohmann K, Münchau A (2017) Adult-onset ataxia or developmental disorder with seizures: two sides of missense changes in CACNA1A. J Neurol 264:1520– 1522. https://doi.org/10.1007/s00415-017-8494-z 27. Suls A, Jaehn JA, Kecskés A, Weber Y, Weckhuysen S, Craiu DC, Siekierska A, Djémié T et al (2013) De novo loss-of-function mu- tations in CHD2 cause a fever-sensitive myoclonic epileptic en- cephalopathy sharing features with Dravet syndrome. Am J Hum Genet 93:967–975. https://doi.org/10.1016/j.ajhg.2013.09.017 12. Du X, Chen Y, Zhao Yet al (2017) Dramatic response to pyridoxine in a girl with absence epilepsy with ataxia caused by a de novo CACNA1A mutation. Seizure - European Journal of Epilepsy 45: 189–191. https://doi.org/10.1016/j.seizure.2016.12.020 28. Galizia EC, Myers CT, Leu C, de Kovel CG, Afrikanova T, Cordero-Maldonado ML, Martins TG, Jacmin M et al (2015) CHD2 variants are a risk factor for photosensitivity in epilepsy. Brain 138:1198–1207. https://doi.org/10.1093/brain/awv052 13. Lee CG, Lee J, Lee M (2018) Multi-gene panel testing in Korean patients with common genetic generalized epilepsy syndromes. PLoS One:13. https://doi.org/10.1371/journal.pone.0199321 29. References 1. Heyes S, Pratt WS, Rees E, Dahimene S, Ferron L, Owen MJ, Dolphin AC (2015) Genetic disruption of voltage-gated calcium channels in psychiatric and neurological disorders. Prog Neurobiol 134:36–54. https://doi.org/10.1016/j.pneurobio.2015.09.002 2. Hillman D, Chen S, Aung TT, Cherksey B, Sugimori M, Llinás RR (1991) Localization of P-type calcium channels in the central ner- vous system. Proc Natl Acad Sci U S A 88:7076–7080. https://doi. org/10.1073/pnas.88.16.7076 1914 Mol Neurobiol (2020) 57:1904–1916 3. Takahashi T, Momiyama A (1993) Different types of calcium chan- nels mediate central synaptic transmission. Nature 366:156–158. https://doi.org/10.1038/366156a0 19. Zwingman TA, Neumann PE, Noebels JL, Herrup K (2001) Rocker is a new variant of the voltage-dependent calcium channel gene Cacna1a. J Neurosci 21:1169–1178 20. Imbrici P, Jaffe SL, Eunson LH, Davies NP, Herd C, Robertson R, Kullmann DM, Hanna MG (2004) Dysfunction of the brain calcium channel CaV2.1 in absence epilepsy and episodic ataxia. Brain 127: 2682–2692. https://doi.org/10.1093/brain/awh301 4. Volsen SG, Day NC, McCormack AL et al (1995) The expression of neuronal voltage-dependent calcium channels in human cerebel- lum. Mol Brain Res 34:271–282. https://doi.org/10.1016/0169- 328X(95)00234-J 21. Jouvenceau A, Eunson LH, Spauschus A, Ramesh V, Zuberi SM, Kullmann DM, Hanna MG (2001) Human epilepsy associated with dysfunction of the brain P/Q-type calcium channel. Lancet 358: 801–807. https://doi.org/10.1016/S0140-6736(01)05971-2 5. Westenbroek RE, Sakurai T, Elliott EM, Hell JW, Starr TV, Snutch TP, Catterall WA (1995) Immunochemical identification and sub- cellular distribution of the alpha 1A subunits of brain calcium chan- nels. J Neurosci 15:6403–6418 22. Zhang Y, Kecskés A, Copmans D, Langlois M, Crawford AD, Ceulemans B, Lagae L, de Witte PA et al (2015) Pharmacological characterization of an antisense knockdown zebrafish model of Dravet syndrome: inhibition of epileptic seizures by the serotonin agonist fenfluramine. PLoS One 10:e0125898. https://doi.org/10. 1371/journal.pone.0125898 6. Igelmund P, Zhao YQ, Heinemann U (1996) Effects of T-type, L- type, N-type, P-type, and Q-type calcium channel blockers on stimulus-induced pre- and postsynaptic calcium fluxes in rat hippo- campal slices. Exp Brain Res 109:22–32. https://doi.org/10.1007/ bf00228623 7. Rossignol E, Kruglikov I, van den Maagdenberg AMJM, Rudy B, Fishell G (2013) CaV 2.1 ablation in cortical interneurons selectively impairs fast-spiking basket cells and causes general- ized seizures. Ann Neurol 74:209–222. https://doi.org/10.1002/ ana.23913 23. Brenet A, Hassan-Abdi R, Somkhit J et al (2019) Defective excitatory/inhibitory synaptic balance and increased neuron apo- ptosis in a zebrafish model of Dravet syndrome. Cells:8. https:// doi.org/10.3390/cells8101199 24. References Samarut É, Swaminathan A, Riché R, Liao M, Hassan-Abdi R, Renault S, Allard M, Dufour L et al (2018) γ-aminobutyric acid receptor alpha 1 subunit loss of function causes genetic generalized epilepsy by impairing inhibitory network neurodevelopment. Epilepsia 59:2061–2074. https://doi.org/10.1111/epi.14576 14. Lv Y, Wang Z, Liu C, Cui L (2017) Identification of a novel CACNA1A mutation in a Chinese family with autosomal recessive progressive myoclonic epilepsy. Neuropsychiatr Dis Treat 13: 2631–2636. https://doi.org/10.2147/NDT.S145774 15. Choi K-D, Kim J-S, Kim H-J, Jung I, Jeong SH, Lee SH, Kim DU, Kim SH et al (2017) Genetic variants associated with episodic ataxia in Korea. Sci Rep 7:1–11. https://doi.org/10.1038/s41598-017- 14254-7 30. Baraban SC, Dinday MT, Hortopan GA (2013) Drug screening in Scn1a zebrafish mutant identifies clemizole as a potential Dravet syndrome treatment. Nat Commun 4:2410. https://doi.org/10.1038/ ncomms3410 16. Epi4K Consortium (2016) De novo mutations in SLC1A2 and CACNA1A are important causes of epileptic encephalopathies. Am J Hum Genet 99:287–298. https://doi.org/10.1016/j.ajhg.2016.06.003 31. Sourbron J, Partoens M, Scheldeman C, Zhang Y, Lagae L, de Witte P (2019) Drug repurposing for Dravet syndrome in scn1Lab−/−mutant zebrafish. Epilepsia 60:e8–e13. https://doi. org/10.1111/epi.14647 17. Kim TY, Maki T, Zhou Y, Sakai K, Mizuno Y, Ishikawa A, Tanaka R, Niimi K et al (2015) Absence-like seizures and their pharmaco- logical profile in tottering-6j mice. Biochem Biophys Res Commun 463:148–153. https://doi.org/10.1016/j.bbrc.2015.05.050 32. Stewart AM, Braubach O, Spitsbergen J, Gerlai R, Kalueff AV (2014) Zebrafish models for translational neuroscience research: from tank to bedside. Trends Neurosci 37:264–278. https://doi. org/10.1016/j.tins.2014.02.011 18. Tokuda S, Kuramoto T, Tanaka K, Kaneko S, Takeuchi IK, Sasa M, Serikawa T (2007) The ataxic groggy rat has a missense mutation in the P/Q-type voltage-gated Ca2+ channel alpha1A subunit gene and exhibits absence seizures. Brain Res 1133:168–177. https:// doi.org/10.1016/j.brainres.2006.10.086 33. Howe K, Clark MD, Torroja CF, Torrance J, Berthelot C, Muffato M, Collins JE, Humphray S et al (2013) The zebrafish reference genome sequence and its relationship to the human genome. Nature 496:498–503. https://doi.org/10.1038/nature12111 1915 Mol Neurobiol (2020) 57:1904–1916 50. Low SE, Woods IG, Lachance M, Ryan J, Schier AF, Saint-Amant L (2012) Touch responsiveness in zebrafish requires voltage-gated calcium channel 2.1b. J Neurophysiol 108:148–159. https://doi.org/ 10.1152/jn.00839.2011 34. Novak AE, Jost MC, Lu Y, Taylor AD, Zakon HH, Ribera AB (2006) Gene duplications and evolution of vertebrate voltage- gated sodium channels. J Mol Evol 63:208–221. https://doi.org/ 10.1007/s00239-005-0287-9 51. References Scheldeman C, Mills JD, Siekierska A et al (2017) mTOR-related neuropathology in mutant tsc2 zebrafish: phenotypic, transcriptomic and pharmacological analysis. Neurobiol Dis 108: 225–237. https://doi.org/10.1016/j.nbd.2017.09.004 35. Russo E, Citraro R (2018) Pharmacology of epileptogenesis and related comorbidities in the WAG/Rij rat model of genetic absence epilepsy. J Neurosci Methods 310:54–62. https://doi.org/10.1016/j. jneumeth.2018.05.020 52. Burgess HA, Granato M (2007) Modulation of locomotor activity in larval zebrafish during light adaptation. J Exp Biol 210:2526– 2539. https://doi.org/10.1242/jeb.003939 36. Proft J, Rzhepetskyy Y, Lazniewska J, et al (2017) The Cacna1h mu- tation in the GAERS model of absence epilepsy enhances T-type Ca2+ currents by altering calnexin-dependent trafficking of Cav3.2 channels. Sci rep 7:. doi: https://doi.org/10.1038/s41598-017-11591-5 53. Leclercq K, Afrikanova T, Langlois M, de Prins A, Buenafe OE, Rospo CC, van Eeckhaut A, de Witte PA et al (2015) Cross-species pharmacological characterization of the allylglycine seizure model in mice and larval zebrafish. Epilepsy Behav 45:53–63. https://doi. org/10.1016/j.yebeh.2015.03.019 37. Afrikanova T, Serruys A-SK, Buenafe OEM et al (2013) Validation of the zebrafish pentylenetetrazol seizure model: locomotor versus electrographic responses to antiepileptic drugs. PLoS One 8: e54166. https://doi.org/10.1371/journal.pone.0054166 54. Baraban SC, Taylor MR, Castro PA, Baier H (2005) Pentylenetetrazole induced changes in zebrafish behavior, neural activity and c-fos expression. Neuroscience 131:759–768. https:// doi.org/10.1016/j.neuroscience.2004.11.031 38. Thisse C, Thisse B (2008) High-resolution in situ hybridization to whole-mount zebrafish embryos. Nat Protoc 3:59–69. https://doi. org/10.1038/nprot.2007.514 39. Nieoczym D, Socała K, Gawel K, Esguerra CV, Wyska E, Wlaź P (2019) Anticonvulsant activity of pterostilbene in zebrafish and mouse acute seizure tests. Neurochem Res 44:1043–1055. https:// doi.org/10.1007/s11064-019-02735-2 55. Depaulis A, David O, Charpier S (2016) The genetic absence epi- lepsy rat from Strasbourg as a model to decipher the neuronal and network mechanisms of generalized idiopathic epilepsies. J Neurosci Methods 260:159–174. https://doi.org/10.1016/j. jneumeth.2015.05.022 40. Grone BP, Marchese M, Hamling KR, Kumar MG, Krasniak CS, Sicca F, Santorelli FM, Patel M et al (2016) Epilepsy, behavioral abnormalities, and physiological comorbidities in syntaxin-binding protein 1 (STXBP1) mutant zebrafish. PLoS One 11:e0151148. https://doi.org/10.1371/journal.pone.0151148 56. Glauser T, Ben-Menachem E, Bourgeois B, Cnaan A, Guerreiro C, Kälviäinen R, Mattson R, French JA et al (2013) Updated ILAE evidence review of antiepileptic drug efficacy and effectiveness as initial monotherapy for epileptic seizures and syndromes. Epilepsia 54:551–563. https://doi.org/10.1111/epi.12074 41. Bouleau A, Desvignes T, Traverso JM et al (2014) Maternally inherited npm2 mRNA is crucial for egg developmental compe- tence in zebrafish. Biol Reprod 91:43. https://doi.org/10.1095/ biolreprod.114.119925 57. References Cross JH (2002) Topiramate monotherapy for childhood absence seizures: an open label pilot study. Seizure 11:406–410 58. Faught E (2007) Topiramate in the treatment of partial and gener- alized epilepsy. Neuropsychiatr Dis Treat 3:811–821. https://doi. org/10.2147/ndt.s512 42. Popgeorgiev N, Bonneau B, Gillet JP et al (2018) Control of pro- grammed cell death during zebrafish embryonic development. Recent Advances in Zebrafish Researches. https://doi.org/10. 5772/intechopen.74494 59. Heller AH, Dichter MA, Sidman RL (1983) Anticonvulsant sensi- tivity of absence seizures in the tottering mutant mouse. Epilepsia 24:25–34 43. Saito H, Okada M, Miki T et al (2009) Knockdown of Cav2.1 calcium channels is sufficient to induce neurological disorders ob- served in natural occurring Cacna1a mutants in mice. Biochem Biophys Res Commun 390:1029–1033. https://doi.org/10.1016/j. bbrc.2009.10.102 60. Nakamura J, Tamura S, Kanda T, Ishii A, Ishihara K, Serikawa T, Yamada J, Sasa M (1994) Inhibition by topiramate of seizures in spontaneously epileptic rats and DBA/2 mice. Eur J Pharmacol 254: 83–89. https://doi.org/10.1016/0014-2999(94)90373-5 44. Todorov B, van de Ven RCG, Kaja S et al (2006) Conditional inactivation of the Cacna1a gene in transgenic mice. Genesis 44: 589–594. https://doi.org/10.1002/dvg.20255 61. Hosford DA, Wang Y (1997) Utility of the lethargic (lh/lh) mouse model of absence seizures in predicting the effects of lamotrigine, vigabatrin, tiagabine, gabapentin, and topiramate against human absence seizures. Epilepsia 38:408–414 45. Sztal TE, Ruparelia AA, Williams C, Bryson-Richardson RJ (2016) Using touch-evoked response and locomotion assays to assess mus- cle performance and function in zebrafish. J Vis Exp. https://doi. org/10.3791/54431 62. Sarkisova KY, Kuznetsova GD, Kulikov MA, van Luijtelaar G (2010) Spike-wave discharges are necessary for the expression of behavioral depression-like symptoms. Epilepsia 51:146–160. https://doi.org/10.1111/j.1528-1167.2009.02260.x 46. Uchitel OD, Protti DA, Sanchez V, Cherksey BD, Sugimori M, Llinás R (1992) P-type voltage-dependent calcium channel medi- ates presynaptic calcium influx and transmitter release in mamma- lian synapses. Proc Natl Acad Sci U S A 89:3330–3333. https://doi. org/10.1073/pnas.89.8.3330 68. Studer F, Laghouati E, Jarre G, David O, Pouyatos B, Depaulis A (2019) Sensory coding is impaired in rat absence epilepsy. J Physiol Lond 597:951–966. https://doi.org/10.1113/JP277297 67. Parker AP, Agathonikou A, Robinson RO, Panayiotopoulos CP (1998) Inappropriate use of carbamazepine and vigabatrin in typical absence seizures. Dev Med Child Neurol 40:517–519 Publisher’s Note Springer Nature remains neutral with regard to juris- dictional claims in published maps and institutional affiliations. aggravation of absence seizures. J Pharmacol Exp Ther 319:790– 798. https://doi.org/10.1124/jpet.106.104968 aggravation of absence seizures. J Pharmacol Exp Ther 319:790– 798. https://doi.org/10.1124/jpet.106.104968 https://doi.org/10.1111/j.1528-1167.2009.02260.x 63. Russo E, Citraro R, Scicchitano F, de Fazio S, Perrotta I, di Paola ED, Constanti A, de Sarro G (2011) Effects of early long-term treatment with antiepileptic drugs on development of seizures and depressive-like behavior in a rat genetic absence epilepsy model. Epilepsia 52:1341–1350. https://doi.org/10.1111/j.1528-1167. 2011.03112.x 47. Naranjo D, Wen H, Brehm P (2015) Zebrafish CaV2.1 calcium chan- nels are tailored for fast synchronous neuromuscular transmission. Biophys J 108:578–584. https://doi.org/10.1016/j.bpj.2014.11.3484 64. Blumenfeld H, Klein JP, Schridde U, Vestal M, Rice T, Khera DS, Bashyal C, Giblin K et al (2008) Early treatment suppresses the development of spike-wave epilepsy in a rat model. Epilepsia 49: 400–409. https://doi.org/10.1111/j.1528-1167.2007.01458.x 48. Wen H, Linhoff MW, Hubbard JM, Nelson NR, Stensland D, Dallman J, Mandel G, Brehm P (2013) Zebrafish calls for reinter- pretation for the roles of P/Q calcium channels in neuromuscular transmission. J Neurosci 33:7384–7392. https://doi.org/10.1523/ JNEUROSCI.5839-12.2013 65. Lasoń W, Dudra-Jastrzębska M, Rejdak K, Czuczwar SJ (2011) Basic mechanisms of antiepileptic drugs and their pharmacokinetic/pharmacodynamic interactions: an update. Pharmacol Rep 63:271–292 49. Granato M, van Eeden FJ, Schach U, Trowe T, Brand M, Furutani- Seiki M, Haffter P, Hammerschmidt M et al (1996) Genes control- ling and mediating locomotion behavior of the zebrafish embryo and larva. Development 123:399–413 66. Liu L, Zheng T, Morris MJ, Wallengren C, Clarke AL, Reid CA, Petrou S, O'Brien TJ (2006) The mechanism of carbamazepine 1916 Mol Neurobiol (2020) 57:1904–1916 Publisher’s Note Springer Nature remains neutral with regard to juris- dictional claims in published maps and institutional affiliations.
https://openalex.org/W3138526354
https://link.springer.com/content/pdf/10.1007/s11896-021-09444-z.pdf
English
null
From Witness to Web Sleuth: Does Citizen Enquiry on Social Media Affect Formal Eyewitness Identification Procedures?
Journal of police and criminal psychology
2,021
cc-by
7,928
Abstract Eyewitnesses to crimes may seek the perpetrator on social media prior to participating in a formal identification proce- dure, but the effect of this citizen enquiry on the accuracy of eyewitness identification is unclear. The current study used a between-participants design to address this question. Participants viewed a crime video, and after a 1–2-day delay were either exposed to social media including the perpetrator, exposed to social media that substituted an innocent suspect for the perpetrator, or not exposed to social media. Seven days after viewing the crime video, all participants made an identification from a video lineup. It was predicted that exposure to social media that did not contain the guilty suspect would reduce the accuracy of subsequent identifications. Analysis revealed no association between social media exposure and lineup response for target present lineups. For target absent lineups, there was a significant association between social media exposure and lineup response, but this was driven by a higher number of correct rejections for participants who saw the guilty suspect on social media. The results suggest that at least in some circumstances, witnesses searching social media do not have a nega- tive effect on formal ID procedures. Keywords  Eyewitness · Memory · Social media · Web sleuthing · Identification Keywords  Eyewitness · Memory · Social media · Web sleuthing · Identification From Witness to Web Sleuth: Does Citizen Enquiry on Social Media Affect Formal Eyewitness Identification Procedures? C. Havard1   · A. Strathie1 · G. Pike1 · Z. Walkington1 · H. Ness1 · V. Harrison1 Accepted: 11 March 2021 / Published online: 22 March 2021 © The Author(s) 2021 1 School of Psychology, Faculty of Arts & Social Sciences, The Open University, Milton Keynes MK6 6AA, UK Journal of Police and Criminal Psychology (2023) 38:309–317 https://doi.org/10.1007/s11896-021-09444-z Journal of Police and Criminal Psychology (2023) 38:309–317 https://doi.org/10.1007/s11896-021-09444-z * C. Havard catriona.havard@open.ac.uk Introduction For example, in response to a police request for help in identifying the perpetrators of a hate crime in Philadelphia, a group of Twitter users worked collectively (0121 3456789) 3 Journal of Police and Criminal Psychology (2023) 38:309–317 310 Codes of Practice 2017) have been updated to detail how evidence should be recorded in the wake of a social media identification, but the update does not consider the effect of social media use on the accuracy of subsequent formal identifications. There has, however, been guidance from the National Visual and Voice Identification Strategy Group (NVVISG) that recommends that the identification officer obtains as much information about the informal identifica- tion to ensure that the best evidence is produced for court. This evidence would include not only the image(s) that the witness saw but also what the witness did, such as how they searched social media or were able to see the image and also why they did it (Kirk et al. 2014). The guidance does not state whether the informal identification of social media images will influence later formal identification from a video lineup, and as this a relatively novel phenomenon, psycho- logical research to inform this issue is also lacking. to match police CCTV footage to social media images. They helped identify several of those involved in the attack, and an investigating officer ‘tweeted’ his thanks to the citizen investigators (Shaw 2014). The previous examples are of large-scale collective public activity in response to high-profile crimes, but those who have directly witnessed a criminal act may also conduct investigations on a smaller scale. Taking advantage of the unrestricted access to images and personal data that may be offered by social media, an eyewitness might attempt to make a ‘Facebook identification’ (Mack and Sampson 2013), in advance of attending an official police lineup. These actions may be well-intentioned, and the appeal of an immediate online identification is easy to see; however, in many juris- dictions, visual identification of criminal suspects is gov- erned by strict guidelines. In England and Wales, police fol- low guidelines for showing video lineups as set out by Code D of the Police and Criminal Evidence Act (PACE 1984; Codes of Practice 2017) and police officers must adhere to these regulations to avoid prejudicing the identification pro- cess. Introduction Informal identifications via social media bypass the safeguards enshrined in a properly conducted police lineup, which can create complications when these cases come to trial, and social media identifications have resulted in appeals in courts in the UK. This evidence would include not only the image(s) that the witness saw but also what the witness did, such as how they searched social media or were able to see the image and also why they did it (Kirk et al. 2014). The guidance does not state whether the informal identification of social media images will influence later formal identification from a video lineup, and as this a relatively novel phenomenon, psycho- logical research to inform this issue is also lacking. Although there has been little, if any, research directly exploring the impact of searching social media on an eye- witness’s subsequent decision at a lineup, there has been a considerable amount of research exploring the impact of other forms of post-event information on eyewitness mem- ory more generally. In a review, Loftus (2005) suggested that in the real-world, a witness’s memory may be affected by misinformation presented by conversing with other wit- nesses, leading questions asked by law enforcement per- sonnel and by media coverage. Paterson and Kemp (2006) compared the impact of these three sources of potential post- event information, finding that where incorrect information was presented that all three can adversely affect memory. Interestingly, ‘co-witness’ information (resulting from two witnesses conferring) appeared to exert a more powerful influence than media reports and even leading questions, a result observed previously in research on co-witness effects (e.g. Shaw 1997).f There have been several documented instances in the UK when witnesses have used Facebook to conduct their own investigations prior to a formal identification pro- cedure. One example is the case of Daniel McGill and Gordon Alexander who were convicted of a robbery after being identified through Facebook by their victim, who relayed the information to the police (R v Alexander and McGill 2012). Both men were then selected from a subse- quent video parade; however, the Court of Appeal claimed the identification from Facebook had been unfair, as the evi- dence had not been presented at court (Hargreaves 2020). Introduction the perpetrator (Mack and Sampson 2013). As this type of online citizen enquiry takes place during the investigatory stage, it may have implications for the evidence gathered by the police, and for the outcome of formal visual identifica- tion procedures. The easy access to information afforded by the worldwide web offers many advantages, but the negative impact it has had on the legal system is well documented. Case details that were easily guarded in the pre-internet age are now freely available, which may compromise a defendant’s right to a fair trial. High-profile contempt of court convic- tions for jurors who investigated a defendant’s previous convictions online (BBC News 2017), contacted a defend- ant via social media (BBC News 2011), or canvassed the opinions of their friends in deciding the outcome of a case (Khan 2008) illustrates the breadth of the problem; they also show that courts are responding to the threat within exist- ing legal frameworks. However, online citizen enquiry is not limited to juror activity during criminal trials, as crime victims and eyewitnesses may also conduct online investiga- tions shortly after experiencing a crime in order to identify The term ‘web sleuthing’ has been adopted to describe such public use of online resources to conduct amateur crime investigations (Yardley et al. 2018). A high-profile example of this occurred in response to the Boston Marathon bomb- ing in 2013, when ‘Reddit’ users crowd-sourced imagery from the crime scene and conducted their own enquiry, concurrent with the official police investigation (Nhan et al. 2017). The citizen investigators publicly named several sus- pects, resulting in harassment and distress for the implicated individuals and their families (Lee 2013). The official inves- tigation revealed that none of those accused by the ‘web sleuths’ had any involvement in the attacks (Lee 2013; Nhan et al. 2017), and Reddit issued a public apology for their role in the affair (BBC News 2013). While this case illustrates the problems of amateur investigations, there can also be advantages. Introduction In another more recent case, three eyewitnesses to a fight that involved the victim being stabbed were all shown a social media image of the defendant by a third party prior to a formal identification procedure (R v Phillips 2020). During the trial, the judge specifically addressed the identification from social media and asked each witness in turn whether the defendant was the person they had witnessed commit the offence or simply the person whose social media image they had been shown. The Court of Appeal emphasised that where an identification had been made via social media, the jury should consider the weakness of this form of identi- fication, as during a formal identification procedure (e.g. lineup), the witness might be identifying the person viewed on social media, rather than the actual offender (Gledhill and Noble 2020). Much of the research on the effects of post-event informa- tion on eyewitness memory has focused on memory for details of the event, but there are also studies that have shown both verbal and visual forms of post-event information can affect memory for the perpetrator’s face (Sporer 1996). Loftus and Greene (1980) demonstrated that memory of the perpetrator’s appearance could be distorted by reading a misleading verbal description, whilst the effects of visual forms of post-event information have been explored in studies examining informal identification procedures, such as mugshot inspection (where the police show eyewitnesses ‘mugshot’ images of suspects prior to holding an official lineup), and street identification (where the police take a witness to a particular place, often driving around the vicinity of the crime scene, to see if they can spot the perpetrator) illustrates the potential risks (.g. Blunt and McAllister 2009; Brown et al. 1977; Godfrey and Clark 2010; Gorenstein and Ellsworth 1980; Memon et al. 2002; Valentine et al. 2012). A meta-analysis of 32 studies In response to the increase of searches for defendants on social media, guidelines in England and Wales (PACE 1984; 1 3 1 3 Journal of Police and Criminal Psychology (2023) 38:309–317 311 that this practice has on the accuracy of a subsequent video line-up identification is unknown.l examining the effect of an intervening mugshot task on lineup accuracy revealed that this both reduced the number of correct identifications and increased the incidence of innocent suspects being selected from a lineup (Deffenbacher, et al. 2006). Design The experiment employed a 3 × 2 between-participants design. The first factor was ’Type of Social Media Exposure’, with three levels: Guilty Suspect (exposure to social media containing the perpetrator), Innocent Suspect (exposure to social media containing an innocent suspect), and Control (no social media exposure). The factor was Lineup Type, with two levels: Target Present (guilty suspect included in the lineup) and Target Absent (innocent suspect included in the lineup in place of guilty suspect). The first depend- ent variable was accuracy on the lineup task. In the Target Present (TP) lineups, participants could make one of three response types: a correct identification (Hit), a foil identi- fication (False Alarm), or an incorrect rejection (Miss). In Target Absent (TA) lineups, participants could make one of three response types: a correct rejection, an innocent suspect identification, or a foil identification. Data from the TP and TA lineups were analysed separately. The second dependent variable was confidence, measured on a 7-point scale from 1 (very unsure) to 7 (very sure). Under PACE code D (PACE 1984; Codes of Practice 2017), a video lineup is the preferred method of suspect identification, and the shortcomings of informal police identification meth- ods are recognised. If suspects are identified via uncontrolled viewing of films or photographs, such as social media, then according to the PACE guidelines, the witness should be asked to give as much detail as possible in regard to the circumstances and conditions under which the viewing took place. Although there is some limited guidance on procedures for when a wit- ness views a social media image prior to seeing a formal iden- tification procedure (Kirk et al. 2014; PACE 1984; Codes of Practice 2017), the police have no control over the amateur use of social media sites for suspect identification, and the impact Introduction In addition, there is evidence that as mugshot inspection involves the witness in multiple identification procedures, it can cre- ate a ‘commitment effect’, such that a witness who selects a mugshot image is more likely to select that same person in a subsequent lineup, regardless of the accuracy of the initial decision (e.g. Blunt and McAllister 2009; Brown et al. 1977; Gorenstein and Ellsworth 1980; Memon et al. 2002). This effect has also been observed in experimental investigations of street identification which has revealed that repeated iden- tification procedures can increase the choosing of foils, and innocent suspects, but often have little effect on guilty suspects (e.g. Godfrey and Clark 2010; Valentine et al. 2012). Evidence for the commitment effect has also found in an analysis of real-world police data, where lineups were conducted follow- ing street identifications. In this research, the majority (84%) of suspects identified in the street were later identified from a video lineup; however, whether those suspects were later found guilty in court was not known (Davis et al. 2015). i The aim of the current study is to investigate the influ- ence of social media exposure of potential suspects on the accuracy of identification from a subsequent video lineup. As previous research has shown that intervening mugshot exposure increases the rate of false identifications in line- ups, it is predicted that exposure to intervening target absent social media images will reduce accuracy in the subsequent lineup task in the same way. Participants One hundred and twenty members of staff at The Open University participated in the experiment (96 female). Par- ticipants received a £5 shopping voucher as recompense for their time. Participants were aged between 22 and 67 years (M = 43.8, SD = 10.8), and all had normal, or corrected-to- normal, vision. In the UK video, lineups now largely replaced live lineups, and research has shown that video lineups are a less biased than live lineups in actual criminal cases (Valentine et al. 2003) and less stressful than live lineups (Brace et al. 2009). When comparing video lineups and static photo lineups, video lineups can reduce the false choosing of lineup members from tar- get absent lineups as compared to photo lineups for adults and children, without reducing the correct identifica- tions from target present lineups (Havard et al. 2010; Valentine et al. 2007). Furthermore, when witnesses are shown a video lineup, to provide safeguards against mistaken recognition, they are always told that person they saw ‘may, or may not, be present and if they cannot make an identification, they should say so’ and they are shown the lineup twice before being asked to make a decision (PACE 1984; Codes of Practice 2017). Procedure The experiment took place over three sessions. During the first session, participants took part in a briefing session and provided basic demographic information, before view- ing the crime video. This session lasted approximately 10 min. The second session took place either 1 or 2 days later. At the start of the second session, all participants com- pleted the filler task, the Need for Closure Questionnaire (Kruglanski et al. 2013), which was presented on-screen using Qualtrics software (Qualtrics, Provo, UT). The Need for Closure Questionnaire (Kruglanski et al. 2013), which consists of 42 questions designed to assess an individual’s need for cognitive closure (and a further five which form a ‘lie scale’), was administered to all participants as a filler task. Photos typical of those used on social media were used to populate the profile pages with images. For the experi- mental manipulation, two versions of a profile page were created for the character ‘David Brown’, one contained photos of the suspect in the crime video (the Guilty Sus- pect condition), and the other contained photos of the innocent suspect (the Innocent Suspect condition). Real photos were supplied by the guilty and innocent suspect actors, taken from their personal social media accounts. The actors were matched in terms of age, build, and gen- eral appearance.i After completing the questionnaire, the participants were then randomly assigned to one of three social media exposure conditions. Those in the experimental conditions viewed the “Friendface” social media site and were given time to explore the site freely. In the ‘Guilty suspect’ con- dition, the perpetrator was included in the social media content; in the ‘Innocent Suspect’ condition, an innocent suspect replaced the perpetrator in the social media con- tent. Participants in each of the two experimental con- ditions were asked to search the mock social media site for the person they had seen committing the theft in the video. They were free to explore the site for as long as they wanted. When they were finished exploring the site, they were asked to tell the experimenter if the perpetrator was present or not, and if present, to supply the name from the social media profile. Participants in the control group did not engage with social media after completing the filler task, so did not make any identification during this session. Materials A short mock crime video was created using a Caucasian male as the target. The film showed two seated women talking while a man stole a handbag from the back of one of their chairs. The man is then seen outside removing the 1 3 312 Journal of Police and Criminal Psychology (2023) 38:309–317 handbag’s contents before throwing the bag away. The film lasted approximately 1 min and 30 s, and the target was visible in both full-face and profile views during the film. same foils were used for TP and TA conditions. All of the videos for the lineup were filmed under the same lighting conditions. ii To expose participants to social media images, an interactive mock social media site called “Friendface” was created using Microsoft PowerPoint. An event page was created for a fake community centre open day, where the mock crime was purported to have taken place. This page contained photos from the event, and names and thumbnail pictures of people who had indicated interest in attending. There were twelve identities in the “Attend- ing” category, and a further twelve in the “Maybe” cat- egory, with equal numbers of men and women in each group. By clicking on these thumbnail images, partici- pants could view the “profile pages” of these individu- als; these pages included a larger version of the thumb- nail image profile picture, and three further images of each individual. Procedure The profile, and every other aspect of the social media site, was otherwise the same in both conditions, and the profile always appeared in the ‘maybe attending’ category on the event page. The images for the additional 23 pro- file pages were obtained from the People In Photo Albums (PIPA) dataset (Zhang et al. 2015), consisting of over 60,000 instances of around 2000 individuals, which originated from Flickr photo albums. p Four 9-person video lineups were created using PRO- MAT Video Identification Parade Software. Half of the lineups were Target Present (TP) and half Target Absent (TA). The Promat software was used to vary the position of the target in the line-up across participants. The guilty suspect and innocent suspect were filmed using stand- ard PROMAT guidelines. The films showed the head and shoulders of each person framed against the green PROMAT background. First the suspects are shown looking straight at the camera, and then they are shown turning their head to the right, then to the left, then back to facing straight ahead. Foils were chosen from the PROMAT database by searching based on keywords related to the suspect’s description (sex, ethnicity, age range, hair style), which yielded a selection of potential foils that matched the suspect’s general appearance. The i The third session took place 7 days after the initial ses- sion. All participants were required to make an identi- fication from a PROMAT video lineup and to rate their confidence in this decision. Each participant was tested individually. Half of the participants viewed a TP lineup, and half viewed a TA lineup. Prior to viewing the lineup, the participants were told ‘Today I am going to show you a video that has pictures of different people in it and the man you saw in the film may or may not be there. We will watch the video twice. When we’ve watched the video I will ask you if you can see the man from the film and if you see him tell me what number he is’. Video Lineup Identification The relationship between confidence and accuracy was examined separately for Target Absent and Target Present Lineups. A 3 x× 2 ANOVA with Social Media Condition (Control/Guilty Suspect/Innocent Suspect) and Lineup Accuracy (Correct/Incorrect) as factors was conducted for each of the two lineup types. In the TP lineups, 85.2% of participants (52 out of 61) cor- rectly identified the perpetrator, 6.6% (4) made an incorrect rejection, and the final 8.2% (5) made a false identification. In TA lineups, 45.8% made a correct rejection (27 out of 59), 13.6% (8) identified the matched distractor (I.e. the innocent suspect), and 54.2% (24) falsely identified another foil. Table 1 shows the percentage of response types in each category. For TP lineups, the main effect of Lineup Accuracy was significant (F (1,55) = 7.67, p = .008, η2 = .122) and the mean confidence score was higher for those who made accu- rate lineup decisions (M = 5.6) than for those who made inaccurate decisions (M = 4.6). There was no main effect of social media condition on confidence (F (2,55) = 1.34, p = .268, η2 = .047), and the interaction was non-significant (F (2,55) = .106, p = .899, η2 = .004]. For TA lineups, the main effect of Lineup Accuracy was non-significant (F (1,53) = .003, p = .96, η2 < .000) and the mean confidence score was similar for those who made accurate lineup deci- sions (M = 4.84) and those who made inaccurate decisions (M = 4.82). There was no main effect of social media condi- tion on confidence (F (2,53) = .585, p = .561, η2 = .022), and the interaction was non-significant (F (2,53) = 1.17, p = .319, η2 = .042). For TP lineups, the main effect of Lineup Accuracy was significant (F (1,55) = 7.67, p = .008, η2 = .122) and the mean confidence score was higher for those who made accu- rate lineup decisions (M = 5.6) than for those who made inaccurate decisions (M = 4.6). There was no main effect of social media condition on confidence (F (2,55) = 1.34, p = .268, η2 = .047), and the interaction was non-significant (F (2,55) = .106, p = .899, η2 = .004]. For TA lineups, the main effect of Lineup Accuracy was non-significant (F (1,53) = .003, p = .96, η2 < .000) and the mean confidence Results Table 1 shows that for TP lineups, response patterns were similar across conditions, and the results of the chi-square analysis confirmed there was no significant effect of social media exposure on lineup response (χ2 (4, N = 61) = 2.1, p = .711, V = .13 n.s.). For TA lineups, the chi-square analy- sis showed the effect of social media exposure on lineup response was significant (χ2 (4, N = 59) = 9.6, p = .047, V = .29). Looking at Table 1, this is likely due to an elevated rate of correct rejections in the ‘Guilty Suspect’ condition compared to the other two conditions. Social Media Identification When participants were exposed to the guilty suspect social media condition, 76.2% (32 out of 42) were able to correctly identify the guilty suspect from the social media, 14.3% (6) made incorrect rejections, and 9.5% (4) falsely identified an alternative. When participants were exposed to social media in the Innocent Suspect condition, 56.4% (22 out of 39) made correct rejections, 7.7% (3) falsely identified the matched distractor, and 35.9% (14) falsely identified another person on the social media site. Procedure Following the PROMAT protocol, and Code D of PACE (PACE 1984; Codes of Practice 2017), each lineup was 3 3 313 Journal of Police and Criminal Psychology (2023) 38:309–317 either TP (χ2 (1, N = 41) = .81, p = .37, V = .14) or TA (χ2 (1, N = 40) = .84, p = .36, V = .15] lineups.f presented sequentially via a laptop, and the lineup was shown twice before the witness was asked to make a decision. either TP (χ2 (1, N = 41) = .81, p = .37, V = .14) or TA (χ2 (1, N = 40) = .84, p = .36, V = .15] lineups.f To examine the effect of social media exposure on lineup identification decisions, separate analyses were conducted for TP and TA lineups. The Relationship Between Social Media Identification and Video Lineup Identification The accuracy of social media identification was not signifi- cantly associated with accuracy of lineup identification for Table 1   Lineup responses in percentages (frequencies in parenthe- ses), as a function of social media condition (control/guilty suspect on SM/innocent suspect on SM) and line-up composition (TP/TA) Social media condition Lineup response Control Guilty suspect Innocent suspect Total Target Present Correct ID 80 (16) 86.4 (19) 89.5 (17) 85.2 (52) Foil ID 15 (3) 4.5 (1) 5.3 (1) 8.2 (5) Incorrect rejection 5 (1) 9.1 (2) 5.3 (1) 6.6 (4) Target Absent Correct rejec- tion 31.6 (6) 70 (14) 35 (7) 45.8 (27) Innocent suspect 10.5 (2) 5 (1) 25 (5) 13.6 (8) Other foil ID 57.9 (11) 25 (5) 40 (8) 40.7 (24) Table 1   Lineup responses in percentages (frequencies in parenthe- ses), as a function of social media condition (control/guilty suspect on SM/innocent suspect on SM) and line-up composition (TP/TA) Discussion When the target was present in the lineup, accuracy was high across the three conditions, and exposure to social media did not significantly affect lineup identification decisions. When the target was absent from the lineup, social media exposure did affect identification decisions; however, this effect was driven by an increase in correct rejections for participants who saw the perpetrator on social media, rather than the predicted increase in false identifications following exposure 1 3 1 Journal of Police and Criminal Psychology (2023) 38:309–317 314 could be confused for the target on the mock social-media site, and this may have contributed to a lower error rate in the current study; however, this explanation is not entirely consistent with the findings of Deffenbacher et al. (2006) meta-analysis. to the guilty suspect on social media. For participants in the social media exposure groups, the accuracy of their social media identification was not related to the accuracy of their lineup identification. i Control participants did not make an identification from social media, so the PROMAT lineup, which took place 7 days after viewing the mock crime video, was the only form of identification for this group. While the PROMAT video lineup and the Social Media Identification differ on several dimensions, and therefore cannot be directly compared, the percentage correct identification for control TP PROMAT lineups (80%) is similar to the accuracy for the social media TP identification (76%). This suggests that where a guilty suspect is encountered on social media, the accuracy of the subsequent identification may not be substantially compro- mised by the medium in which they are encountered. The percentage of correct rejections in the social media iden- tifications (56.4%) was higher than the percentage of cor- rect rejections in the control TA PROMAT lineups (31.6%), which may reflect the higher number of realistic distrac- tors present in the PROMAT lineups compared to the mock social media site, which contained few identities that resem- bled the guilty suspect. y In the studies included in Deffenbacher et al.’s meta- analysis, the number of mugshots participants viewed varied between 12 and 60 (median = 21), and studies in which par- ticipants viewed more than the median number of mugshots did not generate a reliably negative effect on the accuracy of subsequent identifications. Discussion The five studies that used fewer than the median number of interpolating mugshots did pro- duce a reliable negative effect on subsequent identifications. This suggests that a small number of intervening mugshots may have a more damaging effect on accuracy than a large number. However, in the current study, the number of identi- ties that could be confused with the target is low in compari- son with the bottom half of the median-split in Deffenbacher et al.’s meta-analysis, so the possibility that there were too few realistic distractors on the mock social media site to generate an effect cannot be ruled out. On the other hand, the studies in the Deffenbacher et al. meta-analysis that exposed participants to a large number of images did not have a del- eterious effect on the accuracy of subsequent lineup identi- fications. In the current study, participants were exposed to an array of 32 identities on a single page, so if the effect is driven by the quantity of faces seen, rather than the quality of the matches, this could explain the lack of impairment following social media exposure in the current task. Further research could vary the number and similarity of the identi- ties viewed on social media to distinguish between these two competing explanations. In the studies included in Deffenbacher et al.’s meta- analysis, the number of mugshots participants viewed varied between 12 and 60 (median = 21), and studies in which par- ticipants viewed more than the median number of mugshots did not generate a reliably negative effect on the accuracy of subsequent identifications. The five studies that used fewer than the median number of interpolating mugshots did pro- duce a reliable negative effect on subsequent identifications. The prediction that social media exposure would nega- tively affect the accuracy of subsequent identification deci- sions was not supported for either TA or TP lineups in the current study. This finding contrasts with the results of a meta-analysis on intervening mugshot inspection (Deffen- bacher et al. 2006), which demonstrates that this practice is associated with a reduction in correct identifications, and an increase in false identifications, on subsequent lineup tasks. Similarly, research on street identifications suggests they negatively affect the accuracy of subsequent identifications (Godfrey and Clark 2010; Valentine et al. 2012). Discussion As such, the study used a single target identity, and while it offers a useful starting point in investigating how social media expo- sure affects lineup identification, further research is required to validate the findings with multiple identities. i Importantly, this research demonstrates that exposure to interpolating images between witnessing a crime and taking part in a formal identification procedure does not always have a cost for accuracy. While previous research on mugshot exposure (e.g. Deffenbacher et al. 2006) and street identifications (e.g. Davis et al. 2015) demonstrates that these practices may harm subsequent lineup identi- fications, the current study offers the first indication that social media exposure does not have similar consequences. This suggests that the decisions of appeal courts to uphold convictions where a social media identification preceded a formal identification procedure may be well founded. How- ever, in the current study the social media exposure was presented to participants without bias or additional context, which may not be reflective of most real-world experi- ences. In the appeal case cited (R v Alexander and McGill, 2012), there were additional factors (e.g. cues from friends, repeated viewing of the imagery) which may have a greater influence on subsequent decisions compared to social media exposure alone. Until the effect of these additional factors is established, social media identifications should be consid- ered with caution. Jenkins et al. (2011) propose that an individual image is a poor representation of a face because appearance varies across images, and within-person variation can be greater than between-person variation. This means that two images of the same person may differ to a greater extent than images of two different people. In their study they administered a card-sorting task, which required people to divide sets of 40 facial images (20 × 2 individuals), into their constituent identities. When participants unfamiliar with the people in the images performed the task, the median number of piles was 7.5; when participants familiar with the identities sorted the same image sets, the median number of piles was 2. Interestingly, while participants made errors in separating each of the two identities into several different piles, they did not create piles that mixed the two identities. Discussion In addition, for the TP lineups, even if participants picked someone else from the social media, that identity would not appear in the final lineup, so the perpetrator is the only identity in the lineup to which partici- pants have been previously exposed. These factors should be explored in future studies.f results in the current study is consistent with the idea that exposure to multiple images of the perpetrator offered partic- ipants an understanding of the way in which his face varies, creating a more robust representation of that individual face that could not accommodate any of the foils. This finding builds on existing theory on within-person variability by demonstrating that exposure to facial variation also benefits face learning in an eyewitness memory paradigm.f little room for error. In addition, for the TP lineups, even if participants picked someone else from the social media, that identity would not appear in the final lineup, so the perpetrator is the only identity in the lineup to which partici- pants have been previously exposed. These factors should be explored in future studies. Although there was no effect of social media exposure on TP lineup identifications there was a significant effect on TA lineups. Contrary to our prediction, this difference was driven by higher accuracy for those who saw the perpetrator on social media, relative to the control and distractor condi- tions. This suggests that social media exposure to the correct perpetrator helps participants to correctly reject target absent lineups, but social media exposure to an innocent suspect does not increase false alarms relative to controls. The find- ing that viewing additional images of the perpetrator is ben- eficial for subsequent facial identification is consistent with research on face memory conducted by Bruce (1982), which demonstrated that differences between images at study and test (e.g. change of expression) carry a high cost for correct identification. More recently, research on face matching has focussed on within-person variability, and the challenge of ‘telling people together’ (e.g. Jenkins et al. 2011; Burton et al. 2016). The current finding could be accommodated within this theoretical framework. While the current study offers useful insights into the effect of social media exposure on subsequent identification procedures, because the study was designed to simulate real- world conditions, it was necessarily very time-consuming and involved testing people over several sessions. Discussion However, while exposure to intervening images is common to both the current study and previous research on intervening identifi- cation tasks, there are a number of differences between these approaches that may account for the conflicting findings. Although the current results contrast with research on mugshot exposure, they are similar to the findings of recent research investigating the effect of facial composite con- struction on the accuracy of subsequent lineup identification. Whilst a few studies have reported that composite construc- tion appears to increase misidentification rates (e.g. Wells et al. 2005), the majority of studies have either reported no effect (e.g. Pike et al. 2020, 2019) or even a beneficial effect (e.g. Davis et al. 2014), and a recent meta-analysis concluded that composite construction does not appear to affect lineup decision (Tredoux et al. 2020). li First, mugshot studies aim to simulate situations in which police show the images to witnesses, so the images are standardised and are chosen to match the appearance of the perpetrator. In contrast, the current study aims to simulate the unconstrained viewing of social media images prior to making a formal identification, so the images and identities are necessarily more diverse. The fake social media site that was used to expose participants to facial images in the cur- rent study contained an array of 32 identities, 16 of which were male, but only one of these was specifically selected to be similar to the target in appearance. Examination of the false alarms from the social media identification data shows that only the matched distractor and two other identities were ever mistakenly identified from this stage of the study. This raises the possibility that there were few identities that f Considering TP performance, accuracy was high across all three conditions, with relatively few participants incor- rectly rejecting the target or making false identifications in the final lineup. This may indicate that the task was not diffi- cult enough. The mock-crime video used in the current study was very high quality, and the perpetrator’s face was vis- ible from a number of angles, including in close-up. While the aim was to simulate the experience of witnessing a live crime, the range and quality of the footage may have offered views that exceeded those of real-life encounters, leaving 1 3 3 3 315 Journal of Police and Criminal Psychology (2023) 38:309–317 little room for error. Discussion The errors were with ‘telling people together’, that is thinking there were more identities than were present, rather than mistaking two different identities as being the same person.fi As the use of social media by citizens conducting their own investigations is becoming more commonplace, policy makers need to consider the impact that this can have on more formal identification procedures. There have been some suggested guidelines from the National Visual and Voice Identification Strategy Group (NVVISG) that could help to inform legislation (Kirk et al. 2014) and from the legal profession (McGorrey 2016). Guidelines for the police suggest that suspect descriptions should be obtained as soon as possible from a witness, followed by a formal identifica- tion procedure, prior the opportunity for any self-directed searches on social media and that the police should also advice the witness to avoid searching for the suspect on social media (McGorrey 2016). The NVVISG guidelines f Jenkins et al. (2011) offer this finding as evidence that exposure to multiple images of a face under different condi- tions helps form a robust representation, incorporating indi- vidual variation in appearance. Importantly, as variation is idiosyncratic, the benefits of exposure to facial variation are specific and do not generalise to other identities. Further research has shown that exposure to multiple images of a face benefits performance on a subsequent matching task, which suggests that facial variability exposure offers a fast- track to face learning (Andrews et al. 2015). The pattern of 1 3 1 Journal of Police and Criminal Psychology (2023) 38:309–317 316 identification parades. Int J Police Sci Manag 11(2):183–192. https://​doi.​org/​10.​1350/​ijps.​2009.​11.2.​122 suggest obtaining as much information as possible about the informal identification the witness had taken part in to ensure that the best evidence is produced. This evidence would consist of not only the image(s) that the witness saw but also the process by which they were obtained, and whether they were guided by another party to the images. Then when the evidence is presented in court, the jury should be made aware of the informal identification proce- dure and its potential pitfalls, such as a witness identifying someone they have seen on social media, rather than actually identifying the suspect they saw commit the offence. p g jp Brown E, Deffenbacher K, Sturgill W (1977) Memory for faces and the circumstances of encounter. J Appl Psychol 62(3):311–318. Conflict of Interest  The authors declare no competing interests. Conflict of Interest  The authors declare no competing interests. Conflict of Interest  The authors declare no competing interests. Open Access  This article is licensed under a Creative Commons Attri- bution 4.0 International License, which permits use, sharing, adapta- tion, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. Gorenstein GW, Ellsworth PC (1980) Effect of choosing an incorrect photograph on a later identification by an eyewitness. J Appl Psy- chol 65(5):616–622. https://​doi.​org/​10.​1037/​0021-​9010.​65.5.​616i Hargreaves, B. (2020, December 9) Social media and identification. Carmelite Chambers https://​www.​carme​litec​hambe​rs.​co.​uk/​blog/​ blog-​social-​media-​and-​ident​ifica​tionf i Havard C, Memon A, Clifford B, Gabbert F (2010) A comparison of video and static photo lineups with child and adolescent witnesses. Appl Cogn Psychol 24:1209–1221. https://​doi.​org/​10.​1002/​acp.​1645 Jenkins R, Van Montfort X, White D, Burton AM (2011) Variability in photos of the same face. Cognition 121(3):313–323 Kirk A, Waterman K, Monaghan A, Sherrington L (2014) Internet Social Media and Identification Procedures. Guidance produced by the National Visual and Voice Identification Strategy Group (NVVIS) https://​libra​ry.​colle​ge.​police.​uk/​docs/​APPREF/​NVVIS-​Guida​nce-​ on-​Inter​net-​Social-​Media-​and-​Ident​ifica​tion-​Proce​dures.​pdf Discussion https://​doi.​org/​10.​1037/​0021-​9010.​62.3.​311 p g Bruce V (1982) Changing faces: Visual and non-visual coding pro- cesses in face recognition. Bri J Psychol 73(1):105–116. https://​ doi.​org/​10.​1111/j.​2044-​8295.​1982.​tb017​95.x Burton AM, Kramer RSS, Ritchie KL, Jenkins R (2016) Identity from variation: representations of faces derived from multiple instances. Cogn Sci 40(1):202–223. https://​doi.​org/​10.​1111/​cogs.​12231i Davis J, Valentine T, Memon A, Roberts A (2015) Identification on the street: a field comparison of police street identifications and video line-ups in England. Psychol Crime Law 21:9–27. https://​doi.​org/​ 10.​1080/​10683​16X.​2014.​915322l Acknowledgements  We are grateful to Steff Reicher and Camilla Elphick who collected data for this study. Davis JP, Gibson S, Solomon C (2014) The positive influence of creating a holistic facial composite on video line-up identifi- cation. Appl Cogn Psychol 28(5):634–639. https://​doi.​org/​10.​ 1002/​acp.​3045 Funding  This work was supported by a Police Knowledge Fund grant from HEFCE and the Home Office. Deffenbacher KA, Bornstein BH, Penrod SD (2006) Mugshot Exposure Effects: Retroactive Interference, Mugshot Com- mitment, Source Confusion, and Unconscious Transference. Law Hum Behav 30(3):287–307. https://​doi.​org/​10.​1007/​ s10979-​006-​9008-1i Declarations Ethical Approval  The study adhered to the British Psychology Guidelines Code of Ethics and Conduct (2018) and received ethical approval from the Open University Human Research Ethics Committee (HREC). Gledhill S, Noble G (2020) The impact of social media on identifi- cation procedures. 3 Temple Gardens. https://​www.​3tg.​co.​uk/​ libra​ry/​theim​pacto​fsoci​almed​iaoni​denti​ficat​ionpr​ocedu​res.​pdf i Godfrey RD, Clark SD (2010) Repeated eyewitness identifica- tion procedures: Memory, decision-making, and probative value. Law Hum Behav 34:241–258. https://​doi.​org/​10.​1007/​ s10979-​009-​9187-7 References i Khan U (2008, November 24) Juror dismissed from a trial after using Facebook to help make a decision. The Telegraph. Retrieved from: http://​www.​teleg​raph.​co.​uk Andrews S, Jenkins R, Cursiter H, Burton AM (2015) Telling faces together: Learning new faces through exposure to multiple instances. Q J Exp Psychol 68(10):2041–2050. https://​doi.​org/​ 10.​1080/​17470​218.​2014.​10039​49 Kruglanski AW, Atash MN, De Grada E, Mannetti L, Pierro A (2013) Need for Closure Scale (NFC). Retrieved from https://​www.​mids.​ b f h i l i BBC News (2013) Reddit apologises for Boston bombings witch hunt. BBC News Technology. Retrieved from: http://​www.​bbc.​co.​uk/​ news/​techn​ology-​22263​020 Lee D (2013) Boston bombing: How internet detectives got it very wrong. BBC News Technology. Retrieved from http://​www.​bbc.​ co.​uk/​news/​techn​ology-​22214​511 BBC News (2011) Facebook juror sentenced to eight months for con- tempt. Retrieved from: http://​www.​bbc.​co.​uk/​news/​uk-​13792​080 Loftus EF (2005) Planting misinformation in the human mind: A 30-year investigation of the malleability of memory. Learn Mem 12(4):361–366 BBC News (2017) Juror sentenced for internet research on convictions. Retrieved from: http://​www.​bbc.​co.​uk/​news/​uk-​engla​nd-​tyne-​39810​73f Loftus EF, Greene E (1980) Warning: Even memory for faces may be contagious. Law Hum Behav 4(4):323–334i Blunt MR, McAllister HA (2009) Mug shot exposure effects: Does size matter? Law Hum Behav 33:175–182. https://​doi.​org/​10.​ 1007/​s10979-​008-​9126-z Mack J, Sampson R. (2013) "Facebook Identifications". Criminal Law & Justice Weekly. 177, JPN 73. Brace NA, Pike GE, Kemp RI, Turner J (009) Eye-witness identi- fication procedures and stress: a comparison of live and video McGorrey P (2016) But I was so sure if was him: How face could be making eyewitness identifications unreliable. Internet Law Bulletin. Retrieved from https://​www.​resea​rchga​te.​net/​profi​le/​ 1 3 317 Journal of Police and Criminal Psychology (2023) 38:309–317 Paul-​Mcgor​rery/​publi​cation/​29839​1277_​But_I_​was_​so_​sure_​ it_​was_​him_​How_​Faceb​ook_​could_​be_​making_​eyewi​tness_ ​ident​ifica​tions_​unrel​iable/​links/​56e91​01908​aea51​e7f3b​a1ca/​ But-I-​was-​so-​sure-​it-​was-​him-​How-​Faceb​ook-​could-​be-​making-​ eyewi​tness-​ident​ifica​tions-​unrel​iable.​pdf Paul-​Mcgor​rery/​publi​cation/​29839​1277_​But_I_​was_​so_​sure_​ it_​was_​him_​How_​Faceb​ook_​could_​be_​making_​eyewi​tness_ ​ident​ifica​tions_​unrel​iable/​links/​56e91​01908​aea51​e7f3b​a1ca/​ But-I-​was-​so-​sure-​it-​was-​him-​How-​Faceb​ook-​could-​be-​making-​ eyewi​tness-​ident​ifica​tions-​unrel​iable.​pdf Shaw JS III, Garven S, Wood JM (1997) Co-witness information can have immediate effects on eyewitness memory reports. Law Hum Behav 21:503–523 Sporer SL (1996) Experimentally induced person mix-ups through media exposure and ways to avoid them. Adv Res Psychol Law pp 64–73 i Memon A, Hope L, Bartlett J, Bull, R (2002) Eyewitness recognition errors: The effects of mugshot viewing and choosing in young and old adults. Mem Cogn 30(8):1219–1227. https://​doi.​org/​10.​ 3758/​BF032​13404 Tredoux CG, Sporer SL, Vredeveldt A, Kempsen K, Nortje A (2020) Does constructing a facial composite affect eyewitness memory? A research synthesis and meta-analysis. J Exp Criminol. Advance online publication. https://​doi.​org/​10.​1007/​s11292-​020-​9432-z Nhan J, Huey L, Broll R (2017) Digilantism: An analysis of crowd- sourcing and the Boston Marathon bombings. References British Journal of Criminology. 57(2):341–361. https://​doi.​org/​10.​1093/​bjc/​azv118 Valentine T, Davis JP, Memon A, Roberts A (2012) Live showups and their influence on a subsequent video lineup. Appl Cogn Psychol 26(1):1–23. https://​doi.​org/​10.​1002/​acp.​1796 Paterson HM, Kemp RI (2006) Comparing methods of encountering post-event information: The power of co-witness suggestion. Appl Cogn Psychol 20(8):1083–1099 Valentine T, Darling S, Memon A (2007) Do strict rules and moving images increase the reliability of sequential identification pro- cedures? Appl Cogn Psychol 21(7):933–949. https://​doi.​org/​10.​ 1002/​acp.​1306 Pike GE, Brace NA, Turner J, Ness H, Vredeveldt A (2020) Advances in facial composite technology, utilizing holistic construction, do not lead to an increase in eyewitness misidentifications compared to older feature-based systems. Front Psychol 10, Article 1962. https://​doi.​org/​10.​3389/​fpsyg.​2019.​01962f Valentine T, Harris N, Colom Piera A, Darling S (2003) Are police video identifications fair to African-Caribbean suspects? Appl Cogn Psychol 17(4):459–476. https://​doi.​org/​10.​1002/​acp.​880 Pike GE, Brace NA, Turner J, Vredeveldt A (2019) The effect of facial composite construction on eyewitness identification accuracy in an ecologically valid paradigm. Crim Justice Behav 46(2):319–336. https://​doi.​org/​10.​1177/​00938​54818​811376 Wells GL, Charman SD, Olson EA (2005) Building face composites can harm lineup identification performance. Journal of Experi- mental Psychology: Applied 11(3):147–156. https://​doi.​org/​10.​ 1037/​1076-​898x.​11.3.​147 Police and Criminal Evidence Act (1984) Codes of Practice, Code D (2017) Retrieved from: https://​www.​gov.​uk/​guida​nce/​police-​and-​crimi​nal-​ evide​nce-​act-​1984-​pace-​codes-​of-​pract​ice Yardley E, Thomas Lynes AG, Wilson D, Kelly E (2018) What’s the deal with ‘websleuthing’? News media representations of amateur detectives in networked spaces. Crime Media Cult 14(1):81–109. https://​doi.​org/​10.​1177/​17416​59016​674045 p p R v Alexander and McGill [2012] EWCA Crim 2768. https://​www.​ 3tg.​co.​uk/​libra​ry/​theim​pacto​fsoci​almed​iaoni​denti​ficat​ionpr​ocedu​ res.​pdf Zhang N, Paluri M, Taigman Y, Fergus R, Bourdev L (2015) Beyond frontal faces: improving person recognition using multiple cues,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Boston: IEEE), 4804–4813. R v Phillips (2020) EWCA CRIM126 R v Phillips (2020) EWCA CRIM126 Shaw E (2014) ‘Philly Hate Crime Suspects Tracked Down by Anony- mous Twitter Hero’, Gawker, Retrieved from http://​gawker.​com/​ philly-​hate-​crime-​suspe​cts-​track​ed-​down-​by-​anony​mous-​tw-​ 16356​61609/​all Publisher’s Note  Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 1 3 1 3 1 3
https://openalex.org/W4365484715
https://aacr.figshare.com/articles/journal_contribution/Supplementary_Table_S1_Recruiting_TIL_trials_for_patients_with_non-melanoma_solid_cancers_from_TIL_Therapy_Facts_and_Hopes/22734073/1/files/40392964.pdf
English
null
TIL Therapy: Facts and Hopes
Clinical cancer research
2,023
cc-by
4,126
gov Sponsor Study Title Site Pha se Histology Lympho depletio n IL-2 Treatment Estimated enrollment (n) Primary Endpoint 8 XinWu Single Arm Phase I Trial of Autologous Tumor Infiltrating Lymphocyte Injectio n (GT202) in the Treatment of Metastatic or Recurrent Gynecological Tumors The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, Shanghai, China, 200000 I Metastatic or Recurrent Gynecological Tumors (limited to cervical cancer, ovarian cancer and endometrial cancer) Yes Yes, regimen unknow Tumor Infiltrating Lymphocytes manufactured to express mbIL-12 (GT202) 36 Overall Response Rate Duration of Response Progression-free Survival Overall Survival Disease Control Rate 3 Udai Kammula Adoptive Transfer of Tumor Infiltrating Lymphocytes for Biliary Tract Cancers Allyson Welsch, Pittsburgh, Pennsylvania, United States, 15232 II Metastatic biliary tract carcinoma (including intrahepatic or extrahepatic cholangiocarcinoma, gallbladder cancer, or ampullary carcinoma). Yes HD Autologous Tumor- Infiltrating Lymphocytes (TIL) 59 Objective Response Rate Complete Response Rate Duration of Response Disease control rate Progression-free Survival Overall Survival EORTC Quality of Life Questionnaire-Core 30 (QLQ-C30) EuroQol 5 dimensions 5 levels (EQ-5D-5L) 4 Vall d'Hebron Institute of Oncology Assessment of the Safety and Tolerability of ex vivo Next- generation Neoantigen- selected Tumor- infiltrating Lymphocyte (TIL) Therapy in Advanced Epithelial Tumors and Immune Checkpoint Blockade (ICB) Resistant Solid Tumors Vall d'Hebron Institute of Oncology, Barcelona, Spain I All solid tumors Yes HD NEXT-GEN-TIL (TILs that are selected based on their ability to recognize patient- specific neoantigens) 10 Incidence of AE Incidence of SAE Treatment-limiting toxicity Incidence of alternations in clinical laboratory test results Incidence of alterations in vital signs measurement Incidence of physical examination findings Assessment of performance status. gov Sponsor Study Title Site Pha se Histology Lympho depletio n IL-2 Treatment Estimated enrollment (n) Primary Endpoint 8 XinWu Single Arm Phase I Trial of Autologous Tumor Infiltrating Lymphocyte Injectio n (GT202) in the Treatment of Metastatic or Recurrent Gynecological Tumors The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, Shanghai, China, 200000 I Metastatic or Recurrent Gynecological Tumors (limited to cervical cancer, ovarian cancer and endometrial cancer) Yes Yes, regimen unknow Tumor Infiltrating Lymphocytes manufactured to express mbIL-12 (GT202) 36 Overall Response Rate Duration of Response Progression-free Survival Overall Survival Disease Control Rate 3 Udai Kammula Adoptive Transfer of Tumor Infiltrating Lymphocytes for Biliary Tract Cancers Allyson Welsch, Pittsburgh, Pennsylvania, United States, 15232 II Metastatic biliary tract carcinoma (including intrahepatic or extrahepatic cholangiocarcinoma, gallbladder cancer, or ampullary carcinoma). Yes HD Autologous Tumor- Infiltrating Lymphocytes (TIL) 59 Objective Response Rate Complete Response Rate Duration of Response Disease control rate Progression-free Survival Overall Survival EORTC Quality of Life Questionnaire-Core 30 (QLQ-C30) EuroQol 5 dimensions 5 levels (EQ-5D-5L) 4 Vall d'Hebron Institute of Oncology Assessment of the Safety and Tolerability of ex vivo Next- generation Neoantigen- selected Tumor- infiltrating Lymphocyte (TIL) Therapy in Advanced Epithelial Tumors and Immune Checkpoint Blockade (ICB) Resistant Solid Tumors Vall d'Hebron Institute of Oncology, Barcelona, Spain I All solid tumors Yes HD NEXT-GEN-TIL (TILs that are selected based on their ability to recognize patient- specific neoantigens) 10 Incidence of AE Incidence of SAE Treatment-limiting toxicity Incidence of alternations in clinical laboratory test results Incidence of alterations in vital signs measurement Incidence of physical examination findings Assessment of performance status. 8 Iovance Biotherapeutics, Inc. gov Sponsor Study Title Site Pha se Histology Lympho depletio n IL-2 Treatment Estimated enrollment (n) Primary Endpoint 8 XinWu Single Arm Phase I Trial of Autologous Tumor Infiltrating Lymphocyte Injectio n (GT202) in the Treatment of Metastatic or Recurrent Gynecological Tumors The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, Shanghai, China, 200000 I Metastatic or Recurrent Gynecological Tumors (limited to cervical cancer, ovarian cancer and endometrial cancer) Yes Yes, regimen unknow Tumor Infiltrating Lymphocytes manufactured to express mbIL-12 (GT202) 36 Overall Response Rate Duration of Response Progression-free Survival Overall Survival Disease Control Rate 3 Udai Kammula Adoptive Transfer of Tumor Infiltrating Lymphocytes for Biliary Tract Cancers Allyson Welsch, Pittsburgh, Pennsylvania, United States, 15232 II Metastatic biliary tract carcinoma (including intrahepatic or extrahepatic cholangiocarcinoma, gallbladder cancer, or ampullary carcinoma). Yes HD Autologous Tumor- Infiltrating Lymphocytes (TIL) 59 Objective Response Rate Complete Response Rate Duration of Response Disease control rate Progression-free Survival Overall Survival EORTC Quality of Life Questionnaire-Core 30 (QLQ-C30) EuroQol 5 dimensions 5 levels (EQ-5D-5L) 4 Vall d'Hebron Institute of Oncology Assessment of the Safety and Tolerability of ex vivo Next- generation Neoantigen- selected Tumor- infiltrating Lymphocyte (TIL) Therapy in Advanced Epithelial Tumors and Immune Checkpoint Blockade (ICB) Resistant Solid Tumors Vall d'Hebron Institute of Oncology, Barcelona, Spain I All solid tumors Yes HD NEXT-GEN-TIL (TILs that are selected based on their ability to recognize patient- specific neoantigens) 10 Incidence of AE Incidence of SAE Treatment-limiting toxicity Incidence of alternations in clinical laboratory test results Incidence of alterations in vital signs measurement Incidence of physical examination findings Assessment of performance status. Study of Autologous Tumor Infiltrating Lymphocytes in Patients With Solid Tumors University of California, San Diego La Jolla, California, United States and 44 more II Cohort 1A, 1B, 1C: Malignant Melanoma Cohort 2A: Squamous Cell Carcino ma of the Head and Neck (HNSCC) Cohort 3A, 3B, 3C: Non- small Cell Lung Cancer (NSCLC) Yes Yes, regimen unknow n Cohort 2A + 3A: LN- 145 + Pembrolizumab (post tumor resection) for up to 2 years Cohort 3B: LN-145 Cohort 3C LN-145 l + Ipilimumab (pre tumorresection) Nivolumab (post tumor resection) for up to 2 years 178 (total in all cohorts) Objective response rate Safety profile measured by Grade ≥ 3 treatment- emergent adverse event 5 Shanghai Juncell Therapeutics A Clinical Study on TIL for the Treatment of Advanced Solid Tumors Sir Run Run Shaw Hospital, Zhejiang University, School of Medicine, Hangzhou, Zhejiang, China, 310016 I Advanced Solid Tumors Yes No Autologous Tumor- Infiltrating Lymphocytes (TIL) 50 Adverse events Objective Response Rate Disease Control Rate Duration of Response Progression-Free Survival Overall Survival 0 Grit Biotechnology Autologous Tumor- infiltrating Lymphocyte Injection (GT201) for the Treatment of Metastatic/Recurre nt Advanced Solid Tumors The First Hospital of Zhejiang University Hangzhou, Zhejiang, China I Metastatic/Recurrent Advanced Solid Tumors Yes Yes, regimen unknow Autologous Tumor- Infiltrating Lymphocytes (TIL) (GT201) 30 Safety Profile Measured by Grade ≥3 TEAEs 3 Udai Kammula Adoptive Transfer of Tumor Infiltrating Lymphocytes for Advanced Solid Cancers UPMC Hillman Cancer Center Pittsburgh, Pennsylvania, United States II Gastric Cancer, Colorectal Cancer, Pancreatic Cancer, Sarcoma, Mesothelioma, Neuroendocrine Tumors, Squamous Cell Cancer, Merkel Cell Carcinoma, Mismatch Repair Deficiency, Microsatellite Instability Yes HD Autologous Tumor- Infiltrating Lymphocytes (TIL) 10 Objective Response Rate 1 Gregory Daniels Adoptive Cell Transfer of Autologous Tumor Infiltrating Lymphocytes and UC San Diego Moores Cancer Center La Jolla, California, United States I Metastatic Melanoma Head and Neck Cancer Yes HD Autologous Tumor- Infiltrating Lymphocytes (TIL) 24 Dose Limiting Toxicity High-Dose Interleukin 2 in Select Solid Tumors Hebei Senlang Biotechnology Inc., Ltd The Safety Study of Autologous TILs Therapy for Patients With Glioblastoma Multiforme. gov Sponsor Study Title Site Pha se Histology Lympho depletio n IL-2 Treatment Estimated enrollment (n) Primary Endpoint 8 XinWu Single Arm Phase I Trial of Autologous Tumor Infiltrating Lymphocyte Injectio n (GT202) in the Treatment of Metastatic or Recurrent Gynecological Tumors The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, Shanghai, China, 200000 I Metastatic or Recurrent Gynecological Tumors (limited to cervical cancer, ovarian cancer and endometrial cancer) Yes Yes, regimen unknow Tumor Infiltrating Lymphocytes manufactured to express mbIL-12 (GT202) 36 Overall Response Rate Duration of Response Progression-free Survival Overall Survival Disease Control Rate 3 Udai Kammula Adoptive Transfer of Tumor Infiltrating Lymphocytes for Biliary Tract Cancers Allyson Welsch, Pittsburgh, Pennsylvania, United States, 15232 II Metastatic biliary tract carcinoma (including intrahepatic or extrahepatic cholangiocarcinoma, gallbladder cancer, or ampullary carcinoma). Yes HD Autologous Tumor- Infiltrating Lymphocytes (TIL) 59 Objective Response Rate Complete Response Rate Duration of Response Disease control rate Progression-free Survival Overall Survival EORTC Quality of Life Questionnaire-Core 30 (QLQ-C30) EuroQol 5 dimensions 5 levels (EQ-5D-5L) 4 Vall d'Hebron Institute of Oncology Assessment of the Safety and Tolerability of ex vivo Next- generation Neoantigen- selected Tumor- infiltrating Lymphocyte (TIL) Therapy in Advanced Epithelial Tumors and Immune Checkpoint Blockade (ICB) Resistant Solid Tumors Vall d'Hebron Institute of Oncology, Barcelona, Spain I All solid tumors Yes HD NEXT-GEN-TIL (TILs that are selected based on their ability to recognize patient- specific neoantigens) 10 Incidence of AE Incidence of SAE Treatment-limiting toxicity Incidence of alternations in clinical laboratory test results Incidence of alterations in vital signs measurement Incidence of physical examination findings Assessment of performance status. The Second Hospital of HeBei Medical University Shijiazhuang, Hebei, China I Glioblastoma Multiforme Yes No Autologous Tumor- Infiltrating Lymphocytes (TIL) 20 Number of adverse events related to TILs infusion Intima Bioscience, Inc A Study of Metastatic Gastrointestinal Cancers Treated With Tumor Infiltrating Lymphocytes in Which the Gene Encoding the Intracellular Immune Checkpoint CISH Is Inhibited Using CRISPR Genetic Engineering Masonic Cancer Center, University of Minnesota Minneapolis, Minnesota, United States I/II Gastrointestinal Epithelial Cancer Colo-rectal Cancer Pancreatic Cancer Gall Bladder Cancer Colon Cancer Esophageal Cancer Stomach Cancer Yes HD Tumor Infiltrating Lymphocytes (TIL) in which the intracellular immune checkpoint CISH has been inhibited using CRISPR gene editing 20 Maximum tolerated dose (MTD) Preliminary efficacy of tumor reactive autologous lymphocytes with knockout of CISH gene in patients with refractory metastatic gastrointestinal epithelial cancers: changes in diameter Safety of tumor reactive autologous lymphocytes with knockout of the CISH gene - Incidence of Adverse Events Shanghai Juncell Therapeutics Study on TIL for the Treatment of Advanced Breast Cancer Shanghai Tenth People's Hospital Shanghai, China I Breast Cancer Yes No Autologous Tumor- Infiltrating Lymphocytes (TIL) 50 Adverse Events (AE) Objective Response Rate (ORR) Disease Control Rate (DCR ) Duration of Response (DOR) Progression-Free Survival (PFS) Overall Survival (OS) Shanghai Juncell Therapeutics Study on TIL for the Treatment of Advanced Solid Tumors Tongren Hospital Shanghai Jiao Tong University School Of Medicine. Shanghai, China I Advanced Solid Tumors Yes No Autologous Tumor- Infiltrating Lymphocytes (TIL) 20 Adverse Events (AE) Objective Response Rate (ORR) Disease Control Rate (DCR ) Duration of Response (DOR) Progression-Free Survival (PFS) Overall Survival (OS) 7 Shanghai Juncell Therapeutics Study on TIL for the Treatment of Advanced Hepatobiliary- Pancreatic Cancers Shanghai Tenth People's Hospital Shanghai, Shanghai, China I Advanced Liver Cancers Yes No Autologous Tumor- Infiltrating Lymphocytes (TIL) 50 Adverse Events (AE) Objective Response Rate (ORR) Disease Control Rate (DCR ) Duration of Response (DOR) Progression-Free Survival (PFS) Overall Survival (OS) 47 Fudan University Study of C-TIL052A Cell Therapy in Advanced Cervical Cancer Fundan University Shanghai Cancer Center, Shanghai, China Cervical Cancer Yes Yes, regimen unknow n Autologous Tumor- Infiltrating Lymphocytes (TIL) 20 Adverse Events (AE) 3 Iovance Biotherapeutics, Inc. gov Sponsor Study Title Site Pha se Histology Lympho depletio n IL-2 Treatment Estimated enrollment (n) Primary Endpoint 8 XinWu Single Arm Phase I Trial of Autologous Tumor Infiltrating Lymphocyte Injectio n (GT202) in the Treatment of Metastatic or Recurrent Gynecological Tumors The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, Shanghai, China, 200000 I Metastatic or Recurrent Gynecological Tumors (limited to cervical cancer, ovarian cancer and endometrial cancer) Yes Yes, regimen unknow Tumor Infiltrating Lymphocytes manufactured to express mbIL-12 (GT202) 36 Overall Response Rate Duration of Response Progression-free Survival Overall Survival Disease Control Rate 3 Udai Kammula Adoptive Transfer of Tumor Infiltrating Lymphocytes for Biliary Tract Cancers Allyson Welsch, Pittsburgh, Pennsylvania, United States, 15232 II Metastatic biliary tract carcinoma (including intrahepatic or extrahepatic cholangiocarcinoma, gallbladder cancer, or ampullary carcinoma). Yes HD Autologous Tumor- Infiltrating Lymphocytes (TIL) 59 Objective Response Rate Complete Response Rate Duration of Response Disease control rate Progression-free Survival Overall Survival EORTC Quality of Life Questionnaire-Core 30 (QLQ-C30) EuroQol 5 dimensions 5 levels (EQ-5D-5L) 4 Vall d'Hebron Institute of Oncology Assessment of the Safety and Tolerability of ex vivo Next- generation Neoantigen- selected Tumor- infiltrating Lymphocyte (TIL) Therapy in Advanced Epithelial Tumors and Immune Checkpoint Blockade (ICB) Resistant Solid Tumors Vall d'Hebron Institute of Oncology, Barcelona, Spain I All solid tumors Yes HD NEXT-GEN-TIL (TILs that are selected based on their ability to recognize patient- specific neoantigens) 10 Incidence of AE Incidence of SAE Treatment-limiting toxicity Incidence of alternations in clinical laboratory test results Incidence of alterations in vital signs measurement Incidence of physical examination findings Assessment of performance status. Autologous LN-145 in Patients With Metastatic Non- Small-Cell Lung Cancer City of Hope Duarte, California, United States and 40 more locations II Non Small Cell Lung Cancer Yes Yes, regimen unknow Autologous Tumor- Infiltrating Lymphocytes (TIL/LN- 145) 95 Objective Response Rate 1 National Cancer Institute (NCI) Immunotherapy Using Tumor Infiltrating Lymphocytes for Patients With Metastatic Cancer National Institutes of Health Clinical Center Bethesda, Maryland, United States II Colorectal Cancer Pancreatic Cancer Ovarian Cancer Breast Carcinoma Endocrine Tumors/Neuroendocrin e Tumors Yes HD Experimental 1: Young CD8+ enriched TIL Experimental 2: Young unselected TIL Experimental 3: Young unselected TIL + Pembrolizumab pre (x1) and post (x 3) cell infusion Experimental 4: Young unselected TIL + Pembrolizumab (up to 8 doses) upon progression 332 Response rate 3 Shanghai Juncell Therapeutics Study on TIL for the Treatment of Brain Glioma The Second Affiliated Hospital of Soochow University Suzhou, Jiangsu, China I Glioma Yes No Autologous Tumor- Infiltrating Lymphocytes (TIL) 50 Adverse Events (AE) Objective Response Rate (ORR) Disease Control Rate (DCR Duration of Response (DOR) Progression-Free Survival (PFS) Overall Survival (OS) 2 Shanghai Juncell Therapeutics Study on TIL for the Treatment of r/r Gastrointestinal Tumors Shanghai Tenth People's Hospital Shanghai, China I Gastrointestinal Tumor Yes No Autologous Tumor- Infiltrating Lymphocytes (TIL) 50 Objective Response Rate (ORR) Disease Control Rate (DCR Duration of Response (DOR) Progression-Free Survival (PFS) Overall Survival (OS) 0 Shanghai Juncell Therapeutics Study on TIL for the Treatment of r/r Gynecologic Tumors Shanghai Tenth People's Hospital Shanghai, Shanghai, China I Gynecologic Cancer Yes No Autologous Tumor- Infiltrating Lymphocytes (TIL) 50 Objective Response Rate (ORR) Disease Control Rate (DCR Duration of Response (DOR) Progression-Free Survival (PFS) Overall Survival (OS) 8 Suzhou BlueHorse Therapeutics Co., Ltd. A Clinical Study of LM103 Injection in the Treatment of Addvanced Solid Tumors Tianjin Beichen Hospital Tianjin, China I Melanoma Non Small Cell Lung Cancer Cervical Carcinoma Yes Yes, regimen unknow n Autologous Tumor- Infiltrating Lymphocytes (TIL) 15 Incidence and severity of adverse events (AEs) 0 H. gov Sponsor Study Title Site Pha se Histology Lympho depletio n IL-2 Treatment Estimated enrollment (n) Primary Endpoint 8 XinWu Single Arm Phase I Trial of Autologous Tumor Infiltrating Lymphocyte Injectio n (GT202) in the Treatment of Metastatic or Recurrent Gynecological Tumors The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, Shanghai, China, 200000 I Metastatic or Recurrent Gynecological Tumors (limited to cervical cancer, ovarian cancer and endometrial cancer) Yes Yes, regimen unknow Tumor Infiltrating Lymphocytes manufactured to express mbIL-12 (GT202) 36 Overall Response Rate Duration of Response Progression-free Survival Overall Survival Disease Control Rate 3 Udai Kammula Adoptive Transfer of Tumor Infiltrating Lymphocytes for Biliary Tract Cancers Allyson Welsch, Pittsburgh, Pennsylvania, United States, 15232 II Metastatic biliary tract carcinoma (including intrahepatic or extrahepatic cholangiocarcinoma, gallbladder cancer, or ampullary carcinoma). Yes HD Autologous Tumor- Infiltrating Lymphocytes (TIL) 59 Objective Response Rate Complete Response Rate Duration of Response Disease control rate Progression-free Survival Overall Survival EORTC Quality of Life Questionnaire-Core 30 (QLQ-C30) EuroQol 5 dimensions 5 levels (EQ-5D-5L) 4 Vall d'Hebron Institute of Oncology Assessment of the Safety and Tolerability of ex vivo Next- generation Neoantigen- selected Tumor- infiltrating Lymphocyte (TIL) Therapy in Advanced Epithelial Tumors and Immune Checkpoint Blockade (ICB) Resistant Solid Tumors Vall d'Hebron Institute of Oncology, Barcelona, Spain I All solid tumors Yes HD NEXT-GEN-TIL (TILs that are selected based on their ability to recognize patient- specific neoantigens) 10 Incidence of AE Incidence of SAE Treatment-limiting toxicity Incidence of alternations in clinical laboratory test results Incidence of alterations in vital signs measurement Incidence of physical examination findings Assessment of performance status. Lee Moffitt Cancer Center and Research Institute Clinical Trial of CD40L-Augmented TIL for Patients With EGFR, ALK, ROS1 or HER2- Driven NSCLC Moffitt Cancer Center Tampa, Florida, United States I/II Non Small Cell Lung Cancer Yes HD Tumor-Infiltrating Lymphocytes (TIL) Nivolumab (pre and post cell infusion for up to 12 months) 20 Adverse Events (AE) 7 Sheba Medical Center Phase 2, Single- Center, Open Label Study of Autologous, Adopti ve Cell Therapy Following a Reduced Intensity, Non-myeloablative, Lymphodepleting Induction Regimen in Metastatic Urothelial Carcinoma Patients Sheba Medical Center, Israel II Urothelial Carcinoma Yes, reduced intensity HD Autologous Tumor- Infiltrating Lymphocytes (TIL) 20 Efficacy Safety 0 Shanghai Juncell Therapeutics A Phase I Study on Autologous Tumor Chinese PLA General Hospital I Cohort 1: Advanced solid tumors Yes Autologous Tumor- Infiltrating 60 Maximal Tolerance Dose Dose Limiting Toxicity Infiltrating Lymphocytes Injecti on (GC101 TIL) for the Treatment of Advanced Malignant Solid Tumors Beijing, Beijing, China Cohort 2: cervix tumors Cohort 3: malignant melanoma Cohort 4: HNSCC Lymphocytes (TIL/ GC101 TIL) + Sintilimab Adverse Events 5573035 Lyell Immunopharma, Inc. A Study to Investigate LYL845 in Adults With Solid Tumors Ohio State University Medical Center Columbus, Ohio, United States and 3 other locations I Melanoma Non-small Cell Lung Cancer Colorectal Cancer No No LYL845: autologous tumor infiltrating lymphocyte (TIL) enhanced via Epi-R, a proprietary epigenetic reprogramming technology 108 Incidence of dose-limiting toxicities (DLTs) Incidence of treatment- emergent adverse events (TEAEs) Severity of treatment- emergent adverse events (TEAEs) Determine recommended Phase 2 Dose Range (RP2DR) 3449108 M.D. gov Sponsor Study Title Site Pha se Histology Lympho depletio n IL-2 Treatment Estimated enrollment (n) Primary Endpoint 8 XinWu Single Arm Phase I Trial of Autologous Tumor Infiltrating Lymphocyte Injectio n (GT202) in the Treatment of Metastatic or Recurrent Gynecological Tumors The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, Shanghai, China, 200000 I Metastatic or Recurrent Gynecological Tumors (limited to cervical cancer, ovarian cancer and endometrial cancer) Yes Yes, regimen unknow Tumor Infiltrating Lymphocytes manufactured to express mbIL-12 (GT202) 36 Overall Response Rate Duration of Response Progression-free Survival Overall Survival Disease Control Rate 3 Udai Kammula Adoptive Transfer of Tumor Infiltrating Lymphocytes for Biliary Tract Cancers Allyson Welsch, Pittsburgh, Pennsylvania, United States, 15232 II Metastatic biliary tract carcinoma (including intrahepatic or extrahepatic cholangiocarcinoma, gallbladder cancer, or ampullary carcinoma). Yes HD Autologous Tumor- Infiltrating Lymphocytes (TIL) 59 Objective Response Rate Complete Response Rate Duration of Response Disease control rate Progression-free Survival Overall Survival EORTC Quality of Life Questionnaire-Core 30 (QLQ-C30) EuroQol 5 dimensions 5 levels (EQ-5D-5L) 4 Vall d'Hebron Institute of Oncology Assessment of the Safety and Tolerability of ex vivo Next- generation Neoantigen- selected Tumor- infiltrating Lymphocyte (TIL) Therapy in Advanced Epithelial Tumors and Immune Checkpoint Blockade (ICB) Resistant Solid Tumors Vall d'Hebron Institute of Oncology, Barcelona, Spain I All solid tumors Yes HD NEXT-GEN-TIL (TILs that are selected based on their ability to recognize patient- specific neoantigens) 10 Incidence of AE Incidence of SAE Treatment-limiting toxicity Incidence of alternations in clinical laboratory test results Incidence of alterations in vital signs measurement Incidence of physical examination findings Assessment of performance status. Anderson Cancer Center LN-145 or LN-145- S1 in Treating Patients With Relapsed or Refractory Ovarian Cancer, Triple Negative Breast Cancer (TNBC), Anaplastic Thyroid Cancer, Osteosarcoma, or Other Bone and Soft Tissue Sarcomas M D Anderson Cancer Center Houston, Texas, United States II Cohort 1: Ovarian Cancer, Triple Negative Breast Cancer (TNBC), Osteosarcoma, Other Bone and Soft Tissue Sarcomas Cohort 2: Anaplastic Thyroid Cancer Yes HD Cohort 1: Autologous tumor infiltrating lymphocyte (TIL), Nivolumab + Ipilimumab (x1) pre surgery, Nivolumab (x4) post TIL infusion Corhort 2: Autologous tumor infiltrating lymphocyte (TIL) 95 Objective response rate 5430373 Grit Biotechnology GT101 Injection for the Treatment of Metastatic or Recurrent Solid Tumors The fifth medical center of the General Hospital of the Chinese people's Liberation Army Beijing, Beijing, China I Solid tumors Yes HD Autologous tumor- infiltrating lymphocytes (TIL/ GT101) 31 Safety Profile Measured by Grade ≥3 TEAEs Objective response rate Progression-free survival Overall survival 4643574 Centre Hospitalier Universitaire Vaudois NeoTIL in Advanced Solid Tumors Centre hospitalier universitaire vaudois (CHUV) I Solid tumors Yes HD Autologous Tumor- Infiltrating Lymphocytes Enriche 42 Evaluation of the number of patients who successfully receive NeoTIL-ACT in Lausanne, Vaud, Switzerland d for Tumor Antigen Specificity (NeoTIL) Low dose-irradiation (LDI) administered once to tumor lesions before infusion of NeoTIL combination with LDI (feasibility) Toxicity of NeoTIL-ACT in combination with LDI Objective response rate 3 Leiden University Medical Center Adoptive T Cell Therapy in Patients With Recurrent Ovarian Cancer Leiden University Medical Center, Netherlands I/II Epithelial Ovarian Cancer No No Cohort 1: Carboplatin-paclitaxel day1, q3 weeks, 6x TIL starting 14 days after the 2nd chemotherapy cycle Cohort 2: Above regimen + IFNα (3x10e6 U daily) starting one week before the first TIL infusion for 12 weeks in total 12 NCI CTC criteria 5 Iovance Biotherapeutics, Inc Study of LN-145, Autologous Tumor Infiltrating Lymphocytes in the Treatment of Patients With Cervical Carcinoma St. Table S1. Recruiting TIL trials for patients with non-melanoma solid cancers (assessed, January 23, 2023). Trial information is assessed from Clinicaltrials.gov using search setting: “Recruiting”, “Interventional (clinical trial)”, “Adults”, “Tumor infiltrating Lymphocytes”. HD: High Dose. ls for patients with non-melanoma solid cancers (assessed, January 23, 2023). Trial information is assessed from Clinicaltrials.gov using search setting: al (clinical trial)”, “Adults”, “Tumor infiltrating Lymphocytes”. HD: High Dose. gov Sponsor Study Title Site Pha se Histology Lympho depletio n IL-2 Treatment Estimated enrollment (n) Primary Endpoint 8 XinWu Single Arm Phase I Trial of Autologous Tumor Infiltrating Lymphocyte Injectio n (GT202) in the Treatment of Metastatic or Recurrent Gynecological Tumors The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, Shanghai, China, 200000 I Metastatic or Recurrent Gynecological Tumors (limited to cervical cancer, ovarian cancer and endometrial cancer) Yes Yes, regimen unknow Tumor Infiltrating Lymphocytes manufactured to express mbIL-12 (GT202) 36 Overall Response Rate Duration of Response Progression-free Survival Overall Survival Disease Control Rate 3 Udai Kammula Adoptive Transfer of Tumor Infiltrating Lymphocytes for Biliary Tract Cancers Allyson Welsch, Pittsburgh, Pennsylvania, United States, 15232 II Metastatic biliary tract carcinoma (including intrahepatic or extrahepatic cholangiocarcinoma, gallbladder cancer, or ampullary carcinoma). Yes HD Autologous Tumor- Infiltrating Lymphocytes (TIL) 59 Objective Response Rate Complete Response Rate Duration of Response Disease control rate Progression-free Survival Overall Survival EORTC Quality of Life Questionnaire-Core 30 (QLQ-C30) EuroQol 5 dimensions 5 levels (EQ-5D-5L) 4 Vall d'Hebron Institute of Oncology Assessment of the Safety and Tolerability of ex vivo Next- generation Neoantigen- selected Tumor- infiltrating Lymphocyte (TIL) Therapy in Advanced Epithelial Tumors and Immune Checkpoint Blockade (ICB) Resistant Solid Tumors Vall d'Hebron Institute of Oncology, Barcelona, Spain I All solid tumors Yes HD NEXT-GEN-TIL (TILs that are selected based on their ability to recognize patient- specific neoantigens) 10 Incidence of AE Incidence of SAE Treatment-limiting toxicity Incidence of alternations in clinical laboratory test results Incidence of alterations in vital signs measurement Incidence of physical examination findings Assessment of performance status. Joseph's Hospital and Medical Center Center For Women's Health, Phoenix, Arizona, United States, 85013 and 39 other locations II Cervical carcinoma Yes Yes, regimen unknow n Cohort 1 + 2: LN-145 Cohort 2: LN Cohort 3: LN-145 + Pembrolizumab (up to 24 months) Cohort 4: LN-145 Cohort 5: LN-145 189 Cohort 1 and 2: Objective Response Rate Cohort 3: Adverse Events Cohort 4: Efficacy and Adverse Events Cohort 5: Efficacy and Adverse Events 6 Inge Marie Svane T-cell therapu in Combination With Nivolumab, Relatlimab and Ipilimumab for Patients With Metastatic Ovarian Cancer National Center for Cancer Immune Therapy, Herlev, Denmark I/II Epithelial ovarian cancer Yes No Step 1: TIL + Nivolumab (x4) +Relatlimab (x 4) Step 2: Ipilimumab (x1) + TIL + Nivolumab (x4) + Relatlimab (x4) 18 Number of patients excluded due to treatment related safety issues Fraction of patients experiencing grade III or worse adverse events Number of patients excluded due to feasibility issues 3 Instil Bio ITIL-306 in Advanced Solid Tumors Washington University School of Medicine Saint Louis, I Epithelial Ovarian Cancer Non-small Cell Lung Cancer Renal Cell Carcinoma Yes No Tumor-infiltrating lymphocytes containing a unique molecule designed to increase TIL activity 51 Frequency and severity of ITIL-306 treatment- emergent adverse events (AEs), serious AEs, and AEs of special interest (AESI) Missouri, United States Memorial Sloan Kettering Cancer Center New York, New York, United States when it encounters folate receptor α (FOLR1) on the tumor (ITIL-306) Phase 1a: Dose Escalation Phase 2: Expansion 8 Shanghai OriginCell Therapeutics Co., Ltd. TILs for Treatment of Metastatic or Recurrent Cervical Cancer Shanghai general hospital Shanghai, Shanghai, China I Cervical Cancer Yes HD Autologous Tumor- Infiltrating Lymphocytes (TIL) 15 dose limited toxicity, DLT 4 Iovance Biotherapeutics, Inc. A Study to Investigate the Efficacy and Safety of an Infusion of IOV-4001 in Adult Participants With Unresectable or Metastatic Melanoma or Stage III or IV Non-small- cell Lung Cancer University of Louisville Louisville, Kentucky, United States Memorial Sloan Kettering Cancer Center, New York, United States University of Cincinnati, Ohio, United States I/II Melanoma NSCLC Yes HD PD-1 Knockout Tumor- infiltrating Lymphocytes (IOV- 4001) 53 (total in all cohorts) Phase I: Safety of IOV-4001 Phase 2: Objective Response Rate (ORR)
https://openalex.org/W4379797426
https://amt.copernicus.org/articles/16/2821/2023/amt-16-2821-2023.pdf
English
null
Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products
Atmospheric measurement techniques
2,023
cc-by
11,430
Correspondence: Anja Hünerbein (anjah@tropos.de) Correspondence: Anja Hünerbein (anjah@tropos.de) Correspondence: Anja Hünerbein (anjah@tropos.de) Received: 17 November 2022 – Discussion started: 25 November 2022 Revised: 31 March 2023 – Accepted: 28 April 2023 – Published: 7 June 2023 Received: 17 November 2022 – Discussion started: 25 November 2022 Revised: 31 March 2023 – Accepted: 28 April 2023 – Published: 7 June 2023 Abstract. The EarthCARE (Earth Clouds, Aerosols and Ra- diation Explorer) satellite mission will provide new insights into aerosol–cloud–radiation interactions by means of syn- ergistic observations of the Earth’s atmosphere from a col- lection of active and passive remote sensing instruments, fly- ing on a single satellite platform. The Multi-Spectral Imager (MSI) will provide visible and infrared images in the cross- track direction with a 150 km swath and a pixel sampling at 500 m. The suite of MSI cloud algorithms will deliver cloud macro- and microphysical properties complementary to the vertical profiles measured from the Atmospheric Lidar (ATLID) and the Cloud Profiling Radar (CPR) instruments. This paper provides an overview of the MSI cloud mask al- gorithm (M-CM) being developed to derive the cloud flag, cloud phase and cloud type products, which are essential in- puts to downstream EarthCARE algorithms providing cloud optical and physical properties (M-COP) and aerosol opti- cal properties (M-AOT). The MSI cloud mask algorithm has been applied to simulated test data from the EarthCARE end- to-end simulator and satellite data from the Moderate Reso- lution Imaging Spectroradiometer (MODIS) as well as from the Spinning Enhanced Visible InfraRed Imager (SEVIRI). Verification of the MSI cloud mask algorithm to the simu- lated test data and the official cloud products from SEVIRI and MODIS demonstrates a good performance of the algo- rithm. Some discrepancies are found, however, for the detec- tion of thin cirrus clouds over bright surfaces like desert or snow. This will be improved by tuning of the thresholds once real observations are available. 1 Introduction Clouds cover about 70 % of our Earth’s surface and play an important role in the global radiation and energy budgets. The influence of clouds on radiative fluxes exhibits a com- plex dependency on cloud type, phase and geometric height as well as their optical and microphysical properties, poten- tially introducing significant radiative feedbacks in response to climate change. The Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report summarizes the current state of knowledge, concluding that clouds are ex- pected to amplify global warming as a result of an increase in high-level clouds and a reduction in low-level clouds (IPCC, 2021). The report provides a best estimate of the net cloud feedback, having a positive value of 0.42 W m−2. While the uncertainty related to cloud feedbacks has been halved com- pared to the previous Fifth Assessment Report, the response of clouds to a warming Earth remains one of the biggest chal- lenges in our understanding of the climate system. The determination of cloud, atmospheric and surface prop- erties from multi-spectral satellite imagery relies on the ac- curate discrimination of cloudy and cloud-free pixels. This discrimination is typically done by a cloud mask algorithm as the first step in a processing chain of satellite imagery. If for instance cloudy areas are misclassified as clear or vice versa, this could negatively impact subsequent retrievals of aerosol or cloud optical properties, which underlies the importance of an accurate cloud-masking algorithm. Different compar- ison studies and intercomparison studies have been done like the Cloud Masking Intercomparison eXercise (CMIX) to evaluate the cloud-masking algorithms (Skakun et al., 2022; Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products Anja Hünerbein1, Sebastian Bley1, Stefan Horn1,3, Hartwig Deneke1, and Andi Walther2 1Remote Sensing of Atmospheric Processes, Leibniz Institute for Tropospheric Research, Leipzig, Germany 2Cooperative Institute for Meteorological Satellite Studies, Madison, WI, United States 3Meteologix AG, Sattel, Switzerland Atmos. Meas. Tech., 16, 2821–2836, 2023 https://doi.org/10.5194/amt-16-2821-2023 © Author(s) 2023. This work is distributed under the Creative Commons Attribution 4.0 License. Atmos. Meas. Tech., 16, 2821–2836, 2023 https://doi.org/10.5194/amt-16-2821-2023 © Author(s) 2023. This work is distributed under the Creative Commons Attribution 4.0 License. A. Hünerbein et al.: The M-CM product A. Hünerbein et al.: The M-CM product 2822 namic thresholds were derived from a histogram-based scene analysis (Saunders and Kriebel, 1988; Strabala et al., 1994). A new milestone in instrumental capabilities was reached by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, providing observations in 36 spectral channels from NASA’s Earth Observing System satellites Terra and Aqua, launched in 1999 and 2002, respectively. The operational cloud mask product for MODIS considers the spectral information from 19 of these channels (Acker- man et al., 2002; Platnick et al., 2003). While several spec- tral tests are similar to those used by the APOLLO and IS- CCP cloud detection schemes, the availability of channels in water vapor and CO2 absorption bands enabled an improved cloud detection in particular for thin high-level clouds and for polar night conditions (e.g., Liu et al., 2004; Nakajima et al., 2011). Zekoll et al., 2021). These techniques are mostly based on two general assumptions, namely that clouds appear brighter in solar channels, due to the strong reflection of sunlight, and colder in infrared channels relative to cloud-free surfaces, due to the decrease in atmospheric temperature with height. In addition, discrimination of clouds from cloud-free regions is commonly based on a variety of spectral features, spatial structure measures or temporal characteristics in time series because clouds are often more variable than the underlying surface (Saunders and Kriebel, 1988). namic thresholds were derived from a histogram-based scene analysis (Saunders and Kriebel, 1988; Strabala et al., 1994). y ( , ; , ) A new milestone in instrumental capabilities was reached by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, providing observations in 36 spectral channels from NASA’s Earth Observing System satellites Terra and Aqua, launched in 1999 and 2002, respectively. The operational cloud mask product for MODIS considers the spectral information from 19 of these channels (Acker- man et al., 2002; Platnick et al., 2003). While several spec- tral tests are similar to those used by the APOLLO and IS- CCP cloud detection schemes, the availability of channels in water vapor and CO2 absorption bands enabled an improved cloud detection in particular for thin high-level clouds and for polar night conditions (e.g., Liu et al., 2004; Nakajima et al., 2011). A. Hünerbein et al.: The M-CM product ( , ) Operational cloud mask algorithms generally combine a variety of individual tests by means of a decision tree, as no single test is able to achieve a sufficient accuracy for the diversity of clouds and atmospheric conditions encountered globally (e.g., Saunders and Kriebel, 1988). An alternative is the use of fuzzy-logic-based or Bayesian schemes to combine tests to yield a confidence value or probability for the classi- fication (e.g., Ackerman et al., 1998; Hollstein et al., 2015). More recently, convolutional neural networks have been ap- plied to discriminate between different land surfaces, ocean, clouds and cloud shadows (Mateo-García et al., 2017; Li et al., 2019; Hughes and Kennedy, 2019). Such cloud-masking approaches are often applied to high-resolution satellite im- ages (e.g., Landsat, Sentinel-2) and require large training datasets. In practice, these training datasets have to be cre- ated manually, and the significant effort required for estab- lishing high-quality training datasets and validating their per- formance has so far not led to operational application in global-scale long-term cloud climate data records. Rossow and Garder (1993) classify the different tests used in cloud mask algorithms into radiance threshold tests, spatial vari- ance tests, temporal variance tests and tests using indepen- dent datasets to estimate clear-sky radiances. The perfor- mance of these tests strongly depends on the satellite sensor specifications including spatial, spectral and temporal reso- lution. EarthCARE, the Earth Clouds, Aerosols and Radiation Explorer, is a joint European and Japanese mission and part of ESA’s Living Planet program (Illingworth et al., 2015; Wehr et al., 2023). The mission objective is to improve our understanding of aerosol–cloud–radiation interactions and the role of aerosols and clouds in the Earth radiation bud- get. While observation of clouds have gradually improved over the past decades, the launch of the EarthCARE satellite is expected to bring a breakthrough by means of its novel ob- servational capabilities. To achieve the mission objective, ac- curate and simultaneous measurements of microphysical and optical properties of aerosol and clouds together with solar and infrared radiation fluxes are crucial. EarthCARE will of- fer the unique opportunity to collect these observations at a global scale due to its polar orbit. The satellite will carry an exceptional collection of active and passive remote sensing instruments, flying on a single satellite platform in an orbit at an altitude of 393 km. Published by Copernicus Publications on behalf of the European Geosciences Union. Published by Copernicus Publications on behalf of the European Geosciences Union. 2.1.1 Visible reflection tests The visible reflectance test compares the reflectance in the 0.67 µm channel or the reflectance in the 0.865 µm chan- nel with surface-dependent thresholds (Fig. 2). These thresh- olds are initially taken from the MODIS cloud mask algo- rithm. These thresholds have been tuned based on simulated MSI properties, while further adaptions are planned at a later stage, when actual MSI data will become available. If the reflectance exceeds the upper threshold, pixels are assumed to be very likely cloudy. Pixels with reflectances below the lower threshold are classified with high confidence as cloud- free. The pixels in between are classified by calculating prob- ability functions, as described in Sect. 2.1.3. 2.1 M-CF: binary cloud flag The algorithm derives a cloud mask by applying individual threshold tests to brightness temperatures and reflectances of individual channels. The threshold tests and the way that re- sults are combined are adapted from the MODIS cloud mask algorithm (Ackerman et al., 2002). The thresholds rely on the assumption that spectral signatures of cloud-free pixels and pixels covered by different cloud types differ. As the thresh- olds vary globally, only the upper (cloudy) and lower (cloud- free) limits of the thresholds are defined, and a linear func- tion is used to determine the probability that a cloud is really present based on how close the observation is to the limits. Furthermore, the probability of being cloud-free from the ap- plied tests is combined to an overall probability which may provide, in combination with the number of applied tests, a measure of the confidence of the result. From the over- all probability a binary cloud mask indicating if a pixel is cloudy or not is derived with four levels of confidence: clear, probably clear, probably cloudy and cloudy. This paper is structured as follows. Section 2 describes the algorithms for deriving the operational Level 2 M-CM prod- ucts, which comprise a binary cloud flag, cloud phase and cloud type as well as confidence statistics. The verification of the algorithm using MODIS and Meteosat Second Gen- eration (MSG) SEVIRI scenes as well as synthetic test data from the EarthCARE end-to-end simulator (Donovan et al., 2023) is provided in Sect. 3. Comprehensive comparisons between the operational M-CM product and the synthetic test fields are presented in Appendix A. The data process- ing chain including the role of M-CM is explained in more detail in Eisinger et al. (2023). A. Hünerbein et al.: The M-CM product nels. The reflectances (ρi) of each channel i are obtained from the measured radiance (L) and the solar irradiance E0 as able. Reflectances in the solar channels are used to detect clouds by means of a visible reflectance test and a reflectance ratio test. The visible reflectance test assumes that the re- flectance of clouds exceeds the reflectance of cloud-free sur- faces, with the exception of highly reflective surfaces. The reflectance ratio test compares the ratio of the reflectances of two shortwave channels to thresholds. Complementing the solar channel tests, a brightness temperature test uses infor- mation from the thermal infrared (TIR) channels to detect clouds based on the assumption that the brightness tempera- ture of clouds is significantly lower than the brightness tem- perature of cloud-free pixels. as ρi (θ0,θ,φ) = πLi (θ0,θ,φ) E0 cos(θ0) , i = 0.6,0.8,1.6,2.2, (1) (1) with the sun zenith angle θ0, the viewing zenith angle θ and the relative azimuth angle φ. An important input for the al- gorithm is the day/night flag. The daytime condition is con- sidered for a certain pixel of the sun zenith angle θ0 < 80◦. Additionally, the sunglint angle θr is calculated over ocean as cos(θr) = sin(θ) × sin(θ0) × cos(φ) + cos(θ) × cos(θ0). (2) If θr < 36◦, the pixel is flagged with sunglint provided in the surface flag. The estimation of the expected difference in cloud-free brightness temperatures for the three infrared channels is an important aspect for the accuracy of cloud detection. This difference depends on differences in atmospheric absorp- tion (water vapor) and surface emissivity. Therefore, scene- dependent lookup tables or online radiative transfer simula- tions have to be elaborated to determine suitable thresholds. All tests yield a probability that a pixel is cloud-free. Some of the individual tests are however not independent of each other because they rely on similar channels and principles. Hence, the resulting probabilities of those tests are combined. For every 500 m resolution pixel of the 150 km wide MSI swath, the M-CM products provide a classification whether it is cloud-covered or cloud-free as the final output. Addition- ally, for the cloudy pixels, the cloud type and cloud phase of the uppermost cloud layer will be reported. If θr < 36◦, the pixel is flagged with sunglint provided in the surface flag. A. Hünerbein et al.: The M-CM product The instruments include the Atmo- spheric Lidar (ATLID), the Cloud Profiling Radar (CPR), the Multi-Spectral Imager (MSI) and the Broad-Band Radiome- ter (BBR). The International Satellite Cloud Climatology Project (IS- CCP; Schiffer and Rossow, 1983) was the earliest effort to provide a comprehensive global cloud climatology from multi-spectral meteorological satellite imagers. Its cloud de- tection algorithm is described in Rossow and Garder (1993) and is based on a combination of static and dynamic thresh- old tests for one window channel in the visible and one win- dow channel in the thermal infrared wavelength range. This choice was made based on the limited availability of channels from early geostationary satellites, specifically the Meteosat, GMS (Geostationary Meteorological Satellite) and GOES (Geostationary Operational Environmental Satellite) series. This paper describes the algorithm used to produce the cloud flag, type and phase products based alone on MSI ob- servations. The approaches selected for EarthCARE’s MSI cloud mask (M-CM) products relies on the research on and experience with cloud-masking approaches during the past 40 years since the start of the satellite era. It exploits the full spectral information content of the MSI instrument (e.g., the cloud type is determined using 3D histograms of the VIS, visible; SWIR-2, short-wave infrared; and TIR-2, ther- mal infrared, channels). It is, however important to real- ize that its performance is also determined by the selection of four solar and three infrared channels for MSI, having central wavelengths of 670 nm (VIS), 865 nm (NIR, near infrared), 1650 nm (SWIR-1), 2210 nm (SWIR-2), 8.8 µm (TIR-1), 10.8 µm (TIR-2) and 12.0 µm (TIR-3). Given this specification, MSI’s capabilities and sensitivity is more simi- lar to that of AVHRR than of MODIS. In particular, no chan- nels within absorption bands of atmospheric gases are avail- Based on the Advanced Very High Resolution Radiometer (AVHRR) which has been flown on NOAA’s polar-orbiting satellites since the early 1980s, the APOLLO (AVHRR Pro- cessing scheme Over cLoud, Land, and Ocean) cloud detec- tion scheme used both static and dynamic threshold tests. The availability of additional spectral channels was used in partic- ular to improve nighttime cloud detection performance. Dy- https://doi.org/10.5194/amt-16-2821-2023 Atmos. Meas. Tech., 16, 2821–2836, 2023 2823 Atmos. Meas. Tech., 16, 2821–2836, 2023 2 M-CM algorithm description The MSI cloud product processor (M-CLD) provides algo- rithms for calculation of the cloud flag; cloud phase; cloud type; cloud optical depth; cloud particle size; cloud water path; and cloud top temperature, pressure and height. The processor consists of two main parts, which are sequentially processed. First is the cloud mask (M-CM), which is manda- tory for the other cloud optical and physical properties (M- COP). The present paper describes the cloud mask processor (M-CM), which is schematically shown in Fig. 1. The upper and the lower thresholds differ for land, desert and ocean pixels outside the sunglint region and ocean pix- els in the sunglint region (Fig. 2). Whereas the thresholds are fixed for the first three classes, they depend on the sunglint The algorithm starts with the calculation of the re- flectances at the top of the atmosphere in the shortwave chan- https://doi.org/10.5194/amt-16-2821-2023 Atmos. Meas. Tech., 16, 2821–2836, 2023 2824 A. Hünerbein et al.: The M-CM product 2824 A. Hünerbein et al.: The M- Figure 1. Schematic of the main components of the M-CM algorithm. BT: brightness temperature, LUT: lookup table. Figure 1. Schematic of the main components of the M-CM algorithm. BT: brightness temperature, LUT: lookup table. Figure 2. Flow chart of the visible reflectance test. Figure 2. Flow chart of the visible reflectance test. 2.1.3 Brightness temperature tests The probability of being cloud-free is calculated by assuming a linear probabil- ity function. The tri-spectral window brightness temperature difference test (at 8.8, 10.8 and 12.0 µm) is only applied to water surfaces during daytime. The brightness temperatures at 10.8 and at 12.0 µm are used to detect thin cirrus clouds and cloud edges, which are characterized by a higher bright- ness temperature difference (10.8–12.0 µm) than a cloud-free surface. The pixel is detected as cloudy if 2.2 M-Ctype: cloud types The algorithm applies a maximum-likelihood classifier to re- flectances and brightness temperatures at VIS, SWIR-2 and TIR-2. Before the algorithm assigns a specific cloud type for a certain pixel, the dataset needs to be trained to acquire statistics for predefined cloud classes. This procedure is de- scribed in the following section. 2.1.2 Reflectance ratio test angle in the sunglint region. Over land the test applies the reflectance in the 0.67 µm channel, while over desert the re- flectance in the 0.865 µm channel is used. Ocean pixels lo- cated outside the sunglint region are classified by using the reflectance in the 0.865 µm channel. Ocean pixels affected by sunglint also apply thresholds based on the 0.865 µm channel, but the thresholds are calculated depending on the sunglint angle (see Eq. 2). The lower and upper thresholds of the 0.865 µm tests depend on predefined limits of sunglint angles between 0–10, 10–20 and 20–36◦(Fig. 2). The reflectance ratio test is applied to daytime pixels over oceans and land surfaces with low reflectivities. Therefore, the land pixels are classified in surfaces with high reflectiv- ity like desert, polar and semi-arid regions and low reflec- tivity. Over ocean the reflectance ratio test can be applied as well in the sunglint region. The test score is the ratio of the reflectance in the 0.865 µm channel and the reflectance in the 0.67 µm channel. If the test score is smaller than the Atmos. Meas. Tech., 16, 2821–2836, 2023 https://doi.org/10.5194/amt-16-2821-2023 2825 2.1.4 Estimation of confidence level η = 2(ρ0.8 −ρ0.6) + 1.5 · ρ0.8 + 0.5 · ρ0.6 ρ0.8 + ρ0.6 + 0.5 . (4) (4) The results of all tests are combined in a two-step proce- dure for determination of the confidence level (Fig. 3). In the first step the overall probability for each pixel from the tests applying reflectances is derived because these tests are not independent. This is accomplished by finding the minimum probability Gi of being cloudy in both tests. In the next step the probability from the brightness temperature test and the intermediate result from the reflectance tests are combined by calculation of the square root of the multiplied values if multiple valid test results are available: If m_gemi is greater than m_gemiclear, the pixel is classified with high confidence as clear, and if m_gemi is lower than m_gemicloudy, the pixel is assumed with high confidence to be cloudy. If values in between appear, then the confidence level of being clear is calculated by a linear approach. If m_gemi is greater than m_gemiclear, the pixel is classified with high confidence as clear, and if m_gemi is lower than m_gemicloudy, the pixel is assumed with high confidence to be cloudy. If values in between appear, then the confidence level of being clear is calculated by a linear approach. A. Hünerbein et al.: The M-CM product lower threshold, the pixel is classified with high confidence as cloud-free. A test score larger than the upper threshold re- sults in labeling the pixel with high confidence as cloudy. For pixels with values in between, the confidence level is calcu- lated in a linear way. Upper and lower thresholds are defined for ocean pixels outside and inside the sunglint region, re- spectively. where Tdiff1_cs is calculated with RTTOV for each pixel for clear-sky conditions. By use of the temperature differences at 8.8–10.8 µm, thin cirrus clouds over all surface conditions can be detected. In addition to Eq. (6) if the difference is relatively high compared to the clear-sky condition, then the pixel is classified as cloudy if T8.8 −T10.8 > Tdiff2_cs. (7) (7) For a land pixel indicated by the application mask as ap- propriate, the test score is a modified GEMI (Global Environ- mental Monitoring Index) first described by Pinty and Ver- straete (1992). It is calculated as The probability of being cloud-free is calculated by assum- ing a linear probability function. The same applies for the tri-spectral brightness temperature difference test. Further in- vestigation is needed to define the base threshold, which is strongly dependent on surface and water vapor. m_gemi = η(1 −0.25 · η) −ρ0.6 −0.125 1 −ρ0.6 , (3) (3) with 2.1.3 Brightness temperature tests We use two different approaches for the brightness temper- ature tests, one using simple thresholds and the other one applying brightness temperature differences between differ- ent infrared channels for the separation between cloudy and cloud-free pixels. The first simple threshold test is applied on the 10.85 µm channel for all surface types during nighttime. The pixels is identified as cloudy if Q = n v u u t N Y i=1 Gi. (8) (8) Otherwise the final result consists of the valid test result or is undefined. The square root of the multiplied probabili- ties of a pixel being clear ensures that the overall result does not tend to cloudy pixels as would be the case if results were solely multiplied. This approach is considered clear-sky con- servative. T10.8 < T10.8_cs, (5) (5) T10.8 < T10.8_cs, where the clear-sky brightness temperature T10.8_cs, at top of the atmosphere, is calculated with the IR radiative trans- fer model (RTTOV; Saunders et al., 1999) on the grid of the auxiliary meteorological (X-MET) data and then inter- polated to the geolocation and measurement time of the MSI pixel. The X-MET dataset provides additional meteorologi- cal model parameters required for the processing (Eisinger et al., 2023). Details about the RTTOV forward simulation are described in Hünerbein et al. (2023). If T10.8_cs is larger than T10.8, the pixel is assumed to be cloudy. The probability of being cloud-free is calculated by assuming a linear probabil- ity function. The tri-spectral window brightness temperature difference test (at 8.8, 10.8 and 12.0 µm) is only applied to water surfaces during daytime. The brightness temperatures at 10.8 and at 12.0 µm are used to detect thin cirrus clouds and cloud edges, which are characterized by a higher bright- ness temperature difference (10.8–12.0 µm) than a cloud-free surface. The pixel is detected as cloudy if where the clear-sky brightness temperature T10.8_cs, at top of the atmosphere, is calculated with the IR radiative trans- fer model (RTTOV; Saunders et al., 1999) on the grid of the auxiliary meteorological (X-MET) data and then inter- polated to the geolocation and measurement time of the MSI pixel. The X-MET dataset provides additional meteorologi- cal model parameters required for the processing (Eisinger et al., 2023). Details about the RTTOV forward simulation are described in Hünerbein et al. (2023). If T10.8_cs is larger than T10.8, the pixel is assumed to be cloudy. 2.2.1 Cloud type training using MODIS A large number of MODIS scenes are used to learn statis- tics for nine predefined cloud classes (from thin to thick clouds, high, medium and low clouds) and one cloud-free class, either over sea, land or desert and separated into stripes of 15◦latitude. Nine cloud classes are categorized by us- ing the MODIS cloud top height and cloud optical thickness (6) T10.8 −T12.0 > Tdiff1_cs, T10.8 −T12.0 > Tdiff1_cs, https://doi.org/10.5194/amt-16-2821-2023 Atmos. Meas. Tech., 16, 2821–2836, 2023 2826 A. Hünerbein et al.: The M-CM product Figure 3. Four groups of cloud tests to determine cloud confidences. VRT: visible reflection tests, RRT: reflectance ratio test, dBT: brightness temperature difference. 2826 A. Hünerbein et al.: The M-CM product Figure 3. Four groups of cloud tests to determine cloud confidences. VRT: visible reflection tests, RRT: reflectance ratio test, dBT: brightness temperature difference tests to determine cloud confidences. VRT: visible reflection tests, RRT: reflectance ratio test, dBT: brightness Figure 3. Four groups of cloud tests to determine cloud confidences. VRT: visible reflection tests, RRT: reflectance ratio test, dBT: brightness temperature difference. Figure 4. Observed reflectances (Ref) and brightness (Brt) tempera- tures at VIS, SWIR-2 and TIR-2 (MODIS) for the nine ISCCP cloud classes (cirrus, cirrostratus, deep convection, altocumulus, altostra- tus, nimbostratus, cumulus, stratocumulus and stratus) and seasonal separation. based on the ISCCP cloud classification schemes (Rossow and Schiffer, 1999). From these scenes, the mean vector and covariance matrix are calculated for all cloud classes, with one cloud-free class from the visible channel, the shortwave infrared channel and the infrared channel, and saved in a lookup table. The region, season and surface are identified for each pixel. The regions are defined by a circle of latitude in 15◦ steps. The pixels are separated into four seasons (winter, spring, summer and fall) based on the month (Fig. 4). The surfaces are separated with the land–sea mask into land, water and desert pixels. The nine ISCCP cloud classes can be clearly distinguished between cirrus, cirrostratus, deep convection, altocumulus, altostratus, nimbostratus, cumulus, stratocumulus and stratus. Also a clear-sky class is defined for the different surface types, regions and seasons (not shown in Fig. 4). The statistics are then used to assign each pixel in the measured scene to a certain class by applying a maximum-likelihood classifier. The algorithm assumes ei- ther a completely cloud-covered or completely cloud-free pixel and does not take sub-pixel clouds into account. Figure 4. 2.2.1 Cloud type training using MODIS Observed reflectances (Ref) and brightness (Brt) tempera- tures at VIS, SWIR-2 and TIR-2 (MODIS) for the nine ISCCP cloud classes (cirrus, cirrostratus, deep convection, altocumulus, altostra- tus, nimbostratus, cumulus, stratocumulus and stratus) and seasonal separation. f x|mi, X i ! = 1 q (2π)p P i exp −1 2 (x −mi)T X−1 i (x −mi)  , (10) https://doi.org/10.5194/amt-16-2821-2023 2.3 M-CP: cloud phase The NDSI is the normalized ratio of the difference in re- flectance at VIS and SWIR-1. The atmosphere is transparent at both wavelengths, while snow is very reflective at VIS and not reflective at SWIR-1. The discrimination of the thermodynamic phase at the cloud top is based on the spectral absorption differences in ice and water clouds between the visible (0.67 µm) and the short- wave infrared (1.65 µm) as well as the brightness tempera- tures at 8.8, 10.8 and 12.0 µm. The cloud phase categories of the M-CP algorithm include liquid water, ice, supercooled mixed phase and cloud overlap (e.g., multi-layer clouds). The M-CP retrieval closely follows the approach applied to AVHRR and the Visible Infrared Imaging Radiometer Suite (VIIRS) (Pavolonis et al., 2005; Pavolonis and Heidinger, 2004) as well as for MODIS (Strabala et al., 1994). The al- gorithm consists of several spectral threshold tests applied to the reflectances from the VIS, SWIR and TIR channels. The thresholds are adapted from the corresponding AVHRR channels based on Pavolonis et al. (2005). The fine tuning of these thresholds will be done with the whole measure- ments suite of EarthCARE at nadir. The algorithm starts with a series of threshold tests based on TIR-2, which follows the physical assumption that the cloud top phase depends on the cloud top temperature. The liquid water category in- cludes clouds of liquid water droplets that have a tempera- ture greater than 273.16 K measured by TIR-2. Only non- opaque cirrus clouds can also fall into that category. To de- tect semitransparent cirrus clouds over optically thick water clouds, a cloud overlap test is done. The cloud overlap detec- tion uses the VIS, TIR-2 and TIR-3 channels. This method is adapted from the AVHRR algorithm explained by Pavolonis and Heidinger (2004). The underlying physical theory is that the VIS reflectance will not change much when having an overlapping thin cirrus cloud over a thick water cloud, while the temperature difference between both clouds results in a brightness temperature difference in the IR window chan- nels that is larger than predicted by radiative transfer calcu- lations. A certain pixel is defined as an ice cloud if the BT at 10.8 µm < 233.16 K and the overlap test fails. Supercooled mixed-phase cloud pixels are assumed based on threshold tests with the BT at 10.8 µm between 233.16 and 273.16 K. A. Hünerbein et al.: The M-CM product ists, the classifier applied here is a hard classifier assign- ing a class to every pixel with valid radiation data inde- pendent of the magnitude of the maximum probability. The reliability of a maximum-likelihood classification result de- pends on the probability pi = f (x|mi,P i) for the assigned class i and the probability for the next class j derived as pj = f (x|mi,P j). The next class is determined by mini- mizing argmin = [|pj−pi|] = j. The assignments to the nine cloud classes and the clear-sky class are determined for all pixels. 2.5 M-CM quality flags The M-CM quality flags provide pixel-based quality infor- mation for the cloud flag, the cloud type and the cloud phase products. The quality flags distinguish between high, medium, low and poor quality. These measures do not rep- resent probabilities but rather the number of tests which have been executed for the associated pixel, the consistency among the products or the surface flag. The definitions of the individual quality flags are provided in Table 1. The results of the M-CF and M-Ctype are also combined to a final cloud mask quality flag. A high-quality flag means that both results are consistent. 3 Verification of the M-CM algorithm performance The algorithm performance and processing chaining has been tested by applying the M-CM processor to scenes from the MODIS and MSG SEVIRI instruments and atmospheric test scenes created synthetically with the EarthCARE end-to- end simulator (Donovan et al., 2023). 2.4 Surface flag The surface flag distinguishes between water, land, desert, vegetation, snow, sea ice, sunglint and undefined. While the surface types water, land, desert and sunglint are used as in- put for the M-CM algorithm, the types vegetation and snow are calculated for the cloud-free pixels only, by using the nor- malized difference vegetation index (NDVI) and the normal- ized difference snow index (NDSI). The NDVI is the nor- malized ratio of the difference in reflectance at NIR and VIS based on the red edge feature of the vegetation. (11) NDVI = (ρ0.8 −ρ0.6)/(ρ0.8 + ρ0.6) (11) 2.2.2 Maximum-likelihood classifier (10) The probability is computed for each MSI pixel to all indi- vidual classes by means of a maximum-likelihood classifier. A pixel is assigned to class j if the likelihood of class j is the greatest among the 9 + 1 classes which are relevant for the respective surface. The maximum likelihood is found by with x being the vector of properties (reflectances and bright- ness temperature) in the considered channels, mi being the mean vector of class i, P i being the covariance matrix and p being the number of maximum-likelihood classes for the respective surface. Though a maximum-likelihood classifier that does not assign a class when the maximum- probability value falls below a certain probability also ex- j = argmax " f x|mi X i !# , (9) (9) https://doi.org/10.5194/amt-16-2821-2023 Atmos. Meas. Tech., 16, 2821–2836, 2023 2827 2.3 M-CP: cloud phase During daytime conditions, additional tests are applied using the SWIR-1 channel, which improves the detection of over- lapping and cirrus clouds. NDSI = (ρ0.6 −ρ1.6)/(ρ0.6 + ρ1.6) (12) (12) The algorithm distinguishes between sparse vegetation/o- cean and dense vegetation with the NDVI and identifies snow surfaces with the NDSI. 3.1 Verification against synthetic test scenes Three specific synthetic test scenes have been created based on forecasts from the Global Environmental Multiscale (GEM) model (Qu et al., 2022) to test the full chain of Earth- CARE processors (Donovan et al., 2023). These test scenes cover a variety of atmospheric situations over ocean, land and ice surface during day- and nighttime. The natural-color RGB images of the three test scenes are provided in Ap- pendix A. https://doi.org/10.5194/amt-16-2821-2023 Atmos. Meas. Tech., 16, 2821–2836, 2023 2828 A. Hünerbein et al.: The M-CM product Table 1. Definitions of pixel-based quality flags (high, medium, low, poor) for the cloud flag, the cloud type and the cloud phase products. Quality Cloud flag Cloud type Cloud phase status High All tests executed and results Results consistent Results consistent with BT thresholds for water consistent with M-Ctype with M-CF (BT < 233.16 K) and ice (BT > 273.16 K) Medium All tests executed and results Surface flag is ocean Surface flag is ocean inconsistent with M-Ctype Low Less than 50 % of the tests were executed Surface flag is land Surface flag is desert Poor Only one test executed (e.g., for night) Surface flag is desert Only night tests performed It seems very appealing to verify our cloud algorithm against the test scenes; however, the results should be han- dled with care because they strongly depend on the as- sumptions made in the model. But since no observational EarthCARE-like dataset exists, the synthetic model dataset provides the best available proxy for testing the EarthCARE processing chain and synergistic products (Donovan et al., 2023). The most prominent one is the Halifax scene cover- ing a 6000 km long frame starting over Greenland, cross- ing the eastern end of Canada and ending in the Caribbean (Fig. 5). The scene starts over the Greenland ice sheet with mixed-phase clouds at nighttime, transitioning from deeper clouds with tops up to 6 km around 65◦N to mixed-phase clouds with tops around 3 km at temperatures as cold as −30 ◦C over the eastern edge of Canada. Below there is a high ice cloud regime followed by a low-level cumulus cloud regime embedded in a marine aerosol layer below an elevated dirty dust layer around 5 km altitude. The original model out- puts are generated for 7 December 2015 using the Canadian GEM model (Qu et al., 2022). 3.1 Verification against synthetic test scenes While the binary cloud flag and cloud phase product provide results for the high-latitude part of the Halifax scene, the cloud type product does not show results there. This is due to the nighttime conditions. The maximum-likelihood classifier also requires information in the visible bands, which makes it impossible to classify cloud types during nighttime. For the cloud flag, only bright- ness temperature tests have been applied. For this reason, the cloud mask quality flag indicates only poor quality there. shows the reference cloud flag, based on the 3D extinction profiles for three different thresholds applied to the COT. When assuming pixels with COT ≥0.01 to be cloudy, the overall cloud fraction of the scene would be 72 %. The cloud fraction decreases to 61 % for COT ≥0.1 and to 37 % for COT ≥1. This demonstrates that the reference cloud mask is very sensitive to the choice of the COT threshold. Using M- CF, a cloud fraction of 50 % is determined for this scene (see Fig. 7). The best agreement between the cloud fraction of the reference cloud flag and the M-CF cloud flag is achieved when applying a threshold of COT ≥0.1. The cloud detec- tion sensitivity of the M-CF algorithm is clearly better than COT ≥1, but in contrast to COT ≥0.1, a few cloudy pixels with probably optically thin clouds are not detected by the M-CF cloud flag. Figure 7 illustrates the performance of the M-CF cloud flag compared to the reference cloud flag (us- ing a threshold of COT ≥0.1) by showing the results of the confusion matrix (e.g., true positive, true negative, false pos- itive, false negative). Both cloud flags are in good agreement for most parts of the scene. Only a few false-cloudy pixels are visible over the ocean, which are most likely thin clouds with COT ≤0.1 that are detected by MSI but not in the cloud flag for COT ≥0.1. The orange pixels in the center of the scene show pixels that are detected as clear-sky by M-CF, while the reference cloud flag defines them as cloudy. This can be explained by the fact that different thresholds are applied for snow and land surface types, but there are inconsistencies be- tween the surface types in the M-CF algorithm and the model data. 3.1 Verification against synthetic test scenes The M-CF algorithm uses surface information from the X-MET data as input, while the model data use slightly dif- ferent surface specifications. The scattered false-clear pixels in the lower part of the scene are due to edge pixels of low- level clouds, which are not detected by the M-CF cloud flag. Verification of the M-CF cloud flag with 3D model input fields The M-CF cloud flag is verified against the input from the 3D model fields (Donovan et al., 2023). The model cloud flag is calculated based on the extinction profiles at 680 nm from the model input, which we consider the reference. In the first step, we have calculated the cloud optical thickness (COT) as the extinction of radiation along the path from the Earth’s surface to the top of atmosphere at 680 nm. The second step defines a certain profile as cloudy applying three different thresholds, COT ≥0.01, COT ≥0.1 and COT ≥1. Figure 6 3.2 Verification against MODIS The M-CM cloud mask algorithm has also been verified against MODIS scenes. In contrast to the synthetic scenes, the MODIS scenes do not rely on the assumptions made in the background model. We have used the calibrated radiances of MODIS Terra Level 1B (L1B) (MOD021KM) of seven Atmos. Meas. Tech., 16, 2821–2836, 2023 https://doi.org/10.5194/amt-16-2821-2023 2829 A. Hünerbein et al.: The M-CM product A. Hünerbein et al.: The M-CM product p -CM processor applied to the Halifax scene including the binary cloud flag (M-CF) and cloud mask quality fl (M-CP) and quality flag (c, d), and cloud types (M-Ctype) and quality flag (e, f). The light-grey-shaded region in ndefined by the processor. cu: cumulus, ac: altocumulus, ci: cirrus, sc: stratocumulus, as: altostratus, cs: cirrostra atus, cb: cumulonimbus. Figure 5. M-CM processor applied to the Halifax scene including the binary cloud flag (M-CF) and cloud mask quality flag (a, b), the cloud phase (M-CP) and quality flag (c, d), and cloud types (M-Ctype) and quality flag (e, f). The light-grey-shaded region indicates pixels, labeled as undefined by the processor. cu: cumulus, ac: altocumulus, ci: cirrus, sc: stratocumulus, as: altostratus, cs: cirrostratus, st: stratus, ns: nimbostratus, cb: cumulonimbus. Atmos. Meas. Tech., 16, 2821–2836, 2023 Atmos. Meas. Tech., 16, 2821–2836, 2023 https://doi.org/10.5194/amt-16-2821-2023 A. Hünerbein et al.: The M-CM product 2830 Figure 6. Reference cloud flag based on the 3D extinction fields at 680 nm for the Halifax scene. Cloud-free and cloudy areas are identified by applying three different thresholds on the column-integrated cloud optical thickness, COT ≥0.01 (a), COT ≥0.1 (b) and COT ≥1 (c). The resulting cloud fraction is 72 % (COT ≥0.01), 61 % (COT ≥0.1) and 37 % (COT ≥1). Figure 6 Reference cloud flag based on the 3D extinction fields at 680 nm for the Halifax scene Cloud free and cloudy areas are identified Figure 6. Reference cloud flag based on the 3D extinction fields at 680 nm for the Halifax scene. Cloud-free and cloudy areas are identified by applying three different thresholds on the column-integrated cloud optical thickness, COT ≥0.01 (a), COT ≥0.1 (b) and COT ≥1 (c). The resulting cloud fraction is 72 % (COT ≥0.01), 61 % (COT ≥0.1) and 37 % (COT ≥1). Table 2. Comparison of the scene cloud fraction between M-CF, M-Ctype, the combination of M-CF and M-Ctype, and MODIS. Algorithm M-CF M-Ctype M-CF + MODIS M-Ctype Cloud fraction (%) 52 41 69 80 Table 2. Comparison of the scene cloud fraction between M-CF, M-Ctype, the combination of M-CF and M-Ctype, and MODIS. Table 2. Comparison of the scene cloud fraction between M-CF, M-Ctype, the combination of M-CF and M-Ctype, and MODIS. similar channels to MSI and global forecast data from the Copernicus Atmosphere Monitoring Service (CAMS) as in- put for the M-CLD processor. For verification of our results, however, we use the standard MODIS Level 2 (L2) cloud product which makes use of more spectral channels com- pared to MSI. p Figure 8 shows the MSI M-CM cloud flag and the MODIS cloud flag for an example over western Africa on 11 Septem- ber 2021 at 11:50 UTC. Both cloud flags discriminate be- tween clear-sky, cloudy, probably cloudy and probably clear. The false-color RGB image uses the MODIS band 1 (620– 670 nm), band 4 (545–565 nm) and band 3 (459–479 nm). The MSI surface flag separates between water (1), land (2), desert (3), vegetation (4), snow (5, 6), sea ice (7), sunglint (8) and undefined (0); the scene over western Africa has no snow or sea ice pixels. https://doi.org/10.5194/amt-16-2821-2023 Both desert and sunglint represent difficulties for cloud-masking algorithms, which is why the largest differences between the MODIS and MSI cloud flag are found over these surface types. The MSI cloud flag yields a cloud fraction of 52 %, while MODIS results in 80 %. Con- verting the M-Ctype cloud classes in a binary cloud class re- sults in a cloud fraction of 41 %. The product is independent from M-CF because it uses a maximum-likelihood classifier. When combining both binary M-CM cloud flags into one, the cloud fraction increases to 69 % (Table 2). This result demonstrates that the combination of both independent M- CM cloud products leads to a better agreement with MODIS than just using one of them. The MSI algorithm misses large parts of clouds over desert, but there are also clear differences over the ocean in the upper part of the scenes. These differ- ences are expected because the MODIS cloud tests are based on much more spectral channels. For the majority of clouds, which are visible on the RGB image, the agreement between the MODIS and MSI cloud flag is very good. To get more robust statistics, the cloud mask compari- son has been done for the full month of September 2021. The MSI cloud flag systematically shows a lower cloud frac- tion than the MODIS cloud flag. Only in cases with a strong sunglint effect, do the combined M-CF and M-Ctype cloud mask show a higher cloud fraction than MODIS. For as- sessing the overall agreement between the MSI and MODIS cloud mask, we have calculated the percentage of consis- tency for both clear-sky and cloudy for all 45 MODIS scenes in September 2021. The results are shown in Table 3. We have intercompared the M-CF vs. M-Ctype products, M-CF vs. MODIS, M-Ctype vs. MODIS and M-CF combined with M-Ctype vs. MODIS. The overall agreement between M-CF and MODIS is 76 %. This results increase to 79 % when com- bining M-CF and M-Ctype (Table 3). When excluding all pixels that are labeled as sunglint by the M-CM surface flag, the agreement increases to 91 %. This finding demonstrates that large parts of the discrepancies are due to differences in the handling of the algorithms in scenes effected by sunglint, which will be further investigated by tuning the thresholds with real measurements. Atmos. Meas. Tech., 16, 2821–2836, 2023 https://doi.org/10.5194/amt-16-2821-2023 2831 A. https://doi.org/10.5194/amt-16-2821-2023 Hünerbein et al.: The M-CM product A. Hünerbein et al.: The M-CM product A. Hünerbein et al.: The M-CM product Figure 7. M-CF cloud flag (a) and confusion matrix (b) indicating the classification performance (e.g., true cloudy, true clear, false cloudy, false clear) of the binary M-CF and the reference cloud flag (using a threshold of COT ≥0.1). The M-CF cloud fraction is 50 %, while the reference cloud flag results in a cloud fraction of 61 %. Figure 7. M-CF cloud flag (a) and confusion matrix (b) indicating the classification performance (e.g., true cloudy, true clear, false cloudy, false clear) of the binary M-CF and the reference cloud flag (using a threshold of COT ≥0.1). The M-CF cloud fraction is 50 %, while the reference cloud flag results in a cloud fraction of 61 %. Figure 8. M-CM algorithm applied to satellite data from MODIS over western Africa on 11 September 2021 at 11:50 UTC. The MODIS false-color RGB composite (using MODIS bands 1, 4 and 3) is shown in panel (a), the MSI surface flag is shown in panel (b), the MODIS cloud flag is shown in panel (c) and the MSI cloud flag is shown in panel (d). The MSI surface types 5, 6 and 7 are snow and sea ice flags, which are not present in the present case study. While 1 (water), 2 (land), 3 (desert) and 8 (sunglint) are inputs for the processor, type 4 (vegetation) is based on the NDVI and only calculated for clear-sky pixels in the M-CF flag. Figure 8. M-CM algorithm applied to satellite data from MODIS over western Africa on 11 September 2021 at 11:50 UTC. The MODIS false-color RGB composite (using MODIS bands 1, 4 and 3) is shown in panel (a), the MSI surface flag is shown in panel (b), the MODIS cloud flag is shown in panel (c) and the MSI cloud flag is shown in panel (d). The MSI surface types 5, 6 and 7 are snow and sea ice flags, which are not present in the present case study. While 1 (water), 2 (land), 3 (desert) and 8 (sunglint) are inputs for the processor, type 4 (vegetation) is based on the NDVI and only calculated for clear-sky pixels in the M-CF flag. Atmos. Meas. Tech., 16, 2821–2836, 2023 3.3 Verification against MSG SEVIRI The M-CM cloud mask was also part of a cloud retrieval in- tercomparison study in the framework of the International Cloud Working Group (ICWG). The ICWG supports the as- sessment of cloud retrievals applied to passive imagers on board geostationary satellites (Hamann et al., 2014; Wu et al., 2017). Therefore, the M-CM algorithm has been applied to images from the SEVIRI instrument on board Meteosat Sec- ond Generation (MSG). As in the comparison with MODIS, SEVIRI also provides similar channel characteristics like the MSI. Nevertheless, one should be aware that this leads to uncertainties through the adaptation to SEVIRI due to differ- ences in the central wavelength and spectral response func- tion, radiative transfer simulations, and generated lookup ta- bles. Figure 9. Differences between the cloud masks of 12 algorithms for the MSG SEVIRI disk on 13 April 2008. A value of 0 means that all algorithms for this particular pixel set it as cloudy. The grey values mean that all algorithms agree this pixel is cloud-free. In total the disagreement measure is normalized to 1 if the half of the algorithms classify a pixel as cloudy and the other half classify it as cloud-free. Different scientific institutions (e.g., EUMETSAT central facility, European Organisation for the Exploitation of Me- teorological Satellites; NWC SAF, Nowcasting Satellite Ap- plication Facility; and CM SAF, Climate Monitoring Satel- lite Application Facility) provided cloud mask data for the SEVIRI disk for the intercomparison study. The individual input data have been transformed into a binary cloud mask separating between cloudy and cloud-free. The M-CM cloud mask was with a cloud fraction of 52 % in the range of the other results ranging from 31 % to 64 %. Figure 9 shows the discrepancies of the different cloud masks results. A pixel value of 0 means that all algorithms are in agreement that it is cloudy. Grey values indicate that all algorithms consis- tently label the pixel as clear-sky. A disagreement value of 1 shows that half of the algorithms classified a pixel as cloudy, and the other half did so as cloud-free. The main discrepan- cies between the different cloud masks are found to be over northern Africa, caused by different detection thresholds for thin cirrus clouds over bright surface like desert in this case. It could also be biomass burning aerosol that is classified as clouds by some algorithms. 3.3 Verification against MSG SEVIRI Another area of disagreements is the southern part of the Arabian Peninsula and the adjacent sea. (M-CP) and cloud type (M-Ctype) products. The cloud flag and cloud phase at the cloud top are based on spectral thresh- old tests for the visible and infrared channels, while the cloud type product is based on a maximum-likelihood classifier. While the cloud type product is only available during day- time, the cloud flag and cloud phase products are also re- trieved during nighttime, although with a reduced number of tests (Fig. 1). The M-CM products are an important input for the subsequent retrieval of the cloud optical and physical products (M-COP) (Hünerbein et al., 2023) and the aerosol optical properties (M-AOT) (Docter et al., 2023). In order to test the algorithm performance and to get a bet- ter impression of the products before the EarthCARE launch, the M-CM algorithm has been verified in this study against synthetic test scenes from the EarthCARE end-to-end simu- lator and satellite data from MODIS and MSG SEVIRI. Using synthetic test data, it is found that the M-CM prod- ucts are in good agreement with the products from other pro- cessors within the EarthCARE instrument suite and with the 3D model fields used as input to the simulator which can thus be considered the truth. One should keep in mind that in contrast to ATLID or CPR, which provide vertical profile A. Hünerbein et al.: The M-CM product Table 3. Comparison of the two M-CM cloud flags and the MODIS cloud flag. The agreement in percent is calculated for a binary cloud flag only, where confidently cloudy and probably cloudy is merged to cloudy and the same is done for clear-sky. For M-Ctype, cloud types 1–9 are considered cloudy. M-Ctype vs. MODIS M-CF + M-Ctype vs. MODIS 65 % 79 % 87 % 91 % Figure 9. Differences between the cloud masks of 12 algorithms for the MSG SEVIRI disk on 13 April 2008. A value of 0 means that all algorithms for this particular pixel set it as cloudy. The grey values mean that all algorithms agree this pixel is cloud-free. In total the disagreement measure is normalized to 1 if the half of the algorithms classify a pixel as cloudy and the other half classify it as cloud-free. Algorithm M-CF vs. M-Ctype M-CF vs. MODIS M-Ctype vs. MODIS M-CF + M-Ctype vs. MODIS Full scene 80 % 76 % 65 % 79 % No sunglint 92 % 90 % 87 % 91 % hm M-CF vs. M-Ctype M-CF vs. MODIS M-Ctype vs. MODIS M-CF + M-Ctype vs. MODIS https://doi.org/10.5194/amt-16-2821-2023 https://doi.org/10.5194/amt-16-2821-2023 2832 Appendix A: Natural-color RGB images of the synthetic test scenes For the three test scenes natural-color RGB images are gen- erated to visualize several types of atmospheric and surface features. The natural-color RGB is composed of the VIS, NIR and SWIR-1 channel data. The images have been lin- early stretched within the reflectance ranges to the full range of display values from 0–255 bytes to improve the contrast. The M-CM algorithm has also been applied to measure- ments from MSG SEVIRI, and the results have been com- pared against other cloud mask algorithms in the frame of the International Cloud Working Group. The comparison has demonstrated that the M-CM performance lies in the range of the other cloud masks. p y y p The benefit is the easy interpretation because most of the colors of the image are very similar to a true-color image of the Earth. Figure A1 shows the RGB images for the three test scenes, which includes clouds, snow, vegetation, sunglint and clear skies. Snow on the ground as well as ice over moun- tains, frozen lakes and sea ice appear cyan in the RGB im- ages (Fig. A1b). The more homogeneous the snow/ice cover is, the brighter the cyan color will be. Snow and ice on moun- tains will therefore be depicted in a stronger cyan color than snowy surfaces on ground, which are often disrupted by veg- etation. In addition, clouds with ice crystals also appear cyan in the RGB images (Fig. A1a) as the ice crystals reflected at 0.67 and 0.865 µm and absorb solar radiation at 1.65 µm. Further different cloud heights, ice crystal habits and sun zenith angles lead to an inhomogeneous color pattern. The ocean and lakes in the RGB images appear in dark black (Fig. A1c). Vegetation is indicated by green colors because of the stronger reflection of solar radiation at 0.865 µm than at 0.67 µm (Fig. A1a, e.g., Caribbean island in the Halifax scene). For detailed information on how to interpret RGB im- ages, see the RGB color guide (Eumetrain, 2022). Planned improvements in M-CM will include dynamic thresholds for the threshold tests for the cloud flag. We pro- pose that this tuning should be done after launch once real observations will be available. A tuning of the M-CM thresh- olds towards better agreement with MODIS is not optimal in the current state because of the spectral differences between MSI and MODIS. A. Hünerbein et al.: The M-CM product based on configuration files, which allows for easy adjust- ment, e.g., of cloud mask thresholds without modifying the source code of the whole algorithm chain. information, MSI is a passive instrument that retrieves cloud properties at the cloud top or, for aerosol and optically thin clouds, total column-integrated information. The synergistic products using data from MSI and ATLID will help to bet- ter understand some of the uncertainties in the MSI products (Haarig et al., 2023). In contrast to the pre-launch MSI test data presented in this study, the MSI spectral bands are affected by a shift in the central wavelength depending on the instrument view- ing angle. This effect is caused due to imperfections in the bandpass filters on the curved optical lenses (e.g., Wehr et al., 2023; Wang et al., 2022). Investigations are ongoing to mitigate this effect in the Level 2 M-CLD and M-AOT re- trievals. During the validation phase, aircraft measurements with high spectral resolution will further help to quantify the impact of the central wavelength shift on the MSI cloud and aerosol products. g An overall agreement of 79 % was found between the MSI and the MODIS cloud flag using 1 month of MODIS data over Cabo Verde in September 2021. The agreement signif- icantly improves to 91 % when excluding the sunglint areas from the comparison. Ocean areas characterized by sunglint represent some of the most challenging scenes for cloud- masking algorithms. This indicates that further adjustments are needed for the thresholds of the M-CM cloud flag for sunglint conditions to improve the performance. However, the MSI images are less affected by sunglint in comparison to MODIS due to the fact that the MSI is tilted sideways, with 35 km of the full 150 km swath on the sun-facing side and 115 km on the other side of the nadir track. 4 Conclusions In this paper, the algorithms used by the cloud mask proces- sor (M-CM) for the MSI on board EarthCARE are described. The algorithms provide the cloud flag (M-CF), cloud phase https://doi.org/10.5194/amt-16-2821-2023 Atmos. Meas. Tech., 16, 2821–2836, 2023 2833 https://doi.org/10.5194/amt-16-2821-2023 A. Hünerbein et al.: The M-CM product Figure A1. Natural-color RGB images generated from the MSI VIS, NIR and SWIR-1 channels for (a) Halifax, (b) Baja and (c) Hawaii (Donovan et al., 2023). Figure A1. Natural-color RGB images generated from the MSI VIS, NIR and SWIR-1 channels for (a) Halifax, (b) Baja and (c) Hawaii (Donovan et al., 2023). Data availability. The EarthCARE Level 2 demonstration products from simulated scenes, including the MSI cloud mask products discussed in this paper, are available at https://doi.org/10.5281/zenodo.7117115 (van Zadelhoff et al., 2022). Acknowledgements. The authors thank Tobias Wehr and Michael Eisinger for their continuous support over many years and the EarthCARE developer team for valuable discussions during vari- ous meetings. The authors would like to express their gratitude to the MODIS and SEVIRI science team for providing their data to the scientific community. The authors acknowledge ESA for the finan- cial support. Acknowledgements. The authors thank Tobias Wehr and Michael Eisinger for their continuous support over many years and the EarthCARE developer team for valuable discussions during vari- ous meetings. The authors would like to express their gratitude to the MODIS and SEVIRI science team for providing their data to the scientific community. The authors acknowledge ESA for the finan- cial support. Author contributions. The manuscript was prepared by AH, SB and HD. The M-CM code was developed by AH and SH. AW generated the dataset and created the plots for the ICWG results. Financial support. This research has been funded by the European Space Agency (ESA) (grant nos. 4000112018/14/NL/CT (APRIL) and 4000134661/21/NL/AD (CARDINAL)). Competing interests. The contact author has declared that none of the authors has any competing interests. The publication of this article was funded by the Open Access Fund of the Leibniz Association. Disclaimer. Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Review statement. This paper was edited by Robin Hogan and re- viewed by two anonymous referees. Special issue statement. This article is part of the special issue “EarthCARE Level 2 algorithms and data products”. It is not as- sociated with a conference. Appendix A: Natural-color RGB images of the synthetic test scenes While MSI features 7 spectral bands, MODIS has 36 spectral bands, allowing for better cloud de- tection performance. The advantage of the MSI observations are, in contrast to MODIS, that MSI is flying together with active instruments (e.g., ATLID and CPR) on the same plat- form, which will allow for unique synergies of cloud prod- ucts from different instruments. The algorithm verification in the present study uses syn- thetic test scenes and data from other satellite platforms as the basis. During the validation phase after the Earth- CARE launch, dedicated campaigns will be conducted us- ing ground-based and airborne instruments, which will of- fer the opportunity for a more comprehensive validation of the MSI cloud products. Also geostationary satellites will be used for the validation to support the selection of suitable validation datasets and to provide complementary reference datasets on a global scale. Meteosat Third Generation (MTG) was launched in 2022 into geostationary orbit (Holmlund et al., 2021), offering with its Flexible Combined Imager (FCI) with 16 spectral channels and up to 500 m spatial sampling excellent opportunities for the validation of and synergies with the MSI products. Further improvements in the M-CM product are expected once real observations are available due to its flexible design Atmos. Meas. Tech., 16, 2821–2836, 2023 https://doi.org/10.5194/amt-16-2821-2023 2834 A. Hünerbein et al.: The M-CM product A. Hünerbein et al.: The M-CM product Mateo-García, G., Gómez-Chova, L., and Camps-Valls, G.: Convolutional neural networks for multispectral im- age cloud masking, in: 2017 IEEE International Geo- science and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA, 23–28 July 2017, IEEE, 2255–2258, https://doi.org/10.1109/IGARSS.2017.8127438, 2017. Hamann, U., Walther, A., Baum, B., Bennartz, R., Bugliaro, L., Derrien, M., Francis, P. N., Heidinger, A., Joro, S., Kniffka, A., Le Gléau, H., Lockhoff, M., Lutz, H.-J., Meirink, J. F., Minnis, P., Palikonda, R., Roebeling, R., Thoss, A., Platnick, S., Watts, P., and Wind, G.: Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms, At- mos. Meas. Tech., 7, 2839–2867, https://doi.org/10.5194/amt-7- 2839-2014, 2014. Nakajima, T. Y., Tsuchiya, T., Ishida, H., Matsui, T. N., and Shi- moda, H.: Cloud detection performance of spaceborne visible- to-infrared multispectral imagers, Appl. Optics, 50, 2601, https://doi.org/10.1364/ao.50.002601, 2011. Hollstein, A., Fischer, J., Carbajal Henken, C., and Preusker, R.: Bayesian cloud detection for MERIS, AATSR, and their combination, Atmos. Meas. Tech., 8, 1757–1771, https://doi.org/10.5194/amt-8-1757-2015, 2015. Pavolonis, M. J. and Heidinger, A. K.: Daytime cloud overlap de- tection from AVHRR and VIIRS, J. Appl. Meteorol. Clim., 43, 762–778, 2004. p g Holmlund, K., Grandell, J., Schmetz, J., Stuhlmann, R., Bojkov, B., Munro, R., Lekouara, M., Coppens, D., Viticchie, B., August, T., Theodore, B., Watts, P., Dobber, M., Fowler, G., Bojinski, S., Schmid, A., Salonen, K., Tjemkes, S., Aminou, D., and Blythe, P.: Meteosat Third Generation (MTG): Continuation and Inno- vation of Observations from Geostationary Orbit, B. Am. Mete- orol. Soc., 102, E990–E1015, https://doi.org/10.1175/BAMS-D- 19-0304.1, 2021. Pavolonis, M. J., Heidinger, A. K., and Uttal, T.: Daytime global cloud typing from AVHRR and VIIRS: Algorithm description, validation, and comparisons, J. Appl. Meteorol., 44, 804–826, 2005. Pinty, B. and Verstraete, M.: GEMI: a non-linear index to mon- itor global vegetation from satellites, Vegetatio, 101, 15–20, https://doi.org/10.1007/BF00031911, 1992. Platnick, S., King, M. D., Ackerman, S. A., Menzel, W. P., Baum, B. A., Riedi, J. C., and Frey, R. A.: The MODIS cloud products: Algorithms and examples from Terra, IEEE T. Geosci. Remote, 41, 459–473, 2003. Hughes, M. J. and Kennedy, R.: High-quality cloud masking of Landsat 8 imagery using convolutional neural networks, Remote Sens., 11, 2591, https://doi.org/10.3390/rs11212591, 2019. Qu, Z., Donovan, D. P., Barker, H. W., Cole, J. N. S., Shephard, M. W., and Huijnen, V.: Numerical Model Generation of Test Frames for Pre-launch Studies of EarthCARE’s Retrieval Al- gorithms and Data Management System, Atmos. Meas. Tech. Discuss. A. Hünerbein et al.: The M-CM product 2835 https://atmosphere-imager.gsfc.nasa.gov/sites/default/files/ ModAtmo/MOD35_ATBD_Collection6_1.pdf (last access: 31 May 2023), 2002. https://atmosphere-imager.gsfc.nasa.gov/sites/default/files/ ModAtmo/MOD35_ATBD_Collection6_1.pdf (last access: 31 May 2023), 2002. hard, M. W., Velázquez-Blázquez, A., Wandinger, U., Wehr, T., and van Zadelhoff, G.-J.: The EarthCARE satellite: The next step forward in global measurements of clouds, aerosols, precipita- tion, and radiation, Bulletin of the American Meteorological So- ciety, 96, 1311–1332, 2015. Ackerman, S. A., Strabala, K. I., Menzel, W. P., Frey, R. A., Moeller, C. C., and Gumley, L. E.: Discriminating clear sky from clouds with MODIS, J. Geophys. Res.-Atmos., 103, 32141– 32157, https://doi.org/10.1029/1998JD200032, 1998. IPC IPCC: Climate Change 2021: The Physical Science Basis. Con- tribution of Working Group I to the Sixth Assessment Re- port of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, ISBN: 978-92-9169-158-6, in press, https://www.ipcc.ch/report/ar6/wg1/downloads/report/ IPCC_AR6_WGI_SPM_final.pdf (last access: 31 May 2023), 2021. Docter, N., Preusker, R., Filipitsch, F., Kritten, L., Schmidt, F., and Fischer, J.: Aerosol optical depth retrieval from the Earth- CARE multi-spectral imager: the M-AOT product, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-150, 2023. Donovan, D. P., Kollias, P., Velázquez Blázquez, A., and van Zadel- hoff, G.-J.: The Generation of EarthCARE L1 Test Data sets Using Atmospheric Model Data Sets, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-384, 2023. Eisinger, M., Wehr, T., Kubota, T., Bernaerts, D., and Wallace, K.: The EarthCARE production model and auxiliary products, At- mos. Meas. Tech., in preparation, 2023. Li, Z., Shen, H., Cheng, Q., Liu, Y., You, S., and He, Z.: Deep learn- ing based cloud detection for medium and high resolution remote sensing images of different sensors, ISPRS J. Photogramm., 150, 197–212, https://doi.org/10.1016/j.isprsjprs.2019.02.017, 2019. Eumetrain: RGB color guide, https://www.eumetrain.org/index. php/rgb-color-guide (last access: 22 November 2022), 2022. Haarig, M., Hünerbein, A., Wandinger, U., Docter, N., Bley, S., Donovan, D., and van Zadelhoff, G.-J.: Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023- 327, 2023. Liu, Y., Key, J. R., Frey, R. A., Ackerman, S. A., and Menzel, W.: Nighttime polar cloud detection with MODIS, Remote Sens. En- viron., 92, 181–194, https://doi.org/10.1016/j.rse.2004.06.004, 2004. References Ackerman, A., Strabala, K., Menzel, P., Frey, R., Moeller, C., Gumley, L., Baum, B., Seemann, S., and Zhang, H.: Dis- criminating Clear-Sky from Cloud with MODIS—Algorithm Theoretical Basis Document (MOD35), ATBD Reference Number: ATBD-MOD-06, Goddard Space Flight Center, Atmos. Meas. Tech., 16, 2821–2836, 2023 https://doi.org/10.5194/amt-16-2821-2023 Atmos. Meas. Tech., 16, 2821–2836, 2023 Atmos. Meas. Tech., 16, 2821–2836, 2023 https://doi.org/10.5194/amt-16-2821-2023 Atmos. Meas. Tech., 16, 2821–2836, 2023 A. Hünerbein et al.: The M-CM product 2836 Rossow, W. B. and Schiffer, R. A.: Advances in un- derstanding clouds from ISCCP, B. Am. Meteorol. Soc., 80, 2261–2288, https://doi.org/10.1175/1520- 0477(1999)080<2261:AIUCFI>2.0.CO;2, 1999. Wang, M., Nakajima, T. Y., Roh, W., Satoh, M., Suzuki, K., Kubota, T., and Yoshida, M.: Evaluation of the smile effect on the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE)/Multi- Spectral Imager (MSI) cloud product, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-736, 2022. Saunders, R. W. and Kriebel, K. T.: An improved method for de- tecting clear sky and cloudy radiances from AVHRR data, Int. J. Remote Sens., 9, 123–150, 1988. Wehr, T., Kubota, T., Tzeremes, G., Wallace, K., Nakatsuka, H., Ohno, Y., Koopman, R., Rusli, S., Kikuchi, M., Eisinger, M., Tanaka, T., Taga, M., Deghaye, P., Tomita, E., and Bernaerts, D.: The EarthCARE Mission – Science and System Overview, EGU- sphere [preprint], https://doi.org/10.5194/egusphere-2022-1476, 2023. Saunders, R. W., Matricardi, M., and Brunel, P.: An Improved Fast Radiative Transfer Model for Assimilation of Satellite Radiances Observations, Q. J. Roy. Meteor. Soc., 125, 1407–1425, 1999. Schiffer, R. A. and Rossow, W. B.: The International Satellite Cloud Climatology Project (ISCCP): The First Project of the World Cli- mate Research Programme, B. Am. Meteorol. Soc., 64, 779–784, https://doi.org/10.1175/1520-0477-64.7.779, 1983. Wu, D. L., Baum, B. A., Choi, Y.-S., Foster, M. J., Karlsson, K.- G., Heidinger, A., Poulsen, C., Pavolonis, M., Riedi, J., Roe- beling, R., Sherwood, S., Thoss, A., and Watts, P.: Toward Global Harmonization of Derived Cloud Products, B. Am. Me- teorol. Soc., 98, ES49–ES52, https://doi.org/10.1175/BAMS-D- 16-0234.1, 2017. p g Skakun, S., Wevers, J., Brockmann, C., Doxani, G., Aleksandrov, M., Batiˇc, M., Frantz, D., Gascon, F., Gómez-Chova, L., Hagolle, O., López-Puigdollers, D., Louis, J., Lubej, M., Mateo-García, G., OSMAN, J., Peressutti, D., Pflug, B., Puc, J., Richter, R., Roger, J.-C., Scaramuzza, P., Vermote, E., Vesel, N., Zupanc, A., and Žust, L.: CMIX: Cloud Mask Intercomparison eXercise, in: Living Planet Symposium, Bonn, Germany, 23–27 May 2022, https://elib.dlr.de/187698/ (last access: 31 May 2023), 2022. Zekoll, V., Main-Knorn, M., Alonso, K., Louis, J., Frantz, D., Richter, R., and Pflug, B.: Comparison of Masking Al- gorithms for Sentinel-2 Imagery, Remote Sens., 13, 137, https://doi.org/10.3390/rs13010137, 2021. Strabala, K. I., Ackerman, S. A., and Menzel, W. P.: Cloud Proper- ties inferred from 8–12-µm Data, J. Appl. Meteorol. Clim., 33, 212–229, 1994. van Zadelhoff, G.-J., Barker, H. W., Baudrez, E., Bley, S., Cler- baux, N., Cole, J. N. S., de Kloe, J., Docter, N., Domenech, C., Donovan, D. A. Hünerbein et al.: The M-CM product [preprint], https://doi.org/10.5194/amt-2022-300, in re- view, 2022. Hünerbein, A., Bley, S., Deneke, H., Meirink, J. F., van Zadelhoff, G.-J., and Walther, A.: Cloud optical and phys- ical properties retrieval from EarthCARE multi-spectral imager: the M-COP products, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-305, 2023. Illingworth, A. J., Barker, H., Beljaars, A., Ceccaldi, M., Chepfer, H., Clerbaux, N., Cole, J., Delanoë, J., Domenech, C., Donovan, D. P., Fukuda, S., Hirakata, M., Hogan, R. J., Huenerbein, A., Kollias, P., Kubota, T., Nakajima, T., Nakajima, T. Y., Nishizawa, T., Ohno, Y., Okamoto, H., Oki, R., Sato, K., Satoh, M., Shep- Rossow, W. B. and Garder, L. C.: Cloud detection using satellite measurements of infrared and visible radiances for ISCCP, J. Cli- mate, 6, 2341–2369, 1993. https://doi.org/10.5194/amt-16-2821-2023 Atmos. Meas. Tech., 16, 2821–2836, 2023 https://doi.org/10.5194/amt-16-2821-2023 A. Hünerbein et al.: The M-CM product P., Dufresne, J.-L., Eisinger, M., Fischer, J., García-Marañón, R., Haarig, M., Hogan, R. J., Hünerbein, A., Kollias, P., Koopman, R., Madenach, N., Mason, S. L., Preusker, R., Puigdomènech Treserras, B., Qu, Z., Ruiz-Saldaña, M., Shephard, M., Velázquez-Blazquez, A., Villefranque, N., Wandinger, U., Wang, P., and Wehr, T.: EarthCARE level-2 demonstration products from simulated scenes, Zenodo [data set], https://doi.org/10.5281/zenodo.7117116, 2022. https://doi.org/10.5194/amt-16-2821-2023 Atmos. Meas. Tech., 16, 2821–2836, 2023
https://openalex.org/W3080285104
https://ieeexplore.ieee.org/ielx7/6287639/8948470/09174849.pdf
English
null
Parallel-Type Asymmetric Memristive Diode-Bridge Emulator and Its Induced Asymmetric Attractor
IEEE access
2,020
cc-by
6,820
Received August 10, 2020, accepted August 19, 2020, date of publication August 24, 2020, date of current version September 8, 2020. 2020, accepted August 19, 2020, date of publication August 24, 2020, date of current version September 8, 2020. Received August 10, 2020, accepted August 19, 2020, date of publication August 24, 2020, date of current version September 8, 2020. Digital Object Identifier 10.1109/ACCESS.2020.3018728 Digital Object Identifier 10.1109/ACCESS.2020.3018728 INDEX TERMS Asymmetry, parallel-type AMDB emulator, asymmetric attractor, Chua’s circuit. INDEX TERMS Asymmetry, parallel-type AMDB emulator, asymmetric attractor, Chua’s circu Parallel-Type Asymmetric Memristive Diode-Bridge Emulator and Its Induced Asymmetric Attractor YI YE , (Graduate Student Member, IEEE), JIE ZHOU, (Graduate Student Member, IEEE), QUAN XU , (Member, IEEE), MO CHEN , (Member, IEEE), AND HUAGAN WU , (Member, IEEE) School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China Corresponding author: Huagan Wu (wuhg@cczu.edu.cn) is work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ YI YE , (Graduate Student Member, IEEE), JIE ZHOU, (Graduate Student Member, IEEE), QUAN XU , (Member, IEEE), MO CHEN , (Member, IEEE), AND HUAGAN WU , (Member, IEEE) School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China This work was supported in part by the National Natural Science Foundation of China under Grant 61801054 and Grant 51777016, in part by the Natural Science Foundation of Jiangsu Province, China, under Grant BK20191451, and in part by the Postgraduate Education Reform Projects of Jiangsu Province under Grant KYCX19_1766 and Grant KYCX20_2550. ABSTRACT Symmetry brings beauty, while asymmetry is the general law of nature. This paper reports a novel parallel-type asymmetric memristive diode-bridge (AMDB) emulator, which is implemented by an unbalance diode-bridge linked with a RC filter. Following the voltage constraints of the unbalance diode-bridge, the mathematical model of the parallel-type AMDB emulator is established. Thereafter, the asymmetric property of the hysteresis loops is demonstrated by the numerical simulations and confirmed by the hardware experiments. Furthermore, by importing the parallel-type AMDB emulator into the classical Chua’s circuit, a novel memristive Chua’s circuit is proposed, so that the asymmetric double-scroll chaotic attractor, asymmetric coexisting single-scroll chaotic attractors, and asymmetric coexisting limit cycles can be revealed herein. The parallel-type AMDB emulator enriches the types of memristor emulators and it can mimic the asymmetric property of the physical memristor device. I. INTRODUCTION M i k welcomed because of the simple structure, no grounded lim- itation, easy circuit access and so on. Memristor, known as the fourth circuit element, is a dazzling star in electronic circuit fundamentals [1], [2]. Its nano-scale property makes the device occupy exceedingly small layout area in IC application [3], the non-volatile property makes it be well received in neuromorphic circuit and informat- ics processing [4]–[7], and the nonlinearity property makes it contribute to the generation of abundant and complex dynamical behaviors in memristive chaotic circuits [8]–[12]. Unfortunately, for the difficulty of its fabrication, the physical memristor device is inconvenient to acquire through regu- lar purchasing channels. For the convenience of scientific research, numerous mathematical models [13]–[15], PSpice models [16] and analog circuit emulators [17]–[20] were reported for equivalently implementing the characteristics of various memristors in the past few years. Among those, the memristive diode-bridge emulator [8], [10] is greatly In general, the diode-bridge circuit has a symmetrical structure with four diode bridge arms. Thus, the pre-existing memristive diode-bridge emulators just exhibit the symmetric hysteresis loops pinched at the origin [8], [20], [21]. However, the physical memristor device usually possesses the asym- metric hysteresis loops [2], [22]. The influence of symmetric- breaking phenomenon on the dynamical systems has attracted much attention [23]–[27]. Recently, Kengne et al took the antiparallel semiconductor diodes pair as an asymmetric nonlinear emulator, upon which various asymmetry-induced dynamical behaviors were revealed in several asymmetric chaotic circuits [28]–[31]. Inspired by this, a series-type asymmetric memristive diode-bridge (AMDB) emulator was newly proposed by inserting an extra diode into the first bridge arm of diode-bridge circuit [32]. Based on the series- type AMDB emulator, two asymmetric memristor-based jerk circuits were constructed. Since there is only one zero equi- librium, these two asymmetric memristor-based jerk circuits only generated the single-scroll attractors with the relatively The associate editor coordinating the review of this manuscript and approving it for publication was Norbert Herencsar . 156299 Y. Ye et al.: Parallel-Type AMDB Emulator and Its Induced Asymmetric Attractor FIGURE 1. Circuit schematic of the parallel-type AMDB emulator. simple dynamics, resulting in that the asymmetry of attractor topologies could not be presented perfectly. Meanwhile, it can be found that the asymmetry property can be enhanced when inserting more diodes into two symmetric bridge arms in series. However, the forward voltage required for the bridge arm will be enlarged. II. CIRCUIT STRUCTURE AND MATHEMATICAL MODEL II. CIRCUIT STRUCTURE AND MATHEMATICAL MODEL The memristive diode-bridge emulators, consisting of a sym- metric diode-bridge and a RC filter, can exhibit the symmetric hysteresis loops pinched at the origin [21]. To mimic the asymmetric hysteresis loops appeared in physical memristor devices [2], [22], two diode parallel arrays are introduced into the first and third branches to obtain asymmetric property, as shown in Fig. 1. Each diode parallel array has m diodes connected in parallel, which is marked as DPA in Fig. 1. The parameter m is a positive integer. Thus, the branches B1 and B3 are different from the branches B2 and B4, rusting in the construction of unbalance diode-bridge. In this paper, such an analog discrete components-based memristor emulator is called as a parallel-type AMDB emulator. vD1 + vD3 = v −v0, (4) (4) and for another circuit loop of D2, C0, D4 and input voltage source, there yields and for another circuit loop of D2, C0, D4 and input voltage source, there yields vD2 + vD4 = −v −v0, (5) (5) Based on Kirchhoff’s current law, for the nodes linked with the branches B1, B4, and the branches B2, B3, we can get the following equations i = iD1 −iD4 = iD3 −iD2, (6) (6) and for the node linked with the branches B1, B2, we can get iD1 + iD2 = C0 dv0 dt + v0 R0 . (7) (7) I. INTRODUCTION M i k In this way, a much larger input voltage should be applied in its application circuit, which extremely limits the circuit applications of series-type AMDB emulator. To solve this issue, a novel parallel-type AMDB emulator is proposed in this paper. The rest of the paper is arranged as follows. In Section II, the circuit structure and mathemat- ical model of the parallel-type AMDB emulator is proposed, and the voltage constrains of the unbalance diode-bridge are verified. Afterwards, the volt-ampere curve of the proposed parallel-type AMDB emulator is demonstrated by the numer- ical simulations and confirmed by the hardware experiments. In Section III, a parallel-type AMDB emulator-based Chua’s circuit is established and some asymmetric chaotic attractors and limit cycles are perfectly embodied by the numerical simulations and the hardware experiments. The end is some discussions and conclusions. FIGURE 1. Circuit schematic of the parallel-type AMDB emulator. B1, B3, and the branches B2, B4). In other word, the voltages satisfy the following constrains vD1 = vD3, vD2 = vD4, (3) (3) The two voltage constraints are the key to derive the math- ematical model of the parallel-type AMDB emulator, which will be confirmed in the next part. According to Kirchhoff’s voltage law, for the circuit loop of DPA1, C0, DPA3 and input voltage source, one can obtain A. MATHEMATICAL MODEL Denote iDk, iDl, and i as the currents flowing through the diode Dk, diode parallel array DPAl, and parallel-type AMDB emulator, respectively. And denote vDk, vDl, and v as the voltages across Dk, DPAl, and AMDB emulator, respectively. All the diodes have identical model parameters IS (reverse saturation current), n (emission coefficient), and VT (thermal voltage). Then, the constitutive relations of the diode Dk and diode parallel array DPAl can be unified as Substituting (3) into (4) and (5), there yields Substituting (3) into (4) and (5), there yields 2vD1 = 2vD3 = v −v0, (8) 2vD2 = 2vD4 = −v −v0. (9) (8) (9) (8) (9) (9) According to the constitutive relations of Dk and DPAl in (1) and (2), the equations given in (6) and (7) can be rewritten as i = IS(me2ξvD3 −e2ξvD2 −m + 1), (10) dv0 dt = IS(me2ξvD3 + e2ξvD2 −m −1) C0 − v0 R0C0 . (11) (10) iDk = IS(e2ξvDk −1), (1) (1) (11) and Substituting (8) and (9) into (10) and (11), the above equa- tions can be organized as iDl = mIS(e2ξvDk −1), (2) (2) i = G(v0, v)v = IS[meξ(v−v0) −e−ξ(v+v0) −m + 1], (12a) dv0 dt = g(v0, v) respectively, where k = 11, . . . , 1m, 2, 31, . . . , 3m, and 4, l = 1, 3, ξ = 1/(2nV T ). (12a) There exist two conditional identities for the voltages across two pairs of the parallel bridge arms (the branches dv0 dt = g(v0, v) VOLUME 8, 2020 156300 Y. Ye et al.: Parallel-Type AMDB Emulator and Its Induced Asymmetric Attractor FIGURE 2. Multisim simulation analysis for the parallel-type AMDB emulator with m = 4 when applying V = 3 sin(40000πt), (a) the voltage constraint of branches B1 and B3, (b) the voltage constraint of branches B2 and B4. FIGURE 3. Experimental synchronous lines of the parallel-type AMDB emulator with m = 4 when applying V = 3 sin(40000πt), (a) the voltage constraint of vD1 = vD3, (b) the voltage constraint of vD2 = vD4. = IS[meξ(v−v0) + e−ξ(v+v0) −m −1] C0 − v0 R0C0 . (12b) Therefore, the proposed parallel-type AMDB emula in Fig. 1 can be described by (12), which accords with t definition of an e tended memristor in [33] FIGURE 2. A. MATHEMATICAL MODEL Experimental captured hysteresis loops for the parallel-type AMDB emulator with R0 = 1.3 k and C0 = 100 nF, (a) m = 4, f = 2 kHz, 10 kHz and 20 kHz; (b) f = 20 kHz, m = 1, 4, 8 and 16. Note that the output signal in Ch4 is enlarged by 10 times of the captured current i. FIGURE 6. Parallel-type AMDB emulator-based Chua’s circuit. A. MATHEMATICAL MODEL Multisim simulation analysis for the parallel-type AMDB emulator with m = 4 when applying V = 3 sin(40000πt), (a) the voltage constraint of branches B1 and B3, (b) the voltage constraint of branches B2 and B4. FIGURE 2. Multisim simulation analysis for the parallel-type AMDB emulator with m = 4 when applying V = 3 sin(40000πt), (a) the voltage constraint of branches B1 and B3, (b) the voltage constraint of branche FIGURE 2. Multisim simulation analysis for the parallel-type AMDB emulator with m = 4 when applying V = 3 sin(40000πt), (a) the voltage constraint of branches B1 and B3, (b) the voltage constraint of branches FIGURE 3. Experimental synchronous lines of the parallel-type AMDB emulator with m = 4 when applying V = 3 sin(40000πt), (a) the voltage constraint of vD1 = vD3, (b) the voltage constraint of vD2 = vD4. = IS[meξ(v−v0) + e−ξ(v+v0) −m −1] C0 − v0 R0C0 . (12b) Therefore, the proposed parallel-type AMDB emulator in Fig. 1 can be described by (12), which accords with the definition of an extended memristor in [33]. Therefore, the proposed parallel-type AMDB emulator in Fig. 1 can be described by (12), which accords with the definition of an extended memristor in [33]. 156301 VOLUME 8, 2020 Y. Ye et al.: Parallel-Type AMDB Emulator and Its Induced Asymmetric Attractor FIGURE 4. Numerical simulated hysteresis loops for the parallel-type AMDB emulator with R0 = 1.3 k and C0 = 100 nF, (a) m = 4, f = 2 kHz, 10 kHz and 20 kHz; (b) f = 20 kHz, m = 1, 4, 8 and 16. FIGURE 5. Experimental captured hysteresis loops for the parallel-type AMDB emulator with R0 = 1.3 k and C0 = 100 nF, (a) m = 4, f = 2 kHz, 10 kHz and 20 kHz; (b) f = 20 kHz, m = 1, 4, 8 and 16. Note that the output signal in Ch4 is enlarged by 10 times of the captured current i. FIGURE 4. Numerical simulated hysteresis loops for the parallel-type AMDB emulator with R0 = 1.3 k and C0 = 100 nF, (a) m = 4, f = 2 kHz, RE 4. Numerical simulated hysteresis loops for the parallel-type AMDB emulator with R0 = 1.3 k and C0 = 100 nF, (a) m z and 20 kHz; (b) f = 20 kHz, m = 1, 4, 8 and 16. FIGURE 5. B. CONFIRMATION OF VOLTAGE CONSTRAIN The blue and red attractors are initiated from (−1 nV, 0 V, 0 V, 0 V) and (1 nV, 0 V, 0 V, 0 V), respectively. FIGURE 8. Equilibrium points fixed by the function curve intersections and phase portraits (C2 = 34 nF) of system (13) with m increasing from 1, to 4, to 8, and to 16 in the v2-v0 plane. The blue and red attractors are initiated from (−1 nV, 0 V, 0 V, 0 V) and (1 nV, 0 V, 0 V, 0 V), respectively. FIGURE 7. Topological evolutions of different types of attractors with m increasing from 1, to 4, to 8, and to 16. (a) double-scroll chaotic attractors under C2 = 15 nF; (b) coexisting single-scroll chaotic attractors under C2 = 20 nF; (c) coexisting period-2 limit cycles under C2 = 34 nF; (d) coexisting period 1 limit cycles under C 45 nF The blue and red attractors are initiated from ( 1 nV 0 V 0 V 0 V) and (1 nV 0 V 0 V FIGURE 7. Topological evolutions of different types of attractors with m increasing from 1, to 4, to 8, and to 16. (a) double-scroll chaotic attractors under C2 = 15 nF; (b) coexisting single-scroll chaotic attractors under C2 = 20 nF; (c) coexisting period-2 limit cycles under C2 = 34 nF; (d) coexisting period-1 limit cycles under C2 = 45 nF. The blue and red attractors are initiated from (−1 nV, 0 V, 0 V, 0 V) and (1 nV, 0 V, 0 V, 0 V), respectively. FIGURE 8. Equilibrium points fixed by the function curve intersections and phase portraits (C2 = 34 nF) of system (13) with m increasing from 1, to 4, to 8, and to 16 in the v2-v0 plane. The blue and red attractors are initiated from (−1 nV, 0 V, 0 V, 0 V) and (1 nV, 0 V, 0 V, 0 V), respectively. FIGURE 8. Equilibrium points fixed by the function curve intersections and phase portraits (C2 = 34 nF) of system (13) with m increasing from 1, to 4, to 8, and to 16 in the v2-v0 plane. The blue and red attractors are initiated from (−1 nV, 0 V, 0 V, 0 V) and (1 nV, 0 V, 0 V, 0 V), respectively. synchronous lines indicate that the two pairs of observed electrical signals are in complete synchronization. VOLUME 8, 2020 B. CONFIRMATION OF VOLTAGE CONSTRAIN The voltage constraints in (3) are the key fundamental for constructing mathematical model (12). Take the parallel-type AMDB emulator with m = 4, R0 = 1.3 k and C0 = 100 nF as an example. Multisim simulations and hardware experiments are used to verify the correctness of the voltage constrains in (3). Firstly, Multisim simulation circuit of the parallel-type AMDB emulator is built, consisting of ten 1N4148 diodes, one capacitor and one resistor. The AC voltage source is used to provide the periodic stimulus, and its peak voltage and frequency are set as 3 V and 20 kHz, respectively. Ocil- loscope XSC1 set as X-Y mode is utilized to capture the electrical signals. The screenshots of the simulation circuit and oscilloscope interactive interface are shown in Fig. 2. The observation objects in Fig. 2(a) are the terminal voltages of branches B1 and B3, whereas those in Fig. 2(b) are the terminal voltages of branches B2 and B4. The simulated FIGURE 6. Parallel-type AMDB emulator-based Chua’s circuit. In fact, once the symmetry of the diode-bridge is broken by connecting some diodes in parallel to one or two bridge arms, an asymmetric memristive diode-bridge emulator is established. Here, we just present a typical case that an equal number of diodes are connected in parallel to the first and third bridge arms. Thus, the yielded mathematical model can be relatively simple. 156302 VOLUME 8, 2020 VOLUME 8, 2020 Y. Ye et al.: Parallel-Type AMDB Emulator and Its Induced Asymmetric Attractor FIGURE 7. Topological evolutions of different types of attractors with m increasing from 1, to 4, to 8, and to 16. (a) double-scroll chaotic attractors under C2 = 15 nF; (b) coexisting single-scroll chaotic attractors under C2 = 20 nF; (c) coexisting period-2 limit cycles under C2 = 34 nF; (d) coexisting period-1 limit cycles under C2 = 45 nF. The blue and red attractors are initiated from (−1 nV, 0 V, 0 V, 0 V) and (1 nV, 0 V, 0 V, 0 V), respectively. FIGURE 7. Topological evolutions of different types of attractors with m increasing from 1, to 4, to 8, and to 16. (a) double-scroll chaotic attractors under C2 = 15 nF; (b) coexisting single-scroll chaotic attractors under C2 = 20 nF; (c) coexisting period-2 limit cycles under C2 = 34 nF; (d) coexisting period-1 limit cycles under C2 = 45 nF. B. CONFIRMATION OF VOLTAGE CONSTRAIN are needed to detect the branch voltages, which can reduce the influence of voltage probes on the hardware circuit. Each subtraction circuit is composed of four 2 M resistors and one AD711JN operational amplifier. The experimen- tal results of the synchronous lines are shown in Fig. 3, which are consistent with the Multisim simulation plots in Fig. 2. Secondly, the physical hardware circuit is also welded and tested. Tektronix AFG3022 function generator is employed to provide the AC voltage source and Tektronix TDS 3034C is used to capture the experimental plots. Different from the Multisim simulation, two additional subtraction circuits 156303 VOLUME 8, 2020 Y. Ye et al.: Parallel-Type AMDB Emulator and Its Induced Asymmetric Attractor TABLE 1. Realization of the non-standard capacitor. FIGURE 9. Hardware breadboard of the asymmetric memristor-based Chua’s circuit and the experimentally captured asymmetric double-scroll chaotic attractor. TABLE 1. Realization of the non-standard capacitor. TABLE 1. Realization of the non-standard capacitor. After the Multisim simulations and the hardware experi- ments, one can draw a conclusion that the voltage constrains in (3) are correct. Thus, the derived mathematical model in (12) is credible. Besides, from Figs. 2(a) and 3(a), one can notice that the forward voltages of the diode-bridge arms B1 and B3 are about 0.7 V. Addtionally, these voltages remain unchanged when m changes. As a result, the DPA in the parallel-type AMDB emulator can be constructed by much more diodes, without the limitation of forward voltage. How- ever, for the series-type AMDB emulator reported in [32], when increasing the numerber of diodes, the forward voltage increases by multiplier. From this aspect, the parallel-type AMDB emulator is much better than the series-type AMDB emulator. FIGURE 9. Hardware breadboard of the asymmetric memristor-based Chua’s circuit and the experimentally captured asymmetric double-scroll chaotic attractor. A. MEMRISTIVE CIRCUIT AND ITS ATTRACTORS To demonstrate the dynamical effect of asymmetric non- linearity, an asymmetric memristor-based Chua’s circuit is constructed using a parallel-type AMDB emulator to couple a passive LC network and an active RC filter, as shown in Fig. 6. The voltages v1, v2 across the capacitors C1 and C2, and the current iL flowing through the inductor L are chosen as the state variables. Together with the inner state variable v0 of the parallel-type AMDB emulator GM, there are four state variables, namely, v1, v2, iL and v0. Also, the hardware experiments for the pinched hysteresis loops are completed according to Fig. 1. The corresponding results are plotted in Fig. 5. Tektronix TCP213A current probe is used to detect the port currents of the parallel-type AMDB emulator. For better visual effect, the test wire is wound around the current probe ten turns, i.e., the output signal in Ch4 (40 mA/div) is enlarged by 10 times of the test current i (4 mA/div). The experimental results in Fig. 5 match well with the numerical results in Fig. 4. Based on the mathematical model of the parallel-type AMDB emulator, when applying Kirchhoff’s law to the asymmetric memristor-based Chua’s circuit in Fig. 6, the cir- cuit state equations can be described as C. ASYMMETRIC HYSTERESIS LOOP Pinched hysteresis loop is the fingerprint of a memristor under periodic stimulus [33]. When the parallel-type AMDB emulator is excited by an AC voltage source V = 3 sin(2πft), its volt-ampere curves in different parameters are plotted in Fig. 4. The RC filter with R0 = 1.3 k, C0 = 100 nF is selected, and the 1N4148 diode with IS = 5.84 nA, n = 1.94, VT = 26 mV is used. In Fig. 4(a), the parameter m is fixed as 4, and the frequency f is set to 2 kHz, 10 kHz, and 20 kHz, respectively. It can be seen that each volt-ampere curve is pinched at the origin, implying the current will vanish when the applied AC voltage vanishes. When increasing the frequency, the lobe area of the volt-ampere curve decreases, but the difference between the peak current and valley current increases. In short, with the increase of f , the asymmetry of hysteresis loop becomes remarkable. In Fig. 4(b), f is fixed as 20 kHz, and m is set to 1, 4, 8 and 16, respectively. With the increase of m, the left lobe area becomes smaller and smaller, whereas the right lobe area gets bigger and bigger. That is to say the differences between the peak currents and valley currents are gradually enhanced when increasing the parameter m. As can be seen, with the frequency evolution, the parallel-type AMDB emulator can exhibit the asymmetric hysteresis loops pinched at the origin (G(v0, 0) ̸= ∞). This implies that the parallel-type AMDB emulator belongs to the extended memristor but without non- volatile property [33]. FIGURE 9. Hardware breadboard of the asymmetric memristor-based Chua’s circuit and the experimentally captured asymmetric double-scroll chaotic attractor. Chua’s circuit can generate symmetric double-scroll attrac- tors, symmetric coexisting single-scroll attractors, or sym- metric multi-scroll attractors [34]–[38]. In this part, the parallel-type AMDB emulator-based Chua’s circuit is taken as an example to explore the dynamical effect of asymmetric nonlinearity. III. PARALLEL-TYPE AMDB EMULATOR-BASED CHUA’S CIRCUIT C1 dv1 dt = IS[meξ(v−v0) −e−ξ(v+v0) −m + 1] −iL, C2 dv2 dt = v2 R −IS[meξ(v−v0) −e−ξ(v+v0) −m + 1], Chua’s diode is a nonlinear resistor. It is the key element for achieving chaotic oscillations in Chua’s circuit. Generally, 156304 156304 156304 VOLUME 8, 2020 VOLUME 8, 2020 VOLUME 8, 2020 Y. Ye et al.: Parallel-Type AMDB Emulator and Its Induced Asymmetric Attractor FIGURE 10. Experimental results of the phase plots with different C2 (a) double-scroll chaotic attractors, C2 = 15.5 nF, (b) coexisting single-scroll chaotic attractors, C2 = 20.2 nF; (c) coexisting period-2 limit cycles, C2 = 29.5 nF; (d) coexisting period-1 limit cycles, C2 = 42.7 nF. FIGURE 10. Experimental results of the phase plots with different C2 (a) double-scroll chaotic attractors, C2 = 15.5 nF, (b) coexisting single-scroll chaotic attractors, C2 = 20.2 nF; (c) coexisting period-2 limit cycles, C2 = 29.5 nF; (d) coexisting period-1 limit cycles, C2 = 42.7 nF. FIGURE 10. Experimental results of the phase plots with different C2 (a) double-scroll chaotic attractors, C2 = 15.5 nF, (b) coexisting single-scroll chaotic attractors, C2 = 20.2 nF; (c) coexisting period-2 limit cycles, C2 = 29.5 nF; (d) coexisting period-1 limit cycles, C2 = 42.7 nF. C0 dv0 dt = IS[meξ(v−v0) + e−ξ(v+v0) −m −1] −v0 R0 , L diL dt = v1, (13) tors, as shown in Fig. 7(a). Similarly, by adjusting C2 to 20 nF, to 34 nF, to 45 nF, system (13) can generate three different types of attractors, including coexisting single-scroll chaotic attractors, coexisting period-2 and period-1 limit cycles, as plotted in Figs. 7(b)-(d). In Fig. 7, the blue and red attractors are initiated from (−1 nV, 0 V, 0 V, 0 V) and (1 nV, 0 V, 0 V, 0 V), respectively. Note that the nonzero initial value is used to provide a weak perturbation for the autonomous system (13). (13) where v = v2 −v1. Seen from (13), all the nonlinear terms are related to the parallel-type AMDB emulator. It means that the parallel-type AMDB emulator has a great influence on the attractor topologies of system (13). III. PARALLEL-TYPE AMDB EMULATOR-BASED CHUA’S CIRCUIT This influence can be revealed by MATLAB numerical simulations based on (13), in which the circuit parameters are fixed as C1 = 10 nF, L = 20 mH, R = 2 k, R0 = 1.3 k, and C0 = 100 nF, and the other two parameters, C2 and m, are taken as the controllable parameters. where v = v2 −v1. Seen from (13), all the nonlinear terms are related to the parallel-type AMDB emulator. It means that the parallel-type AMDB emulator has a great influence on the attractor topologies of system (13). This influence can be revealed by MATLAB numerical simulations based on (13), in which the circuit parameters are fixed as C1 = 10 nF, L = 20 mH, R = 2 k, R0 = 1.3 k, and C0 = 100 nF, and the other two parameters, C2 and m, are taken as the controllable parameters. Obviously, from the phase plots in the first column (m = 1) in Fig. 7, it can be seen that the left- and right-scroll attractors are symmetric about the origin. By contrast, from the second column (m = 4), third column (m = 8), and fourth column (m = 16), it can be found that the right-scroll attrac- tors become smaller and smaller. Therefore, the difference For fixed C2 = 15 nF, set m to 1, 4, 8 and 16, respec- tively. System (13) generates double-scroll chaotic attrac- 156305 156305 VOLUME 8, 2020 Y. Ye et al.: Parallel-Type AMDB Emulator and Its Induced Asymmetric Attractor between the right- and left-scroll attractors is becoming more and more apparent. One can also find that this evolution is consistent with that of the asymmetric hysteresis loops exhibited by the parallel-type AMDB emulator. between the right- and left-scroll attractors is becoming more and more apparent. One can also find that this evolution is consistent with that of the asymmetric hysteresis loops exhibited by the parallel-type AMDB emulator. the pinched property of physical memristor device. In addi- tion, the parallel-type AMDB emulator-based Chua’s circuit was taken as an example. Due to the existence of asymmetric nonlinearity, the equilibrium points of memristive Chua’s circuit are asymmetrically distributed in the phase space, resulting in the appearance of different types of asymmetric attractors. Of course, the dynamical mechanism is more com- plex and interesting, which will be studied in our next work. REFERENCES [1] L. Chua, ‘‘Memristor—The missing circuit element,’’ IEEE Trans. Circuit Theory, vol. CT-18, no. 5, pp. 507–519, Sep. 1971. [2] D. B. Strukov, G. S. Snider, D. R. Stewart, and R. S. Williams, ‘‘The missing memristor found?’’ Nature, vol. 453, pp. 80–83, May 2008. By using the graphical method, the equilibrium points fixed by the function curve intersections and phase portraits with different m in the v2-v0 plane are depicted in Fig.8. MATLAB function ‘ezplot’ is employed to plot the curves of f1 and f2. As can be clearly seen, system (13) has one zero equilibrium point E0 and two non-zero equilibrium points E1 and E2. The coexisting period-2 limit cycles are gener- ated around E1 or E2. With m increasing, E0 and E1 keep unchanged, while E2 gradually glides along the f2 in the first quadrant. As a result, the asymmetric limit cycle pairs are thereby coexisted. [3] Y. Babacan and F. Kaçar, ‘‘Floating memristor emulator with subthreshold region,’’ Anal. Integr. Circuits Signal Process., vol. 90, no. 2, pp. 471–475, Feb. 2017. [4] I. Vourkas, D. Stathis, G. C. Sirakoulis, and S. Hamdioui, ‘‘Alternative architectures toward reliable memristive crossbar memories,’’ IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol. 24, no. 1, pp. 206–217, Jan. 2016. [5] S. Xiao, X. Xie, S. Wen, Z. Zeng, T. Huang, and J. Jiang, ‘‘GST-memristor- based online learning neural networks,’’ Neurocomputing, vol. 272, pp. 677–682, Jan. 2018. [6] T. Chen, L. Wang, and S. Duan, ‘‘Implementation of circuit for reconfig- urable memristive chaotic neural network and its application in associative memory,’’ Neurocomputing, vol. 380, pp. 36–42, Mar. 2020. [7] H. Bao, A. Hu, W. Liu, and B. Bao, ‘‘Hidden bursting firings and bifurca- tion mechanisms in memristive neuron model with threshold electromag- netic induction,’’ IEEE Trans. Neural Netw. Learn. Syst., vol. 31, no. 2, pp. 502–511, Feb. 2020. CONFLICTS OF INTEREST The authors declare that they have no conflicts of interest. The authors declare that they have no conflicts of interest. As can be seen, the equilibrium point E has no connection with the capacitance C2. Take the asymmetric coexisting limit cycles at C2 = 34 nF as examples to explain the equilibrium point evolutions with m increasing. C. EXPERIMENTAL RESULTS [8] H. Wu, Y. Ye, M. Chen, Q. Xu, and B. Bao, ‘‘Extremely slow passages in low-pass filter-based memristive oscillator,’’ Nonlinear Dyn., vol. 97, no. 4, pp. 2339–2353, Jul. 2019. Based on one chip of AD711JN operational amplifier, one inductance coil and some other discrete components, the hardware breadboard of the asymmetric memristor-based Chua’s circuit is fabricated, as shown in Fig. 9. The induc- tance coil is measured as 18.3 mH with the parasitic resis- tance 2 . An AD711JN operational amplifier is employed to realize the negative resistor −R. And the non-standard capacitances of C2 are obtained byparalleling several tanta- lum capacitors, as listed in Tab. 1. Tektronix TDS 3034C with Tektronix TCP213A current probe is used to capture the experimental results of the phase plots. The results are displayed in Fig. 10, which are in good agreement with the numerical ones given in Fig. 7. It is noticed that the coexisting left- or right-attractor is emerged by switching the power on and off repeatedly. [9] H. G. Wu, Y. Ye, B. C. Bao, M. Chen, and Q. Xu, ‘‘Memristor initial boost- ing behaviors in a two-memristor-based hyperchaotic system,’’ Chaos, Solitons Fractals, vol. 121, pp. 178–185, Apr. 2019. [10] Q. Xu, Q. Zhang, B. Bao, and Y. Hu, ‘‘Non-autonomous second-order memristive chaotic circuit,’’ IEEE Access, vol. 5, pp. 21039–21045, Jul. 2017. [11] Z. Li, C. Zhou, and M. Wang, ‘‘Symmetrical coexisting attractors and extreme multistability induced by memristor operating configurations in SC-CNN,’’ AEU—Int. J. Electron. Commun., vol. 100, pp. 127–137, Feb. 2019. [12] Z. Wen, Z. Li, and X. Li, ‘‘Bursting dynamics in parametrically driven memristive jerk system,’’ Chin. J. Phys., vol. 66, pp. 327–334, Aug. 2020, doi: 10.1016/j.cjph.2020.04.009. j jp [13] H. Lin, C. Wang, Q. Hong, and Y. Sun, ‘‘A multi-stable memristor and its application in a neural network,’’ IEEE Trans. Circuits Syst. II, Exp. Briefs, early access, Jun. 8, 2020, doi: 10.1109/TCSII.2020.3000492. [14] Y. Dong, G. Wang, G. Chen, Y. Shen, and J. Ying, ‘‘A bistable nonvolatile locally-active memristor and its complex dynamics,’’ Commun. Nonlinear Sci. Numer. Simul., vol. 84, May 2020, Art. no. 105203. IV. CONCLUSION DATA AVAILABILITY The data used to support the findings of this study are avail- able from the corresponding author upon request. f1 = −meξ(˜v2−˜v0) + e−ξ(˜v2+˜v0) + m −1 + ˜v2 RIS = 0, f2 = meξ(˜v2−˜v0) + e−ξ(˜v2+˜v0) −m −1 − ˜v0 R0IS = 0. (14) B. EQUILBRIUM POINT ANSLYSIS For the parallel-type AMDB emulator-based Chua’s system, the equilibrium point is expressed as E = (0, ˜v2, ˜v0,˜iL), in which ˜iL = IS[meξ(˜v2−˜v0) −e−ξ(˜v2+˜v0) −m+1], and ˜v2 and ˜v0 can be obtained by solving the following equations DATA AVAILABILITY IV. CONCLUSION degree in electronic science and technology from the Xuzhou Institute of Tech- nology, Xuzhou, China, in 2019. He is currently pursuing the M.S. degree in electronic circuits and systems with Changzhou University. His research interests include analysis and implementation of memristor equivalent circuits, and memristive and chaotic systems. JIE ZHOU (Graduate Student Member, IEEE) received the B.S. degree in electronic science and technology from the Xuzhou Institute of Tech- nology, Xuzhou, China, in 2019. He is currently pursuing the M.S. degree in electronic circuits and systems with Changzhou University. His research interests include analysis and implementation of memristor equivalent circuits, and memristive and chaotic systems. [23] J. Kengne, R. L. T. Mogue, T. F. Fozin, and A. N. K. Telem, ‘‘Effects of symmetric and asymmetric nonlinearity on the dynamics of a novel chaotic jerk circuit: Coexisting multiple attractors, period doubling reversals, cri- sis, and offset boosting,’’ Chaos, Solitons Fractals, vol. 121, pp. 63–84, Apr. 2019. [24] J. Gu, C. Li, Y. Chen, H. H. C. Iu, and T. Lei, ‘‘A conditional symmetric memristive system with infinitely many chaotic attractors,’’ IEEE Access, vol. 8, pp. 12394–12401, 2020. [25] S. R. Bishop, A. Sofroniou, and P. Shi, ‘‘Symmetry-breaking in the response of the parameterically excited pendulum model,’’ Chaos, Solit. Fractals, vol. 25, no. 2, pp. 264–277, Jul. 2005. [26] H. Cao, J. M. Seoane, and M. A. F. Sanjuán, ‘‘Symmetry-breaking analysis for the general Helmholtz–Duffing oscillator,’’ Chaos, Solitons Fractals, vol. 34, no. 2, pp. 197–212, Oct. 2007. QUAN XU (Member, IEEE) was born in Lianyun- gang, China, in 1983. He received the B.S. degree in physics from the Huaiyin Teachers College in 2005, and the M.S. and Ph.D. degrees in opti- cal engineering from the University of Electronics Science and Technology of China in 2011. Since 2011, he has been a Lecturer with Changzhou University, China, where he is cur- rently an Associate Professor. He has authored more than 30 articles and holds more than ten inventions. His research interests include memristor and its applications, and memristive neuromorphic circuits. QUAN XU (Member, IEEE) was born in Lianyun- gang, China, in 1983. He received the B.S. degree in physics from the Huaiyin Teachers College in 2005, and the M.S. and Ph.D. degrees in opti- cal engineering from the University of Electronics Science and Technology of China in 2011. [27] M. Heinrich, T. Dahms, V. Flunkert, S. W. Teitsworth, and E. IV. CONCLUSION Schöll, ‘‘Symmetry-breaking transitions in networks of nonlinear circuit ele- ments,’’ New J. Phys., vol. 12, no. 11, Nov. 2010, Art. no. 113030. [28] L. Kamdjeu Kengne, H. T. Kamdem Tagne, A. N. Kengnou Telem, J. R. Mboupda Pone, and J. Kengne, ‘‘A broken symmetry approach for the modeling and analysis of antiparallel diodes-based chaotic circuits: A case study,’’ Anal. Integr. Circuits Signal Process., vol. 104, no. 2, pp. 205–227, May 2020. [29] L. Kamdjeu Kengne, J. Kengne, N. A. Kengnou Telem, J. R. Mboupda Pone, and H. T. Kamdem Tagne, ‘‘Asymmetry-induced dynamics for a class of diode-based chaotic circuits: A case study,’’ J. Circuits, Syst. Comput., Jul. 2020, doi: 10.1142/s0218126621500778. [30] L. K. Kengne, H. T. K. Tagne, J. R. M. Pone, and J. Kengne, ‘‘Dynamics, control and symmetry-breaking aspects of a new chaotic jerk system and its circuit implementation,’’ Eur. Phys. J. Plus, vol. 135, no. 3, pp. 1–28, Mar. 2020. MO CHEN (Member, IEEE) received the B.S. degree in information engineering, and the M.S. and Ph.D. degrees in electromagnetic field and microwave technology from Southeast University, Nanjing, China, in 2003, 2006, and 2009, respec- tively. From March 2009 to July 2013, she was a Lecturer with Southeast University. She is cur- rently an Associate Professor with the School of Information Science and Engineering, Changzhou University, Changzhou, China. Her research inter- ests include memristor and its application circuits, and other nonlinear circuits and systems. MO CHEN (Member, IEEE) received the B.S. degree in information engineering, and the M.S. and Ph.D. degrees in electromagnetic field and microwave technology from Southeast University, Nanjing, China, in 2003, 2006, and 2009, respec- tively. From March 2009 to July 2013, she was a Lecturer with Southeast University. She is cur- rently an Associate Professor with the School of Information Science and Engineering, Changzhou University, Changzhou, China. Her research inter- ests include memristor and its application circuits, and other nonlinear circuits and systems. [31] L. K. Kengne, J. R. M. Pone, H. T. K. Tagne, and J. Kengne, ‘‘Dynam- ics, control and symmetry breaking aspects of a single opamp-based autonomous LC oscillator,’’ AEU-Int. J. Electron. Commun., vol. 118, p. 53146, May 2020. [32] M. Hua, S. Yang, Q. Xu, M. Chen, H. Wu, and B. Bao, ‘‘Forward and reverse asymmetric memristor-based jerk circuits,’’ AEU—Int. J. Electron. Commun., vol. 123, Aug. 2020, Art. no. 153294. g [33] L. O. IV. CONCLUSION [15] H. Wu, Y. Ye, M. Chen, Q. Xu, and B. Bao, ‘‘Periodically switched mem- ristor initial boosting behaviors in memristive hypogenetic jerk system,’’ IEEE Access, vol. 7, pp. 145022–145029, Oct. 2019. This paper reported a novel parallel-type AMDB emulator implemented by an asymmetric diode-bridge cascaded with a RC filter. The mathematical modeling, Multisim circuit anal- yses, MATLAB numerical simulations, and breadboard hard- ware experiments were executed. The parallel-type AMDB emulator, inexpensive and easy to be physically fabricated with the on-the-shelf components, was confirmed to behave [16] M. Nigus Getachew, R. Priyadarshini, and R. M. Mehra, ‘‘SPICE model of HP-memristor using PWL window function for neuromor- phic system design application,’’ Mater. Today, Proc., Feb. 2020, doi: 10.1016/j.matpr.2020.01.540. [17] A. G. Alharbi, M. E. Fouda, Z. J. Khalifa, and M. H. Chowdhury, ‘‘Elec- trical nonlinearity emulation technique for current-controlled memristive devices,’’ IEEE Access, vol. 5, pp. 5399–5409, 2017. 156306 VOLUME 8, 2020 Y. Ye et al.: Parallel-Type AMDB Emulator and Its Induced Asymmetric Attractor [18] V. K. Sharma, M. S. Ansari, and T. Parveen, ‘‘Tunable memristor emu- lator using Off-The-Shelf components,’’ Procedia Comput. Sci., vol. 171, pp. 1064–1073, 2020. YI YE (Graduate Student Member, IEEE) received the B.S. degree in electronic information engineer- ing from the Changzhou Institute of Technology, Changzhou, China, in 2017. He is currently pur- suing the M.S. degree in electronic circuits and systems with Changzhou University. His research interests include analysis and implementation of memristor equivalent circuits, and memristive and chaotic systems. [19] A. Yesil, ‘‘A new grounded memristor emulator based on MOSFET-C,’’ AEU - Int. J. Electron. Commun., vol. 91, pp. 143–149, Jul. 2018. [20] Q. Xu, Q. L. Zhang, H. Qian, H. G. Wu, and B. C. Bao, ‘‘Crisis-induced coexisting multiple attractors in a second-order nonautonomous memris- tive diode bridge-based circuit,’’ Int. J. Circuit Theory Appl., vol. 46, no. 10, pp. 1917–1927, May 2018. [21] B. Bao, J. Yu, F. Hu, and Z. Liu, ‘‘Generalized memristor consisting of diode bridge with first order parallel RC filter,’’ Int. J. Bifurcation Chaos, vol. 24, no. 11, Nov. 2014, Art. no. 1450143. [22] L. Minati, L. V. Gambuzza, W. J. Thio, J. C. Sprott, and M. Frasca, ‘‘A chaotic circuit based on a physical memristor,’’ Chaos, Solitons Frac- tals, vol. 138, Sep. 2020, Art. no. 109990. JIE ZHOU (Graduate Student Member, IEEE) received the B.S. IV. CONCLUSION Chua, ‘‘If it’s pinched it’s a memristor,’’ Semicond. Sci. Technol., vol. 29, no. 10, p. 104001, 2014. p [34] R. Barboza and L. O. Chua, ‘‘The four-element Chua’S circuit,’’ Int. J. Bifurcation Chaos, vol. 18, no. 4, pp. 943–955, Apr. 2008. [35] K. Rajagopal, S. Kacar, Z. Wei, P. Duraisamy, T. Kifle, and A. Karthikeyan, ‘‘Dynamical investigation and chaotic associated behaviors of memristor Chua’s circuit with a non-ideal voltage-controlled memristor and its appli- cation to voice encryption,’’ AEU—Int. J. Electron. Commun., vol. 107, pp. 183–191, Jul. 2019. HUAGAN WU (Member, IEEE) received the B.S. degree in electrical information engineering and automation from the Jiangsu University of Tech- nology, Changzhou, China, in 2010, and the M.S. and Ph.D. degrees in information and commu- nication engineering from the Nanjing Univer- sity of Science and Technology, Nanjing, China, in 2015. HUAGAN WU (Member, IEEE) received the B.S. degree in electrical information engineering and automation from the Jiangsu University of Tech- nology, Changzhou, China, in 2010, and the M.S. and Ph.D. degrees in information and commu- nication engineering from the Nanjing Univer- sity of Science and Technology, Nanjing, China, in 2015. [36] M. Chen, M. Sun, H. Bao, Y. Hu, and B. Bao, ‘‘Flux–Charge analysis of Two-Memristor-Based Chua’s circuit: Dimensionality decreasing model for detecting extreme multistability,’’ IEEE Trans. Ind. Electron., vol. 67, no. 3, pp. 2197–2206, Mar. 2020. [37] N. Wang, C. Li, H. Bao, M. Chen, and B. Bao, ‘‘Generating multi- scroll Chua’s attractors via simplified piecewise-linear Chua’s diode,’’ IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 66, no. 12, pp. 4767–4779, Dec. 2019. She is currently a Lecturer with the School of Information Science and Engineering, Changzhou University, Changzhou. Her research interests include memristor and its application circuits, and other nonlinear circuits and systems. [38] Q. Xu, Y. Lin, B. Bao, and M. Chen, ‘‘Multiple attractors in a non-ideal active voltage-controlled memristor based Chua’s circuit,’’ Chaos, Solitons Fractals, vol. 83, pp. 186–200, Feb. 2016. 156307 156307 VOLUME 8, 2020
https://openalex.org/W2735333277
http://arbor.revistas.csic.es/index.php/arbor/article/download/2184/2965
es
¿Qué es cultura en la «economía de la cultura»? Definiendo la cultura para crear modelos mensurables en economía cultural
Arbor
2,017
cc-by
7,440
ARBOR Ciencia, Pensamiento y Cultura Vol. 193-783, enero-marzo 2017, a376 | ISSN-L: 0210-1963 doi: http://dx.doi.org/10.3989/arbor.2017.783n1007 VARIA / VARIA ¿QUÉ ES CULTURA EN LA «ECONOMÍA DE LA CULTURA»? DEFINIENDO LA CULTURA PARA CREAR MODELOS MENSURABLES EN ECONOMÍA CULTURAL WHAT IS CULTURE IN «CULTURAL ECONOMY»? DEFINING CULTURE TO CREATE MEASURABLE MODELS IN CULTURAL ECONOMY Aníbal Monasterio Astobiza Universidad del País Vasco anibal.monasterio@ehu.eus http://orcid.org/0000-0003-1399-5388 Cómo citar este artículo/Citation: Monasterio Astobiza, A. (2017). ¿Qué es cultura en la «economía de la cultura»? Definiendo la cultura para crear modelos mensurables en economía cultural. Arbor, 193 (783): a376. doi: http://dx.doi. org/10.3989/arbor.2017.783n1007 Copyright: © 2017 CSIC. Este es un artículo de acceso abierto distribuido bajo los términos de la licencia Creative Commons Attribution (CC BY) España 3.0. Recibido: 16 junio 2015. Aceptado: 17 diciembre 2015. RESUMEN: El concepto de cultura es bastante vago y ambiguo para los objetivos formales de la economía. En este escrito se pretende definir y acotar mejor el espacio semántico de la idea de cultura para ayudar a crear explicaciones económicas basadas en la cultura dirigidas a medir el retorno e impacto económico y social de toda actividad o creencia asociada a la cultura. Por cultura, de acuerdo con la definición evolutiva canónica, se entiende cualquier tipo de comportamiento ritualizado o convertido en significativo para un grupo de individuos que permanece, más o menos, constante y es trasmitido intergeneracionalmente a través del tiempo. Toda institución económica se basa, implícita o explícitamente, en una visión de cómo funcionamos los seres humanos, la cultura es imprescindible para entendernos, por ello, es necesario describir correctamente qué es lo que se entiende por cultura. En este escrito hacemos una revisión de la literatura en antropología y psicología evolucionista en torno al concepto de cultura para advertir que una modelización económica de la cultura ignora aspectos intangibles de los beneficios de la cultura y que por tanto la economía se muestra incapaz de medir algunos ítems culturales en la sociedad de consumo digital. ABSTRACT: The idea of culture is somewhat vague and ambiguous for the formal goals of economics. The aim of this paper is to define the notion of culture better so as to help build economic explanations based on culture and therefore to measure its impact in every activity or beliefs associated with culture. To define culture according to the canonical evolutionary definition, it is any kind of ritualised behaviour that becomes meaningful for a group and that remains more or less constant and is transmitted down through the generations. Economic institutions are founded, implicitly or explicitly, on a worldview of how humans function; culture is an essential part of understanding us as humans, making it necessary to describe what we understand by culture correctly. In this paper we review the literature on evolutionary anthropology and psychology dealing with the concept of culture to warn that economic modelling ignores intangible benefits of culture rendering economics unable to measure certain cultural items in the digital consumer society. PALABRAS CLAVE: Cultura; evolución de la cultura; economía de la cultura; cooperación; status; psicología. KEYWORDS: Culture; evolution of culture; cultural economics; cooperation; status; psychology. a376 ¿Qué es cultura en la «economía de la cultura»? Definiendo la cultura para crear modelos mensurables en economía cultural 1. INTRODUCCIÓN: BREVÍSIMA HISTORIA DE LA ECONOMÍA CULTURAL del capitalismo emergerá como consecuencia de las creencias (cultura). La economía cultural o economía de la cultura es una rama de la economía que investiga explicaciones o hipótesis culturales como determinantes de retorno o impacto económico. Con el uso de técnicas analíticas y herramientas empíricas traídas de la matemática se identifican diferencias sistemáticas de la influencia que ejerce la cultura en el desarrollo económico de las regiones, territorios y países. En este sentido, la economía cultural o economía de la cultura (Baumol y Bowen 1965; Baumol y Bowen 1966) es una detallada y específica investigación de las condiciones económicas de la cultura o las artes (literatura, música, cine...). John M. Keynes y sus obras canónicas, entre ellas The General Theory of Employment, Interest and Money, representa una renuncia a la ortodoxia del mercado de la economía clásica y la teoría racional de la utilidad. A pesar de la riqueza del archivo de Keynes los historiadores y economistas solo se han centrado en su opus magnum (La Teoría General). Pero la antología entera de sus escritos con artículos, emisiones radiofónicas y correspondencia epistolar publicada en 1981 por la Royal Economic Society muestra su interés por las artes como una buena analogía del mercado que más allá de comportarse racionalmente es intrínsecamente irracional. La irracionalidad es una característica definitoria de la sociedad civil, y por ende de los mercados. Los “espíritus animales” o, dicho de otro modo, la psicología instintiva de los actores económicos es el verdadero modus operandi de la economía. La psicología instintiva se manifiesta en la creatividad y la creatividad es propia de las artes. En su ensayo Arte y Estado Keynes crítica al gobierno británico por errar en “mantener la grandeza y dignidad del Estado”. Para Keynes son las artes las que hacen de un estado lo que es porque las artes crean un “orgullo cívico y un sentido de unidad social” (Moggridge, 2005, p. 345). Keynes critica que el estado no interfiera en los asuntos sociales. La economía cultural es un desarrollo reciente del discurso económico. Hasta hace bien poco los economistas no tenían por objeto de estudio la cultura porque la consideraban demasiado ambigua, abstracta y muy difícil de medir cuantitativamente. Sin embargo, distintos autores de diferentes épocas empiezan a vislumbrar el poder de las fuerzas culturales (creencias, valores, preferencias...) en el desarrollo económico de las sociedades. Algunos de estos autores son Karl Marx, Max Weber, John M. Keynes o Thorstein Veblen, por citar unos pocos. Pero no todos estos autores pioneros en la consideración de la cultura como factor económico tienen clara la relación o dirección causal entre la economía y la cultura. Algunos de ellos consideran que la economía crea la cultura, mientras que otros creen que la cultura crea la economía. No obstante, en la economía mainstream la cultura será vista como efecto más que como causa de la economía y siempre con un papel más bien secundario. Para Karl Marx la cultura, el orden social, está determinado por los medios de producción de la técnica. Para él el molino de viento crea la sociedad feudal y la máquina de vapor el capitalismo. Max Weber revierte este orden causal en su Ética protestante y el espíritu del capitalismo y ve en la fuerza de la religión (creencias) la espuela que mueve el cambio de paradigma económico. El trabajo duro, la austeridad, pero también la acumulación de capital resultan fomentados por un vuelco en dos dogmas religiosos básicos: la amisibilidad (del latín amittere que significa que se puede “perder”) de la gracia y la predestinación de las almas. Si tu alma no tiene garantizado el perdón eterno y tú no tienes por qué ser elegido de antemano para ir al reino de los cielos, entonces tus acciones en vida son las que serán juzgadas. Si a esto sumamos que la acumulación de capital ya no será condenada moralmente como usura, el origen 2 ARBOR Vol. 193-783, enero-marzo 2017, a376 ISSN-L: 0210-1963 Por su parte, Thorstein Veblen introduce en su obra The Theory of Leisure Class la noción de consumo u ocio conspicuo. Para Veblen el comportamiento de la gente se ve modificado por la riqueza. La gente que posee riqueza o está a la búsqueda de ella solo busca el estatus o eminencia que el dinero otorga. Esto causa una lucha por el dinero que una vez que se tiene crea una necesidad de apariencia social: ostentar. Esta apariencia social mueve a las personas a emular o sobrepasar la riqueza de otros. Y esto se hace a través del consumo u ocio conspicuo. El consumo conspicuo no es un consumo de subsistencia. Si así fuera habría un punto en el que el incentivo de acumular bienes cesaría, pero este no es el caso. Consumir conspicuamente es valioso en sí mismo. Lo que se está señalando cuando se consume conspicuamente es que se tiene la riqueza para consumir bienes ostentosos (en muchos casos superfluos y fruto del esnobismo) y que se forma parte de una clase ociosa que no necesita trabajar para consumir dichos bienes y, a su vez, se señala que el propio estatus social es alto. Los productos de la cultura, las artes, son para la clase ociosa el principal medio o forma de consumo conspicuo. doi: http://dx.doi.org/10.3989/arbor.2017.783n1007 En las siguientes páginas se definirá la noción de cultura desde la aplicación de la teoría darwiniana aplicada a la cultura para establecer apropiadamente qué es la cultura y, finalmente, se reconocerá que una modelización estrictamente económica puede ignorar ciertos beneficios intangibles de la cultura. 2. ¿QUÉ ES LA CULTURA? La cultura es una noción difícil de medir y estudiar a través de los métodos formales que han venido utilizando los economistas. Por dos razones principales: 1) una mala interpretación del término cultura y 2) como consecuencia de una definición equívoca de la idea de cultura, un mal entendimiento de los mecanismos culturales para medir su retorno o impacto económico. Con respecto a la razón 1) la polisemia de la noción de cultura ha llevado a muchas confusiones. Uno puede referirse a la cultura de una empresa, a la cultura de una época histórica, a la cultura de una persona y hasta a la subcultura de un grupo de la sociedad. Todos estos usos de la noción de cultura guardan un aire de familia, pero al mismo tiempo tienen su propia idiosincrasia. En un artículo seminal Alfred Kroeber y Clyde Kluckohn (1952), antropólogos culturales, recogieron más de 162 usos del término y noción de cultura. De entre todos estos significados distintos agruparon o encontraron tres amplias temáticas o categorías en las que se podían subsumir los distintos usos. Una primera te- ARBOR Vol. 193-783, enero-marzo 2017, a376. ISSN-L: 0210-1963 mática aludía a los estados mentales o pensamientos que dotaban de sentido a la cultura. En esta primera temática se englobarían creencias, valores, preferencias que las personas tienen en relación a lo que las personas consideran qué es la cultura. Una segunda temática de significados caracteriza la cultura material de los objetos y artefactos: las instrucciones necesarias para su creación. En esta segunda categoría se incluyen pronunciamientos, copias, imitaciones o aprendizaje social sobre cómo hacer un objeto o cómo proceder a la hora de realizar una práctica. a376 Aníbal Monasterio Astobiza Mientras que Marx relega a la cultura a un segundo plano, Weber es el primero en reconocer cómo ciertos mecanismos de la cultura (creencias) influyen en la economía. Es de interés para este escrito examinar los extremos descritos por esta tétrada de autores: Keynes (cultura pública) y Veblen (cultura privada), Marx (economía crea cultura) y Weber (cultura crea economía) en tanto en cuanto fomentar uno u otro tipo de economía cultural tendrá una diferenciada influencia en la economía común y general. Una de las conclusiones más perennes de la economía de la cultura desde el clásico estudio de Baumol y Bowen (1965), es la gran cantidad de costos adicionales, “enfermedad de los costos”, que las artes en general producen, de ahí que el estado tenga que subsidiarlas. Esta visión de la economía cultural sería considerada más keynesiana-weberiana frente a un enfoque más privado y coleccionista, más propio de una concepción Veblen-Marxiana, donde es la riqueza la que crea cultura. La tercera y última temática describe la cultura exclusivamente humana mediada por la facultad del lenguaje. Mientras que las dos temáticas anteriores de cultura pueden vislumbrarse o estar presentes en otras especies animales, principalmente los primates no-humanos, en los cuales experimentos con chimpancés muestran cómo hay aprendizaje social, elaboración de herramientas rudimentarias, comportamientos ex novo o en los nidos nupciales de las aves de la familia Ptilonorhynchidae (pájaros jardineros como el Capulinero) se puede atribuir un gusto y una representación estética, así como otros procesos culturales (Odling-Smee, Laland y Feldman, 2003), este grupo definicional de la idea de cultura es propia del ser humano. Comprende la arquitectura, la música, la pintura y otras artes donde el lenguaje como sistema de representación y comunicación simbólico es una condición necesaria para la trasmisión de información y creación de cultura. A partir de estas tres amplias clases de temáticas que emergen de los múltiples significados de cultura, revisados por Kroeber y Kluckohn, se puede extraer una definición neutra y comprehensiva de la idea o noción de cultura. La cultura es: tradiciones de comportamientos. Desde la perspectiva evolutiva la cultura es cualquier tipo de comportamiento ritualizado o convertido en significativo para un grupo de individuos que permanece, más o menos, constante y es trasmitido intergeneracionalmente a través del tiempo. Para entender cómo ciertos comportamientos y no otros son beneficiosos para el grupo, qué mecanismos están detrás de la trasmisión de la cultura, cómo ha evolucionado etc., es útil establecer una analogía con la evolución biológica y aplicar el marco teórico darwiniano. Estableciendo esta analogía entre el mundo biológico y el mundo de las variaciones culturales se podrán conocer los mecanismos y causas subyacentes doi: http://dx.doi.org/10.3989/arbor.2017.783n1007 3 a376 ¿Qué es cultura en la «economía de la cultura»? Definiendo la cultura para crear modelos mensurables en economía cultural a la evolución cultural. Es la definición evolutiva de cultura, el por qué y el cómo de su origen, lo que nos interesará, independientemente de las dimensiones o niveles de análisis desde las que se puede estudiar la cultura (país, sociedad, organización o individuo). Desde un punto de vista evolucionista, la cultura es una adaptación a nivel grupal que permite estudiar la diversidad de comportamientos de la misma forma que se puede estudiar la diversidad biológica (Wilson, 2013; Laland, 2017). En biología una adaptación es todo rasgo o característica de un organismo que ha evolucionado por selección natural en virtud de que incrementa la aptitud darwiniana (número de genes que pasarán a la siguiente generación). Por esto el estudio de cualquier ser vivo dado ha de comenzar con la certeza de que se ha adaptado a su entorno, de otra forma no existiría. Las especies biológicas son adaptativas a nivel individual, es decir, son adaptativas porque causan a los individuos que las poseen su supervivencia y reproducción frente a otros individuos. Un ejemplo de adaptación a nivel individual es la potente musculatura del guepardo para correr más rápido que otros animales y así atrapar a las presas. Sin embargo, hay otras especies que tienen adaptaciones a nivel grupal. Hay especies de insectos eusociales (comportamiento social extremo) como las abejas, hormigas y termitas cuyos rasgos (adaptaciones) han evolucionado en virtud de que causan un incremento de la aptitud darwiniana de la colonia frente a otra colonia, no en virtud de un incremento de la aptitud darwiniana de un individuo frente a otro individuo. Como resultado estas colonias se convierten en unidades altamente cooperativas, en superorganismos (Wilson, 2013, p. 105). Esta misma forma de entender la evolución de las especies biológicas se aplica a la evolución de las culturas. Como en el caso de las adaptaciones biológicas estas se han de estudiar caso por caso y la lista es muy extensa, pero la adaptación de las culturas se debe tomar como algo dado porque de otra forma no existirían. Las culturas son comportamientos (tradiciones de comportamientos) que han evolucionado por el bien del grupo. Las culturas son adaptaciones de los grupos a su entorno circundante. Pero ¿qué mecanismos han dado lugar a nuestra capacidad para la cultura? Si se tuvieran que enumerar los dos mecanismos más importantes que dan lugar a la emergencia de la cultura, estos son: la cooperación y las normas. 4 ARBOR Vol. 193-783, enero-marzo 2017, a376 ISSN-L: 0210-1963 Con respecto a la razón 2) de una mala definición de cultura en el discurso económico tradicional se deriva un mal conocimiento de los mecanismos culturales (cooperación y normas) que dan lugar a los productos culturales y, por tanto, la imposibilidad de medir su impacto o retorno económico. ¿Cómo los mecanismos culturales se pueden modelizar económicamente? Si se entiende que los mecanismos principales que hay detrás de la emergencia y evolución de la cultura son la cooperación y las normas, la teoría de juegos es una rama de la matemática ideal para describir cómo estrategias antagónicas de n-personas alcanzan un equilibrio donde no tiene por qué haber un resultado de suma-cero (un jugador gana y el otro pierde), sino un “win-win” (todos ganan). Más abajo indicaremos cómo se producen estas situaciones, pero antes de nada hay que mencionar a quién debemos este progreso en la descripción de las estrategias racionales en situaciones de conflicto. Fue Garrett Hardin, un ecólogo, el que en 1968 publicó un clásico artículo titulado “The Tragedy of the commons” donde se muestra el conflicto y la tensión entre los intereses egoístas y personales, por una parte, y los intereses colectivos, por otra parte. La parábola de Hardin es como sigue. Un grupo de pastores comparten un gran pasto que puede alimentar un gran grupo de animales pero no a infinitos animales. Periódicamente cada pastor decide introducir un animal a su rebaño. ¿Qué ha de hacer un pastor racional? Añadiendo un animal el pastor consigue un buen beneficio cuando vende el animal en el mercado. Sin embargo, el costo de introducir un animal al pasto es compartido por todos los que usan el terreno de pasto. Por lo tanto, el pastor gana mucho y solo paga un poco por añadir un animal adicional a su rebaño. En consecuencia el pastor estará mejor servido si decide introducir un animal más indefinidamente hasta que el pasto esté disponible. Pero por supuesto cada pastor tiene el mismo tipo de incentivos. Si cada pastor actúa de acuerdo a su propio interés el pasto común se extinguirá y no quedará nada para nadie. El dilema del prisionero (Axelrod y Hamilton, 1981), otro tipo de juego dentro de la teoría de juegos, vuelve a mostrar la tensión entre los intereses personales y los intereses colectivos. Lo que tienen en común todos estos juegos es que tratan sobre el problema de la cooperación. La cultura con sus normas institucionalizadas o tácitas e implícitas es una solución para resolver el problema de la cooperación. A veces la cooperación es posible y otras es difícil o imposible. Imaginemos que Juan y Pedro están en un bote en doi: http://dx.doi.org/10.3989/arbor.2017.783n1007 De hecho, sigue siendo la confianza la mayor parte de las veces la que permite todo intercambio entre las personas. Célebre es el pasaje del Libro 1, capítulo 2 de La riqueza de las naciones de Adam Smith: Pero imaginemos que Juan y Pedro están en el mismo bote y este se está yendo a pique y solo queda un salvavidas que no pueden usar los dos. En el primer caso la cooperación es posible, y la mejor solución, y en el segundo caso es imposible. En este caso hipotético se puede tener en cuenta que hay instintos innatos que por deriva genética se han fijado en buena parte de la población. Una demostración es el juego del ultimátum repetido una y otra vez en distintas poblaciones de todo el mundo. Si la situación se diera dentro de un grupo amplio, donde hubiera emparejamientos de uno en uno, la opción de cooperar se daría en al menos el 40% dejando el mayor que sobreviviera el menor, dado que este último tiene más posibilidades de reproducción1. “No es de la benevolencia del carnicero, cervecero o panadero de donde obtendremos nuestra cena, sino de su preocupación por sus propios intereses”. La cooperación se vuelve interesante en los casos intermedios entre los extremos cuando los intereses no están opuestamente alineados. Procesos psicológicos como la confianza sirven para permitir la cooperación y buscar el equilibrio de intereses en situaciones específicas (King-Casas et al., 2005; Corgnet, Espín, Hernán González, Kujal y Rassenti, 2016). La cultura son tradiciones de comportamientos, hábitos más o menos estables que se trasmiten de generación en generación a través del tiempo y que benefician al grupo. La cooperación y las normas contribuyen a la emergencia y evolución de la cultura y la confianza como proceso psicológico facilita la cooperación. Esto es la cultura. Entonces, ¿qué es cultura en la economía de la cultura? Para entender lo que significa “cultura” en la expresión “economía de la cultura” tenemos que fijarnos en un proceso psicológico básico que permite la aparición de los dos mecanismos que hay detrás de la cultura que antes mencionábamos: la cooperación y las normas. Este proceso o estado psicológico básico es la confianza. La confianza es el lubricante necesario para cualquier tipo de intercambio social o económico. La confianza reduce cualquier tipo de costo adicional que solo un contrato legal puede prever y solucionar, pero el imperio de la ley que todos damos por sentado en una sociedad democrática y libre es una invención reciente que no ha existido la mayor parte del tiempo en nuestra historia evolutiva. La confianza es la respuesta natural que ha permitido el acuerdo informal. ARBOR Vol. 193-783, enero-marzo 2017, a376. ISSN-L: 0210-1963 Aquí en este pasaje célebre el motor del intercambio es la búsqueda de la maximización racional del interés propio. Como una “mano invisible” el auto-interés parece conducir al bien común. Pero una lectura del intercambio como auto-interés racional, ejemplo de un paradigma de economía de libre mercado, es seductivamente engañosa y hasta sofista; porque se olvida de reconocer la existencia de actividad económica basada en la confianza2. En este modelo el comprador y el vendedor no ven sus intereses basándose en un intercambio comercial auto-interesado, sino en la creación de valor mutuo. a376 Aníbal Monasterio Astobiza medio del océano y quieren alejarse de una tormenta. Si ambos dejan de lado su interés egoísta de salvarse por ellos mismos y cooperan remando conjuntamente para alejarse de la tormenta es posible que se salven. Se puede definir la confianza como el estado psicológico que contiene la intención de aceptar vulnerabilidad basándose en las expectativas positivas de las intenciones o comportamiento de otro (Rousseau, Sitkin, Burt y Camerer, 1998). Definida así, la confianza es como exponer tu integridad a la expectativa de que otro hará algo bueno, pero puede que no. Eso es la confianza. La confianza crea cooperación y la cooperación crea cultura. Esta es la fórmula de la cultura que un enfoque económico de la misma debe tener claro. El problema es que la confianza como proceso psicológico que crea cooperación y la cooperación (junto con las normas como reforzadoras de la cooperación) son difíciles de formalizar económicamente. En otras palabras, ¿cómo crear modelos de la cultura en la economía de la cultura que sean mensurables y que permitan hacer predicciones para que se puedan aplicar políticas culturales mucho más efectivas? No es el propósito de este escrito decir qué tipo de modelo ha de ser aquel que mida cuantitativamente los factores que hay detrás de la emergencia de la cultura (cooperación, normas y confianza), como sí el de dar las pautas de guía para conocer adecuadamente ese modelo lo suficientemente válido y consistente para describir la cultura. La cultura tiene un impacto en la economía que se produce principalmente por agentes o individuos que influyen a otros. Esta influencia se enciende como una mecha que se expande por toda una población doi: http://dx.doi.org/10.3989/arbor.2017.783n1007 5 a376 ¿Qué es cultura en la «economía de la cultura»? Definiendo la cultura para crear modelos mensurables en economía cultural de potenciales consumidores. Principalmente, lo que hace que alguien sea un “influenciador” es la confianza que otros, implícita o explícitamente, depositan en esa persona. Después, la naturaleza social de las personas y su inherente tendencia a cooperar y a establecer normas tácitas genera el caldo de cultivo para que una representación cultural, es decir, una idea, una preferencia o una creencia, se trasmita rápidamente como un virus que infecta y se propaga entre las personas. Esta descripción es cierta en términos generales, pero por qué se produce la confianza en un primer momento, desde el principio, entre dos personas es una cuestión que ha tenido ocupados a muchos investigadores durante años. Ahora parece que tenemos más pistas para poder apuntar a la causa de por qué se extiende la confianza. De acuerdo con una larga tradición de modelización teórica que ha buscado las causas cognitivas próximas del comportamiento altruista basado en la confianza, la confianza se extiende entre las personas por la forma en la que la selección natural ha favorecido un modelo dual del procesamiento psicológico y conductual y que empíricamente se puede testar con las herramientas de la teoría de juegos. David Rand y colaboradores (Bear y Rand, 2016) han mostrado cómo la evolución y el aprendizaje selecciona agentes (personas) que son: 1) intuitivamente cooperadores (mediado por la confianza) pero que usan la deliberación para engañar o 2) intuitivamente engañadores que nunca deliberan. La confianza es un modo psicológico intuitivo de la motivación de las personas, o por lo menos de algunas, que se muestran cooperativos desde el primer momento y que solo cuando razonan y deliberan pueden actuar estratégicamente y engañar. Por resumir, como somos por naturaleza sociales, somos también confiados por naturaleza. Esta transmisión cultural basada en la confianza es epidemiológicamente hablando más rápida que una infección vírica. Sólo tienes que pensar en lo rápido que se trasmiten los rumores en un vecindario o en el lugar de trabajo. El efecto de propagación es proporcional al contacto o distancia de relación entre las personas (Christakis y Fowler, 2010). Para visualizar mejor cómo se produce la transmisión cultural se tienen que entender los papeles que juegan los distintos actores de cualquier esfera cultural. Los actores fundamentales son tradicionalmente: los creadores, los medios de distribución y los consumidores o usuarios. Con la irrupción de la tecnología digital y el gran acceso a la información y el conocimiento estos actores culturales se han transformado. ¿Por qué? Porque el 6 ARBOR Vol. 193-783, enero-marzo 2017, a376 ISSN-L: 0210-1963 consumidor o usuario ahora puede crear su propia actividad o práctica cultural gracias a la información y conocimiento disponible hoy en día, luego, por consiguiente, los creadores se expanden eliminando el binomio tradicional: creador-consumidor. Pero también los distribuidores se expanden eliminando otro binomio tradicional: distribuidor-consumidor. Ahora los consumidores pueden ser creadores y además distribuir gracias a la tecnología digital (Internet) su propio trabajo. El mapa del análisis económico de la cultura se ha transformado por completo. Esta transformación produce aún más aspectos intangibles de la cultura difíciles de capturar cuantitativamente con una metodología económico-normativa (Gibson y Klocker, 2003). 3. DISCUSIONES: LOS ASPECTOS INTANGIBLES DE LA CULTURA Se ha visto cómo la diversidad biológica y la diversidad cultural se pueden entender desde un mismo marco teórico: la evolución por selección natural de Darwin y Wallace y así conocer qué mecanismos están detrás tanto de los procesos biológicos como de los culturales. Esta analogía es válida y fructífera para entender cómo y por qué tenemos cultura. Sabemos que la cooperación y las normas junto con la confianza son los mecanismos fundamentales de la evolución de la cultura. La confianza es el fenómeno que permite la cooperación y la cooperación -junto con las normas- permite la cultura. Partiendo del reconocimiento de los mecanismos que dan lugar a la cultura se puede intentar modelizar cuantitativamente la cultura. Pero aún así, no se puede ignorar que surgen aspectos intangibles de la cultura. Es un fallo muy común por parte del discurso económico tradicional seguir creyendo que la cultura es un producto que se puede capturar con un valor de utilidad y asignar por tanto un precio de intercambio. Cierto es que al menos para la cultura material sí se puede, pero el componente simbólico de las distintas conceptualizaciones de cultura dota de una polivalencia a lo “cultural” difícilmente mensurable por los modelos económicos. La tecnología digital y las aspiraciones de la gente a que la cultura sea libre y gratuita ha cambiado las reglas de juego. Es difícil mantener un modelo basado en una tecnología de hace siglos con la actual tecnología digital y las nuevas preferencias sociales. También se ha visto una transformación de los agentes culturales tradicionales: el consumidor puede doi: http://dx.doi.org/10.3989/arbor.2017.783n1007 El marco teórico para entender la evolución de la cultura y los mecanismos responsables de su propagación son análogos a la evolución biológica. Este modelo de interpretación es válido. Pero las fuerzas transformadoras de la tecnología y el acceso más democrático al conocimiento han cambiado por completo el mapa de los agentes culturales y han amplificado o pronunciado aún más los aspectos intangibles de la cultura. Por ejemplo, un libro, un concierto de música en directo, entre otros muchos fenómenos culturales, tenían un precio específico fijado por mecanismos de asignación de precios (el mercado) con la tecnología anterior. Ahora la cultura en el siglo XXI ha dejado de ser una cultura material de objetos o productos para convertirse en una cultura de experiencias con un profundo trasfondo social (Boswijk, Thijssen y Peelen, 2007), que hace que la cultura tenga un valor que no se puede expresar en estadísticas (Holden, 2004) y, a veces, ni siquiera se fije un precio. La economía de experiencias ha pasado desapercibida hasta ahora y ha sido la última fase de una transición económica de bienes a servicios y finalmente a experiencias. En esta economía de experiencias ya no es el bien material ni el servicio lo que cuenta, sino cómo te sientes. Si verdaderamente la teoría económica quiere poder crear modelos mensurables de la cultura debe tener en cuenta que las experiencias subjetivas son difíciles de medir -no hay indicadores ni marcadores fiables a pesar de que las tecnologías de neuroimagen se están cada vez más utilizando como una ventana a la actividad de nuestra mente a la hora de consumir, comprar y decidir: Preston, Kringelbach y Knutson (2014)- sobre todo con una metodología de análisis desarrollada para modelizar intercambio de productos o bienes (objetos). La cultura son tradiciones de comportamientos y, por consiguiente, lo que se tendrá que cuantificar son hábitos culturales ARBOR Vol. 193-783, enero-marzo 2017, a376. ISSN-L: 0210-1963 (y experiencias). Un ejemplo de hábito cultural es ir al cine. Pero la economía tradicional te diría que para medir el impacto o retorno económico del cine uno solo tiene que computar el número de asistentes a un estreno etc. Olvidándose del hecho de que la dimensión experiencial no solo se traduce en el número de personas que van a las salas de cine, es la implicación y compromiso de una persona con la experiencia de ver la película que puede llevar a esa persona no solo a ver la película en el cine, sino también a comentar en foros y redes sociales, visitar las localizaciones del filme en otro país (turismo), comprar una entrada para el concierto del artista que aparece en la banda sonora del filme, comprar merchandising del filme (camisetas, tazas...) etc. Y todo esto no se puede prever o computar por el mero hecho de registrar la estadística de cuántos han acudido a las salas de cine (Holden, 2004; Throsby, 2003). Hay que crear modelos económicos que sean capaces de explicar cómo las experiencias son el nuevo activo de la economía cultural. Y mucho me temo que la modelización económica de la cultura ignora aspectos intangibles de los beneficios de la cultura. a376 Aníbal Monasterio Astobiza ser creador y distribuidor de cultura al mismo tiempo (Toffler, 1984). Esto ha existido desde la producción artesanal y flexible pero las tecnologías de la información y de la comunicación, incluidas otras tecnologías mecánicas de producción, la cultura DIY (do it yourself), maker y hacker dan lugar a una economía colaborativa que ha provocado un punto de inflexión y un cambio de paradigma económico (Cohen y Sundararajan, 2015), donde el intercambio no se hace por profesionales, sino por pares, y la estructura de costes y precios puede ni existir o ser compensada por medios alternativos a un sistema monetario (v.g. bancos de tiempo, favores, altruismo puro...). La cultura actual es de experiencias porque el objeto o el producto ya no es lo más importante. Parte de esta desmaterialización, descorporalización del clásico objeto cultural tiene que ver con la irrupción de la tecnología digital. La tecnología digital permite copiar, almacenar, compartir eludiendo la fisicalidad de los objetos. Si recordamos, la “cultura material”, los objetos creados de acuerdo a la trasmisión de información o las tradiciones de comportamientos, era una de las temáticas de la definición dada más arriba de cultura. Pero esta es una de las tres grandes temáticas. La industria de la música y la industria editorial (literatura) son dos ejemplos de artes que han experimentado un cambio de concepto de economía material a una economía de experiencias y la economía cultural debe tomar nota. Si la cultura actual es de experiencias, la economía actual debe ser de conocimiento o creatividad. Otra consecuencia de gran alcance, como se ha visto, es que los consumidores ya no son pasivos y ni siquiera son consumidores. Son creadores activos de cultura. Como consecuencia de este nuevo estatus adquirido de las personas que pasan de ser consumidores a creadores, facilitado por la tecnología pero también por el acceso al conocimiento, incluso el tradicional modelo de derechos de autor, el mito del creador se queda obsoleto. Si todos somos creadores en potencia y la esencia de la cultura es la copia, trasmisión doi: http://dx.doi.org/10.3989/arbor.2017.783n1007 7 a376 ¿Qué es cultura en la «economía de la cultura»? Definiendo la cultura para crear modelos mensurables en economía cultural 8 de información a través del tiempo, copiar y mezclar es el motor de la cultura. “Copiar” es la esencia de la cultura y copiar no es contrario a originalidad, dado que copiar facilita la creatividad, porque de las modificaciones que surgen de un acto inicial surge algo completamente nuevo. La cultura es trasmisión de información a través del aprendizaje social y el aprendizaje social es principalmente imitación, pero la imitación muchas veces no es fiel y de una simple variación que se acumula a través del tiempo surge algo completamente nuevo y original: la creatividad en acción. Nótese que este proceso cultural es similar al proceso de cambio en el mundo biológico. Bien es cierto que de la modificación y copia no fidedigna de una idea se puede producir algo nuevo creativo, como algo nuevo degradado. El proceso de cambio cultural por acumulación de cambios trasmitidos entre personas es un proceso de creación, pero también de degradación. La múltiple copia de una idea cambia el argumento o su contenido, lo muta para deteriorarlo, y esto hace que se pueda saturar la cultura de copias degradadas y mediocres. Esto conlleva que solo los agentes cultos sepan distinguir entre copia con creación de una copia degradada. Pero el mismo “espíritu” o filosofía de esta nueva economía de experiencias, colaborativa y de prosumers (palabra inglesa resultado de la suma de las palabras producers y consumers) hace que todos tendamos hacia el buen discernimiento de lo que es valioso culturalmente hablando. La educación y el conocimiento son, además de en cierta medida intangibles, el fundamento de esta nueva economía del siglo XXI. La mezcla, la copia de otra copia, es lo que caracteriza a la cultura. Sin embargo, la legislación en materia cultural a nivel internacional criminaliza la copia (Lessig, 2008). El famoso copyright ahoga la creatividad cultural y supone una filosofía de la economía cultural cortoplacista y estéril (Lessig, 2002). Solo esta nueva economía cultural será realmente creativa si es libre y gratuita. Puede ser una expectativa o un pronunciamiento político, pero la cultura es un recurso de “comunes” en el sentido de Elinor Olstrom como recurso compartido que no se define por propiedad, sino por derechos de acceso. Y todos tenemos derecho de acceso a la cultura y el conocimiento porque solo así crearemos nueva cultura y conocimiento en tanto y cuanto reconozcamos de dónde viene la idea, pero sabiendo que la idea no es poseída por nadie porque como hemos visto más arriba las ideas se mezclan e intercambian constantemente. Una verdadera economía de la cultura debe potenciar el derecho a mezclar y a copiar. ARBOR Vol. 193-783, enero-marzo 2017, a376 ISSN-L: 0210-1963 La ilusoria filosofía de los derechos de autor o propiedad intelectual por todos conocida, independientemente de la legislación nacional particular, como copyright trata los ítems (bienes y servicios) culturales como cualquier otro producto industrial. Pero esto es un error. Los ítems culturales son símbolos y estos son mucho más poderosos que cualquier iPhone, televisor o electrodoméstico. Como los ítems culturales son principalmente símbolos en la mente de las personas, medir el valor de la cultura con los métodos formales de la economía es una aventura de riesgo. Un euro (o póngase por caso cualquier otra divisa) invertido en cultura no es lo mismo que un euro invertido en otro activo. Mientras la inversión en ese otro activo desaparece con el agotamiento físico de ese bien, la inversión en cultura se perpetúa y se expande en la medida en que se propaga de una persona a otra. Recapitulando, hay aspectos intangibles de la cultura imposibles de modelizar, por lo menos directamente, y con la irrupción de la tecnología y el acceso al conocimiento estos se ven amplificados. La deconstrucción del artefacto o producto cultural es el resultado de la acción de la tecnología y el acceso a gran escala del conocimiento que lleva a que los ítems culturales dejen de ser productos para convertirse en experiencias. Esto hace que crear un modelo de cultura desde la economía cultural sea complejo. Primero, porque no se concibe bien lo que la cultura es, y segundo, porque actualmente los ítems culturales son experiencias, no objetos. Estas ideas expuestas son controvertidas. También es posible que los distintos conceptos de cultura (creencias, estados mentales, valores o cultura material) se hayan entrecruzado en la argumentación y se requiera de un mayor rigor analítico y gran apoyo argumentativo, además de bibliográfico, que solo hemos querido señalar por razones de espacio. Pero esto es precisamente una muestra de la complejidad de la idea de cultura que impide por el momento una modelización económica comprehensiva de la misma. Pero el lector interesado puede dirigirse, como un comienzo para seguir profundizando en la complejidad de la economía cultural basada en la colaboración, el aprendizaje, el conocimiento y la investigación compartida a Throsby (2001) y Benkler (2007). Con este escrito se ha intentado poder entender mejor qué es cultura en la economía de la cultura. Se ha hecho un breve apunte de la historia de la economía cultural y sobre la base de una analogía con el mundo biológico entendida desde el marco teórico del darwinismo se ha acotado el campo semántico de doi: http://dx.doi.org/10.3989/arbor.2017.783n1007 AGRADECIMIENTOS Agradezco el patrocinio del Gobierno Vasco para desarrollar una beca posdoctoral de investigación en el Uehiro Centre for Practical Ethics de la Universidad de Oxford y a esta última institución su cálida acogida. Este trabajo se ha realizado en el marco de los proyectos de investigación KONTUZ!: Responsabilidad causal de la comisión por omisión: Una dilucidación ético-jurídica de los problemas de la inacción indebida (MINECO FFI2014-53926-R), La constitución del sujeto en la interacción social: identidad, normas y sentido de la acción desde la perspectiva de la filosofía de la acción, la epistemología y la filosofía experimental (FFI2015-67569-C2-2-P) y Artificial Intelligence and Biotechnology of Moral Enhancement. Ethical Aspects (FFI2016-79000-P). Agradezco también a los revisores anónimos sus sugerencias y comentarios para mejorar este escrito. a376 Aníbal Monasterio Astobiza la noción de cultura. Se ha comentado la dificultad de medir, y por tanto dar valor, a la cultura teniendo en cuenta que hay aspectos intangibles de la cultura que se ven amplificados por la irrupción de la tecnología y el gran acceso al conocimiento hoy en día. El cómo de la transformación de los ítems culturales de objetos a experiencias, lo dejamos para futuras investigaciones. NOTAS 1 Agradezco a un revisor anónimo señalarme esta posibilidad. coherente o contradice la visión de la motivación humana expresada en The Wealth of Nations. Para muchos lo que se dice en esta última obra contradice lo que se dice en The Theory of Moral Sentiments. Pero quienes han interpretado a Adam Smith como el paladín de una economía de mercado libre sin escrúpulos morales (y hasta legales en forma de regulación) se equivocan intencionadamente o por ignorancia tal y como los editores del Glasgow Edition of the Works and Correspondence of Adam Smith sostienen. Axelrod, R. y Hamilton, W. (1981). The evolution of cooperation. Science, 211, pp. 1390-1396. https://doi.org/10.1126/science.7466396 Christakis, N. y Fowler, J. (2010). Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives. New York. Little Brown and Company. Conference. Auckland: New Zealand Geographical Society, pp. 131-135. Baumol, W. y Bowen, W. (1965). On the Performing Arts: The Anatomy of their Economic Problems. The American Economic Review, 55, 1/2, pp. 495-502. Cohen, M. y Sundararajan, A. (2015). SelfRegulation and Innovation in the Peerto-Peer Sharing Economy. Dialogue. The University of Chicago Law Review, 82, pp. 116-133. Disponible en http://chicagounbound.uchicago.edu/uclrev_online/vol82/iss1/8 2 Existe una disputa hermenéutica sobre la obra de Adam Smith (das Adam Smith problem) sobre si la visión de la motivación humana de Adam Smith reflejada en The Theory of Moral Sentiments es BIBLIOGRAFÍA Baumol, W. y Bowen, W. (1966). Performing Arts. The Economic Dilemma. A Study of Problems Common to Theater, Opera, Music and Dance. New York: The MIT Press. Bear, A. y Rand, D. (2016). Intuition, deliberation, and the evolution of cooperation. Proceedings of the National Academy of the United States of America. 113, 4, pp. 936-941. https://doi.org/10.1073/pnas.1517780113 Benkler, Y. (2007). The Wealth of Networks: How Social Production Transforms Markets and Freedom. New Haven: Yale University Press. Boswijk, A. Thijssen, T. y Peelen, E. (2007). The Experience Economy: A New Perspective. Amsterdam: Pearson. Corgnet, B., Espín, A. M., Hernán González, R., Kujal, P. y Rassenti, S. (2016). To Trust, or Not to Trust: Cognitive Reflection in Trust Games. Journal of Behavioral and Experimental Economics, 64, pp. 20-27. https://doi.org/10.1016/j. socec.2015.09.008 Gibson, N. y Klocker, N. (2003). Cultural industries and cultural policy: a critique of recent discourses in regional economic development. En Gao, J., Le Heron, R. and Logie, J. (eds). Windows on a changing world. Proceedings of the 22nd New Zealand Geographical Society ARBOR Vol. 193-783, enero-marzo 2017, a376. ISSN-L: 0210-1963 Hardin, G. (1968). The tragedy of the commons. Science. 162, pp. 1243-1248. https://doi. org/10.1126/science.162.3859.1243 Holden, J. (2004). The value of culture cannot be expressed only with statistics. Audience numbers give us a poor picture of how culture enriches us. London: Demos. [En línea]. Disponible en http:// www.demos.co.uk/files/CapturingCulturalValue.pdf King-Casas, B., Tomlin, D., Anen, C. Camerer, C. F., Quartz, S. R. y Read Montague, P. (2005). Getting to Know You: Reputation and Trust in a Two-Person Economic Exchange. Science, 308, pp. 78-83. https:// doi.org/10.1126/science.1108062 Kroeber, A. y Kluckohn, C. (1952). Culture. A Critical Review of Concepts and Definitons. Papers of the Peabody Museum of American Archaeology and Ethnology. Cambridge Mass: Harvard University Press. doi: http://dx.doi.org/10.3989/arbor.2017.783n1007 9 a376 ¿Qué es cultura en la «economía de la cultura»? Definiendo la cultura para crear modelos mensurables en economía cultural 10 Laland, K. (2017). Darwin’s Unfinished Symphony: How Culture Made the Human Mind. Princeton: Princeton University Press. https://doi.org/10.1515/9781400884872 Lessig, L. (2002). The Future of Ideas: The Fate of the Commons in a Connected World. New York. Vintage Lessig, L. (2008). Remix: Making Art and Comerce Thrive in The Hybrid Economy. New York: Penguin Press. https://doi. org/10.5040/9781849662505 glected Process in Evolution. Princeton: Princepton University Press. Preston, S., Kringelbach, M. y Knutson, B. (2014). Introduction: Toward an Interdisciplinary Science of Consumption. En Preston, S., Kringelbach, M. y Knutson, B. (eds). The Interdisciplinary Science of Consumption. Cambridge Mass: The MIT Press. https://doi.org/10.7551/ mitpress/9780262027670.001.0001 Moggridge, D. (2005). Keynes, the Arts and the State. History of Political Economy, 37, 3, pp. 535-555. https://doi. org/10.1215/00182702-37-3-535 Rousseau, D. M., Sitkin, S. B., Burt, R. S. y Camerer, C. (1998). Not so different after all: A cross-discipline view of trust. Academy of Management Review, 23, 3, pp. 393-404. https://doi.org/10.5465/ AMR.1998.926617 Odling-Smee, F., Laland, K. y Feldman, M. (2003). Niche Construction: The Ne- Throsby, D. (2001). Economía y Cultura. Madrid: Akal. ARBOR Vol. 193-783, enero-marzo 2017, a376 ISSN-L: 0210-1963 Throsby, D. (2003). Determining the value of cultural goods: How much (or how little) does contingent valuation tell us? Journal of Cultural Economics, 27, 3-4, pp. 275-285. Toffler, A. (1984). The Third Wave. New York: Bantam. Veblen, T. (1899/2001). The Theory of the Leisure Class: An Economic Study of Institutions. University of Virginia Library. Wilson, D. S. (2013). Human Cultures Are Primarily Adaptive at the Group Level (with comment). Cliodynamics: The Journal of Theoretical and Mathematical History, 4, pp. 102-138. doi: http://dx.doi.org/10.3989/arbor.2017.783n1007
https://openalex.org/W4385063411
https://paradigmacreativo.uanl.mx/index.php/revista/article/download/21/14
es
Niveles de depresión de los estudiantes de educación superior como condicionantes de la deserción escolar
null
2,022
cc-by
3,342
Niveles de depresión de los estudiantes de educación superior como condicionantes de la deserción escolar. Martha Paola Garay Mendoza ORCID: 0000-0001-5237-8601, Universidad Autónoma de Nuevo León, Facultad de Música, martha.garaymnd@uanl.edu.mx Resumen 20 Palabras clave: Deserción Universitaria, enfermedad mental, tutoría, depresión, estudiantes, psiquiatría. Las enfermedades mentales del siglo XXI consideradas como las del primer lugar y causadas; la mayoría de las veces debido al contexto socioeconómico, invaden el futuro de los jóvenes estudiantes, sumiéndolos en momentos de delirio y desesperación, son sin duda un tema fresco para tomar como base una investigación, que nos dé como resultado un parteaguas para descifrar bien el camino que deben tomar los catedráticos de las universidades, además de estar atentos a los focos rojos, para guiar en todo momento la estadía dentro de la universidad de los estudiantes y evitar así la deserción escolar. La creatividad de escritores, actores y músicos entre otros, “ha sido asociada a sintomatologías afectivas o emocionales”. La continua exposición a estas situaciones puede generar un riesgo mayor de consumo de sustancias; en otros casos las adicciones pueden estar influenciadas por factores como presión laboral y social, que generalmente provoca ansiedad, o bien “debido a que se involucran desde jóvenes al abuso de sustancias”. Sin embargo cada vez más son la mayoría de la población la que está siendo afectada por este tipo de trastornos llamados coloquial mente como “locura” independientemente del nivel socioeconómico y cultural, afectando las vida de las personas, y que sin una debida atención terminan desgraciadamente claudicando la vidas funcional que tenían y ganando un déficit de vida integral. Abstract The mental illnesses of the 21st century considered as those of the first place and caused; most of the time due to context socioeconomic, invade the future of young students, plunging them into moments of delirium and despair, are undoubtedly a fresh topic to base an investigation, which gives us as the result was a watershed to correctly decipher the path that university professors should take, in addition to being attentive to the red lights, to guide at all times the stay inside the university of students and thus avoid school desertion. The creativity of writers, actors and musicians, among others, “has been associated with affective or emotional symptoms.” The continuous exposure to these situations can generate a greater risk of consumption of substances; in other cases addictions may be influenced by factors such as work and social pressure, which generally causes anxiety, or “because they are involved from a young age in the abuse of substances”. However, they are increasingly the majority of the population. The one who is being affected by this type of disorders colloquially called “madness” regardless of socioeconomic level and cultural, affecting the lives of people, and that without proper attention unfortunately end up giving up functional life they had and gaining a deficit of integral life. Introducción La depresión es un término no muy aceptado aun por la sociedad, ya que aún se genera una especie de rechazo y tabú, debido a que estamos acostumbrados a estar mal del estómago, o de una muela y acudir al doctor, pero no de igual forma decirle al mundo ; disculpen tengo cita con mi psiquiatra. La Psiquiatría se ha dedicado a examinar y a describir sus dos dominios principales: los trastornos mentales, y la conducta del individuo en caso de salud y enfermedad. Los pacientes tratados por los psiquiatras tienden a experimentar trastornos “idiopáticos” o “funcionales”, cuyas causas se desconocen y que a menudo se llegan a corregir mediante instrumentos y fármacos. En general, la psiquiatría clínica, de manera muy significante, es semejante a lo que ocurre con la medicina, no es una “ciencia dura” y no requiere serlo para tener eficacia clínica. El presente estudio de investigación pretende establecer los niveles de ansiedad registrados en relación al bajo desempeño y finalmente a su deserción en la vida académica universitaria de 45 estudiantes de Licenciatura de las Facultades de Música, Visuales y Comunicación de la U.A.N.L Keywords: college dropout, mental illness, tutoring, depression, students, psychiatry. 21 En conclusión, se proponen dos estrategias para favorecer la retención de los universitarios: 1) formalizar la tutoría por medio de un seguimiento personalizado aplicando test de Niveles de depresión. 2) Fortalecer la estadía por medio de terapias con especialista de la mano con el Tutor, para detectar alguna enfermedad mental y tratarla de manera inmediata. Objetivos principales Formalizar la tutoría por medio de un seguimiento personalizado aplicando test de depresión. Objetivos secundarios Fortalecer la estadía por medio de terapias con especialista de la mano con el Tutor, para detectar alguna enfermedad mental y tratarla de manera inmediata. Desarrollo 22 22 22 Durante los últimos años, al trabajar como catedrática en la Facultad de Música de la UANL, en la acentuación en piano, he percibido que cada semestre, por lo menos cinco de cada 10 alumnos llegan a experimentar trastornos de salud mental. Dos de los más comunes son depresión y ansiedad, que, aunque el Manual de Psiquiatría lo describe de forma separada, son dos elementos inseparables, ya que cuando existe depresión, uno de sus síntomas es la ansiedad. Estos alumnos han requerido atención especializada con base en medicación con antidepresivos, ansiolíticos más terapia psicológica o psiquiátrica, a fin de poder sobrellevar la carga escolar, personal, laboral y económica de su vida. Los trastornos mentales tales como depresión, trastorno bipolar, psicosis, demencia o trastorno límite de la personalidad y abuso de sustancias, se han considerado estar asociados a factores biológicos, genéticos y sociodemográficos. Todo lo que pasa a nuestro alrededor afecta, las personas que no acepten esta teoría tendrían que tener un alto grado de resiliencia “llamada así como la habilidad de salir delante de cualquier adversidad” más aun especifico; El significado de resiliencia, según la definición de la Real Academia Española (RAE) es la capacidad humana de asumir con flexibilidad situaciones límite y sobreponerse a ellas, pero en psicología añadimos algo más al concepto de resiliencia: no sólo gracias a ella somos capaces de afrontar las crisis o situaciones potencialmente traumáticas, sino que también podemos salir fortalecidos de ellas. La deserción universitaria es una dificultad universal, definido en Colombia como la ausencia de actividad académica durante dos semestres consecutivos en un programa específico (Ministerio de Educación Nacional –MEN-, 2009. El abandono de un estudiante de su proceso formativo-académico se puede observar des- de dos perspectivas, según Tinto (1989): la primera se refiere al momento en que abandona la universidad, clasificándose en precoz, cuando se presenta entre la admisión y el inicio de la vida universitaria; temprana, entre el inicio y la mitad de la carrera; y tardía, entre el inicio de la segunda mitad y la conclusión del programa. La segunda perspectiva se refiere al espacio donde se presenta, pudiéndose distinguir dos tipos de deserción: la institucional, cuando el estudiante abandona por completo la universidad; y la interna, cuando el estudiante cambia de carrera. La enfermedad de trastorno mental como la ansiedad, provocan efectos que inciden en otros procesos psicológicos de forma gradual y negativa; han inducido a una intensa investigación por parte de los especialistas. Los índices estadísticos emocionales de ansiedad interactúan y modulan de manera entrelazada otros procesos psicológicos como la vigilia, la atención, la percepción, el razonamiento y la memoria, que forman una parte central en el procesamiento cognitivo.(Hernández ,Ramírez, Macías, 2015) Las reacciones de ansiedad pueden ser adaptativas y por tanto ventajosas al favorecer al individuo mediante un estado de alerta y de tensión que aumenta la probabilidad de un mejor rendimiento en determinadas situaciones demandantes, o por el contrario sostener una relación disfuncional con el entorno. En ese sentido las reacciones ansiosas en el contexto escolar, dependiendo de su intensidad y de las condiciones a las que se enfrenta la persona, pueden favorecer o perjudicar el rendimiento académico. La influencia de la ansiedad en el ámbito escolar ha sido un tema de considerable interés y debate entre los especialistas, mismos que han observado que los estudiantes tienen ejecuciones académicas bajas en situaciones caracterizadas por altos grados de ansiedad y al mismo tiempo se ha documentado una influencia Ansiedad, calificaciones, y probabilidad de fracaso escolar 47 | Psychol. av. discip. | Bogotá, Colombia | Vol. 9 | N.° 1 | p. 4557 | Enero - Junio | 2015 | ISSN 1900-2386 | mediadora positiva que pueden ejercer niveles bajos de ansiedad sobre el desempeño académico (Cassady, & Johnson, 2002; Contreras, Espinosa, Haikal, Polania, & Rodríguez, 2005), dependiendo del área de conocimiento particular en que se evalúe dicho desempeño. También se ha registrado en diferentes niveles. Muchas actividades que se realizan en la universidad, son esenciales para superar los retos académicos, y generan una apreciable fuente de estrés y ansiedad. Al comprender el estrés académico es indispensable tener en cuenta las condiciones sociales, económicas, familiares, culturales e institucionales. En general, la vulnerabilidad de la sociedad al estrés se ve 23 23 influenciada por su temperamento, la capacidad de resiliencia y el apoyo familiar comentan Suárez y Díaz (2014). Aunque la definición de deserción estudiantil continúa en discusión, existe consenso en precisarla como un abandono que puede ser explicado por diferentes categorías de variables: socioeconómicas, individuales, institucionales y académicas. Las definiciones de deserción planteadas por Tinto (1982) y Giovagnoli (2002). El estudio de Gutiérrez (2010) descubrió que la relación entre depresión y severidad del estrés es estadísticamente importante y que la prevalencia de la depresión podría llegar al 47,2 % de la población estudiada. Entonces, el estrés académico es un elemento que favorece el estrés crónico y el deterioro de la salud mental. 24 24 24 La educación superior ha vivido un proceso de aumento a lo largo de los años, produciéndose una diversificación en el eje social y aumento de matrícula, lo que conlleva la inclusión de otros sectores sociales, arrastrando un mayor número de estudiantes con problemas de salud mental. La transición de los jóvenes a un establecimiento educativo hacia la universidad, constituye un cambio muy importante, tanto en términos sociales y académicos. El sistema universitario requiere un perfil de mayor autonomía, además un justo equilibrio del tiempo personal, seguridad en la toma de decisiones y adaptación a la nueva cultura disciplinaria, lo cual afecta su estilo de vida comentan Trunce, Villarroel, Arntz, Muñoz, Werner (2020). La tutoría forma e integra conocimientos y experiencias de los diferentes ámbitos educativos, además de la experiencia escolar; en general; la vida diaria. Bajo esta perspectiva, el desarrollo de la práctica tutorial asume que la educación sea sinceramente integral y personalizada, que no quede reducida solamente a la instrucción o impartición de actividades académicas. La tutoría implica que se brinden servicios de psicología educativa mediante métodos indirectos. Los servicios de tutoría en este rubro, habitualmente reconocen y resaltan la importancia de utilizar procedimientos cooperativos y de colaboración para abordar los problemas de los estudiantes, comentan González, González, Soltero (2011). Síntomas de trastorno depresivo El trastorno depresivo mayor es un padecimiento recidivante caracterizado por una gama de síntomas físicos, emocionales y cognitivos, que varían de acuerdo con el tipo de seriedad y duración; sus síntomas son los siguientes: a) Tristeza o baja en el estado de ánimo. b) Pérdida del interés en actividades habituales. c) Dificultad para concentrarse. d) Bajo nivel de energía o fatiga. e) Manifestación de ansiedad como agitación psicomotora. f) g) Alteraciones neurovegetativas como el insomnio,dificultades para conciliar el sueño o mantenerlo, o despertar antes de lo habitual, pérdida del apetito y peso. Pensamientos acerca de morir, ideación suicida o intento suicida. Existen diferentes escalas auto aplicables que ayudan al diagnóstico y a la entrevista clínica; éstas determinan la intensidad de los síntomas depresivos: BDI (inventario de depresión Beck), QIDS-SR (Inventario–Aplicable Rápido para la Sintomatología Depresiva de 16 reactivos) y el PHQ (Cuestionario de Salud del Paciente de 9 reactivos), y con escalas de aplicación clínica como la Escala de Depresión de Hamilton y la Escala de Montgomery Asberg 48. Los episodios depresivos pueden ser leves, moderados, o severos sin síntomas psicóticos (con intento suicida), o severos con síntomas psicóticos (con alucinaciones o ideas delirantes). Otras características clínicas del episodio depresivo son las siguientes: a) Episodio depresivo mayor crónico (duración 2 años). b) Característica catatónicas (inmovilidad motora- catalepsia actividad motora excesiva o agitación, negativos o extremos). c) Característica melancólica; se presenta en los cuadros más severos y se asocia a un aumento en el cortisol. d) Característica Atípica (reactividad a los estímulos) en respuesta a eventos positivos, aumento de apetito, hipersomnia. 25 25 e) De inicio en el postparto, si aparece en las cuatro semanas después del parto. f) Con patrón estacional, si hay relación temporal entre el inicio del episodio depresivo mayor y una época en particular del año- otoño o invierno-, con remisión completa en una época particular del año habitualmente en la primavera. Origen de la causa probable de la depresión 26 26 26 La depresión es producto de la interacción de factores genéticos y ambientales; los genes ayudan a controlar la síntesis de los neurotransmisores y/o la conformación de sus receptores, las concesiones sinópticas, la transfusión intracelular, las señales neuronales y los cambios en sus características en respuesta a los estresores ambientales. El BNDF es el factor neurotrófico derivado del cerebro y es debido a su crecimiento de las células neuronales a lo largo de la vida y en relación también a su plasticidad. En las personas deprimidas crónicamente y sin tratamiento puede producirse que el tamaño del hipocampo se vea disminuido con el tiempo (Rot, Mathew y Charles, 2009). La depresión se caracteriza por anormalidades en la noradrenalina, serotonina y dopamina, (Nemeroff 2008). Los eventos estresantes, que se han relacionado con el inicio de la depresión, aumentan la actividad de los circuitos noradrenérgicos en el cerebro. En los pacientes deprimidos y en los suicidas hay una baja concentración del metabolito de la norepinefrina, el ácido 5-hidroxiindolacetico en líquido cefalorraquídeo y las plaquetas. Existe una relación entre las monoaminas con los síntomas de la depresión mayor, existe una participación general conjunta de la norapinefrina o noradrenalina, serotonina y dopamina en el estado de ánimo, emociones y funcionamiento cognitivo; de la norepinefrina y la serotonina; ansiedad e irritabilidad; en la norepinefrina y dopamina en respuesta a lo sexual el apetito y la agresividad. La glándula tiroides juega un papel crucial en los diagnósticos de la depresión, 10% de los pacientes presentan enfermedad tiroidea, una tercera parte muestra una respuesta aplanada de la tirotrofina (TSH) a tiroliberina (TRH) y algunos de ellos tienen alguna alteración autoinmune que afecta la tiroides (Sadock y Sadock, 2003). Ritmos circadianos; estos son ritmos biológicos intrínsecos de periodos de 24 horas y determinan el apetito y el sueño, la temperatura corporal, regulados por osciladores endógenos del núcleo supraquiasmático del hipotálamo. La luz viaja de la retina al sistema nervioso central por los tractos retino hipotalámico y geniecillo hipotalámico, vía núcleo geniculado ventrolateral; la señal circadiana se envía a través de la intervención simpática periférica a la glándula pineal; el ritmo se precisa sobre 24 horas, adelantándose o retrasándose con relación a la exposición de luz, la luz de la mañana adelanta el ritmo y produce una fase avanzada de secreción de la Melatonina y la luz de la tarde la retrasa; cuando éstas son alteradas se ha relacionado con inicio a la recurrencia de la depresión (Ontiveros- Uribe y Chávez–León, 2008). El trastorno depresivo mayor está en la población mexicana en un 3.3 %, alguna vez en su vida, 1.5% en el último año y de 0.6% en el último mes. La edad promedio de inicio son los dos años. La prevalencia en el primer nivel de atención es de 10% y en pacientes hospitalizados es de 1.5%. En todo el mundo la relación es de mujeres deprimidas por la vida por un 4.5% y en cambio solo el 2% de los varones (Medina-Mora, es al, 2003). Estudio 45 de los estudiantes de la U.A.N.L. encuestados con el inventario de Beck arrojaron la siguiente información; 16 alumnos salieron con resultados normales de estado de ánimo lo cual no es la mayoría eso nos sitúa en una posición moderada, en depresión de leve a moderada 10 alumnos, en depresión moderada a severa 9 alumnos, y en depresión severa 10 alumnos, si sumamos los 9 de depresión moderada a severa; más los 10 de depresión severa, nos da un total de 19; sin lugar a duda debemos estar preparados como Maestros-Tutores para guiar y mejorar la estadía emocional de los alumnos en su trayectoria en la Universidad para poder lograr el perfil de egreso satisfactorio con los estándares oficiales de la visión de la U.A.N.L. 27 27 Conclusión Se considera al trastorno depresivo mayor recurrente y tendiente a la cronicidad. El 50% de los pacientes tendrá un único episodio depresivo mayor en toda su vida. Sin embargo, los pacientes con enfermedades mentales y aquellos que han tenido un segundo episodio depresivo, tendrán varios episodios más en su vida. Por ejemplo el paciente que ha tenido dos episodios en su vida, tendrá un 70% de probabilidades de sufrir nuevos episodios. Si existe un tercer episodio tendrá un 90% de sufrir mucho más episodios. La asociación de la depresión con el suicidio es clara, el 70% de los suicidas tienen antecedentes de depresión no asistida, y el 15% de pacientes con depresión cometen suicidio. Aunque la cifra de intentos suicidas es mayor (Chávez- León y Ontiveros- Uribe, 2009, pp.108-113.). Seleccionar el tratamiento antidepresivo es crucial para establecer un tratamiento efectivo; la elección inicial habitualmente se basa en la sintomatología predominante, los efectos secundarios potenciales del fármaco y de la coexistencia de patologías médicas. 28 Referencias Giovagnoli, P. (2002) Determinantes de la deserción y graduación universitaria: una aplicación utilizando modelos de duración, Documento de Trabajo 37, Universidad Nacional de la Plata. Gonzalez, E., González, A., & Soltero, M. (2020). Desarrollo integral de los alumnos. El caso de la FCA de la UACH. Disponibl en: http://www.fca.uach.mx/apcam/2014/04/08/ Ponencia%20126-UACH.pdf Gutiérrez JA, Montoya LP, Toro BE, Briñón MA, Rosas E, Salazar LE. Depresión en estudiantes universitarios y su asociación con el estrés académico. Rev CES Med. 2010; 24 (1): 7-17. Hernández, M., Ramírez, N., López, S., & Macías, D. (2015). Relación entre ansiedad, desempeño y riesgo de deserción en aspirantes a bachillerato. Psychologia.Avances de Martha Paola Garay Mendoza la disciplina, vol. 9, núm. 1, pp.45-57. Disponible en: https://www.redalyc.org/pdf/2972/297233780003.pdf Pianista, concertista y profesora de tiempo en la Facultad de Músi- Linares R. (2021). Los 12 hábitos de las personas resilientes. El ca de la U.A.N.L. Con Maestría en Educación en EDEC de Monterrey, prado psicólogos, p. 4. Disponible en: https://www. y miembro del Comité organizador del Concurso Jóvenes Virtuosos elpradopsicologos.es/blog/resiliencia-resilientes de la Facultad de Música llevado a cabo cada año; en algunas otras Suárez, N., & Luz, B. (2014). Estrés académico, deserción y estrategias de retención de estudiantes en la educación ocasiones en el Festival internacional y Masterclass de Piano a cargo de la directora general Antonina Dragan. superior.Rev. Salud pública. 17(2), pp.300-313. Disponible en: http://www.scielo.org.co/pdf/rsap/ Imparte las cátedras de Piano a nivel Técnico y Licenciatura: Música v17n2/v17n2a13.pdf de Cámara, Acompañamiento Artístico y Coordinadora del Área de Tinto V. Dropouts from Higher Education: A Theoretical Synthesis Pianistas Acompañantes. También pertenece al Cuerpo Académico of the Recent Literature. A Review of Educational de Educación para la Música. Acreedora del perfil deseable de PRO- Research.1975; 45, 89-125. DEP Programa para el Desarrollo Profesional Docente, desde 2018. Trunce, S., Villarroel, G., Arntz, J., Muñoz, S., & Werner, K (2020). Niveles de depresión, ansiedad, estrés y su relación con El 31 de enero de 2019 publicó su primer libro “Estrategias de ense- el rendimiento académico en estudiantes universitarios. ñanza pianística musical para el desarrollo de habilidades cogniti- Investigación Scielo, Vol.9, “p”.36. Disponible en: vas”, con la Editorial T&R. El 28 de diciembre de 2020 publicó su se- http://www.scielo.org.mx/scielo.php?script=sci_ gundo libro “El lado oscuro de una Pianista con la Editorial T&R. arttext&pid=S2007-50572020000400008 Vera.L, Niño J, Porras A, Navarro J, Caballero M, Delgado P, & Durán J. (2020). Salud mental y deserción en una población universitaria con bajo rendimiento académico. Católica del Norte, Fundación Universitaria; Pioneros en educación virtual., Núm. 60, pp 137-158.Disponible en: https://www.redalyc.org/journal/1942/194263234008 29
https://openalex.org/W2910617019
https://eprints.leedsbeckett.ac.uk/id/eprint/5628/1/CausesofDelaysDuringHousingAdaptationPV-OYEGOKE.pdf
English
null
Causes of Delays during Housing Adaptation for Healthy Aging in the UK
International journal of environmental research and public health/International journal of environmental research and public health
2,019
cc-by
12,359
Received: 12 October 2018; Accepted: 28 December 2018; Published: 11 January 2019 Abstract: Housing adaptation is a rehabilitation intervention that removes environmental barriers to help older people accommodate changing needs and age in place. In the UK, funding application for home adaptations to local authorities is subject to several procedural steps, including referral, allocation, assessment, funding and installation. The five stages need to complete in a sequential manner, often cause long delays. This study aims to investigate the timelines across these key stages of the adaptation process and examine the main causes of delays in current practice. A mixed-methods research strategy was employed. A questionnaire survey was first undertaken with all 378 local authorities in England, Scotland and Wales; it was followed by 5 semi-structured interviews and 1 focus group meeting with selected service providers, and 2 case studies of service users. The results showed that the average length of time taken to complete the whole process is relatively long, with the longest waiting time being observed at the funding decision stage. Delays were found in each of the key stages. Main causes of delay include insufficient resources, lack of joint work, legal requirements, shortage of competent contractors and the client’s decisions. These issues need to be addressed in order to improve the efficiency and effectiveness of future housing adaptation practice. Keywords: housing adaptation; process stage; aging in place; waiting time; delays Citation: Zhou, W and Oyegoke, AS and Ming, S (2019) Causes of Delays during Housing Adaptation for Healthy Aging in the UK. International Journal of Environmental Research and Public Health, 16. ISSN 1660-4601 DOI: https://doi.org/10.3390/ijerph16020192 Citation: Zhou, W and Oyegoke, AS and Ming, S (2019) Causes of Delays during Housing Adaptation for Healthy Aging in the UK. International Journal of Environmental Research and Public Health, 16. ISSN 1660-4601 DOI: https://doi.org/10.3390/ijerph16020192 Citation: Zhou, W and Oyegoke, AS and Ming, S (2019) Causes of Delays during Housing Adaptation for Healthy Aging in the UK. International Journal of Environmental Research and Public Health, 16. ISSN 1660-4601 DOI: https://doi.org/10.3390/ijerph16020192 Citation: Zhou, W and Oyegoke, AS and Ming, S (2019) Causes of Delays during Housing Adaptation for Healthy Aging in the UK. International Journal of Environmental Research and Public Health, 16. ISSN 1660-4601 DOI: https://doi.org/10.3390/ijerph16020192 Link to Leeds Beckett Repository record: https://eprints.leedsbeckett.ac.uk/id/eprint/5628/ Document Version: Article (Published Version) Creative Commons: Attribution 4.0 Creative Commons: Attribution 4.0 The aim of the Leeds Beckett Repository is to provide open access to our research, as required by funder policies and permitted by publishers and copyright law. The Leeds Beckett repository holds a wide range of publications, each of which has been checked for copyright and the relevant embargo period has been applied by the Research Services team. We operate on a standard take-down policy. If you are the author or publisher of an output and you would like it removed from the repository, please contact us and we will investigate on a case-by-case basis. Each thesis in the repository has been cleared where necessary by the author for third party copyright. If you would like a thesis to be removed from the repository or believe there is an issue with copyright, please contact us on openaccess@leedsbeckett.ac.uk and we will investigate on a case-by-case basis. International Journal of Environmental Research and Public Health Int. J. Environ. Res. Public Health 2019, 16, 192; doi:10.3390/ijerph16020192 Causes of Delays during Housing Adaptation for Healthy Aging in the UK Wusi Zhou 1,* , Adekunle Sabitu Oyegoke 2 and Ming Sun 3 Wusi Zhou 1,* , Adekunle Sabitu Oyegoke 2 and Ming Sun 3 1 School of Public Administration, Hangzhou Normal University, Hangzhou 311121, China 2 School of Built Environment & Engineering, Leeds Beckett University, Leeds LS1 3HE, UK; A.Oyegoke@leedsbeckett.ac.uk 3 School of Architecture, Design and the Built Environment, Nottingham Trent University, Nottingham NG1 4FQ, UK; ming.sun@ntu.ac.uk * Correspondence: wzhou5421@gmail.com    1 School of Public Administration, Hangzhou Normal University, Hangzhou 311121, China 2 School of Built Environment & Engineering, Leeds Beckett University, Leeds LS1 3HE, UK; A.Oyegoke@leedsbeckett.ac.uk 3 School of Architecture, Design and the Built Environment, Nottingham Trent University, Nottingham NG1 4FQ, UK; ming.sun@ntu.ac.uk * Correspondence: wzhou5421@gmail com y g 3 School of Architecture, Design and the Built Environment, Nottingham Trent University, Nottingham NG1 4FQ, UK; ming.sun@ntu.ac.uk * C d h 5421@ il Received: 12 October 2018; Accepted: 28 December 2018; Published: 11 January 2019 1. Introduction In England and Wales, for example, although all owner occupiers and tenants in the private or social sector are eligible for disabled facilities grants (DFGs), local housing authorities and housing associations commonly use their own budgets, such as housing revenue account and housing association funding, to undertake adaptations for their tenants. Therefore, DFG is the main source of funding for private sector adaptations. g p p According to the “Housing Grants, Construction and Regeneration Act 1996”, to award a DFG, the housing authority must be satisfied that an adaptation is necessary and appropriate to meet the applicant’s needs and that the work is reasonable and practical in terms of the property’s age and condition. Also, the housing department needs to consult the social services department in deciding the necessity and appropriateness of the adaptation work. Therefore, there are at least two departments involved in the adaptation process, with the social services providing assessments and the housing services awarding grants. This multiple organisational arrangement becomes more complicated under two-tier administrations in England, where the county council is responsible for social services and the district council for housing services. Since the Local Government and Housing Act 1989 provided financial support for home improvement agencies (HIAs), many local authorities have worked with them to deliver housing adaptations. With the involvement of multiple organisations and multiple departments, the adaptation system is fragmented and confusing. Clients often have to deal with a network of organisations and numerous professionals when applying funding for housing adaptations [26,27]. Although DFGs are mandatory, they are subject to means test to determine whether an applicant has to make a financial contribution towards the cost of an adaptation. In addition, there is a maximum award limit for DFG, £30,000 in England and £36,000 in Wales. The system requires the applicant to pay any cost that exceeds the statutory maximum. For a successful adaptation, an applicant has to navigate through a number of procedural steps, including referral, allocation, assessment, funding and installation [28,29]. The adaptation process usually starts when an applicant is referred by their GP or other healthcare professionals to the welfare authority, such as the social services in England and Wales and the social work in Scotland. In some councils, clients are able to refer themselves for adaptation services. 1. Introduction The UK’s population is aging. For many older people, the aging process results in gradual loss in physical capacity; environmental barriers frequently turn their home into a place of embarrassment or confinement [1,2]. On the other hand, over 85% of older people have a strong desire to “stay put” in their own houses and to remain engaged in the community [3,4]. Behind this desire lies a strong attachment to the home, which keeps people busy and active, shields privacy and freedom, and boosts sense of identity and self-esteem [5,6]. Housing adaptation is recognised as an effective intervention to enhance home accessibility and to meet the changing needs of older people [7–9]. When health deteriorates and mobility reduces, older people can remove obstacles by adapting their houses to manage daily activities at home and participate in social life [10,11]. Both physical activity and social participation have important implications for healthy aging [12]. Housing adaptation has been defined in a variety of ways, such as a temporary rearrangement of furniture or fittings [13,14], an alteration to permanent features of the physical environment [15,16], and a physical change to the home environment including the provision of equipment [17]. This study defines housing adaptation as modification of physical features in the indoor and immediate outdoor environment (e.g., changes to the layout or the structure features and installation of fixtures and fittings) Int. J. Environ. Res. Public Health 2019, 16, 192; doi:10.3390/ijerph16020192 www.mdpi.com/journal/ijerph 2 of 16 Int. J. Environ. Res. Public Health 2019, 16, 192 to reduce environmental barriers and restore independent living. In essence, the home environment is adapted to meet the specific needs of individuals who are experiencing difficulties in performing daily activities at home [18]. The underlying assumption that adapting the environment can improve functional performance is based on the ecological theory of aging [19–21]. Specifically, there is an optimal person-environment fit when personal competence is compatible with the environmental demand, while a misfit occurs when the environmental press exceeds individual ability [22,23]. In the UK, local councils have a statutory duty to provide financial assistance for housing adaptations that are assessed to be necessary to meet the special needs of disabled people and help them maintain independent living at home [24,25]. There are various funding avenues that people could access to assist with adaptations, depending on the types of housing tenure and the location of the property. 1. Introduction On receipt of referrals, an initial screening process normally takes place to prioritise cases and allocate them to specific fieldworkers like occupational therapists (OTs) for assessments. Immediately after allocation of each case, the OT makes the first home visit, assesses the client’s needs against the eligibility criteria and decides the type of adaptation required. The case is then passed on to the housing department for funding authorisation; the grant officer will send the client an application form and associated documents for means testing. Agencies, such as HIAs or care and repair (C&R), are often informed to help clients complete the grant application and the installation work. Before starting any construction work on site, there need to be landlord’s consent when the client is a tenant and planning permission when the adaptation involves an extension or a structural alteration [30]. Once plans and specifications for an adaptation are confirmed, contractors are invited to submit quotations for its installation. A contractor is selected by the client to carry out the work; the finished work is then inspected and approved before payment can be made. These complex procedures have resulted in slow service pathways for housing adaptations and unnecessary waste of limited public resources [31,32]. 3 of 16 Int. J. Environ. Res. Public Health 2019, 16, 192 As the current adaptation process is fragmented and involves several linear steps, the length of time taken to complete these steps decides the efficiency and effectiveness of the whole process. If significant delays occur during this process, older clients may have to move into care homes or be transferred to hospitals. Such a result will cause additional stress and reduced quality of life for the elderly. Previous research [29,31,33] found that long waiting time was a longstanding problem in the delivery of adaptations and had attracted frequent complaints from service users. Recently, national strategies have placed a particular emphasis on tackling delays associated with the adaptation process [34–36]. However, there were still frequent reports by service providers and services users on long waiting lists during housing adaptations [33,37]. g g g g p There have been several studies on evaluating housing adaptation practices. Clayton and Silke [30] evaluated housing adaptation grant scheme with a framework covering effectiveness, consistency, impact and prioritisation. Bibbings et al. 1. Introduction [38] reviewed the program of independent living adaptation and identified strengths and weaknesses of the delivery system by measuring quality, speed, appropriateness and value for money. Kempton and Warby [39] measured the social return on investment of adaptations through reduced costs, increased safety and improved well-being and independence of older people. Chiatti and Iwarsson [15] postulated that three aspects had to be considered for an evaluation of home adaptation interventions, including the perspective of the evaluation, the evaluated content of the intervention and the time frame. Time is a common criterion in all these evaluation studies. However, none of these studies reported empirical data of time on the current housing adaptation practice. This study seeks to fill this knowledge gap and to draw international attention to the importance of addressing the housing crisis for older people. It also contributes to the ongoing global debate about creative housing solutions to the big problem caused by the rapidly aging population. This study is aimed at reviewing the timelines of the adaptation process in local authorities across the UK and examining the causes of delays in the current practice. It seeks to address the following questions: 1. What is the average waiting time for the whole process and for each key stage? 2. Where are extensive delays experienced by clients during their application for adaptations? 3. What are the main causes for these delays during the housing adaptation process? 2.1. Sampling and Participants This study adopts a mixed-methods approach [40,41]. In the first phase, a questionnaire survey was carried out to investigate how local authorities organise their adaptation services. This was followed by five interviews, two specific cases and a focus group meeting with stakeholders to gain different perspectives of the adaptation system. Quantitative analysis is used to examine the current status and identify issues within each stage of the adaptation process in different local authorities, while the qualitative data are used to supplement the qualitative findings. The rationale for the choice of mixed-methods is that neither quantitative method nor qualitative method, on its own, is sufficient to evaluate the effectiveness of housing adaptation practices but the combination of the two can produce a more comprehensive analysis [40,42]. The research chooses to focus on homeowners and private tenants, as they account for the majority of households in the UK and most of them have little knowledge about where to start and what assistances are available when they need adaptations. Purposive sampling [43] was used for the survey, as local authorities have the powers and duties to provide housing adaptations in the UK. County councils in England were excluded as they do not fund adaptations directly and only provide OT assessments. Also, local authorities in Northern Ireland were excluded, as they have a unique Health and Social Services under a unified structure that leads to organisational differences towards adaptation services from other nations in the UK [37]. As a result, the questionnaire was sent to the remaining 378 local authorities in England, Scotland and Wales. After the survey, a sample of survey respondents and relevant professionals were approached for semi-structured interviews. This sample was selected purposively, with specific criteria including those Int. J. Environ. Res. Public Health 2019, 16, 192 4 of 16 currently working in local authorities or associated organisations and being responsible for different stages of the adaptation process. The rationale for this purposive selection is that professionals, who have been involved in the adaptation process, have in-depth knowledge of the existing delivery system. Five professional participants were invited for face to face interviews. To examine service effectiveness, it is essential to capture service users’ experiences and views of their adaptation services. During the interviews with staff from the adaptation service provider—C&R, two client participants were identified as case studies. 2.1. Sampling and Participants The selected clients were older adults (aged 65 or over) with disabilities, living in private properties and had received a housing adaptation grant within the previous two years. p y One local council was chosen for a focus group meeting, because it has the social work department, the housing department and C&R working in partnership to provide adaptations and was accessible to the researcher. Participants of the focus group included one OT, one housing surveyor, one grant officer, one technical officer, one C&R manager and one administrative assistant; they have worked together and attended regular meeting for the delivery of adaptations over 2 years. 2.2. Data Collection As explained earlier, the application process for housing adaptations consists of five key steps, including referral, case allocation, assessment, funding approval and installation. The questionnaire asked about waiting time for these five stages and for the whole process. Local authorities were allowed to describe their own processes, where these may be different from the five standard stages in the questionnaire. Once the questionnaire was designed, a pilot test was conducted with 20 local councils prior to the main survey. Results from the pilot led to modification of some questions. The finalised questionnaire, along with a cover letter and postage prepaid envelope, was sent to the housing department of all local authorities across the UK. At the same time, an online survey was activated for those who preferred to respond online. After four weeks, reminder phone calls and emails were made to non-respondents. At the end of this process, a total of 112 local authorities responded to the survey, with 61 sent back by post, 28 replied online, and another 23 by emails. The response rate was 29.6% that is comparable to other studies, such as Connell et al. [44] and Davies et al. [45]. Following the quantitative study, qualitative data were gathered through interviews with five professionals, two case studies and a focus group. The five identified professionals were interviewed in their offices, which lasted between 60 and 150 min. The interview questions were open-ended, focusing on service delivery timelines and blockages within each key stage. Two case studies were carried out with older clients to explore their experiences and concerns of the adaptation process. The dates for every stage of the adaptation process were also collected from both clients. A focus group meeting was organised in one local council; it discussed key issues with local adaptation arrangements and main causes for process delays. All interview and focus group discussions were recorded and transcribed verbatim afterwards. 2.4. Ethics This study complied with the university’s research ethics policy and was approved by the University Research and Ethics Committee. Informed consent was obtained from all participants before interviews, case studies and the focus group. 2.3. Data Analysis This paper provides empirical analysis of waiting times for key stages and causes of delays in adaptation provision that were captured through quantitative and qualitative research. Data analysis was conducted based on the integrated procedures in the mixed-methods approach [40]. Initially descriptive analysis identified the minimum, average and maximum waiting times between process steps across local authorities and measured an overall effectiveness of service delivery. These quantitative results then were discussed with support of qualitative data from the interviews and focus group [42]. For the case studies, the number of days for each client to wait between stages of the adaptation process were calculated. Significant statements on process delays were identified; content analysis was used to identify any causes of delays in the provision. 5 of 16 Int. J. Environ. Res. Public Health 2019, 16, 192 p y g p The referral to assessment stages are not known as they are belonging to the county council. The OT recommendation to grant approval stage is 189 days. From grant approval to installation is 152 days. 3.1. Overall Average Waiting Time Public Health 2019, 16, 192 On average, the total length of time for the whole adaptation process in Category I and II was 193 days and 243 days respectively, while the two stages from OT recommendation to installation in Category III took up to 227 days. On average, the total length of time for the whole adaptation process in Category I and II was 193 days and 243 days respectively, while the two stages from OT recommendation to installation in Category III took up to 227 days. g y p y The results showed great variations in the application processing speed in different local councils. For example, from the initial request to case allocation, the quickest local authority in Category I took just 1 day while the slowest needed 189 days; the average is 41 days. Following case allocation, the OT required 1 to 103 days to make the first assessment visit; the average time was 21 days. Once the assessment started, it could be expected to complete within a minimum of 2 days and an average of 46 days, but a maximum of 233 days was not exceptional. When the OT assessed the client’s need and specified the required adaptation, the case was passed to the grant officer for funding approval. The time taken to obtain this approval varied markedly across local authorities from 3 days to 233 days, with an average of 85 days. Once a grant was authorised, the installation work could go ahead. It could take 14 to 90 days to finish, with an average time of 54 days. To complete the whole process, the quickest local authority took up to 60 days, while the slowest needed 360 days. Compared with Category I, the timelines in Category II and III showed greater variations within each stage and longer waiting between stages. In Category II, time from referral to assessment varied from a minimum of 28 days to a maximum of 573 days. The time taken in getting funding approved was much longer, with an average of 118 days in Category II and of 112 days in Category III, and could be up to 630 days in Category II and 385 days in Category III. Similarly, the average time taken by the contractor to complete an adaptation was over three months in both Category II and III. 3.1. Overall Average Waiting Time Table 1 shows the average waiting times between key stages of the adaptation process. As some local authorities introduced their own stages and some provided partial records, the information is presented under three categories, each of which describes different process patterns and timelines through the adaptation process. Category I includes 35 local councils and shows the timelines across five key stages of the process and the total time, as listed in the questionnaire. Here, the total time is not a simple sum of delays of all stages but a reported length of time taken to complete the whole process. Category II includes 24 local authorities and presents waiting timelines between three stages of provision. These local authorities merged the first three stages from referral to assessment into one, as presented in Table 1 and described by a housing officer: 1. Referral to OT recommendation is normally 3 months; 2. OT recommendation to grant approval is 60 days; 3. Grant approval to installation is 60 days; 4. The total time is 180 days. Table 1. Timelines between stages of the adaptation process. The Adaptation Process Minimum Average Maximum Median Stages (day) Category I 1 Referral 1 41 189 28 2 Case allocation 1 21 103 7 3 Assessment 2 46 233 21 4 Funding approval 3 85 233 60 5 Installation 14 54 90 56 Total 60 193 360 166 Category II 1–3 Referral to assessment 28 121 573 85 4 Funding approval 23 118 630 67 5 Installation 30 93 226 77 Total 90 243 474 236 Category III 4 Funding approval 7 112 385 92 5 Installation 7 115 356 96 Total 84 227 522 188 Table 1. Timelines between stages of the adaptation process. Category III includes 43 local councils and only displays waiting times for the two stages of funding approval and installation. Due to different departments and agencies being responsible for different stages, some partners, particularly in local authorities under the two-tier system, could only provide their own delivery times. A grant officer reported: The referral to assessment stages are not known as they are belonging to the county council. The OT recommendation to grant approval stage is 189 days. From grant approval to installation is 152 days. 6 of 16 Int. J. Environ. Res. 3.1. Overall Average Waiting Time It was common practice that local authorities applied the eligibility framework to prioritise cases and urgent needs were dealt with immediately while other applicants were placed on the waiting list. A social worker confirmed: We have different time targets for assessment of different priorities. So if the case is priority 1, the client will be seen between 24 to 48 h; if it is priority 2, within 72 h; if it is priority 3, must be seen in 28 days; if it is 4, then it is 12 weeks. In addition, simple adaptations where assessment and installation could be done quickly were usually provided straightaway, while more complex needs tended to require more work thus experienced longer waiting times: There are huge variations for total time—simple cases can be 3–4 months and complex cases can be several years. (a grant officer) 3.2. Case Studies 3.2.1. Case One 13/10/2013 Referral to social work 50 days 03/12/2013 Allocation for OT assessment 27 days 30/12/2013 OT assessment completion 59 days 27/02/2014 Case came to C&R 13 days 12/03/2014 C&R's first visit 18 days 30/03/2014 C&R's technical officer visited to quote 44 days 13/05/2014 Grant application 143 days 03/10/2014 Grant approval 58 days 20/11/2014 Contractor instructed 55 days 14/01/2015 Work resumed after the client poseponed 7 days 21/01/2015 Case completed Total 474 days Figure 1. The timeline of the adaptation process for Client A. 03/12/2013 Allocation for OT assessment 13/10/2013 Referral to social work 30/12/2013 OT assessment completion 50 days 59 days 30/03/2014 C&R's technical officer visited to quote 12/03/2014 C&R's first visit 27/02/2014 Case came to C&R 03/10/2014 Grant approval 13/05/2014 Grant application 20/11/2014 Contractor instructed 14/01/2015 Work resumed after the client poseponed 21/01/2015 Case completed 474 days Figure 1. The timeline of the adaptation process for Client A. Figure 1. The timeline of the adaptation process for Client A. Client A’s timeline was consistent with the general trend of significant delays during the two stages of funding and installation. The longest wait of 143 days remained at the funding approval stage, which was mainly caused by limited available resources in conjunction with large backlogs of grant applications. Because the client’s property is a typical flat, the adaptation work requires a building warrant. Applying for this warrant took roughly six weeks, resulting in an elapse of 58 days from grant approval to contractor instructed. Installation work took 62 days, within which the client postponed the process for two weeks in order to celebrate Christmas and New Year with her family. Likewise, the client experienced significant waiting times from referral to allocation, although assessment of need was undertaken shortly afterwards. Normally, once the assessment is completed, the OT closes off the case and soon passes it to C&R. However, in this case, it took 59 days for the case to come to C&R after assessment. This substantial delay reflected fragmented responsibilities and the lack of partnership working. In fact, C&R did not know until the case came from OTs and was not able to start the subsequent process as soon as assessment was completed. 3.2.1. Case One Client A was a woman aged 79, living alone in an upper flat of a block. There was no elevator and she had to manage twelve steps to the entrance door. She had an upper and lower limb weakness that limited her mobility and also had difficulties getting into her bathtub. She was an owner-occupier and had applied for mandatory grants to replace the existing bathtub with a level access shower tray. Client A received her new shower with funding of £3624.32 on 21 January 2015 and the whole process took around 15 months (Figure 1). She was initially referred by C&R to the social work department on 13 October 2013 and 50 days later, the case was allocated to the OT for assessment, which was completed on 30 December 2013. C&R, an adaptation agency, involved after the OT completed the assessment. It provided a range of assistance, including supporting the client to access grant funding and coordinating the installation process. Within two weeks after receiving the case, C&R visited the client on 12 March 2014 to look at the property’s condition, offer technical and architectural advice about the adaptation, and check the client’s entitlement to benefits. Eighteen days later, when the specification and appropriate technical drawings for the adaptation were produced, C&R invited contractors to visit the client with a view of providing quotes for the work. Once an estimate was received, C&R prepared all the relevant documents, including planning permission, building insurance, 7 of 16 7 of 16 Int. J. Environ. Res. Public Health 2019, 16, 192 property deed, relevant certificates and benefits evidence, on behalf of the client for grant application. This took nearly two months from 20 March 2014 to 13 May 2014. Furthermore, the housing department took nearly five months to approve the grant application; the client had to wait for more than three months after grant approval before using the new shower tray. Int. J. Environ. Res. Public Health 2019, 16, x 7 of 16 Figure 1. The timeline of the adaptation process for Client A. 3.2.1. Case One After C&R took over the case, there was another prolonged wait of 75 days and the main cause was preparation of all supporting documents for grant application, including an application form, an OT report, an approval of pension credit, a schedule of works, two priced estimates, a copy of the title deed. Client A’s timeline was consistent with the general trend of significant delays during the two stages of funding and installation. The longest wait of 143 days remained at the funding approval stage, which was mainly caused by limited available resources in conjunction with large backlogs of grant applications. Because the client’s property is a typical flat, the adaptation work requires a building warrant. Applying for this warrant took roughly six weeks, resulting in an elapse of 58 days from grant approval to contractor instructed. Installation work took 62 days, within which the client postponed the process for two weeks in order to celebrate Christmas and New Year with her family. Likewise, the client experienced significant waiting times from referral to allocation, although assessment of need was undertaken shortly afterwards. Normally, once the assessment is completed, the OT closes off the case and soon passes it to C&R. However, in this case, it took 59 days for the case to come to C&R after assessment. This substantial delay reflected fragmented responsibilities and the lack of partnership working. In fact, C&R did not know until the case came from OTs and was not able to start the subsequent process as soon as assessment was completed. After C&R took over the case, there was another prolonged wait of 75 days and the main cause was preparation of all supporting documents for grant application, including an application form, an OT report, an approval of pension credit, a schedule of works, two priced estimates, a copy of the title deed. 3.2.2. Case Two 3.2.2. Case Two On 19 August 2015 C&R assisted the client with submitting an application form together with all supporting documents for the grant. Funding was granted within two weeks and the selected contractor was then instructed. On 12 December 2015 the case was completed and the whole process took around one year and eight months (Figure 2). Int. J. Environ. Res. Public Health 2019, 16, x 8 of 16 first visit. On 3 June 2014, the OT visited his house. Thereafter, the process seemed to have stalled until 10 July 2015 when the case was passed to C&R. During this period, of more than one year, the client spent time in a hospital twice because of health problems, with the first stay for three weeks and the second for seven weeks. When the case did eventually arrive at C&R, on that very same day a C&R officer visited the client to explain the process, describe the building work and provide information needed for the funding application. When plans and specifications for adaptations were ready, the technical officer invited contractors to the client’s house for tenders. On 19 August 2015 C&R assisted the client with submitting an application form together with all supporting documents for the grant. Funding was granted within two weeks and the selected contractor was then instructed. On 12 December 2015 the case was completed and the whole process took around one year and eight months (Figure 2). 10/04/2014 Referral to social work 35 days 15/05/2014 Referral allocated 11 days 26/05/2014 Letter informed OT's first visit 8 days 03/06/2014 OT's first visit 402 days 10/07/2015 Case came to C&R 1 days 10/07/2015 C&R's first visit 11 days 21/07/2015 C&R's second visit to tender 29 days 19/08/2015 Grant application 15 days 03/09/2015 Grant approval 4 days 07/09/2015 Contractor instructed 96 days 12/12/2015 Case completed Total 612 days Figure 2. The timeline of the adaptation process for Client B. 15/05/2014 Referral allocated 10/04/2014 Referral to social work 21/07/2015 C&R's second visit to tender 19/08/2015 Grant application 12/12/2015 Case completed Figure 2. The timeline of the adaptation process for Client B. Figure 2. The timeline of the adaptation process for Client B. In this case, the longest waiting times occurred at the assessment stage and the installation stage, which accounted for 81.4% of the total time. Client B experienced a significant delay in accessing the OT assessment. 3.2.2. Case Two 3.2.2. Case Two There was an unacceptable wait of 402 days, causing by a couple of factors. First, due to deterioration of health condition, the client was taken to hospital twice and stayed for a total of 10 weeks during the assessment process. Each hospital stay had resulted in the assessment being suspended until the OT was informed to resume the work. Secondly, poor arrangement and cooperation between different OTs was reported to delay the assessment process. Client B started the assessment with one OT, who was five months pregnant and off for maternity leave three months later. After that, another OT came out to re-assess the client, which took another several months. Thirdly, the OT worked part-time which caused delays in the assessment process. As an OT just worked for certain days, she was always fully booked in the week and the client always had to wait for another week when he needed to be seen. Besides, a lengthy wait of 96 days was also evident in the installation of the external ramp. The major problem with this was the supplier, who did not provide the ramp within ten weeks. Without the equipment, the contractor could not carry out any In this case, the longest waiting times occurred at the assessment stage and the installation stage, which accounted for 81.4% of the total time. Client B experienced a significant delay in accessing the OT assessment. There was an unacceptable wait of 402 days, causing by a couple of factors. First, due to deterioration of health condition, the client was taken to hospital twice and stayed for a total of 10 weeks during the assessment process. Each hospital stay had resulted in the assessment being suspended until the OT was informed to resume the work. Secondly, poor arrangement and cooperation between different OTs was reported to delay the assessment process. Client B started the assessment with one OT, who was five months pregnant and off for maternity leave three months later. After that, another OT came out to re-assess the client, which took another several months. Thirdly, the OT worked part-time which caused delays in the assessment process. As an OT just worked for certain days, she was always fully booked in the week and the client always had to wait for another week when he needed to be seen. 3.2.2. Case Two 3.2.2. Case Two Client B was a man of about 75 years of age, living in a detached house where he and his wife had lived for around twenty years. Since his wife passed away three years earlier, client B had problems with his legs; his mobility deteriorated and went from using a walking stick to sitting in a wheelchair. To get into and out of his home, he used a lift that carried his wheelchair up and down Client B was a man of about 75 years of age, living in a detached house where he and his wife had lived for around twenty years. Since his wife passed away three years earlier, client B had problems with his legs; his mobility deteriorated and went from using a walking stick to sitting in a wheelchair. To get into and out of his home, he used a lift that carried his wheelchair up and down the stairs at 8 of 16 Int. J. Environ. Res. Public Health 2019, 16, 192 the main entrance door. He had applied for grants for the installation of an external ramp in order to exit the house on his own and participate in social activities. Furthermore, as he could no longer manage to get into the bathtub, he had applied for grants for remodelling the bathroom to install a shower unit. Client B was initially referred by his doctor to the social work department on 10 April 2014 and five weeks later, he received a letter from the local authority that acknowledged receipt of his referral. On 26 May 2014, he received another letter concerning a firm date for the OT’s first visit. On 3 June 2014, the OT visited his house. Thereafter, the process seemed to have stalled until 10 July 2015 when the case was passed to C&R. During this period, of more than one year, the client spent time in a hospital twice because of health problems, with the first stay for three weeks and the second for seven weeks. When the case did eventually arrive at C&R, on that very same day a C&R officer visited the client to explain the process, describe the building work and provide information needed for the funding application. When plans and specifications for adaptations were ready, the technical officer invited contractors to the client’s house for tenders. 3.3.1. Insufficient Resources The analysis of timelines indicated that it took an average of 6 months to deliver an adaptation and that delays could occur at any stage of the provision chain. In fact, 81.7% of the survey respondents believed that their clients frequently or sometimes experienced delays in the adaptation process. These delays were connected to a range of factors. First, the combination of unanticipated high demand and limited available resources, including finance and staff, was one main cause for delays in providing adaptations: Lack of funding had led to DFG cases being held back—at the end of the financial year, this can be up to 8–12 weeks delay before grant being approved. (a grant officer) Not enough staff to deal with delivering adaptations, which means there is a waiting list, approximately 16 months at present. (a housing officer) The second case study showed that it was crucial to provide adequate supply of OTs; relying on one part-time OT alone could delay the assessment process. This was also confirmed by a policy officer and a housing officer: The second case study showed that it was crucial to provide adequate supply of OTs; relying on one part-time OT alone could delay the assessment process. This was also confirmed by a policy officer and a housing officer: There are huge variations in the number of occupational therapists per population in each area. The waiting lists for assessment vary considerably. There are huge variations in the number of occupational therapists per population in each area. The waiting lists for assessment vary considerably. The main issue with adaptations in our area is the time it takes for social services to provide an OT report. If we had more OTs, it would speed up the process considerably and we could then extend help to more people. The main issue with adaptations in our area is the time it takes for social services to provide an OT report. If we had more OTs, it would speed up the process considerably and we could then extend help to more people. These delays could impact the client’s ability to live independently and increase the need for residential care, leading to a waste of public resources [46,47]. For example, in one case, the installation of a stairlift took 18 months at a cost of £2700. 3.2.2. Case Two 3.2.2. Case Two Besides, a lengthy wait of 96 days was also evident in the installation of the external ramp. The major problem with this was the supplier, who did not provide the ramp within ten weeks. Without the equipment, the contractor could not carry out any installation work. As a result, the case was put on hold and there was a ten-week delay in installing the ramp. Another issue was to obtain a building warrant for installation of the external ramp, leading to delays of up to Int. J. Environ. Res. Public Health 2019, 16, 192 9 of 16 four weeks. Furthermore, the client complained about the long waiting time when his doctor referred him to the hospital clinic who then made referral to the specialist in the social work. four weeks. Furthermore, the client complained about the long waiting time when his doctor referred him to the hospital clinic who then made referral to the specialist in the social work. 3.3. Main Causes of Delays 3.3.1. Insufficient Resources During this time, the applicant used 5 h of additional home care every week costing £3850 in total [48]. The Audit Commission further calculated that one year’s delay in providing an adaptation to a client costed up to £4000 for extra home care [49]. Therefore, it is essential to bring in sufficient resources to tackle delays in the adaptation provision, as suggested by a housing officer and a social worker: gg y g More money and more staff to deal with adaptations quicker so the client is not waiting as long as they currently are doing. Resources are always the key. When we had more staff, DFG was delivered within the 10 weeks using 4 full-time officers. Current circumstances in the local authority have resulted in a change; procurement is in place and times are around 20 weeks with just 1.7 officers. 3.3.3. Bureaucratic Procedures Therefore, there is a need for central government to review the legal framework governing the provision of grants and empower local authorities to be more flexible in carrying out housing adaptations. For example, service providers may be allowed to carry out adaptations first for urgent cases and to complete the paperwork retrospectively, as suggested by a C&R manager: Therefore, there is a need for central government to review the legal framework governing the provision of grants and empower local authorities to be more flexible in carrying out housing adaptations. For example, service providers may be allowed to carry out adaptations first for urgent cases and to complete the paperwork retrospectively, as suggested by a C&R manager: The hospital will discharge the client when we get the adaptation done. If we can get the adaptation done and then follow up with the paperwork, the client can get out of hospital more quickly. Not for every single one, only for the high priority cases, the big ones. 3.3.2. Lack of Joint Work It was quite common to find that three or more organisations working together to deliver an adaptation job. Ineffective joint work between these partner organisations at different stages was reported as a potential hazard to the successful service delivery. An OT pointed out: Sometimes we didn’t get enough information from social workers. Delays generally occur during peaks in the number of referrals. Such complaints became more frequent when the adaptation process spread over more than one local authorities, as reported by a housing officer: Such complaints became more frequent when the adaptation process spread over more than one local authorities, as reported by a housing officer: OT in the county council has to shut their cases down once it is passed to the district council. If the case has any question or changes, we have to request to reopen the case again in the county council. It takes time as it could be a different OT to deal with the case. This disconnection was also found in the second case study, in which the OT did not pass the case to C&R soon after assessment, resulting in the client had to wait for nearly two months. This was confirmed by a HIA officer: Int. J. Environ. Res. Public Health 2019, 16, 192 10 of 16 We know until the cases come to us from OTs. Apart from that, we don’t have details or would not be told what we will receive. So we don’t know who has been assessed and is on the waiting list, we just do what tell us. We know until the cases come to us from OTs. Apart from that, we don’t have details or would not be told what we will receive. So we don’t know who has been assessed and is on the waiting list, we just do what tell us. It is clear that the lack of partnership working can lead to unnecessary delays in delivering housing adaptations. In addition, poor communication and ineffective arrangement can withhold the process. In the second case, because the second OT did not collaborate with the first OT before she took maternity leave, Client B had two assessments that took a number of months and resulted in delays of over one year during the assessment stage. 3.3.3. Bureaucratic Procedures Some delays were the symptom of bureaucratic procedures and excessive paperwork, such as the landlord’s consent and planning permission. Any kind of adaptation in the private rented sector, no matter how minor, could not be carried out until receiving the landlord’s permission. The process was described by administrative staff as lengthy but necessary: We have to contact the landlords and get their approvals for the building work. Some landlords are v ast and good, the clients can get the letter within a week. But in some cases, it probably takes two or three w In the case of structural changes to a property, planning permission must be obtained before an adaptation could go ahead. These additional procedures are more time-consuming and expensive, as commented by a C&R officer: When a client stays in hospital, it costs around £4000 a week. If the client needs a shower adaptation and we can get it done in two working weeks, the adaptation will cost roughly £3500 and the hospital stay will cost £8000. But if we follow the legal procedures, it could be 6, 8, 10, 12 weeks. If we say 10 weeks, that is £40,000, minimum. This was also evidenced in both case studies; Client A waited for approximately six weeks to receive the building warrant while Client B for four weeks. Likewise, as these bureaucratic procedures take place during funding approval and installation, the survey found that the two stages were where the main blockages occurred in the adaptation process, with the longest waiting time of 139 days in Category I, 211 days in Category II and 227 days in Category III. Because these are legal requirements, housing officers felt completely helpless about the time taken for them: I find that the legal requirement for planning consent is annoying as it extends the process by several weeks. In addition, these legal procedures placed a particular restriction to what can be achieved as they must be adhered to, as reported by a housing officer: There is a reluctance to move away from the legal framework of the mandatory grant. The attendant bureaucracy adds delays. Attempts to develop “fast track” schemes fail due to fears that non-mandatory grant scheme will fail to get funding via Communities and Local Government. 3.3.4. Gap between Grant and Cost The need for applicants to make extra financial contributions to cover the difference between the amount of grants they received from local authorities and the total cost of their adaptations can also delay the process from funding to installation [30]. Normally mandatory grants (e.g., DFGs) are issued subject to a means test and a maximum grant limit—that is, clients, who have certain earning/saving, or need adaptations costing above the upper limit, would be asked to pay for any works in excess of their grants. When clients have any difficulty to make their contribution towards the whole and part of the cost, the funding process would break down and a delay occurs. The survey showed that the Int. J. Environ. Res. Public Health 2019, 16, 192 11 of 16 longest average waiting time was at the funding approval stage. A housing officer and a grant officer also pointed out: longest average waiting time was at the funding approval stage. A housing officer and a grant officer also pointed out: There are more difficulties when clients have to pay for the 20% of the cost; they have to find charitable funding to assist at times, resulting in delays to the delivery of adaptation works. So the time taken to find the top-up funding needs a couple of months. This will delay the process. A delay in raising the additional funding might trigger a second delay caused by price inflation or might lead to early closure of the case without any adaptation being done. As noted by a local authority in Perry’s study, approximately 25% of the cases, with DFGs granted, did not complete due to the lack of client’s contribution [47]. 3.3.5. Shortage of Reliable Contractors The survey revealed that the two stages of funding and installation were major barriers to efficiency of the adaptation provision. The major source of the longest waiting time, between funding approval and installation, was reaching the agreement of the schedule of work and getting contractors engaged and then finishing the job. Sometimes, it was unacceptably slow to finalise the specifications of an adaptation and to secure a contractor for carrying out the work, as complained by a grant officer: The process takes for too long. The process would be easier and more efficient if we can build up the speed in doing drawings, putting on to tender and starting the installation. In some local areas, finding a reliable contractor was difficult and time-consuming: One of the main delays in the system is the lack of availability of builders to do the work. (a housing To help clients get the requisite number of quotes in a timely manner, 70.9% local authorities kept an approved list of contractors. Those, who have not yet compiled such a list, should be encouraged to produce it in order for clients to identify suitable contractors quicker and speed up the installation process: Maximise availability of contractors to undertake works, therefore minimising waiting time for work to start on site. (a housing officer) Delays were frequently seen after the contractor had started the adaptation work on site. They might be caused by any of the following: lack of materials/equipment, shortage of skilled laborers, or delay of interim payments [30,50]. For example, in the second case study, the installation process was delayed for ten weeks because the contractor’s supplier failed to provide the external ramp. This isolated the client from any social or community activities and left him at risk of injury or harm, as complained by the older person: I was unhappy with this supply, it took 10 weeks and should be here earlier. That made me worse, I cannot go outside to see my family and visit my friends. Often clients tended to choose the lowest tenders, who may not be the right contractor for a speedy completion. A C&R officer said: Normally there are two quotes, the grant is based on the lowest quote and most clients go for the lowest one. The lowest quote, unfortunately, takes the longest time to get this done. 4. Discussions Waiting time has been identified as a key benchmark against which effectiveness of adaptation provision is assessed [29]. In practice, most local authorities record the timelines across key stages of the adaptation process. Their records, however, varied substantially. The whole process is broken down by different authorities into different stages. This made comparison in terms of service efficiency across local councils difficult. Without such a comparison, it is almost impossible to benchmark service performance and to produce a more efficient system. Therefore, there should be a uniform procedure to record delivery times for all the steps of the adaptation process across all local authorities. More accurate time recording can help to improve performance. This is also found by this survey, local councils who recorded waiting timelines for all five stages, those in Category I, delivered quicker adaptation services than those who did not, councils in Category II and III. Although almost all local authorities responded to the timelines question, some had provided partially completed answers. The area with the most omissions was details from referral to assessment, as information on these stages was held by different departments within one local council or across different councils. This showed one of the flaws of the current system that partner organisations within one authority or across different authorities did not have a shared database for adaptation provision. On the other hand, strong links between different stages of the provision chain are the key to an efficient and seamless service [26]. If one partner is unable to access all the necessary data from other partners within a local authority or from another authority, as was the case for some of the survey respondents, it is difficult to capture what is happening in the adaptation delivery system and how to improve the service performance [27]. The joint working arrangement has a significant impact on the waiting time between the process stages. Therefore, it is essential for local authorities to develop a shared system and a high standard of coordination, which will enable all the partners to process cases quickly and to minimise the negative impact of the fragmented service delivery. All stages form an integral part of the sequential adaptation process; each stage must be completed before the next can begin [50]. 3.3.6. Clients’ Decisions Another major delay factor was the client’s own decisions. In principle, the decision about when to start the building work remained in the hands of the client. The process was often delayed for weeks, or even months, when a client took control of the progress, as highlighted by a housing officer and a social worker: The council operates an application process which affords the applicant with as much control as possible over the destiny of their application. While this can at times present delays in the system it leaves maximum control with the client. You will be surprised by a number of people who just take for ever to get the ramp or shower done. You would think that they will do it straight away, but they don’t. Why? No idea. 12 of 16 Int. J. Environ. Res. Public Health 2019, 16, 192 Even worse, after holding up the process for a long period of time, some clients might decide not to go ahead with their adaptation, as pointed out by a C&R officer: The clients have the choice, they can turn around and say I don’t want it, even the grant is approved and everything is ready. Some clients turned down the council or agency’s help and spent more time to appoint their own contractor, as reported by a housing officer: There can be a time delay between assessments and the work being carried out due to the selection and appointment of contractors to carry out work which owners are involved in. In addition, there might be further delays when the client’s own chosen contractor lacks relevant skills and experience to undertake the adaptation work: When applicants arrange their own works, we have, on occasion, concerns about the quality of the work of their contractors. They tend to take longer than us to organise from start to finish. (a housing officer) 4. Discussions p p p g The survey showed that there were significant variations in the waiting time not only within each stage but also between stages across local authorities. Within one local authority, there are equally big variations between different cases and adaptation types. Such variability was experienced by the older clients of the two cases studies, even though they were within the same local authority and had their adaptations within approximately the same period of time (i.e., 2013 to 2015). The major blockage in the first case occurred at the stage of funding approval; while in the second case the main delay was at the assessment stage. Although C&R helped both clients with preparing all the information, applying for grants and supervising the building work, there were still significant delays between funding and installation. Notably, because of some factors, including the client’s ten weeks of hospital stay, lack of collaborative work between the two OTs, and the OT working on a part-time basis, the second client had to wait for more than one year for his assessment to be completed. This was an incredibly long wait, indicating that the effectiveness of OTs, although improved to some extent, still needed to be strengthened. Similar to the survey results, the social work department took more than one month to allocate the two cases for assessments, leading to overall delay. Despite these variations, an analysis of timelines showed the patterns of waiting times across the adaptation process and weak links between the stages from initial referral to work completion. Improvement is needed in all main aspects of housing adaptation, including referral management, joint work, funding authorisation and installation process, in order to provide a more effective and efficient service. There is a wide variety of reasons for delays in delivering adaptations. A common root cause stemmed from a lack of resources, as not enough money and staff were allocated to keep up with the increased demand, as found in this study as well as other research, such as Bibbings et al. [38], Jones [31], Mackintosh and Leather [32]. Additional resources are required to strengthen the capacity of local authorities to provide adaptations. As the adaptation process is administered by multiple departments and organisations, disconnections between them often create unnecessary delays. 4. Discussions When a blockage occurs at one stage, the whole process breaks down and the client cannot receive their adaptation in a timely manner [28,51]. To improve the efficiency of the adaptation process, it is necessary to identify the existing weak links in the provision chain, or the stages where the waiting time is long and delays are frequent [29]. According to the survey, the average waiting time for each stage was quite high; delays were frequently found at different stages. The longest waiting time was found during the funding stage and the installation stage, accounting for over half of the total waiting days. On the other hand, the lowest level of waiting occurred at the case allocation stage and assessment was also undertaken within a relatively short space of time. This indicates that the assessment process, which traditionally had longer waiting time [31,46], has been streamlined considerably. Finally, the wait time from the initial request to case allocation was comparatively high. 13 of 16 Int. J. Environ. Res. Public Health 2019, 16, 192 Overall, the time taken to complete an adaptation was still unacceptably long; clients had to wait for months, or even years, before their adaptations were delivered. To reduce the waiting time and ensure a smooth process flow, waiting time targets for each key stage of the process from referral to completion had been proposed by Clayton and Silke [30] and Audit Scotland [52]. This proposal had set off a heated debate, which was also reflected in the survey. Some officers believed that setting timescale for the adaptation process and its stages was the most effective way of avoiding delays and waiting times. However, others argued that setting timescales might speed up the process but bring down the service quality. Such an argument would not be valid if the time for completing each key stage is set reasonably and realistically. In fact, a clear timeline for the process enables all partners to schedule their tasks and complete them in time. The survey also showed that councils in Category I who recorded the time between each key stage completed the adaptation process much faster than other councils in Category II and III. Therefore, introducing a reasonable waiting time for each stage is important to produce an effective process and to minimise waiting time. 4. Discussions To achieve a seamless service process, it is important to ensure that all partners within a local authority or across different authorities have real collaborative working. If an adaptation is required for a rented property or it affects a building’s structure, it is necessary to get landlord permission or planning permission. Also, due to the mandatory nature of adaptation grants, there has to be a means test for all applications, except for those from children or young people. Going through these inevitable legal procedures often results in an extended period of time. There is a need to review the legal framework governing the provision of grants and allow local authorities more flexibility in carrying out housing adaptations. Importantly, when funding is authorised, there are still delays while decisions are made by the client on how and when to carry out the work. Delays are more common when clients are directly involved in the selection and appointment of a contractor, as they are often inexperienced to select competent contractors. It requires a clear guidance to make effective involvement of service users who could be in good control of their adaptation. Int. J. Environ. Res. Public Health 2019, 16, 192 14 of 16 14 of 16 Although this study contributes to a better understanding of waiting times and causes of delays across the key stages of the adaptation process, there are some limitations. First, it proved to be a real challenge in recruiting all local authorities to the survey and obtaining a high response rate, as staff responsible for providing adaptations always face overwhelming caseloads and participation in research is not their priority. Therefore, data were only collected from less than a third of the councils; and caution is required when generalising the research findings. Secondly, although the researchers adopted measures to maximise validity and reliability of the interview data, there are always potential biases on the interpretation of open questions and the discussion of some aspects. Finally, due to time constraints, the numbers of interviews and case studies were relatively small. Further investigation should be undertaken to get a more complete picture of the adaptation practice in the UK. 5. Conclusions This study investigated the timelines for the delivery of housing adaptations in local authorities across the UK. Overall, the average waiting time for the whole adaptation process from referral to completion was unacceptably long, with significant delays occurring at all stages, especially during funding approval and installation. There was a lack of consistency with wide variations in waiting times for different stages both within a local authority and across different authorities. Main factors of delays include limited resources, ineffective partnership, bureaucratic procedures, funding gap between grant and cost, lack of skilled contractors and the client’s decisions. Moving forward, extra resources including funding and staff are needed to meet the rising demand for adaptations from an aging population. Close coordination between all partners and a clear timeline for each stage are also needed to ensure a quicker and responsive service. It is also important to review the legal framework and its bureaucratic procedures; local authorities should have more flexibility in preparing all paperwork and delivering adaptation services. Author Contributions: All of the authors contributed to the concept and design of the study and approved the final manuscript version. More specifically, W.Z. organised data collection and analysis, and also drafted and revised the manuscript for submission. A.S.O. and M.S. supervised the project, provided expert advice and critically revised this publication. Funding: This research received no external funding. Funding: This research received no external funding. Acknowledgments: The authors would like to thank Care and Repair Scotland, local authorities across England, Scotland and Wales, and other research participants who shared their time and experiences. Conflicts of Interest: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Conflicts of Interest: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. 7. Means, R. Safe as houses? Ageing in place and vulnerable older people in the UK. Soc. Policy Adm. 2007, 41, 65–85. [CrossRef] References [CrossRef] 15 of 16 Int. J. Environ. Res. Public Health 2019, 16, 192 8. Pettersson, C.; Slaug, B.; Granbom, M.; Kylberg, M.; Iwarsson, S. Housing accessibility for senior citizens in Sweden: Estimation of the effects of targeted elimination of environmental barriers. Scand. J. Occup. Ther. 2017, 1–15. [CrossRef] [PubMed] 9. Renaut, S.; Ogg, J.; Petite, S.; Chamahian, A. Home environments and adaptations in the context of Ageing Soc. 2015, 35, 1278–1303. [CrossRef] 10. Sixsmith, J.; Sixsmith, A.; Fänge, A.M.; Naumann, D.; Kucsera, C.; Tomsone, S.; Haak, M.; Dahlin-Ivanoff, S.; Woolrych, R. Healthy ageing and home: The perspectives of very old people in five European countries. Soc. Sci. Med. 2014, 106, 1–9. [CrossRef] 11. Thordardottir, B.; Chiatti, C.; Ekstam, L.; Fänge, A.M. Heterogeneity of characteristics among housing adaptation clients in Sweden—Relationship to participation and self-rated health. Int. J. Environ. Res. Public Health 2016, 13, 91. [CrossRef] 12. Haak, M.; Ivanoff, S.D.; Fänge, A.; Sixsmith, J.; Iwarsson, S. Home as the locus and origin for participation: Experiences among very old Swedish people. OTJR 2007, 27, 95–103. [CrossRef] 13. Pynoos, J.; Nishita, C.; Perelma, L. Advancements in the home modification field: A tribute to M. Powell Lawton. J. Hous. Elder. 2003, 17, 105–116. [CrossRef] 14. Sanford, J.A. Universal Design as a Rehabilitation Strategy: Design for the Ages; Springer: Salmon Tower Building, NY, USA, 2003. 15. Chiatti, C.; Iwarsson, S. Evaluation of housing adaptation interventions: Integrating the economic perspective into occupational therapy practice. Scand. J. Occup. Ther. 2014, 21, 323–333. [CrossRef] [PubMed] 16. Hwang, E.; Cummings, L.; Sixsmith, A.; Sixsmith, J. Impacts of home modifications on ageing-in-place. J. Hous. Elder. 2011, 25, 246–257. [CrossRef] 17. Stark, S. Home modifications that enable occupational performance. In Using Environments to Enable Occupational Performance; Letts, L., Rigby, P., Eds.; SLACK Incorporated: Thorofare, NJ, USA, 2003; pp. 220–225. 18. Fänge, A.; Iwarsson, S. Changes in ADL dependence and aspects of usability following housing adaptation—A longitudinal perspective. Am. J. Occup. Ther. 2005, 59, 296–304. [CrossRef] [PubMed] 19. Gitlin, L.N. Conducting research on home environments: Lessons learned and new directions. Gerontologist 2003, 43, 628–637. [CrossRef] [PubMed] 20. Lawton, M.P.; Nahemow, L. Ecology and the aging process. In The Psychology of Adult Development and Aging; Eisdorfer, C., Lawton, M.P., Eds.; American Psychological Association: Washington, DC, USA, 1973; pp. 619–674. 21. Lien, L.L.; Steggell, C.D.; Iwarsson, S. References 1. Cho, H.Y.; MacLachlan, M.; Clarke, M.; Mannan, H. Accessible home environments for people with functional limitations: A systematic review. Int. J. Environ. Res. Public Health 2016, 13, 826. [CrossRef] [PubMed] 1. Cho, H.Y.; MacLachlan, M.; Clarke, M.; Mannan, H. Accessible home environments for people with functional limitations: A systematic review Int J Environ Res Public Health 2016 13 826 [CrossRef] [PubMed] limitations: A systematic review. Int. J. Environ. Res. Public Health 2016, 13, 826. [CrossRef] [PubMed] 2. Kylén, M.; Ekström, H.; Haak, M.; Elmståhl, S.; Iwarsson, S. Home and health in the third age—Methodological background and descriptive findings. Int. J. Environ. Res. Public Health 2014, 11, 7060–7080. [CrossRef] [PubMed] 2. Kylén, M.; Ekström, H.; Haak, M.; Elmståhl, S.; Iwarsson, S. Home and health in the third age—Methodological background and descriptive findings. Int. J. Environ. Res. Public Health 2014, 11, 7060–7080. [CrossRef] [PubMed] 7060–7080. [CrossRef] [PubMed] 3. Frank, J.B. The Paradox of Aging in Place in Assisted Living; Bergin & Garvey: Westport, CT, USA, 2002. 3. Frank, J.B. The Paradox of Aging in Place in Assisted Living; Bergin & Garvey: Westport, CT, USA, 200 . Frank, J.B. The Paradox of Aging in Place in Assisted Living; Bergin & Garvey: Westport, CT, USA, 2002. 4. Wiles, J. Conceptualizing place in the care of older people: The contributions of geographical gerontology. J. Clin. Nurs. 2005, 14, 100–108. [CrossRef] [PubMed] 4. Wiles, J. Conceptualizing place in the care of older people: The contributions of geographical gerontology. J. Clin. Nurs. 2005, 14, 100–108. [CrossRef] [PubMed] 5. Farber, N.; Shinkle, D.; Lynott, J.; Fox-Grage, W.; Harrell, R. Aging in Place: A State Survey of Livability Policies and Practices; AARP Public Policy Institute: Washington, DC, USA, 2011. 5. Farber, N.; Shinkle, D.; Lynott, J.; Fox-Grage, W.; Harrell, R. Aging in Place: A State Survey of Livability Policies and Practices; AARP Public Policy Institute: Washington, DC, USA, 2011. 6. Sixsmith, J. The meaning of home: An exploratory study of environmental experience. J. Environ. Psychol. 1986, 6, 281–298. [CrossRef] 6. Sixsmith, J. The meaning of home: An exploratory study of environmental experience. J. Environ. Psychol. 1986, 6, 281–298. [CrossRef] 7. Means, R. Safe as houses? Ageing in place and vulnerable older people in the UK. Soc. Policy Adm. 2007, 41, 65–85. [CrossRef] 7. Means, R. Safe as houses? Ageing in place and vulnerable older people in the UK. Soc. Policy Adm. 2007, 41, 65–85. References Adaptive strategies and person-environment fit among functionally limited older adults aging in place: A mixed methods approach. Int. J. Environ. Res. Public Health 2005, 12, 11954–11974. [CrossRef] [PubMed] 22. Lawton, M.P. The elderly in context: Perspectives from environmental psychology and gerontology. Environ. Behav. 1985, 17, 501–519. [CrossRef] 23. Wahl, H.W.; Iwarsson, S.; Oswald, F. Aging well and the environment: Toward an integrative model and research agenda for the future. Gerontologist 2012, 52, 306–316. [CrossRef] 24. Mandelstam, M. Home Adaptations: The Care Act 2014 and Related Provision across the United Kingdom; College of Occupational Therapists Ltd.: London, UK, 2016. 5. Morgan, D.J.; Boniface, G.E.; Reagon, C. The effects of adapting their home on the meaning of home families with a disabled child. Disabil. Soc. 2016, 31, 481–496. [CrossRef] 26. Ramsay, M. Adapting for a Lifetime: The Key Role of Home Improvement Agencies in Adaptations Delivery; Foundations: Derbyshire, UK, 2010. 27. Zhou, W.; Oyegoke, A.S.; Sun, M. Service planning and delivery outcomes of home adaptations for ageing in the UK. J. Hous. Built Environ. 2017, 1–19. [CrossRef] 28. Bradford, I. The adaptation process. In Housing Options for Disabled People; Bull, R., Ed.; Jessica Kingsley: London, UK, 1998; pp. 78–114. 29. Hall, E.; Scottish Work Services Inspectorate. Equipment and Adaptation Services in Scotland: A Survey of Waiting Times for Social Work Provision; Scottish Executive Central Research Unit: Edinburgh, UK, 2001. 30. Clayton, V.; Silke, D. Evaluation of the Housing Adaptation Grant Schemes for Older People and People with a Disability; Housing Agency: Dublin, UK, 2010. Int. J. Environ. Res. Public Health 2019, 16, 192 16 of 16 16 of 16 31. Jones, C. Review of Housing Adaptations Including Disabled Facilities Grants—Wales; Welsh Government: Cardiff, UK, 2005. 32. Mackintosh, S.; Leather, P. The Disabled Facilities Grant: Before and after the Introduction of the Better Care Fund; Foundations: Derbyshire, UK, 2016. 33. Adaptation Working Group. Adapting for Change; Scottish Government: Edinburgh, UK, 2012. 34. Department for Communities and Local Government. Lifetime Homes, Lifetime Neighbourhoods; DCLG Publications: London, UK, 2008. 35. Scottish Government. Age, Home and Community: A Strategy for Housing for Scotland’s Older People: 2012–2021; Scottish Government: Edinburgh, UK, 2011. 36. Welsh Government. The Strategy for Older People in Wales 2013–2023—Living Longer, Aging Well; Welsh Government Publications: Cardiff, UK, 2013. 37. Boniface, G.; Mason, M.; Macintyre, J.; Synan, C.; Riley, J. References The effectiveness of local authority social services’ occupational therapy for older people in Great Britain: A critical literature review. Br. J. Occup. Ther. 2013, 76, 538–547. [CrossRef] 38. Bibbings, J.; Boniface, G.; Campbell, J.; Findlay, G.; Reeves-McAll, E.; Zhang, M.; Zhou, P. A Review of Independent Living Adaptations; Welsh Government: Cardiff, UK, 2015. 9. Kempton, O.; Warby, A. Measuring the Social Return on Investment of Stage 3 Adaptations and Very Shelt Housing in Scotland; Envoy Partnership: London, UK, 2012. 40. Creswell, J.W. Research Design. Qualitative, Quantitative, and Mixed Methods Approaches, 2nd ed.; Sage Publications, Inc.: Thousand Oaks, CA, USA, 2003. 41. Pettersson, C.; Löfqvist, C.; Malmgren Fänge, A. Clients’ experiences of housing adaptations: A longitudinal mixed-methods study. Disabil. Rehabil. 2012, 34, 1706–1715. [CrossRef] [PubMed] 42. Schwingel, A.; Gálvez, P.; Linares, D.; Sebastião, E. Using a mixed-methods re-aim framework to evaluate community health programs for older Latinas. J. Aging Health 2016, 4, 551–593. [CrossRef] [PubMed] 42. Schwingel, A.; Gálvez, P.; Linares, D.; Sebastião, E. Using a mixed-methods re-aim framework to evaluate 43. Teddlie, C.; Yu, F. Mixed methods sampling: A typology with examples. J. Mix. Methods Res. 2007, 1, 77–100. [CrossRef] 44. Connell, J.; Page, S.J.; Bentley, T. Towards sustainable tourism planning in New Zealand: Monitoring local government planning under the Resource Management Act. Tour. Manag. 2009, 30, 867–877. [CrossRef] 45. Davies, K.; Bullock, M.; Brandon, A.; Wainman, K.; Craig, L.; Fletcher, P.; Duncan, A. A Study of the Housing and Support Needs of Older People in Herefordshire; Peter Fletcher Associates Ltd.: Northumberland, UK, 2012. 46. Heywood, F.; Gangoli, G.; Langan, J.; Marsh, A.; Moyers, S.; Smith, R.; Sutton, E.; Hodges, M.; Hamilton, J. Reviewing the Disabled Facilities Grant Programme; Office of the Deputy Prime Minister: London, UK, 2005. 47. Perry, F.C. Adaptation Works: How Disabled Facilities Grants Are the Overlooked Solution to the Accessible Housing Shortage and Associated Costs; Disability United: Warwickshire, UK, 2015. 48. Scottish Executive. Equipped for Inclusion: Report of the Strategy Forum: Equipment and Adaptations; Scottish Executive: Edinburgh, UK, 2003. 49. Audit Commission. Home Alone: The Role of Housing in Community Care; Audit Commission: London, UK, 1998. 50. Keeble, U. Aids and Adaptations; Bedford Square Press: London, UK, 1979. p q 51. Home Adaptations Consortium. Home Adaptations for Disabled People: A Detailed Guide to Related Legislation, Guidance and Good Practice; Care & Repair England: Nottingham, UK, 2013. 52. Audit Scotland. References Adapting to the Future—Management of Community Equipment and Adaptations; Audit Scotland: Edinburgh, UK, 2004. © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
https://openalex.org/W1999639533
https://hts.org.za/index.php/hts/article/download/131/212
English
null
Responsibility, God and society: The cry of the Other in the sacred texts as a challenge towards responsible global citizenship
HTS teologiese studies
2,009
cc-by
7,486
Original Research abstract The article seeks to respond to the question: What role can the sacred texts play in the construction of a Christian identity that is responsible to the Other in a pluralistic global world? The sacred texts of the Judaic-Christian tradition offer not only an understanding of the wholly otherness of God, but also form the basis of our understanding and perception of humanity (anthropology), the world and ourselves (personhood/identity). This understanding is constructed in the context of responding to the call of the wholly Other and the others. Identities are traditionally constructed through the identifi cation and exclusion of differences (otherness), thus leading to an ethic of exclusion and responsibility only to oneself/ourselves. Yet these identity-forming texts harbour a persistent otherness, which challenges these traditional identities by interrupting them with a call to responsibility toward the other. The otherness harboured in these texts takes various forms, namely: The otherness of the ancient world to our world, the otherness of the transcendental Other, and the otherness of the text itself, as there is always a différance that has not yet been heard. These various forms of otherness, of our identity-forming texts, deconstruct our identity constructions, thus calling us to a continuous responsibility towards the other. This call could form the basis of a Christian identity and ethic of global cosmopolitan citizenship that is always responding to the eschatological interruption by the other, who is not yet present or who has not been offered presence. Affi liations: 1Department of Practical Theology, University of Pretoria, South Africa Affi liations: 1Department of Practical Theology, University of Pretoria, South Africa 2Pastor of the Evangelisch-Luterische St Petersgemeinde Pretoria, South Africa Correspondence to: Johann-Albrecht Meylahn e-mail: jmeylahn@lantic.net Keywords: sacred texts; Christian identity; global citizenship; Christian anthropology; personhood and religious identity This article is available at: http://www.hts.org.za I will read this text from a narrative hermeneutical perspective, and thus remain within the text and not disappear behind the text to its social, textual and historical setting. This text I will read together with texts by three philosophers (Levinas, Ricoeur and Derrida). Although these three philosophers have very different interpretations of the other, they have had a tremendous impact on the contemporary debate about identity, responsibility and alterity (the other). By bringing these texts into dialogue with each other, new light might be shed on these contemporary questions concerning identity (citizenship) and responsibility (love) toward neighbour. Could this text, read in dialogue with contemporary philosophy, shed light on a possible new reading of sacred texts in which the question of identity is placed secondary to the question of responsibility towards the other, and thus offer the contemporary audience new possibilities of interpreting God and interpreting themselves as responsible toward the other in society? RESPONSIBILITY, GOD AND SOCIETY: THE CRY OF THE oTHER IN THE SACRED TEXTS AS A CHALLENGE TOWARDS RESPONSIBLE GLOBAL CITIZENSHIP TEXTS AS A C author: Johann-Albrecht Meylahn1,2 Affi liations: 1Department of Practical Theology, University of Pretoria, South Africa 2Pastor of the Evangelisch-Luterische St Petersgemeinde Pretoria, South Africa Correspondence to: Johann-Albrecht Meylahn e-mail: jmeylahn@lantic.net Keywords: sacred texts; Christian identity; global citizenship; Christian anthropology; personhood and religious identity Postal address: PO Box 14885, Lyttelton, 0140, South Africa Dates: Received: 11 Aug. 2008 Accepted: 18 Nov. 2008 Published: 21 Apr. 2009 How to cite this article: Meylahn, J-A., 2009, ‘Responsibility, God and society: The cry of the Other in the sacred texts as a challenge towards responsible global citizenship’, HTS Teologiese Studies/Theological Studies 65(1), Art. #131, 5 pages. DOI: 10.4102/hts.v65i1.131 This article is available at: http://www.hts.org.za note: This article is a re-worked paper delivered at the international conference ‘Responsibility, God and Society: Theological Ethics i Di l ’ h ld t th author: Johann-Albrecht Meylahn1,2 author: Johann-Albrecht Meylahn1,2 introdUction How to cite this article: Meylahn, J-A., 2009, ‘Responsibility, God and society: The cry of the Other in the sacred texts as a challenge towards responsible global citizenship’, HTS Teologiese Studies/Theological Studies 65(1), Art. #131, 5 pages. DOI: 10.4102/hts.v65i1.131 note: This article is a re-worked paper delivered at the international conference ‘Responsibility, God and Society: Theological Ethics in Dialogue,’ held at the Katholieke Universiteit Leuven, 7–10 May 2008. Is it possible in the Christian faith community to re-read these sacred texts, but with an awareness of otherness and responsibility towards otherness so that global cosmopolitan citizenship is interrupted by the continuous call of the other other, who is not yet heard, not yet fully present or who has not yet been offered hospitality within the cosmo-polis? © 2009. The Authors. Licensee: OpenJournals Publishing. This work is licensed under the Creative Commons Attribution License. introdUction HTS Teologiese Studies/Theological Studies Article #131 In this article I will seek to discover what role the sacred texts can play in the construction of a Christian identity that is responsible towards the other in a pluralistic global world. Worldwide, Christians currently are rediscovering the power of Scripture to shape and form their daily lives. Christian individual and collective identity, as well as praxis, is formed and shaped by Scriptures, as the Bible plays a vital role in shaping and infl uencing the contemporary audiences’ understanding of God, their identities and public ethos (Mouton 2004:3). How religious communities understand God, society and their responsibility is dependent on how they read their sacred texts. ese Studies/Theological Studies Article #131 Many religious communities are extremely exclusive and hostile towards others, and this hostility is often founded, condoned and perpetuated by a specifi c reading of the sacred texts of these communities. Is that the only possible reading of the sacred texts, or is there another reading that could construct identities that are open and responsible towards otherness? Dates: Received: 11 Aug. 2008 Accepted: 18 Nov. 2008 Published: 21 Apr. 2009 In the Christian canon there is a text that stands out with regard to these themes of God, identity and responsibility towards others, thus to society, namely Luke 10:25–37. In this text, the nomikos asks Jesus a question that has direct bearing on both our interpretation of God and the identity of the community. Jesus responds to this question about identity by telling a story in which the stranger (the other) calls us into an infi nite responsibility to love. This story elucidates the love we are called to have for our neighbour, as it is a story about responding to the cry of an other. Levinas (2006a:88) echoes this thought when he writes: ‘That is the responsibility for my neighbour, which is, no doubt, the harsh name for what we call love of one’s neighbor.’ This interpretation of love that Jesus offers in his story gives me the freedom in this article to use the terms love and responsibility interchangeably, or to use love interpreted as responsibility. I believe that such an interpretation would be in line with the tradition of Augustine and more specifi cally Kierkegaard’s interpretation of agapē or caritas as responding to the other without an expectation of return (Kierkegaard 1995). From text to responsibility In the Gospels, Jesus is often in conflict with the experts in the law because of questions concerning identity – the identity of God, the Messiah or the people of God. In the text, the entity in question is the religious community (those who love God and their neighbour) and the question seems to be concerned with the defining norm of this religious community. The nomikos asks the question: ‘Who is my neighbour?’ This question does not refer to any specific person, but is a question about a hypothetical third. For him it is not a question of nearness but, on the contrary, a question of limitation and exclusion, because responsibility toward neighbours must have a limit, as responsibility to all would destroy the self as an identity.2 Unlimited responsibility destroys the entity that is seeking to be responsible and therefore limits/norms/laws/definitions (nomos) have to be established to prevent such destruction of the entity or oikos.3 An individual cannot be responsible to all, neither can a home (oikos) offer hospitality to all as that would destroy the very conditions of hospitality, namely the home.4 I can offer hospitality/responsibility to another, but as soon as there is another other, namely a third, it is no longer just a question of hospitality/responsibility, but also a question of identity founded on the limitation of responsibility/hospitality. What is the limit of responsibility towards the other other (third) before I begin to lose my identity, my home? If the chosen of God are responsible and open to all (e.g. Samaritans), will they not lose their identity as the chosen people? Responsibility/ hospitality needs to be limited (normed) to protect the identity of the oikos, or identity will be lost. The task of the nomikos is to determine these limitations of responsibility to protect the identity of the entity, and defining these limitations could be the Grund of the question the nomikos is asking. The question of the nomikos is an oiko-nomic question. Identities are established on the Grund of the identification (nominating/naming) and exclusion (limitation) of differences. As soon as there is a law there is partition and thus limitation, and therefore exclusion: ‘as soon as there is nomy, there is economy’ (Derrida 1992:6). As soon as there is a norm/limit/definition of responsibility, there is economy (oiko-nomy) and thus identity. Identity is oikos- nomos (economic) – to define/norm the entity (oikos). From text to responsibility It is an expert in the law (nomikos), one who interprets and understands the law, who poses the question Vol. 65 No. 1 Page 1 of 5 27 HTS HTS http://www.hts.org.za (page number not for citation purposes) Original Research Meylahn This return might be numerous things – the return of what I gave (what I give I receive), or the return of a peaceful and harmonious oikos, or the return of an identity,6 in which case responsibility or love given to the other has as reward the constitution (reappropriation) of the self as an identity. The question of the nomikos is not really about responsibility/love to one other, but specifically to the third (the other other). It is clear to him that one should love one’s own people, those of the oikos. It is on the Grund of responsibility given or denied to the third that the identity of the oikos as society is given.7 As an expert of the law, his profession is to determine and to define and set the boundaries of sameness, and therefore the question about the neighbour is vitally important, for it is on the basis of the answer to that question that the identity of the community can be determined. Identities are traditionally constructed through the identification (nominating) of differences, thus leading to an ethic of exclusion and responsibility only to oneself/ ourselves. As soon as the limits of love and responsibility have been established, the conditions for self, home and society have also been established. The answer to the question, who is my neighbour (to whom am I responsible?) is the norm that establishes the oikos – the norm that is necessary to establish who is included and who is not within a given society. to Jesus, ‘Who is my neighbour (καὶ τίς ἐστίν μου πλησίον)?‘ This is odd, because as an expert in the nomos he is an expert in nominating and norming and, as such, he should have no problem in nominating who the neighbour is. Is there another Grund1 for his question? Every text is heterogeneous because there is différance, so one cannot discover a single Grund, but I would like to follow one of the many traces, namely the trace of this nomikos and why he asks such a question. A nomikos is concerned with the nomos. It is through norms and names that identities and entities are determined. 6.‘… a subject identical to itself and conscious of its identity, indeed seeking through the gesture of the gift to constitute its own unity and, precisely, to get its own identity recognized so that the identity comes back to it, so that it can reappropriate its iden- tity: as its property’ (Derrida 1992:11). 3.In this article I use the word oikos in a broader sense, which includes home, family, community, society, polis and self, as an identity that is at home within him/herself. 1.I use the German word Grund, because in it are contained at least two meanings that are important for this paper, namely Grund as ground, foundation, bottom, as well as Grund as the reason for something. 7.’Through the fact that the other [l’autre] is also a third part [tiers], in relation to an other who is also his neighbour (in society, one is never two but at least three), through the fact that I find myself before the neighbour and the third party, I must compare; I must weigh and evaluate’ (Levinas 2000:182–183). ‘The institutions of the state itself can be found on the basis of the third part’s intervening in the relationship of nearness’ (Levinas 2000:183). 2.‘Unlimited responsibility would amount to indifference, by overthrowing the ‘mine- ness’ of my action’ (Ricoeur 2005:109). 4.For further discussion on the aporia of hospitality see Derrida, J., 2000, Of Hospitality: Anne Dufourmantelle invites Jacques Derrida to respond, transl. Rachel Bowlby, Stanford University Press, Stanford. 5.’Nomos does not only signify the law in general, but also the law of distribution (nemein), the law of sharing or partition [partage], the law of partition (moira), the given or assigned part, participation’ (Derrida 1992:6). 10.‘Love your neighbour as you love yourself’ (Mt 22:39). From text to responsibility One has to be economic with one’s responsibility, in the sense of defining (norm/nomos)5 the norms and limits of the oikos. Before we leave the question of the nomikos looking for a norm to limit responsibility, let us turn to a modern nomination of this norm, namely the Kantian categorical imperative in its two formulations.8 The imperative seeks to nominate the limit of responsibility. Ricoeur compares the categorical imperative to the golden rule9 and has two main criticisms of the imperative. Firstly, that it subordinates human relations to the principle of autonomy, which states in a monological way the rule for the universalisation of maxims (Ricoeur 1995:294), and therefore Kant’s imperative does not thematically apply to a plurality of subjects, as it does not take cognisance of the ‘third’. The second criticism is that the second formulation of the imperative is addressed to humanity ‘that is identical in each person, not to persons as in fact multiple and different …’ (Ricoeur 1995:294). Ricoeur therefore believes that the golden rule is more suitable than the categorical imperative as a norm for society, as the imperative functions on the Grund of identity at the expense of the exclusion of otherness, which is the same Grund as that of the nomikos. Ricoeur turns to the golden rule as a norm for responsibility, which is comparable to the second part of the Great Commandment10 to which the nomikos responds by asking his question. In the golden rule and in the Great Commandment there is a close relationship between love/responsibility toward neighbour and the self (identity). Is the Grund for responsibility always about the economy (oikos-nomos) of self/oikos and must responsibility always be thought within the economy of identity, or is there another Grund? HTS Teologiese Studies/Theological Studies Article #131 1.I use the German word Grund, because in it are contained at least two meanings that are important for this paper, namely Grund as ground, foundation, bottom, as well as Grund as the reason for something. 2.‘Unlimited responsibility would amount to indifference, by overthrowing the ‘mine- ness’ of my action’ (Ricoeur 2005:109). 3.In this article I use the word oikos in a broader sense, which includes home, family, community, society, polis and self, as an identity that is at home within him/herself. 4.For further discussion on the aporia of hospitality see Derrida, J., 2000, Of Hospitality: Anne Dufourmantelle invites Jacques Derrida to respond, transl. Rachel Bowlby, Stanford University Press, Stanford. 5.’Nomos does not only signify the law in general, but also the law of distribution (nemein), the law of sharing or partition [partage], the law of partition (moira), the given or assigned part, participation’ (Derrida 1992:6). HTS Teologiese Studies/Theological Studies Article #131 Here there seems to be another Grund for responsibility, which is not identity, but alterity as otherness. However, this is impossible, as it would mean the end of the same (identity/ oikos), and because the supraethical as Grund is groundless and as such unthinkable.15 To make this love commandment (groundless Grund) thinkable as Grund, it needs to be placed within a new economy or a new identity, namely the economy of divine giving (Ricoeur 1995:293–302). ese Studies/Theological Studies Article #131 In our text, Jesus tells a story of a wounded stranger who is placed or given in the path of three people, unsolicited and unwanted, and as such he is given to them. He is passive, wounded, vulnerable and patiently awaiting a response, without awaiting anything in particular. Two pass by, ignoring this gift for the sake of their identity, for the sake of their oikos-nomos. The third who passes by is a stranger/foreigner himself and yet he responds by giving all he has to the other. Here a new Grund for responsibility, an uneconomic Grund, seems to be established – a Grund that is not based on identity or reciprocity, but on substitution, as he substitutes himself for the wounded other. Ricoeur places the golden rule into the context of the economy of divine giving. I can give to the other (love or responsibility), on the Grund that I have received from God. This is the Grund for responsibility toward the other as other. God has given and in response (in responsibility) I give to the other – I am responsible to the other. Responsibility toward the other is placed within the economy of the gift that is proclaimed in the narrative of God as Creator (original giver), Sustainer (continuous giver) and Giver of new life (Christ). After telling this story, Jesus reverses the question of the nomikos.17 It is no longer: ‘Who is my neighbour?’ but ‘Who was a neighbour to the man who fell amongst thieves?’. By turning the question around, Jesus establishes a different Grund for the norm of responsibility (love for neighbour), which is not identity. From responsibility to God an immanent economy (of my or our oikos), but is included in the transcendental economy of a gracious God. It is because I believe my life to be a gift from a gracious God that I can respond by giving love (being responsible) to others, even strangers and enemies. My/our identity no longer depends on the limitation of responsibility by defining others into neighbours/friends or strangers/enemies, but on the prior gift of God. Prior to my responsibility to another, God was and is responsible toward me and therefore I can be responsible toward strangers and enemies. The only way to think another/think of/think about another Grund is if this economy is broken open, and the only way this norm or economy can be broken open is by a true gift, namely a gift without a return or a gift beyond economy that can interrupt this economy. The gift, for Derrida, is essentially uneconomic and thereby breaks open the economy11 of the same with that which is utterly different and cannot be included.12 The other, as other, interrupts and disturbs identity as sameness with a foreignness that refuses to be included or reduced to the same. The only way to think another/think of/think about another Grund is if this economy is broken open, and the only way this norm or economy can be broken open is by a true gift, namely a gift without a return or a gift beyond economy that can interrupt this economy. The gift, for Derrida, is essentially uneconomic and thereby breaks open the economy11 of the same with that which is utterly different and cannot be included.12 The other, as other, interrupts and disturbs identity as sameness with a foreignness that refuses to be included or reduced to the same. The other as other thus functions like a gift. The other remains other and must remain other for the sake of his/her otherness, and as stranger the other seeks a response (responsibility), but without being included in the economy of the same, as she/he remains a stranger. g The other as other thus functions like a gift. The other remains other and must remain other for the sake of his/her otherness, and as stranger the other seeks a response (responsibility), but without being included in the economy of the same, as she/he remains a stranger. From responsibility to God This thinking is still economic in both senses of the word as it still concerns itself with norms and thus identity, and secondly with circularity and reciprocity. I can because God gave first (I give to the other and thereby indirectly give back to God). This leads us to the second part of the theme of the conference, namely God. Ricoeur finds in the supraethical of the love commandment that which can break open this economy, namely to love the other in their otherness, that is to love the enemy (that which can destroy the same). As discussed previously, the question of responsibility is in essence about preserving the identity from destruction by alterity. Ricoeur, in his search for another Grund, argues that the golden rule needs to be understood within the context of the supraethical of the love commandment.13 The supraethical is the only way for true movement from self towards the other as other. Ricoeur finds in the supraethical of Scripture the Grund for the universal norm (golden rule) of responsibility toward the other as other, which is beyond identity, and thus the golden rule needs to be interpreted in the light of the love commandment.14 Is God to be thought in such economic terms – as original giver (prime mover)? HTS Teologiese Studies/Theological Studies Article #131 or is there another Grund? Besides the values of home, division, distribution and partition, the idea of economy also implies the idea of exchange, circulation and return. Responsibility, limited and defined, is incorporated immediately into an economy of exchange and return. I ‘give’ my responsibility, my love, to an other in order to get a return. 8.The first formulation: ‘Act only according to that maxim by which you can at the same time will that it should become a universal law.’ Kant’s second formulation: ‘Act so that you treat humanity, whether in your own person or in that of another, always as an end and never as a means only.’ 9.The golden rule formulated negatively by Hillel: ‘Do not do to your neighbour what you would hate to have done to you.’ The golden rule formulated positively by Jesus in the two gospels – in the Sermon on the Mount: ‘In everything do to others as you would have them do to you; for this is the law and the prophets’ (Mt 7:12) and in the Sermon on the Plain: ‘Do to others as you would have them do to you’ (Lk 6:31). 10.‘Love your neighbour as you love yourself’ (Mt 22:39). 28 Vol. 65 No. 1 Page 2 of 5 HTS HTS http://www.hts.org.za (page number not for citation purposes) Original Research Responsibility, God and society 17.Luke 10:36: τίς τούτων τῶν τριῶν πλησίον δοκεῖ σοι γεγονέναι τοῦ ἐμπεσόντος εἰς τοὺς λῃστάς; Which of these three, do you think proved neighbour to the man who fell among the thieves? 15.If thinking is strictly bound to being and economy, it is impossible to think something that is groundless and beyond economy. 11.‘But is not the gift, if there is any, also that which interrupts economy? That which in suspending economic calculation, no longer gives rise to exchange? That which opens the circle so as to defy reciprocity or symmetry, the common measure, and so as to turn aside the return in view of the no-return?’ (Derrida 1992:7). 12.Not that it remains foreign to the circle, but it must keep a relation of foreignness to the circle, a relation without relation of familiar foreignness’ (Derrida 1992:7). 16.For further reflections on Levinas’s hermeneutic, see Annette Aronowicz’s Introduction in Nine Talmudic readings by Emmanuel Levinas, and Roger Burggraeve’s article, The Bible gives to thought: Levinas on the possibility and proper nature of biblical thinking. 13.‘This context [Sermon on the Mount], we know, is dominated by the commandment to love one’s enemies. It is this commandment, not the golden rule, that seems to constitute the expression closest, on the ethical plane, to what I have called the economy of the gift’ (Ricoeur 1995:300). 14.‘The commandment to love, according to this interpretation, brings about a conver- sion of the golden rule from its penchant for self-interest to a welcoming attitude toward the other. It substitutes for the ‘in order that’ of the do ut des the because of the economy of the gift: ‘Because it has been given to you, you can give in turn.’’ (Ricoeur 1995:300) ‘What is called ‘Christian ethics,’ or as I would prefer to say, ‘communal ethics as in a religious perspective,’ consists, I believe, in the tension between unilateral love [love commandment] and bilateral justice [golden rule], and in the interpretation of each of these in terms of the other’ (Ricoeur 1995:301). Is God to be thought in such economic terms – as original giver (prime mover)? 16.For further reflections on Levinas’s hermeneutic, see Annette Aronowicz’s Introduction in Nine Talmudic readings by Emmanuel Levinas, and Roger Burggraeve’s article, The Bible gives to thought: Levinas on the possibility and proper nature of biblical thinking. 17.Luke 10:36: τίς τούτων τῶν τριῶν πλησίον δοκεῖ σοι γεγονέναι τοῦ ἐμπεσόντος εἰς τοὺς λῃστάς; Which of these three, do you think proved neighbour to the man who fell among the thieves? From God to ethics or God-beyond-being Levinas has a different hermeneutical approach to the Scriptures and thus to God, namely to seek the universal in the particularity of Scripture rather than to make the particularity of Scripture universal. Levinas believes that the universal is hidden in the particularity of Scripture and that this universal needs to be wrested from the text and translated from Hebrew into Greek (the universal language).16 I will turn to this particular text to seek the universal, and thereby seek to elucidate some of Levinas’s arguments regarding responsibility toward other as other, thus discovering yet another possible Grund for responsibility that is beyond economy. e Studies/Theological Studies Levinas, in his reflections on religious identity (in his case Jewish identity), argues that true, intrinsic religious identity can only be established if the religious community learns to think the Scriptures.27 The sacred texts play an important role in the construction of identities within faith communities, as identities are shaped by the narratives of that community, which are founded largely on the sacred texts and which form the basis for praxis within society and for how we respond to the other. There is a storied relationship between the individual and his/her identity and the narratives of the faith community (Root 1989:266). To be human means to act intentionally, and the way one intends depends on how one attends to the world (Goldberg 1982:175). The narratives with which one interprets the world and oneself shape the way one attends to the world. This raises the question, Do we think the Scriptures? How do we think them? With what question do we read the sacred texts? Do we read these normative texts with the question of the nomikos, seeking clear boundaries and norms with which to establish our identity and interpret the world? Or do we read these texts as challenged by the story Jesus told, namely to read by understanding ourselves as called into responsibility by the other? For Levinas, God is a trace in the inescapable face of the other.23 ‘The ethical is not merely the corollary of the religious but is, in itself, the element in which religious transcendence receives its original sense’ (Levinas 1982:133). God is in the infinite inescapable responsibility toward the face of the other.24 Levinas argues that God signifies the other of being (Levinas 2000:124); in other words God is to be found in the otherwise than being, which is contrary to metaphysics and ontology, where meaning is only to be found in being. 18.‘But it is always starting out from the Face, from the responsibility for the other that justice appears …’ (Levinas 2006a:89). 19.‘…for the other [autrui], the neighbour is the first come’ (Levinas 2000:138) 20.‘This responsibility goes to the point of fission, all the way to the enucleation of the ‘me’. And therein lies the subjectivity of ‘me’’ (Levinas 2000:138). ‘It is by this supplementary responsibility that subjectivity is not the Ego [le Moi], but me [moi]’ (Levinas 2006b:68). From God-beyond-being to society It is obvious that one cannot live in such an ethical relation with all. How does the responsibility toward the other include the third (the other other)? The question of the third becomes a question of society, namely who is included in my/our responsibility and who is not. Levinas argues that as soon as a third appears, thinking and philosophy begins, as we need to weigh and evaluate. It is in the presence of the third that identity, oikos and societies, are formed and politics begins. This brings us back to the question of the nomikos: Who is my/our neighbour? It is in the moment the third appears that the me, who is the neighbour, is forced by the third to make a choice and limit his/her responsibility and thereby establish his/her identity as an I who is part of an economy, a society and thus a citizenship. Identities are constructed in the forgetting of this groundless Grund of ethics. The I becomes an I when I forget that I was a neighbour (me) first. Identity is constructed in the presence of the third on the basis of the exclusion of differences and the limitations of responsibility. Prior to the question of a subject (identity), ‘Who is my neighbour?’ is the question, ‘To whom am I a neighbour?’ Identity or subjectivity is the response to the prior call to responsibility.19 The subject comes into being as a response to the call of the wounded other,20 as a ‘me’ who is a neighbour to the wounded.21 Subjectivity/identity is a gift given by this call that is infinite as well as before time,22 and thus cannot be appropriated within any economy. There is an infinite responsibility, which cannot be cancelled or paid back. It remains outside the economy. Before I was, the other was. Before I came, the ‘I’ was a ‘me’ of unique inescapable responsibility. Before I can be, I am a neighbour. This is the groundless (infinite/transcendent) Grund for Levinas. Prior to the question of a subject (identity), ‘Who is my neighbour?’ is the question, ‘To whom am I a neighbour?’ Identity or subjectivity is the response to the prior call to responsibility.19 But where is God in this Grund? From God-beyond-being to society For Ricoeur the groundless Grund was in the supraethical of the love commandment, but because it is impossible/unthinkable, it needed to be placed within the economy of divine giving – a prior economy. In platonic thinking, the Grund, the repose, of all being and therefore of all meaning is the firmness and the stability of the earth. In modern philosophy, this Grund, in the sense of a foundation, has shifted to the subject (Levinas 2000:132). By the reverse of the nomikos’ question, this subject has been unseated by the other, thus there is a groundless Grund to be found in the infinite transcendence and infinite patience of the other who awakens me to responsibility. There is groundlessness in ethics or an infinite transcendence. 27.‘Faith is mature or fully developed only if it is reflective, that is, only if it involves a thinking interaction with the Scriptures which orient and inspire it’ (Burggraeve 2000:155). ‘The intrinsic religious identity rests on an intellectual and reflective appropriation of the confession of faith and the message bound up with it’ (Burggraeve 2000:155,161). 26.Ethics signifies the bursting of unity, originally synthetic, or experience, and there- fore a beyond of that very experience’ (Levinas 2000:200). 28.Otherness in the texts takes on various forms, namely: the text’s cultural and social context is other to our cultural and social context; • in the text there is a continual trace of the wholly and Holy otherness of God; • there is the unavoidable call of the other (stranger, widow, orphan, poor, naked, • hungry, thirsty, homeless, imprisoned and sick) in the texts; there is the unavoidable différance in the texts; • there is the otherness of the implied reader who is other than the actual reader. • HTS Teologiese Studies/Theological Studies Article #131 Jesus fully understands the Grund behind the nomikos’ question and therefore he tells the story of a despised stranger, one who is excluded from that society, excluded from the oikos, and who is an enemy (a threat to the identity of that society), and he turns the question around so that it is no longer: ‘What is the limit of my responsibility?’ (based on a definition of neighbour), but ‘who is called and who responds to the wounded?’ Responsibility is thus not something I choose to give or deny, but is a state in which I find myself prior to any identity as an I who can make a choice. Responsibility is prior to my identity and subjectivity, and therefore even prior to the question of the nomikos. This prior responsibility (this new Grund of responsibility) Levinas The responsibility to love strangers/enemies is placed within a new economy of God’s gracious giving. It is no longer the economy of identity of the self, but a prior economy of the divine identity as graciousness. Responsibility is no longer included in 14.‘The commandment to love, according to this interpretation, brings about a conver- sion of the golden rule from its penchant for self-interest to a welcoming attitude toward the other. It substitutes for the ‘in order that’ of the do ut des the because of the economy of the gift: ‘Because it has been given to you, you can give in turn.’’ (Ricoeur 1995:300) ‘What is called ‘Christian ethics,’ or as I would prefer to say, ‘communal ethics as in a religious perspective,’ consists, I believe, in the tension between unilateral love [love commandment] and bilateral justice [golden rule], and in the interpretation of each of these in terms of the other’ (Ricoeur 1995:301). 29 Vol. 65 No. 1 Page 3 of 5 HTS http://www.hts.org.za (page number not for citation purposes) Original Research Meylahn Levinas challenges this ontological metaphysical presumption, arguing that there is meaning without/before being.25 This groundlessness, which is beyond being, beyond subjectivity,26 is meaningful and can be thought, as it is the very Grund of thought, but it is often forgotten. calls ethics. Levinas argues that there is a responsibility (ethics) prior to justice and prior to the nomos of the oikos on which justice is founded.18 There is ethics prior to economy. 25.‘What is meaningful does not necessarily have to be’ (Levinas 2000:125). Is meaningful thought not a subversion of being, a disinterestedness (that is stepping out of the Order)? ‘What does not escape the same order, does not escape Order’ (Levinas 1991:9). 19.‘…for the other [autrui], the neighbour is the first come’ (Levinas 2000:138) HTS Teologiese Studies/Theological Studies Article #131 I believe he would go even further and argue that it is on the basis of this prior ethics that oikonomy can be constructed. Ethics is the Grund in which the self is discovered as a self that is inescapably responsible before the face of the other. 18.‘But it is always starting out from the Face, from the responsibility for the other that justice appears …’ (Levinas 2006a:89). e Studies/Theological Studies If we read the texts like the nomikos, we will read with the desire to exclude the other and the otherness of these texts. Yet, the identity-forming texts of the Christian community harbour a persistent otherness28 that cannot be avoided or ignored. It is thus 21.‘The subject – the famous subject resting upon itself – is unseated by the other [autrui], by a wordless exigency or accusation, and one to which I cannot respond with words, but for which I cannot deny my responsibility. The position of the subject is already his deposition. To be me (and not I [Moi]) is not perseverance in one’s being, but the substitution of the hostage expiating to the limit for the persecution it suffered.…We must therefore emphasize here the fact that freedom is not first. The self is responsible before freedom, whatever the paths that lead to the social superstructure. The for-oneself, in the accusative, is responsible prior to freedom through an untransferable responsibility that makes it unique. Freedom can here be thought as the possibility of doing what no one can do in my place; freedom is thus the uniqueness of that responsibility. Through substitution, it is not the singularity of the me that is asserted, it is its uniqueness’ (Levinas 2000:181). 22.This passivity transcends the limits of my time and is a priority prior to any representable priority. As if the ‘me’ as responsible for another had an immemorial past…’ (Levinas 2000:177). 22.This passivity transcends the limits of my time and is a priority prior to any representable priority. As if the ‘me’ as responsible for another had an immemorial past…’ (Levinas 2000:177). 23.’The way in which the Infinite is glorified (its glorification) is not representation. It is produced, in inspiration, in the form of my responsibility for the neighbor or ethics’ (Levinas 2000:195). ‘The sign given to another is sincerity, veracity, according to which glory is glorified. The Infinite has glory only through the approach of the other, through my substitution for the other, or through my expiation for another’ (Levinas 2000:200). 23.’The way in which the Infinite is glorified (its glorification) is not representation. It is produced, in inspiration, in the form of my responsibility for the neighbor or ethics’ (Levinas 2000:195). ‘The sign given to another is sincerity, veracity, according to which glory is glorified. HTS Teologiese Studies/Theological Studies Article #131 HTS Teologiese Studies/Theological Studies Article #131 28.Otherness in the texts takes on various forms, namely: 29.Stanley Hauerwas explains how a community of character is constructed by the narratives of Jesus. ‘If Jesus cannot be said to have a social ethic or have implication for a social ethic but his story is a social ethic, then the form of the church must exemplify that ethic’ (Hauerwas 1981:40). As well as: ‘…there is no way to speak of Jesus’ story without its forming our own. The story it forms creates a community which corresponds to the form of his life’ (Hauerwas 1981:51). e Studies/Theological Studies The Infinite has glory only through the approach of the other, through my substitution for the other, or through my expiation for another’ (Levinas 2000:200). 24.‘But there can be a relationship with God, in which the neighbor is an indispensa- ble moment’ (Levinas 2000:199). 24.‘But there can be a relationship with God, in which the neighbor is an indispensa- ble moment’ (Levinas 2000:199). Vol. 65 No. 1 Page 4 of 5 30 HTS HTS http://www.hts.org.za (page number not for citation purposes) Original Research Responsibility, God and society unavoidable, when learning to think the Scriptures, to also learn to think this otherness, thereby making it impossible to forget the primacy of ethics. It is in learning to think this otherness that the faith community becomes a community of character.29 Identity is and has to be formed in the presence of the third on the basis of exclusion, but the persistent otherness in the texts reminds us that identity is never complete. The other infinitely transcends what is present and thus there is always another other still to come, who calls us back into responsibility, reminding us that we are first a neighbour before we choose our neighbours. unavoidable, when learning to think the Scriptures, to also learn to think this otherness, thereby making it impossible to forget the primacy of ethics. It is in learning to think this otherness that the faith community becomes a community of character.29 Identity is and has to be formed in the presence of the third on the basis of exclusion, but the persistent otherness in the texts reminds us that identity is never complete. The other infinitely transcends what is present and thus there is always another other still to come, who calls us back into responsibility, reminding us that we are first a neighbour before we choose our neighbours. 30.Matthew 25:31–46. REFERENCES Aronowicz, A., 1990, ‘Translator’s introduction’, in Nine Talmudic readings by Emmanuel Levinas, transl. A. Aronowicz, Indiana University Press, Indianapolis. y p Burggraeve, R., 2000, ‘The Bible gives to thought: Levinas on the possibility and proper nature of biblical thinking’, in J. Bloechl (ed.), The face of the Other and the trace of God: Essays on the philosophy of Emmanuel Levinas, Fordham University Press, New York. Derrida, J., 1992, Given time, I: Counterfeit money, transl. P. Kamuf, University of Chicago Press, Chicago. f y University of Chicago Press, Chicago. The community-forming texts remind us of this messianic other/third,30 thereby reminding us of the priority of ethics, the groundless Grund of our responsibility, and thus shaping the ethos of a community toward a cosmopolitan citizenship that is always responding to the eschatological interruption by the other other who is not yet present. Goldberg, M., 1982, Theology and narrative: A critical introduction, Abington Press, Nashville. Hauerwas, S., 1981, A community of character: Toward a constructive Christian social ethic, University of Notre Dame Press, Notre Dame. Kierkegaard, S., 1995, Works of love, transl. H. Hong & E. Hong (eds.), Princeton University Press, Princeton.i Although it is in the presence of the third that identities/ societies are constructed by justifiably excluding or including the third, the justifiably excluded third is simultaneously the other in whose presence identity is constructed, as well as the other/stranger/enemy who challenges and deconstructs the identity. This then opens identity/society toward greater democracy (to hear the third who has not been heard), greater justice as dikē (to give space to the other who has no space) and greater hospitality (to give a home to the homeless). Levinas, E., 1969, Totality and infinity: An essay on exteriority, transl. A. Lingis, Duquesne University Press, Pittsburgh. g q y g Levinas, E., 1982, L’ au-delà du verset, Les Éditions de Minuit, Paris. Levinas, E., 1991, Otherwise than Being or Beyond Essence, transl. A Li i Kl A d i P bli h D d ht Levinas, E., 1991, Otherwise than Being or Beyond Essence, transl. A. Lingis, Kluwer Academic Publishers, Dordrecht. A. Lingis, Kluwer Academic Publishers, Dordrecht. Levinas, E. ,2000, God, death, and time, transl. B. Bergo, Sta Levinas, E. ,2000, God, death, and time, transl. B. Bergo, Stanford University Press, Stanford. University Press, Stanford. y Levinas, E., 2006a, Entre Nous, Continuum, New York. HTS Teologiese Studies/Theological Studies Article #131 HTS Teologiese Studies/Theological Studies Article #131 In conclusion, the story of Luke 10 challenges us to read differently. To read with a different question, where the foremost question is not my/our identity, but my/our responsibility toward the other. I believe that this reading can provide a response to the plurality of others in the global world by forever challenging our identities, communities and norms, and our interpretations of citizenship and justice, by reminding those who are called into responsibility by this text, the faith Christian community, that there is always still another other who is excluded and to whom I am responsible. This reading cannot and should not offer a moral solution to the challenges of global citizenship, but calls to a journey towards greater justice and democracy. Levinas, E., 2006b, Humanism of the Other, transl. N Levinas, E., 2006b, Humanism of the Other, transl. N. Poller, University of Illinois Press, Chicago. University of Illinois Press, Chicago. y g Mouton, E., 2004, The reorienting potential of biblical narrative as resource for Christian ethos, with special reference to Luke 7:36- 50. SBL paper, 2004 Annual Meeting, San Antonio, USA. 50. SBL paper, 2004 Annual Meeting, San Antonio, USA p p g Ricoeur, P., 1995, ‘Ethical and theological considerations on the golden rule’, in Figuring the sacred: Religion, narrative and imagination, transl. D. Pellauer, Fortress Press, Minneapolis. Ricoeur, P., 2005, The course of recognition, transl. D. Pellauer, Harvard University Press, London. Root, M., 1989, ‘The narrative structure of soteriology’, in S. Hauerwas & L.G. Jones (eds.), Why narrative? Readings in narrative theology, Eerdmans, Grand Rapids. Vol. 65 No. 1 Page 5 of 5 31 HTS 31 http://www.hts.org.za HTS (page number not for citation purposes) (page number not for citation purposes)
https://openalex.org/W2332242060
https://www.scienceopen.com/document_file/643a8e0d-40d3-41a9-9173-480e1f8f5ea2/ScienceOpen/08109028.2016.1144669.pdf
English
null
Theory of emergence: introducing a model-centred approach to applied social science research
Prometheus
2,015
cc-by
9,545
*Corresponding author. Email: omer.yezdani@griffithuni.edu.au © 2016 Informa UK Limited, trading as Taylor & Francis Group RESEARCH PAPER Theory of emergence: introducing a model-centred approach to applied social science research Omer Yezdani* , Louis Sanzogni and Arthur Poropat Department of International Business and Asian Studies, Griffith University, Brisbane, Australia This paper explores a model-centred approach to augment the development and refinement of the theory of emergence. Its focus is on the relational process of leadership as an emergent event in complex human organisations. Emergence in complex organisations is a growing field of inquiry with many remaining research opportunities, yet a number of its central themes continue to be loosely connected to practical application and reliant on equivocal translations from root meaning. This paper offers a novel model of semantic conceptualisation of theory and phenomena with simulations to strengthen the theory–model–phe- nomenon link, building on the work of previous authors. Strengthening this link yields numerous applications, including making sense of complex organisational dynamics and supporting a wide range of theory-building research methods in applied social science and interdisciplinary research. The paper begins with a reflection on the main ideas of the theory of emergence, followed by discussion on prevalent model-centred approaches. A programme of semantic conceptuali- sation to expand real-world application of the theory of emergence is proposed. Prometheus, 2015 Vol. 33, No. 3, 305–322, http://dx.doi.org/10.1080/08109028.2016.1144669 Prometheus, 2015 Vol. 33, No. 3, 305–322, http://dx.doi.org/10.1080/08109028.2016.1144669 Prometheus, 2015 Vol. 33, No. 3, 305–322, http://dx.doi.org/10.1080/08109028.2016.1144669 O. Yezdani et al. O. Yezdani et al. This paper presents a model-centred approach to augment the development and refinement of the theory of emergence. Its focus is on the relational process of lead- ership as an emergent event. The paper begins with a reflection on the main ideas of the theory of emergence, followed by discussion on prevalent model-centred approaches. Finally, a programme of semantic conceptualisation to expand real-world application of the theory of emergence is proposed. This proposed programme refers to the application of interdisciplinary theory to diverse phenomena through empiri- cally-linked conceptual models. To this end, the semantic conceptualisation process involves testing compatibility between models, and offers significant possibilities to extend applied social science and interdisciplinary research into complexity and emergence. g The concept of emergence is interwoven with the broader umbrella of complexity theory, and refers to novel and coherent forms (structure, pattern, order) arising from the dynamic interplay among elements at successive layers within a complex adap- tive system (Goldstein, 1999; Chiles et al., 2004). Many classic examples of emer- gence exist in patterns that arise spontaneously in ecosystems, economics, chemistry, physics and the social sciences. Complex systems are adaptive if they possess this capacity for emergent order (Anderson, 1999). The emergence of self-organised structure and strategy in communities of practice occurs both with and without man- agerial control, within and beyond the boundaries of the organisation (Mintzberg, 1994; Plowman and Duchon, 2008). If emergence is to be understood as a product of underlying human interaction, researchers must first observe and measure the nature, dynamics and increments of interpersonal influence and their consequent links to system-level behaviours (Hazy, 2008; Lichtenstein and Plowman, 2009). Complexity theory is derived from a broad and well-documented intellectual movement rejecting nineteenth century assumptions and incorporating the non-reduc- tionist tenets of early-1900s gestalt and holistic thinking, explorations into the mech- anisms of feedback, communication and control in cybernetics (Weiner, 1948), and the broadly-diffused general systems theory view of organisations as ecosystems of interdependent actions and consequences (Skyttner, 2006). Introduction Over the last few decades, the study of complex systems, known as ‘complexity theory’, has been making its way into the social sciences (Anderson, 1999; Goldstein, 1999; Wheatley, 1999; Marion and Uhl-Bien, 2001; Osborn et al., 2002; Plowman, Solanski et al., 2007). This relatively recent application of complexity principles has generated a deeper understanding of the non-linear, complex and adap- tive behaviours within and between organisations that give rise to the emergence of form (Lichtenstein et al., 2006; Uhl-Bien et al., 2007). Complexity theory applies an understanding of leadership and organisation less as an art of prediction, and more as one of sense-making, cultivated participation, interaction and influence between individuals across all levels of the organisation where leadership itself is viewed as an emergent event (Lichtenstein et al., 2006). However, the utility of the concept of emergence in applied social science research and practice relies on a tenuous theory– phenomenon link which, as argued in this paper, remains relatively underdeveloped despite its central importance to the robustness of theory and its real-world applica- tion. The effective isomorphism of theory and structures in real-world behaviours is vital to the reliability of theory, without which there are few reasons to believe a theory of emergence for human organisation exists (McKelvey, 1999). 306 O. Yezdani et al. Drawing on the precepts of general systems theory, cybernetics and the observation of dissipative structures in chemical systems (Nicolis and Prigogine, 1977), later works have posited further adaptations from the natural, physical, chemical and mathematical sciences to human social systems, including a punctuated equilibrium of discontinuous and radical tech- nological change (Tushman and Anderson, 1986), evolutionary and emergent pro- cesses of self-organisation in the context of the modern firm (Brown and Eisenhardt, 1997; Chiles et al., 2004) and of humans as agents with ‘schemata’, a malleable set of rules (Anderson, 1999). The application of complex adaptive systems to human social systems has performed well as a metaphorical device, but lacks a definitive link to root theory through compatible conceptual models. Distinguishing between complexity as a lens through which greater understanding may be acquired, and applying this understanding as a concrete definition remain areas of interest in com- plexity research. The current practice of describing organisations as complex adap- tive systems (directly from root theory) serves well as a metaphor, but if researchers are to say these phenomena are complex adaptive systems, the theory must be ade- quately tied to the phenomena through a more concrete process. Morgan’s (1998) exploration of the use of various metaphors to describe organisations suggests they have been useful as a sense-making and conceptual tool. However, the distinction between metaphor and reality must be clear. 307 Prometheus In the maiden volume of Emergence: Complexity and Organisation, McKelvey (1999) contends that the future success of complexity sciences hinges on the execu- tion of a systematic agenda linking theory development with mathematical and com- putational models, and the testing of models with real-world structures via a process of semantic conception. Semantic conception is defined in this paper as a process whereby scientific theories are shaped in the form of conceptual models, with theory used for the specification and testing of those models (Thompson, 1988; Suppe, 1989). In semantic conception, theory is linked to real-world phenomena through conceptual models with rules and parameters. To this end, a model-centred isomor- phism of theory is required to support the interdisciplinary transfer of ideas and con- cepts across the sciences, particularly between epistemological branches. O. Yezdani et al. Over the last decade, a range of case studies has contributed to the conceptual development of emergence in and around organisations, testing, adapting, confirming and refining measurement instruments and theoretical constructs (Lichtenstein, 2000; Chiles et al., 2004; Plowman, Baker et al., 2007). In parallel, a series of computational and mathematical models has been presented and is available for wider use (March, 1991; Tyler et al., 2005; Hazy, 2008). Expanding the model-centred approach dis- cussed in this paper first requires an examination of the conceptualisation process as it applies to the theory of emergence in human organisations. Conceptualisation process for a theory of emergence One of the first accounts of an empirical theory of emergence is provided by Rueben Ablowitz (1939), who claims its concepts and terminology were derived from diverse sources, including J. S. Mill’s Logic, G. H. Lewes’s Problems of Life and Mind, S. Alexander’s Space, Time and Deity, C. L. Morgan’s Emergent Evolution and The Emergence of Novelty. Ablowitz offers a description of emergence as the sublime force that ‘accounts for the transformation of quantity into quality’, together with earlier definitions, including the ‘tendency of units of one kind in combination, to constitute units of a new kind, with more complex constitution and new qualities due to the new togetherness of the parts’ (Sellars, 1922). However, Ablowitz chooses to illustrate the ideas of emergence with a number of examples, one being the char- acteristic liquidity of water, a quality not possessed by its atomic components, hydro- gen and oxygen. Although Ablowitz’s example was soon debunked with subsequent theories of quantum bonding (Goldstein, 2010), his original idea remains valid while suggesting the need for circumspection in its use. The novel concepts of emergence have challenged the existing lexicon in a search for ways to describe complex and counterintuitive ideas. At first glance, it may appear that the study of complex systems is defined as much by what it is not, as by what it is (Marion, 2008). Complexity theory employs a vast range of negative prefixes such as non-linearity, uncertainty, unpredictability and disequilibrium, emphasising that the emergence of coherent form can occur spontaneously through the interplay of underlying components that interact on the basis of simple rules without centralised coordination or control (Anderson, 1999; Goldberg and Markoczy, 2000). The idea of emergent order would be more difficult to imagine were it not for the use of metaphorical device stemming from the act of interdisci- plinary borrowing at a conceptual level, such as the seamlessly moving flock of birds that reflects a cascade of small, relatively simple, localised interactions (Reynolds, 1987). Similar swarm behaviours are exhibited by fish, ants, bees or buffalo. While O. Yezdani et al. 308 these examples offer insight into the simple rules that facilitate harmonious movement of a collective of individuals, a direct translation to unfamiliar territory potentially serves to stigmatise the field (Burnes, 2005). The problem arises from the translation of ideas in a manner far removed from their root meaning. Conceptualisation process for a theory of emergence For obvious reasons, humans are not the equivalent of ants, bees, birds, liquids or gases. This issue is exemplified by Burnes (2005) in the assertion that there is a world of difference between restructuring an organisation because science has discovered that this action is necessary, and doing the same thing because that is what a computer simulation has shown that a flock of birds would do if faced with wind turbulence. This particular stream of criticism argues that complexity theory’s success as a metaphorical device has exceeded its utility as a practical tool for organisations and management, an issue that is firmly rooted in the process of semantic conception, referred to in this paper as the translation of theory to its respective phenomena through conceptual models. To contextualise our examination of a model-centred approach to semantic conception, we first revisit the anchoring themes of emergent self-organisation and the nature of dynamic interaction and influence as they apply to complex firms. Emergent self-organisation Emergent self-organisation has been referred to as the anchor-point phenomenon of complexity theory, a process whereby system-level order spontaneously emerges as a result of dynamic interactions among individual agents (Anderson, 1999; Chiles et al., 2004; McKelvey, 2008). At the point of reaching a critical threshold, systems collapse or re-organise/re-combine into new configurations (McKelvey, 2008; Licht- enstein and Plowman, 2009). Foundation elements of complexity dynamics were devised by Nicolis and Prigogine (1977) in their identification of antecedent condi- tions that explain how order is generated (especially in chemical systems) through spatiotemporal ‘dissipative structures’ that arise through the mechanics of energy dis- sipation. Dissipative structures result from high sensitivity to initial conditions far from equilibrium states, and through amplification of small change, emergent self-or- ganisation and reinforcing feedback (Nicolis and Prigogine, 1977; Anderson, 1999; Lichtenstein and Plowman, 2009). Everyday examples of dissipative structures can be found in the convection of liquid or cyclones, visible in the collective movement of components (Nicolis and Prigogine, 1977). With the aid of a multitude of local interactions and feedback loops, individual behaviours are amplified then dissipated across systems from which collective tendencies spontaneously emerge (Anderson, 1999; Lichtenstein, 2000). Self- reinforcing feedback stabilises the system at the collective level, at which point coherent structures, patterns and observable forms of order begin to emerge (Anderson, 1999). Self-organisation in open systems occurs only with the continuous importation of energy (Prigogine and Stengers, 1984; Anderson, 1999; Chiles et al., 2004). When energy build-up reaches an unstable threshold, or ‘edge of chaos’ (Osborn et al., 2002), agents suddenly dissipate energy in a cascade of adaptive ten- sion-breaking, thereby generating order through energy dissipation (Marion, 2008). Unpacking the active elements in the process of self-organisation and translating 309 Prometheus these concepts to human behaviour is a critical step in enhancing the practical application of emergence in organisations and management. As there are fundamental differences between particles and human beings, a substantial level of abstraction is required to apply the Nicolis and Prigogine (1977) dissipative structures theorem to human social systems, particularly when quantify- ing the mechanisms by which the importation and dissipation of energy are achieved. The terms for this abstraction are evident in the expressions used to describe the nat- ure of ‘energy’ in social systems: Chiles et al. Emergent self-organisation (2004) describe fluctuations in energy as new events, activities, financial resources, market growth; Anderson (1999) refers to new sources of energy as members, suppliers, partners and customers; whereas Marion (2008) refers to ‘any agent that controls energy’ with implications for the inter-relational processes of leadership. Such definitions give an inexact idea of what energy is and how it is imported, transferred and maintained among human agents in dynamic and complex social systems, where system boundaries are invariably por- ous, changing and subject to negotiation and perception. Defining these boundaries is necessary before the system’s behaviour can be understood. The absence of satis- factory definition limits the conceptualisation and measurement of specific human behaviours as mechanisms for energy importation, transmission and transference (Macintosh and Maclean, 1999; Lichtenstein and Plowman, 2009). Further refine- ment of terms is required if they are to be useful in practice. Principles of self-organisation apply to organisations given appropriate conditions, such as multiple agents with schemata, intricate webs of interdependency and interaction, importation of energy, amplifying and reinforcing feedback, disequilibrium, continuous change and so forth (Anderson, 1999). The application of principles of self-organisation to modern firms is, however, not without obstacles. Among these is the long-held expectation placed on managers and leaders to make the decisions that will lead to desired outcomes (Burns, 1978; Plowman and Duchon, 2008). Leadership, dynamic interaction and influence The conduct of leaders and emergent outcomes arising from interactions among indi- vidual agents do not need to be opposite sides of the coin; for instance, emergence does not imply that leaders are unnecessary, but rather that they are potent actors in the creation of social pattern and system-level order. The nature of leadership in human systems contrasts with physical and chemical systems that do not possess equivalent socio-cultural attributes. One example is the understanding of leadership as a function that can transcend transactional processes in the form of transforma- tional, idealised or charismatic influence (Burns, 1978). In the physical system, there can be a presumption that equivalent agents are of roughly equal status. This is not the case with human actors in social systems, where influence is not equitably dis- tributed. System histories are also known to be a salient in determining future states, given the effects of structural inertia (Hannan and Freeman, 1984) and sensitivity to initial conditions. The complexity viewpoint positions leadership as an emergent characteristic of dynamic interaction and influence occurring among agents in a com- plex system, mutually contingent on follower attributes, such as need for autonomy (Lichtenstein et al., 2006). Leadership behaviours have the potential to foster the conditions necessary for emergence to occur through interactions with members across all levels of an organisation, a concept that Macintosh and Maclean (1999) 310 O. Yezdani et al. refer to as ‘conditioned emergence’. Exploring further through a meta-analysis of complexity leadership research, Lichtenstein and Plowman (2009) identify four beha- vioural processes that co-generate the conditions for new emergent order: disrupting existing patterns of behaviour; encouraging novelty; sense-making from patterns and symbols; and stabilising feedback. Understanding the nature of dynamic interaction among individual agents is a crucial aspect of emergent self-organisation in human social systems, making it a common element in defining the boundaries of complexity theory. Numerous authors have employed variations that incorporate common themes to describe complexity theory as the study of interacting agents/units that together form a complex system (Anderson, 1999; Goldstein, 1999; Plowman, Solanski et al., 2007; Marion, 2008; Lichtenstein and Plowman, 2009). Hence, a system that entirely prohibits interaction is incapable of complex adaptive behaviours. Leadership, dynamic interaction and influence Agent interaction has also played a pivotal role in redefining leadership (via complexity leadership theory) as a process that expands beyond the capabilities of the individual, where leadership itself is an emergent event, a product of ‘relationships, complex interactions, and influences that occur in the “spaces between” individuals’ (Lichtenstein et al., 2006). Understanding the character of interaction between individuals is where the associated paradigms of complexity, emergence and leadership converge (Lichtenstein et al., 2006; Goldstein, 2008). The dynamic interaction and interdependencies among components within and around complex systems make calculating behaviours for the purpose of practical application in ‘real-world’ systems a challenging task, especially given the multitude of variables that affect behaviour in open systems (Nicolis and Prigogine, 1977; Anderson, 1999; Marion and Uhl-Bien, 2001). This aspect is embedded in discus- sions by many complexity theorists, yet remains an area of concern. For example, Burnes (2005) suggests that computer simulations and interdisciplinary semantics are not enough to generate reliable predictions of macro-level behaviour, which restricts the application of complexity to the laboratory environment. However, a key benefit of idealised computational and mathematical models is the ability to isolate variables and the principles on which emergent outcomes are based for use in a theory– model–phenomena conceptualisation (McKelvey, 1999), also serving to support an expanding horizon of empirical method. An illustrative metaphor would be testing the aerodynamics of an aircraft through simulation before sending it out on the run- way. McKelvey (1999) elaborates on the concept by suggesting that experimental accuracy should be developed in parallel with ontological adequacy (to represent a specific portion of reality) via a systematic agenda linking model structures to the real world. A revisitation of this fundamental and continuing agenda follows. A model-centred approach to emergent self-organisation The study of emergence in organisations does not mark the beginning of previously non-existent phenomena, but rather the application of a new lens, capable of detect- ing and making sense of complex and dynamic behaviours (Goldstein, 1999; Marion, 2008). Over the course of the last two decades, the lens of complexity and emergence has been applied to an increasingly wide variety of fields, each iteration providing insights and perspectives and in many cases direct feedback for the application and refinement of theory. 311 Prometheus Prometheus Emergence and complexity in organisations are dealt with in various ways in classic organisational theory, such as Mintzberg’s (1994) inclusion of emergent strategies to describe the practical reality that unplanned activity is a key process of strategy, and this in turn requires a departure from the traditional focus on planned and deliberate activities. Cohen et al. (1972) deal with complexity in the form of organised anarchy in which opportunities for choice are viewed as a garbage can into which problems and solutions are thrown and choices are ultimately made, depend- ing on the mixture of cans available, their labels, and the speed of collecting and removing garbage. The garbage can model highlights the importance of energy input, problem and choice ‘load’ at a given point, and the observation that decision outcomes frequently do not resolve underlying problems (Cohen et al., 1972). Lewin (1952) explores behaviours within the concept of group dynamics; a group is more than the sum of its individual members and behaves in ways not necessarily repre- sentative of each member (commonly referred to as ‘groupthink’, a process that often leads to substandard decision making). As proposed more than a decade ago by Goldstein (1999), the study of emergent phenomena has been ripe for exploration, particularly in the areas of emergent (infor- mal) leadership and emergent networks. Communities of practice that emerge within and beyond the boundaries of the organisation provide a practical example of emer- gent networks and informal leadership influences (Juriado and Niklas, 2007). In con- ceiving a framework of research prospects, Goldstein (1999) locates major research opportunities that can be illustrated within a simple matrix of sources and types of structure applicable to organisations. Goldstein’s grid contrasts source of organisa- tional structure (imposed and self-organised) with type of structure (hierarchical and participative), and is reproduced here (see Figure 1). A model-centred approach to emergent self-organisation The upper right quadrant ‘emer- gent networks’ is highlighted by Goldstein (1999) as a new area of research and refers to ‘authentic’ instances of emergence in complex firms. Goldstein’s grid is a useful tool to position and contrast literature in relation to hierarchical, imposed, participative and self-organised organisational dynamics. Goldstein’s prediction of a fertile research agenda has proved correct, with significant growth of inquiry occurring over the last decade. Goldstein (1999) and Source of Structure Imposed Self-Organised Informal Leadership Imposed Teams Emergent Networks Command and Control Hierarchical Participative Type of Structure Figure 1. Emergence and organisational dynamics. Source: From Goldstein (1999) (shaded areas added). Figure 1. Emergence and organisational dynamics. Source: From Goldstein (1999) (shaded areas added). 312 O. Yezdani et al. McKelvey (1999) both point out that ontological adequacy would be a key require- ment for giving credence to a theory of emergence. Goldstein also suggests a notion of ontological plurality to accompany the observation and understanding (across multiple levels of analysis) of new subsystem levels coming into being through emergence. In parallel, McKelvey proposes the use of a systematic conceptualisation process that avoids axiomatic reduction; in other words, not deriving ontological adequacy by means of a single model and in turn increasing the potential for external validity. McKelvey details this systematic process of semantic conception by sug- gesting that theory is always ‘hooked’ to models, each model consisting of experi- mental testing via an ‘idealised physical system’ (computational or mathematical models) with ontological adequacy testing undertaken through isomorphism of ide- alised structures against real-world phenomena that fall within the scope of theory. McKelvey (1999) both point out that ontological adequacy would be a key require- ment for giving credence to a theory of emergence. Goldstein also suggests a notion of ontological plurality to accompany the observation and understanding (across multiple levels of analysis) of new subsystem levels coming into being through emergence. In parallel, McKelvey proposes the use of a systematic conceptualisation process that avoids axiomatic reduction; in other words, not deriving ontological adequacy by means of a single model and in turn increasing the potential for external validity. A model-centred approach to emergent self-organisation McKelvey details this systematic process of semantic conception by sug- gesting that theory is always ‘hooked’ to models, each model consisting of experi- mental testing via an ‘idealised physical system’ (computational or mathematical models) with ontological adequacy testing undertaken through isomorphism of ide- alised structures against real-world phenomena that fall within the scope of theory. g p p y From these foundational processes of theory building, we are led to two crucial questions: have we realised the opportunity of Goldstein’s promised research, and have we achieved the systematic agenda proposed by McKelvey? To illustrate, a hybrid grid is presented, juxtaposing the former (Goldstein) proposed research agenda and the latter (McKelvey) idealised model-centred mode of conceptualisa- tion, expressed here as simulated versus non-simulated empirical method (see Figure 2). Figure 2 represents a limited exposition of selected articles (n=13; see Table 1), applying thin search parameters (relevance, citation frequency, primary data collection) to identify articles relating to emergent networks and emergent leadership that contribute to the research agenda proposed by McKelvey and Goldstein. A num- ber of search platforms were used to locate prominent articles that employ primary data collection methods. Although this reveals a relatively small sample of literature, it is apparent that non-simulated methods have been the dominant feature over the course of the last decade. The use of the grid allows this selection of literature to be positioned with reference to other works. From this brief review, it is also apparent that simulated methods of emergent leadership that are capable of providing detailed insights into relational processes are a less-explored combination. There has also been growing use of computational and mathematical modelling in theory develop- ment (Levinthal and Warglien, 1999; Hazy, 2006), but even these more conceptual Focus of Inquiry Emergent Emergent Leadership Networks Simulated Non-Simulated Empirical Method a b c d e f g h i j k l m Figure 2. Focus of inquiry and empirical method grid. Empirical Method Figure 2. Focus of inquiry and empirical method grid. 313 Prometheus Table 1. Review of selected empirical works plotted in the grid at Figure 2 Ref. Author Description a Chiles et al. (2004) In-depth case study into organisational emergence/recombination of a collective across musical theatres b Plowman, Baker et al. O. Yezdani et al. O. Yezdani et al. Among the key limitations of the direct theory–phenomenon link identified by McKelvey (1999) is the need for high instrumental reliability and justification of ontological adequacy that rests on the predictive accuracy of theory to real-world scenarios. Both are areas of concern if there is an absence of ontologically-adequate models that are accompanied by appropriate idealised experimentation (i.e. computa- tional models) where instrumental reliability is high enough to formulate prediction, and generalisability within specified parameters. The semantic conception process addresses the risk of post hoc phenomenological labelling, given the generally higher levels of instrumental reliability and recursive testing available in a simulated envi- ronment (McKelvey, 1999). As alluded to earlier, semantic conception may be used to generate principles upon which the conception of ‘energy’ and the mechanisms for its dissipation in human social systems can be generally applied. The prominence of a theory–phenomenon approach (Lichtenstein, 2000; Chiles et al., 2004; Plowman, Baker et al., 2007) may be associated with a tendency to undertake non- simulated empirical methods that centre around real-world case studies, such as those proposed by Eisenhardt (1989), in which idealised model–phenomena testing is less apparent. Lee’s (1989) exploration of the ‘controversial’ division between objectivist and subjectivist schools of thought describes what appeared to be a widening gap between these major approaches to organisational research. Lee raises several methodological concerns about the use of objectivist or natural science-based experi- ments with organisations, highlighting the difference between laboratory conditions and the organisational setting that affects replicability, generalisability and the rules of logic in qualitative analysis to describe how systems function. Investigations of complexity impose particular challenges on researchers beyond those presented by simpler, hypothetico-deductive research. Figure 4 illustrates a model of semantic conception suggested by McKelvey (1999) as the preferred tool for exploring emergent phenomena. According to the model of semantic conception, theory is always linked to and tested via (idealised) models, where theory attempts to explain the behaviour within a model, and models attempt to explain phenomeno- logical behaviour (McKelvey, 1999). From this viewpoint, formalised computational and mathematical models take a central role in theory development. The process of semantic conception posits that theory, models and phenomena are distinctly separate entities. Thus, theory attempts to explain the behaviour of only models (McKelvey, 1999), with ontological adequacy achieved by isomorphism of the model against that portion of real-world phenomena (McKelvey, 1999). A model-centred approach to emergent self-organisation (2007) In-depth single case study of the emergence and amplification of change within mission church c Lichtenstein (2000) Multiple case studies on emergence in several high-potential technology-enabled new venture firms d Blackler et al. (2000) Comparative case study of three strategy teams within a single high-tech firm, processes of organisation via networks of activity e McKendrick et al. (2003) Emergence of organisational form in the global disk array market (note: this study is based on archival data) f Pescosolido (2002) Observation of how emergent leaders influence interacting groups, multiple case analysis of jazz music and rowing groups g Kickul and Neuman (2000) Survey of 320 university students on the behaviours of emergent leaders and their relationship to team processes and outcomes h Carte et al. (2006) Emergent leadership across 22 self-managed virtual project teams of university students i Zott (2003) Simulation study on the emergence of intra-industry differential firm performance, the link between capabilities, resources and performance j Huygens et al. (2001) Co-evolution of firm capability using multiple case studies of firms within the music industry k Prietula and Carley (1994) Thirty computational modelling simulations of individual and collective behaviour of agents in varying conditions l March (1991) Modelling of two cases involving mutual learning of an organisational code, and learning and competitive advantage m Hazy (2008) Case study of influence-signalling in an growth-stage entrepreneurial firm Table 1. Review of selected empirical works plotted in the grid at Figure 2 approaches provide further opportunity for application in primary data collection (Lichtenstein et al., 2006). The publication of the studies presented by Anderson (1999), Lichtenstein (2000) and Chiles et al. (2004) demonstrate that the method of systematic inquiry based on direct theory–phenomenon conception has been reasonably well-accepted into the process of theory building for complexity. Figure 3 illustrates the theory– phenomenon (‘organisation science’) conception discussed here (McKelvey, 1999). The direct theory–phenomenon conception applies a recursive cycle of continuous refinement where formalised models are developed in parallel with theory, and onto- logical adequacy is established through predictions (directly from theory) and confir- mation/disconfirmation against sampled, real-world phenomena (McKelvey, 1999). Theory Model Phenomena Figure 3. Organisation science conception. Source: McKelvey (1999). Phenomena Figure 3. Organisation science conception. Source: McKelvey (1999). 314 O. Yezdani et al. p p ( y ) There are several limitations to the existing conceptual approaches illustrated at Figure 3. These have resulted in McKelvey’s empirical predictions being unrealised and – consequently – Goldstein’s research agenda not being entirely fulfilled. The limitations of McKelvey’s semantic conception model are first that it is heavily Theory Axiomatic base Phenomena Model Figure 4. Semantic conception. Source: McKelvey (1999). Figure 4. Semantic conception. Source: McKelvey (1999). 315 Prometheus weighted to a narrow array of research methods (idealised or simulation-based test- ing), yet numerous and arguably more prominent contributions to the complexity lit- erature fall outside this scope, such as those referred to in Table 1. Secondly, McKelvey’s approach does not outline the necessary interdisciplinary link required to make the leap from one field of study to another (via conceptual models), despite this practice being a common characteristic in the complexity literature. In McKel- vey’s simulation-based approach, concepts are isomorphs of derivative and single theories. They improve the flexibility of the (organisation science) theory–phe- nomenon link, but leave a fragmented field of study. While McKelvey’s model illus- trates the linkage among theory, models and phenomena, the important relationship among abstractions that take shape as conceptual models is absent. g p p McKelvey’s semantic conception model can be logically expanded through a dis- crete process of conceptualisation that supports both the organisation science (the- ory–phenomenon) conception and semantic (theory–model–phenomena) conception methods, so as not to rule out any particular methodological approach. A novel model of semantic conceptualisation is offered here at Figure 5. A more extensive conceptualisation process presents numerous benefits. It tightens the (organisation science) theory–phenomenon conceptual loop through ontologically appropriate con- ceptualisation (addressing the ‘metaphorical device’ issue), while simultaneously lending support to formalised computational and mathematical models, expanding and testing semantic conceptualisation between models, as necessary. The ‘original’ McKelvey semantic conception provides for conceptualisation embedded within the- ory–model links: what is discussed here is a pragmatic, explicit and broadly applica- ble process of conceptualisation in support of current and potential empirical works, regardless of their approach. A robust conceptual model applicable to the services industry (for example) may comprehensively define and describe the minimum num- ber of inputs or behaviours required to achieve transformation, as proposed in theory and confirmed through models (Johns and Lee-Ross, 1998; Checkland, 2000), in terms that are fit for purpose in either simulated or non-simulated methods. O. Yezdani et al. O. Yezdani et al. The new model for semantic conceptualisation (Figure 5) offers greater variety of empirical method and broad scope for the interdisciplinary application of multiple theories to seemingly disparate phenomena, such as the behaviours of water molecules in human systems. A recursive cycle of conceptualisation to verify the comparability of models enables several pathways from theory, through models to phenomena. An example of this process of abstraction is provided at Figure 6: the- ory a linked to model x, which is then recursively-linked to model y, in turn capable of explaining multiple phenomena, provided the conceptual models are valid and consistent – which continue to be hooked via the theory–model–phenomena link – and provided the interpositions have practical consequences. The model supports theory building as a recursive process that involves continual study and conceptual development, adaptation, and refinement of theory that is informed by its use in real- world applications (Lynham, 2002). Simulation-based research may be used to strengthen the semantic conceptualisation process through the interchange of phe- nomena-based variables. The use of models in this process may take a variety of forms, depending on the fluidity and complexity of subject matter. For example, the model can be adapted to enable interpretive models for human social culture to be explored with thick description, non-reductionism and with at least semiotic utility (Geertz, 1973). A tool such as this supporting interdisciplinary importation through conceptual modelling is of enormous use to the nascent theory of emergence, and of importance across the sciences that deal in both reducible and holistic constructs, and the relationship between them, in applied research and theory building. The model of semantic conceptualisation can be applied in support of a systems- thinking approach to organisational learning. For example, in practice an organisa- tion may consider theories in use and mental models to inform and develop simula- tions to facilitate the transition to a more workable or sophisticated mental model, using data from the semantic conceptualisation process. While mental models are an ingrained way of understanding the world, building further understanding about the existing form of these models individually and at the system level through simula- tions would support Senge’s (1990) notions of a learning organisation. O. Yezdani et al. In this scenario, future studies would benefit from being tied to a common link, or general method, to the explicit meaning of active ingredients that form part of a complex system so as not to rule out all reducibility. Theory A Phenomena Phenomena Model X Theory B Model Y The environment in which we live and experience the world Conceptual domain Axiomatic base Axiomatic base Semantic conceptualisation Simulation Simulation Interdisciplinary domain Figure 5. Model for semantic conceptualisation of theory and phenomena with simulations. Conceptual domain The environment in which we live and experience the world Model X Semantic conceptualisation Model Y Figure 5. Model for semantic conceptualisation of theory and phenomena with simulations. 316 O. Yezdani et al. The study of complex systems avoids overly simplistic forms of reductionism in the sense that the behaviour of whole systems is not directly assured through analysis of a single component held in isolation with all other factors assumed to be constant (Anderson, 1999; Goldstein, 1999). Therefore, a successful model for the conceptualisation of emergence ideally treats reductionism and holism as complementary strategies necessary to achieving coherence among multiple scales of Theory A Phenomena Model X Model Y Axiomatic base Semantic conceptualisation Simulation Figure 6. Example of semantic conceptualisation of theory, models and phenomena with a simulation. Axiomatic base Theory A Figure 6. Example of semantic conceptualisation of theory, models and phenomena with a simulation. 317 Prometheus analysis (Anderson, 1999). The idea of multi-level and irreducible phenomena is supported by Polanyi (1968), who describes mechanisms, such as knowledge, with the use of boundary conditions that are dependent on, but irreducible to, the laws of nature. Cases of holistic phenomena are described as such because they are irre- ducible; for instance, the relation of mind to body, and the multi-level nature of knowledge about the physical world (Polanyi, 1968). From this perspective, the semantic conceptualisation process is capable of incorporating multiple axiomatic bases and multiple models, opening greater possibilities for coherence between successive or meso-level analysis while maintaining ontological adequacy. Such a process is well-grounded in the philosophical tradition of pragmatism to link recur- sively theory with practice (Dewey, 1905), such that it achieves the representative utility of ‘good’ theory (Lynham, 2002). Implications and issues The model for semantic conceptualisation of theory and phenomena with simulations introduced at Figure 5 in this paper has numerous practical applications, including further development and refinement of a theory of emergence and supporting a range of theory-building methods in applied social science research. Further development and refinement of a theory of emergence has implications for the study of organisa- tions and management. Prigogine (1997), Marion (2008) and Plowman and Duchon (2008) argue that the world is inherently unpredictable and in a state of continuous flux such that organisations must possess a capacity to adapt. It is not enough to sim- ply predict change. It is also suggested by Plowman and Duchon (2008) and Licht- enstein and Plowman (2009) that the emergence of order and structure may persist either with or without managerial guidance, which has profound implications for the notion of ‘leadership’. As explanations of organisational phenomena have moved along a continuum of focusing on the functioning and properties of parts to configu- rations of parts within emergent whole systems (from parts to wholes) (Goldstein, 1999), the focus associated with human agents within complex systems has also moved from behaviours and traits of individuals to characteristics of interdepen- dency, interaction and relations among components in context (from individuals to interactions) (Lichtenstein et al., 2006; McKelvey, 2008). The implication of such a shift in conceptualisation is not to suggest that organisations should abandon all structure or routine, but rather that they should re-examine what may previously have been considered ‘givens’ for the creation of order and stability (Marion, 2008), such as the predetermination of specific futures, direction of change, elimination of disorder and formal designation of leadership (Plowman and Duchon, 2008). Simi- larly, concluding that the world is inherently unpredictable does not concurrently imply a state of constant chaos. Rather, there is an intermediate space between the two extremes of utter determinism and a world of pure chance (Prigogine, 1997). The development of a theory of emergence is more likely to benefit rather than be weighed down by the use of formalised computational and mathematical models, within a balanced empirical spectrum (McKelvey, 1999; Goldstein, 1999; Marion and Uhl-Bien, 2001; Lichtenstein et al., 2006). For this purpose, a range of computational and mathematical modelling approaches is on offer (March, 1991; Prietula and Carley, 1994; Kaczmarski and Cooperrider, 1997; Levinthal and Warglien, 1999; Moldoveanu and Bauer, 2004; Hazy, 2006, 2008). A note on the utility of ‘good’ theory Yezdani et al. 318 A note on the utility of ‘good’ theory Theory can be broadly defined as ‘coherent description, explanation and representa- tion of observed or experienced phenomena’ of practical use to describe, explain, diagnose and further understand phenomena (Gioia and Pitre, 1990). The real-world practical utility of theory is ideally the antithesis of reflections posed by Blumer (1954) on the state of 1950s social theory. This suffered ‘glaring divorcement’ from empirical science and a series of ‘grave shortcomings’ as a result of defective modes of inquiry. Thankfully, several modern variants that define ‘good’ social theory assert there is no need for an artificial divide between theory and practice. Hence, theory has utility value to help us act in certain ways, and is continually informed by, and applicable to, real-world practice (Van de Ven, 1989; Lynham, 2000; Corbin and Strauss, 2008). Consistent with this assertion, theory building can be described as the ‘ongoing process of producing, confirming, applying and adapting theory’ (Lynham, 2000), to which end theory-building methods ideally possess two inherent qualities: validity and utility (Van de Ven, 1989). As surmised by Gioia and Pitre (1990), ‘it would be useful for theory building to be viewed not as a search for the truth, but as more of a search for comprehensiveness stemming from different worldviews’. Among the difficulties encountered in the process of theory building is overcoming broadly-accepted views by posing new ways of viewing or understand- ing everyday phenomena. With its own emergent qualities, theory faces this challenge. Although the existence of a greater number of alternative paradigms to explain, predict or define organisations and their actors is likely to deliver more comprehensive understanding of organisational realities, the incommensurability of paradigms is also likely to produce scholarly fragmentation – a possible cause of confusion among practitioners (Gioia and Pitre, 1990; Burnes, 2005). Further strategies to address this dilemma include the development of a multi-paradigmatic bridging tool (see Gioia and Pitre, 1990). Such a tool may be capable of exploring the permeability between parallel constructs, and may be used to extend the semantic conceptualisation process as a part measure to address compatibility issues arising from interdisciplinary borrowing. The continual pursuit of theory building is driven by a range of factors, including the pursuit of a comprehensive understanding about our world and how we experience it, and the need to formulate ways to address issues or problems that reality presents us (Lynham, 2002). Thereby we advance the vocation of research. O. Conclusion This paper has provided an exploration of the existing theory–model–phenomena link commonly used in complexity research. Despite the growing body of research pertaining to a nascent theory of emergence, its central themes are based on a limited theory–model–phenomena conception that does not adequately support those con- ceptual abstractions. Take, for instance, the direct transfer of microscopic concepts to macroscopic levels of analysis. Strengthening the conceptual link beyond metaphori- cal device is essential to a robust process of theory building and holds numerous applications, such as underpinning further social science research and theory-build- ing pursuits. Without an effective isomorphism of theory and structures to real-world behaviour, it is an arguable conclusion that a theory of emergence for human organi- sation does not currently exist. Such is the importance of ontological adequacy and the interchange between conceptual models. It facilitates the practice of interdisci- plinary science that characterises much of complexity research. This paper has identified a range of concerns relating to the ontological adequacy of model-centred conceptions and challenges of instrumental reliability in direct theory–phenomenon conceptions. It is supported by literature demonstrating method- ological selection. This study finds that while the research has been fruitful, major limitations are associated with the direct transfer of concepts to unfamiliar territory without adequate support from a structured model of semantic conceptualisation. For example, while it is accepted that complex systems require continuous importation of energy to achieve the conditions required for emergence, authors apply an incon- sistent understanding of what energy is in this context and how it is imported, trans- ferred and maintained among human agents, instead relying on a direct abstraction from the chemical or molecular world. Such abstractions also suffer from compara- bly low instrumental reliability and the impracticality of studying complex human systems in isolation from their environment. For these reasons, the former McKelvey (1999) model of semantic conception has not been successfully realised within subsequent empirical research. The novel model of semantic conceptualisation offered in this paper enables a stronger conceptual framework to underpin and sup- port further research. A range of possibilities remains in exploring novel applications of emergence and the products of dynamic interaction to extend the existing body of research using formalised computational models and real-world case studies that are tied together by a common thread or conceptual link. Implications and issues The formalisation of multiple models will benefit from the addition of discrete efforts to advance the semantic conceptualisation process, building on the notions of McKelvey (1999) as extended here. Given the nascent stage of various strands of complexity theory (Marion and Uhl-Bien, 2001; Schneider and Somers, 2006), it is probable that semantic conceptualisation will also assist in resolving issues relating to interdisciplinary importation and the conceptual ill-fit problem (Ander- son, 1999; Burnes, 2005). The conceptual model presented in this paper should have broad appeal for researchers interested in multidisciplinary research, and in meso-level and emergent fields where behaviour of a certain kind at one level leads to the genera- tion of structure or form at another level. In relation to future case study selection and practical application, the isomor- phism of the semantic conceptualisation process to real-world scenarios need not be a stifling task. Kauffman (1993) posits that the ingredients necessary for the creation of emergent order may be as simple as a group of heterogeneous agents, a motive to connect and a sufficient number of connections with other agents (McKelvey, 2008). 319 Prometheus Based on this description, locating a complex organisation may be a relatively straightforward process. Adding to this mix is the need for the right conditions, such as the diagnostic use of critical values (or threshold states) above the first critical value (‘edge of order’) and within second value (‘edge of chaos’) (Osborn et al., 2002; McKelvey, 2008), the intermediate of which is somewhat philosophically referred to by Prigogine (1997) as the ‘narrow path’. The model of semantic concep- tualisation can be used in these cases as a tool for multi-paradigmatic bridging and connecting models to explain, with a diverse array of measurement instruments, phenomena of various kinds occurring at multiple levels. Based on this description, locating a complex organisation may be a relatively straightforward process. Adding to this mix is the need for the right conditions, such as the diagnostic use of critical values (or threshold states) above the first critical value (‘edge of order’) and within second value (‘edge of chaos’) (Osborn et al., 2002; McKelvey, 2008), the intermediate of which is somewhat philosophically referred to by Prigogine (1997) as the ‘narrow path’. Implications and issues The model of semantic concep- tualisation can be used in these cases as a tool for multi-paradigmatic bridging and connecting models to explain, with a diverse array of measurement instruments, phenomena of various kinds occurring at multiple levels. References Ablowitz, R. (1939) ‘The theory of emergence’, Philosophy of Science, 6, 1, pp.1–16. A d (1999) ‘C l i h d i i i ’ O S Anderson, P. (1999) ‘Complexity theory and organisation science’, Organisation Science, 10, 3, pp.216–32. Blackler, F., Crump, N. and McDonald, S. (2000) ‘Organising processes in complex activity networks’, Organisation, 7, 2, pp.277–300. Blumer, H. (1954) ‘What is wrong with social theory?’, American Sociological Review, 19, pp.3–10. Brown, S. and Eisenhardt, K. (1997) ‘The art of continuous change: linking complexity the- ory and time-paced evolution in relentlessly shifting organisations’, Administrative Science Quarterly, 42, 1, pp.1–34. Q y, , , pp Burnes, B. (2005) ‘Complexity theories and organisational change’, International Journal Management Reviews, 7, 2, pp.73–90. g , , , pp Burns, J. (1978) Leadership, Harper and Row, New York, NY. Carte, T., Chidambaram, L. and Becker, A. (2006) ‘Emergent leadership in self-managed vir- tual teams: a longitudinal study of concentrated and shared leadership behaviours’, Group Decision and Negotiation, 15, 4, pp.323–43. g , , , pp Checkland, P. (2000) ‘Soft systems methodology: a thirty year retrospective’, Systems Research and Behavioural Science, 17, S1, pp.S11–58. Chiles, T., Meyer, A. and Hench, T. (2004) ‘‘Organisational emergence: the origin and trans- formation of Branson’, Missouri’s musical theatres’, Organisation Science, 15, 5, pp.499–519. pp Cohen, M., March, J. and Olsen, J. (1972) ‘A garbage can model of organisational choice’, Administrative Science Quarterly, 17, 1, pp.1–25. Q y, , , pp Corbin, J. and Strauss, A. (2008) Basics of Qualitative Research, Sage, London. (190 ) ‘ h li f i ’ l f h l h h l Dewey, J. (1905) ‘The realism of pragmatism’, Journal of Philosophy, Psychology and Scie tific Methods, 2, 12, pp.324–27. tific Methods, 2, 12, pp.324–27. Eisenhardt, K. (1989) ‘Building theories from case study research’, Academy of Management Review 14 4 pp 532 50 Eisenhardt, K. (1989) ‘Building theories from case study research’, Academy of Manageme Review, 14, 4, pp.532–50. Geertz, C. (1973) The Interpretation of Cultures, Basic Books, New York, NY. Gioia, M. and Pitre, E. (1990) ‘Multiparadigm perspectives on theory building’, Academy of Management Review, 15, 4, pp.584–602. Goldberg, J. and Markoczy, L. (2000) ‘Complex rhetoric and simple games’, Emergenc Complexity and Organisation, 2, 1, pp.72–100. p y g , , , pp Goldstein, J. (1999) ‘Emergence as a construct: history and issues’, Emergence: Complexity and Organisation, 1, 1, pp.49–72. Conclusion This paper makes a contribution to the execution of a comprehensive programme of semantic conceptualisation, building on previous studies, to support theory–model–phenomena linkages, and ontological adequacy that lead to a wider variety of research methods than proposed by previous O. Yezdani et al. 320 authors. Such a process is supported by a stepwise positioning of semantic conceptu- alisation within the broader frame of a general method for theory-building research. The contemporary method of semantic conceptualisation provided in this paper is recommended for applied social science and theory-building research, particularly in relation to complex and emergent phenomena. Disclosure statement No potential conflict of interest was reported by the authors. ORCID Omer Yezdani http://orcid.org/0000-0001-7908-0979 Louis Sanzogni http://orcid.org/0000-0001-5193-8048 Arthur Poropat http://orcid.org/0000-0002-8496-1815 References g pp Goldstein, J. (2008) ‘Conceptual foundations of complexity science: development and main constructs’ in Uhl-Bien, M. and Marion, R. (eds) Complexity Leadership Part I: Conceptual Foundations, Information Age Publishing, North Carolina, pp.17–48. 321 Prometheus Goldstein, J. (2010) ‘Classic paper: The Theory of Emergence’, Emergence: Complexity a Organisation, 12, 3, pp.133–54. g , , , pp Hannan, M. and Freeman, J. (1984) ‘Structural inertia and organisational change’, Americ Sociological Review, 49, 2, pp.149–64. Hazy, J. (2006) ‘Measuring leadership effectiveness in complex socio-technical systems’, Emergence: Complexity and Organisation, 8, 3, pp.58–77. Hazy, J. (2008) ‘Patterns of leadership: a case study of influence signalling in an entrepre- neurial firm’ in Uhl-Bien, M. and Marion, R. (eds) Complexity Leadership Part I: Conceptual Foundations, Information Age Publishing, North Carolina, pp.379–415. Huygens, M., Baden-Fuller, C., Van Den Bosch, F. and Volberda, H. (2001) ‘Co-evolution of firm capabilities and industry competition: investigating the music industry’, Organisation Studies, 22, 6, pp.971–1011. Johns, N. and Lee-Ross, D. (1998) Research Methods in Service Industry Management, Cassell, London. Juriado, R. and Niklas, G. (2007) ‘Emergent communities of practice in tempora inter-organisational partnerships’, Learning Organisation, 14, 1, pp.50–61. Juriado, R. and Niklas, G. (2007) ‘Emergent communities of practice in temporary inter-organisational partnerships’, Learning Organisation, 14, 1, pp.50–61. Kaczmarski, K. M. and Cooperrider, D. L. (1997) ‘Constructionist leadership in the global Kaczmarski, K. M. and Cooperrider, D. L. (1997) ‘Constructionist leadership in the glob relational age’, Organisation and Environment, 10, 3, pp.235–58. Kauffman, S. (1993) The Origins of Order, Oxford University Press, Oxford. , ( ) g f , y , Kickul, J. and Neuman, G. (2000) ‘Emergent leadership behaviours: the function of personal- ity and cognitive ability in determining teamwork performance and KSAs’, Journal of Business and Psychology, 15, 1, pp.27–51. y gy pp Lee, A. (1989) ‘Case studies as natural experiments’, Human Relations, 42, 2, pp.117–37. Lee, A. (1989) ‘Case studies as natural experiments’, Human Relations, 42, 2, pp.117–37. Levinthal, D. and Warglien, M. (1999) ‘Landscape design: designing for local action in complex worlds’, Organisation Science, 10, 3, pp.342–57. Levinthal, D. and Warglien, M. (1999) ‘Landscape design: designing for local action complex worlds’, Organisation Science, 10, 3, pp.342–57. p , g , , , pp Lewin, K. (1952) ‘Group decision and social change’ in Swanson, G., Newcomb, T. and Hartley, E. (eds) Readings in Social Psychology, Holt, New York, NY, pp.459–73. y ( ) g y gy pp Lichtenstein, B. References Pescosolido, A. (2002) ‘Emergent leaders as managers of group emotion’, Leadership Quarterly, 13, 5, pp.583–99. Plowman, D., Baker, L., Beck, T., Kulkarni, M., Solanski, S. and Travis, D. (2007) ‘Radical change accidentally: the emergence and amplification of small change’, Academy of Management Journal, 50, 3, pp.515–43. g pp Plowman, D. and Duchon, D. (2008) ‘Dispelling the myths about leadership: from cybernet- ics to emergence’ in Uhl-Bien, M. and Marion, R. (eds) Complexity Leadership Part I: Conceptual Foundations, Information Age Publishing, North Carolina, pp.129–52. p g g pp Plowman, D., Solanski, S., Beck, T., Baker, L., Kulkarni, M. and Travis, D. (2007) ‘The role of leadership in emergent self-organisation’, Leadership Quarterly, 18, 4, pp.341–56. P l i M (1968) ‘Lif ’ i d ibl t t ’ S i 160 3834 1308 12 Polanyi, M. (1968) ‘Life’s irreducible structure’, Science, 160, 3834, pp.1308–12. Prietula, M. and Carley, K. (1994) ‘Computational organisation theory: autonomous agents and emergent behaviour’, Journal of Organisational Computing and Electronic Commerce, 4, 1, pp.41–83. , , , pp Prigogine, I. (1997) The End of Certainty: Time, Chaos, and the New Laws of Nature, Fr Press, New York, NY. Prigogine, I. and Stengers, I. (1984) Order out of Chaos, Bantam, New York, NY. Reynolds, C. (1987) ‘Flocks, herds and schools: a distributed behavioural model’, Computer Graphics, 21, 4, pp.25–34. p pp Schneider, M. and Somers, M. (2006) ‘Organisations as complex adaptive systems: implica- tions of complexity theory for leadership research’, Leadership Quarterly, 17, 4, pp.351–65. pp Sellars, R. (1922) Evolutionary Naturalism, Open Court, Chicago, IL. Senge, P. (1990) The Fifth Discipline: The Art and Practice of the Learning Organisatio Doubleday, New York, NY. y Skyttner, L. (2006) General Systems Theory: Problems, Perspectives, Practice, World Scientific, London. Suppe, F. (1989) The Semantic Conception of Theories and Scientific Realism, University of Illinois Press, Champaign IL. Thompson, P. (1988) ‘Explanation in the semantic conception of theory structure’, Proceed- ings of the Biennial Meeting of the Philosophy of Science Association, 1988, 2, pp.286–96. pp Tushman, M. and Anderson, P. (1986) ‘Technological discontinuities and organisational environments’, Administrative Science Quarterly, 31, 3, pp.439–65. l ilki d b ( ) il d Tyler, J., Wilkinson, D. and Huberman, B. (2005) ‘E-mail as spectroscopy: automated discovery of community structure within organisations’, Information Society, 21, 2, pp.133–41. Uhl-Bien, M., Marion, R. and McKelvey, B. References (2000) ‘Self-organised transitions: a pattern amid the chaos of transformative change’, Academy of Management Executive, 14, 4, pp.128–41. Lichtenstein, B. and Plowman, D. (2009) ‘The leadership of emergence: a complex systems leadership theory of emergence at successive organisational levels’, Leadership Quarterly, 20, 4, pp.617–30. pp Lichtenstein, B., Uhl-Bien, M., Marion, R., Seers, A., Orton, J. and Schreiber, C. (2006) ‘Complexity leadership theory: an interactive perspective on leading in complex adaptive systems’, Emergence: Complexity and Organisation, 8, 4, pp.2–12. Lynham, S. (2000) ‘Theory building in the human resource development profession’, Hum Resource Development Quarterly, 11, 2, pp.159–78. Lynham, S. (2002) ‘The general method of applied theory building research’, Advances in Developing Human Resources, 4, 3, pp.221–41. p g pp Macintosh, R. and Maclean, D. (1999) ‘Conditioned emergence: a dissipative structures approach to transformation’, Strategic Management Journal, 20, 4, pp.297–316. March, J. (1991) ‘Exploration and exploitation in organisational learning’, Organisation Science, 2, 1, pp.71–87. Marion, R. (2008) ‘Complexity theory for organisations and organisational leadership’ in Uhl-Bien, M. and Marion, R. (eds) Complexity Leadership Part I: Conceptual Foundations, Information Age Publishing, North Carolina, pp.1–16. , g g, , pp Marion, R. and Uhl-Bien, M. (2001) ‘Leadership in complex organisations’, Leadership Quarterly, 12, pp.389–418. Q y pp McKelvey, B. (1999) ‘Complexity theory in organisation science: seizing the promise or becoming a fad?’, Emergence: Complexity and Organisation, 1, 1, pp.5–32. McKelvey, B. (2008) ‘Emergent strategy via complexity leadership: using complexity science and adaptive tension to build distributed intelligence’ in Uhl-Bien, M. and Marion, R. (eds) Complexity Leadership Part I: Conceptual Foundations, Information Age Publish- ing, North Carolina, pp.225–68. McKendrick, D., Jaffee, J., Carroll, G. and Khessina, O. (2003) ‘In the bud? Disk array pro- ducers as a (possibly) emergent organisational form’, Administrative Science Quarterly, 48, 1, pp.60–93. , , pp Mintzberg, H. (1994) The Rise and Fall of Strategic Planning, Free Press, New York, NY. O. Yezdani et al. 322 Moldoveanu, M. and Bauer, R. (2004) ‘On the relationship between organisational complexity and organisational structuration’, Organisation Science, 15, 1, pp.98–118. p y g , g , , , pp Morgan, G. (1998) Images of Organisation, Berrett-Koehler Publishers, Oakland, CA. g ( ) g f g Nicolis, G. and Prigogine, I. (1977) Self-Organisation in Non-equilibrium Systems: From Dissipative Structures to Order through Fluctuations, Wiley, New York, NY. Osborn, R., Hunt, J. and Jauch, L. (2002) ‘Toward a contextual theory of leadership’, Leadership Quarterly, 13, 6, pp.797–837. References (2007) ‘Complexity leadership theory: shifting leadership from the industrial-age to the knowledge-era’, Leadership Quarterly, 18, 4, pp.298–318. pp Van de Ven, A. (1989) ‘Nothing is quite so practical as a good theory’, Academy Management Review, 14, 4, pp.486–89. g pp Weiner, N. (1948) Cybernetics: or Control and Communication in the Animal and t Machine, Wiley, New York, NY. y Wheatley, M. (1999) Leadership and the New Science, Berrett-Koehler, San Francisco. Zott, C. (2003) ‘Dynamic capabilities and the emergence of intra-industry differential firm performance: insights from a simulation study’, Strategic Management Journal, 24, 2, pp.97–125.
https://openalex.org/W2789325074
https://digitalcommons.mtu.edu/cgi/viewcontent.cgi?article=2861&context=michigantech-p
English
null
Methods to Improve Survival and Growth of Planted Alternative Species Seedlings in Black Ash Ecosystems Threatened by Emerald Ash Borer
Forests
2,018
cc-by
8,331
Digital Commons @ Michigan Tech Michigan Technological University Michigan Technological University Digital Commons @ Michigan Tech Digital Commons @ Michigan Tech Michigan Tech Publications 3-16-2018 Methods to improve survival and growth of planted alternative Methods to improve survival and growth of planted alternative species seedlings in black ash ecosystems threatened by emerald species seedlings in black ash ecosystems threatened by emerald ash borer ash borer Nicholas Bolton Michigan Technological University, nwbolton@mtu.edu Joseph Shannon Michigan Technological University, jpshanno@mtu.edu Joshua Davis Michigan Technological University, joshuad@mtu.edu Matthew J. Van Grinsven Michigan Technological University Nam Jin Noh Michigan Technological University, nnoh@mtu.edu See next page for additional authors Follow this and additional works at: https://digitalcommons.mtu.edu/michigantech-p Part of the Forest Sciences Commons Recommended Citation Recommended Citation Bolton, N., Shannon, J., Davis, J., Van Grinsven, M. J., Noh, N., Schooler, S., Kolka, R., Pypker, T., & Wagenbrenner, J. (2018). Methods to improve survival and growth of planted alternative species seedlings in black ash ecosystems threatened by emerald ash borer. Forests, 9(3), 146. http://doi.org/ 10.3390/f9030146 Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/1869 F ll hi d ddi i l k h //di i l d / i hi h Digital Commons @ Michigan Tech Michigan Technological University Michigan Technological University Digital Commons @ Michigan Tech Digital Commons @ Michigan Tech Michigan Tech Publications 3-16-2018 Methods to improve survival and growth of planted alternative Methods to improve survival and growth of planted alternative species seedlings in black ash ecosystems threatened by emerald species seedlings in black ash ecosystems threatened by emerald ash borer ash borer Nicholas Bolton Michigan Technological University, nwbolton@mtu.edu Joseph Shannon Michigan Technological University, jpshanno@mtu.edu Joshua Davis Michigan Technological University, joshuad@mtu.edu Matthew J. Van Grinsven Michigan Technological University Nam Jin Noh Michigan Technological University, nnoh@mtu.edu See next page for additional authors Follow this and additional works at: https://digitalcommons.mtu.edu/michigantech-p Part of the Forest Sciences Commons Recommended Citation Recommended Citation Bolton, N., Shannon, J., Davis, J., Van Grinsven, M. J., Noh, N., Schooler, S., Kolka, R., Pypker, T., & Wagenbrenner, J. (2018). Methods to improve survival and growth of planted alternative species seedlings in black ash ecosystems threatened by emerald ash borer. Forests, 9(3), 146. http://doi.org/ 10.3390/f9030146 Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/1869 Follow this and additional works at: https://digitalcommons.mtu.edu/michigantech-p Part of the Forest Sciences Commons Michigan Technological University Michigan Technological University Digital Commons @ Michigan Tech Digital Commons @ Michigan Tech Michigan Tech Publications Part of the Forest Sciences Commons Part of the Forest Sciences Commons Recommended Citation Recommended Citation Bolton, N., Shannon, J., Davis, J., Van Grinsven, M. J., Noh, N., Schooler, S., Kolka, R., Pypker, T., & Wagenbrenner, J. (2018). Methods to improve survival and growth of planted alternative species seedlings in black ash ecosystems threatened by emerald ash borer. Forests, 9(3), 146. http://doi.org/ 10.3390/f9030146 Follow this and additional works at: https://digitalcommons.mtu.edu/michigantech-p Follow this and additional works at: https://digitalcommons.mtu.edu/michigantech-p Part of the Forest Sciences Commons Part of the Forest Sciences Commons Nicholas Bolton, Joseph Shannon, Joshua Davis, Matthew J. Van Grinsven, Nam Jin Noh, Shon Schooler, Randall K Kolka, Thomas Pypker, and Joseph Wagenbrenner Authors Authors Nicholas Bolton, Joseph Shannon, Joshua Davis, Matthew J. Van Grinsven, Nam Jin Noh, Shon Schooler, Randall K Kolka, Thomas Pypker, and Joseph Wagenbrenner This article is available at Digital Commons @ Michigan Tech: https://digitalcommons.mtu.edu/mich This article is available at Digital Commons @ Michigan Tech: https://digitalcommons.mtu.edu/michigantech-p/1869 Methods to Improve Survival and Growth of Pl Alternative Species Seedlings in Black Ash Ecosystems Threatened by Emerald Ash Borer Nicholas Bolton 1,2,* ID , Joseph Shannon 1 ID , Joshua Davis 1 ID , Matthew Van Grinsven 1,3 ID , Nam Jin Noh 1,4 ID , Shon Schooler 5, Randall Kolka 6, Thomas Pypker 7 and Joseph Wagenbrenner 1,8 Nicholas Bolton 1,2,* ID , Joseph Shannon 1 ID , Joshua Davis 1 ID , Matthew Van Grinsven 1,3 ID , Nam Jin Noh 1,4 ID , Shon Schooler 5, Randall Kolka 6, Thomas Pypker 7 and Joseph Wagenbrenner 1,8 1 School of Forest Resources & Environmental Science, Michigan Technological University, Houghton, MI 49931, USA; jpshanno@mtu.edu (J.S.) joshuad@mtu.edu (J.D.); mvangrin@nmu.edu (M.V.G.); n.noh@westernsydney.edu.au (N.J.N.); jwagenbrenner@fs.fed.us (J.W.) 1 School of Forest Resources & Environmental Science, Michigan Technological University, Houghton, MI 49931, USA; jpshanno@mtu.edu (J.S.) joshuad@mtu.edu (J.D.); mvangrin@nmu.edu (M.V.G.); n.noh@westernsydney.edu.au (N.J.N.); jwagenbrenner@fs.fed.us (J.W.) 2 Daniel B. Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602, USA 3 Department of Earth, Environment, & Geosciences, Northern Michigan University, Marquette, MI 49855, USA 2 Daniel B. Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602, USA 3 Department of Earth, Environment, & Geosciences, Northern Michigan University, Marquette, MI 49855, USA 4 Hawkesbury Institute for the Environment, Western Sydney University, Richmond, NSW 2753, Australia 5 Lake Superior National Estuarine Research Reserve, University of Wisconsin-Superior, Superior, WI 54880, USA; sschoole@uwsuper.edu y , y y y, , , 5 Lake Superior National Estuarine Research Reserve, University of Wisconsin-Superior, Superior, WI 54880, USA; sschoole@uwsuper.edu p 6 USDA (United States Department of Agriculture) Forest Service, Northern Research Station, Grand Rapids, MN, 55744, USA; rkolka@fs.fed.us 7 Department of Natural Resource Sciences, Thompson Rivers University, Kamloops, BC V2C 0C8, Canada; TPypker@tru.ca yp 8 USDA (United States Department of Agriculture) Forest Service, Pacific Southwest Research Station, Arcata, CA 95521, USA * Correspondence: Nicholas.Bolton@uga.edu Received: 22 February 2018; Accepted: 14 March 2018; Published: 16 March 2018 Abstract: Emerald ash borer (EAB) continues to spread across North America, infesting native ash trees and changing the forested landscape. Black ash wetland forests are severely affected by EAB. As black ash wetland forests provide integral ecosystem services, alternative approaches to maintain forest cover on the landscape are needed. We implemented simulated EAB infestations in depressional black ash wetlands in the Ottawa National Forest in Michigan to mimic the short-term and long-term effects of EAB. These wetlands were planted with 10 alternative tree species in 2013. Keywords: EAB; Fraxinus nigra; underplanting; mitigation; microsite 1. Introduction Since the confirmation of emerald ash borer ((EAB) Agrilus planipennis Fairmaire (Coleoptera: Buprestidae)) in 2002 [1,2], quarantine zones and other management recommendations have not slowed the pace of EAB infestation and it has spread across 31 American states and two Canadian provinces (Emerald Ash Borer Information Network 2017). It is projected that the invasive exotic insect will continue to move across North America, continuing to alter forest landscapes by killing host ash (Fraxinus spp.) trees [3]. While some studies indicate that there are certain ash trees that may be resistant despite the infested condition of the surrounding forest [4], EAB-induced mortality in ash species in infested forests is approximately 99% [5]. The outlook for North American ash trees is bleak as the confirmed range of EAB continues to expand. One forested ecosystem that is severely impacted by EAB’s continued expansion is black ash (Fraxinus nigra Marsh) wetlands. Black ash grows in three ecotypes of the Upper Great Lakes region: depressional headwater catchments, wetland complexes, and riparian corridors [6,7]. All three of these ecotypes have prolonged periods of inundation or saturation throughout the growing season, the time of year when precipitation and temperature are conducive to plant growth. These wetland forest systems provide many ecosystem services. For example, black ash forested wetlands provide habitat and food sources for game birds, small animals, and deer [7], the canopy reduces heat input into streams [8,9], and the root structure maintains soil integrity during rain events, reducing erosion and sediment deposition downstream [10,11]. Current theories predict that cover type changes after EAB infestation will lead to loss of the tree canopy on the landscape and forested wetlands in the short-term will become dominated by a robust herbaceous community [12] and in the long-term possibly a shrub layer consisting of alder (Alnus spp.) [13,14]. Planting alternative species within black ash wetlands may be an approach to shift forest composition towards one that will be more resilient to EAB, thereby maintaining ecosystem services provided by forested wetlands. However, artificial regeneration within northern wetlands is a difficult task because of the unique conditions and climate stresses on seedlings [15,16]. For instance, a seedling planted within the region will endure a dramatic annual temperature swing and periods of time when standing water is prevalent. Methods to Improve Survival and Growth of Pl Alternative Species Seedlings in Black Ash Ecosystems Threatened by Emerald Ash Borer Based on initial results in the Michigan sites, a riparian corridor in the Superior Municipal Forest in Wisconsin was planted with three alternative tree species in 2015. Results across both locations indicate that silver maple (Acer saccharinum L.), red maple (Acer rubrum L.), American elm (Ulmus americana L.), and northern white cedar (Thuja occidentalis L.) are viable alternative species to plant in black ash-dominated wetlands. Additionally, selectively planting on natural or created hummocks resulted in two times greater survival than in adjacent lowland sites, and this suggests that planting should be implemented with microsite selection or creation as a primary control. Regional landowners and forest managers can use these results to help mitigate the canopy and structure losses from EAB and maintain forest cover and hydrologic function in black ash-dominated wetlands after infestation. Keywords: EAB; Fraxinus nigra; underplanting; mitigation; microsite Forests 2018, 9, 146; doi:10.3390/f9030146 www.mdpi.com/journal/forests Forests 2018, 9, 146 2 of 11 1. Introduction A recent study in northern Minnesota investigated planting in black ash wetland complexes in tandem with forest management practices [17], and their results highlighted a low survivorship among seedlings. In this study, we used simulated EAB infestations to determine the impacts of EAB on tree seedling survival and used the initial results to subsequently test alternative planting techniques in uninfested ash forests. Our objectives were to (i) compare survival rates among deciduous and coniferous tree seedlings in black ash wetlands where manipulated overstory treatments reflected the timing of EAB infestation, and (ii) compare microsite and herbivory treatments to inform best practices for future plantings to mitigate EAB impact on forest canopy and structure. 2.1. Ottawa National Forest Site Description 2.1. Ottawa National Forest Site Description Three depressional wetland study sites were located in the Ottawa National Forest of the western Upper Peninsula of Michigan, USA (Figure 1, ). Study site elevations ranged from 371 to 507 m, areas ranged from 0.25 to 1.2 ha, and soils were comprised of Histosols with the depth to clay lens or bedrock between 40 and 480 cm (Table 1). Mean annual precipitation was 836 mm and mean temperatures ranged from −15.7 °C in January to 18.1 °C in July. Study site canopies were dominated by black ash with lesser amounts of red maple (Acer rubrum L.), yellow birch (Betula alleghaniensis Britton), northern white cedar (Thuja occidentalis L.), and balsam fir (Abies balsamea L. (Mill)). Three depressional wetland study sites were located in the Ottawa National Forest of the western Upper Peninsula of Michigan, USA (Figure 1, ). Study site elevations ranged from 371 to 507 m, areas ranged from 0.25 to 1.2 ha, and soils were comprised of Histosols with the depth to clay lens or bedrock between 40 and 480 cm (Table 1). Mean annual precipitation was 836 mm and mean temperatures ranged from −15.7 ◦C in January to 18.1 ◦C in July. Study site canopies were dominated by black ash with lesser amounts of red maple (Acer rubrum L.), yellow birch (Betula alleghaniensis Britton), northern white cedar (Thuja occidentalis L.), and balsam fir (Abies balsamea L. (Mill)). Table 1. Treatment and planting years, soil type [18], elevation, and canopy characteristics on the Ottawa National Forest (ONF) and Superior Municipal Forest (SMF) study wetlands. Site Percent Canopy Black Ash (%) Planting Year Soil Type Elevation (m) Canopy Openness (%) ONF Control 48 2013 Woody peat Histosol 507 19.7 ONF Girdle 88 2013 Woody peat Histosol 499 16.5 ONF Ash-Cut 38 2013 Woody peat Histosol 371 6.6 SMF 90 2015 Arnheim mucky silt loam or Udifluvents 183 Closed–open 2 2 Ottawa National Forest Study Design Table 1. Treatment and planting years, soil type [18], elevation, and canopy characteristics on the Ottawa National Forest (ONF) and Superior Municipal Forest (SMF) study wetlands. Site Percent Canopy Black Ash (%) Planting Year Soil Type Elevation (m) Canopy Openness (%) ONF Control 48 2013 Woody peat Histosol 507 19.7 ONF Girdle 88 2013 Woody peat Histosol 499 16.5 ONF Ash-Cut 38 2013 Woody peat Histosol 371 6.6 SMF 90 2015 Arnheim mucky silt loam or Udifluvents 183 Closed–open 2.2. 2. Materials and Methods This study consisted of three black ash wetlands that were part of an overstory manipulation study located on the Ottawa National Forest (ONF) and one uninfested black ash riparian corridor located on the Superior Municipal Forest (SMF) (Figure 1). There was some overlap in alternative species planted and details for each forest are presented below. 3 of 11 3 of 11 Forests 2018, 9, 146 Fo e t 2018 9 FOR Figure 1. Map of the Great Lakes region with the three study locations in the Ottawa National Forest (), in the western Upper Peninsula of Michigan, and the one study location in the Superior Municipal Forest (), in northwestern Wisconsin. The shaded region is the Great Lakes Watershed with United States and Canadian boundaries. Figure 1. Map of the Great Lakes region with the three study locations in the Ottawa National Forest ( ), in the western Upper Peninsula of Michigan, and the one study location in the Superior Municipal Forest (▲), in northwestern Wisconsin. The shaded region is the Great Lakes Watershed with United States and Canadian boundaries. Figure 1. Map of the Great Lakes region with the three study locations in the Ottawa National Forest (), in the western Upper Peninsula of Michigan, and the one study location in the Superior Municipal Forest (), in northwestern Wisconsin. The shaded region is the Great Lakes Watershed with United States and Canadian boundaries. Figure 1. Map of the Great Lakes region with the three study locations in the Ottawa National Forest ( ), in the western Upper Peninsula of Michigan, and the one study location in the Superior Municipal Forest (▲), in northwestern Wisconsin. The shaded region is the Great Lakes Watershed with United States and Canadian boundaries. 2.1. Ottawa National Forest Site Description 2.1. Ottawa National Forest Site Description Ottawa National Forest Study Design Table 1. Treatment and planting years, soil type [18], elevation, and canopy characteristics on the Ottawa National Forest (ONF) and Superior Municipal Forest (SMF) study wetlands. Table 1. Treatment and planting years, soil type [18], elevation, and canopy characteristics on the Ottawa National Forest (ONF) and Superior Municipal Forest (SMF) study wetlands. Table 1. Treatment and planting years, soil type [18], elevation, and canopy characteris Ottawa National Forest (ONF) and Superior Municipal Forest (SMF) study wetlands. Table 1. Treatment and planting years, soil type [18], elevation, and canopy characteris Ottawa National Forest (ONF) and Superior Municipal Forest (SMF) study wetlands. p g y , yp [ ], , py Ottawa National Forest (ONF) and Superior Municipal Forest (SMF) study wetlands Ottawa National Forest (ONF) and Superior Municipal Forest (SMF) study wetlands 2.3. Superior Municipal Forest Site Description 2.3. Superior Municipal Forest Site Description The study area was along the riparian corridor of the Pokegama River that meanders through the Superior Municipal Forest in northwestern Wisconsin, USA (Figure 1, ▲). Soils were one of two distinct types: a sandy berm adjacent to the river that was created by deposits of coarse sediment, and clay-loams in adjacent lowland “back bays” (Table 1). The riparian corridor overstory was comprised of black ash and green ash (Fraxinus pennsylvanica Marsh) with lesser amounts of northern white cedar, balsam fir, and trembling aspen (Populus tremuloides Michx.). Forests 2018, 9, 146 Forests 2018, 9, 146 4 of 11 Forests 2018, 9, 146 Ottawa National Forest study wetlands were planted with ten tree species suitable for saturated soils in summer 2013 (Table 2). Seedling ages ranged from two to four years and were purchased from the USDA (United States Department of Agriculture) Forest Service J.W. Toumey Nursery in Watersmeet, MI, USA. A series of ten transects were established across each wetland and seedlings were planted in pairs in high (hummock) and low (hollow) planting microsites within 1 m every 2 m along each transect, totaling 60 trees of each species in each wetland. Seedings were measured each year of the study during the last week of July. Table 2. Ottawa National Forest species and seedling ages and planting stock type (BR—bare root, P—plug). Common Name Scientific Name Age (Years) Stock Type American elm Ulmus Americana L. 2 P basswood (linden) Tilia americana L. 3 BR burr oak Quercus macrocarpa Michx. 3 BR red maple Acer rubrum L. 2 BR silver maple Acer saccharinum L. 4 BR yellow birch Betula alleghaniensis Britton 2 P balsam fir Abies balsamea (L.) Mill 2 BR black spruce Picea marina (Mill.) Britton 2 P northern white cedar Thuja occidentalis L. 2 P tamarack Larix larcinia K. Koch 2 BR 2.3. Superior Municipal Forest Site Description Table 2. Ottawa National Forest species and seedling ages and planting stock type (BR—bare root, P—plug). 2 2 Ottawa National Forest Study Design 2.2. Ottawa National Forest Study Design 2 2 Ottawa National Forest Study Design 2.2. Ottawa National Forest Study Design 2.2. Ottawa National Forest Study Design Treatments in the three wetlands were an untreated control (“Control”), girdling (“Girdle”), and felling of black ash (“Ash-Cut”). All black ash greater than 2.5 cm in diameter were treated in the Girdle and Ash-Cut wetlands. This is a similar design to a sister-study [12] and our intention for the Girdle treatment was to simulate the short-term impacts of an EAB infestation, while the Ash-Cut treatment simulated the long-term impacts of EAB infestation [1] Treatments in the three wetlands were an untreated control (“Control”), girdling (“Girdle”), and felling of black ash (“Ash-Cut”). All black ash greater than 2.5 cm in diameter were treated in the Girdle and Ash-Cut wetlands. This is a similar design to a sister-study [12] and our intention for the Girdle treatment was to simulate the short-term impacts of an EAB infestation, while the Ash-Cut treatment simulated the long-term impacts of EAB infestation [1]. 2.4. Superior Municipal Forest Study Design Tree species were chosen for their suitability in saturated or inundated soils as well as their projected range within forecasted climate models [19]. Seedling species were red maple, hackberry (Celtis occidentalis L.), and northern white cedar (Table 3) obtained from the Wisconsin Department of Natural Resources nursery in Hayward, WI, USA. Planting groups were established in different microsite, herbivory deterrence, and elevational conditions. The three microsite conditions were natural flat areas (“Natural”), constructed hummocks (“Con. Hummock”), and cleared soil (“Scarification”). The constructed hummocks were created by placing a shovel-blade full of local soil on top of the forest floor and then fortifying it by covering it with burlap matting. The cleared planting locations were created by removing existing vegetation with a spade. Table 3. Superior Municipal Forest species and seedling ages and planting stock type (BR—bare root, P—plug). Common Name Scientific Name Age (Years) Stock Type hackberry Celtis occidentalis L. 2 BR red maple Acer rubrum L. 2 BR northern white cedar Thuja occidentalis L. 2 BR The three herbivore exclusion treatments were no treatment (“Control”), herbivore repellant (“Repellant”) (Plantskydd®, Tree World Plant Care Products Inc., St. Joseph, MO, USA) and fencing 3. Superior Municipal Forest species and seedling ages and planting stock type (BR—bare root, ug) Table 3. Superior Municipal Forest species and seedling ages and planting stock type (BR—bare root, P—plug). Table 3. Superior Municipal Forest species and seedling ages and planting stock type (BR—bare root, P—plug). Common Name Scientific Name Age (Years) Stock Type hackberry Celtis occidentalis L. 2 BR red maple Acer rubrum L. 2 BR northern white cedar Thuja occidentalis L. 2 BR The three herbivore exclusion treatments were no treatment (“Control”), herbivore repellant (“Repellant”) (Plantskydd®, Tree World Plant Care Products Inc., St. Joseph, MO, USA) and fencing The three herbivore exclusion treatments were no treatment (“Control”), herbivore repellant (“Repellant”) (Plantskydd®, Tree World Plant Care Products Inc., St. Joseph, MO, USA) and fencing 5 of 11 Forests 2018, 9, 146 (“Fence”). The herbivore repellant was applied in the spring and fall each year following manufacturer instructions and fenced planting locations were 1.3 m tall. Each combination of microsite (3) and tree species (3) was replicated 36 times in a low elevation and 36 times in a high elevation planting zone, each approximately parallel to the river channel. One-third, or 12 planting groups per elevation zone, were assigned an herbivore treatment. 2.4. Superior Municipal Forest Study Design Each of the 72 planting groups had three seedlings of each of the three species, for a total of nine seedlings per group or 648 seedlings. Seedlings were planted in fall 2015. Seedlings were measured each spring and fall for each year of the study period. 2.5. Field and Laboratory Procedures Field measurements included seedling height and root collar diameter, microsite characteristics including hummock material (mineral soil or coarse woody debris and decay class), mortality, and disease. When cause of death was clear (e.g., fungus), it was recorded. Canopy openness for the ONF study was measured during the early morning, late evening, or under cloudy conditions in early July 2015 using hemispherical photography (Nikon P5000, Nikon FC-E8 fisheye lens, Nikon, Tokyo, Japan). Nine digital photographs were processed using WinSCANOPY software (Pro Version, 2010, Regent Instruments, Inc., Quebec, QC, Canada) [20] and were averaged for each planting site. Canopy openness for the SMF study was categorized from visual observations as one of three coverages: open, partial, or closed canopy and the canopy composition was recorded. 2.6. Analysis Differences in seedling establishment and survivorship among groups of species, microsite, and treatment were tested for significance using contingency tables via Fisher’s exact test. Analysis of variance (ANOVA) was used to assess species growth metrics, and relative height and diameter (calculated by RH/RD = (W2 −W1)/(W1/(t2 −t1)); where RH = relative height, RD = relative diameter, W = size, and t = time), among treatment, microsite, herbivore deterrent, zone, and canopy openness. Significance level was 0.05 for all statistical tests. All statistical analyses were performed using R: A Language and Environment for Statistical Computing (Version 3.3.1, 2016, R Foundation for Statistical Computing, Vienna, Austria) [21]. 3.1. Ottawa National Forest The planting year experienced elevated water tables throughout the growing season because of an unusually high snow pack and delayed snowmelt [22]. Additionally, standing water was present during the initial growing season at intermittent times due to high intensity rain storms [22]. Overall seedling survival across all treatments and microsites (n = 1800) after the first winter for the ONF planting study was 36% and after three years 22% of the planted seedlings survived. The second- and third-year survivorship was significantly higher than seedling establishment. Overall seedling survivorship from years 1–2 and years 2–3 was 75% and 87%, respectively. The hardwood species with the highest survivorship across the study period were silver maple, American elm, and basswood with 74%, 53%, and 40%, respectively (Table 4). The softwood species with the highest survivorship across the study period was northern white cedar at 23% (Table 4). None of the tamarack survived the 3-year study period. We found no statistical difference in seedling survival or growth from bare root stock or plug seedlings. Initial survival rates for seedlings planted on hummocks and hollows were 44% and 29%, respectively. Over the course of the study, seedlings planted on hummocks survived better than those planted in hollows (Table 4). On average, there was a 19% (range: 4–47%) greater rate of survival than the corresponding paired seedling in the hollow over the 3-year span. However, of the top performing species, only silver maple did not display a preference between hummock or hollow and survived well on both microsites after three years with 76% and 72% survival, respectively. The ONF results indicate that survivorship and growth were not statistically different when canopy treatment was compared. 6 of 11 Forests 2018, 9, 146 Table 4. Three-year mean seedling survival rate, relative height growth, and relative diameter growth across all treatments by microsite hummock and hollow for each planted species in the Ottawa National Forest study. Statistical significance indicated (*) for hummock vs. hollow comparisons within species for survival. Standard deviations are indicated by ± for height and diameter. Forests 2018, 9, x FOR PEER REVIEW 6 of 11 Table 4. 3.1. Ottawa National Forest Three-year mean seedling survival rate, relative height growth, and relative diameter growth across all treatments by microsite hummock and hollow for each planted species in the Ottawa Species Microsite Survival (%) Relative Height Growth (cm) Relative Diameter Growth (cm) American elm Hummock 68 * 6.4 ± 15.0 0.1 ± 0.1 Hollow 38 3.5 ± 10.4 0.1 ± 0.1 Basswood (linden) Hummock 64 * 2.2 ± 16.0 0.1 ± 0.3 Hollow 17 −0.1 ± 6.3 0.0 ± 0.2 burr oak Hummock 38 * −1.2 ± 7.6 0.0 ± 0.3 Hollow 11 0.4 ± 2.4 0.0 ± 0.1 red maple Hummock 11 * 0.2 ± 5.8 0.0 ± 0.2 Hollow 2 0.1 ± 1.0 0.0 ± 0.0 silver maple Hummock 76 4.2 ± 14.7 0.1 ± 0.2 Hollow 72 7.1 ± 17.1 0.1 ± 0.3 yellow birch Hummock 8 * −0.3 ± 4.0 0.0 ± 0.1 Hollow 0 - - balsam fir Hummock 7 * 0.2 ± 1.4 0.0 ± 0.0 Hollow 0 - - black spruce Hummock 13 * 0.9 ± 2.9 0.0 ± 0.1 Hollow 2 0.3 ± 1.9 0.0 ± 0.0 northern white cedar Hummock 39 * 2.8 ± 6.1 0.1 ± 0.2 Hollow 8 0.3 ± 2.6 0.3 ± 2.6 tamarack Hummock 0 - - Hollow 0 - - * Statistical significance at p = 0.05 level. National Forest study. Statistical significance indicated ( ) for hummock vs. hollow comparisons within species for survival. Standard deviations are indicated by ± for height and diameter. 3.1. Ottawa National Forest Species Microsite Survival (%) Relative Height Growth (cm) Relative Diameter Growth (cm) American elm Hummock 68 * 6.4 ± 15.0 0.1 ± 0.1 Hollow 38 3.5 ± 10.4 0.1 ± 0.1 Basswood (linden) Hummock 64 * 2.2 ± 16.0 0.1 ± 0.3 Hollow 17 −0.1 ± 6.3 0.0 ± 0.2 burr oak Hummock 38 * −1.2 ± 7.6 0.0 ± 0.3 Hollow 11 0.4 ± 2.4 0.0 ± 0.1 red maple Hummock 11 * 0.2 ± 5.8 0.0 ± 0.2 Hollow 2 0.1 ± 1.0 0.0 ± 0.0 silver maple Hummock 76 4.2 ± 14.7 0.1 ± 0.2 Hollow 72 7.1 ± 17.1 0.1 ± 0.3 yellow birch Hummock 8 * −0.3 ± 4.0 0.0 ± 0.1 Hollow 0 - - balsam fir Hummock 7 * 0.2 ± 1.4 0.0 ± 0.0 Hollow 0 - - black spruce Hummock 13 * 0.9 ± 2.9 0.0 ± 0.1 Hollow 2 0.3 ± 1.9 0.0 ± 0.0 northern white cedar Hummock 39 * 2.8 ± 6.1 0.1 ± 0.2 Hollow 8 0.3 ± 2.6 0.3 ± 2.6 tamarack Hummock 0 - - Hollow 0 - - * St ti ti l i ifi t 0 05 l l * Statistical significance at p = 0.05 level. Hollow 0 - Average 3-year relative height growth for all the species except tamarack was 1.3 cm. Three-year relative height growth for six of these species was significantly higher for seedlings planted on hummocks compared to seedlings planted in hollows. In contrast, silver maple and burr oak relative growth rates were greater for hollow microsites than hummocks (Figure 2a). Average relative diameter growth across the study period was 0.3 cm, and northern white cedar planted on hummocks had the greatest increase in diameter, but the growth was highly variable (Table 3, Figure 2b). Statistical significance at p 0.05 level. Average 3-year relative height growth for all the species except tamarack was 1.3 cm. Three-year relative height growth for six of these species was significantly higher for seedlings planted on hummocks compared to seedlings planted in hollows. In contrast, silver maple and burr oak relative growth rates were greater for hollow microsites than hummocks (Figure 2a). Average relative diameter growth across the study period was 0.3 cm, and northern white cedar planted on hummocks had the greatest increase in diameter, but the growth was highly variable (Table 3, Figure 2b). (a) (b) Figure 2. 3.1. Ottawa National Forest (a) Relative growth of height (cm) and (b) diameter (cm) of the 10 wetland-adapted tree species (American elm, basswood, burr oak, red maple, silver maple, yellow birch, balsam fir, black spruce, northern white cedar, tamarack) planted across three black ash-dominated wetlands in the Ottawa National Forest over the 3-year study period. The bars represent the mean relative growth rate for each species by microsite condition. The error bars represent ± one standard error. Figure 2. (a) Relative growth of height (cm) and (b) diameter (cm) of the 10 wetland-adapted tree species (American elm, basswood, burr oak, red maple, silver maple, yellow birch, balsam fir, black spruce, northern white cedar, tamarack) planted across three black ash-dominated wetlands in the Ottawa National Forest over the 3-year study period. The bars represent the mean relative growth rate for each species by microsite condition. The error bars represent ± one standard error. (b) (a) (b) (a) Figure 2. (a) Relative growth of height (cm) and (b) diameter (cm) of the 10 wetland-adapted tree species (American elm, basswood, burr oak, red maple, silver maple, yellow birch, balsam fir, black spruce, northern white cedar, tamarack) planted across three black ash-dominated wetlands in the Ottawa National Forest over the 3-year study period. The bars represent the mean relative growth rate for each species by microsite condition. The error bars represent ± one standard error. Figure 2. (a) Relative growth of height (cm) and (b) diameter (cm) of the 10 wetland-adapted tree species (American elm, basswood, burr oak, red maple, silver maple, yellow birch, balsam fir, black spruce, northern white cedar, tamarack) planted across three black ash-dominated wetlands in the Ottawa National Forest over the 3-year study period. The bars represent the mean relative growth rate for each species by microsite condition. The error bars represent ± one standard error. Forests 2018, 9, 146 7 of 11 7 of 11 3.2. Superior Municipal Forest The growing season monthly temperature (mean 14.8 ◦C, range 9.4–19.4 ◦C) and precipitation (mean 7.3 cm, range 4.0–11.5 cm) were within the 30-year average for the Superior, Wisconsin region National Oceanic Atmospheric Administration. In contrast to the relatively low first-year survival rates on the ONF, the overall mean seedling survival across all treatments and microsites at SMF was 82% one year after planting and 54% two years after planting. Red maple had a two-year survival rate of 63%, hackberry’s survival rate was 62%, and northern white cedar’s survival rate was 38% (Table 5). Table 5. Two-year mean seedling survival rate, height, and diameter across all treatments by microsite constructed hummock (CH), natural (N), and scarification (S) for each planted species in the Superior Municipal Forest study. There were no significant differences in seedling survival, relative height growth, and relative diameter growth. Species Microsite Survival (%) Relative Height Growth (cm) Relative Diameter Growth (cm) hackberry CH 66 −0.1 ± 14.6 0.4 ± 5.6 N 60 −0.9 ± 11.9 −0.6 ± 1.8 S 58 −1.0 ± 10.4 −0.6 ± 1.7 red maple CH 68 12.2 ± 20.9 0.2 ± 1.8 N 57 10.9 ± 19.9 −0.5 ± 1.8 S 63 6.4 ± 14.1 −0.6 ± 1.2 northern white cedar CH 39 −1.2 ± 7.9 0 ± 1.4 N 43 0.2 ± 5.6 −0.1 ± 1.3 S 32 0.3 ± 9.7 −0.1 ± 1.9 For the SMF study, there were no statistical differences in survivorship or growth among any of our study factors: species, microsite, herbivore exclusion, and zones; therefore, we pooled the planting data and report the results here. There were no statistical differences in survivorship among browse treatments when species were pooled (mean 54%, range 39–65%). Similarly, there were no statistical differences in survivorship between the elevation zones (both 54%) despite the presence of standing water for most lower elevation (Zone 2) seedlings at the time of the 2017 measuring campaign. There were no differences among the microsite treatments when species were pooled (mean 54%, range 51–58%). Height growth for red maple was positive while hackberry showed no growth and northern white cedar decreased in height over the study period (Table 5). Average height growth for red maple was 9 cm, hackberry 0 cm, and northern white cedar −2 cm. 4. Discussion Therefore, establishing future canopy species in the understory would limit the negative environmental consequences, and provide additional time for understory vegetation to establish itself prior to exposure to the harsh environmental conditions expected following an EAB infestation. p p p g The 4-year old silver maple seedlings had greater survival rates in both the hummocks and hollows compared to other species. The age-related height difference may explain the success of silver maple compared to the rest of the species and may have confounded the results due to the difference in planting stock. While silver maple had the highest survival rates in the ONF planting study, this species is not currently found in great numbers on this landscape, and most of the population’s nearest individuals are found ~80 km to the southwest. Adaptation models suggest that future climate conditions may expand the suitable habitat for silver maple into the headwater wetlands of the upper Great Lakes region [27,28]. As global temperatures continue to rise, the cold-intolerant silver maple may shift to northerly latitudes. American elm and basswood were also relatively successful in the ONF study. These species are commonly found along the hydric to mesic gradient near the black ash-dominated wetlands in the Great Lakes Basin. American elm is more tolerant of extended periods of inundation and saturated conditions, while basswood does not survive well when subjected to standing water [19]. If predicted future climate conditions [29] for the upper Great Lakes region come to fruition, this would put American elm at an advantage and basswood at a disadvantage because of the projected wetter and longer spring season. Northern white cedar was the only conifer to survive at ONF in both microsite conditions, and it also had high survivorship at the SMF site. Northern white cedar is found within both black ash-dominated headwater wetlands and black ash-dominated riparian corridors. As a long-term management strategy, however, converting hardwood-dominated forests to northern white cedar may not be sustainable as northern white cedar within the region regenerates poorly and may be converted to other species [30]. Also, northern white cedar regeneration is heavily pressured by herbivores [31–33] and while our second-year results did not show a statistical difference among herbivore exclusion treatments, it may be too early to detect herbivore pressure. Within the SMF, red maple had the highest survivorship and vigor after the first-year and based on our first year vs. 4. Discussion Survival was greater for seedlings planted on hummocks when compared to seedlings planted in hollows or on cleared ground, except for silver maple at the ONF site which showed no difference between microsite conditions. Mounding has long been used in wetland forestry to establish seedlings [23] as a means to elevate seedlings out of standing water and provide a more favorable moisture regime. While the constructed hummocks in SMF were much smaller than the natural hummocks in ONF and smaller than typical mounding microsites, they still provided a marginal advantage over the hollows and cleared microsites at the two study sites. The low survival rates on the ONF may be explained by the high amount of precipitation in the 2013 water year [24], which resulted in elevated water tables throughout the growing season and may have masked our ability to detect a difference among the treatments. The higher retention in the later years indicates that successful establishment of plantings greatly increases the probability of survival in the future. These results are similar to a study conducted on the nearby Chippewa National Forest in Minnesota [17] which showed that the successful establishment during the first growing season and Forests 2018, 9, 146 8 of 11 winter are the major hurdles for seedling survival. Winter within the study region typically consists of high snowfall and months-long periods of below freezing temperatures. winter are the major hurdles for seedling survival. Winter within the study region typically consists of high snowfall and months-long periods of below freezing temperatures. Black ash canopy tree species loss has been determined to significantly influence water tables within black ash-dominated wetlands within northern Minnesota [25]. Black ash loss has been determined to significantly lower rates of stand transpiration in the ONF [26], significantly smaller rates of growing season drawdown within the ONF [22], and significantly higher water tables across the upper Great Lakes region [22,25] were detected in ash-dominated wetlands following a simulated EAB infestation or timber harvest. These changes subject regeneration to higher standing water levels for longer periods of time after spring inundation and after episodic summertime precipitation events. The cascading effects of forest cover loss may result in increased erosion and downstream sediment deposition. 4. Discussion The poor recruitment despite high natural regeneration indicates that the success of planting efforts may rely in part on the conditions in which the seedling establishes, and further highlights the importance of the findings in the current study. The planting success of hackberry suggests it is a viable alternative species to ash within these systems; however, hackberry is not currently found in great numbers on this landscape, and the northernmost individuals of the defined population are found ~120 km to the southwest. As with silver maple, adaptation models suggest that future climate conditions may expand the suitable habitat for hackberry to move further north in the upper Great Lakes region [27]. In a similar study on the Chippewa National Forest, hackberry had a 52.9% survivorship over a three-year period, indicating high survival in ash-dominated wetlands [17]. While hackberry does not establish well or flourish within very wet sites [36], the hydrology of the riparian corridor may be more suitable to hackberry than the seasonal inundation in the ONF depressional wetlands. Author Contributions: N.B., J.S., S.S., J.W., R.K. and T.P. conceived and designed the experiments; N.B., J.D., J.S., M.V.G., N.J.N. and S.S. performed the experiments; N.B. and J.S. analyzed the data; and all authors contributed to writing the paper. 4. Discussion third year survival rates from the ONF, we expect the survival rate for red maple to remain high. Red maple on the ONF did not fare well due to the relatively low-quality growing stock. The red maple seedlings often had missing terminal buds and were visibly less hardy when compared to the other planted seedlings. While all of the planting stock were subjected to undesirable conditions (e.g., in and out of cold storage, transport to remote study sites without temperature control) red maple’s low survivorship may have been because of its small stature and frailty. Red maple is commonly found within black ash-dominated wetlands as a co-occurring species and survives in a variety of conditions [34], which indicates that red maple is a promising alternative species to plant within black ash-dominated forests. However, red maple is not very shade tolerant [35] and its success therefore will depend on release opportunities, such as those initiated by EAB infestation. As witnessed between these two study locations, if red maple were planted as an alternative species to black ash, quality growing stock and handling care will greatly enhance the success rates of planting efforts. 9 of 11 Forests 2018, 9, 146 Forests 2018, 9, 146 In a related study on the ONF, natural red maple regeneration was abundant, with density of stems ≤50 cm similar to black ash (21,944 ± 12,638 vs. 21,105 ± 13,017 stems ha−1, respectively). However, In a related study on the ONF, natural red maple regeneration was abundant, with density of stems ≤50 cm similar to black ash (21,944 ± 12,638 vs. 21,105 ± 13,017 stems ha−1, respectively). However, the relative density of the species decreased with increasing size class. As historical data from these forests is not available, it is not clear whether this decline in density is due to legacy effects of prior growing conditions, red maple shade tolerance, poor recruitment due to current growing conditions, or some combination of these and other unidentified factors. However, this forest type is dominated by red maple elsewhere in the region [6], which suggests that a future canopy dominated by red maple is a possibility. That red maple seedlings were not negatively affected by increased herbaceous cover in our related study supports this possibility, though declines in natural regeneration may occur in the future as time since disturbance increases. Conflicts of Interest: The authors declare no conflict of interest. References 1. Haack, R.; Jendek, E.; Liu, H.; Marchant, K.; Petrice, T.; Poland, T.; Ye, H. The emerald ash borer: A new exotic Pest in North America. Newslett. Mich. Entomol. Soc. 2002, 47, 1–5. 2. Siegert, N.; McCullough, D.; Liebhold, A.; Telewski, F. Dendrochronological reconstruction of the epicentre and early spread of emerald ash borer in North America. Divers. Distrib. 2014, 20, 847–858. [CrossRef] 2. Siegert, N.; McCullough, D.; Liebhold, A.; Telewski, F. Dendrochronological reconstruction of the epicentre and early spread of emerald ash borer in North America. Divers. Distrib. 2014, 20, 847–858. [CrossRef] 3. MacFarlane, D.; Meyer, S. Characteristics and distribution of potential ash tree hosts for emerald ash borer. For Ecol Manag 2005 213 15 24 [CrossRef] 3. MacFarlane, D.; Meyer, S. Characteristics and distribution of potential ash tree hosts for emerald ash borer. For. Ecol. Manag. 2005, 213, 15–24. [CrossRef] . Marshall, J.; Smith, E.; Mech, R.; Storer, A. Estimates of Agrilus planipennis infestation rates and poten survival of ash. Am. Midl. Nat. 2013, 169, 179–193. [CrossRef] . Herms, D.; McCullough, D. Emerald ash borer invasion of North America: History, biology, ecology, imp and management. Annu. Rev. Entomol. 2014, 59, 13–30. [CrossRef] [PubMed] 6. Erdmann, G.; Crow, T.; Ralph, M., Jr.; Wilson, C. Managing black ash in the Lake States. In General Technical Report NC-115; U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station: St. Paul, MN, USA, 1987. 7. Wright, J.; Rauscher, H. Fraxinus nigra marsh. Black ash. Silv. N. Am. 1990, 2, 344–347. 8. Hewlett, J.; Fortson, J. Stream temperature under an inadequate buffer strip in the southeast piedmont. J. Am. Water Resour. Assoc. 1982, 18, 983–988. [CrossRef] 9. Bourque, C.A.; Pomeroy, J.H. Effects of forest harvesting on summer stream temperatures in New Brunswick, Canada: An inter-catchment, multiple-year comparison. Hydrol. Earth Syst. Sci. Discuss. 2001, 5, 599–614. [CrossRef] 10. Sheridan, J.; Lowrance, R.; Bosch, D. Management effects on runoff and sediment transport in riparia buffers. Trans. Am. Soc. Agric. Eng. 1999, 42, 55–64. [CrossRef] 11. Lowrance, R.; Altier, L.; Newbold, J.; Schnabel, R.; Groffman, P.; Denver, J.; Correll, D.; Gilliam, J.; Robinson, J.; Brinsfield, R. Water quality functions of riparian forest buffers in Chesapeake Bay watersheds. Environ. Manag. 1997, 21, 687–712. [CrossRef] 12. Davis, J.; Shannon, J.; Bolton, N.; Kolka, R.; Pypker, T. Vegetation responses to simulated emerald ash borer infestation in Fraxinus nigra-dominated wetlands of Upper Michigan, USA. Can. J. For. Res. 5. Conclusions This research includes two studies that compared plantings of wetland-adapted tree species survival and growth within black ash-dominated wetlands. In one study, seedlings were planted within black ash wetlands that underwent overstory treatments that simulated our estimated short- and long-term EAB-induced conditions. In the second study, seedlings were planted in an uninfested black and green ash-dominated riparian corridor with manipulated microsite conditions and herbivore browse exclusion treatments. Our results indicate higher survivorship of planted seedlings when planted on hummocks in ash-dominated wetland sites in the Great Lakes region of the US. These results suggest that perching seedlings on elevated beds enhances their survivorship by providing a more stable environment. The highest surviving species we planted were silver maple, American elm, basswood, hackberry, red maple, and northern white cedar and were determined to be species well suited for alternative species plantings in ash-dominated wetlands when compared to natural regeneration within similar systems. Acknowledgments: Funding for this work primarily came from the Great Lakes Restoration Initiative through the USDA Forest Service Northern Research Station (EPA Great Lakes Initiative Template #664: Future of Black Ash Wetlands in the Great Lakes Region) and the Wisconsin Department of Natural Resources through the Lake Superior National Estuarine Research Reserve. Additional funding came from the School of Forest Resources and Environmental Science, Ecosystem Science Center and the Center for Water and Society at Michigan Technological University. We would like to thank the Ottawa National Forest, particularly Mark Fedora, as well as the City of Superior, Wisconsin and the Superior Municipal Forest for letting us conduct this research on their lands. We would like to thank Sarah Harttung, Ashlee Lehner, and Alex Perram for assisting in data collection from the Ottawa National Forest planting sites and we would like to thank the volunteer planting crew as well as the student interns from the Lake Superior National Estuarine Research Reserve for their help at the Superior Municipal Forest planting site. Author Contributions: N.B., J.S., S.S., J.W., R.K. and T.P. conceived and designed the experiments; N.B., J.D., J.S., M.V.G., N.J.N. and S.S. performed the experiments; N.B. and J.S. analyzed the data; and all authors contributed to writing the paper. Conflicts of Interest: The authors declare no conflict of interest. 10 of 11 10 of 11 Forests 2018, 9, 146 References 2017, 47, 319–330. [CrossRef] 13. Palik, B.; Ostry, M.; Venette, R.; Abdela, E. Fraxinus nigra (black ash) dieback in Minnesota: Regional variation and potential contributing factors. For. Ecol. Manag. 2011, 261, 128–135. [CrossRef] 14. Palik, B.; Ostry, M.; Venette, R.; Abdela, E. Tree regeneration in black ash (Fraxinus nigra) stands exhibiting crown dieback in Minnesota. For. Ecol. Manag. 2012, 269, 26–30. [CrossRef] 15. Ponnamperuma, F. Effects of flooding on soils. In Flooding and Plant Growth; Academic Press, Inc.: New York, NY, USA, 1984; pp. 9–45. 16. Roy, V.; Bernier, P.; Plamondon, A.; Ruel, J. Effect of drainage and microtopography in forested wetlands on the microenvironment and growth of planted black spruce seedlings. Can. J. For. Res. 1999, 29, 563–574. [CrossRef] 17. Looney, C.; D’Amato, A.; Palik, B.; Slesak, R. Overstory treatment and planting season affect survival of replacement tree species in emerald ash borer threatened Fraxinus nigra forests in Minnesota, USA. Can. J. For. Res. 2015, 45, 1728–1738. [CrossRef] 18. Staff, S.S. Natural Resources Conservation Service Web Soil Survey, United States Department of Agriculture. 2017. Available online: http://websoilsurvey.sc.egov.usda.gov/ (accessed on 26 April 2017). 19. Burns, R.; Honkala, B. Silvics of North America: 1. Conifers; 2. Hardwoods; United States Department of Agriculture: Washington, DC, USA, 1990. 20. WinSCANOPY, Pro Version ed; Regent Instruments Inc.: Quebec, QC, Canada, 2010. g 21. R Development Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2016. 22. Van Grinsven, M.; Shannon, J.; Davis, J.; Bolton, N.; Wagenbrenner, J.; Kolka, R.; Pypker, T. Source water contributions and hydrologic responses to simulated emerald ash borer infestations in depressional black ash wetlands. Ecohydrology 2017, 10, e1862. [CrossRef] 23. Londo, A.; Mroz, G. Bucket mounding as a mechanical site preparation technique in wetlands. North. J. Appl. For. 2001, 18, 7–13. 11 of 11 Forests 2018, 9, 146 24. Van Grinsven, M. Implications of Emerald Ash Borer Disturbance on Black Ash Wetland Watershed Hydrology, Soil Carbon Efflux, and Dissolved Organic Matter. Ph.D. Thesis, Michigan Technological University, Houghton, MI, USA, 2015. 25. Slesak, R.A.; Lenhart, C.F.; Brooks, K.N.; D’Amato, A.W.; Palik, B.J. Water table response to harvesting and simulated emerald ash borer mortality in black ash wetlands in Minnesota, USA. Can. J. For. Res. 2014, 44, 961–968. [CrossRef] 26. Shannon, J.; Van Grinsven, M.; Davis, J.; Bolton, N.; Noh, N.; Pypker, T.; Kolka, R. References Water level controls on sap flux of canopy species in black ash wetlands. Forests 2018, accepted. 27. Williams, M.; Dumroese, R. Preparing for climate change: Forestry and assisted migration. J. For. 2013, 111, 287–297. [CrossRef] 28. Iverson, L.; Knight, K.S.; Prasad, A.; Herms, D.A.; Matthews, S.; Peters, M.; Smith, A.; Hartzler, D.M.; Long, R.; Almendinger, J. Potential species replacements for black ash (Fraxinus nigra) at the confluence of 28. Iverson, L.; Knight, K.S.; Prasad, A.; Herms, D.A.; Matthews, S.; Peters, M.; Smith, A.; Hartzler, D.M.; Long, R.; Almendinger, J. Potential species replacements for black ash (Fraxinus nigra) at the confluence of two threats: Emerald ash borer and a changing climate. Ecosystems 2016, 19, 248–270. [CrossRef] 29. Janowiak, M.; Iverson, L.; Mladenoff, D.; Peters, E.; Wythers, K.; Xi, W.; Brandt, L.; Butler, P.; Handler, S.; Shannon, P.; et al. Forest Ecosystem Vulnerability Assessment and Synthesis for Northern Wisconsin and Western Upper Michigan: A Report from the Northwoods Climate Change Response Framework Project; General Technical Report NRS-136; U.S. Department of Agriculture, Forest Service, Northern Research Station: Newtown Square, PA, USA, 2014; Volume 247. 30. Chimner, R.; Hart, J. Hydrology and microtopography effects on northern white-cedar regeneration in michigan’s Upper Peninsula. Can. J. For. Res. 1996, 26, 389–393. [CrossRef] 31. Cornett, M.; Frelich, L.; Puettmann, K.; Reich, P. Conservation implications of browsing by Odocoileus virginianus in remnant upland Thuja occidentalis forests. Biol. Conserv. 2000, 93, 359–369. [CrossRef] 32. Rooney, T.; Waller, D. Direct and indirect effects of white-tailed deer in forest ecosystems. For. Ecol. Manag. 2003, 181, 165–176. [CrossRef] 33. Russell, F.; Zippin, D.; Fowler, N. Effects of white-tailed deer (Odocoileus virginianus) on plants, plant populations and communities: A review. Am. Midl. Nat. 2001, 146, 1–26. [CrossRef] 34. Abrams, M.D. The red maple paradox. BioScience 1998, 48, 355–364. [CrossRef] 35. Kobe, R.; Pacala, S.; Silander, J.; Canham, C. Juvenile tree survivorship as a component of shade to Ecol. Appl. 1995, 5, 517–532. [CrossRef] pp 36. Krajicek, J.; Williams, R. Celtis occidentalis L. Hackberry. Silv. N. Am. 1990, 2, 262. 36. Krajicek, J.; Williams, R. Celtis occidentalis L. Hackberry. Silv. N. Am. 1990, 2, 262. © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
https://openalex.org/W3202686002
https://www.nature.com/articles/s41598-021-99494-4.pdf
English
null
Enhancement of the bone-implant interface by applying a plasma-sprayed titanium coating on nanohydroxyapatite/polyamide66 implants in a rabbit model
Scientific reports
2,021
cc-by
4,003
www.nature.com/scientificreports www.nature.com/scientificreports Enhancement of the bone‑implant interface by applying a plasma‑sprayed titanium coating on nanohydroxyapatite/ polyamide66 implants in a rabbit model OPEN Solid fusion at the bone-implant interface (BII) is considered one of the indicators of a satisfactory clinical outcome for spine surgery. Although the mechanical and physical properties of nanohydroxyapatite/polyamide66 (n-HA/PA66) offers many advantages, the results of long-term follow-up for BIIs remain limited. This study aimed to improve the BII of n-HA/PA66 by applying plasma-sprayed titanium (PST) and assessing the mechanical and histological properties. After the PST coating was applied to n-HA/PA66 implants, the coating had uneven, porous surfaces. The compression results were not significantly different between the two groups. The micro-CT results demonstrated that at 6 weeks and 12 weeks, the bone volume (BV), BV/tissue volume (TV) and trabecular number (Tb.N) values of the n-HA/PA66-PST group were significantly higher than those of the n-HA/PA66 group. The results of undecalcified bone slicing showed that more new bone appeared to form around n-HA/PA66-PST implant than around n-HA/PA66 implant. The bone-implant contact (BIC) and push-out test results of the n-HA/PA66-PST group were better than those of the n-HA/PA66 group. In conclusion, after PST coating, direct and additional new bone-to-implant bonding could be achieved, improving the BII of n-HA/PA66 implants. The n-HA/PA66-PST implants could be promising for repair purposes. The clinical use of biomaterials varies by clinicians or surgeons. The definition and understanding of human biomaterials remain to be refined and clarified. A biomaterial implant as an independent unit is designed to make direct interactions with living tissue. The adaptability of implants in vivo is still important. The nano- hydroxyapatite/polyamide66(n-HA/PA66) is a novel biomaterial implant with components of nanohydroxyapa- tite and polyamide simulating natural bones and has been used clinically in China for more than fifteen years. Many studies, especially preclinical ­studies1–4, have demonstrated that n-HA/PA66 is biocompatible. At the final follow-up in constructing cervical spine stability of the anterior cervical corpectomy decompression and fusion (ACCF), the “radiolucent gap” appeared in the n-HA/PA66 strut and the bone. Our team considered the main reason for the appearance of the “radiolucent gap” to be the insufficient osteogenic induction of n-HA/PA66 ­itself2–4. Making improvements to the bone-implant interface is still a main issue. g p p At present, surface coating for implants is an important method to improve osteogenesis induction. Our study first used a plasma-sprayed titanium (PST)4–6 coating to n-HA/PA66 to improve the bone-implant interface (BII), enhancing osteogenesis induction in a rabbit model and providing additional modification possibilities for biomaterials. Department of Orthopaedics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China. *email: 492467112@qq.com Methods Sample preparation. Cylindrical struts (6 mm*10 mm) of either n-HA/PA66 or n-HA/PA66 with a PST coating were used in the experiment (Fig. 1). The surface features of the n-HA/PA66 samples were qualitatively examined using scanning electron microscopy (SEM). The compression test was performed by an electronic universal testing machine (the loading speed was 0.5 mm/min. Axial pressure was gradually applied until the specimen was destroyed), and the stress–strain curve was recorded. The pull-out tests were performed at 6 w and 12 w, and the rabbits were sacrificed following the intravenous injection of sodium pentobarbital at a dose of 200 mg/kg. After the samples were taken, the specimens were fixed in 4% paraformaldehyde solution, and then the axis was changed to ensure the same axis was used across samples. The axial direction of the implant was adjusted to be consistent with the pushing direction of the universal testing machine, and the pushing speed was adjusted to 0.05 mm/min. The maximum pushing force (Fmax) was recorded, and the results were recorded in the form of the maximum surface shear strength sμ N ­mm2. The formula is sμ = Fmax/SBIC. ­SBIC is the contact area between the implant and bone ­(SBIC = лDL), where D is the diameter of the specimen and L is the mean thickness of the bilateral cortical ­bone7–9. Surgery procedure. The study was carried out in compliance with the ARRIVE guidelines. All methods were carried out in accordance with relevant guidelines and regulations. And all experimental protocols were approved by the Committee of The First Affiliated Hospital of Chongqing Medical University (No: 20187801). Twelve adult male New Zealand white rabbits with a weight of 2.0–3.0 kg were used and were randomly divided into two groups (6 in each group). One femur was selected randomly as the surgical region. General anaesthesia was intravenously administered with 3% sodium pentobarbital solution (1.0 mL/kg) (Sigma-Aldrich Co.). After successful anaesthesia, the surgical site was shaved and disinfected. A longitudinal lateral incision of 3.5 cm was made to expose the femoral groove with medial dislocation of the patella. After flexion of the knee, a bone defect (6 mm width × 10 mm depth) was created in the femoral groove with a bone drill (4 mm width × 2 mm thick- ness). The n-HA/PA66 and n-HA/PA66-PST struts were implanted at the defect site (Fig. 2). Enhancement of the bone‑implant interface by applying a plasma‑sprayed titanium coating on nanohydroxyapatite/ polyamide66 implants in a rabbit model OPEN | https://doi.org/10.1038/s41598-021-99494-4 Scientific Reports | (2021) 11:19971 www.nature.com/scientificreports/ www.nature.com/scientificreports/ Figure 1. A view of n-HA/PA66 (A), n-HA/PA66-PST (B) struts. Figure 1. A view of n-HA/PA66 (A), n-HA/PA66-PST (B) struts. Figure 2. A depiction of the surgery. Figure 2. A depiction of the surgery. Methods Sample preparation. Cylindrical struts (6 mm*10 mm) of either n-HA/PA66 or n-HA/PA66 with a PST coating were used in the experiment (Fig. 1). The surface features of the n-HA/PA66 samples were qualitatively examined using scanning electron microscopy (SEM). The compression test was performed by an electronic universal testing machine (the loading speed was 0.5 mm/min. Axial pressure was gradually applied until the specimen was destroyed), and the stress–strain curve was recorded. The pull-out tests were performed at 6 w and 12 w, and the rabbits were sacrificed following the intravenous injection of sodium pentobarbital at a dose of 200 mg/kg. After the samples were taken, the specimens were fixed in 4% paraformaldehyde solution, and then the axis was changed to ensure the same axis was used across samples. The axial direction of the implant was adjusted to be consistent with the pushing direction of the universal testing machine, and the pushing speed was adjusted to 0.05 mm/min. The maximum pushing force (Fmax) was recorded, and the results were recorded in the form of the maximum surface shear strength sμ N ­mm2. The formula is sμ = Fmax/SBIC. ­SBIC is the contact area between the implant and bone ­(SBIC = лDL), where D is the diameter of the specimen and L is the mean thickness of the bilateral cortical ­bone7–9. Figure 2. A depiction of the surgery. Figure 2. A depiction of the surgery. Methods The incision was sutured in layers, and the lateral ligament was sutured tightly to avoid patellar dislocation. Penicillin sodium at 20,000 IU/kg/d (Southwest Pharmaceutical Co., Ltd., Chongqing) was injected intramuscularly 3 days after sur- gery. The rabbits were kept in separate cages and allowed to move fully after the operation. They were sacrificed after intravenous injection of sodium pentobarbital (200 mg/kg) at 6 and 12 weeks. https://doi.org/10.1038/s41598-021-99494-4 Scientific Reports | (2021) 11:19971 | www.nature.com/scientificreports/ www.nature.com/scientificreports/ Figure 3. SEM of n-HA/PA66 (A) and n-HA/PA66-PST (B). The two sample groups were examined using SEM. The surface of the n-HA/PA66 implants was relatively smooth and lacked surface features. The PST coating in on the n-HA/PA66 sample demonstrates a rough topography for bone on growth and cavities for bone ingrowth. Figure 3. SEM of n-HA/PA66 (A) and n-HA/PA66-PST (B). The two sample groups were examined using SEM. The surface of the n-HA/PA66 implants was relatively smooth and lacked surface features. The PST coating in on the n-HA/PA66 sample demonstrates a rough topography for bone on growth and cavities for bone ingrowth. Figure 4. Micro-CT image of n-HA/PA66 (A), n-HA/PA66-PST (B) implants. Figure 4. Micro-CT image of n-HA/PA66 (A), n-HA/PA66-PST (B) implants. Statistical analysis. Statistical Analysis System software (SAS Institute, Inc., Cary, NC, USA) was applied to analyse the data. Quantitative variables are expressed as the mean ± SD. The chi-squared test was used for the categorical variables. P < 0.05 was considered statistically significant. Resultsh The surface morphology of n-HA/PA66 and n-HA/PA66-PST implants was observed using SEM and micro-CT to confirm the presence of the plasma-sprayed titanium coating on the surface (Figs. 3 and 4). Macroscopic (Figs. 1, 3, and 4) and SEM assessments revealed the lack of surface features on the n-HA/PA66 sample with a relatively smooth interface, whereas the n-HA/PA66 sample demonstrated the presence of the PST layer. The PST coatings all had uneven, porous surfaces that were irregular in appearance in the order of microns, which better promoted osteoblast adhesion and bone growth. The PST layer was uniform along the length of the implant. The plasma-sprayed titanium layer was well integrated with n-HA/PA66 with no macroscopic alterations to the appearance at the titanium-n-HA/PA66 interface. https://doi.org/10.1038/s41598-021-99494-4 https://doi.org/10.1038/s41598-021-99494-4 Scientific Reports | (2021) 11:19971 | scientificreports/ Figure 5. BV/TV and Tb.N at 6 weeks. Figure 6. BV/TV and Tb.N at 12 weeks. www.nature.com/scientificreports/ Figure 5. BV/TV and Tb.N at 6 weeks. Figure 5. BV/TV and Tb.N at 6 weeks. Figure 5. BV/TV and Tb.N at 6 weeks. Figure 6. BV/TV and Tb.N at 12 weeks. Figure 6. BV/TV and Tb.N at 12 weeks. Figure 6. BV/TV and Tb.N at 12 weeks. The rabbits were in good condition after strut implantation. The incision showed varying degrees of swell- ing, but no infections occurred. Rabbits were sacrificed 6 and 12 weeks postoperatively, and the samples were removed for tests.h The three-dimensional micro-CT images showed that more bone tissues were detected around the n-HA/ PA66-PST strut than around the n-HA/PA66 strut. At 6 weeks and 12 weeks, the formation of new bone was quantitatively analysed by micro-CT, and the bone volume (BV)/tissue volume (TV) and the trabecular number (Tb.N) were determined. At 6 weeks, the BV/TV values and Tb.N of the n-HA/PA66-PST struts were signifi- cantly higher than those of the n-HA/PA66 groups (P < 0.05). At 12 weeks, the BV/TV values and Tb.N of n-HA/ PA66-PST implants were significantly higher than those of the n-HA/PA66 group (P < 0.05) (Figs. 5 and 6). Furthermore, the PST coating on n-HA/PA66 improved the BV/TV and Tb.N comparing those without coating (P < 0.05). The three-dimensional micro-CT images showed that more bone tissue was detected within the n-HA/ PA66-PST group than in the n-HA/PA66 group (Fig. 7).t At 6 weeks after surgery, n-HA/PA66 and n-HA/PA66-PST were tightly implanted into the surrounding bone tissue and closely integrated. Around the strut of n-HA/PA66-PST, there were more osteoblasts. However, around the strut of n-HA/PA66, few osteoblasts and more fibrochondrocytes were observed (Fig. 8). At 12 weeks, more osteoblasts were observed in the n-HA/PA66-PST group. The osteoblasts did not seem to be in close contact with the strut of n-HA/PA66, but the opposite finding was noted in the n-HA/PA66-PST group. The bone implant contact (BIC) of the n-HA/PA66-PST implants was better (P < 0.05) than that of the n-HA/PA66 implants (Fig. 9). The compression results, the compression modulus and compression yield stress, of the two groups are shown in Fig. https://doi.org/10.1038/s41598-021-99494-4 10, there was no significant difference (P > 0.05).hif if The results of the two groups at 6 w and 12 w are shown in Table 1 and Fig. 11, with a significant difference (P < 0.05), indicating that the osseointegration of n-HA/PA66-PST was better than that of n-HA/PA66. Scientific Reports | (2021) 11:19971 | https://doi.org/10.1038/s41598-021-99494-4 www.nature.com/scientificreports/ Figure 7. Micro-CT images of n-HA/PA66 (A) and n-HA/PA66-PST (B) at 6 and 12 weeks. Figure 7. Micro-CT images of n-HA/PA66 (A) and n-HA/PA66-PST (B) at 6 and 12 weeks. Figure 8. Histological analysis (H&E staining, × 100) of femoral condylar defects and new bone tissue at 6 weeks and 12 weeks after surgery. (A) n-HA/PA66; (B) n-HA/PA66-PST. Figure 8. Histological analysis (H&E staining, × 100) of femoral condylar defects and new bone tissue at 6 weeks and 12 weeks after surgery. (A) n-HA/PA66; (B) n-HA/PA66-PST. Discussionh Pull-out test at 6 weeks and 12 weeks of n-HA/PA66 and n-HA/PA66-PST implants. shear strength than the n-HA/PA66 struts. Similarly, according to the BIC results, the BII of n-HA/PA66-PST struts was better than that of n-HA/PA66 struts and supported superior mechanical properties due to increased direct bone contact. The BII findings of gap tissue between n-HA/PA66 implants and host bone tissue that had been reported previously and in our study did not show a significant gap around the new bone tissue and n-HA/ PA66-PST implant. The PST coating on the n-HA/PA66 implant provides a means for direct new bone tissue on growth. Although the ideal model provides a means of direct comparison, many factors, such as implants, surgical techniques, and animal mobility, may have complex limitations, affecting the implant response to the host bone tissue. We hope to observe more time points to further determine the long-term benefits of PST coating in bone remodelling, considering more complex biomechanical and biological ­environments14–18. shear strength than the n-HA/PA66 struts. Similarly, according to the BIC results, the BII of n-HA/PA66-PST struts was better than that of n-HA/PA66 struts and supported superior mechanical properties due to increased direct bone contact. The BII findings of gap tissue between n-HA/PA66 implants and host bone tissue that had been reported previously and in our study did not show a significant gap around the new bone tissue and n-HA/ PA66-PST implant. The PST coating on the n-HA/PA66 implant provides a means for direct new bone tissue on growth. Although the ideal model provides a means of direct comparison, many factors, such as implants, surgical techniques, and animal mobility, may have complex limitations, affecting the implant response to the host bone tissue. We hope to observe more time points to further determine the long-term benefits of PST coating in bone remodelling, considering more complex biomechanical and biological ­environments14–18. l l ld h b f d h g g p g In conclusion, a PST coating on n-HA/PA66 implants could achieve better fusion in BIIs and improve the osteogenesis-inducing ability of the implant, providing potential surface modification of materials. Received: 14 April 2021; Accepted: 27 September 2021 Discussionh The ideal bone-implant interface is influenced by surgical, biomechanical, manufacturing, and commercial fac- tors. n-HA/PA66 is a nonmetallic biomaterial implant that is a composite of nanohydroxyapatite and polyamide 66, and it simulates natural ­bone1–4. Our team has reported satisfactory clinical outcomes, but we observed that the “radiolucent gap” was imaged more often between the n-HA/PA66 strut and the bone at both the one-year and final follow-up and that the subsidence rate was higher in ­patients2–5. We discussed this phenomenon, and we considered the reason was insufficient osteogenic induction in the n-HA/PA66 implant. Additionally, a solid https://doi.org/10.1038/s41598-021-99494-4 Scientific Reports | (2021) 11:19971 | www.nature.com/scientificreports/ Figure 9. BIC of n-HA/PA66 and n-HA/PA66-PST implants. Figure 9. BIC of n-HA/PA66 and n-HA/PA66-PST implants. Figure 10. The stress–strain curve of n-HA/PA66 (A) and n-HA/PA66-PST (B) implants. Figure 10. The stress–strain curve of n-HA/PA66 (A) and n-HA/PA66-PST (B) implants. Table 1. The results of the push-out test. Groups 6 weeks (N/mm2) 12 weeks (N/mm2) n-HA/PA66 5.00 ± 0.70 18.00 ± 2.35 n-HA/PA66-PST 7.20 ± 0.84 23.00 ± 1.87 P value 0.0020 0.0058 BII is vital for treatment success, which remains significantly important and of great research interest. Many methods have been used to modify the surface mechanically or chemically to make the implant adapt to host ­tissue4–9. Biologically, the PST coating on the n-HA/PA66 strut significantly adapted to the bone tissue, providing more new bone growth. Mechanistically, the compression results did not show a significant difference between n-HA/PA66 and n-HA/PA66-PST implants. p In our study, the uneven and porous appearance of PST coating could better promote osteoblast adhesion and bone growth. The three-dimensional micro-CT results showed the BV/TV values and Tb.N of n-HA/PA66-PST implants were significantly higher than those of the n-HA/PA66 group at 12 weeks and the PST coating on n-HA/ PA66 improved the BV/TV and Tb.N comparing those without coating. And also at 12 weeks of histological analysis, more osteoblasts were observed in the n-HA/PA66-PST and more osteoblasts were in close contact with the strut of n-HA/PA66-PST.h The study used a well-established rabbit model in which direct new bone ingrowth could be ­observed10–13. The pull-out test performed 6 and 12 weeks after surgery showed that the n-HA/PA66-PST struts achieved better Scientific Reports | (2021) 11:19971 | https://doi.org/10.1038/s41598-021-99494-4 www.nature.com/scientificreports/ p / Figure 11. Pull-out test at 6 weeks and 12 weeks of n-HA/PA66 and n-HA/PA66-PST implants. Figure 11. References 1. Zhang, Y. et al. Long-term results of anterior cervical corpectomy and fusion with nano-hydroxyapatite/polyamide 66 strut for cervical spondylotic myelopathy. Sci. Rep. 6, 26751 (2016).tf 2. Zhong, W. et al. Nanohydroxyapatite/polyamide 66 strut subsidence after one-level corpectomy: underlying mechanism and effect on cervical neurological function. Sci. Rep. 8(1), 12098 (2018).t g p 3. Zhong, W. et al. Imaging evaluation of nano-hydroxyapatite/polyamide 66 strut in cervical construction after 1-level corpectomy: a retrospective study of 520 patients. Eur. J. Med. Res. 25(1), 38 (2020). g p 3. Zhong, W. et al. Imaging evaluation of nano-hydroxyapatite/polyamide 66 strut in cervical construction after 1-level corpectomy: a retrospective study of 520 patients. Eur. J. Med. Res. 25(1), 38 (2020). p y p 4. Walsh, W. R. et al. Plasma-sprayed titanium coating to polyetheretherketone improves the bone-implant interface. Spine J. 15(5) 1041–1049 (2015). p y p 4. Walsh, W. R. et al. Plasma-sprayed titanium coating to polyetheretherketone improves the bone-implant interface. Spine J. 1 1041–1049 (2015). 5. Torstrick, F. B. et al. Porous PEEK improves the bone-implant interface compared to plasma-sprayed titanium coating on PEEK. Biomaterials 185, 106–116 (2018). 5. Torstrick, F. B. et al. Porous PEEK improves the bone-implant interface compared to plasma-sprayed titanium coating on PEEK. Biomaterials 185, 106–116 (2018). ( ) 6. Hoppe, S. et al. First results of a new vacuum plasma sprayed (VPS) titanium-coated carbon/PEEK composite cage for lumbar interbody fusion. J. Funct. Biomater. 9(1), 23 (2018).i 6. Hoppe, S. et al. First results of a new vacuum plasma sprayed (VPS) titanium-coated carbon/PEEK composite cage for lumbar interbody fusion. J. Funct. Biomater. 9(1), 23 (2018).i y ( ) ( ) 7. Svehla, M. et al. Morphometric and mechanical evaluation of titanium implant integration: comparison of five surface struct J. Biomed. Mater. Res. 51, 15–22 (2000).ll y a, M. et al. Morphometric and mechanical evaluation of titanium implant integration: comparison of five surface structures. med. Mater. Res. 51, 15–22 (2000).ll 8. Bertollo, N. et al. Inflfluence of electron beam melting manufactured implants on ingrowth and shear strength in an ovine m J. Arthroplasty 27, 1429–1436 (2012).ii 8. Bertollo, N. et al. Inflfluence of electron beam melting manufactured implants on ingrowth and shear strength in an ovine model. J. Arthroplasty 27, 1429–1436 (2012).ii 8. Bertollo, N. et al. Inflfluence of electron beam melting manufactured implants on ingrowth and shear strength in an ovine model. J. Arthroplasty 27, 1429–1436 (2012).ii p y 9. References Devine, D. M. et al. Coating of carbon fifiber-reinforced polyetheretherketone implants with titanium to improve bone apposition. J. Biomed. Mater. Res. B Appl. Biomater. 101, 591–598 (2013). p y 9. Devine, D. M. et al. Coating of carbon fifiber-reinforced polyetheretherketone implants with titanium to improve bone apposition. J. Biomed. Mater. Res. B Appl. Biomater. 101, 591–598 (2013). p y 9. Devine, D. M. et al. Coating of carbon fifiber-reinforced polyetheretherketone implants with titanium to improve bone apposition J. Biomed. Mater. Res. B Appl. Biomater. 101, 591–598 (2013). ii J. Biomed. Mater. Res. B Appl. Biomater. 101, 591–598 (2013). pp 0. McGilvray, K. C. et al. Bony ingrowth potential of 3D-printed porous titanium alloy: a direct comparison of interbody cage materi- als in an in vivo ovine lumbar fusion model. Spine J. 18(7), 1250–1260 (2018). 10. McGilvray, K. C. et al. Bony ingrowth potential of 3D-printed porous titanium alloy: a direct co als in an in vivo ovine lumbar fusion model. Spine J. 18(7), 1250–1260 (2018). p ( ) ( ) 1. Yoon, B. J. et al. Optimizing surface characteristics for cell adhesion and proliferation on titanium plasma spray coatings on poly- etheretherketone. Spine J. 16(10), 1238–1243 (2016). p ( ) ( ) 11. Yoon, B. J. et al. Optimizing surface characteristics for cell adhesion and proliferation on titanium plasma spray coatings on poly- etheretherketone. Spine J. 16(10), 1238–1243 (2016). p 11. Yoon, B. J. et al. Optimizing surface characteristics for cell adhesion and proliferation on titanium plasma spray coatings on poly- etheretherketone. Spine J. 16(10), 1238–1243 (2016). p 2. Torstrick, F. B. et al. Getting PEEK to stick to bone: the development of porous PEEK for interbody fusion devices. Tech. Orthop 32(3), 158–166 (2017).i 3. Wang, W. T. et al. Dual pitch titanium-coated pedicle screws improve initial and early fixation in a polyetheretherketone rod semi- rigid fixation system in sheep. Chin. Med. J. (Engl.) 132(21), 2594–2600 (2019). rigid fixation system in sheep. Chin. Med. J. (Engl.) 132(21), 2594 2600 (2019). 14. Cheng, B. C. et al. Porous titanium-coated polyetheretherketone implants exhibit an improved bone-implant interface: an in vitro and in vivo biochemical, biomechanical, and histological study. Med. Devices (Auckl.) 1, 391–402 (2018). gi y p J ( g ) ( ) ( ) 14. Cheng, B. C. et al. Porous titanium-coated polyetheretherketone implants exhibit an improved bone-implant interface: an in vitro and in vivo biochemical, biomechanical, and histological study. Med. Acknowledgements Not applicable. g Not applicable. Competing interests h p g The authors declare no competing interests. Author contributions W.Y.Z. designed the study. W.Y.Z., J.X.L., C.B.H., Z.X.Q. and D.M.J. implemented the experiment. W.Y.Z. wrote and revised the manuscript. All authors read and approved the final manuscript. References Devices (Auckl.) 1, 391–402 (2018). gi y p ( g ) ( ) ( ) 4. Cheng, B. C. et al. Porous titanium-coated polyetheretherketone implants exhibit an improved bone-implant interface: an in vitro and in vivo biochemical, biomechanical, and histological study. Med. Devices (Auckl.) 1, 391–402 (2018). h l h b l b d d d l b g y 5. Kashii, M. et al. Comparison in the same intervertebral space between titanium-coated and uncoated PEEK cages in lumbar interbody fusion surgery. J. Orthop. Sci. 25(4), 565–570 (2020). y g y p 16. Hickey, D. J., Lorman, B. & Fedder, I. L. Improved response of osteoprogenitor cells to titanium plasma-sprayed PEEK surfaces. Colloids Surf. B Biointerfaces 175, 509–516 (2019). https://doi.org/10.1038/s41598-021-99494-4 Scientific Reports | (2021) 11:19971 | www.nature.com/scientificreports/ www.nature.com/scientificreports/ 17. Stübinger, S. et al. Titanium and hydroxyapatite coating of polyetheretherketone and carbon fiber-reinforced polyetheretherketone: a pilot study in sheep. J. Biomed. Mater. Res. B Appl. Biomater. 104(6), 1182–1191 (2016). p y p pp 8. Torstrick, F. B. et al. Impaction durability of porous polyether-ether-ketone (PEEK) and titanium-coated PEEK interbody fusion devices. Spine J. 18(5), 857–865 (2018). Fundingh g The study was supported by the medical programme of Chongqing Health and Science Commission and Technol- ogy Commission (2021MSXM285). The funding body was not involved in the design, data collection, analysis, interpretation or writing of the manuscript. Additional information Correspondence and requests for materials should be addressed to W.Z. Reprints and permissions information is available at www.nature.com/reprints. Publisher’s note  Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. © The Author(s) 2021 https://doi.org/10.1038/s41598-021-99494-4 Scientific Reports | (2021) 11:19971 |
https://openalex.org/W2268914619
http://sedici.unlp.edu.ar/bitstream/handle/10915/78578/Documento_completo.pdf?sequence=1
English
null
Commissioning of the ATLAS Muon Spectrometer with cosmic rays
European physical journal. C, Particles and fields
2,010
cc-by
39,700
Eur. Phys. J. C (2010) 70: 875–916 DOI 10.1140/epjc/s10052-010-1415-2 Special Article - Tools for Experiment and Theory Special Article - Tools for Experiment and Theory Commissioning of the ATLAS Muon Spectrometer with cosmic rays The ATLAS Collaboration?,?? G. Aad48, B. Abbott111, J. Abdallah11, A.A. Abdelalim49, A. Abdesselam118, O. Abdinov10, B. Abi112, M. Abolins88, H. Abramowicz152, H. Abreu115, B.S. Acharya163a,163b, D.L. Adams24, T.N. Addy56, J. Adelman174, C. Adorisio36a,36b, P. Adragna75, T. Adye129, S. Aefsky22, J.A. Aguilar-Saavedra124b, M. Aharrouche81, S.P. Ahlen21, F. Ahles48, A. Ahmad147, H. Ahmed2, M. Ahsan40, G. Aielli133a,133b, T. Akdogan18a, T.P.A. Åkesson79, G. Akimoto154 A.V. Akimov94, A. Aktas48, M.S. Alam1, M.A. Alam76, S. Albrand55, M. Aleksa29, I.N. Aleksandrov65, C. Alexa25a, G. Alexander152, G. Alexandre49, T. Alexopoulos9, M. Alhroob20, M. Aliev15, G. Alimonti89a, J. Alison120, M. Aliyev10, P.P. Allport73, S.E. Allwood-Spiers53, J. Almond82, A. Aloisio102a,102b, R. Alon170, A. Alonso79, M.G. Alviggi102a,102b, K. Amako66, C. Amelung22, A. Amorim124a, G. Amorós166, N. Amram152, C. Anastopoulos139, T. Andeen29, C.F. Anders48, K.J. Anderson30, A. Andreazza89a,89b, V. Andrei58a, X.S. Anduaga70, A. Angerami34, F. Anghinolfi29, N. Anjos124a, A. Annovi47, A. Antonaki8, M. Antonelli47, S. Antonelli19a,19b, J. Antos144b, B. Antunovic41, F. Anulli132a, S. Aoun83, G. Arabidze8, I. Aracena143, Y. Arai66, A.T.H. Arce14, J.P. Archambault28, S. Arfaoui29,a, J.-F. Arguin14, T. Argyropoulos9, M. Arik18a, A.J. Armbruster87, O. Arnaez4, C. Arnault115, A. Artamonov95, D. Arutinov20, M. Asai143, S. Asai154, R. Asfandiyarov171, S. Ask82, B. Åsman145a,145b, D. Asner28, L. Asquith77, K. Assamagan24, A. Astbury168, A. Astvatsatourov52, G. Atoian174, B. Auerbach174, K. Augsten127, M. Aurousseau4, N. Austin73, G. Avolio162, R. Avramidou9, D. Axen167, C. Ay54, G. Azuelos93,b, Y. Azuma154, M.A. Baak29, A.M. Bach14, H. Bachacou136, K. Bachas29, M. Backes49, E. Badescu25a, P. Bagnaia132a,132b, Y. Bai32a, T. Bain157, J.T. Baines129, O.K. Baker174, M.D. Baker24, S. Baker77, F. Baltasar Dos Santos Pedrosa29, E. Banas38, P. Banerjee93, S. Banerjee168, D. Banfi89a,89b, A. Bangert137, V. Bansal168, S.P. Baranov94, S. Baranov65, A. Barashkou65, T. Barber27, E.L. Barberio86, D. Barberis50a,50b, M. Barbero20, D.Y. Bardin65, T. Barillari99, M. Barisonzi173, T. Barklow143, N. Barlow27, B.M. Barnett129, R.M. Barnett14, A. Baroncelli134a, A.J. Barr118, F. Barreiro80, J. Barreiro Guimarães da Costa57, P. Barrillon115, R. Bartoldus143, D. Bartsch20, R.L. Bates53, L. Batkova144a, J.R. Batley27, A. Battaglia16, M. Battistin29, F. Bauer136, H.S. Bawa143, M. Bazalova125, B. Beare157, T. Beau78, P.H. Beauchemin118, R. Beccherle50a, N. Becerici18a, P. Bechtle41, G.A. Beck75, H.P. Beck16, M. Beckingham48, K.H. Becks173, A.J. Beddall18c, A. Beddall18c, V.A. Bednyakov65, C. Bee83, M. Begel24, S. Behar Harpaz151, P.K. Behera63, M. Beimforde99, C. Belanger-Champagne165, P.J. Bell49, W.H. Bell49, G. Bella152, L. Bellagamba19a, F. Bellina29, M. Bellomo119a, A. Belloni57, K. Belotskiy96, O. Beltramello29, S. Ben Ami151, O. Benary152, D. Benchekroun135a, M. Bendel81, B.H. Benedict162, N. Benekos164, Y. Benhammou152, G.P. Commissioning of the ATLAS Muon Spectrometer with cosmic rays Benincasa124a, D.P. Benjamin44, M. Benoit115, J.R. Bensinger22, K. Benslama130, S. Bentvelsen105, M. Beretta47 D. Berge29, E. Bergeaas Kuutmann41, N. Berger4, F. Berghaus168, E. Berglund49, J. Beringer14, P. Bernat115, R. Bernhard48, C. Bernius77, T. Berry76, A. Bertin19a,19b, M.I. Besana89a,89b, N. Besson136, S. Bethke99, R.M. Bianchi48, M. Bianco72a,72b, O. Biebel98, J. Biesiada14, M. Biglietti132a,132b, H. Bilokon47, M. Bindi19a,19b, S. Binet115, A. Bingul18c, C. Bini132a,132b, C. Biscarat179, U. Bitenc48, K.M. Black57, R.E. Blair5, J.-B. Blanchard115, G. Blanchot29, C. Blocker22, A. Blondel49, W. Blum81, U. Blumenschein54, G.J. Bobbink105, A. Bocci44, M. Boehler41, J. Boek173, N. Boelaert79, S. Böser77, J.A. Bogaerts29, A. Bogouch90,†, C. Bohm145a, J. Bohm125, V. Boisvert76, T. Bold162,c, V. Boldea25a, V.G. Bondarenko96, M. Bondioli162, M. Boonekamp136, S. Bordoni78, C. Borer16, A. Borisov128, G. Borissov71, I. Borjanovic72a, S. Borroni132a,132b, K. Bos105, D. Boscherini19a, M. Bosman11, H. Boterenbrood105, J. Bouchami93, J. Boudreau123, E.V. Bouhova-Thacker71, C. Boulahouache123, C. Bourdarios115, A. Boveia30, J. Boyd29, I.R. Boyko65, I. Bozovic-Jelisavcic12b, J. Bracinik17, A. Braem29, P. Branchini134a, G.W. Brandenburg57, A. Brandt7, G. Brandt41, O. Brandt54, U. Bratzler155, B. Brau84, J.E. Brau114, H.M. Braun173, B. Brelier157, J. Bremer29, R. Brenner165, S. Bressler151, D. Britton53, F.M. Brochu27, I. Brock20, R. Brock88, E. Brodet152, C. Bromberg88, G. Brooijmans34, W.K. Brooks31b, G. Brown82, P.A. Bruckman de Renstrom38, D. Bruncko144b, R. Bruneliere48, S. Brunet41, A. Bruni19a, G. Bruni19a, M. Bruschi19a, F. Bucci49, J. Buchanan118, P. Buchholz141, A.G. Buckley45, I.A. Budagov65, B. Budick108, Eur. Phys. J. C (2010) 70: 875–916 876 V. Büscher81, L. Bugge117, O. Bulekov96, M. Bunse42, T. Buran117, H. Burckhart29, S. Burdin73, T. Burgess13, S. Burke129, E. Busato33, P. Bussey53, C.P. Buszello165, F. Butin29, B. Butler143, J.M. Butler21, C.M. Buttar53, J.M. Butterworth77, T. Byatt77, J. Caballero24, S. Cabrera Urbán166, D. Caforio19a,19b, O. Cakir3a, P. Calafiura14, G. Calderini78, P. Calfayan98, R. Calkins106a, L.P. Caloba23a, D. Calvet33, P. Camarri133a,133b, D. Cameron117, S. Campana29, M. Campanelli77, V. Canale102a,102b, F. Canelli30, A. Canepa158a, J. Cantero80, L. Capasso102a,102b, M.D.M. Capeans Garrido29, I. Caprini25a, M. Caprini25a, M. Capua36a,36b, R. Caputo147, C. Caramarcu25a, R. Cardarelli133a, T. Carli29, G. Carlino102a, L. Carminati89a,89b, B. Caron2,b, S. Caron48, G.D. Carrillo Montoya171, S. Carron Montero157, A.A. Carter75, J.R. Carter27, J. Carvalho124a, D. Casadei108, M.P. Casado11, M. Cascella122a,122b, A.M. Castaneda Hernandez171, E. Castaneda-Miranda171, V. Castillo Gimenez166, N.F. Castro124b, G. Cataldi72a, A. Catinaccio29, J.R. Catmore71, A. Cattai29, G. Cattani133a,133b, S. Caughron34, D. Cauz163a,163c, P. Cavalleri78, D. Cavalli89a, M. Cavalli-Sforza11, V. Cavasinni122a,122b, F. Ceradini134a,134b, A.S. Cerqueira23a, A. Cerri29, L. Cerrito75, F. Cerutti47, S.A. Cetin18b, A. Commissioning of the ATLAS Muon Spectrometer with cosmic rays Chafaq135a, D. Chakraborty106a, K. Chan2 J.D. Chapman27, J.W. Chapman87, E. Chareyre78, D.G. Charlton17, V. Chavda82, S. Cheatham71, S. Chekanov5, S.V. Chekulaev158a, G.A. Chelkov65, H. Chen24, S. Chen32c, X. Chen171, A. Cheplakov65, V.F. Chepurnov65, R. Cherkaoui El Moursli135d, V. Tcherniatine24, D. Chesneanu25a, E. Cheu6, S.L. Cheung157, L. Chevalier136, F. Chevallier136, V. Chiarella47, G. Chiefari102a,102b, L. Chikovani51, J.T. Childers58a, A. Chilingarov71, G. Chiodini72a, V. Chizhov65, G. Choudalakis30, S. Chouridou137, I.A. Christidi77, A. Christov48, D. Chromek-Burckhart29, M.L. Chu150, J. Chudoba125, G. Ciapetti132a,132b, A.K. Ciftci3a, R. Ciftci3a, D. Cinca33, V. Cindro74, M.D. Ciobotaru162, C. Ciocca19a,19b, A. Ciocio14, M. Cirilli87, M. Citterio89a, A. Clark49, P.J. Clark45, W. Cleland123, J.C. Clemens83, B. Clement55, C. Clement145a,145b, Y. Coadou83, M. Cobal163a,163c, A. Coccaro50a,50b, J. Cochran64, J. Coggeshall164, E. Cogneras179, A.P. Colijn105, C. Collard115, N.J. Collins17, C. Collins-Tooth53, J. Collot55, G. Colon84, P. Conde Muiño124a, E. Coniavitis165, M. Consonni104, S. Constantinescu25a, C. Conta119a,119b, F. Conventi102a,d, M. Cooke34, B.D. Cooper75, A.M. Cooper-Sarkar118, N.J. Cooper-Smith76, K. Copic34, T. Cornelissen50a,50b, M. Corradi19a, F. Corriveau85,e, A. Corso-Radu162, A. Cortes-Gonzalez164, G. Cortiana99, G. Costa89a, M.J. Costa166, D. Costanzo139, T. Costin30, D. Côté41, R. Coura Torres23a, L. Courneyea168, G. Cowan76, C. Cowden27, B.E. Cox82, K. Cranmer108, J. Cranshaw5, M. Cristinziani20, G. Crosetti36a,36b, R. Crupi72a,72b, S. Crépé-Renaudin55, C .Cuenca Almenar174, T. Cuhadar Donszelmann139, M. Curatolo47, C.J. Curtis17, P. Cwetanski61, Z. Czyczula174, S. D’Auria53, M. D’Onofrio73, A. D’Orazio99, C. Da Via82, W. Dabrowski37, T. Dai87, C. Dallapiccola84, S.J. Dallison129,*, C.H. Daly138, M. Dam35, H.O. Danielsson29, D. Dannheim99, V. Dao49, G. Darbo50a, G.L. Darlea25b, W. Davey86, T. Davidek126, N. Davidson86 R. Davidson71, M. Davies93, A.R. Davison77, I. Dawson139, R.K. Daya39, K. De7, R. de Asmundis102a, S. De Castro19a,19b, P.E. De Castro Faria Salgado24, S. De Cecco78, J. de Graat98, N. De Groot104, P. de Jong105, L. De Mora71, M. De Oliveira Branco29, D. De Pedis132a, A. De Salvo132a, U. De Sanctis163a,163c, A. De Santo148, J.B. De Vivie De Regie115, G. De Zorzi132a,132b, S. Dean77, D.V. Dedovich65, J. Degenhardt120, M. Dehchar118, C. Del Papa163a,163c, J. Del Peso80, T. Del Prete122a,122b, A. Dell’Acqua29, L. Dell’Asta89a,89b, M. Della Pietra102a,d, D. della Volpe102a,102b, M. Delmastro29, P.A. Delsart55, C. Deluca147, S. Demers174, M. Demichev65, B. Demirkoz11, J. Deng162, W. Deng24, S.P. Denisov128, J.E. Derkaoui135c, F. Derue78, P. Dervan73, K. Desch20, P.O. Deviveiros157, A. Dewhurst129, B. DeWilde147, S. Dhaliwal157, R. Dhullipudi24,f, A. Di Ciaccio133a,133b, L. Di Ciaccio4, A. Di Domenico132a,132b, A. Di Girolamo29, B. Di Girolamo29, S. Di Luise134a,134b, A. Di Mattia88, R. Eur. Phys. J. C (2010) 70: 875 916 877 H. Evans61, L. Fabbri19a,19b, C. Fabre29, K. Facius35, R.M. Fakhrutdinov128, S. Falciano132a, Y. Fang171, M. Fanti89a,89b, A. Farbin7, A. Farilla134a, J. Farley147, T. Farooque157, S.M. Farrington118, P. Farthouat29, P. Fassnacht29, D. Fassouliotis8, B. Fatholahzadeh157, L. Fayard115, F. Fayette54, R. Febbraro33, P. Federic144a, O.L. Fedin121, W. Fedorko29, L. Feligioni83, C.U. Felzmann86, C. Feng32d, E.J. Feng30, A.B. Fenyuk128, J. Ferencei144b, J. Ferland93, B. Fernandes124a, W. Fernando109, S. Ferrag53, J. Ferrando118, V. Ferrara41, A. Ferrari165, P. Ferrari105, R. Ferrari119a, A. Ferrer166, M.L. Ferrer47, D. Ferrere49, C. Ferretti87, M. Fiascaris118, F. Fiedler81, A. Filipˇciˇc74, A. Filippas9, F. Filthaut104, M. Fincke-Keeler168, M.C.N. Fiolhais124a, L. Fiorini11, A. Firan39, G. Fischer41, M.J. Fisher109, M. Flechl165, I. Fleck141, J. Fleckner81, P. Fleischmann172, S. Fleischmann20, T. Flick173, L.R. Flores Castillo171, M.J. Flowerdew99, T. Fonseca Martin76, A. Formica136, A. Forti82, D. Fortin158a, D. Fournier115, A.J. Fowler44, K. Fowler137, H. Fox71, P. Francavilla122a,122b, S. Franchino119a,119b, D. Francis29, M. Franklin57, S. Franz29, M. Fraternali119a,119b, S. Fratina120, J. Freestone82, S.T. French27, R. Froeschl29, D. Froidevaux29, J.A. Frost27, C. Fukunaga155, E. Fullana Torregrosa5, J. Fuster166, C. Gabaldon80, O. Gabizon170, T. Gadfort24, S. Gadomski49, G. Gagliardi50a,50b, P. Gagnon61, C. Galea98, E.J. Gallas118, V. Gallo16, B.J. Gallop129, P. Gallus125, E. Galyaev40, K.K. Gan109, Y.S. Gao143,g, A. Gaponenko14, M. Garcia-Sciveres14, C. García166, J.E. García Navarro49, R.W. Gardner30, N. Garelli29, H. Garitaonandia105, V. Garonne29, C. Gatti47, G. Gaudio119a, V. Gautard136, P. Gauzzi132a,132b, I.L. Gavrilenko94, C. Gay167, G. Gaycken20, E.N. Gazis9, P. Ge32d, C.N.P. Gee129, Ch. Geich-Gimbel20, K. Gellerstedt145a,145b, C. Gemme50a, M.H. Genest98, S. Gentile132a,132b, F. Georgatos9, S. George76, A. Gershon152, H. Ghazlane135d, N. Ghodbane33, B. Giacobbe19a, S. Giagu132a,132b, V. Giakoumopoulou8, V. Giangiobbe122a,122b, F. Gianotti29, B. Gibbard24, A. Gibson157, S.M. Gibson118, L.M. Gilbert118, M. Gilchriese14, V. Gilewsky91, D.M. Gingrich2,b, J. Ginzburg152, N. Giokaris8, M.P. Giordani163a,163c, R. Giordano102a,102b, F.M. Giorgi15, P. Giovannini99, P.F. Giraud29, P. Girtler62, D. Giugni89a, P. Giusti19a, B.K. Gjelsten117, L.K. Gladilin97, C. Glasman80, A. Glazov41, K.W. Glitza173, G.L. Glonti65, J. Godfrey142, J. Godlewski29, M. Goebel41, T. Göpfert43, C. Goeringer81, C. Gössling42, T. Göttfert99, V. Goggi119a,119b„h, S. Goldfarb87, D. Goldin39, T. Golling174, A. Gomes124a, L.S. Gomez Fajardo41, R. Gonçalo76, L. Gonella20, C. Gong32b, S. González de la Hoz166, M.L. Gonzalez Silva26, S. Gonzalez-Sevilla49, J.J. Goodson147, L. Goossens29, H.A. Gordon24, I. Gorelov103, G. Gorfine173, B. Gorini29, E. Gorini72a,72b, A. Gorišek74, E. Gornicki38, B. Gosdzik41, M. Gosselink105, M.I. Gostkin65, I. Gough Eschrich162, M. Gouighri135a, D. Goujdami135a, M.P. Goulette49, A.G. Goussiou138, C. Goy4, I. Grabowska-Bold162,c, P. Grafström29, K.-J. Grahn146, S. Grancagnolo15, V. Grassi147, V. Gratchev121, N. Grau34, H.M. Gray34,i, J.A. Gray147, E. Graziani134a, B. Green76, T. Greenshaw73, Z.D. Greenwood24,f, I.M. Gregor41, P. Grenier143, E. Griesmayer46, J. Griffiths138, N. Grigalashvili65, A.A. Grillo137, K. Grimm147, S. Grinstein11, Y.V. Grishkevich97, M. Groh99, M. Groll81, E. Gross170, J. Grosse-Knetter54, J. Groth-Jensen79, K. Grybel141, C. Guicheney33, A. Guida72a,72b, T. Guillemin4, H. Guler85,j, J. Gunther125, B. Guo157, A. Gupta30, Y. Gusakov65, A. Gutierrez93, P. Gutierrez111, N. Guttman152, O. Gutzwiller171, C. Guyot136, C. Gwenlan118, C.B. Gwilliam73, A. Haas143, S. Haas29, C. Haber14, H.K. Hadavand39, D.R. Hadley17, P. Haefner99, R. Härtel99, Z. Hajduk38, H. Hakobyan175, J. Haller41,k, K. Hamacher173, A. Hamilton49, S. Hamilton160, L. Han32b, K. Hanagaki116, M. Hance120, C. Handel81, P. Hanke58a, J.R. Hansen35, J.B. Hansen35, J.D. Hansen35, P.H. Hansen35, T. Hansl-Kozanecka137, P. Hansson143, K. Hara159, G.A. Hare137, T. Harenberg173, R.D. Harrington21, O.M. Harris138, K. Harrison17, J. Hartert48, F. Hartjes105, A. Harvey56, S. Hasegawa101, Y. Hasegawa140, K. Hashemi22, S. Hassani136, S. Haug16, M. Hauschild29, R. Hauser88, M. Havranek125, C.M. Hawkes17, R.J. Hawkings29, T. Hayakawa67, H.S. Hayward73, S.J. Haywood129, S.J. Head82, V. Hedberg79, L. Heelan28, S. Heim88, B. Heinemann14, S. Heisterkamp35, L. Helary4, M. Heller115, S. Hellman145a,145b, C. Helsens11, T. Hemperek20, R.C.W. Henderson71, M. Henke58a, A. Henrichs54, A.M. Henriques Correia29, S. Henrot-Versille115, C. Hensel54, T. Henß173, Y. Hernández Jiménez166, A.D. Hershenhorn151, G. Herten48, R. Hertenberger98, L. Hervas29, N.P. Hessey105, E. Higón-Rodriguez166, J.C. Hill27, K.H. Hiller41, S. Hillert145a,145b, S.J. Hillier17, I. Hinchliffe14, E. Hines120, M. Hirose116, F. Hirsch42, D. Hirschbuehl173, J. Hobbs147, N. Hod152, M.C. Hodgkinson139, P. Hodgson139, A. Hoecker29, M.R. Hoeferkamp103, J. Hoffman39, D. Hoffmann83, M. Hohlfeld81, T. Holy127, J.L. Holzbauer88, Y. Homma67, T. Horazdovsky127, T. Hori67, C. Horn143, S. Horner48, S. Horvat99, J.-Y. Hostachy55, S. Hou150, A. Hoummada135a, T. Howe39, J. Hrivnac115, T. Hryn’ova4, P.J. Hsu174, S.-C. Hsu14, G.S. Huang111, Z. Hubacek127, F. Hubaut83, F. Huegging20, E.W. Hughes34, G. Hughes71, M. Hurwitz30, U. Husemann41, N. Huseynov10, J. Huston88, J. Huth57, G. Iacobucci102a, G. Iakovidis9, I. Ibragimov141, L. Iconomidou-Fayard115, J. Idarraga158b, P. Iengo4, O. Igonkina105, Y. Ikegami66, M. Ikeno66, Y. Ilchenko39, D. Iliadis153, T. Ince168, P. Ioannou8, M. Iodice134a, 1, L. Fabbri19a,19b, C. Fabre29, K. Facius35, R.M. Fakhrutdinov128, S. Falciano132a, Y. Fang171, Commissioning of the ATLAS Muon Spectrometer with cosmic rays Di Nardo133a,133b, A. Di Simone133a,133b, R. Di Sipio19a,19b, M.A. Diaz31a, F. Diblen18c, E.B. Diehl87, J. Dietrich48, T.A. Dietzsch58a, S. Diglio115, K. Dindar Yagci39, J. Dingfelder48, C. Dionisi132a,132b, P. Dita25a, S. Dita25a, F. Dittus29 F. Djama83, R. Djilkibaev108, T. Djobava51, M.A.B. do Vale23a, A. Do Valle Wemans124a, T.K.O. Doan4, D. Dobos29, E. Dobson29, M. Dobson162, C. Doglioni118, T. Doherty53, J. Dolejsi126, I. Dolenc74, Z. Dolezal126, B.A. Dolgoshein96 T. Dohmae154, M. Donega120, J. Donini55, J. Dopke173, A. Doria102a, A. Dos Anjos171, A. Dotti122a,122b, M.T. Dova70, A. Doxiadis105, A.T. Doyle53, Z. Drasal126, M. Dris9, J. Dubbert99, E. Duchovni170, G. Duckeck98, A. Dudarev29, F. Dudziak115, M. Dührssen29, L. Duflot115, M.-A. Dufour85, M. Dunford30, H. Duran Yildiz3b, A. Dushkin22, R. Duxfield139, M. Dwuznik37, M. Düren52, W.L. Ebenstein44, J. Ebke98, S. Eckweiler81, K. Edmonds81, C.A. Edwards76, K. Egorov61, W. Ehrenfeld41, T. Ehrich99, T. Eifert29, G. Eigen13, K. Einsweiler14, E. Eisenhandler75, T. Ekelof165, M. El Kacimi4, M. Ellert165, S. Elles4, F. Ellinghaus81, K. Ellis75, N. Ellis29, Eur. Phys. J. C (2010) 70: 875–916 877 Eur. Phys. J. C (2010) 70: 875–916 877 H. Evans61, L. Fabbri19a,19b, C. Fabre29, K. Facius35, R.M. Fakhrutdinov128, S. Falciano132a, Y. Fang171, M. Fanti89a,89b, A. Farbin7, A. Farilla134a, J. Farley147, T. Farooque157, S.M. Farrington118, P. Farthouat29, P. Fassnacht29, D. Fassouliotis8, B. Fatholahzadeh157, L. Fayard115, F. Fayette54, R. Febbraro33, P. Federic144a, O.L. Fedin121, W. Fedorko29, L. Feligioni83, C.U. Felzmann86, C. Feng32d, E.J. Feng30, A.B. Fenyuk128, J. Ferencei144b, J. Ferland93, B. Fernandes124a, W. Fernando109, S. Ferrag53, J. Ferrando118, V. Ferrara41, A. Ferrari165, P. Ferrari105, R. Ferrari119a, A. Ferrer166, M.L. Ferrer47, D. Ferrere49, C. Ferretti87, M. Fiascaris118, F. Fiedler81, A. Filipˇciˇc74, A. Filippas9, F. Filthaut104, M. Fincke-Keeler168, M.C.N. Fiolhais124a, L. Fiorini11, A. Firan39, G. Fischer41, M.J. Fisher109, M. Flechl165, I. Fleck141, J. Fleckner81, P. Fleischmann172, S. Fleischmann20, T. Flick173, L.R. Flores Castillo171, M.J. Flowerdew99, T. Fonseca Martin76, A. Formica136, A. Forti82, D. Fortin158a, D. Fournier115, A.J. Fowler44, K. Fowler137, H. Fox71, P. Francavilla122a,122b, S. Franchino119a,119b, D. Francis29, M. Franklin57, S. Franz29, M. Fraternali119a,119b, S. Fratina120, J. Freestone82, S.T. French27, R. Froeschl29, D. Froidevaux29, J.A. Frost27, C. Fukunaga155, E. Fullana Torregrosa5, J. Fuster166, C. Gabaldon80, O. Gabizon170, T. Gadfort24, S. Gadomski49, G. Gagliardi50a,50b, P. Gagnon61, C. Galea98, E.J. Gallas118, V. Gallo16, B.J. Gallop129, P. Gallus125, E. Galyaev40, K.K. Gan109, Y.S. Gao143,g, A. Gaponenko14, M. Garcia-Sciveres14, C. García166, J.E. García Navarro49, R.W. Gardner30, N. Garelli29, H. Garitaonandia105, V. Garonne29, C. Gatti47, G. Gaudio119a, V. Gautard136, P. Gauzzi132a,132b, I.L. Commissioning of the ATLAS Muon Spectrometer with cosmic rays Gavrilenko94, C. Gay167, G. Gaycken20, E.N. Gazis9, P. Ge32d, C.N.P. Gee129, Ch. Geich-Gimbel20, K. Gellerstedt145a,145b, C. Gemme50a, M.H. Genest98, S. Gentile132a,132b, F. Georgatos9, S. George76, A. Gershon152, H. Ghazlane135d, N. Ghodbane33, B. Giacobbe19a, S. Giagu132a,132b, V. Giakoumopoulou8, V. Giangiobbe122a,122b, F. Gianotti29, B. Gibbard24, A. Gibson157, S.M. Gibson118, L.M. Gilbert118, M. Gilchriese14, V. Gilewsky91, D.M. Gingrich2,b, J. Ginzburg152, N. Giokaris8, M.P. Giordani163a,163c, R. Giordano102a,102b, F.M. Giorgi15, P. Giovannini99, P.F. Giraud29, P. Girtler62, D. Giugni89a, P. Giusti19a, B.K. Gjelsten117, L.K. Gladilin97, C. Glasman80, A. Glazov41, K.W. Glitza173, G.L. Glonti65, J. Godfrey142, J. Godlewski29, M. Goebel41, T. Göpfert43, C. Goeringer81, C. Gössling42, T. Göttfert99 V. Goggi119a,119b„h, S. Goldfarb87, D. Goldin39, T. Golling174, A. Gomes124a, L.S. Gomez Fajardo41, R. Gonçalo76, L. Gonella20, C. Gong32b, S. González de la Hoz166, M.L. Gonzalez Silva26, S. Gonzalez-Sevilla49, J.J. Goodson147, L. Goossens29, H.A. Gordon24, I. Gorelov103, G. Gorfine173, B. Gorini29, E. Gorini72a,72b, A. Gorišek74, E. Gornicki38, B. Gosdzik41, M. Gosselink105, M.I. Gostkin65, I. Gough Eschrich162, M. Gouighri135a, D. Goujdami135a, M.P. Goulette49, A.G. Goussiou138, C. Goy4, I. Grabowska-Bold162,c, P. Grafström29, K.-J. Grahn146, S. Grancagnolo15, V. Grassi147, V. Gratchev121, N. Grau34, H.M. Gray34,i, J.A. Gray147, E. Graziani134a, B. Green76, T. Greenshaw73, Z.D. Greenwood24,f, I.M. Gregor41, P. Grenier143, E. Griesmayer46, J. Griffiths138, N. Grigalashvili65, A.A. Grillo137, K. Grimm147, S. Grinstein11, Y.V. Grishkevich97, M. Groh99, M. Groll81, E. Gross170, J. Grosse-Knetter54, J. Groth-Jensen79, K. Grybel141, C. Guicheney33, A. Guida72a,72b, T. Guillemin4, H. Guler85,j, J. Gunther125, B. Guo157, A. Gupta30, Y. Gusakov65, A. Gutierrez93, P. Gutierrez111, N. Guttman152, O. Gutzwiller171, C. Guyot136, C. Gwenlan118, C.B. Gwilliam73, A. Haas143, S. Haas29, C. Haber14, H.K. Hadavand39, D.R. Hadley17, P. Haefner99, R. Härtel99, Z. Hajduk38, H. Hakobyan175, J. Haller41,k, K. Hamacher173, A. Hamilton49, S. Hamilton160, L. Han32b, K. Hanagaki116, M. Hance120, C. Handel81, P. Hanke58a, J.R. Hansen35, J.B. Hansen35, J.D. Hansen35, P.H. Hansen35, T. Hansl-Kozanecka137, P. Hansson143, K. Hara159, G.A. Hare137, T. Harenberg173, R.D. Harrington21, O.M. Harris138, K. Harrison17, J. Hartert48, F. Hartjes105, A. Harvey56, S. Hasegawa101, Y. Hasegawa140, K. Hashemi22, S. Hassani136, S. Haug16, M. Hauschild29, R. Hauser88 M. Havranek125, C.M. Hawkes17, R.J. Hawkings29, T. Hayakawa67, H.S. Hayward73, S.J. Haywood129, S.J. Head82, V. Hedberg79, L. Heelan28, S. Heim88, B. Heinemann14, S. Heisterkamp35, L. Helary4, M. Heller115, S. Hellman145a,145b, C. Helsens11, T. Hemperek20, R.C.W. Henderson71, M. Henke58a, A. Henrichs54, A.M. Henriques Correia29, S. Henrot-Versille115, C. Hensel54, T. Henß173, Y. Hernández Jiménez166, A.D. Hershenhorn151, G. Herten48, R. Hertenberger98, L. Hervas29, N.P. Hessey105, E. Higón-Rodriguez166, J.C. Hill27, K.H. Commissioning of the ATLAS Muon Spectrometer with cosmic rays Hiller41, S. Hillert145a,145b, S.J. Hillier17, I. Hinchliffe14, E. Hines120, M. Hirose116, F. Hirsch42, D. Hirschbuehl173, J. Hobbs147, N. Hod152, M.C. Hodgkinson139, P. Hodgson139, A. Hoecker29, M.R. Hoeferkamp103 J. Hoffman39, D. Hoffmann83, M. Hohlfeld81, T. Holy127, J.L. Holzbauer88, Y. Homma67, T. Horazdovsky127, T. Hori67, C. Horn143, S. Horner48, S. Horvat99, J.-Y. Hostachy55, S. Hou150, A. Hoummada135a, T. Howe39, J. Hrivnac115, T. Hryn’ova4, P.J. Hsu174, S.-C. Hsu14, G.S. Huang111, Z. Hubacek127, F. Hubaut83, F. Huegging20, E.W. Hughes34, G. Hughes71, M. Hurwitz30, U. Husemann41, N. Huseynov10, J. Huston88, J. Huth57, G. Iacobucci102a, G. Iakovidis9, I. Ibragimov141, L. Iconomidou-Fayard115, J. Idarraga158b, P. Iengo4, O. Igonkina105, Y. Ikegami66, M. Ikeno66, Y. Ilchenko39, D. Iliadis153, T. Ince168, P. Ioannou8, M. Iodice134a, O. Igonkina105, Y. Ikegami66, M. Ikeno66, Y. Ilchenko39, D. Iliadis153, T. Ince168, P. Ioannou8, M. Iodice134a, 878 Eur. Phys. J. C (2010) 70: 875–916 A. Irles Quiles166, A. Ishikawa67, M. Ishino66, R. Ishmukhametov39, T. Isobe154, V. Issakov174,*, C. Issever118, S. Istin18a, Y. Itoh101, A.V. Ivashin128, W. Iwanski38, H. Iwasaki66, J.M. Izen40, V. Izzo102a, B. Jackson120, J.N. Jackson73, P. Jackson143, M.R. Jaekel29, V. Jain61, K. Jakobs48, S. Jakobsen35, J. Jakubek127, D.K. Jana111, E. Jansen104, A. Jantsch99, M. Janus48, R.C. Jared171, G. Jarlskog79, L. Jeanty57, I. Jen-La Plante30, P. Jenni29, P. Jez35, S. Jézéquel4, W. Ji79, J. Jia147, Y. Jiang32b, M. Jimenez Belenguer29, S. Jin32a, O. Jinnouchi156, D. Joffe39, M. Johansen145a,145b, K.E. Johansson145a, P. Johansson139, S. Johnert41, K.A. Johns6, K. Jon-And145a,145b, G. Jones82, R.W.L. Jones71, T.J. Jones73, P.M. Jorge124a, J. Joseph14, V. Juranek125, P. Jussel62, V.V. Kabachenko12 M. Kaci166, A. Kaczmarska38, M. Kado115, H. Kagan109, M. Kagan57, S. Kaiser99, E. Kajomovitz151, S. Kalinin173 L.V. Kalinovskaya65, A. Kalinowski130, S. Kama41, N. Kanaya154, M. Kaneda154, V.A. Kantserov96, J. Kanzaki66, B. Kaplan174, A. Kapliy30, J. Kaplon29, D. Kar43, M. Karagounis20, M. Karagoz Unel118, V. Kartvelishvili71, A.N. Karyukhin128, L. Kashif57, A. Kasmi39, R.D. Kass109, A. Kastanas13, M. Kastoryano174, M. Kataoka4, Y. Kataoka154, E. Katsoufis9, J. Katzy41, V. Kaushik6, K. Kawagoe67, T. Kawamoto154, G. Kawamura81, M.S. Kayl105, F. Kayumov94, V.A. Kazanin107, M.Y. Kazarinov65, J.R. Keates82, R. Keeler168, P.T. Keener120, R. Kehoe39, M. Keil54, G.D. Kekelidze65, M. Kelly82, M. Kenyon53, O. Kepka125, N. Kerschen29, B.P. Kerševan74, S. Kersten173, K. Kessoku154, M. Khakzad28, F. Khalil-zada10, H. Khandanyan164, A. Khanov112, D. Kharchenko6 A. Khodinov147, A. Khomich58a, G. Khoriauli20, N. Khovanskiy65, V. Khovanskiy95, E. Khramov65, J. Khubua51, H. Kim7, M.S. Kim2, P.C. Kim143, S.H. Kim159, O. Kind15, P. Kind173, B.T. King73, J. Kirk129, G.P. Kirsch118, L.E. Commissioning of the ATLAS Muon Spectrometer with cosmic rays Kirsch22, A.E. Kiryunin99, D. Kisielewska37, T. Kittelmann123, H. Kiyamura67, E. Kladiva144b, M. Klein73, U. Klein73, K. Kleinknecht81, M. Klemetti85, A. Klier170, A. Klimentov24, R. Klingenberg42, E.B. Klinkby44, T. Klioutchnikova29, P.F. Klok104, S. Klous105, E.-E. Kluge58a, T. Kluge73, P. Kluit105, M. Klute54, S. Kluth99, N.S. Knecht157, E. Kneringer62, B.R. Ko44, T. Kobayashi154, M. Kobel43, B. Koblitz29, M. Kocian143, A. Kocnar113 P. Kodys126, K. Köneke41, A.C. König104, S. Koenig81, L. Köpke81, F. Koetsveld104, P. Koevesarki20, T. Koffas29, E. Koffeman105, F. Kohn54, Z. Kohout127, T. Kohriki66, H. Kolanoski15, V. Kolesnikov65, I. Koletsou4, J. Koll88, D. Kollar29, S. Kolos162,l, S.D. Kolya82, A.A. Komar94, J.R. Komaragiri142, T. Kondo66, T. Kono41,k, R. Konoplich1 S.P. Konovalov94, N. Konstantinidis77, S. Koperny37, K. Korcyl38, K. Kordas153, A. Korn14, I. Korolkov11, E.V. Korolkova139, V.A. Korotkov128, O. Kortner99, P. Kostka41, V.V. Kostyukhin20, S. Kotov99, V.M. Kotov65, K.Y. Kotov107, C. Kourkoumelis8, A. Koutsman105, R. Kowalewski168, H. Kowalski41, T.Z. Kowalski37, W. Kozanecki136, A.S. Kozhin128, V. Kral127, V.A. Kramarenko97, G. Kramberger74, M.W. Krasny78, A. Krasznahorkay108, A. Kreisel152, F. Krejci127, J. Kretzschmar73, N. Krieger54, P. Krieger157, K. Kroeninger54, H. Kroha99, J. Kroll120, J. Kroseberg20, J. Krstic12a, U. Kruchonak65, H. Krüger20, Z.V. Krumshteyn65, T. Kubota154, S. Kuehn48, A. Kugel58c, T. Kuhl173, D. Kuhn62, V. Kukhtin65, Y. Kulchitsky90, S. Kuleshov31b, C. Kummer98, M. Kuna83, J. Kunkle120, A. Kupco125, H. Kurashige67, M. Kurata159, L.L. Kurchaninov158a, Y.A. Kurochkin90, V. Kus125, R. Kwee15, L. La Rotonda36a,36b, J. Labbe4, C. Lacasta166, F. Lacava132a,132b, H. Lacker15, D. Lacour78, V.R. Lacuesta166, E. Ladygin65, R. Lafaye4, B. Laforge78, T. Lagouri80, S. Lai48, M. Lamanna29, C.L. Lampen6, W. Lampl6, E. Lancon136, U. Landgraf48, M.P.J. Landon75, J.L. Lane82, A.J. Lankford162, F. Lanni24, K. Lantzsch29, A. Lanza119a, S. Laplace4, C. Lapoire83, J.F. Laporte136, T. Lari89a, A. Larner118, M. Lassnig29, P. Laurelli47, W. Lavrijsen14, P. Laycock73, A.B. Lazarev65, A. Lazzaro89a,89b, O. Le Dortz78, E. Le Guirriec83, E. Le Menedeu136, M. Le Vine24, A. Lebedev64, C. Lebel93, T. LeCompte5, F. Ledroit-Guillon55, H. Lee105, J.S.H. Lee149, S.C. Lee150, M. Lefebvre168, M. Legendre136, B.C. LeGeyt120, F. Legger98, C. Leggett14, M. Lehmacher20, G. Lehmann Miotto29, X. Lei6, R. Leitner126, D. Lellouch170, J. Lellouch78, V. Lendermann58a, K.J.C. Leney73, T. Lenz173, G. Lenzen173, B. Lenzi136, K. Leonhardt43, C. Leroy J.-R. Lessard168, C.G. Lester27, A. Leung Fook Cheong171, J. Levêque83, D. Levin87, L.J. Levinson170, M. Leyton1 H. Li171, S. Li41, X. Li87, Z. Liang39, Z. Liang150,m, B. Liberti133a, P. Lichard29, M. Lichtnecker98, K. Lie164, W. Liebig105, J.N. Lilley17, H. Lim5, A. Limosani86, M. Limper63, S.C. 878 Eur. Phys. J. C (2010) 70: 875 91 A. Irles Quiles166, A. Ishikawa67, M. Ishino66, R. Ishmukhametov39, T. Isobe154, V. Issakov174,*, C. Issever118, S. Istin18a, Y. Itoh101, A.V. Ivashin128, W. Iwanski38, H. Iwasaki66, J.M. Izen40, V. Izzo102a, B. Jackson120, J.N. Jackson73, P. Jackson143, M.R. Jaekel29, V. Jain61, K. Jakobs48, S. Jakobsen35, J. Jakubek127, D.K. Jana111, E. Jansen104, A. Jantsch99, M. Janus48, R.C. Jared171, G. Jarlskog79, L. Jeanty57, I. Jen-La Plante30, P. Jenni29, P. Jez35, S. Jézéquel4, W. Ji79, J. Jia147, Y. Jiang32b, M. Jimenez Belenguer29, S. Jin32a, O. Jinnouchi156, D. Joffe39, M. Johansen145a,145b, K.E. Johansson145a, P. Johansson139, S. Johnert41, K.A. Johns6, K. Jon-And145a,145b, G. Jones82, R.W.L. Jones71, T.J. Jones73, P.M. Jorge124a, J. Joseph14, V. Juranek125, P. Jussel62, V.V. Kabachenko128 M. Kaci166, A. Kaczmarska38, M. Kado115, H. Kagan109, M. Kagan57, S. Kaiser99, E. Kajomovitz151, S. Kalinin173, L.V. Kalinovskaya65, A. Kalinowski130, S. Kama41, N. Kanaya154, M. Kaneda154, V.A. Kantserov96, J. Kanzaki66, B. Kaplan174, A. Kapliy30, J. Kaplon29, D. Kar43, M. Karagounis20, M. Karagoz Unel118, V. Kartvelishvili71, A.N. Karyukhin128, L. Kashif57, A. Kasmi39, R.D. Kass109, A. Kastanas13, M. Kastoryano174, M. Kataoka4, Y. Kataoka154, E. Katsoufis9, J. Katzy41, V. Kaushik6, K. Kawagoe67, T. Kawamoto154, G. Kawamura81, M.S. Kayl105, F. Kayumov94, V.A. Kazanin107, M.Y. Kazarinov65, J.R. Keates82, R. Keeler168, P.T. Keener120, R. Kehoe39, M. Keil54, G.D. Kekelidze65, M. Kelly82, M. Kenyon53, O. Kepka125, N. Kerschen29, B.P. Kerševan74, S. Kersten173, K. Kessoku154, M. Khakzad28, F. Khalil-zada10, H. Khandanyan164, A. Khanov112, D. Kharchenko65, A. Khodinov147, A. Khomich58a, G. Khoriauli20, N. Khovanskiy65, V. Khovanskiy95, E. Khramov65, J. Khubua51, H. Kim7, M.S. Kim2, P.C. Kim143, S.H. Kim159, O. Kind15, P. Kind173, B.T. King73, J. Kirk129, G.P. Kirsch118, L.E. Kirsch22, A.E. Kiryunin99, D. Kisielewska37, T. Kittelmann123, H. Kiyamura67, E. Kladiva144b, M. Klein73, U. Klein73, K. Kleinknecht81, M. Klemetti85, A. Klier170, A. Klimentov24, R. Klingenberg42, E.B. Klinkby44, T. Klioutchnikova29, P.F. Klok104, S. Klous105, E.-E. Kluge58a, T. Kluge73, P. Kluit105, M. Klute54, S. Kluth99, N.S. Knecht157, E. Kneringer62, B.R. Ko44, T. Kobayashi154, M. Kobel43, B. Koblitz29, M. Kocian143, A. Kocnar113, P. Kodys126, K. Köneke41, A.C. König104, S. Koenig81, L. Köpke81, F. Koetsveld104, P. Koevesarki20, T. Koffas29, E. Koffeman105, F. Kohn54, Z. Kohout127, T. Kohriki66, H. Kolanoski15, V. Kolesnikov65, I. Koletsou4, J. Koll88, D. Kollar29, S. Kolos162,l, S.D. Kolya82, A.A. Komar94, J.R. Komaragiri142, T. Kondo66, T. Kono41,k, R. Konoplich10 S.P. Konovalov94, N. Konstantinidis77, S. Koperny37, K. Korcyl38, K. Kordas153, A. Korn14, I. Korolkov11, E.V. Korolkova139, V.A. Korotkov128, O. Kortner99, P. Kostka41, V.V. Kostyukhin20, S. Kotov99, V.M. Kotov65, K.Y. Kotov107, C. Kourkoumelis8, A. Koutsman105, R. Kowalewski168, H. Kowalski41, T.Z. Kowalski37, W. Kozanecki136, A.S. Kozhin128, V. Kral127, V.A. Kramarenko97, G. Kramberger74, M.W. Krasny78, A. Krasznahorkay108, A. Kreisel152, F. Krejci127, J. Kretzschmar73, N. Krieger54, P. Krieger157, K. Kroeninger54, H. Kroha99, J. Kroll120, J. Kroseberg20, J. Krstic12a, U. Kruchonak65, H. Krüger20, Z.V. Krumshteyn65, T. Kubota154, S. Kuehn48, A. Kugel58c, T. Kuhl173, D. Kuhn62, V. Kukhtin65, Y. Kulchitsky90, S. Kuleshov31b, C. Kummer98, M. Kuna83, J. Kunkle120, A. Kupco125, H. Kurashige67, M. Kurata159, L.L. Kurchaninov158a, Y.A. Kurochkin90, V. Kus125, R. Kwee15, L. La Rotonda36a,36b, J. Labbe4, C. Lacasta166, F. Lacava132a,132b, H. Lacker15, D. Lacour78, V.R. Lacuesta166, E. Ladygin65, R. Lafaye4, B. Laforge78, T. Lagouri80, S. Lai48, M. Lamanna29, C.L. Lampen6, W. Lampl6, E. Lancon136, U. Landgraf48, M.P.J. Landon75, J.L. Lane82, A.J. Lankford162, F. Lanni24, K. Lantzsch29, A. Lanza119a, S. Laplace4, C. Lapoire83, J.F. Laporte136, T. Lari89a, A. Larner118, M. Lassnig29, P. Laurelli47, W. Lavrijsen14, P. Laycock73, A.B. Lazarev65, A. Lazzaro89a,89b, O. Le Dortz78, E. Le Guirriec83, E. Le Menedeu136, M. Le Vine24, A. Lebedev64, C. Lebel93, T. LeCompte5, F. Ledroit-Guillon55, H. Lee105, J.S.H. Lee149, S.C. Lee150, M. Lefebvre168, M. Legendre136, B.C. LeGeyt120, F. Legger98, C. Leggett14, M. Lehmacher20, G. Lehmann Miotto29, X. Lei6, R. Leitner126, D. Lellouch170, J. Lellouch78, V. Lendermann58a, K.J.C. Leney73, T. Lenz173, G. Lenzen173, B. Lenzi136, K. Leonhardt43, C. Leroy93 J.-R. Lessard168, C.G. Lester27, A. Leung Fook Cheong171, J. Levêque83, D. Levin87, L.J. Levinson170, M. Leyton14, H. Li171, S. Li41, X. Li87, Z. Liang39, Z. Liang150,m, B. Liberti133a, P. Lichard29, M. Lichtnecker98, K. Lie164, W. Liebig105, J.N. Lilley17, H. Lim5, A. Limosani86, M. Limper63, S.C. Lin150, J.T. Linnemann88, E. Lipeles120, L. Lipinsky125, A. Lipniacka13, T.M. Liss164, D. Lissauer24, A. Lister49, A.M. Litke137, C. Liu28, D. Liu150,n, H. Liu87 J.B. Liu87, M. Liu32b, T. Liu39, Y. Liu32b, M. Livan119a,119b, A. Lleres55, S.L. Lloyd75, E. Lobodzinska41, P. Loch6, W.S. Lockman137, S. Lockwitz174, T. Loddenkoetter20, F.K. Loebinger82, A. Loginov174, C.W. Loh167, T. Lohse15, K. Lohwasser48, M. Lokajicek125, R.E. Long71, L. Lopes124a, D. Lopez Mateos34,i, M. Losada161, P. Loscutoff14, X. Lou40, A. Lounis115, K.F. Loureiro109, L. Lovas144a, J. Love21, P.A. Love71, A.J. Lowe61, F. Lu32a, H.J. Lubatti138 C. Luci132a,132b, A. Lucotte55, A. Ludwig43, D. Ludwig41, I. Ludwig48, F. Luehring61, L. Luisa163a,163c, D. Lumb48, L. Luminari132a, E. Lund117, B. Lund-Jensen146, B. Lundberg79, J. Lundberg29, J. Lundquist35, D. Lynn24, J. Lys14 E L k 79 H M 24 L L M 171 J A M G i 93 G M 47 A M hi l 99 B M ˇ k74 J. Machado Miguens124a, R. Mackeprang35, R.J. Madaras14, W.F. Mader43, R. Maenner58c, T. Maeno24, P. Mättig173, S. Mättig41, P.J. Magalhaes Martins124a, E. Magradze51, Y. Mahalalel152, K. Mahboubi48, A. Mahmood1, C. Maiani132a,132b, C. Maidantchik23a, A. Maio124a, S. Majewski24, Y. Makida66, M. Makouski128, N. Makovec115, Pa. Malecki38, P. Malecki38, V.P. Maleev121, F. Malek55, U. Mallik63, D. Malon5, S. Maltezos9, V. Malyshev107, S. Malyukov65, M. Mambelli30, R. Mameghani98, J. Mamuzic41, L. Mandelli89a, I. Mandi´c74, R. Mandrysch15, J. Maneira124a, P.S. Mangeard88, I.D. Manjavidze65, P.M. Manning137, A. Manousakis-Katsikakis8, B. Mansoulie136, A. Mapelli29, L. Mapelli29, L. March80, J.F. Marchand4, F. Marchese133a,133b, G. Marchiori78, M. Marcisovsky125, C.P. Marino61, F. Marroquim23a, Z. Marshall34,i, S. Marti-Garcia166, A.J. Martin75, A.J. Martin174, B. Martin29, B. Martin88, F.F. Martin120, J.P. Martin93, T.A. Martin17, B. Martin dit Latour49, M. Martinez11, V. Martinez Outschoorn57, A. Martini47, A.C. Martyniuk82, F. Marzano132a, A. Marzin136, L. Masetti20, T. Mashimo154, R. Mashinistov96, J. Masik82, A.L. Maslennikov107, I. Massa19a,19b, N. Massol4, A. Mastroberardino36a,36b, T. Masubuchi154, P. Matricon115, H. Matsunaga154, T. Matsushita67, C. Mattravers118,o, S.J. Maxfield73, A. Mayne139, R. Mazini150, M. Mazur48, M. Mazzanti89a, J. Mc Donald85, S.P. Mc Kee87, A. McCarn164, R.L. McCarthy147, N.A. McCubbin129, K.W. McFarlane56, H. McGlone53, G. Mchedlidze51, S.J. McMahon129, R.A. McPherson168,e, A. Meade84, J. Mechnich105, M. Mechtel173, M. Medinnis41, R. Meera-Lebbai111, T.M. Meguro116, S. Mehlhase41, A. Mehta73, K. Meier58a, B. Meirose48, C. Melachrinos30, B.R. Mellado Garcia171, L. Mendoza Navas161, Z. Meng150,p, S. Menke99, E. Meoni11, P. Mermod118, L. Merola102a,102b, C. Meroni89a, F.S. Merritt30, A.M. Messina29, J. Metcalfe103, A.S. Mete64, J.-P. Meyer136, J. Meyer172, J. Meyer54, T.C. Meyer29, W.T. Meyer64, J. Miao32d, S. Michal29, L. Micu25a, R.P. Middleton129, S. Migas73, L. Mijovi´c74, G. Mikenberg170, M. Mikestikova125, M. Mikuž74, D.W. Miller143, W.J. Mills167, C.M. Mills57, A. Milov170, D.A. Milstead145a,145b, D. Milstein170, A.A. Minaenko128, M. Miñano166, I.A. Minashvili65, A.I. Mincer108, B. Mindur37, M. Mineev65, Y. Ming130, L.M. Mir11, G. Mirabelli132a, S. Misawa24, S. Miscetti47, A. Misiejuk76, J. Mitrevski137, V.A. Mitsou166, P.S. Miyagawa82, J.U. Mjörnmark79, D. Mladenov22, T. Moa145a,145b, S. Moed57, V. Moeller27, K. Mönig41, N. Möser20, W. Mohr48, S. Mohrdieck-Möck99, R. Moles-Valls166, J. Molina-Perez29, J. Monk77, E. Monnier83, S. Montesano89a,89b, F. Monticelli70, R.W. Moore2, C. Mora Herrera49, A. Moraes53, A. Morais124a, J. Morel54, G. Morello36a,36b, D. Moreno161, M. Moreno Llácer166, P. Morettini50a, M. Morii57, A.K. Morley86, G. Mornacchi29, S.V. Morozov96, J.D. Morris75, H.G. Moser99, M. Mosidze51, J. Moss109, R. Mount143, E. Mountricha136, S.V. Mouraviev94, E.J.W. Moyse84, M. Mudrinic12b, F. Mueller58a, J. Mueller123, K. Mueller20, T.A. Müller98, D. Muenstermann42, A. Muir167, Y. Munwes152, R. Murillo Garcia162, W.J. Murray129, I. Mussche105, E. Musto102a,102b, A.G. Myagkov128, M. Myska125, J. Nadal11, K. Nagai159, K. Nagano66, Y. Nagasaka60, A.M. Nairz29, K. Nakamura154, I. Nakano110, H. Nakatsuka67, G. Nanava20, A. Napier160, M. Nash77,q, N.R. Nation21, T. Nattermann20, T. Naumann41, G. Navarro161, S.K. Nderitu20, H.A. Neal87, E. Nebot80, P. Nechaeva94, A. Negri119a,119b, G. Negri29, A. Nelson64, T.K. Nelson143, S. Nemecek125, P. Nemethy108, A.A. Nepomuceno23a, M. Nessi29, M.S. Neubauer164, A. Neusiedl81, R.M. Neves108, P. Nevski24, F.M. Newcomer120, R.B. Nickerson118, R. Nicolaidou136, L. Nicolas139, G. Nicoletti47, B. Nicquevert29, F. Niedercorn115, J. Nielsen137, A. Nikiforov15, K. Nikolaev65, I. Nikolic-Audit78, K. Nikolopoulos8, H. Nilsen48, P. Nilsson7, A. Nisati132a, T. Nishiyama67, R. Nisius99, L. Nodulman5, M. Nomachi116, I. Nomidis153, M. Nordberg29, B. Nordkvist145a,145b, D. Notz41, J. Novakova126, M. Nozaki66, M. Nožiˇcka41, I.M. Nugent158a, A.-E. Nuncio-Quiroz20, G. Nunes Hanninger20, T. Nunnemann98, E. Nurse77, D.C. O’Neil142, V. O’Shea53, F.G. Oakham28,b, H. Oberlack99, A. Ochi67, S. Oda154, S. Odaka66, J. Odier83, H. Ogren61, A. Oh82, S.H. Oh44, C.C. Ohm145a,145b, T. Ohshima101, H. Ohshita140, T. Ohsugi59, S. Okada67, H. Okawa162, Y. Okumura101, T. Okuyama154, A.G. Olchevski65, M. Oliveira124a, D. Oliveira Damazio24, J. Oliver57, E. Oliver Garcia166, D. Olivito120, A. Olszewski38, J. Olszowska38, C. Omachi67,r, A. Onofre124a, P.U.E. Onyisi30, C.J. Oram158a, M.J. Oreglia30, Y. Oren152, D. Orestano134a,134b, I. Orlov107, C. Oropeza Barrera53, R.S. Orr157, E.O. Ortega130, B. Osculati50a,50b, R. Ospanov120, C. Osuna11, J.P. Ottersbach105, F. Ould-Saada117, A. Ouraou136, Q. Ouyang32a, M. Owen82, S. Owen139, A. Oyarzun31b, V.E. Ozcan77, K. Ozone66, N. Ozturk7, A. Pacheco Pages11, C. Padilla Aranda11, E. Paganis139, C. Pahl63, F. Paige24, K. Pajchel117, S. Palestini29, D. Pallin33, A. Palma124a, J.D. Palmer17, Y.B. Pan171, E. Panagiotopoulou9, B. Panes31a, N. Panikashvili87, S. Panitkin24, D. Pantea25a, M. Panuskova125, V. Paolone123, Th.D. Papadopoulou9, S.J. Park54, W. Park24,s, M.A. Parker27, S.I. Parker14, F. Parodi50a,50b, J.A. Parsons34, U. Parzefall48, E. Pasqualucci132a, A. Passeri134a, F. Pastore134a,134b, Fr. Pastore29, G. Pásztor49,t, S. Pataraia99, J.R. Pater82, S. Patricelli102a,102b, A. Patwa24, T. Pauly29, L.S. Peak149, M. Pecsy144a, M.I. Pedraza Morales171, S.V. Peleganchuk107, H. Peng171, A. Penson34, J. Penwell61, M. Perantoni23a, K. Perez34,i, 73, S. Mättig41, P.J. Magalhaes Martins124a, E. Magradze51, Y. Mahalalel152, K. Mahboubi48, Machado Miguens124a, R. Mackeprang35, R.J. Madaras14, W.F. Mader43, R. Maenner58c, T. Ma Commissioning of the ATLAS Muon Spectrometer with cosmic rays Lin150, J.T. Linnemann88, E. Lipeles120, L. Lipinsky125, A. Lipniacka13, T.M. Liss164, D. Lissauer24, A. Lister49, A.M. Litke137, C. Liu28, D. Liu150,n, H. Liu J.B. Liu87, M. Liu32b, T. Liu39, Y. Liu32b, M. Livan119a,119b, A. Lleres55, S.L. Lloyd75, E. Lobodzinska41, P. Loch6, W.S. Lockman137, S. Lockwitz174, T. Loddenkoetter20, F.K. Loebinger82, A. Loginov174, C.W. Loh167, T. Lohse15, K. Lohwasser48, M. Lokajicek125, R.E. Long71, L. Lopes124a, D. Lopez Mateos34,i, M. Losada161, P. Loscutoff14, X. Lou40, A. Lounis115, K.F. Loureiro109, L. Lovas144a, J. Love21, P.A. Love71, A.J. Lowe61, F. Lu32a, H.J. Lubatti1 C. Luci132a,132b, A. Lucotte55, A. Ludwig43, D. Ludwig41, I. Ludwig48, F. Luehring61, L. Luisa163a,163c, D. Lumb48, zschmar73, N. Krieger54, P. Krieger157, K. Kroeninger Eur. Phys. J. C (2010) 70: 875–916 879 J. Machado Miguens124a, R. Mackeprang35, R.J. Madaras14, W.F. Mader43, R. Maenner58c, T. Maeno24, P. Mättig173, S. Mättig41, P.J. Magalhaes Martins124a, E. Magradze51, Y. Mahalalel152, K. Mahboubi48, A. Mahmood1, C. Maiani132a,132b, C. Maidantchik23a, A. Maio124a, S. Majewski24, Y. Makida66, M. Makouski128, N. Makovec115, Pa. Malecki38, P. Malecki38, V.P. Maleev121, F. Malek55, U. Mallik63, D. Malon5, S. Maltezos9, V. Malyshev107, S. Malyukov65, M. Mambelli30, R. Mameghani98, J. Mamuzic41, L. Mandelli89a, I. Mandi´c74, R. Mandrysch15, J. Maneira124a, P.S. Mangeard88, I.D. Manjavidze65, P.M. Manning137, A. Manousakis-Katsikakis8, B. Mansoulie136, A. Mapelli29, L. Mapelli29, L. March80, J.F. Marchand4, F. Marchese133a,133b, G. Marchiori78, M. Marcisovsky125, C.P. Marino61, F. Marroquim23a, Z. Marshall34,i, S. Marti-Garcia166, A.J. Martin75, A.J. Martin174, B. Martin29, B. Martin88, F.F. Martin120, J.P. Martin93, T.A. Martin17, B. Martin dit Latour49, M. Martinez11, V. Martinez Outschoorn57, A. Martini47, A.C. Martyniuk82, F. Marzano132a, A. Marzin136, L. Masetti20, T. Mashimo154, R. Mashinistov96, J. Masik82, A.L. Maslennikov107, I. Massa19a,19b, N. Massol4, A. Mastroberardino36a,36b, T. Masubuchi154, P. Matricon115, H. Matsunaga154, T. Matsushita67, C. Mattravers118,o, S.J. Maxfield73, A. Mayne139, R. Mazini150, M. Mazur48, M. Mazzanti89a, J. Mc Donald85, S.P. Mc Kee87, A. McCarn164, R.L. McCarthy147, N.A. McCubbin129, K.W. McFarlane56, H. McGlone53, G. Mchedlidze51, S.J. McMahon129, R.A. McPherson168,e, A. Meade84, J. Mechnich105, M. Mechtel173, M. Medinnis41, R. Meera-Lebbai111, T.M. Meguro116, S. Mehlhase41, A. Mehta73, K. Meier58a, B. Meirose48, C. Melachrinos30, B.R. Mellado Garcia171, L. Mendoza Navas161, Z. Meng150,p, S. Menke99, E. Meoni11, P. Mermod118, L. Merola102a,102b, C. Meroni89a, F.S. Merritt30, A.M. Messina29, J. Metcalfe103, A.S. Mete64, J.-P. Meyer136, J. Meyer172, J. Meyer54, T.C. Meyer29, W.T. Meyer64, J. Miao32d, S. Michal29, L. Micu25a, R.P. Middleton129, S. Migas73, L. Mijovi´c74, G. Mikenberg170, M. Mikestikova125, M. Mikuž74, D.W. Miller143, W.J. Mills167, C.M. Mills57, A. Milov170, D.A. Commissioning of the ATLAS Muon Spectrometer with cosmic rays Milstead145a,145b, D. Milstein170, A.A. Minaenko128, M. Miñano166, I.A. Minashvili65, A.I. Mincer108, B. Mindur37, M. Mineev65, Y. Ming130, L.M. Mir11, G. Mirabelli132a, S. Misawa24, S. Miscetti47, A. Misiejuk76, J. Mitrevski137, V.A. Mitsou166, P.S. Miyagawa82, J.U. Mjörnmark79, D. Mladenov22, T. Moa145a,145b, S. Moed57, V. Moeller27, K. Mönig41, N. Möser20, W. Mohr48, S. Mohrdieck-Möck99, R. Moles-Valls166, J. Molina-Perez29, J. Monk77, E. Monnier83, S. Montesano89a,89b, F. Monticelli70, R.W. Moore2, C. Mora Herrera49, A. Moraes53, A. Morais124a, J. Morel54, G. Morello36a,36b, D. Moreno161, M. Moreno Llácer166, P. Morettini50a, M. Morii57, A.K. Morley86, G. Mornacchi29, S.V. Morozov96, J.D. Morris75, H.G. Moser99, M. Mosidze51, J. Moss109, R. Mount143, E. Mountricha136, S.V. Mouraviev94, E.J.W. Moyse84, M. Mudrinic12b, F. Mueller58a, J. Mueller123, K. Mueller20, T.A. Müller98, D. Muenstermann42, A. Muir167, Y. Munwes152, R. Murillo Garcia162, W.J. Murray129, I. Mussche105, E. Musto102a,102b, A.G. Myagkov128, M. Myska125, J. Nadal11, K. Nagai159, K. Nagano66, Y. Nagasaka60, A.M. Nairz29, K. Nakamura154, I. Nakano110, H. Nakatsuka67, G. Nanava20, A. Napier160, M. Nash77,q, N.R. Nation21, T. Nattermann20, T. Naumann41, G. Navarro161, S.K. Nderitu20, H.A. Neal87, E. Nebot80, P. Nechaeva94, A. Negri119a,119b, G. Negri29, A. Nelson64, T.K. Nelson143, S. Nemecek125, P. Nemethy108, A.A. Nepomuceno23a, M. Nessi29, M.S. Neubauer164, A. Neusiedl81, R.M. Neves108, P. Nevski24, F.M. Newcomer120, R.B. Nickerson118, R. Nicolaidou136, L. Nicolas139, G. Nicoletti47, B. Nicquevert29, F. Niedercorn115, J. Nielsen137, A. Nikiforov15, K. Nikolaev65, I. Nikolic-Audit78, K. Nikolopoulos8, H. Nilsen48, P. Nilsson7, A. Nisati132a, T. Nishiyama67, R. Nisius99, L. Nodulman5, M. Nomachi116, I. Nomidis153, M. Nordberg29, B. Nordkvist145a,145b, D. Notz41, J. Novakova126, M. Nozaki66, M. Nožiˇcka41, I.M. Nugent158a, A.-E. Nuncio-Quiroz20, G. Nunes Hanninger20, T. Nunnemann98, E. Nurse77, D.C. O’Neil142, V. O’Shea53, F.G. Oakham28,b, H. Oberlack99, A. Ochi67, S. Oda154, S. Odaka66, J. Odier83, H. Ogren61, A. Oh82, S.H. Oh44, C.C. Ohm145a,145b, T. Ohshima101, H. Ohshita140, T. Ohsugi59, S. Okada67, H. Okawa162, Y. Okumura101, T. Okuyama154, A.G. Olchevski65, M. Oliveira124a, D. Oliveira Damazio24, J. Oliver57, E. Oliver Garcia166, D. Olivito120, A. Olszewski38, J. Olszowska38, C. Omachi67,r, A. Onofre124a, P.U.E. Onyisi30, C.J. Oram158a, M.J. Oreglia30, Y. Oren152, D. Orestano134a,134b, I. Orlov107, C. Oropeza Barrera53, R.S. Orr157, E.O. Ortega130, B. Osculati50a,50b, R. Ospanov120, C. Osuna11, J.P. Ottersbach105, F. Ould-Saada117, A. Ouraou136, Q. Ouyang32a, M. Owen82, S. Owen139, A. Oyarzun31b, V.E. Ozcan77, K. Ozone66, N. Ozturk7, A. Pacheco Pages11, C. Padilla Aranda11, E. Paganis139, C. Pahl63, F. Paige24, K. Pajchel117, S. Palestini29, D. Pallin33, A. Palma124a, J.D. Palmer17, Y.B. Pan171, E. Panagiotopoulou9, B. Panes31a, N. Panikashvili87, S. Panitkin24, D. 880 Eur. Phys. J. C (2010) 70: 875–9 E. Perez Codina11, M.T. Pérez García-Estañ166, V. Perez Reale34, L. Perini89a,89b, H. Pernegger29, R. Perrino72a, S. Persembe3a, P. Perus115, V.D. Peshekhonov65, B.A. Petersen29, T.C. Petersen35, E. Petit83, C. Petridou153, E. Petrolo132a, F. Petrucci134a,134b, D. Petschull41, M. Petteni142, R. Pezoa31b, A. Phan86, A.W. Phillips27, G. Piacquadio29, M. Piccinini19a,19b, R. Piegaia26, J.E. Pilcher30, A.D. Pilkington82, J. Pina124a, M. Pinamonti163a,16 J.L. Pinfold2, B. Pinto124a, C. Pizio89a,89b, R. Placakyte41, M. Plamondon168, M.-A. Pleier24, A. Poblaguev174, S. Poddar58a, F. Podlyski33, P. Poffenberger168, L. Poggioli115, M. Pohl49, F. Polci55, G. Polesello119a, A. Policicchio138, A. Polini19a, J. Poll75, V. Polychronakos24, D. Pomeroy22, K. Pommès29, P. Ponsot136, L. Pontecorvo132a, B.G. Pope88, G.A. Popeneciu25a, D.S. Popovic12a, A. Poppleton29, J. Popule125, X. Portell Bueso4 R. Porter162, G.E. Pospelov99, S. Pospisil127, M. Potekhin24, I.N. Potrap99, C.J. Potter148, C.T. Potter85, K.P. Potter G. Poulard29, J. Poveda171, R. Prabhu20, P. Pralavorio83, S. Prasad57, R. Pravahan7, L. Pribyl29, D. Price61, L.E. Price5, P.M. Prichard73, D. Prieur123, M. Primavera72a, K. Prokofiev29, F. Prokoshin31b, S. Protopopescu24, J. Proudfoot5, X. Prudent43, H. Przysiezniak4, S. Psoroulas20, E. Ptacek114, C. Puigdengoles11, J. Purdham87, M. Purohit24,s, P. Puzo115, Y. Pylypchenko117, M. Qi32c, J. Qian87, W. Qian129, Z. Qin41, A. Quadt54, D.R. Quarrie W.B. Quayle171, F. Quinonez31a, M. Raas104, V. Radeka24, V. Radescu58b, B. Radics20, T. Rador18a, F. Ragusa89a,89b G. Rahal179, A.M. Rahimi109, S. Rajagopalan24, M. Rammensee48, M. Rammes141, F. Rauscher98, E. Rauter99, M. Raymond29, A.L. Read117, D.M. Rebuzzi119a,119b, A. Redelbach172, G. Redlinger24, R. Reece120, K. Reeves40, E. Reinherz-Aronis152, A. Reinsch114, I. Reisinger42, D. Reljic12a, C. Rembser29, Z.L. Ren150, P. Renkel39, S. Rescia24, M. Rescigno132a, S. Resconi89a, B. Resende136, P. Reznicek126, R. Rezvani157, A. Richards77, R.A. Richards88, R. Richter99, E. Richter-Was38,u, M. Ridel78, M. Rijpstra105, M. Rijssenbeek147, A. Rimoldi119a,119b, L. Rinaldi19a, R.R. Rios39, I. Riu11, F. Rizatdinova112, E. Rizvi75, D.A. Roa Romero161, S.H. Robertson85,e, A. Robichaud-Veronneau49, D. Robinson27, J.E.M. Robinson77, M. Robinson114, A. Robson53, J.G. Rocha de Lima106a, C. Roda122a,122b, D. Roda Dos Santos29, D. Rodriguez161, Y. Rodriguez Garcia15, S. Roe29 O. Røhne117, V. Rojo1, S. Rolli160, A. Romaniouk96, V.M. Romanov65, G. Romeo26, D. Romero Maltrana31a, L. Roos78, E. Ros166, S. Rosati138, G.A. Rosenbaum157, L. Rosselet49, V. Rossetti11, L.P. Rossi50a, M. Rotaru25a, J. Rothberg138, D. Rousseau115, C.R. Royon136, A. Rozanov83, Y. Rozen151, X. Ruan115, B. Ruckert98, N. Ruckstuhl105, V.I. Rud97, G. Rudolph62, F. Rühr58a, F. Ruggieri134a, A. Ruiz-Martinez64, L. Rumyantsev65, Z. Rurikova48, N.A. Rusakovich65, J.P. Rutherfoord6, C. Ruwiedel20, P. Ruzicka125, Y.F. Ryabov121, P. Ryan88, G. Rybkin115, S. Rzaeva10, A.F. Saavedra149, H.F.-W. Sadrozinski137, R. Sadykov65, H. Sakamoto154, G. Salamanna105, A. Salamon133a, M.S. Saleem111, D. Salihagic99, A. Salnikov143, J. Salt166, B.M. Salvachua Ferrando5, D. Salvatore36a,36b, F. Salvatore148, A. Salvucci47, A. Salzburger29, D. Sampsonidis153, B.H. Samset117, H. Sandaker13, H.G. Sander81, M.P. Sanders98, M. Sandhoff173, P. Sandhu157, R. Sandstroem105, S. Sandvoss173, D.P.C. Sankey129, B. Sanny173, A. Sansoni47, C. Santamarina Rios85, C. Santoni33, R. Santonico133a,133b, J.G. Saraiva124a, T. Sarangi171, E. Sarkisyan-Grinbaum7, F. Sarri122a,122b, O. Sasaki66, N. Sasao68, I. Satsounkevitch90, G. Sauvage4, P. Savard157,b, A.Y. Savine6, V. Savinov123, L. Sawyer24,f, D.H. Saxon53, L.P. Says33, C. Sbarra19a,19b, A. Sbrizzi19a,19b, D.A. Scannicchio29, J. Schaarschmidt43, P. Schacht99, U. Schäfer81, S. Schaetzel58b, A.C. Schaffer115, D. Schaile98, R.D. Schamberger147, A.G. Schamov107, V.A. Schegelsky121, D. Scheirich87, M. Schernau162, M.I. Scherzer14, C. Schiavi50a,50b, J. Schieck99, M. Schioppa36a,36b, S. Schlenker29, K. Schmieden20, C. Schmitt81, M. Schmitz20, M. Schott29, D. Schouten142, J. Schovancova125, M. Schram85, A. Schreiner63, C. Schroeder81, N. Schroer58c, M. Schroers173, J. Schultes173, H.-C. Schultz-Coulon58a, J.W. Schumacher43, M. Schumacher48, B.A. Schumm137, Ph. Schune136, C. Schwanenberger82, A. Schwartzman14 Ph. Schwemling78, R. Schwienhorst88, R. Schwierz43, J. Schwindling136, W.G. Scott129, J. Searcy114, E. Sedykh121, E. Segura11, S.C. Seidel103, A. Seiden137, F. Seifert43, J.M. Seixas23a, G. Sekhniaidze102a, D.M. Seliverstov121, B. Sellden145a, N. Semprini-Cesari19a,19b, C. Serfon98, L. Serin115, R. Seuster99, H. Severini111, M.E. Sevior86, A. Sfyrla164, E. Shabalina54, M. Shamim114, L.Y. Shan32a, J.T. Shank21, Q.T. Shao86, M. Shapiro14, P.B. Shatalov9 K. Shaw139, D. Sherman29, P. Sherwood77, A. Shibata108, M. Shimojima100, T. Shin56, A. Shmeleva94, M.J. Shochet30, M.A. Shupe6, P. Sicho125, A. Sidoti15, F. Siegert77, J. Siegrist14, Dj. Sijacki12a, O. Silbert170, J. Silva124a, Y. Silver152, D. Silverstein143, S.B. Silverstein145a, V. Simak127, Lj. Simic12a, S. Simion115, B. Simmons7 M. Simonyan35, P. Sinervo157, N.B. Sinev114, V. Sipica141, G. Siragusa81, A.N. Sisakyan65, S.Yu. Sivoklokov97, J. Sjoelin145a,145b, T.B. Sjursen13, K. Skovpen107, P. Skubic111, M. Slater17, T. Slavicek127, K. Sliwa160, J. Sloper29, T. Sluka125, V. Smakhtin170, S.Yu. Smirnov96, Y. Smirnov24, L.N. Smirnova97, O. Smirnova79, B.C. Smith57, D. Smith143, K.M. Smith53, M. Smizanska71, K. Smolek127, A.A. Snesarev94, S.W. Snow82, J. Snow111, J. Snuverink105, S. Snyder24, M. Soares124a, R. Sobie168,e, J. Sodomka127, A. Soffer152, C.A. Solans166, M. Solar127 Commissioning of the ATLAS Muon Spectrometer with cosmic rays Rosselet49, V. Rossetti11, L.P. Rossi50a, M. Rotaru25a, J. Rothberg138, D. Rousseau115, C.R. Royon136, A. Rozanov83, Y. Rozen151, X. Ruan115, B. Ruckert98, N. Ruckstuhl105, V.I. Rud97, G. Rudolph62, F. Rühr58a, F. Ruggieri134a, A. Ruiz-Martinez64, L. Rumyantsev65, Z. Rurikova48, N.A. Rusakovich65, J.P. Rutherfoord6, C. Ruwiedel20, P. Ruzicka125, Y.F. Ryabov121, P. Ryan88, G. Rybkin115, S. Rzaeva10, A.F. Saavedra149, H.F.-W. Sadrozinski137, R. Sadykov65, H. Sakamoto154, G. Salamanna105, A. Salamon133a, M.S. Saleem111, D. Salihagic99, A. Salnikov143, J. Salt166, B.M. Salvachua Ferrando5, D. Salvatore36a,36b, F. Salvatore148, A. Salvucci47, A. Salzburger29, D. Sampsonidis153, B.H. Samset117, H. Sandaker13, H.G. Sander81, M.P. Sanders98, M. Sandhoff173, P. Sandhu157, R. Sandstroem105, S. Sandvoss173, D.P.C. Sankey129, B. Sanny173, A. Sansoni47, C. Santamarina Rios85, C. Santoni33, R. Santonico133a,133b, J.G. Saraiva124a, T. Sarangi171, E. Sarkisyan-Grinbaum7, F. Sarri122a,122b, O. Sasaki66, N. Sasao68, I. Satsounkevitch90, G. Sauvage4, P. Savard157,b, A.Y. Savine6, V. Savinov123, L. Sawyer24,f, D.H. Saxon53, L.P. Says33, C. Sbarra19a,19b, A. Sbrizzi19a,19b, D.A. Scannicchio29, J. Schaarschmidt43, P. Schacht99, U. Schäfer81, S. Schaetzel58b, A.C. Schaffer115, D. Schaile98, R.D. Schamberger147, A.G. Schamov107, V.A. Schegelsky121, D. Scheirich87, M. Schernau162, M.I. Scherzer14, C. Schiavi50a,50b, J. Schieck99, M. Schioppa36a,36b, S. Schlenker29 K. Schmieden20, C. Schmitt81, M. Schmitz20, M. Schott29, D. Schouten142, J. Schovancova125, M. Schram85, A. Schreiner63, C. Schroeder81, N. Schroer58c, M. Schroers173, J. Schultes173, H.-C. Schultz-Coulon58a, J.W. Schumacher43, M. Schumacher48, B.A. Schumm137, Ph. Schune136, C. Schwanenberger82, A. Schwartzman14 Ph. Schwemling78, R. Schwienhorst88, R. Schwierz43, J. Schwindling136, W.G. Scott129, J. Searcy114, E. Sedykh121 E. Segura11, S.C. Seidel103, A. Seiden137, F. Seifert43, J.M. Seixas23a, G. Sekhniaidze102a, D.M. Seliverstov121, B. Sellden145a, N. Semprini-Cesari19a,19b, C. Serfon98, L. Serin115, R. Seuster99, H. Severini111, M.E. Sevior86, A. Sfyrla164, E. Shabalina54, M. Shamim114, L.Y. Shan32a, J.T. Shank21, Q.T. Shao86, M. Shapiro14, P.B. Shatalov9 K. Shaw139, D. Sherman29, P. Sherwood77, A. Shibata108, M. Shimojima100, T. Shin56, A. Shmeleva94, M.J. Shochet30, M.A. Shupe6, P. Sicho125, A. Sidoti15, F. Siegert77, J. Siegrist14, Dj. Sijacki12a, O. Silbert170, J. Silva124a, Y. Silver152, D. Silverstein143, S.B. Silverstein145a, V. Simak127, Lj. Simic12a, S. Simion115, B. Simmons M. Simonyan35, P. Sinervo157, N.B. Sinev114, V. Sipica141, G. Siragusa81, A.N. Sisakyan65, S.Yu. Sivoklokov97, J. Sjoelin145a,145b, T.B. Sjursen13, K. Skovpen107, P. Skubic111, M. Slater17, T. Slavicek127, K. Sliwa160, J. Sloper29, T. Sluka125, V. Smakhtin170, S.Yu. Smirnov96, Y. Smirnov24, L.N. Smirnova97, O. Smirnova79, B.C. Smith57, D. Smith143, K.M. Smith53, M. Smizanska71, K. Smolek127, A.A. Snesarev94, S.W. Snow82, J. Snow111, J. Snuverink105, S. Snyder24, M. Soares124a, R. Sobie168,e, J. Sodomka127, A. Soffer152, C.A. Solans166, M. Solar127 E. Commissioning of the ATLAS Muon Spectrometer with cosmic rays Pantea25a, M. Panuskova125, V. Paolone123, Th.D. Papadopoulou9, S.J. Park54, W. Park24,s, M.A. Parker27, S.I. Parker14, F. Parodi50a,50b, J A Parsons34 U Parzefall48 E Pasqualucci132a A Passeri134a F Pastore134a,134b Fr Pastore29 G Pásztor49,t M.I. Pedraza Morales171, S.V. Peleganchuk107, H. Peng171, A. Penson34, J. Penwell61, M. Perantoni23a, K. Perez34,i, 880 Eur. Phys. J. C (2010) 70: 875–916 E. Perez Codina11, M.T. Pérez García-Estañ166, V. Perez Reale34, L. Perini89a,89b, H. Pernegger29, R. Perrino72a, S. Persembe3a, P. Perus115, V.D. Peshekhonov65, B.A. Petersen29, T.C. Petersen35, E. Petit83, C. Petridou153, E. Petrolo132a, F. Petrucci134a,134b, D. Petschull41, M. Petteni142, R. Pezoa31b, A. Phan86, A.W. Phillips27, G. Piacquadio29, M. Piccinini19a,19b, R. Piegaia26, J.E. Pilcher30, A.D. Pilkington82, J. Pina124a, M. Pinamonti163a,16 J.L. Pinfold2, B. Pinto124a, C. Pizio89a,89b, R. Placakyte41, M. Plamondon168, M.-A. Pleier24, A. Poblaguev174, S. Poddar58a, F. Podlyski33, P. Poffenberger168, L. Poggioli115, M. Pohl49, F. Polci55, G. Polesello119a, A. Policicchio138, A. Polini19a, J. Poll75, V. Polychronakos24, D. Pomeroy22, K. Pommès29, P. Ponsot136, L. Pontecorvo132a, B.G. Pope88, G.A. Popeneciu25a, D.S. Popovic12a, A. Poppleton29, J. Popule125, X. Portell Bueso R. Porter162, G.E. Pospelov99, S. Pospisil127, M. Potekhin24, I.N. Potrap99, C.J. Potter148, C.T. Potter85, K.P. Potter G. Poulard29, J. Poveda171, R. Prabhu20, P. Pralavorio83, S. Prasad57, R. Pravahan7, L. Pribyl29, D. Price61, L.E. Price5, P.M. Prichard73, D. Prieur123, M. Primavera72a, K. Prokofiev29, F. Prokoshin31b, S. Protopopescu24, J. Proudfoot5, X. Prudent43, H. Przysiezniak4, S. Psoroulas20, E. Ptacek114, C. Puigdengoles11, J. Purdham87, M. Purohit24,s, P. Puzo115, Y. Pylypchenko117, M. Qi32c, J. Qian87, W. Qian129, Z. Qin41, A. Quadt54, D.R. Quarrie W.B. Quayle171, F. Quinonez31a, M. Raas104, V. Radeka24, V. Radescu58b, B. Radics20, T. Rador18a, F. Ragusa89a,89b G. Rahal179, A.M. Rahimi109, S. Rajagopalan24, M. Rammensee48, M. Rammes141, F. Rauscher98, E. Rauter99, M. Raymond29, A.L. Read117, D.M. Rebuzzi119a,119b, A. Redelbach172, G. Redlinger24, R. Reece120, K. Reeves40, E. Reinherz-Aronis152, A. Reinsch114, I. Reisinger42, D. Reljic12a, C. Rembser29, Z.L. Ren150, P. Renkel39, S. Rescia24, M. Rescigno132a, S. Resconi89a, B. Resende136, P. Reznicek126, R. Rezvani157, A. Richards77, R.A. Richards88, R. Richter99, E. Richter-Was38,u, M. Ridel78, M. Rijpstra105, M. Rijssenbeek147, A. Rimoldi119a,119b, L. Rinaldi19a, R.R. Rios39, I. Riu11, F. Rizatdinova112, E. Rizvi75, D.A. Roa Romero161, S.H. Robertson85,e, A. Robichaud-Veronneau49, D. Robinson27, J.E.M. Robinson77, M. Robinson114, A. Robson53, J.G. Rocha de Lima106a, C. Roda122a,122b, D. Roda Dos Santos29, D. Rodriguez161, Y. Rodriguez Garcia15, S. Roe29 O. Røhne117, V. Rojo1, S. Rolli160, A. Romaniouk96, V.M. Romanov65, G. Romeo26, D. Romero Maltrana31a, L. Roos78, E. Ros166, S. Rosati138, G.A. Rosenbaum157, L. Commissioning of the ATLAS Muon Spectrometer with cosmic rays Perez Codina11, M.T. Pérez García-Estañ166, V. Perez Reale34, L. Perini89a,89b, H. Pernegger29, R. Perrino72a, S. Persembe3a, P. Perus115, V.D. Peshekhonov65, B.A. Petersen29, T.C. Petersen35, E. Petit83, C. Petridou153, , , , , , cci134a,134b, D. Petschull41, M. Petteni142, R. Pezoa31b, A. Phan86, A.W. Phillips27, Eur. Phys. J. C (2010) 70: 875–916 881 Eur. Phys. J. C (2010) 70: 875–916 881 J. Solc127, E. Solfaroli Camillocci132a,132b, A.A. Solodkov128, O.V. Solovyanov128, R. Soluk2, J. Sondericker24, V. Sopko127, B. Sopko127, M. Sosebee7, A. Soukharev107, S. Spagnolo72a,72b, F. Spanò34, E. Spencer137, R. Spighi19a, G. Spigo29, F. Spila132a,132b, R. Spiwoks29, M. Spousta126, T. Spreitzer142, B. Spurlock7, R.D. St. Denis53, T. Stahl141, J. Stahlman120, R. Stamen58a, S.N. Stancu162, E. Stanecka29, R.W. Stanek5, C. Stanescu134a, S. Stapnes117, E.A. Starchenko128, J. Stark55, P. Staroba125, P. Starovoitov91, J. Stastny125, P. Stavina144a, G. Steele53, P. Steinbach43, P. Steinberg24, I. Stekl127, B. Stelzer142, H.J. Stelzer41, O. Stelzer-Chilton158a, H. Stenzel52, K. Stevenson75, G.A. Stewart53, M.C. Stockton29, K. Stoerig48, G. Stoicea25a, S. Stonjek99, P. Strachota126, A.R. Stradling7, A. Straessner43, J. Strandberg87, S. Strandberg14, A. Strandlie117, M. Strauss111, P. Strizenec144b, R. Ströhmer172, D.M. Strom114, R. Stroynowski39, J. Strube129, B. Stugu13, D.A. Soh150,v, D. Su143, Y. Sugaya116, T. Sugimoto101, C. Suhr106a, M. Suk126, V.V. Sulin94, S. Sultansoy3d, T. Sumida29, X.H. Sun32d, J.E. Sundermann48, K. Suruliz163a,163b, S. Sushkov11, G. Susinno36a,36b, M.R. Sutton139, T. Suzuki154, Y. Suzuki66, I. Sykora144a, T. Sykora126, T. Szymocha38, J. Sánchez166, D. Ta20, K. Tackmann29, A. Taffard162, R. Tafirout158a, A. Taga117, Y. Takahashi101, H. Takai24, R. Takashima69, H. Takeda67, T. Takeshita140, M. Talby83, A. Talyshev107, M.C. Tamsett76, J. Tanaka154, R. Tanaka115, S. Tanaka131, S. Tanaka66, S. Tapprogge81, D. Tardif157, S. Tarem151, F. Tarrade24, G.F. Tartarelli89a, P. Tas126, M. Tasevsky125, E. Tassi36a,36b, M. Tatarkhanov14, C. Taylor77, F.E. Taylor92, G.N. Taylor86, R.P. Taylor168, W. Taylor158b, P. Teixeira-Dias76, H. Ten Kate29, P.K. Teng150, Y.D. Tennenbaum-Katan151, S. Terada66, K. Terashi154, J. Terron80, M. Terwort41,k, M. Testa47, R.J. Teuscher157,e, M. Thioye174, S. Thoma48, J.P. Thomas17, E.N. Thompson84, P.D. Thompson17, P.D. Thompson157, R.J. Thompson82, A.S. Thompson53, E. Thomson120, R.P. Thun87, T. Tic125, V.O. Tikhomirov94, Y.A. Tikhonov107, P. Tipton174, F.J. Tique Aires Viegas29, S. Tisserant83, B. Toczek37, T. Todorov4, S. Todorova-Nova160, B. Toggerson162, J. Tojo66, S. Tokár144a, K. Tokushuku66, K. Tollefson88, L. Tomasek125, M. Tomasek125, M. Tomoto101, L. Tompkins14, K. Toms103, A. Tonoyan13, C. Topfel16, N.D. Topilin65, E. Torrence114, E. Torró Pastor166, J. Toth83,t, F. Touchard83, D.R. Tovey139, T. Trefzger172, L. Tremblet29, A. Tricoli29, I.M. Trigger158a, S. Trincaz-Duvoid78, T.N. Commissioning of the ATLAS Muon Spectrometer with cosmic rays Trinh78, M.F. Tripiana70, N. Triplett64, W. Trischuk157, A. Trivedi24,s, B. Trocmé55, C. Troncon89a, A. Trzupek38, C. Tsarouchas9, J.C.-L. Tseng118, M. Tsiakiris105, P.V. Tsiareshka90, D. Tsionou139, G. Tsipolitis9, V. Tsiskaridze51, E.G. Tskhadadze51, I.I. Tsukerman95, V. Tsulaia123, J.-W. Tsung20, S. Tsuno66, D. Tsybychev147, J.M. Tuggle30, D. Turecek127, I. Turk Cakir3e, E. Turlay105, P.M. Tuts34, M.S. Twomey138, M. Tylmad145a,145b, M. Tyndel129, K. Uchida116, I. Ueda154, M. Ugland13, M. Uhlenbrock20, M. Uhrmacher54, F. Ukegawa159, G. Unal29, A. Undrus24, G. Unel162, Y. Unno66, D. Urbaniec34, E. Urkovsky152, P. Urquijo49,w, P. Urrejola31a, G. Usai7, M. Uslenghi119a,119b, L. Vacavant83, V. Vacek127, B. Vachon85, S. Vahsen14, P. Valente132a, S. Valentinetti19a,19b, S. Valkar126, E. Valladolid Gallego166, S. Vallecorsa151, J.A. Valls Ferrer166, R. Van Berg120, H. van der Graaf105, E. van der Kraaij105, E. van der Poel105, D. van der Ster29, N. van Eldik84, P. van Gemmeren5, Z. van Kesteren105, I. van Vulpen105, W. Vandelli29, A. Vaniachine5, P. Vankov73, F. Vannucci78, R. Vari132a, E.W. Varnes6, D. Varouchas14, A. Vartapetian7, K.E. Varvell149, L. Vasilyeva94, V.I. Vassilakopoulos56, F. Vazeille33, C. Vellidis8, F. Veloso124a, S. Veneziano132a, A. Ventura72a,72b, D. Ventura138, M. Venturi48, N. Venturi16, V. Vercesi119a, M. Verducci172, W. Verkerke105, J.C. Vermeulen105, M.C. Vetterli142,b, I. Vichou164, T. Vickey118, G.H.A. Viehhauser118, M. Villa19a,19b, E.G. Villani129, M. Villaplana Perez166, E. Vilucchi47, M.G. Vincter28, E. Vinek29, V.B. Vinogradov65, S. Viret33, J. Virzi14, A. Vitale19a,19b, O. Vitells170, I. Vivarelli48, F. Vives Vaque11, S. Vlachos9, M. Vlasak127, N. Vlasov20, A. Vogel20, P. Vokac127, M. Volpi11, H. von der Schmitt99, J. von Loeben99, H. von Radziewski48, E. von Toerne20, V. Vorobel126, V. Vorwerk11, M. Vos166, R. Voss29, T.T. Voss173, J.H. Vossebeld73, N. Vranjes12a, M. Vranjes Milosavljevic12a, V. Vrba125, M. Vreeswijk105, T. Vu Anh81, D. Vudragovic12a, R. Vuillermet29, I. Vukotic115, P. Wagner120, J. Walbersloh42, J. Walder71, R. Walker98, W. Walkowiak141, R. Wall174, C. Wang44, H. Wang171, J. Wang55, S.M. Wang150, A. Warburton85, C.P. Ward27, M. Warsinsky48, R. Wastie118, P.M. Watkins17, A.T. Watson17, M.F. Watson17, G. Watts138, S. Watts82, A.T. Waugh149, B.M. Waugh77, M.D. Weber16, M. Weber129, M.S. Weber16, P. Weber58a, A.R. Weidberg118, J. Weingarten54, C. Weiser48, H. Wellenstein22, P.S. Wells29, M. Wen47, T. Wenaus24, S. Wendler123, T. Wengler82, S. Wenig29, N. Wermes20, M. Werner48, P. Werner29, M. Werth162, U. Werthenbach141, M. Wessels58a, K. Whalen28, A. White7, M.J. White27, S. White24, S.R. Whitehead118, D. Whiteson162, D. Whittington61, F. Wicek115, D. Wicke81, F.J. Wickens129, W. Wiedenmann171, M. Wielers129, P. Wienemann20, C. Wiglesworth73, L.A.M. Wiik48, A. Wildauer166, M.A. Wildt41,k, H.G. Wilkens29, E. J. Solc127, E. Solfaroli Camillocci132a,132b, A.A. Solodkov128, O.V. Solovyanov128, R. Soluk2, J. Sondericker24, V. Sopko127, B. Sopko127, M. Sosebee7, A. Soukharev107, S. Spagnolo72a,72b, F. Spanò34, E. Spencer137, R. Spighi19a, G. Spigo29, F. Spila132a,132b, R. Spiwoks29, M. Spousta126, T. Spreitzer142, B. Spurlock7, R.D. St. Denis53, T. Stahl141, J. Stahlman120, R. Stamen58a, S.N. Stancu162, E. Stanecka29, R.W. Stanek5, C. Stanescu134a, S. Stapnes117, E.A. Starchenko128, J. Stark55, P. Staroba125, P. Starovoitov91, J. Stastny125, P. Stavina144a, G. Steele53, P. Steinbach43, P. Steinberg24, I. Stekl127, B. Stelzer142, H.J. Stelzer41, O. Stelzer-Chilton158a, H. Stenzel52, K. Stevenson75, G.A. Stewart53, M.C. Stockton29, K. Stoerig48, G. Stoicea25a, S. Stonjek99, P. Strachota126, A.R. Stradling7, A. Straessner43, J. Strandberg87, S. Strandberg14, A. Strandlie117, M. Strauss111, P. Strizenec144b, R. Ströhmer172, D.M. Strom114, R. Stroynowski39, J. Strube129, B. Stugu13, D.A. Soh150,v, D. Su143, Y. Sugaya116, T. Sugimoto101, C. Suhr106a, M. Suk126, V.V. Sulin94, S. Sultansoy3d, T. Sumida29, X.H. Sun32d, J.E. Sundermann48, K. Suruliz163a,163b, S. Sushkov11, G. Susinno36a,36b, M.R. Sutton139, T. Suzuki154, Y. Suzuki66, I. Sykora144a, T. Sykora126, T. Szymocha38, J. Sánchez166, D. Ta20, K. Tackmann29, A. Taffard162, R. Tafirout158a, A. Taga117, Y. Takahashi101, H. Takai24, R. Takashima69, H. Takeda67, T. Takeshita140, M. Talby83, A. Talyshev107, M.C. Tamsett76, J. Tanaka154, R. Tanaka115, S. Tanaka131, S. Tanaka66, S. Tapprogge81, D. Tardif157, S. Tarem151, F. Tarrade24, G.F. Tartarelli89a, P. Tas126, M. Tasevsky125, E. Tassi36a,36b, M. Tatarkhanov14, C. Taylor77, F.E. Taylor92, G.N. Taylor86, R.P. Taylor168, W. Taylor158b, P. Teixeira-Dias76, H. Ten Kate29, P.K. Teng150, Y.D. Tennenbaum-Katan151, S. Terada66, K. Terashi154, J. Terron80, M. Terwort41,k, M. Testa47, R.J. Teuscher157,e, M. Thioye174, S. Thoma48, J.P. Thomas17, E.N. Thompson84, P.D. Thompson17, P.D. Thompson157, R.J. Thompson82, A.S. Thompson53, E. Thomson120, R.P. Thun87, T. Tic125, V.O. Tikhomirov94, Y.A. Tikhonov107, P. Tipton174, F.J. Tique Aires Viegas29, S. Tisserant83, B. Toczek37, T. Todorov4, S. Todorova-Nova160, B. Toggerson162, J. Tojo66, S. Tokár144a, K. Tokushuku66, K. Tollefson88, L. Tomasek125, M. Tomasek125, M. Tomoto101, L. Tompkins14, K. Toms103, A. Tonoyan13, C. Topfel16, N.D. Topilin65, E. Torrence114, E. Torró Pastor166, J. Toth83,t, F. Touchard83, D.R. Tovey139, T. Trefzger172, L. Tremblet29, A. Tricoli29, I.M. Trigger158a, S. Trincaz-Duvoid78, T.N. Trinh78, M.F. Tripiana70, N. Triplett64, W. Trischuk157, A. Trivedi24,s, B. Trocmé55, C. Troncon89a, A. Trzupek38, C. Tsarouchas9, J.C.-L. Tseng118, M. Tsiakiris105, P.V. Tsiareshka90, D. Tsionou139, G. Tsipolitis9, V. Tsiskaridze51, E.G. Tskhadadze51, I.I. Tsukerman95, V. Tsulaia123, J.-W. Tsung20, S. Tsuno66, D. Tsybychev147, J.M. Tuggle30, D. Turecek127, I. Turk Cakir3e, E. Turlay105, P.M. Tuts34, M.S. Twomey138, M. Tylmad145a,145b, M. Tyndel129, K. Uchida116, I. Ueda154, M. Ugland13, M. Uhlenbrock20, M. Uhrmacher54, F. Ukegawa159, G. Unal29, A. Undrus24, G. Unel162, Y. Unno66, D. Urbaniec34, E. Urkovsky152, P. Urquijo49,w, P. Urrejola31a, G. Usai7, M. Uslenghi119a,119b, L. Vacavant83, V. Vacek127, B. Vachon85, S. Vahsen14, P. Valente132a, S. Valentinetti19a,19b, S. Valkar126, E. Valladolid Gallego166, S. Vallecorsa151, J.A. Valls Ferrer166, R. Van Berg120, H. van der Graaf105, E. van der Kraaij105, E. van der Poel105, D. van der Ster29, N. van Eldik84, P. van Gemmeren5, Z. van Kesteren105, I. van Vulpen105, W. Vandelli29, A. Vaniachine5, P. Vankov73, F. Vannucci78, R. Vari132a, E.W. Varnes6, D. Varouchas14, A. Vartapetian7, K.E. Varvell149, L. Vasilyeva94, V.I. Vassilakopoulos56, F. Vazeille33, C. Vellidis8, F. Veloso124a, S. Veneziano132a, A. Ventura72a,72b, D. Ventura138, M. Venturi48, N. Venturi16, V. Vercesi119a, M. Verducci172, W. Verkerke105, J.C. Vermeulen105, M.C. Vetterli142,b, I. Vichou164, T. Vickey118, G.H.A. Viehhauser118, M. Villa19a,19b, E.G. Villani129, M. Villaplana Perez166, E. Vilucchi47, M.G. Vincter28, E. Vinek29, V.B. Vinogradov65, S. Viret33, J. Virzi14, A. Vitale19a,19b, O. Vitells170, I. Vivarelli48, F. Vives Vaque11, S. Vlachos9, M. Vlasak127, N. Vlasov20, A. Vogel20, P. Vokac127, M. Volpi11, H. von der Schmitt99, J. von Loeben99, H. von Radziewski48, E. von Toerne20, V. Vorobel126, V. Vorwerk11, M. Vos166, R. Voss29, T.T. Voss173, J.H. Vossebeld73, N. Vranjes12a, M. Vranjes Milosavljevic12a, V. Vrba125, M. Vreeswijk105, T. Vu Anh81, D. Vudragovic12a, R. Vuillermet29, I. Vukotic115, P. Wagner120, J. Walbersloh42, J. Walder71, R. Walker98, W. Walkowiak141, R. Wall174, C. Wang44, H. Wang171, J. Wang55, S.M. Wang150, A. Warburton85, C.P. Ward27, M. Warsinsky48, R. Wastie118, P.M. Watkins17, A.T. Watson17, M.F. Watson17, G. Watts138, S. Watts82, A.T. Waugh149, B.M. Waugh77, M.D. Weber16, M. Weber129, M.S. Weber16, P. Weber58a, A.R. Weidberg118, J. Weingarten54, C. Weiser48, H. Wellenstein22, P.S. Wells29, M. Wen47, T. Wenaus24, S. Wendler123, T. Wengler82, S. Wenig29, N. Wermes20, M. Werner48, P. Werner29, M. Werth162, U. Werthenbach141, M. Wessels58a, K. Whalen28, A. White7, M.J. White27, S. White24, S.R. Whitehead118, D. Whiteson162, D. Whittington61, F. Wicek115, D. Wicke81, F.J. Wickens129, W. Wiedenmann171, M. Wielers129, P. Wienemann20, C. Wiglesworth73, L.A.M. Wiik48, A. Wildauer166, M.A. Wildt41,k, H.G. Wilkens29, E. Williams34, H.H. Williams120, S. Willocq84, J.A. Wilson17, M.G. Wilson143, A. Wilson87, I. Wingerter-Seez4, F. Winklmeier29, M. Wittgen143, M.W. Wolter38, H. Wolters124a, B.K. Wosiek38, J. Wotschack29, M.J. Woudstra84, K. Wraight53, C. Wright53, D. Wright143, B. Wrona73, S.L. Wu171, X. Wu49, E. Wulf34, B.M. Wynne45, L. Xaplanteris9, S. Xella35, S. Xie48, D. Xu139, N. Xu171, M. Yamada159, A. Yamamoto66, K. Yamamoto64, S. Yamamoto154, T. Yamamura154, J. Yamaoka44, T. Yamazaki154, Y. Yamazaki67, Z. Yan21, H. Yang87, U.K. Yang82, Z. Yang145a,145b, W.-M. Yao14, Y. Yao14, Y. Yasu66, J. Ye39, S. Ye24, M. Yilmaz3c, R. Yoosoofmiya123, K. Yorita169, R. Yoshida5, C. Young143, S.P. Youssef21, D. Yu24, J. Yu7, L. Yuan78, A. Yurkewicz147, R. Zaidan63, A.M. Zaitsev128, Z. Zajacova29, V. Zambrano47, L. Zanello132a,132b, A. Zaytsev107, C. Zeitnitz173, M. Zeller174, A. Zemla38, C. Zendler20, O. Zenin128, T. Zenis144a, Z. Zenonos122a,122b, S. Zenz14, D. Zerwas115, G. Zevi della Porta57, Z. Zhan32d, H. Zhang83, J. Zhang5, Q. Zhang5, X. Zhang32d, L. Zhao108, T. Zhao138, Z. Zhao32b, A. Zhemchugov65, J. Zhong150,x, B. Zhou87, N. Zhou34, Y. Zhou150, C.G. Zhu32d, H. Zhu41, Y. Zhu171, X. Zhuang98, V. Zhuravlov99, R. Zimmermann20, S. Zimmermann20, S. Zimmermann48, M. Ziolkowski141, L. Živkovi´c34, G. Zobernig171, A. Zoccoli19a,19b, M. zur Nedden15, V. Zutshi106a ?CERN 1211 Genève 23 Switzerland ?CERN, 1211 Genève 23, Switzerland 1University at Albany, 1400 Washington Ave, Albany, NY 12222, United States of America 1University at Albany, 1400 Washington Ave, Albany, NY 12222, United States of America y y g y 2University of Alberta, Department of Physics, Centre for Particle Physics, Edmonton, AB T6G 2G7, Canada 3 ( ) y y g y rsity of Alberta, Department of Physics, Centre for Particle Physics, Edmonton, AB T6G 2G7, Canada ( ) y , p y , y , , , 3Ankara University(a), Faculty of Sciences, Department of Physics, TR 061000 Tandogan, Ankara; Dumlupinar University(b), Faculty of Arts and Sciences, Department of Physics, Kutahya; Gazi University(c), Faculty of Arts and Sciences, Department of Physics, 06500, 3Ankara University(a), Faculty of Sciences, Department of Physics, TR 061000 Tandogan, Ankara; Dumlupinar University(b), Faculty of Arts and Sciences, Department of Physics, Kutahya; Gazi University(c), Faculty of Arts and Sciences, Department of Physics, 06500, Teknikokullar, Ankara; TOBB University of Economics and Technology(d), Faculty of Arts and Sciences, Division of Physics, 06560, (e) 3Ankara University(a), Faculty of Sciences, Department of Physics, TR 061000 Tandogan, Ankara; Dumlupinar University(b), Faculty of Arts and Sciences, Department of Physics, Kutahya; Gazi University(c), Faculty of Arts and Sciences, Department of Physics, 06500, (d) y gy y Sogutozu, Ankara; Turkish Atomic Energy Authority(e), 06530, Lodumlu, Ankara, Turkey 4 Sogutozu, Ankara; Turkish Atomic Energy Authority(e), 06530, Lodum 4 4LAPP, Université de Savoie, CNRS/IN2P3, Annecy-le-Vieux, France 5 5Argonne National Laboratory, High Energy Physics Division, 9700 S. Cass Avenue, Argonne IL 60439, United Sta 6U i it f A i D t t f Ph i T AZ 85721 U it d St t f A i 5Argonne National Laboratory, High Energy Physics Division, 9700 S. Cass Avenue, Argonne I 6 Argonne National Laboratory, High Energy Physics Division, 9700 S. ?CERN, 1211 Genève 23, Switzerland 15, D-12489 Berlin, Germany 16University of Bern, Albert Einstein Center for Fundamental Physics, Laboratory for High Energy Physics, Sidlerstrasse 5, CH-3012 Bern, Switzerland 1 16University of Bern, Albert Einstein Center for Fundamental Physics, Laboratory for High Energy Physics, Sidlerstr Switzerland 17University of Birmingham, School of Physics and Astronomy, Edgbaston, Birmingham B15 2TT, United Kingdom 18 ( ) (b 18Bogazici University(a), Faculty of Sciences, Department of Physics, TR-80815 Bebek-Istanbul; Dogus University(b), Faculty of Arts and Sciences, Department of Physics, 34722, Kadikoy, Istanbul; (c)Gaziantep University, Faculty of Engineering, Department of Physics Engineering, 27310, Sehitkamil, Gaziantep, Turkey; Istanbul Technical University(d), Faculty of Arts and Sciences, Department of Physics, 34469, Maslak, Istanbul, Turkey 18Bogazici University(a), Faculty of Sciences, Department of Physics, TR-80815 Bebek-Istanbul; Dogus University(b), Faculty of Arts and Sciences, Department of Physics, 34722, Kadikoy, Istanbul; (c)Gaziantep University, Faculty of Engineering, Department of Physics Engineering, 27310, Sehitkamil, Gaziantep, Turkey; Istanbul Technical University(d), Faculty of Arts and Sciences, Department of Physics, 34469, Maslak, Istanbul, Turkey 19 ( ) (b) y 19INFN Sezione di Bologna(a); Università di Bologna, Dipartimento di Fisica(b), viale C. Berti Pichat, 6/2, IT - 40127 Bologna, Italy 19INFN Sezione di Bologna(a); Università di Bologna, Dipartimento di Fisica(b), viale C. Berti Pichat, 6/2, IT - 40127 f Bonn, Physikalisches Institut, Nussallee 12, D-53115 Bon 21Boston University, Department of Physics, 590 Commonwealth Avenue, Boston, MA 02215, United States of America 22 21Boston University, Department of Physics, 590 Commonwealth Avenue, Boston, MA 02215, United States of America 22 21Boston University, Department of Physics, 590 Commonwealth Avenue, Boston, MA 02 22 22Brandeis University, Department of Physics, MS057, 415 South Street, Waltham, MA 02454, United States of Ame 23 ( ) y p y 23Universidade Federal do Rio De Janeiro, COPPE/EE/IF (a), Caixa Postal 68528, Ilha do Fundao, BR-21945-970 Rio de Janeiro; (b)Universidade de Sao Paulo, Instituto de Fisica, R.do Matao Trav. R.187, Sao Paulo-SP, 05508-900, Brazil 24 , , , , ; (b)Universidade de Sao Paulo, Instituto de Fisica, R.do Matao Trav. R.187, Sao Paulo-SP, 05508-900, Brazil (b)Universidade de Sao Paulo, Instituto de Fisica, R.do Matao Trav. R.187, Sao Paulo-SP, 05508-900, Brazil 24Brookhaven National Laboratory, Physics Department, Bldg. 510A, Upton, NY 11973, United States of Ameri 25 ( ) 25National Institute of Physics and Nuclear Engineering(a), Bucharest-Magurele, Str. Atomistilor 407, P.O. Box MG- University Politehnica Bucharest(b), Rectorat–AN 001, 313 Splaiul Independentei, sector 6, 060042 Bucuresti; We 25National Institute of Physics and Nuclear Engineering(a), Bucharest-Magurele, Str. ?CERN, 1211 Genève 23, Switzerland Cass Avenue, Argonne IL 60439, United States of Amer 6University of Arizona, Department of Physics, Tucson, AZ 85721, United States of America g y g gy y g 6University of Arizona, Department of Physics, Tucson, AZ 85721, United States of America 7 7The University of Texas at Arlington, Department of Physics, Box 19059, Arlington, TX 76019, United States of A 8 8University of Athens, Nuclear & Particle Physics, Department of Physics, Panepistimiopouli, Zogra 9 8University of Athens, Nuclear & Particle Physics, Department of Physics, Panepistimiopouli, Zografou, GR 15771 9N ti l T h i l U i it f Ath Ph i D t t 9 I P l t h i GR 15780 Z f G 9National Technical University of Athens, Physics Department, 9-Iroon Polytechniou, GR 15780 Zografou, Greece y j y j 11Institut de Física d’Altes Energies, IFAE, Edifici Cn, Universitat Autònoma de Barcelona, ES-08193 Bellaterra (Barcelona), Spain 12University of Belgrade(a), Institute of Physics, P.O. Box 57, 11001 Belgrade; Vinca Institute of Nuclear Sciences(b), Mihajla Petrovica Alasa 12-14, 11001 Belgrade, Serbia 11Institut de Física d’Altes Energies, IFAE, Edifici Cn, Universitat Autònoma de Barcelona, ES-08193 Bellaterra (Barcelona), Spain 12University of Belgrade(a), Institute of Physics, P.O. Box 57, 11001 Belgrade; Vinca Institute of Nuclear Sciences(b), Mihajla Petrovica Alasa 12-14, 11001 Belgrade, Serbia 13University of Bergen, Department for Physics and Technology, Allegaten 55, NO-5007 Bergen, Norway 13University of Bergen, Department for Physics and Technology, Allegaten 55, NO-5007 Bergen, Norway 14L B k l N ti l L b t d U i it f C lif i Ph i Di i i MS50B 6227 1 C l t R d B k l CA 14Lawrence Berkeley National Laboratory and University of California, Physics Division, MS50B-6227, 1 Cyclotron 94720, United States of America 15Humboldt University, Institute of Physics, Berlin, Newtonstr. 15, D-12489 Berlin, Germany 16 15Humboldt University, Institute of Physics, Berlin, Newtonstr. ?CERN, 1211 Genève 23, Switzerland Box 918, 19 Yuquan Road, Shijing Shan District, CN-Beijing 100049; University of Science & Technology of China (USTC), Department of Modern Physics(b), Hefei, CN-Anhui 230026; Nanjing University, Universidad Técnica Federico Santa María, Departamento de Física , Avda. Espãna 1680, Casilla 110 V, Valparaíso, Chile 32Institute of High Energy Physics, Chinese Academy of Sciences(a), P.O. Box 918, 19 Yuquan Road, Shijing Shan District, CN-Beijing 100049; University of Science & Technology of China (USTC), Department of Modern Physics(b), Hefei, CN-Anhui 230026; Nanjing University, Department of Physics(c), 22 Hankou Road, Nanjing, 210093; Shandong University, High Energy Physics Group(d), Jinan, ?CERN, 1211 Genève 23, Switzerland Atomistilor 407, P.O. Box MG-6, R-077125, Romani University Politehnica Bucharest(b), Rectorat–AN 001, 313 Splaiul Independentei, sector 6, 060042 Bucuresti; West University(c) in Timisoara, Bd. Vasile Parvan 4, Timisoara, Romania 25National Institute of Physics and Nuclear Engineering(a), Bucharest-Magurele, Str. Atomistilor 407, P.O. Box MG-6, R-077125, Romania; University Politehnica Bucharest(b), Rectorat–AN 001, 313 Splaiul Independentei, sector 6, 060042 Bucuresti; West University(c) in Timisoara Bd Vasile Parvan 4 Timisoara Romania in Timisoara, Bd. Vasile Parvan 4, Timisoara, Romania 26Universidad de Buenos Aires, FCEyN, Dto. Fisica, Pab I–C. Universitaria, 1428 Buenos Aires, Argentina 27U i it f C b id C di h L b t J J Th A C b id CB3 0HE U it d Ki d 26Universidad de Buenos Aires, FCEyN, Dto. Fisica, Pab I–C. Universitaria, 1428 Buenos Aires, Argentina 27University of Cambridge, Cavendish Laboratory, J.J. Thomson Avenue, Cambridge CB3 0HE, United Kingdom 26Universidad de Buenos Aires, FCEyN, Dto. Fisica, Pab I–C. Universitaria, 1428 Buenos Aires, Argentina 27University of Cambridge, Cavendish Laboratory, J.J. Thomson Avenue, Cambridge CB3 0HE, United Kingdom 26Universidad de Buenos Aires, FCEyN, Dto. Fisica, Pab I–C. Universitaria, 1428 Buenos Aires, Argentina 27University of Cambridge Cavendish Laboratory J J Thomson Avenue Cambridge CB3 0HE United Kingdo Universidad de Buenos Aires, FCEyN, Dto. Fisica, Pab I– 29CERN, CH-1211 Geneva 23, Switzerland 30University of Chicago, Enrico Fermi Institute, 5640 S. Ellis Avenue, Chicago, IL 60637, United States of America 31Pontificia Universidad Católica de Chile, Facultad de Fisica, Departamento de Fisica(a), Avda. Vicuna Mackenna 4860, San Joaquin, Santiago; Universidad Técnica Federico Santa María, Departamento de Física(b), Avda. Espãna 1680, Casilla 110-V, Valparaíso, Chile 32Institute of High Energy Physics, Chinese Academy of Sciences(a), P.O. Box 918, 19 Yuquan Road, Shijing Shan District, CN-Beijing 100049; University of Science & Technology of China (USTC), Department of Modern Physics(b), Hefei, CN-Anhui 230026; Nanjing University, Department of Physics(c), 22 Hankou Road, Nanjing, 210093; Shandong University, High Energy Physics Group(d), Jinan, CN Shandong 250100 China University of Chicago, Enrico Fermi Institute, 5640 S. Ellis Avenue, Chicago, IL 60637, United States of America 31Pontificia Universidad Católica de Chile, Facultad de Fisica, Departamento de Fisica(a), Avda. Vicuna Mackenna 4860, San Joaquin, Santiago; Universidad Técnica Federico Santa María, Departamento de Física(b), Avda. Espãna 1680, Casilla 110-V, Valparaíso, Chile 32Institute of High Energy Physics, Chinese Academy of Sciences(a), P.O. Commissioning of the ATLAS Muon Spectrometer with cosmic rays Williams34, H.H. Williams120, S. Willocq84, J.A. Wilson17, M G Wil 143 A Wil 87 I Wi t S 4 F Wi kl i 29 M Witt 143 M W W lt 38 H W lt 124a 882 Eur. Phys. J. C (2010) 70: 875–916 X. Wu49, E. Wulf34, B.M. Wynne45, L. Xaplanteris9, S. Xella35, S. Xie48, D. Xu139, N. Xu171, M. Yamada159, A. Yamamoto66, K. Yamamoto64, S. Yamamoto154, T. Yamamura154, J. Yamaoka44, T. Yamazaki154, Y. Yamazaki67, Z. Yan21, H. Yang87, U.K. Yang82, Z. Yang145a,145b, W.-M. Yao14, Y. Yao14, Y. Yasu66, J. Ye39, S. Ye24, M. Yilmaz3c, R. Yoosoofmiya123, K. Yorita169, R. Yoshida5, C. Young143, S.P. Youssef21, D. Yu24, J. Yu7, L. Yuan78, A. Yurkewicz147, R. Zaidan63, A.M. Zaitsev128, Z. Zajacova29, V. Zambrano47, L. Zanello132a,132b, A. Zaytsev107, C. Zeitnitz173, M. Zeller174, A. Zemla38, C. Zendler20, O. Zenin128, T. Zenis144a, Z. Zenonos122a,122b, S. Zenz14, D. Zerwas115, G. Zevi della Porta57, Z. Zhan32d, H. Zhang83, J. Zhang5, Q. Zhang5, X. Zhang32d, L. Zhao108, T. Zhao138, Z. Zhao32b, A. Zhemchugov65, J. Zhong150,x, B. Zhou87, N. Zhou34, Y. Zhou150, C.G. Zhu32d, H. Zhu41, Y. Zhu171, X. Zhuang98, V. Zhuravlov99, R. Zimmermann20, S. Zimmermann20, S. Zimmermann48, M. Ziolkowski141, L. Živkovi´c34, G. Zobernig171, A. Zoccoli19a,19b, M. zur Nedden15, V. Zutshi106a ?CERN 1211 Genève 23 Switzerland X. Wu49, E. Wulf34, B.M. Wynne45, L. Xaplanteris9, S. Xella35, S. Xie48, D. Xu139, N. Xu171, M. Yamada159, A. Yamamoto66, K. Yamamoto64, S. Yamamoto154, T. Yamamura154, J. Yamaoka44, T. Yamazaki154, Y. Yamazaki67, Z. Yan21, H. Yang87, U.K. Yang82, Z. Yang145a,145b, W.-M. Yao14, Y. Yao14, Y. Yasu66, J. Ye39, S. Ye24, M. Yilmaz3c, R. Yoosoofmiya123, K. Yorita169, R. Yoshida5, C. Young143, S.P. Youssef21, D. Yu24, J. Yu7, L. Yuan78, A. Yurkewicz147, R. Zaidan63, A.M. Zaitsev128, Z. Zajacova29, V. Zambrano47, L. Zanello132a,132b, A. Zaytsev107, C. Zeitnitz173, M. Zeller174, A. Zemla38, C. Zendler20, O. Zenin128, T. Zenis144a, Z. Zenonos122a,122b, S. Zenz14, D. Zerwas115, G. Zevi della Porta57, Z. Zhan32d, H. Zhang83, J. Zhang5, Q. Zhang5, X. Zhang32d, L. Zhao108, T. Zhao138, Z. Zhao32b, A. Zhemchugov65, J. Zhong150,x, B. Zhou87, N. Zhou34, Y. Zhou150, C.G. Zhu32d, H. Zhu41, Y. Zhu171, X. Zhuang98, V. Zhuravlov99, R. Zimmermann20, S. Zimmermann20, S. Zimmermann48, M. Ziolkowski141, L. Živkovi´c34, G. Zobernig171, A. Zoccoli19a,19b, M. zur Nedden15, V. Zutshi106a ?CERN 1211 Genève 23 Switzerland CN-Shandong 250100, China 9, GE-380086 Tbilisi, Georgia y g 52Justus-Liebig-Universität Giessen, II Physikalisches Institut, Heinrich-Buff Ring 16, D-35392 Giessen, Germa 53 g y g y 53University of Glasgow, Department of Physics and Astronomy, Glasgow G12 8QQ, United Kingdom 54 53University of Glasgow, Department of Physics and Astronomy, Glasgow G12 8QQ, United Kingdom 54Georg-August-Universität, II. Physikalisches Institut, Friedrich-Hund Platz 1, D-37077 Göttingen, Germa 55 Georg August Universität, II. CN-Shandong 250100, China 85, D-22603 Hamburg and Platanenallee 6, D-15738 Zeuthen, Germany 42TU Dortmund, Experimentelle Physik IV, DE-44221 Dortmund, Germany nd, Experimentelle Physik IV, DE-44221 Dortmund, Germa 42TU Dortmund, Experimentelle Physik IV, DE-44221 Dortmund, Germany 43T h i l U i it D d I tit t fü K d T il h h ik Z ll h W 19 D 01069 D d G p y y 43Technical University Dresden, Institut für Kern- und Teilchenphysik, Zellescher Weg 19, D-01069 Dresden, G 44 p y y 43Technical University Dresden, Institut für Kern- und Teilchenphysik, Zelles 44 University Dresden, Institut für Kern- und Teilchenphysik, 44Duke University, Department of Physics, Durham, NC 27708, United States of America 45 45University of Edinburgh, School of Physics & Astronomy, James Clerk Maxwell Building, The Kings Buildin EH9 3JZ, United Kingdom g 46Fachhochschule Wiener Neustadt; Johannes Gutenbergstrasse 3 AT-2700 Wiener Neustadt, Austria 46Fachhochschule Wiener Neustadt; Johannes Gutenbergstrasse 3 AT-2700 Wiener Neustadt, Austria 46Fachhochschule Wiener Neustadt; Johannes Gutenbergstrasse 3 AT-2700 Wiener Neustadt, Austria 47INFN Laboratori Nazionali di Frascati, via Enrico Fermi 40, IT-00044 Frascati, Italy y udwigs-Universität, Fakultät für Mathematik und Physik, Hermann-Herder Str. 3, D-79104 Freiburg i.Br., Germany y 48Albert-Ludwigs-Universität, Fakultät für Mathematik und Physik, Hermann-Herder Str. 3, D-79104 Freiburg 49Université de Genève, Section de Physique, 24 rue Ernest Ansermet, CH-1211 Geneve 4, Switzerland 49Université de Genève, Section de Physique, 24 rue Ernest Ansermet, CH-1211 Geneve 4, Switzerland 50 ( ) (b) 49Université de Genève, Section de Physique, 24 rue Ernest Ansermet, CH-1211 Geneve 4, Switzerland 50INFN Sezione di Genova(a); Università di Genova, Dipartimento di Fisica(b), via Dodecaneso 33, IT-16146 Genova, Italy 51Institute of Physics of the Georgian Academy of Sciences, 6 Tamarashvili St., GE-380077 Tbilisi; Tbilisi State University, HEP Institute, University St. 9, GE-380086 Tbilisi, Georgia 52 INFN Sezione di Genova ; Università di Genova, Dipartimento di Fisica , via Dodecaneso 33, IT 16146 Genova 51Institute of Physics of the Georgian Academy of Sciences, 6 Tamarashvili St., GE-380077 Tbilisi; Tbilisi State Uni University St. 9, GE-380086 Tbilisi, Georgia ; , p , , , y 51Institute of Physics of the Georgian Academy of Sciences, 6 Tamarashvili St., GE-380077 Tbilisi; Tbilisi State University, HEP Institute, University St. CN-Shandong 250100, China 67, 1900 La Plata, Argentina 70Universidad Nacional de La Plata, FCE, Departamento de Física, IFLP (CONICET-UNLP), C.C. 67, 1900 L p 71Lancaster University, Physics Department, Lancaster LA1 4YB, United Kingdom y y p g 72INFN Sezione di Lecce(a); Università del Salento, Dipartimento di Fisica(b)Via Arnesano IT-73100 Lecce, Italy p 73University of Liverpool, Oliver Lodge Laboratory, P.O. CN-Shandong 250100, China 33Laboratoire de Physique Corpusculaire, Clermont Université, Université Blaise Pascal, CNRS/IN2P3, FR-63177 Aubiere Cedex, France 34 33Laboratoire de Physique Corpusculaire, Clermont Université, Université Blaise Pascal, CNRS/IN2P3, FR-63177 Aubiere Cedex, France 34 33Laboratoire de Physique Corpusculaire, Clermont Université, Université Blaise Pascal, CNRS/IN2P3, FR-63177 Aubiere Cedex, France 34Columbia University Nevis Laboratory 136 So Broadway Irvington NY 10533 United States of America y, y, y, g , , y of Copenhagen, Niels Bohr Institute, Blegdamsvej 17, DK-2100 Kobenhavn 0, Denmark y y y g 35University of Copenhagen, Niels Bohr Institute, Blegdamsvej 17, DK-2100 Kobenhavn 0, Denmark o Collegato di Cosenza(a); Università della Calabria, Dipartimento di Fisica(b), IT-87036 Arcavacata di Rende, Italy 36INFN Gruppo Collegato di Cosenza(a); Università della Calabria, Dipartimento di Fisica(b), IT-87036 A 883 Eur. Phys. J. C (2010) 70: 875–916 37Faculty of Physics and Applied Computer Science of the AGH-University of Science and Technology (FPACS, AGH-UST), al. Mickiewicza 30, PL-30059 Cracow, Poland 37Faculty of Physics and Applied Computer Science of the AGH-University of Science and Technology (FPACS, AGH-UST), al. Mickiewicza 30, PL-30059 Cracow, Poland 38The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, ul. Radzikowskiego 152, PL-31342 Krakow, Poland 39Southern Methodist University, Physics Department, 106 Fondren Science Building, Dallas, TX 75275-0175, United States of America 40 The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, ul. Radzikowskiego 152, PL-31342 Krakow, Poland 39Southern Methodist University, Physics Department, 106 Fondren Science Building, Dallas, TX 75275-0175, United States of America 39Southern Methodist University, Physics Department, 106 Fondren Science Building, Dallas, TX 75275-0175, United States of America 39Southern Methodist University, Physics Department, 106 Fondren Science Building, Dallas, TX 7527 y y p g ersity of Texas at Dallas, 800 West Campbell Road, Richardson, TX 75080-3021, United States of America 40University of Texas at Dallas, 800 West Campbell Road, Richardson, TX 75080-3021, United States of Americ y p Y, Notkestr. 85, D-22603 Hamburg and Platanenallee 6, D-15738 Zeuthen, Germany y p 41DESY, Notkestr. CN-Shandong 250100, China Physikalisches Institut, Friedrich Hund Platz 1, D 37077 Göttingen, Germany 55Laboratoire de Physique Subatomique et de Cosmologie, CNRS/IN2P3, Université Joseph Fourier, INPG, 53 avenue des Martyrs, FR-38026 Grenoble Cedex, France g g y g y 55Laboratoire de Physique Subatomique et de Cosmologie, CNRS/IN2P3, Université Joseph Fourier, INPG, 53 avenue des Martyrs, FR-38026 Grenoble Cedex, France 55Laboratoire de Physique Subatomique et de Cosmologie, CNRS/IN2P3, Université Joseph Fourier, INPG, 53 Grenoble Cedex, France , 56Hampton University, Department of Physics, Hampton, VA 23668, United States of America 5 pton University, Department of Physics, Hampton, VA 236 57Harvard University, Laboratory for Particle Physics and Cosmology, 18 Hammond Street, Cambridge, MA 02138, United States of America 58R h K l U i i ä H id lb Ki hh ff I i fü Ph ik(a) I N h i F ld 227 D 69120 H id lb 57Harvard University, Laboratory for Particle Physics and Cosmology, 18 Hammond Street, Cam 57Harvard University, Laboratory for Particle Physics and Cosmology, 18 Hammond Street, Cambridge, MA 02138, United States of America 58 ( ) 58Ruprecht-Karls-Universität Heidelberg: Kirchhoff-Institut für Physik(a), Im Neuenheimer Feld 227, D-69120 Heide (b) ( ) 58Ruprecht-Karls-Universität Heidelberg: Kirchhoff-Institut für Physik(a), Im Neuenheimer Feld 227, D-69120 Heidelberg; Physikalisches Institut(b), Philosophenweg 12, D-69120 Heidelberg; ZITI Ruprecht-Karls-University Heidelberg(c), Lehrstuhl für Informatik V, B6, 23-29, DE-68131 Mannheim, Germany 59 Physikalisches Institut(b), Philosophenweg 12, D-69120 Heidelberg; ZITI Ruprecht-Karls-University Heidelberg(c) Physikalisches Institut(b), Philosophenweg 12, D-69120 Heidelberg; ZITI Ruprecht-Karls-University Heidelberg(c), Lehrstuhl für Informatik V, B6, 23-29, DE-68131 Mannheim, Germany y p g g p y g Lehrstuhl für Informatik V, B6, 23-29, DE-68131 Mannheim, Germany Lehrstuhl für Informatik V, B6, 23-29, DE-68131 Mannheim, Germany y 59Hiroshima University, Faculty of Science, 1-3-1 Kagamiyama, Higashihir 60 59Hiroshima University, Faculty of Science, 1-3-1 Kagamiyama, Higashihiroshima-shi, JP–Hiroshima 739-8526, Jap 60 Hiroshima University, Faculty of Science, 1 3 1 Kagamiyama, Higashihiroshima shi, JP Hiroshima 739 8526, Japan 60Hiroshima Institute of Technology, Faculty of Applied Information Science, 2-1-1 Miyake Saeki-ku, Hiroshima-shi, JP–Hiroshima 731-5193, Japan 60Hiroshima Institute of Technology, Faculty of Applied Information Science, 2-1-1 Miyake Saeki-ku, Hiroshima-shi, JP–Hiroshima 731-5193, Japan 62Institut für Astro- und Teilchenphysik, Technikerstrasse 25, A-6020 Innsbruck, Austria 63 63University of Iowa, 203 Van Allen Hall, Iowa City, IA 52242-1479, United States of America 64 64Iowa State University, Department of Physics and Astronomy, Ames High Energy Physics Group, Ames, IA 50011-3160 United States of America 65 65Joint Institute for Nuclear Research, JINR Dubna, RU-141 980 Moscow Region, Russia 66 66KEK, High Energy Accelerator Research Organization, 1-1 Oho, Tsukuba-shi, Ibaraki-ken 305-0801, Japan 67 67Kobe University, Graduate School of Science, 1-1 Rokkodai-cho, Nada-ku, JP Kobe 657-8501, Japan y y y y y y 69Kyoto University of Education, 1 Fukakusa, Fujimori, Fushimi-ku, Kyoto-shi, JP–Kyoto 612-8522, Japan y j y y p Nacional de La Plata, FCE, Departamento de Física, IFLP (CONICET-UNLP), C.C. CN-Shandong 250100, China Box 147, Oxford Street, Liverpool L69 3BX, United K 74Jožef Stefan Institute and University of Ljubljana, Department of Physics, SI-1000 Ljubljana, Slovenia y j j p y j j 75Queen Mary University of London, Department of Physics, Mile End Road, London E1 4NS, United Kingdom y y y p y g g y g 77University College London, Department of Physics and Astronomy, Gower Street, London WC1E 6BT, United Kingdom 8 77University College London, Department of Physics and Astronomy, Gower Street, London WC1E 6BT, United Kingdom 78Laboratoire de Physique Nucléaire et de Hautes Energies, Université Pierre et Marie Curie (Paris 6), Université De CNRS/IN2P3 T 33 4 l J i FR 75252 P i C d 05 F 78Laboratoire de Physique Nucléaire et de Hautes Energies, Université Pierre et Marie Curie (Paris 6), Université CNRS/IN2P3, Tour 33, 4 place Jussieu, FR-75252 Paris Cedex 05, France ratoire de Physique Nucléaire et de Hautes Energies, Université Pierre et Marie Curie (Paris 6), Université Denis Dide 78Laboratoire de Physique Nucléaire et de Hautes Energies, Université Pierre et CNRS/IN2P3, Tour 33, 4 place Jussieu, FR-75252 Paris Cedex 05, France Laboratoire de Physique Nucléaire et de Hautes Energies, Université Pierre CNRS/IN2P3, Tour 33, 4 place Jussieu, FR-75252 Paris Cedex 05, France 79Lunds Universitet, Naturvetenskapliga Fakulteten, Fysiska Institutionen, Box 118, SE-221 00 Lund, Sweden 80 Lunds Universitet, Naturvetenskapliga Fakulteten, Fysiska I 79Lunds Universitet, Naturvetenskapliga Fakulteten, Fysiska Institutionen, Box 118, SE-221 00 Lund, Sweden , p g , y , , , 80Universidad Autonoma de Madrid, Facultad de Ciencias, Departamento de Fisica Teorica, ES-28049 Madrid, versidad Autonoma de Madrid, Facultad de Ciencias, Depar 81Universität Mainz, Institut für Physik, Staudinger Weg 7, DE-55099 Mainz, Germany 82University of Manchester, School of Physics and Astronomy, Manchester M13 9PL, United Kingdom and Astronomy, Manchester M13 9PL, United Kingdom niversity of Manchester, School of Physics and Astronomy, 84University of Massachusetts, Department of Physics, 710 North Pleasant Street, Amherst, MA 0100 85 84University of Massachusetts, Department of Physics, 710 North Pleasant Street, Amherst, MA 01003, United States of America 85M Gill U i it Hi h E Ph i G 3600 U i it St t M t l Q b H3A 2T8 C d 84University of Massachusetts, Department of Physics, 710 North Pleasant Street, Amherst, MA 01003, United States of America 85 Gill i i i h h i G 3600 i i S l Q b 3A 2 8 C d 84University of Massachusetts, Department of Physics, 710 North Pleasant Street, Amherst, MA 01003, United States of America 85McGill University, High Energy Physics Group, 3600 University Street, Montreal, Quebec H3A 2T8, Canada ersity of Massachusetts, Department of Physics, 710 North 84University of Massachusetts, Department of Physics, 710 North Pleasant Street, Amherst, MA 01003, United S 85McGill University, High Energy Physics Group, 3600 University Street, Montreal, Quebec H3A 2T8, Canada 86 University of Massachusetts, Department of Physics, 710 North Pleasant Street, Amherst, MA 01003, U 85McGill University, High Energy Physics Group, 3600 University Street, Montreal, Quebec H3A 2T8, C 86 85McGill University, High Energy Physics Group, 3600 University Street, Montreal, Qu 86 86University of Melbourne, School of Physics, AU–Parkville, Victoria 3010, Australia 87 86University of Melbourne, School of Physics, AU–Parkville, Victoria 3010, Australia 87 87The University of Michigan, Department of Physics, 2477 Randall Laboratory, 500 East University, Ann Arbor, MI 48109-1120, United States of America 87The University of Michigan, Department of Physics, 2477 Randall Laboratory, 500 East University, Ann Arbor, MI 48109-1120, United States of America 88 88Michigan State University, Department of Physics and Astronomy, High Energy Physics Group, East Lansing, MI 48824-2320, United States of America 88Michigan State University, Department of Physics and Astronomy, High Energy Physics Group, East Lansing, MI 48824-2320, United States of America Sezione di Milano(a); Università di Milano, Dipartimento di Fisica(b), via Celoria 16, IT-20133 Milano, Italy I i f Ph i N i l A d f S i f B l I d d A 68 Mi k 220072 89INFN Sezione di Milano(a); Università di Milano, Dipartimento di Fisica(b), via Celoria 16, IT-20133 Milano, I 90 90B.I. CN-Shandong 250100, China 25, RU 117 218 Moscow, R 96Moscow Engineering & Physics Institute (MEPhI), Kashirskoe Shosse 31, RU-115409 Moscow, Russia 97L M St t U i it Sk b lt I tit t f N l Ph i (MSU SINP) 1(2) L i ki 96Moscow Engineering & Physics Institute (MEPhI), Kashirskoe Shosse 31, RU-115409 Moscow, Russia 97 g g y ( ) 97Lomonosov Moscow State University Skobeltsyn Institute of Nuclear Physics (MSU SINP), 1(2), Leninskie gory, G Russian Federation, Russia 98Ludwig-Maximilians-Universität München, Fakultät für Physik, Am Coulombwall 1, DE-85748 Garching, German 99 y ( g ), g g , , y 100Nagasaki Institute of Applied Science, 536 Aba-machi, JP Nagasaki 851-0193, Japan y ( g ) g g y 100Nagasaki Institute of Applied Science, 536 Aba-machi, JP Nagasaki 851-0193, Japan g pp g p 101Nagoya University, Graduate School of Science, Furo-Cho, Chikusa-ku, Nagoya, 464-8602, Japan 102 ( ) (b) 102INFN Sezione di Napoli(a); Università di Napoli, Dipartimento di Scienze Fisiche(b), Complesso Universitario di Monte Sant’Angelo, via Cinthia, IT-80126 Napoli, Italy 102INFN Sezione di Napoli(a); Università di Napoli, Dipartimento di Scienze Fisiche(b), Complesso Universitario di Monte Sant’Angelo, via Cinthia, IT-80126 Napoli, Italy p y 103University of New Mexico, Department of Physics and Astronomy, MSC07 4220, Albuquerque, NM 87131 USA, United States of America 104Radboud University Nijmegen/NIKHEF, Department of Experimental High Energy Physics, Heyendaalseweg 135, NL-6525 AJ, Nijmegen, Netherlands p y 103University of New Mexico, Department of Physics and Astronomy, MSC07 4220, Albuquerque, NM 87131 USA, United States of America 104Radboud University Nijmegen/NIKHEF, Department of Experimental High Energy Physics, Heyendaalseweg 135, NL-6525 AJ, Nijmegen, Netherlands y , p y y, , q q , , 104Radboud University Nijmegen/NIKHEF, Department of Experimental High Energy Physics, Heyendaalseweg 135, NL-6525 AJ, Nijmegen, Netherlands 105 105Nikhef National Institute for Subatomic Physics, and University of Amsterdam, Science Park 105, 1098 XG Am 106( ) 105Nikhef National Institute for Subatomic Physics, and University of Amsterdam, Science Park 105, 1098 XG Amsterdam, Netherlands 106(a)DeKalb, Illinois 60115, United States of America Nikhef National Institute for Subatomic Physics, and University of Amsterdam, Science Park 105, 1098 XG Amsterdam, Netherlands 106(a)DeKalb, Illinois 60115, United States of America y y 106(a)DeKalb, Illinois 60115, United States of America 6(a)DeKalb, Illinois 60115, United States of America 107Budker Institute of Nuclear Physics (BINP), RU–Novosibirsk 630 090, Russia y niversity, Department of Physics, 4 Washington Place, New York NY 10003, USA, United States of America 108New York University, Department of Physics, 4 Washington Place, New York NY 10003, USA, United States o 109 109Ohio State University, 191 West Woodruff Ave, Columbus, OH 43210-1117, United States of America 109Ohio State University, 191 West Woodruff Ave, Columbus, OH 43210-1117, United States of America 109Ohio State University, 191 West Woodruff Ave, Columbus, OH 43210-1117, United States of America 111University of Oklahoma, Homer L. United States of America Pontecorvo 3, IT-56127 Pisa, Italy ersity of Pittsburgh Department of Physics and Astronomy 3941 O’Hara Street Pittsburgh PA 15260 United States ; , p , g , , y 123University of Pittsburgh, Department of Physics and Astronomy, 3941 O’Hara Street, Pittsburgh, PA 15260, United States of Ame y g , p y y, , g , , 124Laboratorio de Instrumentacao e Fisica Experimental de Particulas–LIP(a), Avenida Elias Garcia 14-1, PT-1000-149 Lisboa, Portugal; Universidad de Granada, Departamento de Fisica Teorica y del Cosmos and CAFPE(b), E-18071 Granada, Spain p , , 9 , Universidad de Granada, Departamento de Fisica Teorica y del Cosmos and CAFPE(b), E-18071 Granada, Spain p , , Universidad de Granada, Departamento de Fisica Teorica y del Cosmos and CAFPE(b), E-18071 Granada, Spain 25Institute of Physics, Academy of Sciences of the Czech Republic, Na Slovance 2, CZ-18221 Praha 8, Czech Repub y , y p , , , p 126Charles University in Prague, Faculty of Mathematics and Physics, Institute of Particle and Nuclear Physics, V Holesovickach 2, CZ-18000 Praha 8, Czech Republic 126Charles University in Prague, Faculty of Mathematics and Physics, Institute of Particle and Nuclear Physics, V Holesovickach 2, CZ-18000 Praha 8, Czech Republic p 127Czech Technical University in Prague, Zikova 4, CZ-166 35 Praha 6, Czech Republic y g p Research Center Institute for High Energy Physics, Moscow Region, 142281, Protvino, Pobeda street, 1, Russia 128State Research Center Institute for High Energy Physics, Moscow Region, 142281, Protvino, Pobeda street, 1, 129 g gy y , g , , , , , 129Rutherford Appleton Laboratory, Science and Technology Facilities Council, Harwell Science and Innovation Campus, Didcot OX11 0QX, United Kingdom 129Rutherford Appleton Laboratory, Science and Technology Facilities Council, Harwell Science and Innovation C United Kingdom 130University of Regina, Physics Department, Canada 131 130University of Regina, Physics Department, Canada 131 meikan University, Noji Higashi 1 chome 1-1, JP–Kusatsu, Shiga 525-8577, Japan ( ) (b) 131Ritsumeikan University, Noji Higashi 1 chome 1-1, JP–Kusatsu, Shiga 525-8577, Japan 132 ( ) (b) 131Ritsumeikan University, Noji Higashi 1 chome 1-1, JP 132 ( ) zione di Roma I(a); Università La Sapienza, Dipartimento di Fisica(b), Piazzale A. Moro 2, IT-00185 Roma, Italy ( ) (b) 132INFN Sezione di Roma I(a); Università La Sapienza, Dipartimento di Fisica(b), Piazzale A. United States of America 12Oklahoma State University, Department of Physics, 145 Physical Sciences Building, Stillwater, OK 74078-3072, U 13Palacký University, 17. listopadu 50a, 772 07 Olomouc, Czech Republic 112Oklahoma State University, Department of Physics, 145 Physical Sciences Building, Stillwater, OK 74078-3072, United States of America 113Palacký University, 17. listopadu 50a, 772 07 Olomouc, Czech Republic 112Oklahoma State University, Department of Physics, 145 Physical Sciences Building, Stillwater, OK 74078-3072, United States of America 113Palacký University, 17. listopadu 50a, 772 07 Olomouc, Czech Republic 114University of Oregon, Center for High Energy Physics, Eugene, OR 97403-1274, United States of America 114University of Oregon, Center for High Energy Physics 115LAL, Univ. Paris-Sud, IN2P3/CNRS, Orsay, France 116 115LAL, Univ. Paris-Sud, IN2P3/CNRS, Orsay, France 116 116Osaka University, Graduate School of Science, Machikaneyama-machi 1-1, Toyonaka, Osaka 560-0043, Japa 117 116Osaka University, Graduate School of Science, Machikaneyama-machi 1-1, Toyonaka, Osaka 560-0043, Japan 118Oxford University, Department of Physics, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH, United Kingdom 119INFN S i di P i (a) U i i à di P i Di i di Fi i N l T i (b) Vi B i 6 IT 27100 P i I l 118Oxford University, Department of Physics, Denys Wilkinson Building, Keble Road, Oxford OX1 3 119 ( ) (b) INFN Sezione di Pavia ; Università di Pavia, Dipartimento di Fisica Nucleare e Teorica , Via Bassi 6, IT 27100 Pavia, Italy 120University of Pennsylvania, Department of Physics, High Energy Physics Group, 209 S. 33rd Street, Philadelphia, PA 19104, United States of America 121 INFN Sezione di Pavia ; Università di Pavia, Dipartimento di Fisica Nucleare e Teorica , Via Bassi 6, IT 27100 Pavia, Italy 120University of Pennsylvania, Department of Physics, High Energy Physics Group, 209 S. 33rd Street, Philadelphia, PA 19104, United States of America 121Petersburg Nuclear Physics Institute, RU-188 300 Gatchina, Russia 122 ( ) 122INFN Sezione di Pisa(a); Università di Pisa, Dipartimento di Fisica E. Fermi(b), Largo B. Pontecorvo 3, IT-5612 123 Sezione di Pisa(a); Università di Pisa, Dipartimento di Fisica E. Fermi(b), Largo B. CN-Shandong 250100, China Stepanov Institute of Physics, National Academy of Sciences of Belarus, Independence Avenue 68, Minsk 220072, Republic of Bela 90B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Independence Avenue 68, Minsk 220072, Republic of Belaru Eur. Phys. J. C (2010) 70: 875–916 884 91National Scientific & Educational Centre for Particle & High Energy Physics, NC PHEP BSU, M. Bogdanovich St. 153, Minsk 220040, Republic of Belarus 92Massachusetts Institute of Technology, Department of Physics, Room 24-516, Cambridge, MA 02139, United States of America 93University of Montreal, Group of Particle Physics, C.P. 6128, Succursale Centre-Ville, Montreal, Quebec, H3C 3J7, Canada Massachusetts Institute of Technology, Department of Physics, Room 24 516, Cambridge, MA 02139, United States of Ame 93University of Montreal, Group of Particle Physics, C.P. 6128, Succursale Centre-Ville, Montreal, Quebec, H3C 3J7, Canada gy, p y , , g , , 93University of Montreal, Group of Particle Physics, C.P. 6128, Succursale Centre-Ville, Montreal, Quebec, H3C 3J7 94 93University of Montreal, Group of Particle Physics, C.P. 6128, Succursale Centre-Ville, Montreal, Quebec, H3C 3J7, Canada 94P.N. Lebedev Institute of Physics, Academy of Sciences, Leninsky pr. 53, RU-117 924 Moscow, Russia 95 95Institute for Theoretical and Experimental Physics (ITEP), B. Cheremushkinskaya ul. CN-Shandong 250100, China Dodge Department of Physics and Astronomy, 440 West Brooks, Room 100, Norman, OK 73019-0225, United States of America 11University of Oklahoma, Homer L. Dodge Department of Physics and Astronomy, 440 West Brooks, Room 100, N United States of America United States of America of Valencia, and Instituto de Microelectrónica de Barcelona (IMB-CNM-CSIC) 08193 Bellaterra Bar 167 Univ. of Valencia, and Instituto de Microelectrónica de Barcelona (IMB-CNM-CSIC) 08193 Bellaterra Barcelona, 67 167University of British Columbia, Department of Physics, 6224 Agricultural Road, CA–Vancouver, B.C. V6T 1Z 169Waseda University, WISE, 3-4-1 Okubo, Shinjuku-ku, Tokyo, 169-8555, Japan 169Waseda University, WISE, 3-4-1 Okubo, Shinjuku-ku, Tokyo, 169-8555, Japan 170The Weizmann Institute of Science, Department of Particle Physics, P.O. Box 26, IL-76100 Rehovot, Israel 171 171University of Wisconsin, Department of Physics, 1150 University Avenue, WI 53706 Madison, Wisconsin, Uni 172 172Julius-Maximilians-University of Würzburg, Physikalisches Institute, Am Hubland, 97074 Würzburg, Germany 173 173Bergische Universität, Fachbereich C, Physik, Postfach 100127, Gauss-Strasse 20, D-42097 Wuppertal, Germa 174Yale University, Department of Physics, PO Box 208121, New Haven CT, 06520-8121, United States of Ameri 175 175Yerevan Physics Institute, Alikhanian Brothers Street 2, AM-375036 Yerevan, Armenia 175Yerevan Physics Institute, Alikhanian Brothers Street 2, AM-375036 Yerevan, Armenia 6ATLAS-Canada Tier-1 Data Centre, TRIUMF, 4004 Wesb 177GridKA Tier-1 FZK, Forschungszentrum Karlsruhe GmbH, Steinbuch Centre for Computing (SCC), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany 177GridKA Tier-1 FZK, Forschungszentrum Karlsruhe GmbH, Steinbuch Centre for Computing (SCC), Hermann- Eggenstein-Leopoldshafen, Germany 1 8 177GridKA Tier-1 FZK, Forschungszentrum Karlsruhe GmbH, Steinbuch Centre for Computing (SCC), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany United States of America of Subnuclear Physics(b), Watsonova 47, SK-04353 Kosice, Slovak Republic 145S kh l U i i D f Ph i (a) Th O k Kl i C (b) Alb N SE 106 91 S kh l S d 144Comenius University, Faculty of Mathematics, Physics & Informatics(a), Mlynska dolina F2, SK-84248 Bra Physics of the Slovak Academy of Sciences, Dept. of Subnuclear Physics(b), Watsonova 47, SK-04353 Kos 5 b Comenius University, Faculty of Mathematics, Physics & Informatics( ), Mlynska dolina F2, SK-84248 Bratislava; Institute of Experimental Physics of the Slovak Academy of Sciences, Dept. of Subnuclear Physics(b), Watsonova 47, SK-04353 Kosice, Slovak Republic 145Stockholm University: Department of Physics(a); The Oskar Klein Centre(b), AlbaNova, SE-106 91 Stockholm, Sweden Physics of the Slovak Academy of Sciences, Dept. of Subnuclear Physics(b), Watsonova 47, SK-04353 Kosice, Slovak Republic 145Stockholm University: Department of Physics(a); The Oskar Klein Centre(b), AlbaNova, SE-106 91 Stockholm, Sweden 145Stockholm University: Department of Physics(a); The Oskar Klein Centre(b), AlbaNova, SE-106 91 Stockholm, Sweden 6 146Royal Institute of Technology (KTH), Physics Department, SE-106 91 Stockholm, Sweden y gy ( ), y p , , 147Stony Brook University, Department of Physics and Astronomy, Nicolls Road, Stony Brook, NY 11794-3800, United States of America 148University of Sussex, Department of Physics and Astronomy Pevensey 2 Building, Falmer, Brighton BN1 9QH, United Kingdom 149University of Sydney, School of Physics, AU–Sydney NSW 2006, Australia y gy y p 147Stony Brook University, Department of Physics and Astronomy, Nicolls Road, Stony Brook, NY 11794-3800, U 147Stony Brook University, Department of Physics and Astronomy, Nicolls Road, Stony Brook, NY 11794-3800, United States of America 148University of Sussex, Department of Physics and Astronomy Pevensey 2 Building, Falmer, Brighton BN1 9QH, United Kingdom 149 i i f S d S h l f h i S d S 2006 li 148University of Sussex, Department of Physics and Astronomy Pevensey 2 Building, Falmer, Brighton BN1 9QH, United Kingdom 149 y p y y y g g Q 149University of Sydney, School of Physics, AU–Sydney NSW 2006, Australia 5 sity of Sydney, School of Physics, AU–Sydney NSW 2006 150Insitute of Physics, Academia Sinica, TW–Taipei 11529, Taiwan 151Technion, Israel Inst. United States of America Moro 2, IT-00185 R 133 ( ) (b) 133INFN Sezione di Roma Tor Vergata(a); Università di Roma Tor Vergata, Dipartimento di Fisica(b), via della Ricerca Scientifica, IT-00133 Roma, Italy 134 ( ) (b) 134INFN Sezione di Roma Tre(a); Università Roma Tre, Dipartimento di Fisica(b), via della Vasca Navale 84, IT-00 135Réseau Universitaire de Physique des Hautes Energies (RUPHE): Université Hassan II, Faculté des Sciences Ain Chock(a), B.P. 5366, MA–Casablanca; Centre National de l’Energie des Sciences Techniques Nucleaires (CNESTEN)(b), B.P. 1382 R.P. 10001 Rabat 10001; Université Mohamed Premier(c), LPTPM, Faculté des Sciences, B.P.717. Bd. Mohamed VI, 60000, Oujda; Université Mohammed V, Faculté des Sciences(d), 4 Avenue Ibn Battouta, BP 1014 RP, 10000 Rabat, Morocco Premier(c), LPTPM, Faculté des Sciences, B.P.717. Bd. Mo Faculté des Sciences(d), 4 Avenue Ibn Battouta, BP 1014 RP, 10000 Rabat, Morocco 136CEA, DSM/IRFU, Centre d’Etudes de Saclay, FR-91191 Gif-sur-Yvette, France 137 SM/IRFU, Centre d’Etudes de Saclay, FR-91191 Gif-sur-Y 137University of California Santa Cruz, Santa Cruz Institute for Particle Physics (SCIPP), Santa Cruz, CA 95064, United States of America 138University of Washington Seattle Department of Physics Box 351560 Seattle WA 98195-1560 United States of America 137University of California Santa Cruz, Santa Cruz Institute for Particle Physics (SCIPP), Santa Cr 138 137University of California Santa Cruz, Santa Cruz Institute for Particle Physics (SCIPP), Santa Cruz, CA 95064, United States of America 138 f Washington, Seattle, Department of Physics, Box 351560 139University of Sheffield, Department of Physics & Astronomy, Hounsfield Road, Sheffield S3 7RH, United King 139University of Sheffield, Department of Physics & Astronomy, Hounsfield Road, Sheffield S3 7RH, United Kingdom 140 140Shinshu University, Department of Physics, Faculty of Science, 3-1-1 Asahi, Matsumoto-shi, JP–Nagano 390-8 140Shinshu University, Department of Physics, Faculty of Science, 3-1-1 Asahi, Matsumoto-s 141 141Universität Siegen, Fachbereich Physik, D 57068 Siegen, Germany 142 142Simon Fraser University, Department of Physics, 8888 University Drive, CA–Burnaby, BC V5A 1S6, Canada 142Simon Fraser University, Department of Physics, 8888 University Drive, CA–Burnaby, BC V5A 1S6, Canada 142Simon Fraser University, Department of Physics, 8888 University Drive, C Fraser University, Department of Physics, 8888 University 885 Eur. Phys. J. C (2010) 70: 875–916 143SLAC National Accelerator Laboratory, Stanford, California 94309, United States of America 144 ( ) 144Comenius University, Faculty of Mathematics, Physics & Informatics(a), Mlynska dolina F2, SK-84248 Bratislava; Institute of Experimental Physics of the Slovak Academy of Sciences, Dept. United States of America aAlso at CPPM, Marseille, France. b United States of America of Technology, Department of Physics, Technion City, IL–Haifa 32000, Israel 152 152Tel Aviv University, Raymond and Beverly Sackler School of Physics and Astronomy, Ramat Aviv, IL–Tel Aviv 69978, Israel 153Aristotle University of Thessaloniki, Faculty of Science, Department of Physics, Division of Nuclear & Particle Physics, University Campus GR-54124, Thessaloniki, Greece 154The University of Tokyo, International Center for Elementary Particle Physics and Department of Physics, 7-3-1 Hongo, Bunkyo-ku, JP–Tokyo 113-0033, Japan y , p 155Tokyo Metropolitan University, Graduate School of Science and Technology, 1-1 Minami-Osawa, Hachioji, Tok 156Tokyo Institute of Technology, 2-12-1-H-34 O-Okayama, Meguro, Tokyo 152-8551, Japan 157University of Toronto, Department of Physics, 60 Saint George Street, Toronto M5S 1A7, Ontario, Canada 158 ( ) (b) University of Toronto, Department of Physics, 60 Saint George Street, Toronto M5S 1A7, Ontario, Canada 158TRIUMF(a), 4004 Wesbrook Mall, Vancouver, B.C. V6T 2A3; (b)York University, Department of Physics and Astronomy, 4700 Keele St., Toronto, Ontario, M3J 1P3, Canada Tsukuba, Institute of Pure and Applied Sciences, 1-1-1 Tennoudai, Tsukuba-shi, JP–Ibaraki 305-8571, Japan 159University of Tsukuba, Institute of Pure and Applied Sciences, 1-1-1 Tennoudai, Tsukuba-shi, JP–Ibaraki 305-8 6 160Tufts University, Science & Technology Center, 4 Colby Street, Medford, MA 02155, United States of America 161 161Universidad Antonio Narino, Centro de Investigaciones, Cra 3 Este No. 47A-15, Bogota, Colombia 161Universidad Antonio Narino, Centro de Investigaciones, Cra 3 Este No. 47A-15, Bogota, Colombia University of California, Irvine, Department of Physics & Astronomy, CA 92697-4575, United States of America 163INFN Gruppo Collegato di Udine(a); ICTP(b), Strada Costiera 11, IT-34014, Trieste; Università di Udine, Dipartimento di Fisica(c), via delle Scienze 208, IT-33100 Udine, Italy 164 y p y y 163INFN Gruppo Collegato di Udine(a); ICTP(b), Strada Costiera 11, IT-34014, Trieste; Università di Udine, Dipartimento di Fisica(c), via delle Scienze 208, IT-33100 Udine, Italy 63INFN Gruppo Collegato di Udine(a); ICTP(b), Strada Costiera 11, IT-34014, Trieste; Università di Udine, Dipartime Scienze 208, IT-33100 Udine, Italy 64 64University of Illinois, Department of Physics, 1110 West Green Street, Urbana, Illinois 61801, United States of Am 165University of Uppsala, Department of Physics and Astronomy, P.O. Box 516, SE-51 20 Uppsala, Sweden 165University of Uppsala, Department of Physics and Astronomy, P.O. Box 516, SE-51 20 Uppsala, Sweden 166 y pp p y y pp 66Instituto de Física Corpuscular (IFIC) Centro Mixto UVEG-CSIC, Apdo. 22085 ES-46071 Valencia, Dept. Física A 166Instituto de Física Corpuscular (IFIC) Centro Mixto UVEG-CSIC, Apdo. 22085 ES-46071 Valencia, Dept. Univ. g Eggenstein-Leopoldshafen, Germany gg p y 178Port d’Informacio Cientifica (PIC), Universitat Autonoma de Barcelona (UAB), Edifici D, E-08193 Bellaterra, ( ), ( ), , , p 179Centre de Calcul CNRS/IN2P3, Domaine Scientifique de la Doua, 27 bd du 11 Novembre 1918, 69622 Villeurbanne Cedex, France 180 179Centre de Calcul CNRS/IN2P3, Domaine Scientifique de la Doua, 27 bd du 11 Novembre 1918, 69622 Villeurbanne Cedex q 180INFN-CNAF, Viale Berti Pichat 6/2, 40127 Bologna, Italy g y 81Nordic Data Grid Facility, NORDUnet A/S, Kastruplundgade 22, 1, DK-2770 Kastrup, Denmark 82 181Nordic Data Grid Facility, NORDUnet A/S, Kastruplundgade 22, 1, DK-2770 Kastrup, Denmark 182 82SARA Reken- en Netwerkdiensten, Science Park 121, 1098 XG Amsterdam, Netherlands 83 182SARA Reken- en Netwerkdiensten, Science Park 121, 1098 XG Amsterdam, Netherlands 183 183Academia Sinica Grid Computing, Institute of Physics, Academia Sinica, No.128, Sec. 2, Academia Rd., Nankang, Taipei, Taiwan 11529, Taiwan 184 183Academia Sinica Grid Computing, Institute of Physics, Academia Sinica, No.128, Sec. 2, Academia Rd., Nankang, Taipei, Taiwan 11529, Taiwan 184UK-T1-RAL Tier-1, Rutherford Appleton Laboratory, Science and Technology Facilities Council, Harwell Scie Didcot OX11 0QX, United Kingdom 5 Didcot OX11 0QX, United Kingdom 185RHIC and ATLAS Computing Facility, Physics Department, Building 510, Brookhaven National Laboratory, Upton, New York 11973, United States of America 185RHIC and ATLAS Computing Facility, Physics Department, Building 510, Brookhaven National Laboratory, Upton, New York 11973, U it d St t f A i 1The ATLAS reference system is a Cartesian right-handed coordinate system, with the nominal collision point at the origin. The positive x-axis is defined as pointing from the collision point to the center of the LHC ring and the positive y-axis points upwards while the z-axis is tangent to the beam direction at the collision point. The azimuthal angle φ is measured around the beam axis, and the polar angle θ is the angle measured with respect to the z-axis. The pseudorapidity is defined as η = −lntanθ/2. aAlso at CPPM, Marseille, France. C (2010) 70: 875–916 886 lAlso at Petersburg Nuclear Physics Institute, RU-188 300 Gatchina, Russia lAlso at Petersburg Nuclear Physics Institute, RU-188 300 Gatchina, Russia mAlso at School of Physics and Engineering, Sun Yat-sen University, China so at School of Physics, Shandong University, Jinan, China y , g y, , oAlso at Rutherford Appleton Laboratory, Science and Technology Facilities Council, Harwell Science and Innovation Campus, Didcot OX11, United Kingdom pAl S h l f Ph i Sh d U i i Ji oAlso at Rutherford Appleton Laboratory, Science and Technology Facilities Council, Harwell Science and Innovation Campus, Didcot OX11, United Kingdom p l h l f h i h d i i i pAlso at School of Physics, Shandong University, Jinan y g y qAlso at Rutherford Appleton Laboratory, Science and Technology Facilities Council, Harwell Science and Innovation Campus, Didcot OX11 0QX, United Kingdom rN t KEK qAlso at Rutherford Appleton Laboratory, Science and Technology Facilities Council, Harwell Science and Innovation Campus, Didcot OX11 0QX, United Kingdom rNow at KEK rNow at KEK sUniversity of South Carolina, Dept. of Physics and Astronomy, 700 S. Main St, Columbia, SC 29208, United States of America tAl t KFKI R h I tit t f P ti l d N l Ph i B d t H Also at KFKI Research Institute for Particle and Nuclear Physics, Budap uAlso at Institute of Physics, Jagiellonian University, Cracow, Poland uAlso at Institute of Physics, Jagiellonian University, Cracow, Poland y g y vAlso at School of Physics and Engineering, Sun Yat-sen University, Taiwan wTransfer to LHCb 31.01.2010 Received: 18 June 2010 / Revised: 19 July 2010 / Published online: 23 October 2010 © CERN for the benefit of the ATLAS collaboration 2010. This article is published with open access at Springerlink.com Received: 18 June 2010 / Revised: 19 July 2010 / Published online: 23 October 2010 © CERN for the benefit of the ATLAS collaboration 2010. This article is published with ope 1 The ATLAS Muon Spectrometer Abstract The ATLAS detector at the Large Hadron Col- lider has collected several hundred million cosmic ray events during 2008 and 2009. These data were used to commis- sion the Muon Spectrometer and to study the performance of the trigger and tracking chambers, their alignment, the detector control system, the data acquisition and the analy- sis programs. We present the performance in the relevant parameters that determine the quality of the muon mea- surement. We discuss the single element efficiency, reso- lution and noise rates, the calibration method of the detec- tor response and of the alignment system, the track recon- struction efficiency and the momentum measurement. The results show that the detector is close to the design per- formance and that the Muon Spectrometer is ready to de- tect muons produced in high energy proton–proton colli- sions. The ATLAS Muon Spectrometer (MS in the following) is designed to provide a standalone measurement of the muon momentum with an uncertainty in the transverse momentum varying from 3% at 100 GeV to about 10% at 1 TeV, and to provide a trigger for muons with varying transverse momen- tum thresholds down to a few GeV. A detailed description of the muon spectrometer and of its expected performance can be found in [1–3]. Here only a brief overview is given. The muon momentum is determined by measuring the track cur- vature in a toroidal magnetic field. The muon trajectory is always normal to the main component of the magnetic field so that the transverse momentum resolution is roughly inde- pendent of η over the whole acceptance. The magnetic field is provided by three toroids, one in the “barrel” (|η| < 1.1) and one for each “end-cap” (1.1 < |η| < 2.7), with a field integral between 2 and 8 Tm. The muon curvature is mea- sured by means of three precision chamber stations posi- tioned along its trajectory. In order to meet the required pre- cision each muon station should provide a measurement on the muon trajectory with an accuracy of 50 µm. In Fig. 1 a schematic view of the muon spectrometer1 is given. aAlso at CPPM, Marseille, France. bAlso at TRIUMF, 4004 Wesbrook Mall, Vancouver, B.C. V6T 2A3, Canada bAlso at TRIUMF, 4004 Wesbrook Mall, Vancouver, B.C. V6T 2A3, Canada cAlso at Faculty of Physics and Applied Computer Science of the AGH-University of Science and Te cAlso at Faculty of Physics and Applied Computer Science of the AGH-University of Science and Technology (FPA cAlso at Faculty of Physics and Applied Computer Science of the AGH-University of Science and Technology (FPACS, AGH-UST), al. Mickiewicza 30, PL-30059 Cracow, Poland cAlso at Faculty of Physics and Applied Computer Science of the y y pp p y gy al. Mickiewicza 30, PL-30059 Cracow, Poland al. Mickiewicza 30, PL-30059 Cracow, Poland dAlso at Università di Napoli Parthenope, via A. Acton 38, IT-80133 Napoli, Italy dAlso at Università di Napoli Parthenope, via A. Acton 38, IT-80133 Napoli, Italy dAlso at Università di Napoli Parthenope, via A. A eAlso at Institute of Particle Physics (IPP), Canada y ( ), fLouisiana Tech University, 305 Wisteria Street, P.O. Box 3178, Ruston, LA 71272, United States of America y fLouisiana Tech University, 305 Wisteria Street, P.O. Box 3178, Ruston, LA 71272, United States of America fLouisiana Tech University, 305 Wisteria Street, P.O. Box 3178, Ruston, LA 71272, United States of America Louisiana Tech University, 305 Wisteria Street, P.O. Box 31 At Department of Physics, California State University, Fresn urrently at Istituto Universitario di Studi Superiori IUSS, V.le Lungo Ticino Sforza 56, 27100 Pavia, Italy hCurrently at Istituto Universitario di Studi Superiori IUSS, V.le Lungo Ticino Sforza 56, 27100 Pavia, Italy hCurrently at Istituto Universitario di Studi Superiori IUSS, V.le Lungo Ticino Sforza 56, 27100 Pavia, Italy i rnia Institute of Technology, Physics Department, Pasadena iAlso at California Institute of Technology, Physics Department, Pasadena, CA 91125, United States of America j iAlso at California Institute of Technology, Physics Department, Pasadena, CA 91125, United States of j so at California Institute of Technology, Physics Departmen jAlso at University of Montreal, Canada k lso at University of Montreal, Canada lso at Institut für Experimentalphysik, Universität Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany y lso at Institut für Experimentalphysik, Universität Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany kAlso at Institut für Experimentalphysik, Universität Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany Eur. Phys. J. ?? e-mail: atlas.secretariat@cern.ch Contents 1 The ATLAS Muon Spectrometer . . . . . . . . . 886 2 Data sample and reconstruction software . . . . . 888 3 Trigger configuration during data taking . . . . . 890 4 Data quality assessment . . . . . . . . . . . . . . 891 5 MDT chamber calibration . . . . . . . . . . . . . 894 6 Detector performance: efficiency and resolution . 897 7 MDT optical alignment . . . . . . . . . . . . . . 902 8 Pattern recognition and segment reconstruction . 908 9 Track reconstruction . . . . . . . . . . . . . . . . 910 10 Summary . . . . . . . . . . . . . . . . . . . . . . 914 Acknowledgements . . . . . . . . . . . . . . . . . . 915 Open Access . . . . . . . . . . . . . . . . . . . . . . 915 References . . . . . . . . . . . . . . . . . . . . . . . 915 For most of the acceptance Monitored Drift Tube (MDT) chambers are deployed [2]. The coordinate in the plane per- pendicular to the wires, measured by the MDT, is referred to as the precision, or bending coordinate, being mainly per- 887 Eur. Phys. J. C (2010) 70: 875–916 Schematic view of the muon spectrometer in the x–y (top) and z–y (bottom) projections. Inner, Middle and Outer chamber stati ed BI, BM, BO in the barrel and EI, EM, EO in the end-cap Fig. 1 Schematic view of the muon spectrometer in the x–y (top) and z–y (bottom) projections. Inner, Middle and Outer chamber stations are denoted BI, BM, BO in the barrel and EI, EM, EO in the end-cap 888 Eur. Phys. J. C (2010) 70: 875–916 pendicular to the direction of the toroidal field. In the end- cap inner region, for |η| < 2.0, Cathode Strip Chambers (CSC) [2] are used because of their capability to cope with higher background rates. Beginning in September 2008 the ATLAS detector was operated continuously up to November 2008 and then for different periods starting from Spring 2009. The first beams were circulated in the LHC machine in September 2008 but no beam-beam collisions were delivered. During these peri- ods, the ATLAS detector collected mainly cosmic ray data. All muon detector technologies were included in the run with the exception of CSCs for which the Read Out chain was still not yet commissioned and therefore they are not included in the results presented in this paper. The MDT chambers are composed of two MultiLayers (ML) made of three or four layers of tubes. Each tube is 30 mm in diameter and has an anode wire of 50 µm diameter. The gas mixture used is 93% Ar and 7% CO2 with a small admixture of water vapor, the drift velocity is not saturated and the total drift time is about 700 ns. The space resolu- tion attainable with a single tube is about 80 µm, measured in a test beam [4, 5]. The CSC chambers are multiwire pro- portional chambers with cathode strip read out. The cathode planes are equipped with orthogonal strips and the precision coordinate is obtained measuring the charge induced on the strips making the charge interpolation between neighboring strips. Typical resolution obtained with this read-out scheme is about 50 µm. The analyzed data samples and the reconstruction soft- ware are described in Sect. 2. The cosmic ray trigger is described in Sect. 3. Studies of data quality, calibration, and alignment are presented in Sects. 4, 5, 6, 7 respec- tively, while studies on tracking performance are presented in Sects. 8 and 9. The results are summarized in Sect. 2.1 Data sample In preparation for LHC collisions, the ATLAS detector has acquired several hundred million cosmic ray events during several run periods in 2008 and 2009. The analysis of a sub- set of data corresponding to about 60 M events is presented here. These runs allowed commissioning the ATLAS exper- iment, the trigger, the data acquisition, the various detectors and the reconstruction software. Most of the cosmic rays reach the underground detectors via the two big shafts. They have incident angles close to the vertical axis and they are mainly triggered by the RPCs. The selected runs, together with the status of the magnetic field in the MS and the num- ber of collected events for the different trigger streams, are listed in Table 1. Similarly in the end-cap two TGC doublets and one triplet are installed close to the middle station and provide the low-pT and high-pT trigger signals. The TGCs also measure the coordinate of the muons in the direction par- allel to the MDT wires. This coordinate is referred to as the second, or non-bending coordinate. For this purpose TGC chambers are also installed close to the MDTs in the inner layer of the end-cap (EI). Some MS naming conventions adopted in this paper are introduced here. The MS is divided in the x–y-plane (also referred to as φ-plane) in 16 sectors: Sector 5 being the up- per most and Sector 13 the lower most. In both barrel and end-cap regions the MS is divided into 8 ‘Large’ sectors (odd numbered sectors) and 8 ‘Small’ sectors (even num- bered sectors), determined by their coverage in φ. The muon stations are named ‘Inner’, ‘Middle’, and ‘Outer’, according to the distance from the Interaction Point (IP). The three sta- tions for the barrel are denoted BI, BM, and BO, and for the End-Cap EI, EM, and EO, respectively. Along the z axis, the MS is divided into two sides, called side A (positive z) and C (negative z). Table 1 List of analyzed data runs together with the corresponding trigger stream, statistics and status of the MS magnetic field. 10. The trigger system of the MS is based on two different chamber technologies: Resistive Plate Chambers (RPC) [2] instrument the barrel region while Thin Gap Chambers (TGC) [2] are used in the higher background environment of the end-cap regions. Two RPC chambers are attached to the middle barrel chambers providing a low-pT trigger. A high- pT trigger is provided by the RPC modules installed on the outer barrel chambers in combination with the low pT signal provided by the middle chambers. The RPCs also provide the coordinate along the MDT wires that is not measured by the MDT chambers. 2.2 Muon reconstruction software – reconstruction of local segments in each muon station in the identified ROA – reconstruction of local segments in each muon station in the identified ROA – reconstruction of local segments in each muon station in the identified ROA The data were processed using the complete ATLAS soft- ware chain [6]: data decoding, data preparation (which in- cludes calibration and alignment), and track reconstruction. Muon reconstruction has been handled by two independent packages, namely Moore [7] and Muonboy [8]. The two re- construction algorithms are similar in design but differ in some details. The general strategy is to reconstruct muon trajectories both at the local (individual chamber), as well as at the global (spectrometer), level. The trajectories re- constructed in individual chambers can be approximated as straight lines over a short distance where bending has little effect and are therefore fit to track segments. Full tracks are formed by combining segments from multiple chambers. – combination of segments of different muon stations to form muon track candidates using three-dimensional tracking in magnetic field – global track fit of the muon track candidates through the full system using individual hit information. – global track fit of the muon track candidates through the full system using individual hit information. The topology of cosmic ray tracks is accommodated by re- laxing the Region Of Activity requirement of pointing in a projective geometry when associating hits to form segments, or matching segments to form tracks. Moreover, since cos- mic ray events have low occupancy, looser quality criteria were used for the selection of segments and tracks. The Muonboy algorithm for the Gt0-refit consists of a scan of different gt0 values in steps of 10 ns, doing the full segment reconstruction at each step. The gt0 value giving the best reconstruction quality factor is kept and a parabolic fit is performed using this best value and the two closer val- ues along the parabola. Then the gt0 corresponding to the minimum of the quality factor parabola is chosen. In order to obtain high efficiency, the accuracy requirement for the MDT single hit resolution is relaxed by adding in quadra- ture a 0.5 mm constant smearing to the intrinsic resolution function (described in Sect. 6). This smearing is increased by additional 0.5 mm if the Gt0-refit fails. 2.1 Data sample All runs were collected in Fall 2008, with the exceptions of run 113860 col- lected in Spring 2009, and run 121080 in Summer 2009 Run Trigger B-field N of Evts Period 91060 RPC Off 17 M Fall 08 91060 TGC Off 0.2 M Fall 08 89106 TGC Off 0.4 M Fall 08 89403 TGC Off 0.4 M Fall 08 91803 TGC On 50 K Fall 08 91890 RPC On 16 M Fall 08 113860 RPC Off 6 M Spring 09 121080 RPC On 21 M Summ 09 As a complementary source of information, two publica tions [4, 5] on a detector system-test with a high momentum muon beam can be consulted. Eur. Phys. J. C (2010) 70: 875–916 889 2.4 Moore track reconstruction 2.4 Moore track reconstruction The reconstruction algorithms were adapted for these “cosmic ray” conditions as described below. Both programs were modified by relaxing the standard tracking require- ments and implementing a procedure to accommodate the cosmic ray timing conditions. The tolerance for hit associ- ation to form track segments and the uncertainty associated with each hit position were increased. Moreover, a proce- dure called global t0 refit (Gt0-refit) was developed in both reconstruction algorithms to compensate for the 25 ns time jitter and the imprecise trigger timing. The aim of this pro- cedure is to determine with better precision the time when the cosmic ray crossed the detector by introducing a free global timing parameter (gt0) in the segment reconstruction. The implementation of the Gt0-refit in the two reconstruc- tion algorithms is briefly described below while the results are presented in Sect. 5. The Moore reconstruction algorithm is built out of several distinct stages: The Moore reconstruction algorithm is built out of several distinct stages: – identification of global roads throughout the entire spec- trometer using all muon detectors (MDT, CSC, RPC and TGC) – reconstruction of local segments in each muon station seeded by the identified global roads – combination of segments of different muon stations to form muon track candidates – global, three-dimensional, tracking and final track fit. Several modifications to the standard pattern recognition were made to optimize the reconstruction of cosmic ray tracks. In the global road finding step, a straight line Hough transform was used to allow for non-pointing tracks. The cuts on distance and direction between the road and the seg- ment were relaxed. In the segment finding no cuts were ap- plied on the number of missing hits (i.e. drift tubes that are expected to be crossed but have no hits). 2.3 Muonboy track reconstruction 2.4 Moore track reconstruction 2.4 Moore track reconstruction 2.2 Muon reconstruction software Moreover, a less demanding track quality factor is required for tracks when hits are missing or are not associated to the track. Prompt muons produced in proton–proton collisions have trajectories that point back to the Interaction Point (IP). Moreover they are synchronous with the collision since all the detector front end electronics are synchronized with the LHC bunch crossing frequency of 40 MHz. In contrast, cos- mic ray muons are “non-pointing” and are asynchronous with the detector clock: they have an additional 25 ns jitter with respect to the clock selected by the trigger. In addition, during commissioning the different trigger detectors were not timed with sufficient precision, leading to variations in timing depending on the region of the detector that origi- nated the trigger. A further difficulty in track reconstruc- tion was due to the lack of precise alignment of the muon detectors during this commissioning phase, as described in Sect. 7. 2.3 Muonboy track reconstruction The strategy of the Muonboy reconstruction algorithm can be summarized in four main steps: The strategy of the Muonboy reconstruction algorithm can be summarized in four main steps: The Gt0-refit consists in varying simultaneously the global time offset (gt0) for each segment reconstructed in a chamber. Then all measured times of hits associated to the segment are translated into drift radii after subtraction of the – identification of Regions Of Activity (ROA) in the muon system with the information provided by the RPC/TGC detectors Eur. Phys. J. C (2010) 70: 875–916 890 trigger logic also demands the track to be pointing towards the IP both in φ and η. In the cosmic ray runs only three of the six thresholds were used in the barrel and were defined as MU0_LOW, MU0_HIGH and MU6. The two thresholds MU0_LOW/HIGH did not select a physical pT range; in fact, the MU0_LOW was triggered only by the time coin- cidence of 3 out of 4 hits without any pointing constraint and the MU0_HIGH was triggered by the coincidence of a MU0_LOW with at least a hit in the corresponding outer plane. The threshold MU6 required not only a time coinci- dence but also an IP-pointing constraint in the φ-projection only. To emulate the timing expected for beam collisions, and to enhance the illumination of the Inner Detector (ID), the cosmic ray trigger was issued mainly by the bottom sec- tors. This was achieved by delaying the top sector trigger by 5 BC (125 ns) preventing it from arriving first at the Central Trigger Processor (CTP) and thus forming the trigger. gt0. The gt0 value that minimizes the sum in quadrature of the weighted residuals (corresponding to the segment recon- struction χ2) is selected. In this fit the MDT uncertainties are set to twice the test- beam drift tube resolution. If the segment fit is not success- ful, a straight line fit is performed assuming a constant 1 mm error. Hits are removed if their distance from the segment is greater than 7σ. In the track fit the MDT errors are en- larged to 2 mm to account for uncertainties in the alignment of chamber stations. 3.2 End-cap level-1 trigger The level-1 TGC trigger system provided three thresholds, named MU0_TGC_HALO, MU0_TGC and MU6_TGC. The trigger was issued by the coincidence between several TGC layers. The logic was based both on timing (BC identifica- tion) and geometry (pointing track). The main difference be- tween the three trigger thresholds is related to the required number of layers and to the degree of pointing to the IP. MU0_TGC_HALO required a 3 out of 4 layer coincidence in the two outermost TGC stations, the so-called Doublet chambers, in both η (bending) and φ (non-bending) pro- jections and a pointing requirement within 20◦. MU0_TGC and MU6_TGC required in addition a 2 out of 3 layer co- incidence in the TGC stations closer to the IP, the so-called Triplet chambers, in the η projection only. The pointing re- quirement of MU0_TGC was of ±10◦degrees while for MU6_TGC was of ±5◦. In beam-collision configuration, the level-1 muon trig- ger selects pointing tracks with six different thresholds in transverse momentum and sends information to the Central- Trigger-Processor (CTP). The six thresholds, three low-pT and three high-pT , do not distinguish between different de- tector regions, barrel or end-cap. For cosmic rays, to help commissioning separately the two regions, it was chosen to assign three thresholds to the barrel and three to the end-cap. 3 Trigger configuration during data taking A more detailed description of the trigger system can be found in [2, 9]. Here only specific issues related to the 2008–2009 cosmic ray data taking are introduced. The muon level-1 trigger is issued by the RPC in the barrel and by the TGC in the end-caps. During cosmic ray data taking most of the statistics were collected using this trigger. Special trigger configurations were adopted with different geometries (e.g. non pointing to the IP) and different timing (e.g. delaying the triggers issued by the upper sectors in order to trigger only in the lower sectors to mimic particles coming from the IP) when commissioning the muon trigger system itself or when selecting cosmic rays for commissioning the other ATLAS sub-systems. In the fall 2008 data taking period, the timing of the low- pT trigger and the data read-out latencies were still under commissioning. This had a large impact on the detector cov- erage. The situation has largely improved for the runs taken in 2009 both in terms of detector coverage and in trigger timing as shown in Sects. 4.3 and 6.2. 4.1 Introduction The data quality assessment consists of several software al- gorithms working at different levels of the data taking. The Detector Control System (DCS) [11] is the first source of information available during the operation of the detector. Here information on the hardware status of the different sub- detectors and on the settings of Low Voltage (LV) and High Voltage (HV) power supplies and on the gas system is avail- able. The DCS also receives information from the Data Ac- quisition (DAQ) [11] as soon as problems during the read- out of a chamber appear. A detailed list of hardware problems found in run 91060 is reported in Table 2. The cosmic ray flux was not suffi- cient for a detailed analysis of single drift tubes for 15 MDT chambers (∼3 K channels). Thus we were able to analyze individually 336 K, out of the working 339 K, drift tubes. To summarize, about 5 K channels, out of 336 K, have shown some problems in run 91,060, corresponding to 1.5%. Most of these channels have been recovered during the 2008–2009 shutdown period. Only a very small fraction of problems, at the level of a few per mill, could not be solved, such as permanently disconnected tubes (broken wires) or chambers with very difficult access. The next stage in the chain of data quality assessment is the on-line monitoring. It receives input from the data acqui- sition system running in a spectator mode. Once the data are decoded, monitoring histograms are filled showing quanti- ties related to the detector operation. Part of the muon data selected by the level-1 trigger Region Of Interest (ROI) are transferred by the level-2 trigger processors to three dedi- cated computing farms (referred to as calibration centers) to monitor and determine the calibration parameters of the MS chambers. The larger event samples available at the cal- ibration centers allow the analysis of single drift tube re- sponses. The goal of the analysis at the calibration centers is to provide drift tube and trigger chambers calibration con- stants and to give general feedback on the detector operation within 24 hours, which is the time needed, at high luminos- ity, to collect enough statistics to calculate new calibration constants. In addition to monitoring in the DAQ framework (on- line monitoring), the data are also processed with the of- fline reconstruction program which produces monitoring histograms. 3.1 Barrel level-1 trigger The barrel trigger detectors are arranged in three stations each having a doublet of RPC layers at increasing distances from the IP. In each sector the first two stations are mechan- ically coupled to the BM MDT while the third is coupled with the BO MDT as shown in Fig. 1. The trigger was timed for high-momentum muons com- ing from the IP. All the delays due to different time-of-flight and cable lengths were properly set and cross-checked using a test pulse system achieving a relative timing within 4 ns. For most of the cosmic run period, only the level-1 trigger generated from the TGC bottom sectors was used. This was chosen to ensure good timing of the trigger with the read-out of the ID, since cosmic muons triggered by the TGC bottom sectors and crossing the ID have a time-of-flight similar to muons produced in collisions. The trigger algorithm is steered by signals on the middle layers, named Pivot plane. When a hit is found on this plane, the low-pT trigger logic searches for hits in the inner layers, named Confirm plane, and requires a coincidence in time of three hits over the four layers in a pre-calculated cone. The width of this cone defines the pT threshold. If hits are also found in a pre-calculated cone of the outermost plane in coincidence with a low-pT trigger, a high-pT trigger is issued. Also in this case the pT threshold is defined by the width of the cone. In addition to the pT requirement, the Eur. Phys. J. C (2010) 70: 875–916 891 4.1 Introduction This ensures that the reconstruction works prop- erly and that the correct conditions data (calibration and alignment constants) are used in the first processing of the data. The off-line monitoring gathers and presents informa- tion on several variables for single drift tubes, e.g. drift time and collected charge distributions, hit occupancy and noise rate. These variables are obtained for individual MDTs or grouped for regions, such as η or φ sectors, barrel or end- cap, side A or C. Variables related to segments or tracks are also monitored. On a longer time scale, using the full reconstructed AT- LAS event information, the off-line data monitoring pro- vides the final information on the data quality. At each step a flag summarizing the data quality at that level is stored in a database. 4 Data quality assessment of hits per tube for each MDT is represented in a η–φ plot where the higher cosmic illumination on the top and bot- tom sectors (3–7, 11–15) compared to the vertical sectors (16–2 and 8–10) is clearly seen as well as the larger illumi- nation on the A side of the detector where the larger shaft is present. The five chambers not included in the data acquisi- tion are marked as dark gray boxes. Two more chambers are visible with very low statistics due to problems with the HV supplies. For 32 MDT chambers one of the two multi-layers was disconnected from HV. 4.2 MDT chambers Commissioning of the RPC detectors progressed continu- ously and substantial improvements were made during the 2008–2009 shut-down. As an example Fig. 3 shows a two- dimensional distribution of RPC strips requiring a 3 out of 4 majority coincidence for the low-pT trigger demonstrat- ing that the trigger coverage in Spring 2009 was at the 95% level. In the fall 2008 period (e.g. Run 91060) only five out of 1110 MDT chambers were not included in the data taking. Of these five chambers, two were not yet connected to ser- vices and three had problems with the gas system. Due to the cosmic ray illumination and the trigger coverage not all chambers had sufficient event samples to determine the performance of single drift tubes. The studies reported here were done at different levels of detail, from chamber infor- mation down to single drift tube information when the event samples were sufficient. The data survey searched for prob- lems of individual read-out channels as well as of clusters corresponding to hardware related groups of tubes. A screen shot of one of the online monitoring applications used for the MDT chambers is shown in Fig. 2. Here the average number Studies of the trigger performance were made using the data of run 91,060 after implementation of the trigger roads [10]. For the low-pT trigger the four RPC layers in the Middle station are involved, both in η and φ projections. Tracks were accepted by the trigger if any strip of the pivot plane was in coincidence with a group of strips of the con- firm plane aligned with the IP, realizing a majority combina- tion of 3 out of 4 RPC layers. Figure 4(A) shows the spatial Eur. Phys. J. C (2010) 70: 875–916 892 Fig. 2 Screen shot of a monitoring application displaying the MDT hit occupancy for all chambers. Each chamber is represented by a small box. The color of the box is related to the average number of raw hits per tube. The boxes are arranged in an η–φ grid: a column represents an η slice, perpendicular to the beam axis; a row represents one of the sixteen φ sectors. 4.4 End-cap trigger chambers: TGC In the end-caps the muon trigger is provided by the TGC chambers installed in three layers that surround the MDT Middle chambers. All together they form the so-called Big Wheels (BW), one in each end-cap. In addition, TGC cham- bers are also installed close to the EI chambers in the Small Wheels (SW), but these are only used to measure the muon φ coordinate. In Fall 2008 all the BW TGC sectors were read- out. Given the installation schedule for the ATLAS detec- tors, the Inner TGC station were the last chambers installed and they were not fully operational during 2008 runs. For this reason they are not discussed in the following. Fig. 3 RPC low-pT trigger coverage in η–φ for Run 113,860 (Spring 2009). Each η and φ strip producing a low-pT trigger corresponds to an entry in the plot. The coverage in Spring 2009 was about 95% Fig. 4 (A): RPC spatial correlation between the pivot strip number and the confirm strip number in the φ projection for a programmed trigger road. 128 strips correspond to a RPC plane 3.8 m long. (B): Distribu- tion of strip noise rates per unit area measured with a random trigger for 310 K RPC strips. The larger noise present on some strips is prob- ably due to local weaknesses of grounding connections Two types of trigger configuration were adopted in Fall 2008. One was optimized to study the end-cap muon de- tectors with cosmic rays. In this configuration all TGC BW sectors were used in the trigger. The other setting was opti- mized to provide the trigger for the ID tracking detectors and was used for timing the ID. In order to mimic muons coming from the IP, only the five bottom sectors were used to trigger. The typical detector coverage in these two trigger configura- tions is shown in Fig. 5 by plotting the coincidence positions in the x–y plane for wire and strip hits for run 91,060 (A) and run 91,803 (B). Only about 0.8% of chambers were not operational due to HV or gas problems. Since for the trigger a majority logic is required these inactive chambers do not produce any dead regions in the trigger acceptance. The HV and front-end threshold setting, the gate widths for wires and strips, and the trigger sectors are listed in Ta- ble 3 for these two runs. 4.2 MDT chambers Within each sector chambers of the Inner, Middle, Outer ring are displayed separately Table 2 List of MDT channels with problems in run 91,060 Number of channels analyzed with sufficient event samples 336,144 Fraction Channels not included in the read out 936 0 28% Fig. 2 Screen shot of a monitoring application displaying the MDT hit occupancy for all chambers. Each chamber is represented by a small box. The color of the box is related to the average number of raw hits per tube. The boxes are arranged in an η–φ grid: a column represents an η slice, perpendicular to the beam axis; a row represents one of the sixteen φ sectors. Within each sector chambers of the Inner, Middle, Outer ring are displayed separately Fig. 2 Screen shot of a monitoring application displaying the MDT hit occupancy for all chambers. Each chamber is represented by a small box. The color of the box is related to the average number of raw hits per tube. The boxes are arranged in an η–φ grid: a column represents an η slice, perpendicular to the beam axis; a row represents one of the sixteen φ sectors. Within each sector chambers of the Inner, Middle, Outer ring are displayed separately MDT channels un 91,060 Number of channels analyzed with sufficient event samples 336,144 Fraction Channels not included in the read-out 936 0.28% Channels with read-out or initialization problems 744 0.22% Channels with HV or gas problems 2942 0.88% Permanently dead channels (broken wires) 323 0.10% Total problematic channels 4945 1.47% Table 2 List of MDT channels with problems in run 91,060 system noise rate. About 310 K strips were analyzed over a total of 350 K working strips. Figure 4(B) shows the dis- tribution of single channel noise rate, normalized to an area of 1 cm2. For each strip, the noise rate is calculated as the number of hits divided by the number of random triggers and the width of the read-out gate of 200 ns, and is normal- correlation between φ strips in the pivot planes and φ strips in the confirm planes. The correlation line is slightly rotated with respect to the diagonal due to the different distance of the confirm and pivot planes with respect to the IP. A random trigger was used to measure the counting rate for each read-out strip. This is a measurement of the RPC Eur. Phys. 4.2 MDT chambers J. C (2010) 70: 875–916 893 Fig. 3 RPC low-pT trigger coverage in η–φ for Run 113,860 (Spring 2009). Each η and φ strip producing a low-pT trigger corresponds to an entry in the plot. The coverage in Spring 2009 was about 95% The fraction of dead channels, considering only the part of the detector included in the read-out in the Fall 2008 runs, was 1.5%, mainly due to problems in the front-end electron- ics. 4.4 End-cap trigger chambers: TGC Three BC crossing, previous, current and next are readout cording to an Interval Of Validity (IOV) mechanism, to b d i th ffli t ti Th IOV d t i f Fig. 6 (A): TGC front-end and (B): sector logic buffers for BC iden- tification. Three BC crossing, previous, current and next are readout Fig. 6 (A): TGC front-end and (B): sector logic buffers for BC iden tification. Three BC crossing, previous, current and next are readout Fig. 5 Map of coincidences of wire and strip hits in the x–y plane. (A): The five bottom sectors (sectors 8–12, 195◦< φ < 345◦) used for timing the ID tracking detectors in run 91,060. (B): With all sectors participating in the trigger during run 91,803 Table 3 TGC sectors participating in the trigger, high voltage setting, threshold and gate width Run Trigger sector HV Threshold Gate widths for wire/strip 91,060 8 to 12 2800 V 100 mV 35/45 ns 91,803 1 to 12 2650 V 80 mV 35/45 ns Table 3 TGC sectors participating in the trigger, high voltage setting, threshold and gate width Fig. 6 (A): TGC front-end and (B): sector logic buffers for BC iden- tification. Three BC crossing, previous, current and next are readout cording to an Interval Of Validity (IOV) mechanism, to be used in the offline reconstruction. The IOV determines for which group of runs the calibration constants are valid. The gas mixture composition varied during the data taking pe- riod since the water injection part of the gas system was un- der commissioning resulting in a not constant admixture of water vapor, as can be seen in Fig. 9. Nonetheless the cali- bration procedure based on the IOV mechanism was able to provide good calibration constants for all the running period. 4.4 End-cap trigger chambers: TGC For each trigger issued by the CTP, the TGC Read Out Driver (ROD) sends to the DAQ system the data correspond- ing to three Bunch Crossings (Previous, Current and Next BC) contained in two separate buffers. Of the two buffers, one is located in the front-end board where the wires and strips providing the low-pT coincidence are separately rec- orded. In the second buffer, located in the Sector Logic Board in the service counting room, the coincidence of the wire and strip signals is done. Each buffer has a program- mable identifier that has to be adjusted in order to read out the correct (Current) BC data. Figure 6 shows the read- out timing for the front-end and the sector logic buffers for level-1 triggers issued by the TGC. About 98.6% of data in the front-end buffer, and 99.8% of data in the sector logic buffer are read out with the correct timing. The small popu- lation in the previous or next BC is due to cosmic ray show- ers. Fig. 4 (A): RPC spatial correlation between the pivot strip number and the confirm strip number in the φ projection for a programmed trigger road. 128 strips correspond to a RPC plane 3.8 m long. (B): Distribu- tion of strip noise rates per unit area measured with a random trigger for 310 K RPC strips. The larger noise present on some strips is prob- ably due to local weaknesses of grounding connections ized to the area of the strip (typically 550 cm2 for a BM eta strips and 900 cm2 for a BO eta strips). Only a few hundred strips showed a counting rate above 10 Hz/cm2 which is the background rate expected when the LHC will run at high- luminosity. The average noise rate of the RPC was stable during the different running periods. Eur. Phys. J. C (2010) 70: 875–916 894 Fig. 5 Map of coincidences of wire and strip hits in the x–y plane. (A): The five bottom sectors (sectors 8–12, 195◦< φ < 345◦) used for timing the ID tracking detectors in run 91,060. (B): With all sectors participating in the trigger during run 91,803 Table 3 TGC sectors participating in the trigger, high voltage setting, threshold and gate width Run Trigger sector HV Threshold Gate widths for wire/strip Fig. 6 (A): TGC front-end and (B): sector logic buffers for BC ide tification. 5.1 Calibration method The t0 offset depends on many fixed delays like cable lengths, front-end electronics response, Level-1 trigger la- tency, time of flight from the IP and has to be determined for each drift tube. The offset is obtained by fitting a Fermi function to the leading edge of the drift time distribution as shown in Fig. 7(A). The precision expected in LHC colli- sion data is better than 1 ns with a dataset of about 10 K muons crossing the drift tube. This uncertainty does not sig- nificantly degrade the position resolution of the MDT tubes which corresponds to a time span of about 5 ns. In Fig. 7(B) also the typical spectrum of ADC for all tubes in a cham- The MDTs require a calibration procedure [12] to precisely convert the measured drift time into a drift distances from the anode wire (drift radius) that is subsequently used in pattern recognition and track fitting. The calibration of the MDT chambers is performed in three steps. In the first step the time offset with respect to the trigger signal, t0, for each tube or group of tubes is determined; in the second step the drift-time to space relation, r(t) function, is computed; in the third step the spatial resolution is determined. The calibration constants are loaded in the Conditions Data Base (known as ‘COOL’) [13] and then retrieved, ac- Eur. Phys. J. C (2010) 70: 875–916 895 ber is reported. Charge information in each tube is obtained using a Wilkinson ADC [14]. As the MDT chambers are op- erated at different temperatures depending on their positions in the MS, the r(t) functions differ depending on location and are determined separately. In addition, variations of the toroidal magnetic field along the drift tubes produce differ- ent Lorentz angles, thus different r(t) functions. An initial rough estimate of the r(t) function is obtained with an ac- curacy of 0.5 mm by integrating the drift-time distribution. This is correct under the approximation of a uniform dn/dr distribution, where n is the number of hits at a drift radius r residuals of track segment fits with an iterative procedure. This minimization procedure, called auto-calibration, takes into account the dependence of the parameters of the fit- ted segments on the applied corrections δr(t) and is mainly based on the geometrical constraints from the precise knowl- edge of the wire positions. 5.1 Calibration method Figure 8 shows a typical resid- ual distribution of a chamber, as a function of the distance of the track segment from the anode wire, after the auto- calibration. In cosmic ray events additional sources of time jitter, beyond the intrinsic resolution, spoil the MDT measure- ment. The first cause of time jitter is due to cosmic ray muons crossing the tubes with an arbitrary phase with re- dn dt = dn dr dr dt = Nhits rmax dr dt ⇒ r(t) = rmax Nhits Z t 0 dn dt0 dt0. dn dt = dn dr dr dt = Nhits rmax dr dt ⇒ r(t) = rmax Nhits Z t 0 dn dt0 dt0. Fig. 8 (A): Residuals as a function of the track segment distance fro the wire after the r(t) auto-calibration and RPC-time corrections. T points correspond to the mean value of the distribution of residuals a the error bars to its RMS value. (B): Residuals as a function of the tra segment distance from the wire after the r(t) auto-calibration usi the Gt0-refit method. The points correspond to the mean value of t distribution of residuals and the error bars to its RMS value. Residu systematics at the level of 50 μm are present using this correction Nhits is the total number of hits in the time spectrum and rmax is the maximum drift radius (14.4 mm). In cosmic rays this approximation is only good at the level of a few hundred μm mainly because of the production of δ-ray elec- trons along the track. An r(t) relation with a higher ac- curacy, of about 20 μm, is obtained from this initial esti- mate by applying corrections, δr(t), which minimize the Fig. 7 (A): typical drift time spectrum in cosmic ray events for an MDT chamber. The position of the inflection point of the leading edge of the spectrum, t0, is determined by fitting a Fermi function (shown in red) to the beginning of the spectrum. (B): Typical spectrum of ADC for all tubes in a chamber. Hits below 50 ADC counts are identified as electronic noise Fig. 8 (A): Residuals as a function of the track segment distance from the wire after the r(t) auto-calibration and RPC-time corrections. The points correspond to the mean value of the distribution of residuals and the error bars to its RMS value. 5.2 End-cap chambers calibration with monitoring chamber spect to the front-end electronics clock [15]. This implies a time jitter corresponding to a 25 ns uniform distribu- tion. The second cause is related to the spread of the trig- ger time for triggers generated in different parts of the de- tector (up to about 100 ns due to the initial stage of the trigger timing). Two different methods have been alterna- tively used to reduce the impact of these effects: the RPC- time correction and the MDT Gt0-refit. The achieved per- formance with both methods are discussed in Sect. 6. In the following a brief description of the former method is given. For the end-cap MDTsystem, due to the limited number of cosmic ray events, a different method to determine the r(t) relation was used. A small MDT chamber installed on the surface of the ATLAS underground hall was set up [16] to monitor continuously the MDT gas composition. One multi- layer is connected to the supply line of the gas recycling system while the other is connected to the return line. This chamber benefits from a very large cosmic ray rate and can therefore determine the r(t) function with high precision in short time intervals. Cosmic ray muons are triggered by scintillator counters mounted on the monitoring chamber. The trigger time is measured and subtracted event-by-event from the tube drift times, in this way the jitter related to the asynchronous front-end clock is automatically removed. The RPC-time correction uses the trigger time measured by the RPC chambers on an event by event basis. This time correction was applied only to the MDT chambers of the BM stations since these chambers are close to the two RPC stations used to issue the trigger and so no corrections due to time of flight and, more importantly, no corrections due to the spread in timing of the trigger signals issued by differ- ent parts of the detector are needed. This method cannot be applied to the end-cap region since the TGC do not provide a measurement of the trigger time but rather they select the appropriate BC. Data from the monitoring chamber are used to derive a r(t) function every 6 hours to monitor the gas drift proper- ties. Figure 9 shows the variation of the maximum drift time (the drift time of muons crossing the drift tube close to its edge) over the period September–October 2008. 5.1 Calibration method (B): Residuals as a function of the track segment distance from the wire after the r(t) auto-calibration using the Gt0-refit method. The points correspond to the mean value of the distribution of residuals and the error bars to its RMS value. Residual systematics at the level of 50 μm are present using this correction Fig. 7 (A): typical drift time spectrum in cosmic ray events for an MDT chamber. The position of the inflection point of the leading edge of the spectrum, t0, is determined by fitting a Fermi function (shown in red) to the beginning of the spectrum. (B): Typical spectrum of ADC for all tubes in a chamber. Hits below 50 ADC counts are identified as electronic noise Eur. Phys. J. C (2010) 70: 875–916 896 Fig. 9 Maximum drift time measured by the gas monitor chamber versus time during September–October 2008. The red points refers to the return line and the blue points to the supply line (green and light blue points are the time average of the supply and return line measurements). The large variation seen between middle of September and 10th of October is due to the change of the quantity of water vapor added to the standard mixture 6.1 MDT 6.1 MDT Eur. Phys. J. C (2010) 70: 875–916 Fig. 10 (A) Distribution of the RMS and (B) of the mean values of the residuals from the fit to track segments in 373 end-cap chambers using the r(t) function derived from the gas monitoring chamber. The black lines represent Gaussian fits to the distributions Figure 10 shows the distribution of the mean and RMS value of the residuals from the fit to track segments in all end-cap chambers (run 91,060). A Gaussian fit is su- perimposed. The r(t) function derived from the gas mon- itor chamber with temperature corrections provides an ac- ceptable calibration for all the MDT chambers of the end- cap: the average standard deviation of the residuals is about 100 μm. knowledge of t0 for each tube is essential for high quality segment and track reconstruction. As explained in Sect. 5, for cosmic rays some additional time jitter is present and must be accounted for. In order to improve the quality of track reconstruction the Gt0-refit time correction has been used. The performance of the Gt0-refit algorithm has been investigated in the past, both using simulated data and using data taken with a BIL (Barrel Inner Large) chamber in a cosmic ray test stand under con- trolled trigger conditions [20]. The achieved Gt0 resolution ranged between 2 and 4 ns depending on the chamber geom- etry (8 layer chambers have better resolution than 6 layer chambers) and hit topology. In particular the Gt0-refit algo- rithm cannot work if all the hits are on the same side of the wires, typically for tracks at 30◦with respect to the cham- ber plane. The selection of good quality segments requires a minimum of five MDT hits and segments with all hits on the same side of the wires are removed. 5.2 End-cap chambers calibration with monitoring chamber Two r(t) functions were used to cover the Fall 2008 run period, for each period the r(t) function for each chamber of the MS was corrected to account for the temperature difference us- ing the data measured by the sensors mounted on any partic- ular chamber. The temperature corrections to the r(t) func- tion were derived from the Garfield–MagBoltz simulation program [17–19]. The output of the simulation was validated by several measurements with a muon beam [5]. In the end- cap region, the temperature varies by about 4◦C from top to bottom of the MS, resulting in a variation of the maximum drift time of about 10 ns. On the other hand the temperature of the cavern was remarkably stable in time. With this correction the time jitter due to the two effects mentioned above is reduced from ∼100 ns to few ns (see Sect. 6). The distribution of the residuals obtained after cal- ibration using the RPC-time correction method is presented in Fig. 8(A). The precision of the auto-calibration is better than ∼20 μm using this correction. The Gt0-refit has also been used to improve the single tube resolution, as discussed in Sect. 6. Also the precision of the auto-calibration is much improved with respect to the uncorrected situation. As shown in Fig. 8 a precision of ∼50 μm is obtained for the residuals of the segment fit after auto-calibration with small residual systematics on the auto-calibration. Fig. 9 Maximum drift time measured by the gas monitor chamber versus time during September–October 2008. The red points refers to the return line and the blue points to the supply line (green and light blue points are the time average of the supply and return line measurements). The large variation seen between middle of September and 10th of October is due to the change of the quantity of water vapor added to the standard mixture 897 Eur. Phys. J. C (2010) 70: 875–916 6.1.2 Drift tube spatial resolution Fig. 11 Difference between the gt0 obtained with the Gt0-refit method and with RPC-time correction. The width of the distribution is a convo- lution of the uncertainties of the RPC-time correction and the Gt0-refit method The MDT single tube resolution, as a function of drift dis- tance, was studied using different time corrections. The ex- traction of the resolution function is based on an iterative method. At the first iteration an approximate input resolu- tion function is assumed. Only segments with a minimum of six hits are considered. These segments are fitted again after removing one hit at the time. Subsequently, the width of the distribution of the residuals for the excluded hit, j, is computed as a function of the drift distance from the wire, σfit,j(r). The errors of the straight line fit (depend- ing on the assumed tube resolution) are then propagated to the excluded hit. The resolution σj(r) is then computed by quadratically subtracting from the standard deviation of the residuals the fit extrapolation error, σextr,j(r): Fig. 12 Drift tube resolution as a function of the radius. The green shadowed (RPC correction method) and the blue hatched (Gt0-refit method) bands represent the resolution function measured with cos- mic rays with the two different methods described in the text. The solid line represents the resolution measured with a high momentum muon beam [5] σj(r) = q σ 2 fit,j(r) −σ 2 extr,j(r) Fig. 12 Drift tube resolution as a function of the radius. The green shadowed (RPC correction method) and the blue hatched (Gt0-refit method) bands represent the resolution function measured with cos- mic rays with the two different methods described in the text. The solid line represents the resolution measured with a high momentum muon beam [5] The procedure is iterated using the new resolution function until the input and output resolutions agree within statistical uncertainties; a small number of iterations (two to four) is usually needed. In Fig. 12 the tube resolution obtained for a BML cham- ber is shown as the green band. The width of the band ac- counts for the systematic uncertainty of the method. Also shown (solid line) is the resolution function obtained for an MDT chamber at a high energy muon test beam [5] with well controlled trigger timing. This can be considered as ref- erence for the single-tube resolution. 6.1.1 MDT drift time distribution The behavior of the drift time distributions of individual tubes is an important quality criterion for the MDT perfor- mance. The minimum and maximum drift times, t0 and tmax, respectively, correspond to particles passing very close to the wire and close to the tube walls, and their stability in- dicates the stability of the calibration. The number of hits recorded in a small time window before the rising edge of the drift time distribution t0 can be used to estimate the rate of noise due to hits not correlated with the trigger. A precise In addition to the Gt0-refit also the RPC-time correction method was used for the MDT chambers in the middle bar- rel station (BM) which are located closely to the RPC trigger chambers. The time measured by these RPC can be used to correct for a global time offset. An example of the effective- ness of the method is given in Fig. 7 where the drift time distribution for a BML chamber is shown after RPC-time Eur. Phys. J. C (2010) 70: 875–916 898 Fig. 11 Difference between the gt0 obtained with the Gt0-refit method and with RPC-time correction. The width of the distribution is a convo- lution of the uncertainties of the RPC-time correction and the Gt0-refit method corrections. The steepness of the rising edge, measured as one of the parameters of the Fermi distribution, is improved, passing from 22 ns without correction, to 3 ns with RPC time corrections, a value in agreement with results from muon beam tests [5]. The precision of the RPC-time correction is about 2 ns as explained in Sect. 6.2. This also includes the contribution of the signal propagation time in the RPC strips. The distribution of the difference between the fitted Gt0 and the RPC timing correction per segment is shown in Fig. 11 for a BML chamber. The standard deviation of about 4 ns is consistent with an uncertainty of 2 ns from the RPC- time correction added to an uncertainty of 3 ns introduced by the Gt0-refit method. Tails up to 30 ns are present in the distribution due to bad hit topologies and background hits. 6.1.2 Drift tube spatial resolution The resolution func- tion measured with cosmic rays is consistent with a time degradation of the reference resolution of about 3 ns. This is in reasonable agreement with the 2 ns time resolution quoted for the RPC-time correction in addition to a small contribu- tion from multiple scattering and individual tube differences in t0. to that presented above with the convergence of the method driven by the estimate of the residual pulls. The resolution function is shown as the blue hatched band in Fig. 12. The measured resolution is consistent with the test beam mea- sured resolution provided that an additional time uncertainty of about 2–3 ns is taken into account. 6.1.3 Drift tube noise The level of noise can be measured in each drift tube by looking at the drift time distribution in a given interval be- fore t0 where only hits uncorrelated with the trigger are present. The noise rate is obtained by dividing the number of The single hit spatial resolution was determined also by applying the Gt0-refit method to track segments recon- structed in the same chamber. The procedure was similar Eur. Phys. J. C (2010) 70: 875–916 899 hits normalized to the number of triggers by the chosen time interval. The charge of drift tube signals, at nominal running conditions, is well above the ADC pedestal corresponding to about 50 counts, see Fig. 7. In the reconstruction algorithms only hits with charge above this value are considered. The distribution of noise rate with and without the ADC charge cut is shown in Fig. 13 for all MDT drift tubes. The average noise rate is only 60 Hz without the ADC cut and 13 Hz with ADC cut, the former figure corresponds to an average tube occupancy of less than 10−4. hit is present but is not associated to the segment because its residual is larger than the association cut. The ineffi- ciency of type (i), referred to as hardware inefficiency, is very small, mostly occurring at large drift distances, near the tube wall, where the short track length results in fewer primary electrons or due to the track passing through the dead material between adjacent tubes. The inefficiency of type (ii), referred to as tracking inefficiency, is dominated by δ-electrons, produced by the muon itself, which can mask the muon hit if the δ-electron has a smaller drift time than the muon. Tube noise can be an additional source of this type of inefficiency. Fig. 14 Distribution of the hit residuals for tubes excluded in the segment fit, as a function of the distance of the track from the wire. Small residuals are associated with efficient hits. The triangular region is populated by early hits produced by δ-electrons. Missing hits, as explained in the text, are assigned a residual value of 15.5 mm. The histogram on the right represent the projection on the residual axis of the plot on the left pane 6.1.4 Drift tube efficiency Figure 14 shows the distribution of the signed residuals for hits in the tube of one barrel chamber as a function of the distance of the segment from the wire. A large population at small values of the residual, compatible with the spatial resolution, is visible. Large positive residuals are associated with early hits mainly due to δ-electrons. If a hit is not found The single tube efficiency was studied by reconstructing segments in a chamber using all tubes except the one un- der observation i.e. excluding one MDT layer at the time in segment reconstruction. Two different types of inefficien- cies can be defined: (i) absence of a hit in the tube; (ii) a The tail of the distribution is due to very few noisy tubes that are suffering from pick up of high frequencies through the HV cables or interferences due to the digital clock present in the front end electronics Fig. 13 Distribution of the drift tube noise rate with (shadowed his- togram, bottom statistical box) and without (empty histogram, top statistical box) the ADC cut described in the text. In the right plot the logarithmic scale allows observation of the very few noisy tubes. The tail of the distribution is due to very few noisy tubes that are suffering from pick up of high frequencies through the HV cables or interferences due to the digital clock present in the front end electronics Fig. 13 Distribution of the drift tube noise rate with (shadowed his- togram, bottom statistical box) and without (empty histogram, top statistical box) the ADC cut described in the text. In the right plot the logarithmic scale allows observation of the very few noisy tubes. e hit d in on of om re ts. n the l esent ual pane 900 Eur. Phys. J. C (2010) 70: 875–916 disconnected wires and were not considered in the average value. in the tube traversed by the muon (thus a residual cannot be computed) a value of 15.5 mm is assigned, larger than the tube radius of 15 mm. The population of missing hits is visible at the top of Fig. 14 and it peaks close to the tube wall. The results of a study on all the barrel chambers with enough cosmic ray illumination to allow the determination of the single tube efficiency is presented in Fig. 17. 6.1.4 Drift tube efficiency The dis- tribution of the tracking efficiency for a 5σ hit association cut is shown for about 81 K drift tubes. In addition to about 0.2% of dead channels, less than 1% of tubes have tracking efficiency below 90%, mainly due to calibration constants determined with insufficient precision. The tracking efficiency is defined as the fraction of hits with a distance from the segment smaller than n times its error, this error being a convolution of the tube resolution and the track extrapolation uncertainty. Figure 15 shows the hardware efficiency and the tracking efficiency as a function of the drift radius for n = 3, 5, and 10. The tracking effi- ciency decreases with increasing radius, mainly due to the contribution of δ-electrons. The average tube hardware ef- ficiency is 99.8%; the tracking efficiency is 97.2%, 96.3% and 94.6% for n equals to 10, 5 and 3 respectively. 6.2 RPC In addition to providing the barrel muon trigger, the RPC system is also used to identify the BC of the interaction that produced the muon. This requires a time resolution much better than the bunch crossing period of 25 ns. For this, the time of the strips that form the trigger coincidence is en- coded in the front-end with a 3-bit interpolator providing an accuracy of 3.125 ns [10]. The distribution of the time difference between the two layers of a pivot plane in the φ projection was used to determine the RPC time resolution. With this method there is no need to correct for the muon time of flight and the signal propagation along the read-out strips. The RMS width of the distribution shown in Fig. 18 is 2.5 ns. From this a time resolution of 1.8 ns is derived for the two RPC layers forming the coincidence. For this measure- ment only strips associated to a reconstructed muon track and belonging to events with one and only one RPC trigger were considered. Figure 16 shows the average value of the tracking effi- ciency for each tube of a BML chamber for n = 5. The av- erage value is about 96%. An efficiency consistent with zero was obtained for two tubes as can be seen in the expanded view on the right plot. These were recognized as tubes with Fig. 15 Tube efficiency as a function of the drift distance averaged over all tubes of a BML chamber. Shown are the hardware efficiency and the tracking efficiency for hit residuals smaller than 3, 5, and 10 times the standard deviation of the distribution Two other important RPC quantities related to the detec- tor performance are the efficiency and the spatial resolution. In order to determine the RPC efficiency two main issues have to be taken into account. The first one is due to the fact that the RPCs are actually providing the muon trigger thus resulting in a trigger bias on the efficiency calculation. The second one is caused by the fact that the RPC hits are Fig. 15 Tube efficiency as a function of the drift distance averaged over all tubes of a BML chamber. Shown are the hardware efficiency and the tracking efficiency for hit residuals smaller than 3, 5, and 10 times the standard deviation of the distribution acking ained in mber. 6.2 RPC ows an egion he wire nd Fig. 16 Single tube tracking efficiencies with a 5σ association cut, as explained in the text, for a BML chamber. The plot on the right shows an expanded view in the region where two tubes with the wire disconnected were found Eur. Phys. J. C (2010) 70: 875–916 901 Fig. 19 Distribution of the average efficiency for RPC of the Middle stations for run 91,060. The two distributions refer to two different trig- gers: RPC trigger (full line, 91.33% peak efficiency) and calorimeter trigger (dashed line, 92.0% peak efficiency). Both distributions are nor- malized to unit area. The measured efficiency is lower than expected mainly because the read-out timing was still not optimal Fig. 17 Distribution of the tracking efficiency, with a 5σ hit associa- tion cut, for ∼81 K drift tubes in the barrel MDT. About 0.2% of tubes were not working and have efficiency compatible with zero Fig. 19 Distribution of the average efficiency for RPC of the Middle stations for run 91,060. The two distributions refer to two different trig- gers: RPC trigger (full line, 91.33% peak efficiency) and calorimeter trigger (dashed line, 92.0% peak efficiency). Both distributions are nor- malized to unit area. The measured efficiency is lower than expected mainly because the read-out timing was still not optimal Fig. 17 Distribution of the tracking efficiency, with a 5σ hit associa- tion cut, for ∼81 K drift tubes in the barrel MDT. About 0.2% of tubes were not working and have efficiency compatible with zero Fig. 17 Distribution of the tracking efficiency, with a 5σ hit associ tion cut, for ∼81 K drift tubes in the barrel MDT. About 0.2% of tub were not working and have efficiency compatible with zero Fig. 19 Distribution of the average efficiency for RPC of the Middle stations for run 91,060. The two distributions refer to two different trig- gers: RPC trigger (full line, 91.33% peak efficiency) and calorimeter trigger (dashed line, 92.0% peak efficiency). Both distributions are nor- malized to unit area. The measured efficiency is lower than expected mainly because the read-out timing was still not optimal Fig. 17 Distribution of the tracking efficiency, with a 5σ hit associa- tion cut, for ∼81 K drift tubes in the barrel MDT. About 0.2% of tubes were not working and have efficiency compatible with zero Fig. 6.2 RPC 18 Distribution of the time difference between the two RPC lay- ers of a pivot plane in the φ projection. The binning of the histogram corresponds to the strip read-out time encoding of 1/8 of BC tribution is peaked at an efficiency of 91.3%. To check the remaining impact of the trigger bias on the efficiency mea- surement, the same analysis was repeated with a sample of cosmic rays selected with a calorimeter trigger (Level-1Calo trigger) independently of the RPC trigger response. The re- sult for the efficiency is superimposed in Fig. 19: a good agreement between the two distributions is observed. The spatial resolution is related to the clusters size, that is the number of strips associated to a muon track. A muon crossing the detector near the center of a readout strip, will in general produce a cluster of size one, while clusters of size two are only observed when muons hit a narrow region at the boundary between two strips. The actual sizes of the re- gions corresponding to clusters of size one and two depends on the detector operating parameters, but it is in general true that the latter is smaller than the former. This implies that the spatial resolution must be smaller when measured on a subset of data with only clusters of size two. The spatial res- olutions of η strips was determined selecting muon tracks reconstructed in the MDT as explained above. For each RPC read out plane, the distribution of the distance from the ex- trapolated track was obtained separately for clusters of size one and two and then was fitted with a Gaussian. The RMS widths of the fit were divided by the strip pitch (ranging from 27 to 32 mm depending on the chamber type) to allow for comparison between different RPC and are shown in Fig. 20. This technique has been used only for the η panels since the MDT are measuring in the Z–Y plane. On average, clusters of size two give a spatial resolution about half as for clusters of size one, which is below 10 mm as expected. Fig. 18 Distribution of the time difference between the two RPC lay- ers of a pivot plane in the φ projection. 6.2 RPC The binning of the histogram corresponds to the strip read-out time encoding of 1/8 of BC also used in the track reconstruction; in particular, they mea- sure the coordinate in the non-bending, φ projection. The second effect has negligible contribution if the efficiency is measured for the η strips, since in this projection the track reconstruction is driven by the MDT. For the efficiency mea- surement, MDT tracks were extrapolated to the RPC plane and the layer was counted as efficient if at least one η hit was found with a distance of less than 7 cm from the ex- trapolation. The effect of the trigger bias has been removed from the efficiency measurement of an RPC plane by se- lecting all the events in which the other three planes (in the case of a Middle Station) were producing hits, since the trig- ger requirement is a 3 over 4 planes majority. The distribu- tion of the efficiency, averaged over each layer, for the RPC chambers in the Middle stations is shown in Fig. 19, the dis- also used in the track reconstruction; in particular, they mea- sure the coordinate in the non-bending, φ projection. The second effect has negligible contribution if the efficiency is measured for the η strips, since in this projection the track reconstruction is driven by the MDT. For the efficiency mea- surement, MDT tracks were extrapolated to the RPC plane and the layer was counted as efficient if at least one η hit was found with a distance of less than 7 cm from the ex- trapolation. The effect of the trigger bias has been removed from the efficiency measurement of an RPC plane by se- lecting all the events in which the other three planes (in the case of a Middle Station) were producing hits, since the trig- ger requirement is a 3 over 4 planes majority. The distribu- tion of the efficiency, averaged over each layer, for the RPC chambers in the Middle stations is shown in Fig. 19, the dis- 6.3 TGC The basic structure of the TGC chambers and their assembly in the MS end-cap wheels is presented elsewhere [2]. Inac- tive regions due to the gas-gap frame and the wire supports 902 Eur. Phys. J. C (2010) 70: 875–916 account for a loss of active area varying from 3% to 6% de- pending on the chamber type. In order to optimize the trigger efficiency these inactive regions are staggered with respect to the trajectory of high momentum muons produced at the IP. In the active area the TGC wires are expected to have an efficiency of more than 98%. For the cosmic ray run 91,060 the trigger logic required a coincidence of 3 out of 4 layers in the doublet chambers (referred to as TGC2 and TGC3 as in Fig. 1). In evaluating the detector efficiency one has to take into account the trigger bias and the fact that cosmic rays are non-pointing to the IP, asynchronous, and do not only consist of single muons but also of extended showers. account for a loss of active area varying from 3% to 6% de- pending on the chamber type. In order to optimize the trigger efficiency these inactive regions are staggered with respect to the trajectory of high momentum muons produced at the IP. In the active area the TGC wires are expected to have an efficiency of more than 98%. For the cosmic ray run 91,060 the trigger logic required a coincidence of 3 out of 4 layers in the doublet chambers (referred to as TGC2 and TGC3 as in Fig. 1). In evaluating the detector efficiency one has to take into account the trigger bias and the fact that cosmic rays are non-pointing to the IP, asynchronous, and do not only consist of single muons but also of extended showers. A similar procedure is used for the triplet chambers (TGC1). When evaluating, the efficiency of a layer, it is re- quired (i) that the other two layers satisfy the 2 out of 3 trig- ger coincidence and (ii) that the line joining the two hits (track) crosses the layer in its active area. In both cases, the layer under test is considered efficient if there is at least one hit associated to any of the previous, current or next BC. 6.3 TGC Figure 21 on the left shows an efficiency map in the wire-strip (η–φ) plane, and on the right its η pro- jection, i.e. the strip efficiency. Some inactive regions are clearly visible: the bands in Fig. 21—Left indicate the loca- tion of the wire supports. The overall efficiency, including the inactive regions, is evaluated for a fraction of TGC layers (about 40% of TGC doublet layers) by requiring that a muon track crosses the layer under test at least 10 cm away from its edge. The muon track is defined using MDT hits combined with TGC hits in the layers that are not under evaluation. Figure 22 shows the distribution of the wire efficiency for different values of high voltage setting: 2650, 2750, 2800 and 2850 V. The average value of the efficiency, at the nominal voltage of 2800 V, is 92% consistent with the local efficiency measured as ex- plained above and the contribution from inactive-regions. To evaluate the efficiency of a layer in the doublet cham- bers, it is required that there is one and only one hit in each of the other three layers and that these three hits are asso- ciated to the current BC. This is intended to remove high multiplicity events (showers) and out-of-time tracks. As a result of this selection, the 3 out of 4 trigger condition is satisfied independently of the presence of a hit in the layer under evaluation. The efficiency of this layer is thus deter- mined in an unbiased way. Fig. 20 Distribution of the spatial resolution provided by the η strips for RPC of the Middle stations. The spatial resolution is divided by the strip pitch. The distributions are normalized to unit area Fig. 21 Left: efficiency map for a TGC chamber layer. The horizontal axis is the strip channel and the vertical axis is the wire channel. Right: efficiency projection to the strip channels. Observed efficiency drops are consistent with the wire support locations 7 MDT optical alignment The design transverse momentum resolution at 1 TeV of the MS is about 10%, this translates into a sagitta resolution of 50 μm. The intrinsic resolution of MDT chambers con- tributes a 40 μm uncertainty to the track sagitta, hence other systematic uncertainties (alignment and calibration) should be kept at the level of 30 μm or smaller. Since long-term mechanical stability in a large structure such as the MS can- not be guaranteed at this level, a continuously running align- ment monitoring system [21] has been installed. This system is based on optical and temperature sensors and detects slow chamber displacements, occurring at a timescale of hours or Fig. 20 Distribution of the spatial resolution provided by the η strips for RPC of the Middle stations. The spatial resolution is divided by the strip pitch. The distributions are normalized to unit area Fig. 21 Left: efficiency map for a TGC chamber layer. The horizontal axis is the strip channel and the vertical axis is the wire channel. Right: efficiency projection to the strip channels. Observed efficiency drops are consistent with the wire support locations Eur. Phys. J. C (2010) 70: 875–916 903 Fig. 22 Distribution of the TGC wire efficiency of individual layers for different high voltage values. The distribution for 2800 V, the nominal voltage in 2008, was obtained with run 91,060 Fig. 22 Distribution of the TGC wire efficiency of individual layers for different high voltage values. The distribution for 2800 V, the nominal voltage in 2008, was obtained with run 91,060 the missing sensors on the final alignment quality is negligi- ble. more. The information from the alignment system is used in the offline track reconstruction to correct for the chamber misalignment. No mechanical adjustments were made to the chambers after the initial positioning. The system consists of a variety of optical sensors, all sharing the same design prin- ciple: a source of light is imaged through a lens onto an elec- tronic image sensor acting as a screen. In addition to optical position measurements, it is also necessary to determine the thermal expansion of the chambers. In total, there are about 12,000 optical sensors and a similar number of temperature sensors in the system. 7 MDT optical alignment Optical and temperature sensors were calibrated before the installation such that they can be used to make an absolute measurement of the chamber positions in space, rather than only following their movements with time relative to some initial positions. The position coordinates, rotation angles, and deforma- tion parameters of the chambers are determined by a global χ2 minimization procedure. The total χ2, as well as the con- tributions of the individual sensor measurements to the χ2 (pulls) can be used to estimate the alignment quality from the internal consistency of the fit. If the observed sensor res- olutions agree with the design values, one expects approx- imately χ2/ndf = 1 and a pull distribution with zero mean and unit RMS width. Figure 23 shows the observed and ex- pected pull distributions in the end-caps, obtained by assum- ing the design resolutions for all sensor types. In a second step, the assumed sensor resolutions are ad- justed until the observed pull distributions, broken down by sensor type, agree with the expected distribution. This yields the observed sensor resolutions, which are used as input to a Monte Carlo simulation of the alignment system. The simu- lation predicts a sagitta accuracy due to alignment of about 45 μm, which is close to the design performance. 7.1 End-cap chamber alignment The end-cap chambers and their alignment system [22] were installed and commissioned during 2005–2008, and contin- uous alignment data-taking with the complete system started in Summer 2008. After commissioning, more than 99% of all alignment sensors were operational, and only a small number failed during the data-taking in 2008. The effect of Validating the alignment as reconstructed from the op- tical sensor measurements requires an external reference. During chamber installation, surveys of the completed end- cap wheels were done using photogrammetry, and the cham- Eur. Phys. J. C (2010) 70: 875–916 904 Fig. 23 The observed (A, from data) and expected (B, from simula- tion) pull distributions for the end-caps, assuming design resolution for all sensor types. Correlations and weakly constrained degrees of free- dom cause the expected pull distribution to have RMS width below unity. The observed χ2/ndf from the fit on data is 1.4, while the one from simulation is 1.0 b iti d ith th li t t d mean value can be accidentally compatible with zero de- spite single towers being significantly misaligned). For cos- mic muons, the observed width of the sagitta distribution is dominated by multiple scattering. A shifted and/or broad- ened distribution would indicate imperfections of the align- ment. Triplets of track segments were selected in the EI- EM-EO chambers, requiring the three segments to be in the same sector and assigned to the same reconstructed track. Some segment quality cuts were applied for this analy- sis: (i) χ2/ndf < 10 and at most one expected hit missing per chamber; (ii) the angle between the segments and the straight line joining the segments in EI and EO was required to be smaller than 5 (50) mrad in the precision (second) co- ordinate; (iii) at least one trigger hit in the second coordi- nate was required to be associated to the track. A total of 1700 segment triplets passing the cuts were selected in run 91,060. Figure 24(A) shows, for the two end-caps, the observed sagitta distribution before and after applying alignment cor- rections (i.e. the chamber positions, rotations, and defor- mations as determined by the optical system, as well as a correction for the gravitational sag of the MDT wires). Figure 24(B) shows the corresponding difference in angle in the precision coordinate between each of the segments and the track (the straight line joining the EI and EO seg- ments). 7.1 End-cap chamber alignment For the distribution in Fig. 24(B), the cut at 5 mrad was omitted. The improvement in both variables is clearly visible, the mean value of the corrected sagitta distribu- tion as obtained from the fit with a double-Gaussian func- tion is (−33 ± 42) μm and thus perfectly compatible with zero within the 45 μm error estimated above from the inter- nal consistency of the alignment fit. The width of the cor- rected sagitta distribution agrees approximately with expec- tations for the typical energies of triggered cosmic muons. The width of the corrected angle distribution, on the other hand, is about twice as large as expected. This is mainly a consequence of the additional time jitter of MDT measure- ments described in Sect. 5 which deteriorates the segment resolution. Fig. 23 The observed (A, from data) and expected (B, from simula- tion) pull distributions for the end-caps, assuming design resolution for all sensor types. Correlations and weakly constrained degrees of free- dom cause the expected pull distribution to have RMS width below unity. The observed χ2/ndf from the fit on data is 1.4, while the one from simulation is 1.0 For the two end-caps separately, the mean value of the sagitta distribution is (−30 ± 61) μm in side A and (−37 ± 57) μm in side C. The sign of the sagitta is defined in such a way that most of the conceivable systematic errors would cause deviations from zero with the same sign in side A and side C. The analysis is limited by statistics even though it uses a significant fraction of the full 2008 data sample. Breaking it down further to the level of sectors, or even to projective towers (where the best sensitivity is obtained) would require significantly more data. ber positions measured with the alignment system agreed with the survey results within 0.5 mm, the quoted accuracy of the survey. While establishing confidence in the optical system, the full validation of the alignment can only be done with tracks. Thus, cosmic muons recorded during magnet- off running were used to cross-check the alignment provided by the optical system. 7.1 End-cap chamber alignment The cross-check with straight tracks confirms that, with the limitations of the analysis, the chamber positions given by the optical alignment system are within the estimated sagitta uncertainties, indicating that the optical system For a perfect alignment, the reconstructed sagitta of straight tracks should be zero for each EI-EM-EO measure- ment tower (note that, when averaged over many towers, the Eur. Phys. J. C (2010) 70: 875–916 905 Table 4 Status of the barrel optical system in Fall 2008. No data were recorded during this period from the “broken” sensors. Naming and functions of the different sensors are detailed in reference [23] Fig. 24 (A): Measured sagitta distribution for the two end-caps. The cross-hatched histogram shows the sagitta before alignment correc- tions, thus reflecting the accuracy of chamber positioning. The filled histogram shows the sagitta after applying alignment corrections, the curve is the fit of a double-Gaussian function, each Gaussian contain- ing 50% of the events. (B): Measured angle in the precision coordinate between the segments and the track to which they are associated Type Total Working Broken Projective 117 117 0 Axial 1036 1031 5 Praxial 2010 2008 2 Reference 256 253 3 CCC 260 260 0 BIR-BIM 32 32 0 Inplane 2110 2101 9 Total 5817 5798 19 % 99.7 0.3 ing cosmic ray data, the barrel optical system was fully in- stalled and 99.7% of the sensors were functioning correctly. Table 4 summarizes the status of the 5817 installed sensors. The complete system is read out continuously, at a rate of one cycle every 20 minutes. The readout was functioning correctly during the complete period of acquisition of cos- mic ray data. The alignment reconstruction consists in determining the chamber positions and orientations (referred to as “align- ment corrections”) from the optical sensor measurements. This requires the precise knowledge of the positions of the sensors with respect to the MDT wires. To this purpose, the optical sensors were calibrated before installation and their mechanical supports were glued with precise tools onto the MDT tubes. However, the original design of the barrel op- tical system suffered from a few errors that eventually de- graded the precision of the alignment corrections. Further- more, the only devices giving projective information in the Small sectors are the CCC sensors which are designed to provide 1 mm accuracy. 7.1 End-cap chamber alignment The alignment of the chambers of the Small sectors is, by design, based on tracks that cross the overlap region between the Small and the Large sectors. However, the statistics obtained in cosmic runs was not suf- ficient to perform a precise check of this method. Fig. 24 (A): Measured sagitta distribution for the two end-caps. The cross-hatched histogram shows the sagitta before alignment correc- tions, thus reflecting the accuracy of chamber positioning. The filled histogram shows the sagitta after applying alignment corrections, the curve is the fit of a double-Gaussian function, each Gaussian contain- ing 50% of the events. (B): Measured angle in the precision coordinate between the segments and the track to which they are associated The alignment corrections discussed here cover the nine upper sectors (1 to 9). The complete period of cosmic data taking was divided in intervals of 6 hours, and alignment corrections were reconstructed using the sensor measure- ments recorded in that interval. This provided data for mon- itoring of significant movements of the MS, e.g. when the magnetic field in the toroids was switched on. works properly. The design accuracy has nearly been reached in the end-caps. It also shows that the system produces a reli- able estimate of the uncertainty of the alignment corrections. The barrel alignment reconstruction is based on the mini- mization of a χ2, whose inputs are, for each optical sensor i: 7.2 Barrel chamber alignment 7.2 Barrel chamber alignment – the recorded response ri The installation and commissioning of the barrel optical sys- tem [23] began in 2005 and continued together with the in- stallation of the chambers until 2008. At the time of record- – a model mi(a), representing the predicted response of sensor i with respect to the alignment corrections a – the error σi, the estimated uncertainty of the model mi. Eur. Phys. J. C (2010) 70: 875–916 906 Fig. 25 η × φ map of the contribution to the sagitta error due to align- ment, as estimated with the method described in the text. As expected from the system design, the Small sectors (even sector numbers) are aligned with significantly less precision than the Large sectors (odd sector numbers) The critical part is the model mi, as it combines all the knowledge of the precise geometry of the optical sensors and their calibration. The free parameters in the fit are the alignment corrections a, and in some cases additional pa- rameters used to model the effect of imprecise sensor posi- tioning or of an incorrect calibration. For all these additional parameters appropriate constraints are included in the fit re- flecting the best estimates of the error contributions men- tioned above. Overall, 4099 parameters are fit simultane- ously. The total reconstruction time for the full barrel is less than one minute. Given the uncertainties introduced by the additional para- meters in the fit procedure, the strategy for alignment in the barrel is slightly different from the one in the end-cap. Ded- icated runs without magnetic field in the toroids (but with field in the solenoid to tag high momentum tracks) will be used to get initial alignment corrections with a precision of 30 μm. The optical alignment system is then used to moni- tor movements due to the switching on of the toroidal field and to temperature effects. The mechanical stability of the system, in periods where the magnetic field was constant, is at the level of 100 μm, while movements of the mag- net structures at the level of few mm were observed when the magnets were switched on and off. The optical align- ment system, which continuously monitors the position of the chambers, is able to follow these movements with the required accuracy. 7.2.1 Performance of the optical alignment in the barrel Similarly to what is done in the end-cap, an estimate of the contribution to the sagitta error due to the alignment system may be inferred from the χ2, using the following formula (V −1)ij = 1 2 ∂2χ2 ∂θi∂θj ¯¯¯¯ ˆθ (V −1)ij = 1 2 ∂2χ2 ∂θi∂θj ¯¯¯¯ ˆθ where θi are the fitted parameters and V is the global er- ror matrix, of size 4099×4099, of all fitted parameters. To estimate the performance of the alignment system in terms of sagitta measurement, straight tracks, originating in the IP and crossing three layers of chambers, were simulated and the whole fit procedure was applied to these tracks. The sagitta of these pseudo-tracks is a function of some of the alignment corrections, and thus the formula of error propa- gation may be used to infer the contribution of the alignment to the error of the resulting sagitta. This technique relies on the hypothesis that the errors of the optical sensors are cor- rectly estimated, and thus that the χ2 is correctly normal- ized. As this is not the case (χ2/ndf = 1.9), the results are where θi are the fitted parameters and V is the global er- ror matrix, of size 4099×4099, of all fitted parameters. To estimate the performance of the alignment system in terms of sagitta measurement, straight tracks, originating in the IP and crossing three layers of chambers, were simulated and the whole fit procedure was applied to these tracks. The sagitta of these pseudo-tracks is a function of some of the alignment corrections, and thus the formula of error propa- gation may be used to infer the contribution of the alignment to the error of the resulting sagitta. This technique relies on the hypothesis that the errors of the optical sensors are cor- rectly estimated, and thus that the χ2 is correctly normal- ized. As this is not the case (χ2/ndf = 1.9), the results are The track alignment algorithm has been tested with Monte Carlo simulations and with cosmic ray data. The sim- ulation studies show that 105 muon tracks with a momentum greater than 20 GeV and pointing to the IP are needed to align the Large sectors with a precision of 30 μm. Small sectors require five times more tracks than Large sectors, due to the multiple scattering in the toroid coils. 7.2.2 Alignment with straight tracks Data with the toroidal field off were used to improve the alignment precision in the barrel and to validate the align- ment corrections in relative mode. The method is to use straight muon tracks to determine in absolute mode the ini- tial spectrometer geometry and, once this geometry is deter- mined, to use the optical alignment system to trace all cham- ber displacements in a relative mode. The alignment proce- dure with straight tracks is based on the so-called MILLE- PEDE fitting method [24]. This method uses both alignment and track parameters inside a global fit. As a result, all cor- relations between alignment and track parameters are taken into account and the alignment algorithm is unbiased. 7.2 Barrel chamber alignment This so-called relative alignment mode has already been tested with success in the MS system-test done with a high-energy muon beam [4, 5]. After the mini- mization, the value obtained for χ2/ndf is 1.9, which shows that the sensor errors are underestimated. Fig. 25 η × φ map of the contribution to the sagitta error due to align- ment, as estimated with the method described in the text. As expected from the system design, the Small sectors (even sector numbers) are aligned with significantly less precision than the Large sectors (odd sector numbers) only considered as a rough estimate of the optical alignment performance. The result is shown in Fig. 25. The Small sectors have a significantly worse alignment than the Large sectors, as explained above. Conservatively, one can conclude that the performance of the optical system, in terms of sagitta preci- sion, is ∼200 μm for the Large sectors, and ∼1 mm for the Small sectors. 7.2.1 Performance of the optical alignment in the barrel Using straight cosmic muon tracks recorded in run 91,060, a set of alignment constants has been produced. A total of 107 events were used corresponding to about 3 × 105 cosmic muon tracks in each of the most illuminated barrel sectors. The statistical uncertainty of the sagitta using Eur. Phys. J. C (2010) 70: 875–916 907 this track alignment procedure was estimated to be 30 μm for Large sectors. 1 mm. To compare the results obtained in different stations, Fig. 27 shows the mean values of the sagitta distribution for the Large upper sectors (3, 5 and 7). One Small sector is also presented, sector 4, since this was illuminated with enough events during the same run to produce a meaningful distrib- ution. The data of run 91,060 were processed with the track re- construction software twice: (i) using the optical alignment corrections and (ii) using the track-based alignment correc- tions. Both geometries were then tested by measuring the distribution of the track sagitta for muons crossing three chamber stations (Inner, Middle and Outer). Only tracks passing close to the IP in the η projection were chosen. Hits in the Inner and Outer chambers were fit to a straight line, and the distribution of the hit residuals in the Middle cham- bers was used to evaluate the sagitta. For perfect alignment, the mean value of the sagitta should be zero for straight tracks and, to a good approximation, the mean value of the distribution gives an estimate of the sagitta error. The results show that the optical alignment system alone provides a precision at the level of 200 μm. When calibrated with sufficient statistics of high momentum straight tracks, the optical system is able reach a precision of 50 μm. The sagitta resolution for runs with no magnetic field in the MS can be studied as a function of the muon momentum measured by the ID. The sagitta resolution as a function of the muon momentum was parameterized as σs(p) = K0 p ⊕K1 σs(p) = K0 p ⊕K1 The results are shown in Fig. 26 for the sets of align- ment corrections; on the left for a station in a Large sector, on the right for a station in a Small sector. For reference, the distributions using the design geometry are also shown. The tails of the distributions are due to multiple scattering of muons. 7.2.1 Performance of the optical alignment in the barrel In the Large sector station, the two distributions are almost identical, but the distribution with optical align- ment is centered at ∼100 μm. In the Small sector station, the distribution with the optical alignment is centered around where the first term K0 is due to multiple scattering in the material of the MS, and the second term K1 is due to the single tube resolution and chamber-to-chamber alignment. These two terms have been already measured at the MS sys- tem test beam [4, 5] and found to be K0 = 9 mm×GeV and K1 = 50 μm. A similar measurement was done with cosmic muons by selecting segment triplets (Inner, Middle Fig. 26 Distribution of the sagitta (as defined in the text) for straight tracks. (A), (B): Using alignment corrections derived from the optical system only; (C), (D): Using track-based alignment corrections. (A), (C): For a station in a Large barrel sector; (B), (D): For a station in a Small barrel sector, the optical system corrections of the small sectors have, by design, an accuracy at a level of 1 mm. In all panels, the hashed distribution is obtained using the “nominal” geometry. Mean and sigma in the statistical boxes refer to the distributions with alignment corrections, the peak is fitted with a Gaussian in a ±1 sigma interval Eur. Phys. J. C (2010) 70: 875–916 908 Fig. 27 Mean value of the track sagitta distributions obtained (A), (B): With the optical alignment system only, (C), (D): and using the track-based alignment. (A), (C): For the upper Large barrel sectors. (B), (D): For a Small barrel sector with 56◦< φ < 79◦ and Outer station) of MS projective towers. The RMS of the sagitta of the Middle station segment with respect to the Outer–Inner straight line extrapolation has been fit in five momentum bins. The result is shown in Fig. 28 for sec- tor 5 (Large sector) with RPC-time corrections applied in the calibration procedure. The fitted value for the two terms is K0 = (12.2±0.7) mm×GeV and K1 = (107±21) μm. In the MS the multiple scattering term is expected to be worse than the one measured at the test beam setup and larger for Small sectors due to the presence of the toroid coils between the Inner and Outer chambers. 7.2.1 Performance of the optical alignment in the barrel The value of K1 measured with cosmic muons in sector 5 is only about a factor two worse than that measured at the test beam. Several effects contribute to this, including alignment, chamber deforma- tions, calibration and single tube resolution. Similar studies performed for other sectors show worse results due to the smaller data sample available for alignment and calibration. These preliminary studies with cosmic rays indicate that the method of track based alignment is robust and with suf Fig. 27 Mean value of the track sagitta distributions obtained (A), (B): With the optical alignment system only, (C), (D): and using the track-based alignment. (A), (C): For the upper Large barrel sectors. (B), (D): For a Small barrel sector with 56◦< φ < 79◦ and Outer station) of MS projective towers. The RMS of the sagitta of the Middle station segment with respect to the Outer–Inner straight line extrapolation has been fit in five momentum bins. The result is shown in Fig. 28 for sec- tor 5 (Large sector) with RPC-time corrections applied in the calibration procedure. The fitted value for the two terms is K0 = (12.2±0.7) mm×GeV and K1 = (107±21) μm. In the MS the multiple scattering term is expected to be worse than the one measured at the test beam setup and larger for Small sectors due to the presence of the toroid coils between the Inner and Outer chambers. The value of K1 measured with cosmic muons in sector 5 is only about a factor two worse than that measured at the test beam. Several effects contribute to this, including alignment, chamber deforma- tions, calibration and single tube resolution. Similar studies performed for other sectors show worse results due to the smaller data sample available for alignment and calibration. These preliminary studies with cosmic rays indicate that the method of track-based alignment is robust and with suf- ficient muon data from collisions the design alignment pre- cision will be achieved. Fig. 28 RMS value of the sagitta distribution in sector 5 as a function of the muon momentum measured by the ID. The fit to the function described in the text is superimposed 8 Pattern recognition and segment reconstruction The pattern recognition algorithm first groups hits close in space and time for each detector. Each pattern is character- ized by a position and a direction and contains all the as- sociated hits. Starting from these patterns, the segments are reconstructed with a straight line fit. The Gt0-refit is applied at this stage and, if the Gt0-refit procedure does not con- verge, the segment parameters are computed with the tube Fig. 28 RMS value of the sagitta distribution in sector 5 as a function of the muon momentum measured by the ID. The fit to the function described in the text is superimposed Eur. Phys. J. C (2010) 70: 875–916 909 Fig. 29 (A): Distribution of the number of MDT hits per segment for segments associated to a track. (B): Segment reconstruction efficiency for 322 MDT chambers t0 provided by the calibration with tube resolution increased to 2 mm. After this, a drift radius is assigned to each tube with an uncertainty of 2 mm (independent of the drift radius value) in order to keep high track reconstruction efficiency even in the case where no precise alignment constants are available. The minimum number of hits per segment was set to 3 and no cuts were applied on the number of missed hits. These relaxed requirements tend to increase the number of fake segments while keeping a high segment efficiency. Since cosmic ray events are quite clean and have low hit multiplicity this fake rate increase is not considered as a problem. On the other hand, a high reconstruction efficiency allows the use of segments to spot hardware problems in individual chambers or in calibration or decoding software. Most of the fake segments are rejected at the track recon- struction level. Figure 29(A) shows, on the left, the number of MDT hits per segment for segments associated to a track. In the distri- bution clear peaks are observed at 6 and 8 hits corresponding to the 6-layer (Middle and Outer) and 8-layer (Inner) cham- bers. The efficiency of the segment reconstruction in run 91,060 was determined in the following way. First, cosmic shower events are suppressed by requiring less than 20 seg- ments in the event. Then a pair of segments in two MDT stations (Inner, Medium or Outer) are fitted to a straight line and the line is extrapolated to the third station. 8 Pattern recognition and segment reconstruction In the extrap- olation multiple scattering is taken into account assuming a 2 GeV momentum for the cosmic muon. If the extrapo- lated line crossed the third station, a reconstructed segment is searched for in that station, but it is not required that the hits of this segment be associated to the muon track. The segment efficiency is then computed for each MDT cham- ber as the fraction of times a segment is found. In order to reduce the effect of the non-instrumented regions a fiducial cut in η was applied for both barrel and end-cap. Chambers that were not operational in the analyzed run were removed from the sample. It was not possible to determine the effi- ciency for all chambers due to the limited coverage of the trigger for the run used for this analysis (Fall 2008) and flux of cosmic rays. For tracks crossing the overlap region be- tween two adjacent chambers (Small/Large sector overlap) it was not required that two segments be reconstructed, since this may lead to a slight overestimation of the efficiency. Fig. 29 (A): Distribution of the number of MDT hits per segment for segments associated to a track. (B): Segment reconstruction efficiency for 322 MDT chambers Table 5 Average value of the segment reconstruction efficiency in the MDT stations MDT station BI BM BO EI EM EO Segment efficiency 0.987 0.992 0.996 0.992 0.998 0.999 refit, on the extrapolation and on the track angle, show that a systematic error of ∼0.5% affects the values of efficiency listed in Table 5. An alternative method to evaluate the segment recon- struction efficiency, almost independent of chamber hard- ware problems, is described in the following. As in the pre- vious case, this method can be used only with no magnetic field in the MS. All segment pairs in two different MDT sta- tions (Inner, Middle or Outer) with a polar angle difference smaller than 7.5 mrad are considered. The segment pairs are fitted to a straight line and this is extrapolated to the third MDT station. The track is kept if at least three hit tubes are found in the third MDT with a signal charge above the ADC The distribution of the segment efficiency is shown in Fig. 29(B) for 322 chambers in the barrel. 9.2 Efficiency – at least 20 hits in the Transition Radiation Tracker – at least 20 hits in the Transition Radiation Tracker The track reconstruction efficiency is computed as the frac- tion of events where a track is reconstructed in the MS top or bottom hemisphere once an ID track was found satisfying the selection criteria described above. In this case also tracks with hits in only two out of three MDT stations (Inner, Mid- dle or Outer) are accepted, even if these tracks have a worse momentum resolution than tracks reconstructed in three sta- tions. About 15% of the selected tracks are in this category. In addition, to compute the track efficiency in the top (bot- tom) hemisphere, a momentum cut of 5 GeV (9 GeV) on the ID track is applied. The result is shown in Fig. 31 as a func- tion of the pseudorapidity of the ID track, for the top and bottom hemisphere separately. – the number of hits summed over the SemiConductor Tracker (SCT) and the Pixel detector greater than 4 – the distance of closest approach in the transverse plane |d0| and along the z axis |z0| smaller than 1 m – the value of the muon track χ2/ndf < 3 – the value of the reconstructed pseudorapidity |η| < 1 – reconstructed momentum greater than 5 GeV. This selection has been applied for all the studies re- ported in this section with the exception of the momentum resolution results. 8 Pattern recognition and segment reconstruction The average value is 99.5% and the segment efficiency is uniform over the ac- ceptance as shown in Table 5. In the efficiency for the barrel chambers there is a small loss of about 0.5% due the pres- ence of the support structure of the ATLAS barrel. The Inner chambers have a slightly lower segment efficiency due to the geometry of the trigger and a larger uncertainty in the track extrapolation. Studies on systematic effects in determining the segment efficiency, such as its dependence on the Gt0- Eur. Phys. J. C (2010) 70: 875–916 910 Fig. 30 Distribution of residuals for MDT hits associated to a track. The residuals have been fitted with a double-Gaussian function with common mean. The mean value is 6 µm, the standard deviation of the narrow Gaussian is about 150 µm and the one of the wide Gaussian is about 700 µm cut and aligned with the track extrapolation within one tube diameter, ±3 cm. The segment efficiency is then computed as the fraction of selected tracks that have a segment recon- structed with at least 3 hits in the identified drift tubes. Since the normalization already requires the presence of three hits in the tested MDT station, this segment efficiency is almost independent of local hardware problems. A segment recon- struction efficiency higher than 0.99 is found in all MDT stations. The rate of fake segments was studied with a random trig- ger. An average rate of 0.06 fake segments per event was found with the relaxed hit association criteria used for cos- mic muons. This rate is expected to be strongly reduced to about 2 × 10−3 if the segment reconstruction requirements are made to be more stringent as shown by using an alterna- tive muon tracking algorithm. Fig. 30 Distribution of residuals for MDT hits associated to a track. The residuals have been fitted with a double-Gaussian function with common mean. The mean value is 6 µm, the standard deviation of the narrow Gaussian is about 150 µm and the one of the wide Gaussian is about 700 µm 9 Track reconstruction The MOORE and Muonboy programs have been optimized to reconstruct muon tracks originating from the IP. To cope with the different topology of cosmic ray muons they have been slightly modified as explained in Sect. 2. To mimic muons in collision events, the tracks are split at their perigee (point of closest approach to the beam axis), giving, usually, two reconstructed tracks: one in the upper part of the MS and one in the lower part. Events with at least one ID track satisfying the following criteria were selected: value. The mean of the distribution was 6 μm and the RMS widths was 150 μm for the narrow Gaussian, accounting for 75% of the distribution, and 700 μm for the other. When compared to the distribution of the segment residuals shown in Sect. 6 two additional effects contribute to the broadening of this distribution: the misalignment between stations and multiple scattering in the MS material. 9.3 Momentum measurement The momentum of cosmic muons was measured in runs with magnetic field. The momentum measurement can be defined at the MS entrance or at the point of closest approach to the IP. In the second case, for tracks crossing the ID, a correc- tion was made for the energy loss in the calorimeters. This correction is based on the average energy loss computed by the track extrapolation algorithm and is on average 3.1 GeV for muons pointing to the interaction region with a distance of closest approach of |d0| < 1 m and |z0| < 2 m. Fig. 32 (A): Distribution of momentum of cosmic muons as measured at the MS entrance for the upper and lower hemispheres. The difference between the two distributions is due to the ID track momentum cut of 5 GeV. (B): Same distributions with track momentum extrapolated to the IP The distribution of momentum at the MS entrance is shown in Fig. 32—(A) for the top and bottom hemispheres separately. The difference between the two distributions is due to the ID track momentum cut of 5 GeV that translates in a different momentum cut-off in the two MS hemispheres, since cosmic muons are directed downwards. The same dis- tribution extrapolated to the perigee is shown in Fig. 32(B), demonstrating that the correction for the energy loss in the calorimeter removes the offset. and the energy loss is twice the value quoted above, in good agreement with the 6.3 GeV mean value of the distribution. The MS momentum resolution has been estimated by comparing for each cosmic muon the two independent mea- surements in the top and bottom hemispheres. In order to increase the available statistics no requirements on the pres- ence of ID tracks were applied in this study. Only events with at least two reconstructed tracks in the MS are consid- ered. Each track is required to have: The distribution of the number of MDT hits associated with a track is shown in Fig. 33(A). For this plot tracks mea- sured in three MDT stations have been selected. A clear peak around 20 hits is visible (8 tubes in the Inner stations, 6 in the Middle and Outer stations). In events with tracks that cross the whole MS, the track is split at the perigee and the two independent momentum measurements, in the top and bottom hemisphere, can be compared. 9.1 Resolution This based on the average energy loss computed by apolation algorithm and is on average 3.1 GeV ointing to the interaction region with a distance proach of |d0| < 1 m and |z0| < 2 m. bution of momentum at the MS entrance is . 32—(A) for the top and bottom hemispheres he difference between the two distributions is track momentum cut of 5 GeV that translates momentum cut-off in the two MS hemispheres, di d d d Th di Fig. 32 (A): Distribution of momentum of cosmic muons as measured at the MS entrance for the upper and lower hemispheres. The difference between the two distributions is due to the ID track momentum cut of 5 GeV. (B): Same distributions with track momentum extrapolated to the IP Fig. 31 Track reconstruction efficiency as a function of pseudorapid- ity. The loss in efficiency in the region near |η| = 0 is due to the loss of acceptance for detector services. The presence of a track measured in the ID with |η| < 1 is required Fig. 31 Track reconstruction efficiency as a function of pseudorapid- ity. The loss in efficiency in the region near |η| = 0 is due to the loss of acceptance for detector services. The presence of a track measured in the ID with |η| < 1 is required 9.1 Resolution The value of the efficiency, integrated over the η accep- tance, is 94.9% for the top and 93.7% for the bottom hemi- sphere respectively. If the four central bins are removed in Fig. 31 the efficiency increases to 98.3% and 96.3% respec- tively. The statistical error on these values is below 0.1%. The lower efficiency in the central detector region, around |η| = 0, is due to the presence of the main ATLAS service gap while lower efficiency in the Bottom hemisphere is ex- plained by the uninstrumented regions occupied by the sup- port structure of the ATLAS barrel. The distribution of residuals for MDT hits associated to a track is shown in Fig. 30. The hit residual is defined as the difference between the drift radius measured in a tube and the distance of the track to the tube wire. The distribution refers only to tracks with MDT hits in at least three differ- ent muon stations (Inner, Middle and Outer) because these tracks have well constrained parameters and individual hits give a small contribution to the track parameters. The distri- bution was fitted to a double Gaussian with common mean Eur. Phys. J. C (2010) 70: 875–916 911 Fig. 32 (A): Distribution of momentum of cosmic muons as measured at the MS entrance for the upper and lower hemispheres. The difference between the two distributions is due to the ID track momentum cut of 5 GeV. (B): Same distributions with track momentum extrapolated to the IP Fig. 31 Track reconstruction efficiency as a function of pseudorapid- ity. The loss in efficiency in the region near |η| = 0 is due to the loss of acceptance for detector services. The presence of a track measured in the ID with |η| < 1 is required reconstruction efficiency as a function of pseudorapid- efficiency in the region near |η| = 0 is due to the loss of detector services. The presence of a track measured in < 1 is required um measurement um of cosmic muons was measured in runs with d. The momentum measurement can be defined trance or at the point of closest approach to the ond case, for tracks crossing the ID, a correc- de for the energy loss in the calorimeters. 9.3 Momentum measurement Figure 33(B) shows the distribution of the dif- ference of the two momentum values, top–bottom measured at the MS entrance, for tracks with momenta greater than 15 GeV. In this case the muons cross the calorimeter twice – at least 17 MDT hits, of which at least 7 in the Inner and 5 in the Middle and Outer stations of the same φ sector 17 MDT hits, of which at least 7 in the Inner and – at least 2 different layers of RPC with a hit in the φ pro- jection – polar angle 65◦< θ < 115◦ 912 Eur. Phys. J. C (2010) 70: 875–916 – distance of closest approach to the IP |d0| < 1 m and |z0| < 2 m The distribution of 1pT /pT was fitted in each bin with a double-Gaussian function with common mean value. The narrow Gaussian was convoluted with a Landau function to account for the distribution of energy loss in the calorimeter. For pT < 10 GeV the normalizations of the two Gaussians were constrained such that 95% of the events are in the nar- row Gaussian. Above 10 GeV this constraint was lowered to 70%. The mean value is representative of the difference in the transverse momentum scale between the two MS hemi- spheres. The RMS of the narrow Gaussian plus the width of the Landau, divided by √ 2, is taken as an estimate of the transverse momentum resolution for each pT bin. The Lan- dau width is added linearly to the narrow Gaussian RMS since the two quantities are strongly correlated. – polar and azimuthal angles of the MS track pair agree within 10 ◦. About 19 K top–bottom track pairs were selected in this way. For each track the value of transverse momentum was evaluated at the IP. The difference between the two values divided by their average 1pT pT = 2 pTup −pTdown pTup + pTdown 1pT pT = 2 pTup −pTdown pTup + pTdown was measured in eleven bins of pT . Since the cosmic muon momentum distribution is a steep function (see Fig. 32), the pT value of each bin was taken as the mean value of the distribution in that bin. The distribution of 1pT /pT is shown in Fig. 34 for all pT bins together with the fitted function. 9.3 Momentum measurement For the eleven bins the fit probability is in the range between 45% and 99%, showing that the chosen parametrization is a good represen- tation of the data distribution. Fig. 33 (A): Number of MDT hits on track. (B): Momentum d ence between momenta measured by the MS in the top and b hemispheres for cosmic muons. The momenta are expressed at th entrance and only tracks with momenta bigger than 15 GeV are sidered. The mean value of 6.3 GeV is due to the energy loss calorimeter material Different fits have been done to study the systematics of the mean and RMS value. (i) The constraint between the two Gaussian areas has been changed by ±10%. (ii) A dou- ble Gaussian with common mean and asymmetric fit range, with the fit range reduced to two standard deviations on the positive side to avoid the energy loss tail. (iii) A fit with two independent Gaussians with no range constraint. The result is that the estimated resolution is quite independent of the fit assumptions. The variation of the fit resolution ranges be- tween 0.5% at low pT up to a maximum of 1% in the highest momentum bin. The fit mean values indicate that the pT scales in the two MS hemispheres are in agreement within 1%, or better. The relative pT resolution, σpT /pT = σ(1pT /pT )/ √ 2, is shown in Fig. 35, for the two main muon reconstruction al- gorithms [7, 8], as a function of the transverse momentum. The two results are consistent taking into account the inde- pendent statistical uncertainties. The resolution function can be fitted with the sum in quadrature of three terms, the uncertainty on the energy loss corrections P0, the multiple scattering term P1, and the in- trinsic resolution P2. σpT pT = P0 pT ⊕P1 ⊕P2 × pT . The result of the fit is shown in Fig. 35. The values of the pa- rameters are: P0 = 0.29 ± 0.03 ± 0.01 GeV, P1 = 0.043 ± 0.002 ± 0.002, P2 = (4.1 ± 0.4 ± 0.6) × 10−4 GeV−1. The second uncertainty, due the systematics of the bin-by-bin fit method, was evaluated by changing the fitting assump- tions as explained above. 9.3 Momentum measurement At high pT the mo- mentum resolution in the barrel Large sectors is worse than in Small sectors because the field integral is smaller (see Fig. 1). Instead, in the low pT region dominated by multiple scattering the resolution in Large sectors is better since the magnet coils are in the Small sectors. Second, the single tube resolution is affected by imper- fect calibrations and the additional time jitter is not com- pletely recovered by the Gt0-refit (see Fig. 12). Part of the tracks in the sample contain segments with a badly converg- ing Gt0-refit. As a cross-check, all the tracks with bad con- vergence were removed and the analysis was repeated. The intrinsic term decreased by about 30%. Finally, with data collected when the magnetic field was on, a first estimate of the spectrometer momentum resolution was obtained. Efficiency and resolution of single elements have been measured for MDT, RPC and TGC chambers and were found in agreement with results obtained previ- ously with high-momentum muon beams. The trigger cham- ber timing has been adjusted with enough precision to guar- antee that the interaction bunch crossing can be identified with a minimal number of failures. The muon trigger logic, based on fast tracking of pointing muons has been exten- sively tested in the regions of the detector with good cos- mic ray illumination. A slight deterioration of the MDT spa- tial resolution, compared to test beam results, was observed, which can be understood in terms of an additional time jit- ter due to the asynchronous timing of cosmic muons and to their non-pointing geometry. These effects were partially removed, modifying the track reconstruction programs with dedicated algorithms. Allowing for an increase of the single hit resolution, to cope with these effects, the track segment efficiency in individual chambers was found to be satisfac- tory and uniform over the large number of chambers. Third, the alignment in many sectors of the MS is still not at the required level due to the limited statistics of straight tracks in the cosmic ray data sample. Last, several other ef- fects that contribute to resolution have not been removed, such as chamber deformations (due to temperature effects), wire sagging (particularly important in large chambers), sin- gle chamber geometrical defects. Each of these effects con- tribute to worsening the resolution and can be removed with dedicated software tools. 9.3 Momentum measurement The values obtained for the barrel MS were: P0 = 0.35 GeV, P1 = 0.035 and P2 = 1.2 × 10−4 GeV−1. single tube resolution, the alignment accuracy and the mag- netic field map. The values obtained for the barrel MS were: P0 = 0.35 GeV, P1 = 0.035 and P2 = 1.2 × 10−4 GeV−1. The result is in fair agreement with the expected values for the first two terms, while the intrinsic term is worse. The difference has been investigated to trace the effects that con- tribute to worsen the resolution as determined with cosmic muons. mance of the Muon Spectrometer after its installation in the ATLAS experiment. Parts of the detector, the Small Wheels in front of the end-cap toroids, were installed during the runs and the commissioning of the many detectors was proceed- ing while debugging the data acquisition and the data control systems. The detector coverage during most of the run pe- riod was higher than 99%, with the exception of the RPC chambers which were still under commissioning. For this detector subsystem the coverage steadily improved during the commissioning runs reaching more than 95% in Spring 2009. Results on several aspects of the Muon Spectrome- ter performance have been presented. These include detector coverage, efficiency, resolution and relative timing of trigger and precision tracking chambers, track reconstruction, cali- bration, alignment and data quality. mance of the Muon Spectrometer after its installation in the ATLAS experiment. Parts of the detector, the Small Wheels in front of the end-cap toroids, were installed during the runs and the commissioning of the many detectors was proceed- ing while debugging the data acquisition and the data control systems. The detector coverage during most of the run pe- riod was higher than 99%, with the exception of the RPC chambers which were still under commissioning. For this detector subsystem the coverage steadily improved during the commissioning runs reaching more than 95% in Spring 2009. Results on several aspects of the Muon Spectrome- ter performance have been presented. These include detector coverage, efficiency, resolution and relative timing of trigger and precision tracking chambers, track reconstruction, cali- bration, alignment and data quality. First, more than 70% of the track pairs considered in the analysis are in the Large sectors 5–13. 9.3 Momentum measurement At the present stage of commis- sioning, the momentum resolution is close to the design value for pT < 50 GeV, but is not as good for higher mo- menta. 9.3 Momentum measurement The expected values for these pa- rameters were computed in reference [3] on the basis of an analytic calculation of the pT resolution that takes into ac- count the detailed description of the material in the MS, the Fig. 33 (A): Number of MDT hits on track. (B): Momentum differ- ence between momenta measured by the MS in the top and bottom hemispheres for cosmic muons. The momenta are expressed at the MS entrance and only tracks with momenta bigger than 15 GeV are con- sidered. The mean value of 6.3 GeV is due to the energy loss in the calorimeter material Eur. Phys. J. C (2010) 70: 875–916 913 Fig. 34 Distributions of 1pT /pT in the eleven pT bins. Fits to the function described in the text are superimposed Eur. Phys. J. C (2010) 70: 875–916 913 Fig. 34 Distributions of 1pT /pT in the eleven pT bins. Fits to the function described in the text are superimpose Eur. Phys. J. C (2010) 70: 875–916 914 Fig. 35 Transverse momentum resolution evaluated with the top–bottom method explained in the text as a function of pT , barrel region only (|η| < 1.1). The fit to the three resolution parameters as described in the text is superimposed single tube resolution, the alignment accuracy and the mag- netic field map. The values obtained for the barrel MS were: P0 = 0.35 GeV, P1 = 0.035 and P2 = 1.2 × 10−4 GeV−1. The result is in fair agreement with the expected values for the first two terms, while the intrinsic term is worse. The difference has been investigated to trace the effects that con- tribute to worsen the resolution as determined with cosmic muons. First, more than 70% of the track pairs considered in the analysis are in the Large sectors 5–13. At high pT the mo- mentum resolution in the barrel Large sectors is worse than in Small sectors because the field integral is smaller (see Fig. 1). Instead, in the low pT region dominated by multiple scattering the resolution in Large sectors is better since the magnet coils are in the Small sectors. Second, the single tube resolution is affected by imper- fect calibrations and the additional time jitter is not com- pletely recovered by the Gt0-refit (see Fig. 12). Part of the tracks in the sample contain segments with a badly converg- ing Gt0-refit. 9.3 Momentum measurement As a cross-check, all the tracks with bad con- d d th l i t d Th mance of the Muon Spectrometer after its installation in the ATLAS experiment. Parts of the detector, the Small Wheels in front of the end-cap toroids, were installed during the runs and the commissioning of the many detectors was proceed- ing while debugging the data acquisition and the data control systems. The detector coverage during most of the run pe- riod was higher than 99%, with the exception of the RPC chambers which were still under commissioning. For this detector subsystem the coverage steadily improved during the commissioning runs reaching more than 95% in Spring 2009. Results on several aspects of the Muon Spectrome- ter performance have been presented. These include detector coverage, efficiency, resolution and relative timing of trigger and precision tracking chambers, track reconstruction, cali- bration, alignment and data quality. Finally, with data collected when the magnetic field was on, a first estimate of the spectrometer momentum resolution was obtained. Efficiency and resolution of single elements have been measured for MDT, RPC and TGC chambers and were found in agreement with results obtained previ- Fig. 35 Transverse momentum resolution evaluated with the top–bottom method explained in the text as a function of pT , barrel region only (|η| < 1.1). The fit to the three resolution parameters as described in the text is superimposed Fig. 35 Transverse momentum resolution evaluated with the top–bottom method explained in the text as a function of pT , barrel region only (|η| < 1.1). The fit to the three resolution parameters as described in the text is superimposed single tube resolution, the alignment accuracy and the mag- netic field map. The values obtained for the barrel MS were: P0 = 0.35 GeV, P1 = 0.035 and P2 = 1.2 × 10−4 GeV−1. The result is in fair agreement with the expected values for the first two terms, while the intrinsic term is worse. The mance of the Muon Spectrometer after its installation in the ATLAS experiment. Parts of the detector, the Small Wheels in front of the end-cap toroids, were installed during the runs and the commissioning of the many detectors was proceed- ing while debugging the data acquisition and the data control single tube resolution, the alignment accuracy and the mag- netic field map. References 1. The ATLAS Muon Collaboration, The ATLAS Muon Spectrometer technical design report. CERN-LHCC/97-22 (31 May 1997). ISBN 92-9083-108-1 2. G. Aad et al. (The ATLAS Collaboration), The ATLAS experiment at the CERN large hadron collider. J. Instrum. 3, S08003 (2008). 1–437 During the long period of commissioning with cosmic rays it was possible to optimize the performance of the var- ious hardware and software elements and to reach a level of understanding, such that we can consider the Muon Spec- trometer to be ready to efficiently detect muons produced in high-energy proton–proton collisions. 3. G. Aad et al. (The ATLAS Collaboration), Expected Performance of the ATLAS Experiment: Detector, Trigger and Physics. CERN- OPEN 2008-020 (December 2008). ISBN 978-92-9083-321-5 4. C. Adorisio et al., System Test of the ATLAS Muon spectrometer in the H8 beam at the CERN SPS. Nucl. Instrum. Meth. A 593, 232–254 (2008) 5. C. Adorisio et al., Study of the ATLAS MDT spectrometer using high energy CERN combined test beam data. Nucl. Instrum. Meth. A 598, 400–415 (2009) Acknowledgements We are greatly indebted to all CERN’s depart- ments and to the LHC project for their immense efforts not only in building the LHC, but also for their direct contributions to the con- struction and installation of the ATLAS detector and its infrastructure. We acknowledge equally warmly all our technical colleagues in the collaborating Institutions without whom the ATLAS detector could not have been built. Furthermore we are grateful to all the funding agencies which supported generously the construction and the commissioning of the ATLAS detector and also provided the computing infrastructure. 6. The ATLAS Collaboration, ATLAS computing technical design report. CERN-LHCC/2005-022 (20 June 2005). ISBN 92-9083- 250-9 7. D. Adams et al., Track reconstruction in the ATLAS Muon spectrometer with MOORE. ATL-SOFT-2003-007, 2.10.2003, http://cdsweb.cern.ch/collection/ATLAS 8. S. Hassani et al., A Muon identification and combined recon- struction procedure for the ATLAS detector at the LHC using (Muonboy, STACO, MuTag) reconstruction packages. Nucl. In- strum. Meth. A 572, 77–79 (2007) The ATLAS detector design and construction has taken about fif- teen years, and our thoughts are with all our colleagues who sadly could not see its final realization. 10 Summary The performance of the end-cap and barrel optical align- ment systems have been measured using cosmic muon tracks with no magnetic field. The results demonstrate that The data collected in several months during the 2008–2009 cosmic ray runs have been analyzed to assess the perfor- 915 Eur. Phys. J. C (2010) 70: 875–916 the end-cap optical system is able to provide the required precision for chamber alignment. The design of the align- ment system in the barrel requires additional constraints provided by straight tracks. The method has been tested with good results, but is limited by the statistics of high- momentum muons with the required pointing geometry. Education and Religion, through the EPEAEK program PYTHAGO- RAS II and GSRT, Greece; ISF, MINERVA, GIF, DIP, and Benoziyo Center, Israel; INFN, Italy; MEXT, Japan; CNRST, Morocco; FOM and NWO, Netherlands; The Research Council of Norway; Ministry of Science and Higher Education, Poland; GRICES and FCT, Portugal; Ministry of Education and Research, Romania; Ministry of Education and Science of the Russian Federation and State Atomic Energy Cor- poration “Rosatom”; JINR; Ministry of Science, Serbia; Department of International Science and Technology Cooperation, Ministry of Ed- ucation of the Slovak Republic; Slovenian Research Agency, Ministry of Higher Education, Science and Technology, Slovenia; Ministerio de Educación y Ciencia, Spain; The Swedish Research Council, The Knut and Alice Wallenberg Foundation, Sweden; State Secretariat for Edu- cation and Science, Swiss National Science Foundation, and Cantons of Bern and Geneva, Switzerland; National Science Council, Taiwan; TAEK, Turkey; The Science and Technology Facilities Council and The Leverhulme Trust, United Kingdom; DOE and NSF, United States of America. the end-cap optical system is able to provide the required precision for chamber alignment. The design of the align- ment system in the barrel requires additional constraints provided by straight tracks. The method has been tested with good results, but is limited by the statistics of high- momentum muons with the required pointing geometry. With the geometry corrections provided by the alignment system, tracks in projective geometry were reconstructed in the barrel showing that the reconstruction efficiency is uni- form over the entire acceptance and that the sagitta error is in agreement with the detector resolution, the alignment pre- cision and the effect of multiple coulomb scattering. Finally with magnetic field, tracks crossing the whole spectrometer were used to obtain two independent mea- surements of the momentum. 10 Summary The momentum resolution was evaluated using the two values in the top and bottom part of the detector and the results were analyzed, fitting the distribution of the difference as function of the mo- mentum. Taking into account the momentum spectrum, the multiple scattering in the spectrometer and the energy loss in traversing the calorimeters, the momentum resolution is in good agreement with results from simulation for trans- verse momenta smaller than 50 GeV. The statistics of high- momentum pointing tracks limits the accuracy of the indi- vidual chamber calibration and the precision of the align- ment. At higher momenta, these limitations result in de- graded momentum resolution. Open Access This article is distributed under the terms of the Cre- ative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. References We acknowledge the support of ANPCyT, Argentina; Yerevan Physics Institute, Armenia; ARC and DEST, Australia; Bundesminis- terium für Wissenschaft und Forschung, Austria; National Academy of Sciences of Azerbaijan; State Committee on Science & Technologies of the Republic of Belarus; CNPq and FINEP, Brazil; NSERC, NRC, and CFI, Canada; CERN; CONICYT, Chile; NSFC, China; COL- CIENCIAS, Colombia; Ministry of Education, Youth and Sports of the Czech Republic, Ministry of Industry and Trade of the Czech Republic, and Committee for Collaboration of the Czech Republic with CERN; Danish Natural Science Research Council and the Lundbeck Founda- tion; European Commission, through the ARTEMIS Research Train- ing Network; IN2P3-CNRS and Dapnia-CEA, France; Georgian Acad- emy of Sciences; BMBF, HGF, DFG and MPG, Germany; Ministry of 9. The ATLAS Collaboration, First level trigger technical design re- port. CERN-LHCC/98-014 (30 June 1998). ISBN 92-9083-128-6 10. F. Anulli et al., The level-1 Muon barrel trigger of the ATLAS experiment. J. Instrum. 4, P04010 (2009). 1–35 11. The ATLAS Collaboration, High-level trigger, data acquisition and controls technical design report. CERN-LHCC/2003-022 (30 June 2003). ISBN 92-9083-205-3 12. P. Bagnaia et al., Calibration model for the MDT chambers of the ATLAS Muon spectrometer. ATL-MUON-PUB-2008-004 (28 March 2008), http://cdsweb.cern.ch/collection/ATLAS 13. M. Verducci, ATLAS database experience with the COOL condi- tions database project. J. Phys. Conf. Ser. 119, 042031 (2008) 916 Eur. Phys. J. C (2010) 70: 875–916 14. Y. Arai, Development of front end electronics and TDC LSI for the ATLAS MDT. Nucl. Instrum. Meth. A 453, 365 (2000) 19. R.M. Avramidou, E. Gazis, R. Veenhof, Drift properties of the ATLAS MDT chambers. Nucl. Instrum. Meth. A 568, 672–681 (2006) 15. Y. Arai et al., ATLAS muon drift tube electronics. J. Instrum. 3, P09001 (2008). 1–58 20. P. Branchini et al., Global time fit for tracking in an array of drift cells: the drift tubes of the ATLAS experiment. IEEE Trans. Nucl. Sci. 55, 620 (2008) 16. D.S. Levin et al., Drift time spectrum and gas monitoring in the ATLAS Muon spectrometer precision chambers. Nucl. Instrum. Meth. A 588, 347–358 (2008) 21. C. Amelung, The alignment system of the ATLAS Muon spec- trometer. Eur. Phys. J. C 33, 999–1001 (2004) 17. R. Veenhof, Garfield, a drift chamber simulation program. Pre- pared for International Conference on Programming and Mathe- matical Methods for Solving Physical Problems, Dubna, Russia, 14–19 June 1993 22. S. 18. S.F. Biagi, Monte Carlo simulation of electron drift and diffusion in counting gases under the influence of electric and magnetic fields. Nuclear Instrum. Methods Phys. Res., Sect. A, Accel. Spec- trom. Detect. Assoc. Equip. 421(1–2), 234–240 (1999) References Aefsky et al., The optical alignment system of the AT- LAS Muon spectrometer endcaps. J. Instrum. 3, P11005 (2008). pp. 1–59 23. C. Guyot et al., The alignment system of the barrel part of the AT- LAS Muon spectrometer. ATLAS Note ATL-MUON-PUB-2008- 007 (2008), http://cdsweb.cern.ch/collection/ATLAS 18. S.F. Biagi, Monte Carlo simulation of electron drift and diffusion in counting gases under the influence of electric and magnetic fields. Nuclear Instrum. Methods Phys. Res., Sect. A, Accel. Spec- trom. Detect. Assoc. Equip. 421(1–2), 234–240 (1999) p 24. V. Blobel, Millepede: linear least squares fits with a large number of parameters, http://www.desy.de/~blobel/mptalks.html
https://openalex.org/W4323655754
http://sjie.journals.sharif.edu/article_22899_869ef64a6558e3078dfd8b4c90cdca06.pdf
English
null
رتبه‌بندی سیستم‌ اندازه‌گیری شرکت‌های قطعه‌سازی خودرو از طریق روش تلفیقی MSA–MADM در شرایط فازی
Muhandisī-i ṣanāyi̒ va mudīriyyat-i Sharīf/Muhandisī-i ṣanāyi̒ va mudīriyyat-i Sharīf
2,023
cc-by
9,516
alalinezhad@gmail.com layah 1985@yahoo.com atqiau@gmail.com Original Article |=yCmQW |Q}oxR=Ov=sDU}U |Ov@x@DQ |k}irD VwQ j}Q] R= wQOwN |R=Uxa]k |R=i \}=QW QO MSA MADM sDU}U uDi=} |=Q@ =yu; |Ov@x@DQ w xU}=kt '|Q}oxR=Ov= |=ysDU}U p}rLD w x}RHD C}a[w Ow@y@ ?@U xm CU= |QwQ[ |Qt= u; R= |Q}PBwor= w Ot;Q=m |Q}oxR=Ov= |Ov@x@DQ xr=kt u}= hOy "OwW|t O}rwD lU}Q Vy=m u; p=@vO x@ w Ot;Q=m=v |=ysDU}U Ovw}B 'u}BU=m x}=tQU C}=Oy |va} wQOwN |R=Uxa]k CmQW GvB |Q}oxR=Ov= |=ysDU}U |=Q@ C=a]k |xOvvmu}t-=D xm CU= xa]k=vO w wQOwN R=UOQU 'u=R=U=Qi 'wQOwN p}rLD R= |@}mQD VwQ l} xr=kt u}= 'Q=m u}= |=Q@ "OvDUy wQOwNu=Q}= w =B}=U |=yCmQW sOa \}=QW QO (MADM) xYN=WOvJ |Q}os}tYD w (MSA) |Q}oxR=Ov= sDU}U =@ xa]k=vO CmQW xm OyO|t u=Wv j}kLD u}= G}=Dv "OyO|t xaUwD w x=Q= =Q |R=i C}a]k u}= G}=Dv T=U= Q@ "OQ=O Q=}DN= QO =Q |Q}oxR=Ov= sDU}U u}QDOt;Q=m 1 818 Xr=N u=}QH |=yptar=QwDUO wQOwNu=Q}= w =B}=U |R=UwQOwN |=yCmQW OwW|t O=yvW}B 'xar=]t Q}=U |=Q@ wor= |Q}oxR=Ov= sDU}U u=wvax@ =Q ?NDvt CmQW |Q}oxR=Ov= sDU}U |}=QH= "Ovvm |D=}rta wQOwN |R=Uxa]k |=yCmQW xQ=}atOvJ |Q}os}tYD '(MSA) |Q}oxR=Ov= |=ysDU}U p}rLD %|O}rm u=oS=w "2s}Ut=B l}vmD '1l}D}Qm l}vmD 'C}a]k sOa \}=QW '(MCDM) Original Article |=yCmQW |Q}oxR=Ov=sDU}U |Ov@x@DQ |k}irD VwQ j}Q] R= wQOwN |R=Uxa]k |R=i \}=QW QO MSA MADM Q=}Wv=O O=Sv|ra =[Q}ra OWQ=T=vWQ u=}QO}L =}ar OWQ= |U=vWQ O=Sv|Qy=] |ra u}wRk OL=w |tqU= O=R; x=oWv=O 'l}vt w `}=vY |UOvyt |xOmWv=O sDU}U uDi=} |=Q@ =yu; |Ov@x@DQ w xU}=kt '|Q}oxR=Ov= |=ysDU}U p}rLD w x}RHD C}a[w Ow@y@ ?@U xm CU= |QwQ[ |Qt= u; R= |Q}PBwor= w Ot;Q=m |Q}oxR=Ov= |Ov@x@DQ xr=kt u}= hOy "OwW|t O}rwD lU}Q Vy=m u; p=@vO x@ w Ot;Q=m=v |=ysDU}U Ovw}B 'u}BU=m x}=tQU C}=Oy |va} wQOwN |R=Uxa]k CmQW GvB |Q}oxR=Ov= |=ysDU}U |=Q@ C=a]k |xOvvmu}t-=D xm CU= xa]k=vO w wQOwN R=UOQU 'u=R=U=Qi 'wQOwN p}rLD R= |@}mQD VwQ l} xr=kt u}= 'Q=m u}= |=Q@ "OvDUy wQOwNu=Q}= w =B}=U |=yCmQW sOa \}=QW QO (MADM) xYN=WOvJ |Q}os}tYD w (MSA) |Q}oxR=Ov= sDU}U =@ xa]k=vO CmQW xm OyO|t u=Wv j}kLD u}= G}=Dv "OyO|t xaUwD w x=Q= =Q |R=i C}a]k u}= G}=Dv T=U= Q@ "OQ=O Q=}DN= QO =Q |Q}oxR=Ov= sDU}U u}QDOt;Q=m 1 818 Xr=N u=}QH |=yptar=QwDUO wQOwNu=Q}= w =B}=U |R=UwQOwN |=yCmQW OwW|t O=yvW}B 'xar=]t Q}=U |=Q@ wor= |Q}oxR=Ov= sDU}U u=wvax@ =Q ?NDvt CmQW |Q}oxR=Ov= sDU}U |}=QH= "Ovvm |D=}rta wQOwN |R=Uxa]k |=yCmQW Original Article |=yCmQW |Q}oxR=Ov=sDU}U |Ov@x@DQ |k}irD VwQ j}Q] R= wQOwN |R=Uxa]k |R=i \}=QW QO MSA MADM Q=}Wv=O O=Sv|ra =[Q}ra OWQ=T=vWQ u=}QO}L =}ar OWQ= |U=vWQ O=Sv|Qy=] |ra u}wRk OL=w |tqU= O=R; x=oWv=O 'l}vt w `}=vY |UOvyt |xOmWv=O sDU}U uDi=} |=Q@ =yu; |Ov@x@DQ w xU}=kt '|Q}oxR=Ov= |=ysDU}U p}rLD w x}RHD C}a[w Ow@y@ ?@U xm CU= |QwQ[ |Qt= u; R= |Q}PBwor= w Ot;Q=m |Q}oxR=Ov= |Ov@x@DQ xr=kt u}= hOy "OwW|t O}rwD lU}Q Vy=m u; p=@vO x@ w Ot;Q=m=v |=ysDU}U Ovw}B 'u}BU=m x}=tQU C}=Oy |va} wQOwN |R=Uxa]k CmQW GvB |Q}oxR=Ov= |=ysDU}U |=Q@ C=a]k |xOvvmu}t-=D xm CU= xa]k=vO w wQOwN R=UOQU 'u=R=U=Qi 'wQOwN p}rLD R= |@}mQD VwQ l} xr=kt u}= 'Q=m u}= |=Q@ "OvDUy wQOwNu=Q}= w =B}=U |=yCmQW sOa \}=QW QO (MADM) xYN=WOvJ |Q}os}tYD w (MSA) |Q}oxR=Ov= sDU}U =@ xa]k=vO CmQW xm OyO|t u=Wv j}kLD u}= G}=Dv "OyO|t xaUwD w x=Q= =Q |R=i C}a]k u}= G}=Dv T=U= Q@ "OQ=O Q=}DN= QO =Q |Q}oxR=Ov= sDU}U u}QDOt;Q=m 1 818 Xr=N u=}QH |=yptar=QwDUO wQOwNu=Q}= w =B}=U |R=UwQOwN |=yCmQW OwW|t O=yvW}B 'xar=]t Q}=U |=Q@ wor= |Q}oxR=Ov= sDU}U u=wvax@ =Q ?NDvt CmQW |Q}oxR=Ov= sDU}U |}=QH= "Ovvm |D=}rta wQOwN |R=Uxa]k |=yCmQW Original Article |=yCmQW |Q}oxR=Ov=sDU}U |Ov@x@DQ |k}irD VwQ j}Q] R= wQOwN |R=Uxa]k |R=i \}=QW QO MSA MADM CRITIC l}vmD "2"2"3 CRITIC l}vmD "2"2"3 %OwW|t u}}aD C XN=W 21 |x]@=Q R= xO=iDU= =@ TBU Cj = j n X k=1 (1 jk) ; j = 1 ; ::: ; n (21) x@U=Lt 22 |x]@=Q R= =yXN=W u=Rw= ,=D}=yv %=yXN=W uRw u}}aD "5 sOk %OwW|t wj = Cj n P j=1 Cj ; j = 1 ; ::: ; n (22) l}vmD xDiQo Q=Qk xO=iDU= OQwt j}kLD u}= QO xm MADM |=yl}vmD R= |m} [23]u=Q=mtyw|mqwm=}O\UwD|Oq}t1995p=UQOl}vmDu}="CU=CRITIC |=y|oS}w R= "OwQ|t Q=m x@ =yXN=W uRw u}}aD |=Q@ |rm Qw] x@ w OW x=Q= |i}m |=yXN=W w CU}v =yXN=W pqkDU= x@ |R=}v xm CU= u}= VwQ u}= R= xO=iDU= =@ =yXN=W uRw l}vmD u}= QO "OvwW|t p}O@D |tm |=yXN=W x@ XN=W Qy QO =yxv}Ro OQmrta p@=kD COW |va} |U=U= swyit wO |[=}Q pO=at l}vmD |=QH= pL=Qt "OwW|t u}}aD Qo}Om} =@ |@=}RQ= |=yXN=W ZQ=aD w %CU= Q}R KQW x@ CRITIC u=}@ =yXN=W w =yxv}Ro T}QD=t u}= QO %s}tYD T}QD=t p}mWD "1 sOk Cj = j n X k=1 (1 jk) ; j = 1 ; ::: ; n PAMSSEM&II l}vmD "3"2"3 xtOkt "1 '|QDWt C}=[Q R= u=v}t]= |=Q@ O}rwD u}L QO CqwYLt C}Q}Ot w C}i}m pQDvm |Qw;`tH |=yxO=O x@ |O=}R OL =D =yv; |WN@QF= 'p=L u}= =@ "CU= |QwQ[ |Qt= w x}RHD R= =yOQ@Q=m QO ,qwtat 'Qw_vt u}= |=Q@ "OQ=O |oDU@ O}rwD \N R= xOW |@=}RQ= |=Q@ |W}=tR; |OQm}wQ |L=Q] xm 1 (MSA) |Q}oxR=Ov= sDU}U p}rLD R= pY=L |=yxO=O C}i}m xRwQt= [1]"OwW|t xO=iDU= 'CU=y|Q}oxR=Ov= C}i}m R= pY=L |Q=t; |=y|oS}w x@ w xOw@ xHwD OQwt |Qo}O u=tR Qy R= V}@ |Q}oxR=Ov= |Q}oxR=Ov=sDU}Ul}QO'Q=O}=B\}=QWCLDxmOQ=O|oDU@|QQmt|=y|Q}oxR=Ov= Ov=wD|t |DL xm u}= p}rO x@ |Q}oxR=Ov= sDU}U C}i}m Qo}O u=}@ x@ "OQ}PB|t s=Hv= Qo= "CU= Q=OQwNQ@ |}xS}w C}ty= R= OyO Q=Qk `=aWr=CLD =Q O}rwD Ov}=Qi C=v=Uwv w x}RHD 'OW=@ u}}=B u; R= pY=L |Q=OQ@xvwtv s=kQ= w |Q}oxR=Ov= sDU}U C}i}m QO =Q K}LY |Q}os}tYD u=wD|tv w CW=O Oy=wNv |@U=vt Q=@Da= Ov}=Qi p}rLD p |UQQ@ w OwHwt C=}@O= j}kO QwQt =@ =DU=Q u}ty QO "CU= wQOwN C=a]k 'j}kLD |xrUt C}y=t |}=U=vW ut[ 'xOW s=Hv= |=yVywSB w C=k}kLD |Q}oxR=Ov= |=ysDU}U p}rLD |xrwkt QO xHwD OQwt |=yQ=}at R= |rt=m CUQyi Q@ Q=PoQ}F-=D |=yXN=W R= l} Qy uRw Oa@ |xrLQt QO "CU= xOW G=QNDU= |=yQ=Ri= sQv R= xO=iDU= =@ w 5 CRITIC l}vmD Q@ |vD@t |Q}oxR=Ov= |=ysDU}U p}rO x@ '=yXN=W uRw u}}aD =@ "CU= xOt; CUO x@ Excel w Minitab 6 PAMSSEM l}vmD R= '|Q}oxR=Ov= sDU}U p}rLD |=yXN=W u}@ |oDU@=w xOW xO=iDU= |Q}oxR=Ov= sDU}U u}QD?U=vt ?=NDv= w |Ov@x@DQ Qw_vtx@ |R=i Q=mv=t}B ?=NDv= QO Ov=wD|t hrDNt |Q}oxR=Ov= |=ysDU}U |xU}=kt "CU= K}LY |Q}os}tYD =} O}rwD Q]N Vy=m Qw_vt x@ '|Q}oxR=Ov= sDU}U p}rLD |=Q@ u=wD|t ?NDvt |Q}oxR=Ov= sDU}U Cwk \=kv R= u}vJty "OW=@ O}it QO Qw_vt u}= |=Q@ "OQm xO=iDU= |Q}oxR=Ov= |=ysDU}U Q}=U C}a[w Ow@y@ xOW xDiQo Q=m x@ MSA QO MADM hrDNt |=yVwQ OQ@Q=m 'xr=kt u}= "CU= C}r@=k p}rLD |=Q@ |WwQ x=Q= x@ [6]xO=R}ra ?Lt "CU= Q=OQwNQ@ l}Uqm VwQ CUO x@ |=yxO=O xm |}=H 'CN=OQB |R=i \}Lt QO Q}eDt |Q}oxR=Ov= sDU}U s=Hv= |=Q@ "OvwW|t ZQi |R=i O=Oa= |xar=]t CLD '|Q}oxR=Ov= Ov}=Qi R= xOt; xO=R\U@ pY= T=U= Q@ |]NQ}e |R}Qxt=vQ@ p=Ut R= CiH l} 'hOy u}= x}RHD |=Q@ ?re= xm OW xrwtQi |@=}RQ= Q=}at w K]U Vy=m |x@U=Lt |=Q@ |WwQ TBU "OvQ}o|t Q=Qk xO=iDU= OQwt Q}eDt |Q}oxR=Ov= sDU}U C}r@=k p}rLD w Q}eDt |Q}oxR=Ov= sDU}U C}r@=k =}; xm u}= |@=}RQ= |=Q@ |R=i O=Oa= |Ov@x@DQ |=Q@ R= xO=iDU= =@ "CiQoQ=Qk xO=iDU= OQwt 'Q}N =} CU= VN@C}=[Q |R=i \}Lt QO x@ QHvt |Q}oxR=Ov= |=yxO=O QO |R=U?}mQD xm OW xO=Ou=Wv |@QHD p=Ft l} |Q}PBQ=QmD|UQQ@hOy=@|WywSB [7]nv;w}yww}m"OwW|tQDj}kOC}r@=kp}rLD [8]u=Q=mty w |JwQB "OvO=O s=Hv= |Qwv |Q}oxR=Ov= sDU}U l} QO |Q}PBQ}FmD w XN=W C=ar=]t T=U= Q@ '|Q}oxR=Ov= sDU}U l} |xQ}eDtOvJ p}rLD |=Q@ |WwQ OQm}wQ [9]u=Q=mty w |U=QDUr=@ "OvOQm O=yvW}B |Q}PBQ}FmD w |Q}PBQ=QmD Ov};Q@ "OvOQm |UQQ@ =Q |Q}oxR=Ov= sDU}U p}rLD QO xQ}eDtOvJ Tv=}Q=w p}rLD |=Q@ |vRw uRw |SD=QDU= u}QDQF-wt xm OyO|t u=Wv |@QHD |=yxO=O |Q=t; p}rLD w x}RHD G=QNDU= |xS}w Q}O=kt R= |OYQO |vRw |SD=QDU= 'GR&R C=ar=]t QO |Q=OQ@ |Q}PBQ}}eD ,=iQY xm C=ar=]t u}= "CU= |Q}oxR=Ov= sDU}U l} T}QD=t R= xOW CQ=_v x@ QO=k |Q}oxR=Ov= sDU}U =}; xm u}= u}}aD |=Q@ 'OvwW|t pt=W =Q |}xv=t}B sDU}U R= |W=v C=Q}}eD Qo= "OvDU}v |i=m 'CU= X=N |O}rwD Ov}=Qi l} Q@ x@ QO=k |Q}oxR=Ov= sDU}U x=ov; 'OW=@ sm Ov}=Qi C=Q}}eD x@ C@Uv |Q}oxR=Ov= Ov}=Qi Q@ CQ=_v |=Q@ Ov=wD|t sDU}U xm CU=vat u=O@ u}= "CU= u; X}NWD w |Q}PBQ=QmD |=yVwQ |UQQ@ x@ [10]u=Q=mty w |v=}U "OQ}o Q=Qk xO=iDU= OQwt *wO Qy "OvDN=OQB |Q}oxR=Ov= sDU}U Qy |rY= |xYNWt wO u=wvax@ |Q}PBQ}FmD |O=}R C=aq]= Ovv=wD|t w OvQ=O =y|Q}oxR=Ov= p}rLD QO |tyt Vkv =y|oS}w u}= "OQ=Po|t |Q}oxR=Ov= sDU}U Qy Q@ |Q}F-=D xJ '|Um xJ xm u}= OQwt QO OvyO@ Q=R@= C=@F |UQQ@ |=Q@ pQDvm Q=Owtv |=Q@ |R=i OQm}wQ l} [11]x}qmq `v=k w Mw; w OvOW p}O@D |}xkvRwP |R=i O=Oa= x@ =yxO=O j}kLD u}= QO "OvDN=OQB |Q}oxR=Ov= VywSB u}= R= pY=L G}=Dv "OvOW |R=i ' VQ@ VwQ R= xO=iDU= =@ pQDvm OwOL sDU}U C=@F u=wD|t sy |R=i Cr=L QO Q=Owtv u}= R= xO=iDU= =@ xm O=O u=Wv Q}PB=v?=vDH= Q}}eD `@vt l} |Q}oxR=Ov= |=]N "O=O Q=Qk xar=]t OQwt =Q |Q}oxR=Ov= |W=v Q}}eD |=RH= "CU= |@QHD C=k}kLD T=U= Q@ |Q}os}tYD Ov}=Qi Qy QO QO Q}}eD xS}w pra w OwW xOR u}tND O}=@ O}rwD Ov}=Qi w |Q}oxR=Ov= sDU}U R= XN=W T=U= Q@ |WywSB [12]u=Q=mty w uwU@=Q "O@=} Vy=m umtt u=tR Qy QO '(Scott-Knott) xv=oOvJ |xU}=kt VwQ R}v w |Q}PBQ}FmD w |Q}PBQ=QmD Qw_vt x@ [13]u=Q=mty w u;w} "OvOQm x=Q= |Q}oxR=Ov= |=ysDU}U p}rLD |xRwL XN=W xU R= 'nvUp=eR C}i}m X}NWD C=R}yHD CkO w CLY R= u=v}t]= C}r@=k |@=}RQ= |=Q@ '=RHt |=yxDUO O=OaD w Q}}eD OYQO '|Q}PBQ}FmD w |Q}PBQ=QmD C}a]k sOa Cq=L R= xO=iDU= |ovwoJ Q@ xOW QmP C=ar=]t "OvOQ@ xQy@ C=R}yHD |=yXN=W Q}F-=D R}v w |Q}oxR=Ov= |=ysDU}U |@=}RQ= |=Q@ |R=i Cr=L Ovv=t xm s}R=OQB|t |D=ar=]t QwQt x@ xt=O= QO "Ov=xOw@ RmQtDt =ysDU}U Q@ |Q}oxR=Ov= |Q}oxR=Ov= |=ysDU}U |Ov@x@DQ w |UQQ@ x@ MADM |=yl}vmD R= xO=iDU= =@ Q[=L j}kLD |=yCmQ=Wt w |Qw;wv w u}W}B C=k}kLD h=mW ,=D}=yv "Ov=xDN=OQB "OwW|t x=Q= r = = 10 m = [14] = =m = r "CW=Ov Cy=@W OQ=O OwHw xRwQt= xJv; x@ C}i}m pQDvm 'syORwv w syOHy uQk QO QO |i]a |x]kv u=wvax@ w O=O MQ C}i}m ?qkv= '|Oq}t 1931 p=U QO |O=YDk= C}i}m pQDvm s=vx@ |@=Dm CQ=wW "OW xDiQo Q_v QO |i}m pQDvm |xRwL C}ak=w l} |Q}PBQ}}eD xm O=O u=Wv ?=Dm u}= QO w= "CWwv [3]CqwYLt p@=k Cq=tDL= pwY= =@ C=Q}}eD u}= "CU= |DavY |oOvR QO Q=mv= p@=kQ}e |UQQ@ |=Q@ =Q |}xD}tm =m}Qt; nvH VN@ 1940 p=U Q@t=UO QO "Ow@ X}NWD CW=O RmQtD pQDvm |=yQ=Owtv R= |Q=OQ@xQy@ w xaUwD Q@ xm C}i}m |=yOQ=Ov=DU= Q@Dm= QO "OW QWDvt 1942 w 1941 |=yp=U QO u; |=yVQ=Ro xm OQm T}U-=D p=U QO xm OvO=O p}mWD =Q C}i}m |UOvyt xat=H 7Qiv xOR}U '1945 p=U pQDvm |xRwL |=Q@ =Q |}=m}Qt; |xat=H w OvOW s=eO= |Qo}O uw}U=QOi =@ |D; QwDwt p=QvH '1987 p=U QO "OQ=O OwHw RwQt= x@ =D xm OvOQm O=H}= 8C}i}m "OQm x=Q= sDU}U |}=v=wD |Q}oxR=Ov= |=Q@ |}=yptar=QwDUO xm Ow@ |DmQW u}rw= |=yptar=QwDUO x @ =Q |Qo}O OQ=wt '1989 p=U QO OQwi CmQW u; R= TB u=tr; QO Vw@ CQ@=Q xwQo ?}DQD x@ 1994 w 1990 p=U QO "OQm xi=[= p@k QO "OvOQm QWDvt =Q |O}OH |Q}oxR=Ov= |=yptar=QwDUO Rv@ TOUQt xwQo w |=yptar=QwDUO uOQm OQ=Ov=DU= w C}a[w Ow@y@ |=Q@ `HQt l} |rm Cr=L 'C=Lq]Y= '|vi VQ=Ro |=yCtQi xty pt=W xm CU= R=}v OQwt |Q}oxR=Ov= |=Q@ QwDwt p=QvH w OQwi 'QrU}=Qm CmQW T=U= u}= Q@ "OW=@ |L=Q] w C=aq]= p}rLD `HQt ?=Dm x=Q= w lQDWt |=yptar=QwDUO O=H}= x@ s}tYD Q=@ u}rw= QWDvt ?=Dm u}= R= swO V}=Q}w 1995 p=U QO xm OvDiQo |Q}oxR=Ov= |=ysDU}U [4]"OW uwvm= '|i}m pQDvm w |Q}oxR=Ov= |=ysDU}U |xJN}Q=D =@ |}=vW; R= TB "s}vm|t QwQt j}kLD |xrUt |=DU=Q QO R}v w |D=k}kLD |xRwL u}= QO =Q |Dq=kt QO CkO w CLY V}=Ri= |=Q@ |R=i VwQ l} |xaUwD x@ [5]u=Q=mty w |t_=m O=Oa= R= xO=iDU= =@ 9 GR&R Q=R@= |Q}PBQ}FmD w |Q}PBQ=QmD |=yXN=W x@U=Lt |OQwt |xar=]t j}Q] R= |O=yvW}B VwQ |R=UxO=}B =@ u=v; "OvDN=OQB |FrFt |R=i Cr=L =@ u; G}=Dv |xU}=kt w u=Q}J=m CmQW QO wQOwN CavY QO Iqm |xa]k x@ C@Uv |QDW}@ |Ot;Q=m w C}U=UL R= |R=i VwQ xm OvO=O u=Wv l}Uqm hrDNt |=ysDU}U |Ov@x@DQ |=Q@ 10Qwm}w VwQ R= [14]u=Q=mty w O=Sv}ra u}= |=Q@ "OvOQm xO=iDU= |Q}oxR=Ov= sDU}U C}i}m uDiQ q=@ Qw_vt x@ |Q}oxR=Ov= 16 2 |xQ=tW '381 |xQwO '1401 u=DUtR h}QW C}Q}Ot w `}=vY |UOvyt KQW x@ j}kLD u}= |O}rm |=yCmQ=Wt w =y|Qw;wv 'xOW x=Q= ?r=]t T=U= Q@ %CU= Q}R w p}rLD w x}RHD |=Q@ MADM w MSA R= |@}mQD VwQ l} |xaUwD w x=Q=  &|Q}oxR=Ov= |=ysDU}U |Ov@x@DQ x@ |R=i Cr=L C}a]k sOa \}=QW QO PAMSSEM l}vmD R= xO=iDU=  &|Q}oxR=Ov= |=ysDU}U C}i}m V}=Ri= Qw_vt "|R=UwQOwN CavY |D=ar=]t OQwt QO xOW x=Q= |@}mQD VwQ |R=UxO=}B  VywSB VwQ "3 VywSB |=ys=o "1"3 |=Q@ 'C=}RH |x=Q= R= V}B "OwW|t u=}@ VywSB |rY= pL=Qt 'VN@ u}= QO Qw] x@ "O}vm xaH=Qt 1 pmW x@ VywSB |=ys=o w j}kLD |L=Q] R= K}LY lQO %CU= Q}R KQW x@ VywSB |=ys=o xYqN |R=Uxa]k CmQW GvB QO |D=}rta |Q}oxR=Ov= |=ysDU}U =OD@= s=o u}= QO "1 s=o |rY= VwQ T=U= Q@ '=ysDU}U |}=U=vW R= TB "OvwW|t |}=U=vW wQOwN |Qw;OQo QwmPt |=yCmQW |=Q@ |Q}oxR=Ov= XN=W VW |=yxO=O 'MSA xO=iDU=OQwt|=yXN=W'pw=s=oQOxOWu}}aD MSA |=yXN=W"OvwW|t &OvyO|t p}mWD =Q |Oa@ s=o QO MADM |=yl}vmD QO =@ =yXN=WuRw =OD@= '|UQQ@ OQwt |=yXN=W u}}aD R= TB s=o u}= QO "2 s=o |Ov@x@DQ R= V}B sRq pL=Qt w O};|t CUO x@ CRITIC l}vmD R= xO=iDU= l}vmDR=xO=iDU==@',=D}=yv"OwW|ts=Hv=|R=Uxa]k|=yCmQW=yxv}Ro|}=yv =yxv}Ro |}=yv |Ov@x@DQ |R=i Cr=L C}a]k sOa \}=QW QO PAMSSEM "OQ}PB|t CQwY u}vJty =yu; "OW x=Q= VIKOR VwQ R= xQ=}atOvJ|Q}os}tYD pOt l} 'Qw_vt [15]u=Q=mtyw |r"OvOQm xO=iDU= 11 AHP VwQR= =yXN=WuRw |x@U=Lt|=Q@ "OvDN=OQB TIWR s=vx@ TOPSIS Q@|vD@t xDi=} Ow@y@ OQm}wQ l} |xar=]t x@ OQwt =Q Ov}=Qi pm x@ \w@Qt |=yOQ=Ov=DU= w ?; C}i}m |=yXN=W VwQ u}= |@=}RQ= |=yQ=}at R= xO=iDU= =@ =Q =yXN=W u}@ |oDU@ty w OyO|t Q=Qk |UQQ@ pY=L |=yxDi=} "OQ}o|t Q_v QO (CRITIC) Q=}at u}@ \=@DQ= VwQ j}Q] R= OQm}wQ *|Q}oQ=mx@ QO u=kkLt w u=oOvQ}os}tYD |=Q@ |tyt C=L}wrD j}kLD u}= R= [16]|rw w xO=RQOv@x=W "OQ=O ?; CU}R\}Lt C}Q}Ot w C_=iL QO TIWR l}vmD R= xO=iDU= =@ u=QyD QyW Ov=tUB `iO |xv}y@ |=yVwQ ?=NDv= w |@=}RQ= s=y@= w u=v}t]= sOa C}y=t x@ xHwD =@ =yu; "OvO=O Q=Qk xar=]t OQwt =Q Arreste "OvOQm xO=iDU= |R=i j]vt R= 'u=QyD QyW |=yOv=tUB `iO |xv}y@ u=R}t QO OwHwt C}=yv QOw OWxO=iDU= CRITIC VwQ R= =yXN=W |yOuRw|=Q@ j}kLD u}=QO |WwQ [17]w=m}=U "OvOW |Ov@C}wrw= u=QyD QyW Ov=tUB `iO |xv}y@ |=yVwQ |Q}PBQ}FmD w |Q}PBQ=QmD XN=W R= xO=iDU= =@ |Q}oxR=Ov= sDU}U |@=}RQ= |=Q@ |=yxQwO |m}v=mt OQmrta |@=}RQ= |xar=]t x@ [18]u=Q=mty w wOU; "OQm O=yvW}B w uwr}=v h=}r= =@ xOW C}wkD 12 (OGFCs) R=@ xOW |Ov@xHQO l=m]Y= xU uDiQo Q_v QO =@ =yV}=tR; |L=Q] 'Qw_vt u}= |=Q@ "OvDN=OQB 13ur}BwQB |rB |=yVvm=w "OW s=Hv= Q@}i |=wDLt w ?UJ |=wDLt 'Q@}i s=vx@ pQDvm pt=a QO sQH hqD= 'xDUw}B syx@ |=wy |=yxQiL 'pm =wy |=yxQiL Ovv=t hrDNt |R=Uxv}y@ l} 'xwqa@ "OvOW C@F ?w]Qt \}=QW QO sQH hqD= w lWN \}=QW "OW s=Hv= CRITIC-WASPAST=BU=w m}D}Qm VwQ j}Q] R= xiOyOvJ VwQ T=U= Q@ =Q O}OH xYN=WOvJ |Q}os}tYD VwQ l} [19]u=Q=mty w nvR O=yvW}B|OwyW|R=iQ}O=ktw TOPSISVwQ 14'(NLP)|]NQ}e|R}Qxt=vQ@ w |WO "OW p=ta= xv}y@ |=yuRw x@ uO}UQ |=Q@ NLP VwQ 'u; QO xm OvOQm |Q}oxR=Ov= sDU}U p}rLD w x}RHD uOw@ |tra C=@F= hOy =@ |}xar=]t [20]|=U}O p}@twD= \UwDt w lJwm |=yCmQW |=Q@ X=N Qw] x@ 'sw=Ot C}i}m Ow@y@ |=Q@ sDU}U uOw@ j}kO |@=}RQ= hOy =@ =Q |k}kLD [21]u=Q=mty w =tQ=W "OvO=O s=Hv= R= xO=iDU= =@ [22]u=Q=mty w |r;wO "OvOQm x=Q= GR&R R= xO=iDU= =@ |Q}oxR=Ov= w |Q}PBQ=QmD 'p}=tD 'C=@F pt=W '|Q}oxR=Ov= sDU}U p}rLD w x}RHD |=yXN=W |@=}RQ= =Q Crm}UQwDwt O}rwD |xv=NQ=m l} QO |Q}oxR=Ov= |=ysDU}U '|Q}PBQ}FmD "OvOQm VywSB VwQ "3 VywSB |=ys=o "1"3 |=Q@ 'C=}RH |x=Q= R= V}B "OwW|t u=}@ VywSB |rY= pL=Qt 'VN@ u}= QO Qw] x@ "O}vm xaH=Qt 1 pmW x@ VywSB |=ys=o w j}kLD |L=Q] R= K}LY lQO %CU= Q}R KQW x@ VywSB |=ys=o xYqN |R=Uxa]k CmQW GvB QO |D=}rta |Q}oxR=Ov= |=ysDU}U =OD@= s=o u}= QO "1 s=o |rY= VwQ T=U= Q@ '=ysDU}U |}=U=vW R= TB "OvwW|t |}=U=vW wQOwN |Qw;OQo QwmPt |=yCmQW |=Q@ |Q}oxR=Ov= XN=W VW |=yxO=O 'MSA xO=iDU=OQwt|=yXN=W'pw=s=oQOxOWu}}aD MSA |=yXN=W"OvwW|t &OvyO|t p}mWD =Q |Oa@ s=o QO MADM |=yl}vmD QO =@ =yXN=WuRw =OD@= '|UQQ@ OQwt |=yXN=W u}}aD R= TB s=o u}= QO "2 s=o |Ov@x@DQ R= V}B sRq pL=Qt w O};|t CUO x@ CRITIC l}vmD R= xO=iDU= l}vmDR=xO=iDU==@',=D}=yv"OwW|ts=Hv=|R=Uxa]k|=yCmQW=yxv}Ro|}=yv =yxv}Ro |}=yv |Ov@x@DQ |R=i Cr=L C}a]k sOa \}=QW QO PAMSSEM "OQ}PB|t CQwY |Q_v |v=@t "2"3 |Q}oxR=Ov= sDU}U p}rLD |=yXN=W "1"2"3 |@U=vt |Q}oxR=Ov= |=ysDU}U x@ |v=tR=U Qy QO jiwt C}i}m u}t[D xt=vQ@ l} |=yVwQ w O=wt 'Cq;u}W=t '|v=Uv= |wQ}v x@ |Q}oxR=Ov= sDU}U swyit "OQ=O R=}v |}=yVwQ xawtHt MSA OQ=O xQ=W= =y|Q}oxR=Ov= uOQw; CUO x@ QO \w@Qt |=yxO=O uOw@Q@Dat w |Q}oxR=Ov= sDU}U R= |W=v C=Q}}eD Q=Okt u}}aD |=Q@ xm CU= p}rLD |=Q@ |Q=R@= |Q}oxR=Ov= sDU}U p}rLD w x}RHD [1]"OwW|t xO=iDU= |Q}oxR=Ov= C=i=QLv=Vy=m|=Q@C}i}mOw@y@'u;|rY=hOywCU=|Q}oxR=Ov=sDU}UC}i}m |Q}oxR=Ov= sDU}U |HwQN s}v=O|t xm Qw]v=ty "CU= |Q}oxR=Ov= sDU}U R= |W=v |@=}RQ= |=Q@ [2]"OwW|t u=}@ OOa l} CQwYx@ '|tm |=yxYNWt OQwt QO |UQQ@ Q}R |tm |=yxYNWt 15wQOwN |R=Uxa]k |=yCmQW |Q}oxR=Ov=sDU}U ?=NDv= |}=yv |=yXN=W u=wvax@ Ow@ TQDUO QO =yu; |=yxO=O xm |OQ=wt w "OvOW |Q}oxR=Ov= R= pY=L |=yxO=O u}ov=}t u}@ Cw=iD %(Bias) p}=tD XN=W  CUO x@ 1 |x]@=Q R= xm Ovt=v|t p}=tD =Q (Xm) xa]k |ak=w xR=Ov= w (  X) &O};|t Bias =  X Xm (1) sDU}U uOw@ j}kO |@=}RQ= hOy =@ =Q |k}kLD [21]u=Q=mty w =tQ=W "OvO=O s=Hv= R= xO=iDU= =@ [22]u=Q=mty w |r;wO "OvOQm x=Q= GR&R R= xO=iDU= =@ |Q}oxR=Ov= w |Q}PBQ=QmD 'p}=tD 'C=@F pt=W '|Q}oxR=Ov= sDU}U p}rLD w x}RHD |=yXN=W |@=}RQ= =Q Crm}UQwDwt O}rwD |xv=NQ=m l} QO |Q}oxR=Ov= |=ysDU}U '|Q}PBQ}FmD "OvOQm |=ysDU}Up}rLDwx}RHD'QmPr=jwiQOxmxOWs=Hv=|=yVywSBwC=k}kLDQO |}=yvD x@ OQ=wt |NQ@ QO xv=oOvJ |=yQ=}at =@ |Q}os}tYD u}vJty w |Q}oxR=Ov= R= |@}mQD VwQ xO=iDU= 'OwW|t xO}O QDsm xm |R}J "CU= xDiQo Q=Qk xO=iDU= OQwt |Q}oxR=Ov= |=ysDU}U p}rLD CyH C}a]k sOa \}=QW QO MADM w MSA MADM l}vmD R= xO=iDU= u}W}B |=yVywSB QO |D=k}kLD h=mW =Pr "CU= xm CU= |Q}oxR=Ov= |=ysDU}U C}i}m V}=Ri= Qw_vt x@ C}a]k sOa \}=QW QO QF-wt |=yXN=W `w[wt C=}@O= |UQQ@ =@ =OD@= j}kLD u}= QO "CU= xHwD p@=k l}D}Qm VwQ R= |yOuRw |=Q@ TBU w xOW |}=U=vW |Q}oxR=Ov= |=ysDU}U Q@ CyH s}Ut=B l}vmD R= =yXN=W uOw@ xDU@=w p}rO x@ ',=D}=yv "CU= xOW xO=iDU= =yXN=WpqkDU=x@|R=}vl}vmDu}=QO=Q}R'CU=xOWxO=iDU==yxv}Ro|Ov@x@DQ =} |rY= `wv x@ xHwD =@ w |}x@DQ=Qi |OQm}wQ =@ s}Ut=B l}vmD "CU}v Qo}Om} R= ?=NDv=|=Q@u=oOvQ}os}tYDC=L}HQD|R=Uwor= x@'XN=WQyQ}O=ktuOw@|@}DQD "OR=OQB|t QDQ@ xv}Ro |Q_v |v=@t "2"3 |Q_v |v=@t "2"3 |Q}oxR=Ov= sDU}U p}rLD |=yXN=W "1"2"3 |@U=vt |Q}oxR=Ov= |=ysDU}U x@ |v=tR=U Qy QO jiwt C}i}m u}t[D xt=vQ@ l} |=yVwQ w O=wt 'Cq;u}W=t '|v=Uv= |wQ}v x@ |Q}oxR=Ov= sDU}U swyit "OQ=O R=}v |}=yVwQ xawtHt MSA OQ=O xQ=W= =y|Q}oxR=Ov= uOQw; CUO x@ QO \w@Qt |=yxO=O uOw@Q@Dat w |Q}oxR=Ov= sDU}U R= |W=v C=Q}}eD Q=Okt u}}aD |=Q@ xm CU= p}rLD |=Q@ |Q=R@= |Q}oxR=Ov= sDU}U p}rLD w x}RHD [1]"OwW|t xO=iDU= |Q}oxR=Ov= C=i=QLv=Vy=m|=Q@C}i}mOw@y@'u;|rY=hOywCU=|Q}oxR=Ov=sDU}UC}i}m |Q}oxR=Ov= sDU}U |HwQN s}v=O|t xm Qw]v=ty "CU= |Q}oxR=Ov= sDU}U R= |W=v |@=}RQ= |=Q@ [2]"OwW|t u=}@ OOa l} CQwYx@ '|tm |=yxYNWt OQwt QO |UQQ@ Q}R |tm |=yxYNWt 15wQOwN |R=Uxa]k |=yCmQW |Q}oxR=Ov=sDU}U ?=NDv= |}=yv |=yXN=W u=wvax@ Ow@ TQDUO QO =yu; |=yxO=O xm |OQ=wt w "OvOW |=ysDU}Up}rLDwx}RHD'QmPr=jwiQOxmxOWs=Hv=|=yVywSBwC=k}kLDQO |}=yvD x@ OQ=wt |NQ@ QO xv=oOvJ |=yQ=}at =@ |Q}os}tYD u}vJty w |Q}oxR=Ov= R= |@}mQD VwQ xO=iDU= 'OwW|t xO}O QDsm xm |R}J "CU= xDiQo Q=Qk xO=iDU= OQwt |Q}oxR=Ov= |=ysDU}U p}rLD CyH C}a]k sOa \}=QW QO MADM w MSA MADM l}vmD R= xO=iDU= u}W}B |=yVywSB QO |D=k}kLD h=mW =Pr "CU= xm CU= |Q}oxR=Ov= |=ysDU}U C}i}m V}=Ri= Qw_vt x@ C}a]k sOa \}=QW QO QF-wt |=yXN=W `w[wt C=}@O= |UQQ@ =@ =OD@= j}kLD u}= QO "CU= xHwD p@=k l}D}Qm VwQ R= |yOuRw |=Q@ TBU w xOW |}=U=vW |Q}oxR=Ov= |=ysDU}U Q@ CyH s}Ut=B l}vmD R= =yXN=W uOw@ xDU@=w p}rO x@ ',=D}=yv "CU= xOW xO=iDU= =yXN=WpqkDU=x@|R=}vl}vmDu}=QO=Q}R'CU=xOWxO=iDU==yxv}Ro|Ov@x@DQ =} |rY= `wv x@ xHwD =@ w |}x@DQ=Qi |OQm}wQ =@ s}Ut=B l}vmD "CU}v Qo}Om} R= ?=NDv=|=Q@u=oOvQ}os}tYDC=L}HQD|R=Uwor= x@'XN=WQyQ}O=ktuOw@|@}DQD "OR=OQB|t QDQ@ xv}Ro Bias =  X Xm Bias =  X Xm (1) 17 17 """ |R=Uxa]k |=yCmQW |Q}oxR=Ov=sDU}U |Ov@x@DQ "VywSB |=ys=o w j}kLD VwQ |rm Q=DN=U "1 pmW "VywSB |=ys=o w j}kLD VwQ |rm Q=DN=U "1 pmW |xrY=i l} |xOvyOu=Wv %(R&R) |Q}PBQ}FmD w |Q}PBQ=QmD Ov};Q@ XN=W  sDU}UCkOu=R}twCU=|Q}oxR=Ov=sDU}UC=v=Uwv|xvt=O|=Q@|OYQO99 %O};|t CUO x@ 5 |x]@=Q R= xm OyO|t u=Wv =Q |Q}oxR=Ov= R&R = p AV 2 + EV 2 (5) 16%(NDC) |Q}oxR=Ov= sDU}U l}miD CQOk XN=W  |Q}oxR=Ov=sDU}U\UwDl}miDwX}NWDp@=kpY=wiu}QDtmx@XN=Wu}= OW=@v?U=vtl}miD|}=v=wD|=Q=O|Q}oxR=Ov=sDU}Uxm|DQwYQO"OQ=OxQ=W= xm |D=a]k QO =Q Ov}=Qi QO OwHwt |=yu=Uwv X}NWD u=wD CU= umtt |Q}oxR=Ov= sDU}U R= O}=@ =Pr "OW=@ xDW=Ov OvQ}o|t Q=Qk |Q}oxR=Ov= OQwt u=}@ 6 |x]@=Q j}Q] R= u=wD|t =Q l}miD CQOk "OQm xO=iDU= |QD=v=wD &OQm NDC = 141  PV R&R (6) |xa]kR=xYNWtl}QQmtQw]x@QwD=QB=l}Qo=%(EV )|Q}PBQ=QmDXN=W  "CU= xO=O MQ |Q}PB Q=QmD Ovm |Q}oxR=Ov= x@=Wt Q=R@= =@ w u=mt QO =Q x@=Wt xvt=O u}ov=}t R u; QO xm O};|t CUO x@ 2 |x]@=Q R= |Q}PBQ=QmD |=]N &O};|t CUO x@ XN=W u}= x@ XDNt |i}m pw=OH R= d2 w CU=yxvwtv EV = 5=15  R d2 (2) QO QF-wt pt=wa R= s=Om Qy Q}}eD R= |W=v |oOvm=QB %(AV ) |Q}PBQ}FmD XN=W  C=a]k QQmt |Q}oxR=Ov= s=ovy """ w VwQ 'Q=R@= 'QwD=QB= Ovv=t '|Q}oxR=Ov= sDU}U O=OaD n O};|t CUO x@ 4 w 3 \@=wQ T=U= Q@ |Q}PBQ}FmD |=]N Q=Okt "CU= &CU= |Q}oxR=Ov= C=aiO O=OaD r w C=a]k AV = s  5=51   XDIF d2  EV 2 n : r  (3)  XDIF = Max  X Min  X (4) "VywSB |=ys=o w j}kLD VwQ |rm Q=DN=U "1 pmW "VywSB |=ys=o w j}kLD VwQ |rm Q=DN=U "1 pmW (5) (2) QO QF-wt pt=wa R= s=Om Qy Q}}eD R= |W=v |oOvm=QB %(AV ) |Q}PBQ}FmD XN=W  C=a]k QQmt |Q}oxR=Ov= s=ovy """ w VwQ 'Q=R@= 'QwD=QB= Ovv=t '|Q}oxR=Ov= sDU}U O=OaD n O};|t CUO x@ 4 w 3 \@=wQ T=U= Q@ |Q}PBQ}FmD |=]N Q=Okt "CU= &CU= |Q}oxR=Ov= C=aiO O=OaD r w C=a]k |QD=v=wD &OQm (6) AV = s  5=51   XDIF d2  EV 2 n : r  (3)  XDIF = Max  X Min  X (4) NDC = 141  PV R&R NDC = 141  PV R&R 2 |xQ=tW '381 |xQwO '1401 u=DUtR h}QW C}Q}Ot w `}=vY |UOvyt "CU= j XN=W QO i xv}Ro |=Q@ s}tYD T}QD=t |x}=QO rij u; QO xm |=yXN=W uOQm T=}kt|@ |=Q@ %s}tYD T}QD=t uOQm T=}kt|@ "2 sOk %OwW|t xO=iDU= 15 w 14 \@=wQ R= ?}DQD x@ s}tYD T}QD=t |ivt w C@Ft xij = rij ri ri+ ri ; i = 1 ; ::: ; m ; j = 1 ; ::: ; n (14) xij = rij ri + ri ri+ ; i = 1 ; ::: ; m ; j = 1 ; ::: ; n (15) j XN=W QO i xv}Ro |=Q@ s}tYD T}QD=t |xOW T=}kt|@ Q=Okt xij 'u; QO xm %CU= Q=QkQ@ 17 w 16 \@=wQ R}v ri w r+ i |=Q@ "CU= ri + = Max (r1; r2 ; ::: ; rm) (16) ri = Min (r1; r2 ; ::: ; rm) (17) u=}t |oDU@ty ?}Q[ %=yXN=W u}@ |oDU@ty ?}Q[ u}}aD "3 sOk %O};|t CUO x@ 18 |x]@=Q T=U= Q@ =yXN=W j k = m P i=1(xijxj)(xikxk) s m P i=1 (xijxj)2 m P i=1 (xikxk)2 ; j; k 2 f1; ::: ; ng (18) R= xj |=Q@ xm OvDUy k w j |=yXN=W xwQo wO u}ov=}t xk w xj u; QO xm %O};|t CUO x@ xk |=Q@ x@=Wt Qw] x@ w 19 |x]@=Q xj = 1 n n X j=1 xij ; i = 1 ; ::: ; m (19) h=QLv= u=R}t 20 |x]@=Q ltm =@ =OD@= sOk u}= QO %C XN=W u}}aD "4 sOk %O};|t CUO x@ XN=W Qy OQ=Ov=DU= j = v u u t 1 n 1 n X j=1 (xij xj)2 ; i = 1 ; ::: ; m (20) %OwW|t u}}aD C XN=W 21 |x]@=Q R= xO=iDU= =@ TBU Cj = j n X k=1 (1 jk) ; j = 1 ; ::: ; n (21) x@U=Lt 22 |x]@=Q R= =yXN=W u=Rw= ,=D}=yv %=yXN=W uRw u}}aD "5 sOk %OwW|t Cj j 1 (22) V}=tR; QO xOW xO=iDU= C=a]k |oOvm=QB Q@=Q@ xa]k x@ xa]k |=yu=Uwv PV %O};|t CUO x@ 7 |x]@=Q R= xm CU PV = 5=15  R P d2 (7 Q=R@= |}=v=wD XN=W |x@U=Lt =@ %(Cg; Cgk) |Q}oxR=Ov= Q=R@= |}=v=wD XN=W u}vJty "OQm |UQQ@ =Q |Q}oxR=Ov= |xr}Uw Qy |D=P C=Q}}eD u=wD|t '|Q}oxR=Ov= Cg Q}O=kt "OQm |@=}RQ= u=tRsy Qw] x@ =Q Q=R@= l} p}=tD w |Q}PBQ=QmD u=wD|t %Ov};|t CUO x@ 9 w 8 \@=wQ R= Cgk w Cg = 0=2  T 6  Sg (8 Cg k = 0=1  T   Xg  Xm 3  Sg (9 XNWtuOw@|]NQwDm=iR=xO=iDU==@%|]N\=@DQ=w (R2)|oOv@}RXN=W u=Um} OwN |Q}oxR=Ov= p@=k |xOwOLt s=tD QO |Q}oxR=Ov= Q=R@= =}; xm OwW|t CUO x@ 11 w 10 \@=wQ R= uOw@ |]N OYQO w |oOv@}R Q=Okt #Ovm|t Q=m %O};|t R2 = Pm i=1 Pn j=1 xiyjPm i=1 xi Pn j=1 yj n  2 4Pm i=1 xi2[ Pm i=1 xi]2 n 3 5 2 4Pn j=1 yj2[ Pn j=1 yj]2 n 3 5 (10 Linearity = j a j  100 (11 O=OaD n w xa]k |ak=w xR=Ov= x 'xa]k p}=tD |xOvyOu=Wv y '11 w 10 \@=wQ Q %O};|t CUO x@ 12 |x]@=Q R= xm CU= \N ?}W a w xO=iDU= OQwt C=a] a = Pm i=1 Pn j=1 xiyj h Pm i=1 xi Pn j=1 yj n i Pm i=1 xi2 [ Pm i=1 xi]2 n (12 CRITIC l}vmD "2"2"3 l}vmD xDiQo Q=Qk xO=iDU= OQwt j}kLD u}= QO xm MADM |=yl}vmD R= |m [23]u=Q=mtyw|mqwm=}O\UwD|Oq}t1995p=UQOl}vmDu}="CU=CRITIC |=y|oS}w R= "OwQ|t Q=m x@ =yXN=W uRw u}}aD |=Q@ |rm Qw] x@ w OW x=Q |i}m |=yXN=W w CU}v =yXN=W pqkDU= x@ |R=}v xm CU= u}= VwQ u R= xO=iDU= =@ =yXN=W uRw l}vmD u}= QO "OvwW|t p}O@D |tm |=yXN=W x XN=W Qy QO =yxv}Ro OQmrta p@=kD COW |va} |U=U= swyit wO |[=}Q pO=a l}vmD |=QH= pL=Qt "OwW|t u}}aD Qo}Om} =@ |@=}RQ= |=yXN=W ZQ=aD 2 |xQ=tW '381 |xQwO '1401 u=DUtR h}QW C}Q}Ot w `}=vY |UOvyt "CU= j XN=W QO i xv}Ro |=Q@ s}tYD T}QD=t |x}=QO rij u |=yXN=W uOQm T=}kt|@ |=Q@ %s}tYD T}QD=t uOQm T=}kt|@ " %OwW|t xO=iDU= 15 w 14 \@=wQ R= ?}DQD x@ s}tYD T}QD=t |ivt w xij = rij ri ri+ ri ; i = 1 ; ::: ; m ; j = 1 ; ::: ; n xij = rij ri + ri ri+ ; i = 1 ; ::: ; m ; j = 1 ; ::: ; n j XN=W QO i xv}Ro |=Q@ s}tYD T}QD=t |xOW T=}kt|@ Q=Okt xij 'u %CU= Q=QkQ@ 17 w 16 \@=wQ R}v ri w r+ i |=Q@ ri + = Max (r1; r2 ; ::: ; rm) ri = Min (r1; r2 ; ::: ; rm) u=}t |oDU@ty ?}Q[ %=yXN=W u}@ |oDU@ty ?}Q[ u}}aD " %O};|t CUO x@ 18 |x]@=Q T=U= Q@ =yX j k = m P i=1(xijxj)(xikxk) s m P i=1 (xijxj)2 m P i=1 (xikxk)2 ; j; k 2 f1; ::: ; ng R= xj |=Q@ xm OvDUy k w j |=yXN=W xwQo wO u}ov=}t xk w xj u; %O};|t CUO x@ xk |=Q@ x@=Wt Qw] x@ w 19 xj = 1 n n X j=1 xij ; i = 1 ; ::: ; m h=QLv= u=R}t 20 |x]@=Q ltm =@ =OD@= sOk u}= QO %C XN=W u}}aD " %O};|t CUO x@ XN=W Qy OQ j = v u u t 1 n 1 n X j=1 (xij xj)2 ; i = 1 ; ::: ; m %OwW|t u}}aD C XN=W 21 |x]@=Q R= xO=iDU= =@ Cj = j n X k=1 (1 jk) ; j = 1 ; ::: ; n x@U=Lt 22 |x]@=Q R= =yXN=W u=Rw= ,=D}=yv %=yXN=W uRw u}}aD " %O wj = Cj n P Cj ; j = 1 ; ::: ; n 2 |xQ=tW '381 |xQwO '1401 u=DUtR h}QW C}Q}Ot w `}=vY |UOvyt "CU= j XN=W QO i xv}Ro |=Q@ s}tYD T |=yXN=W uOQm T=}kt|@ |=Q@ %s}tYD T}QD=t %OwW|t xO=iDU= 15 w 14 \@=wQ R= ?}DQD x@ s} xij = rij ri ri+ ri ; i = 1 ; ::: ; m ; j = xij = rij ri + ri ri+ ; i = 1 ; ::: ; m ; j = j XN=W QO i xv}Ro |=Q@ s}tYD T}QD=t |xOW T %CU= Q=QkQ@ 17 w 16 \@= ri + = Max (r1; r2 ; ::: ; rm) ri = Min (r1; r2 ; ::: ; rm) u=}t |oDU@ty ?}Q[ %=yXN=W u}@ |oDU@t %O};|t CUO x@ 18 j k = m P i=1(xijxj)(xikxk) s m P i=1 (xijxj)2 m P i=1 (xikxk)2 ; j; k 2 f1; R= xj |=Q@ xm OvDUy k w j |=yXN=W xwQo wO u %O};|t CUO x@ xk |=Q@ xj = 1 n n X j=1 xij ; i = 1 ; ::: ; m h=QLv= u=R}t 20 |x]@=Q ltm =@ =OD@= sOk u}= QO % %O};|t C j = v u u t 1 n 1 n X j=1 (xij xj)2 ; i = 1 ; : %OwW|t u}}aD C XN=W 21 Cj = j n X k=1 (1 jk) ; j = 1 ; ::: ; n x@U=Lt 22 |x]@=Q R= =yXN=W u=Rw= ,=D}=yv %=yX wj = Cj n P j=1 Cj ; j = 1 ; ::: ; n PAMSSE xm OW |iQat |Oq}t 1996 QO wUwQ w T}m 'pDQ=t x@ 'XN=W Qy Q}O=kt uOw@ |@}DQD =} |rY= `wv x@ xHw l}vmD "OR=OQB|t QDQ@ |xv}Ro ?=NDv= |=Q@ 'u=oOvQ}o xOt; CUO x@ |OwQw w |HwQN |=yu=}QH |UQQ@ l}vmD QO =t= "OQ}o|t CQwY =yxv}Ro |RH |Ov@x 2 |xQ=tW '381 |xQwO '1401 u=DUtR h}QW C}Q}Ot w `}=vY |UOvyt wO '1401 u=DUtR h}QW C}Q}Ot w `}=vY |UOvyt "CU= j XN=W QO i xv}Ro |=Q@ s}tYD T}QD=t |x}=QO rij u; QO xm |=yXN=W uOQm T=}kt|@ |=Q@ %s}tYD T}QD=t uOQm T=}kt|@ "2 sOk %OwW|t xO=iDU= 15 w 14 \@=wQ R= ?}DQD x@ s}tYD T}QD=t |ivt w C@Ft xij = rij ri ri+ ri ; i = 1 ; ::: ; m ; j = 1 ; ::: ; n (14) xij = rij ri + ri ri+ ; i = 1 ; ::: ; m ; j = 1 ; ::: ; n (15) j XN=W QO i xv}Ro |=Q@ s}tYD T}QD=t |xOW T=}kt|@ Q=Okt xij 'u; QO xm = = 1 16 \= + = = V}=tR; QO xOW xO=iDU= C=a]k |oOvm=QB Q@=Q@ xa]k x@ xa]k |=yu=Uwv PV %O};|t CUO x@ 7 |x]@=Q R= xm CU= PV = 5=15  R P d2 (7) Q=R@= |}=v=wD XN=W |x@U=Lt =@ %(Cg; Cgk) |Q}oxR=Ov= Q=R@= |}=v=wD XN=W  u}vJty "OQm |UQQ@ =Q |Q}oxR=Ov= |xr}Uw Qy |D=P C=Q}}eD u=wD|t '|Q}oxR=Ov= Cg Q}O=kt "OQm |@=}RQ= u=tRsy Qw] x@ =Q Q=R@= l} p}=tD w |Q}PBQ=QmD u=wD|t %Ov};|t CUO x@ 9 w 8 \@=wQ R= Cgk w V = 5=15  R P d2 (7) (7) CU= 16) 17) Cg = 0=2  T 6  Sg (8) Cg k = 0=1  T   Xg  Xm 3  Sg (9) R2 = Pm i=1 Pn j=1 xiyjPm i=1 xi Pn j=1 yj n  2 4Pm i=1 xi2[ Pm i=1 xi]2 n 3 5 2 4Pn j=1 yj2[ Pn j=1 yj]2 n 3 5 (10) Linearity = j a j  100 (11) (10) (11) (12) PAMSSEM&II l}vmD "3"2"3 xm OW |iQat |Oq}t 1996 QO wUwQ w T}m 'pDQ=t \UwD PAMSSEM VwQ x@ 'XN=W Qy Q}O=kt uOw@ |@}DQD =} |rY= `wv x@ xHwD =@ '|}x@DQ=Qi OQm}wQ l} =@ l}vmD "OR=OQB|t QDQ@ |xv}Ro ?=NDv= |=Q@ 'u=oOvQ}os}tYD C=L}HQD |R=Uwor= xOt; CUO x@ |OwQw w |HwQN |=yu=}QH |UQQ@ x@ =yvD PAMSSEM pw= l}vmD QO =t= "OQ}o|t CQwY =yxv}Ro |RH |Ov@x@DQ u; QO w OQ=O X=YDN= |Ov@x@DQ w OwW|t u}}aD |}=yv Q}O=kt u=wvax@ Xr=N u=}QH 'PAMSSEM swO X = 0 B B B @ r11 : : : r1n ... ... ... PAMSSEM&II l}vmD "3"2"3 rm 1    rmn 1 C C C A m  n ; (13) 19 """ |R=Uxa]k |=yCmQW |Q}oxR=Ov=sDU}U |Ov@x@DQ u=}QH w ('+) |OwQw u=}QH %|HwQN w |OwQw u=}QH |x@U=Lt "8 sOk %OwW|t x@U=Lt 31 w 30 \@=wQ j@] =yxv}Ro R= l}Qy (') |HwQN '+(A i) = P A i2A ' (A i ; A i0) ; i; i0 2 f1 ; ::: ; mg (30) '(A i) = P A i2A ' (A i0 ; A i) ; i; i0 2 f1 ; ::: ; mg (31) =yxv}Ro R= l} Qy Xr=N u=}QH sOk u}= QO %Xr=N u=}QH |x@U=Lt "9 sOk %O};|t CUO x@ 32 |x]@=Q R= %CU= Q}R KQW x@ l}vmD u}= |=QH= pL=Qt [24]"OQ}o|t CQwY =yxv}Ro pt=m l}D}Qm l}vmD R= pw= sOk Ovv=ty 'T}QD=t u}= %s}tYD T}QD=t p}mWD "1 sOk "OwW |t p}mWD13 | x]@=Q =@ j@=]t w l}vmD j}Q] R= =yXN=W uRw Q=DWwv u}= QO %=yXN=W uRw u}}aD "2 sOk &CU= xOW x@U=Lt CRITIC |xv=DU; w (P) K}HQD |xv=DU; '(Q) |Dw=iD|@ |xv=DU; %=yxv=DU; u}}aD "3 sOk ?=Dm R= j}kLD u}= QO =yQDt=Q=B "OwW|t XNWt xOvQ}os}tYD \UwD (V ) OQ &CU= xOW xDiQo [25] (MADM) xDUUo |xYN=WOvJ |Q}os}tYD |=yl}vmD |=Q@ |rLt |}x@DQ=Qi XN=W %|rLt |}x@DQ=Qi |=yXN=W u}}aD "4 sOk %O};|t CUO x@ 23 |x]@=Q R= |rY= O=Oa= =@ =yXN=W """ |R=Uxa]k |=yCmQW |Q}oxR=Ov=sDU}U |Ov@x@DQ u=}QH w ('+) |OwQw u=}QH %|HwQN w |OwQw u=}QH |x@U=Lt "8 sOk %OwW|t x@U=Lt 31 w 30 \@=wQ j@] =yxv}Ro R= l}Qy (') |HwQN '+(A i) = P A i2A ' (A i ; A i0) ; i; i0 2 f1 ; ::: ; mg (30) '(A i) = P A i2A ' (A i0 ; A i) ; i; i0 2 f1 ; ::: ; mg (31) o %CU= Q}R KQW x@ l}vmD u}= |=QH= pL=Qt [24]"OQ}o|t CQwY =yxv}Ro pt=m l}D}Qm l}vmD R= pw= sOk Ovv=ty 'T}QD=t u}= %s}tYD T}QD=t p}mWD "1 sOk "OwW |t p}mWD13 | x]@=Q =@ j@=]t w l}vmD j}Q] R= =yXN=W uRw Q=DWwv u}= QO %=yXN=W uRw u}}aD "2 sOk &CU= xOW x@U=Lt CRITIC |xv=DU; w (P) K}HQD |xv=DU; '(Q) |Dw=iD|@ |xv=DU; %=yxv=DU; u}}aD "3 sOk ?=Dm R= j}kLD u}= QO =yQDt=Q=B "OwW|t XNWt xOvQ}os}tYD \UwD (V ) OQ &CU= xOW xDiQo [25] (MADM) xDUUo |xYN=WOvJ |Q}os}tYD |=yl}vmD =yxv}Ro R= l} Qy Xr=N u=}QH sOk u}= QO %Xr=N u=}QH |x@U=Lt "9 sOk %O};|t CUO x@ 32 |x]@=Q R= ' (A i) = '+(A i) '(A i) ; i = 1 ; ::: ; m (32) %PAMSSEM I l}vmD T=U= Q@ =yxv}Ro |RH |Ov@x@DQ "10 sOk PAMSSEMl}vmDj}Q]R=|RH|Ov@x@DQ'|HwQNw|OwQw|=yu=}QHT=U=Q@ %Qo= 'Ow@ Oy=wN QDy@ Ai0 |xv}Ro R= Ai |xv}Ro '33 |x]@=Q j@] "OQ}o|t s=Hv= I (32) (A i ; A i0) = m P i=1 A i0( m P i0=1 A i0 j(A i ; A i0):fj(A i)):fj(A i0) (23) Q@=Q@ w OvDUy xDUUo p=tDL= |r=oJ `@=wD fj(Ai0) w fj(Ai) Q}O=kt u; QO xm 25 w 24 \@=wQ T=U=Q@ R}v j(Ai; Ai0) XN=W Q=Okt "OvwW|t ZQi 1 =@ %OwW|t u}}aD (A i ; A i0) = m P i=1 A i0( m P i0=1 A i0 j(A i ; A i0):fj(A i)):fj(A i0) (23) (23) Q@=Q@ w OvDUy xDUUo p=tDL= |r=oJ `@=wD fj(Ai0) w fj(Ai) Q}O=kt u; QO xm 25 w 24 \@=wQ T=U=Q@ R}v j(Ai; Ai0) XN=W Q=Okt "OvwW|t ZQi 1 =@ %OwW|t u}}aD Q@=Q@ w OvDUy xDUUo p=tDL= |r=oJ `@=wD fj(Ai0) w fj(Ai) Q}O=kt u; QO xm 25 w 24 \@=wQ T=U=Q@ R}v j(Ai; Ai0) XN=W Q=Okt "OvwW|t ZQi 1 =@ %OwW|t u}}aD A i P A i0 if 8 > > < > > : A i P + A i0 and A i P A i0 A i P + A i0 and A i I A i0 A i I + A i0 and A i P A i0 (33) (33) A i P A i0 if < > > : A i P + A i0 and A i I A i0 A i I + A i0 and A i P A i0 (33) %PAMSSEM II l}vmD T=U= Q@ =yxv}Ro |}=yv |Ov@x@DQ "11 sOk Ai0 xv}Ro R= Ai xv}Ro '34 |x]@=Q j@] w Xr=N u=}QH x@ xHwD =@ l}vmD u}= QO %Qo= 'Ow@ Oy=wN QDy@ A i P II A i0 if ' (A i) > ' (A i0) (34) j(A i ; A i0) = 8 > > < > > : 0 if j  Pj jPj Pjqj if Pj < j < qj ; Pj  qj  0 1 if j  qj (24) j = Kj(A i) Kj(A i0) (25) 26|x]@=QR=xO=iDU==@=yxv}Rou=}tj@=]DXN=W%j@=]DXN=Wu}}aD"5sOk k O @ j(A i ; A i0) = 8 > > < > > : 0 if j  Pj jPj Pjqj if Pj < j < qj ; Pj  qj  0 1 if j  qj (24) j = Kj(A i) Kj(A i0) (25) 26|x]@=QR=xO=iDU==@=yxv}Rou=}tj@=]DXN=W%j@=]DXN=Wu}}aD"5sOk %OwW|t u}}aD (24) (25) |D=@U=Lt G}=Dv w xO=O p}rLD "4 =yXN=W w =yxv}Ro "1"4 GvB |Q}oxR=Ov= sDU}U pt=W VywSB u}= Ai |=yxv}Ro 'OW u=}@ QDV}B xm u=vJ %CU= wQOwN C=a]k xv}tR QO |O}rwD CmQW &u}BU=m x}=tQU C}=Oy CmQW %A1 &wQOwN Ovw}B CmQW %A2 &u=R=U=Qi CmQW %A3 &wQOwN R=UOQU CmQW %A4 "xa]k=vO CmQW %A5 QO R}v QwmPt |=yCmQW |Q}oxR=Ov= sDU}U QO |UQQ@ OQwt (Cj) |=yXN=W R= l}Qy |=Q@ (Cj) =yXN=W |=yxO=O |Qw;`tH R= TB "CU= xOt; 1 pwOH |=yVN@ QO xm OwW|t |R=UxO=}B 1 pmW VywSB swO s=o '(Ai) =yxv}Ro "CN=OQB s}y=wN u; x@ |Oa@ C(A i ; A i0) = n P j=1 j(A i ; A i0): Wj ; i ; i0 2 f1 ; ::: ; mg (26) (26) R= R}v =yxv}Ro u=}t j@=]D sOa XN=W %j@=]D sOa XN=W u}}aD "6 sOk %OwW|t x@U=Lt 28 w 27 |x]@=Q D (A i ; A i0) = P A i (P A i0 Dj(A i ; A i0):fj(A i0)):fj(A i) (27) (27) 8 > > < > > : 1 if j  Vj  j+pj Vjpj  if Vj < j < pj ; Vj > pj 0 if j  pj (28) (28) 29|x]@=QT=U=Q@|}x@DQ=Qi|xHQO'sOku}=QO%|}x@DQ=QixHQOu}}aD"7sOk %OwW|t u}}aD CRITIC l}vmD T=U= Q@ =yXN=W uRw u}}aD "2"4 CRITIC l}vmD T=U= Q@ =yXN=W uRw u}}aD "2"4 CmQWGvBR=Q_vOQwt|=yxO=O'=yXN=Ww=yxv}Ro|}=U=vWR=TBVN@u}=QO |Qw;`tH |=yxO=O T=U= Q@ "CU= xOW |Qw;`tH |v=O}t CQwYx@ QwmPt |O}rwD "OQ}PB|t s=Hv= s}tYD T}QD=t p}mWD |va} CRITIC l}vmD R= sOk u}rw= xOW ' (A i ; A i0) = C(A i ; A i0)  Qn j=1 1 Dj3(A i ; A i0)  ; 0  '(A i ; A i0)  1 (29) ' (A i ; A i0) = C(A i ; A i0)  CmQWGvBR=Q_vOQwt|=yxO=O'=yXN=Ww=yxv}Ro|}=U=vWR=TBVN@u}=QO |Qw;`tH |=yxO=O T=U= Q@ "CU= xOW |Qw;`tH |v=O}t CQwYx@ QwmPt |O}rwD "OQ}PB|t s=Hv= s}tYD T}QD=t p}mWD |va} CRITIC l}vmD R= sOk u}rw= xOW (29) 20 2 |xQ=tW '381 |xQwO '1401 u=DUtR h}QW C}Q}Ot w `}=vY |UOvyt |xrLQt QO =yXN=W uRw "OyO|t u=Wv =Q |FrFt |R=i s}tYD T}QD=t CUw}B |U=}kt|@ C}Y=N uDiQo Q_v QO =@ w CRITIC l}vmD R= xO=iDU= =@ |r@k QO 10 pwOH QO u=Rw= u}= |xOW |R=i G}=Dv xm Ot; CUO x@ (Pn j=1 wj = 1) "CU= xOt; CUw}B (V ) OQ |xv=DU; w (P) K}HQD |xv=DU; '(Q) |Dw=iD|@ |xv=DU; '3 sOk QO xDUUo |xYN=WOvJ |=yl}vmD ?=Dm T=U= Q@ u; G}=Dv xm OwW|t u}}aD CUw}B VN@ QO 12 pwOH "CU= xOW xOQw; 11 pwOH QO [25] (MADM) T=U= Q@ 4 sOk QO "CU= |FrFt |R=i CQwYx@ V w P 'Q |=yQDt=Q=B pt=W R}v =} |}xDUy |Ov@x@DQ VwQ Excel Q=Ri=sQv R= xO=iDU= =@ w 25 =D 23 \@=wQ "CUw}B QO 13 pwOH CU= xOt; CUO x@ |rLt |}x@DQ=Qi T}QD=t 17'|RmQt |}x@DQ=Qi T}QD=t ?Q[ pY=L R= xO=iDU= =@ 26 |x]@=Q j@] 5  sOk QO x@ CUw}B QO 14 pwOH 'XN=W Qy xOW |R=i u=Rw= T}QD=t QO XN=W Qy p}mWD CUw}B QO 15 pwOH j@=]t |R=i j@=]D T}QD=t ,=D}=yv "O};|t CUO =@ Qw_vt u}= |=Q@ "OUQ|t j@=]D sOa XN=W u}}aD x@ C@wv 6 sOk QO "OwW|t =} |}xDUy |Ov@x@DQ VwQ R= Dj(Ai; Ai0) XN=W =OD@= 28 |x]@=Q R= xO=iDU= sOa XN=W uOQw; CUO x@ |=Q@ "CUw}B QO 16 pwOH O};|t CUO x@ |RmQt RmQt VwQ R= Qw_vt u}= |=Q@ "OvwW p}O@D |a]k O=Oa= x@ |R=i O=Oa= O}=@ j@=]D %OwW|t xO=iDU= 18pkF "|Q}oxR=Ov= sDU}U |=yXN=W "1 pwOH C}@wr]t |Q=YDN= Ctqa XN=W |ivt C1 R&R C@Ft C2 Cg C@Ft C3 Cgk |ivt C4 BIAS C@Ft C5 NDC C@Ft C6 R2 2 |xQ=tW '381 |xQwO '1401 u=DUtR h}QW 2 |xQ=tW '381 |xQwO '1401 u=DUtR h}QW (V ) OQ |xv=DU; w (P) K}HQD |xv=DU; '(Q) |Dw=iD|@ |xv=DU; '3 sOk QO xDUUo |xYN=WOvJ |=yl}vmD ?=Dm T=U= Q@ u; G}=Dv xm OwW|t u}}aD CUw}B VN@ QO 12 pwOH "CU= xOW xOQw; 11 pwOH QO [25] (MADM) T=U= Q@ 4 sOk QO "CU= |FrFt |R=i CQwYx@ V w P 'Q |=yQDt=Q=B pt=W R}v =} |}xDUy |Ov@x@DQ VwQ Excel Q=Ri=sQv R= xO=iDU= =@ w 25 =D 23 \@=wQ "CUw}B QO 13 pwOH CU= xOt; CUO x@ |rLt |}x@DQ=Qi T}QD=t 17'|RmQt |}x@DQ=Qi T}QD=t ?Q[ pY=L R= xO=iDU= =@ 26 |x]@=Q j@] 5  sOk QO x@ CUw}B QO 14 pwOH 'XN=W Qy xOW |R=i u=Rw= T}QD=t QO XN=W Qy p}mWD CUw}B QO 15 pwOH j@=]t |R=i j@=]D T}QD=t ,=D}=yv "O};|t CUO =@ Qw_vt u}= |=Q@ "OUQ|t j@=]D sOa XN=W u}}aD x@ C@wv 6 sOk QO "OwW|t =} |}xDUy |Ov@x@DQ VwQ R= Dj(Ai; Ai0) XN=W =OD@= 28 |x]@=Q R= xO=iDU= sOa XN=W uOQw; CUO x@ |=Q@ "CUw}B QO 16 pwOH O};|t CUO x@ |RmQt RmQt VwQ R= Qw_vt u}= |=Q@ "OvwW p}O@D |a]k O=Oa= x@ |R=i O=Oa= O}=@ j@=]D %OwW|t xO=iDU= 18pkF x1 m = L+M+U 3 : x2 m = L+2M+U 4 : x3 m = L+4M+U 6 Crispnumber = z = Max (x1 m ; x2 m ; x3 m) (35) "CUw}B QO 17 pwOH Ov=xOW p}O@D |a]k O=Oa= x@ |R=i O=Oa= 35 |x]@=Q j@] sOa XN=W Q}O=kt u}vJty w Dj(Ai; Ai0) XN=W |xOW |R=i|O G}=Dv "CU= xOt; CUw}B QO 19 w 18 pwOH QO ?}DQD x@ 27 |x]@=Q j@] j@=]D TB xm OwW x@U=Lt 29 |x]@=Q =yxv}Ro |}x@DQ=Qi |xHQO O}=@ 7 sOk QO "OwW|t p}mWD 20 pwOH C=@U=Lt s=Hv= R= 31 w 30 \@=wQ T=U= Q@ w 8 sOk QO '=yxv}Ro |}x@DQ=Qi xHQO u}}aD R= TB "CUw}B QO 17 pwOH Ov=xOW p}O@D |a]k O=Oa= x@ |R=i O=Oa= 35 |x]@=Q j@] sOa XN=W Q}O=kt u}vJty w Dj(Ai; Ai0) XN=W |xOW |R=i|O G}=Dv "CU= xOt; CUw}B QO 19 w 18 pwOH QO ?}DQD x@ 27 |x]@=Q j@] j@=]D TB xm OwW x@U=Lt 29 |x]@=Q =yxv}Ro |}x@DQ=Qi |xHQO O}=@ 7 sOk QO "OwW|t p}mWD 20 pwOH C=@U=Lt s=Hv= R= 31 w 30 \@=wQ T=U= Q@ w 8 sOk QO '=yxv}Ro |}x@DQ=Qi xHQO u}}aD R= TB p=Ft Qw] x@ "CU= xOt; CUO x@ =yxv}Ro R= l} Qy |HwQN w |OwQw |=yu=}QH %s}Q=O A1 xv}Ro |=Q@ %|OwQw u=}QH "CUw}B QO 17 pwOH Ov=xOW p}O@D |a]k O=Oa= x@ |R=i O=Oa= 35 |x]@=Q j@]  w}B Q pw H p} @ | @ |R | @Q j@ sOa XN=W Q}O=kt u}vJty w Dj(Ai; Ai0) XN=W |xOW |R=i|O G}=Dv "CU= xOt; CUw}B QO 19 w 18 pwOH QO ?}DQD x@ 27 |x]@=Q j@] j@=]D TB xm OwW x@U=Lt 29 |x]@=Q =yxv}Ro |}x@DQ=Qi |xHQO O}=@ 7 sOk QO "OwW|t p}mWD 20 pwOH C=@U=Lt s=Hv= R= s 31 w 30 \@=wQ T=U= Q@ w 8 sOk QO '=yxv}Ro |}x@DQ=Qi xHQO u}}aD R= TB p=Ft Qw] x@ "CU= xOt; CUO x@ =yxv}Ro R= l} Qy |HwQN w |OwQw |=yu=}QH %s}Q=O A1 xv}Ro |=Q@ %|Ow w u= H '+(A1) = 0 + 0 + 0 + 0 = 0 '(A1) = 0=733 + 0 + 0 + 1=031 = 1=764 xOt; 21 pwOH QO u; G}=Dv xm OwW|t pta q=@ VwQ x@ R}v =yxv}Ro Q}=U |=Q@ "CU= Qy Xr=N u=}QH |Oa@ sOk QO '=yxv}Ro Xr=N u=}QH |x@U=Lt x@ xHwD =@ %OwW|t x@U=Lt 32 |x]@=Q j@] R}v =yv; R= l} '1 = 0 1=764 = 1=764 '2 = 1=764 0 = 1=764 '3 = 0=611 0 = 0=611 '4 = 0 2=429 = 2=429 '5 = 1=818 0 = 1=818 |R=i PAMSSEM l}vmD T=U= Q@ =yxv}Ro |Ov@x@DQ "3"4 sOk QO "CU= KwQWt |R=Uxa]k |=yCmQW |}=yv |Ov@x@DQ pL=Qt VN@ u}= QO QO s}tYD T}QD=t '|FrFt |R=i O=Oa= T=U= Q@ 'PAMSSEM l}vmD R= pw= QO 9 pwOH "OwW|t p}O@D C}a]k sOa \}=QW QO s}tYD T}QD=t x@ |a]k \}=QW 21 """ |R=Uxa]k |=yCmQW |Q}oxR=Ov=sDU}U |Ov@x@DQ x}=tQU C}=Oy 'u=R=U=Qi |=yCmQW "OQ=O Q=Qk swO |x@DQ QO 1 764 Xr=N u=}QH w 1 764 '0 611 Xr=N |=yu=}QH =@ ?}DQD x@ wQOwN R=UOQU w u}BU=m |OQ@Q=m |=yO=yvW}B 'G}=Dv u}= T=U= Q@ "OvQ}o|t Q=Qk |Oa@ |=yx@DQ QO 2 249 u=oOvvmu}t-=D K]U QO =Q MSA xm |R=UwQOwN CavY QO C}i}m u=Q}Ot |=Q@ %CU= Q}R KQW x@ Ovvm|t |R=UxO=}B 'CmQW |x@DQ x@ xHwD =@ O}=@ 'QwmPt |=yCmQW R= l} Qy |i}m u=Q}Ot  xOW |R=UxO=}B QDq=@ x@DQ l} =@ |DmQW QO xm MSA |D=}rta |=yptar=QwDUO Xr=N u=}QH =@ xm wQOwN R=UOQU CmQW p=Ft |=Q@ "Ovvm |R=Uwor= 'CU= ha[ \=kv |xU}=kt w |UQQ@ x@ O}=@ 'OQ=O Q=Qk |@=}RQ= QN; |x@DQ QO |ivt |OwaY Q}U =Q}R &OR=OQB@ u}BU=m x}=tQU C}=Oy CmQW x@ C@Uv OwN Cwk w |] xrLQt x@ xrLQt O}=@ ?wr]t |Q}oxR=Ov= sDU}U |R=UxO=}B QO CiQW}B w |] xa]k=vO CmQW wor= |Q}oxR=Ov= sDU}U x@ uO}UQ =D O}=@ OvwQ u}= "OwW &OwW Q@ RmQtD =@ 19 (R&D) xaUwD w j}kLD |=yOL=w O=H}= x@ O}=@ C}i}m u=Q}Ot  |Q}oQ=mx@=@ R&D|=yOL=w"OvR=OQB@u;|=yC}r=aiVQDUow MSA|xRwL R= |Q}owor= w |Q}o=Qi =@ Ovv=wD|t MSA |xRwL QO xQ@N w XYNDt O=Qi= w <=kDQ= Q}Ut '|R=UwQOwN CavY QO =}vO |Q}oxR=Ov= |=ysDU}U u}QDxDiQW}B &Ovvm Q=wty =Q |rN=O |=yCmQW CiQW}B QwmPt |=yCmQW Ovv=wD|t 'wQOwN C=a]k u=}QDWt u=wvax@ =B}=U w wQOwNu=Q}=  Q_v OQwt |=yOQ=Ov=DU= C}=aQ w OwN |Q}oxR=Ov= sDU}U K]U <=kDQ= x@ sRrt =Q "Ovvm |D=}rta V}B R= V}@ =Q C}i}m u}t[D w |UQR=@ |=yOv}=Qi w xOQm A5 > A2 > A3 > A1 > A4 A5 > A2 > A3 > A1 > A4 |Q}oxH}Dv "6 x}RHD'OW=@u}}=Bu;R=pY=Ls=kQ=C}i}mxH}DvQOw|Q}oxR=Ov=sDU}UC}i}mQo= CUQO=v C=t}tYD P=ND= u=mt= w CW=O Oy=wNv |@U=vt Q=@Da= Ov}=Qi p}rLD w |W=v |=yxv}Ry xm CU= |y}O@ w OQ=O OwHw VQ}PB sOa =} VQ}PB =@ x]@=Q QO |=Q@ =yv; Q}O=kt w QF-wt |=yXN=W 'MSA C}ty= x@ xHwD =@ "OwQ|t q=@ u; R= 'R&R |=yXN=W u=R}t xm CiQo xH}Dv u=wD|t '2 pwOH xa]k=vO CmQW xHwD =@ "OvQ=O |Q}oxR=Ov= |=ysDU}U |@=}RQ= C}i}m Q@ |O=}R Q}F-=D Cgk w Cg Cgk w Cg w CU= |Q}oxR=Ov= sDU}U CLY w CkO Ov};Q@ R&R xm u}= x@ xmu=vJ "OQ@ |B =yv; Q}F-=D w C}ty= x@ u=wD|t 'Ovvm|t |Q}oxR=Ov= =Q sDU}U |}=v=wD Cgk w Cg Q=Okt u}QDW}@ w R&R Q=Okt u}QDtm 'OwW|t xOy=Wt 2 pwOH QO "CU= xOW xDN=vW QDQ@ |xv}Ro xm CU= xa]k=vO CmQW sHvB |xv}Ro x@ \w@Qt R}v =yxv}Ro |}=yv |Ov@x@DQ Q@ =yXN=W uRw u}vJty V w P 'Q |=yQDt=Q=B u=R}t |Q}oxH}Dv "6 VywSB |=yO=yvW}B w EL@ '=yxDi=} "5 R= |Q=OQ@xQy@ C}r@=k w xOW G=QNDU= G}=Dv x@ |WywSB pta Qy Q=@Da= |rmQw]x@ 'VywSB |xv}tR w `w[wt KQW pt=W VywSB C=}rm '=OD@= QO "OQ=O |oDU@ u; wQtrk w Cq=wU 'h=Oy= 'CU=yv; x@ MU=B |wHwCUH QO jkLt xm |Dq=-wU R= TB VywSB u}= QO "CU= xDiQo Q=Qk |UQQ@ OQwt VywSB |v=mt w |v=tR |}=U=vW ut[ 'xOt; CUO x@ C=aq]= p}rLD w x}RHD w |Ov@xDUO '|Qw;`tH x@ 'CRITIC VwQ R= xO=iDU= =@ '|Q}oxR=Ov= |=ysDU}U Q@ QF-wt |=yXN=W |Ov@x@DQ'PAMSSEMVwQR=xO=iDU==@,=D}=yv"OWxDN=OQB=yXN=W|yOuRw "CiQ}PB s=Hv= wQOwN C=a]k xOvvmO}rwD CmQW GvB |Q}oxR=Ov= |=ysDU}U Xr=N u=}QH =@ xa]k =vO CmQW 'p@k VN@ QO xOt; CUO x@ G}=Dv x@ xHwD =@ =@ wQOwN Ovw}B CmQW u; R= Oa@ w |Q}oxR=Ov= sDU}U u}QD?U=vt |=Q=O 1 818 22 "|FrFt |R=i s}tYD T}QD=t "9 pwOH "=yXN=W |R=i u=Rw= "10 pwOH "V w P 'Q |=yxv=DU; Q}O=kt "11 pwOH C6 C5 C4 C3 C2 C1 =yQDt=Q=B 0 02 1 0 001 0 09 0 11 0 35 V 0 015 2 0 001 0 08 0 1 0 33 P 0 005 3 0 0 02 0 08 0 15 Q "V w P 'Q |xOW |R=i |=yQDt=Q=B "12 pwOH "|}xDUy |Ov@x@DQ VwQ T=U= Q@ |rLt |}x@DQ=Qi T}QD=t "13 pwOH "|FrFt |R=i s}tYD T}QD=t "9 pwOH "=yXN=W |R=i u=Rw= "10 pwOH "V w P 'Q |=yxv=DU; Q}O=kt "11 pwOH C6 C5 C4 C3 C2 C1 =yQDt=Q=B 0 02 1 0 001 0 09 0 11 0 35 V 0 015 2 0 001 0 08 0 1 0 33 P 0 005 3 0 0 02 0 08 0 15 Q "V w P 'Q |xOW |R=i |=yQDt=Q=B "12 pwOH "|FrFt |R=i s}tYD T}QD=t "9 pwOH "=yXN=W |R=i u=Rw= "10 pwOH "=yXN=W |R=i u=Rw= "10 pwOH "V w P 'Q |=yxv=DU; Q}O=kt "11 pwOH C6 C5 C4 C3 C2 C1 =yQDt=Q=B 0 02 1 0 001 0 09 0 11 0 35 V 0 015 2 0 001 0 08 0 1 0 33 P 0 005 3 0 0 02 0 08 0 15 Q "V w P 'Q |xOW |R=i |=yQDt=Q=B "12 pwOH "|}xDUy |Ov@x@DQ VwQ T=U= Q@ |rLt |}x@DQ=Qi T}QD=t "13 pwOH 23 23 """ |R=Uxa]k |=yCmQW |Q}oxR=Ov=sDU}U |Ov@x@DQ "|}x@DQ=Qi Q}O=kt QO =yXN=W u=Rw= ?Q[ pY=L G}=Dv "14 pwOH 24 "xOW |R=i|O j@=]D XN=W "17 pwOH "  Dj(Ai; Ai0) xOW |R=i|O G}=Dv "18 pwOH "|R=i j@=]D T}QD=t "15 pwOH "|RmQt |Ov@x@DQ VwQ G}=Dv "16 pwOH 25 25 "j@=]D sOa XN=W "19 pwOH "=yxv}Ro |}x@DQ=Qi xHQO "20 pwOH A5 A4 A3 A2 A1 0 0 0 0  A1 0 1 031 0  0 733 A2 0 0 611  0 0 A3 0  0 0 0 A4  0 787 0 0 1 031 A5 "=yxv}Ro |HwQN w |OwQw |=yu=}QH "21 pwOH ''+ =yxv}Ro 1 764 0 A1 0 1 764 A2 0 0 611 A3 2 429 0 A4 0 1 818 A5 "=yxv}Ro |}x@DQ=Qi xHQO "20 pwOH A5 A4 A3 A2 A1 0 0 0 0  A1 0 1 031 0  0 733 A2 0 0 611  0 0 A3 0  0 0 0 A4  0 787 0 0 1 031 A5 "=yxv}Ro |HwQN w |OwQw |=yu=}QH "21 pwOH ''+ =yxv}Ro 1 764 0 A1 0 1 764 A2 0 0 611 A3 2 429 0 A4 0 1 818 A5 w u=oOvvmu}t-=D u}QDy@ w Q=R=@ u}QDy@ ?=NDv= p=@vO x@ u=R=UwQOwN xRwQt=  MADM |=yl}vmD Qo}O R= xO=iDU= "OvDUy ?wr]t C=tON u=oOvyOx=Q= Ov=wD|t CiQ Q=m x@ |O=yvW}B pOt u=wvax@ VywSB u}= QO xm xJv; Ovv=t ltm wQOwN C=a]k u=oOvvmu}t-=D |Q}oxR=Ov= sDU}U u}QD?U=vt ?=NDv= QO x@ |yOuRw |=Q@ |R=i CRITIC l}vmD R= xO=iDU= 'p=Ft Qw] x@ "Ovm |v=}=W &OW=@ G}=Dv Q=@Da= w CkO Ow@y@ ?Hwt Ov=wD|t =yXN=W w u=oOvvmu}t-=D u}QDy@ w Q=R=@ u}QDy@ ?=NDv= p=@vO x@ u=R=UwQOwN xRwQt=  MADM |=yl}vmD Qo}O R= xO=iDU= "OvDUy ?wr]t C=tON u=oOvyOx=Q= Ov=wD|t CiQ Q=m x@ |O=yvW}B pOt u=wvax@ VywSB u}= QO xm xJv; Ovv=t ltm wQOwN C=a]k u=oOvvmu}t-=D |Q}oxR=Ov= sDU}U u}QD?U=vt ?=NDv= QO x@ |yOuRw |=Q@ |R=i CRITIC l}vmD R= xO=iDU= 'p=Ft Qw] x@ "Ovm |v=}=W &OW=@ G}=Dv Q=@Da= w CkO Ow@y@ ?Hwt Ov=wD|t =yXN=W w `}=vY QO hrDNt |=y|w=m OQwt QO VywSB u}= OQm}wQ OwW|t O=yvW}B  x@ CU= Q=OQwNQ@ |}xS}w C}ty= R= =yv; QO |Q}oxR=Ov= sDU}U xm |}=yu=tR=U &OwW |R=UxO=}B |R=UwQOwN CavY RH |=ysDU}U|@=}RQ=w|Ov@x@DQ|=Q@ 20=yxO=O|WWwBp}rLD|=ypOtR=xO=iDU=  &""" w |QDUm=N 'l}iwUwQDwv Cr=L C}a]k sOa \}=QW QO |Q}oxR=Ov= C=W}=tR; R= O=vDU= p@=k w Q@Dat 'j}kO G}=Dv Ci=}QO |=Q@ OwW|t O=yvW}B  xmr@ OwW xO=iDU= ?Dm w Cq=kt QO OwHwt C=aq]= w =yxO=O R= =yvDxv 'j}kLD MADM |=yl}vmD |=yQDt=Q=B u}}aD |=Q@ u=oQ@N |xt=vVUQB j}Q] R= "OwW xO=iDU= CUwQ@wQ |}=yC}OwOLt w CqmWt =@ VywSB Qy CU= srUt xJv; "Ov=xOw@ QF-wt u}= s=Hv= Ov}=Qi "Ovm|t p=mW= Q=JO hOy x@ uO}WN@ C}at=H QO =Q jkLt xm OQwt EL@t uOw@ |YYND x@ xHwD =@ u=wD|t xm Ow@ xH=wt |DqmWt =@ R}v j}kLD VwQ |=yQDt=Q=B |=Q@ K}LY C=aq]= x@ |UQDUO sOa 'Cq=wU O=}OR= x@ xar=]t p=tDL= ?}Q[ w xv}tR u}= QO |r@k C=ar=]t s=Hv= sOa x@ xHwD =@ PAMSSEM "OQm xQ=W= MU=B QO =]N %OwW|t O=yvW}B 'xOv}; u=QoVywSB x@ p}P |D=ar=]t OQ=wt Q@ RmQtD w xHwD =yCWwv=B 1. References `@=vt 1. Chen, L. and Chang, C. \Approaches for measure- ment system analysis considering randomness and fuzzi- ness", International Journal of Fuzzy System Applica- tions (IJFSA), 9(2), pp. 98-131 (2020). 15. Li, Z.H., Yang, T. and Huang, C.H. SH. \An improved approach for water quality evaluation: TOPSIS-based in- formative weighting and ranking (TIWR) approach", In Ecological Indicators, 89, pp. 356-364 (2017). 2. Goodarzi, A., Dastoor Niko, N., Taheri, A. and et al., Analysis of the System of Measuring Concepts and Im- plementation Methods, In Sapco Publications, 2th Edn., Tehran, (In Persian) (2003). 16. Shahbandehzadeh, H. and Vali, M. \Selection of the op- timal method of nal waste disposal in Tehran using Arreste technique with fuzzy data", In the Second Inter- national Conference on Industrial Management, (20-31 April), Mazandaran (2017). 3. Shewhart, W., Economic Control of Quality of Manu- factured Product, D. Van Nostrand Company, Inc, New York (1931). 4. Automotive Industry Action Group (AIAG). \Measure- ment systems analysis reference manual", American So- ciety for Quality Control, 2th Edn., Chrysler, Ford, Gen- eral Motors Supplier Quality Requirements Task Force, USA (1995). 17. Saikaew, C. \An implementation of measurement system analysis for assessment of machine and part variations in turning operation", In Elsevier, Measurement, 118, pp. 246-252 (2018). 18. Acevedo, C., Rojas, I., Gonzalez, P. and et al. \Multiple- response optimization of open graded friction coursere- inforced with bers through CRITIC-WASPAS based on taguchi methodology", In Construction and Building Materials, 233, pp. 117274-117290 (2019). 5. Kazemi, A., Haleh H., Hajipour, V. and et al. \Devel- oping a method for increasing accuracy and precision in measurement system analysis: a fuzzy approach", In Journal of Industrial Engineering, 6, pp. 25-32, (In Per- sian) (2010). 6. Moheb-Alizadeh, H. \Capability analysis of the variable measurement system with fuzzy data", In Applied Math- ematical Modelling, 38(19-20), pp. 4559-4573 (2013). 19. Zeng, S.H., Chen, SH. M. and Fan, K. Y. \Interval- valued intuitionistic fuzzy multiple attribute decision making based on nonlinear programming methodology and topsis method", In Information Sciences, 506, pp. 424-442 (2019). 7. Kuo, C.C. and Huang, P.J. \Repeatability and repro- ducibility study of thin lm optical measurement sys- tem", In Optik - International Journal for Light and Electron Optics, 124(18), pp. 3489-3493 (2013). 20. Doshi, J.A. and Desai, D.A. \Measurement system anal- ysis for continuous quality improvement in automobile SMEs: multiple case study", In Total Quality Man- agement & Business Excellence, 30(5-6), pp. 626-640 (2019). 8. |Q}oxH}Dv "6 measurement systems analysis 2. multi criteria decision making 3. multi objective decision making 4. multi attribute decision making 5. criteria importance through intercriteria correlation 6. physical asset management strategy execution enforcement mechanism nvH C}i}m pQDvm xwQo |=[a= "7 8. American society for quality control (ASQC) 9. gage Repeatability & reproducibility 10. VIKOR 11. analytic hierarchy process 12. open-graded friction courses 13. polypropylene 14. non-linear programing "xa]k =vO w wQOwN R=UOQU 'u=R=U=Qi 'wQOwNOvw}B 'u}BU=m x}=tQU C}=Oy "15 16. number of distinct categories 17. core ranking method 18. center of gravity 19. research and development 20. data envelopment analysis =yCWwv=B 1. measurement systems analysis 2. multi criteria decision making 3. multi objective decision making 4. multi attribute decision making 5. criteria importance through intercriteria correlation 6. physical asset management strategy execution enforcement mechanism nvH C}i}m pQDvm xwQo |=[a= "7 8. American society for quality control (ASQC) 9. gage Repeatability & reproducibility 10. VIKOR 11. analytic hierarchy process 12. open-graded friction courses 13. polypropylene 14. non-linear programing "xa]k =vO w wQOwN R=UOQU 'u=R=U=Qi 'wQOwNOvw}B 'u}BU=m x}=tQU C}=Oy "15 16. number of distinct categories 17. core ranking method 18. center of gravity 19. research and development 20. data envelopment analysis =yCWwv=B 1. measurement systems analysis 2. multi criteria decision making 3. multi objective decision making 4. multi attribute decision making 5. criteria importance through intercriteria correlation 6. physical asset management strategy execution enforcement mechanism nvH C}i}m pQDvm xwQo |=[a= "7 8. American society for quality control (ASQC) 9. gage Repeatability & reproducibility 10. VIKOR 11. analytic hierarchy process 12. open-graded friction courses 13. polypropylene 14. non-linear programing "xa]k =vO w wQOwN R=UOQU 'u=R=U=Qi 'wQOwNOvw}B 'u}BU=m x}=tQU C}=Oy "15 16. number of distinct categories 17. core ranking method 18. center of gravity 19. research and development 20. data envelopment analysis nvH C}i}m pQDvm xwQo |=[a= "7 nvH C}i}m pQDvm xwQo |=[a= "7 8. American society for quality control (ASQC) H } } 8. American society for quality control (ASQC) 26 26 14. Alinezad, A., Amir, A. and Ziamanesh, M. \Combina- tion VIKOR modeland measurement systems analysis (MSA)", In Journal of Industrial Strategic Management, 2, pp. 52-63 (2017). References `@=vt Peruchi, R.S., Balestrassi, P.P., Paiva, A.P. and et al. \New multi variate gage R&R method for correlated characteristics", In International Journal of Production Economics, 144(1), pp. 301-315 (2013). 21. Sharma, M., Sahni S.P. and Sharma, S. \Validating a destructive measurement system using Gauge R&R - a case study", In Engineering Management in Production and Services, 11(4), pp. 34-42 (2019). 9. Balestrassi, P.P., Peruchi, R.S., Paiva, A.P. and et al. \Weighted approach for multivariate analysis of variance in measurement system analysis", In Precision Engineer- ing, 38(3), pp. 651-658 (2014). 22. Doaly, C.O., Sriwana, I.K. and Salomon, L. \Analysis the measurement quality system of clearence tappet us- ing measurement system analysis on motorcycle man- ufacturing company", In IOP Conf. Ser: Mater. Sci. Eng.852 012124 (2020). 10. Ciani, L., Zanobini, A., Sereni, B. and et al. \Repeata- bility and reproducibility techniques for the analysisof measurement systems", In Elsevier Measurement, 86, pp. 125-132 (2016). 11. Avakh Darestani, S. and Laklayeh, G. \Development of a fuzzy model of measurement system analysis consider- ing the stability of measurement tools", In Sixth Inter- national Conference on Engineering and Art, Rasht, (In Persian) (2016). 23. Diakoulaki, D., Mavrotas, G. and Papayannakis, L. \De- termining objective weights in multiple criteria prob- lems: The critic method", In Computers & Operations Research, 22(7), pp. 763-770 (1995). 12. Robson, B.D.P., Rogerio, S.P. and Anderson, P.P. \Com- bining scott-knott and GR&R methods to identify spe- cial causes of variation", In Elsevier, Measurement, 82, pp. 135-144 (2016). 24. Alinezhad, A. and Khalili, J. \New techniques in mul- tidisciplinary decisions", In Amirkabir University Ji- had Publications, 3th Edn, pp. 96, Tehran (In Persian) (2017). 13. Yuan, Q., Yin, X., Yan, W. and et al. \A new approach for the capability analysis based on measurement system analysis: a case study for coal quality detection equip- ment", Int. J. Appl. Decis. Sci, 9(1), pp. 17-38 (2016). 25. Hamidi, N., MADM Discrete Multi-Index Decision Mak- ing Techniques, In Mehregan Danesh Publications, Tehran, (In Persian) (2020). 27
https://openalex.org/W3120359735
https://europepmc.org/articles/pmc7777219?pdf=render
English
null
Influences of service characteristics and older people’s attributes on outcomes from direct payments
BMC geriatrics
2,021
cc-by
15,298
Davey BMC Geriatrics (2021) 21:1 https://doi.org/10.1186/s12877-020-01943-8 Davey BMC Geriatrics (2021) 21:1 https://doi.org/10.1186/s12877-020-01943-8 Davey BMC Geriatrics (2021) 21:1 https://doi.org/10.1186/s12877-020-01943-8 Open Access Influences of service characteristics and older people’s attributes on outcomes from direct payments Vanessa Davey1, Abstract Background: Direct payments (DPs) are cash-payments that eligible individuals can receive to purchase care services by themselves. DPs are central to current social care policy in England, but their advantages remain controversial. This controversy is partly due to their lack of historical visibility: DPs were deployed in stages, bundled with other policy instruments (first individual budgets, then personal budgets), and amidst increasing budgetary constraints. As a result, little unequivocal evidence is available about the effectiveness of DPs as an instrument for older people’s care. This study aims to partially fill that gap using data obtained during an early evaluation of DP’s that took place between 2005 and 07. Methods: Semi-structured 81 face-to-face interviews with older people (and their proxies) using DPs are analyzed. DPs contribution to outcomes was measured using a standardized utility scale. Data on individual characteristics (dependency, informal support) and received services (types and amount of services) was also gathered. Multiple regression analyses were performed between measured outcome gains and individual and service characteristics. A Poisson log-functional form was selected to account for the low mean and positive skew of outcome gains. Results: Levels of met need compared very favorably to average social care outcomes in the domains of social participation, control over daily living and safety, and user satisfaction was high. Benefit from DPs was particularly affected by the role and function of unpaid care and availability of recruitment support. The freedom to combine funded care packages with self-funded care enhanced the positive impact of the former. The ability to purchase care that deviated from standardized care inputs improved service benefits. Large discrepancies between total care input and that supported through DPs negatively affected outcomes. Conclusions: The results offer clarity regarding the benefit derived from receiving DPs. They also clarify contested aspects of the policy such as the influence of unpaid care, types of care received, funding levels and the role of wider support arrangements. Tangible benefits may results from direct payments but those benefits are highly dependent on policy implementation practices. Implementation of DPs should pay special attention to the balance between DP funded care and unpaid care. Abstract Keywords: Direct payments, Personal budgets, Consumer-directed care, Older people, Social care outcomes Correspondence: vanessa.davey@vhir.org 1Research Fellow, Re-FIT Research Group, Parc Sanitari Pere Virgili & Vall d’Hebrón Institute of Research (VHIR), Barcelona, Spain 2Formerly at Personal Social Services Research Unit (PSSRU), London School of Economics & Political Science (LSE), London, UK Background questioned. While the initial evidence base was drawn from studies of participant direction in the USA [3, 24], ef- forts were made to pilot self-management in a local con- text. The IBSEN study of individual budgets (IBs) (Fig. 1), [25], forerunner to PBs, reported lower psychological well- being in older people receiving IBs, compared to either those receiving standard care or to younger IB holders. Even so, no differences were detected in social care need- related outcomes between older and younger participants. Further analysis, excluding proxy responses, found no dif- ferences even in psychological wellbeing [26–28]. During the past decade social care in England has changed substantially as a result of “personalisation” policies (Fig. 1). These changes are subject to significant criticism [1, 2]. Direct Payments (DPs), cost-equivalent cash pay- ments, are now core routes through which individuals eli- gible for publicly-funded social care can purchase care directly through their “personal” or hypothecated budget (PB). This is a policy drawing on US models of consumer- directed care [3–6], with similarities to recent develop- ments in Australia [7–10] and across Europe [11]. p y g g The conflation of PBs/IBs/DPs, grouped together under the umbrella term “self-directed care”, is problem- atic in reviewing existing data [25, 29]. IBs and PBs fea- ture major changes in assessment and allocation of publicly funded social care, including introduction of supported self-assessment and notional budgets [30]. It is impossible to discern the impact of actual services re- ceived from the impact of how funds are allocated, or how assessment and support planning are handled. PB implementation created significant delays in set-up times for services, increasing service users’ anxieties and impacting on results, particularly among older people [31, 32]. IBs were additionally marred by a “slightly naive attempt to join up funding streams that are very hard to combine” [33]. While alternative options are available to those who prefer not to self-manage (Fig. 1), successive govern- ments have attempted to steer implementation of DPs, placing particular emphasis on uptake among older people [12–17]. Despite this, acceptance of DPs for older people has been slow. The government recently referred to the take-up rate for direct payments for older people as “stubbornly low” [18]. Home care1 remains the mainstay of support for community-dwelling older people, with only 18% of over 65 s receiving a direct payment, versus 40% of younger people supported because of physical disability [19]. 1Home care (also termed ‘domiciliary care’) is care provided at home. Where home care is state-funded, it is arranged through the local au- thority and usually provided by private home care agencies. These agencies recruit and train individuals to provide care per the service users’ support (or ‘care’) plan according to eligible assessed needs. This may include support with personal care, such as washing or dressing; cooking or preparing meals and/ or housekeeping or domestic work. Priority is given to personal care, nutrition and safety needs. 2The pattern of local government in England is complex, with the distribution of functions varying according to the local arrangements. ‘Council’ refers to a council with social services responsibilities which include: London boroughs, Unitary authorities, Shire authorities and Metropolitan councils. Background Yet these figures cover a broad range: the top 5% of councils provide DPs to roughly half of all over 65 s receiving care in the community [19] and a similar proportion of councils2 now spend more per year on DPs to older people than on homecare [20]. This reflects how person- alisation has been used and interpreted differently by dif- ferent actors [21], surpassing previous patterns of social care variation [22]. Existing research is also limited by amalgamation of data on older people that are taking their PB (or IB) as a council-managed budget or a provider-managed budget with those using DPs [25, 27, 31]. PBs managed by local authorities (where the personal budget is “paid to” the council), offer limited participation for recipients in ser- vices they receive [34]. Data on provider-managed bud- gets (also referred to as “Individual Service Funds”) is scarce [34, 35]. Consequently, outcomes data specific to older people in receipt of DPs are extremely limited. The priority given to implement DPs among older people has been questioned. Woolham et al [20, 23] re- cently challenged the sustained promotion of DPs to older people, stating that current policies fail to recognize that “older people may want different things from personal budgets and direct payments to younger people”. This overlooks the fact that it is often the fam- ilies of older people who recognize the possible advan- tages of DPs. Attempting to address these issues, Woolham et al [36] compared the outcomes of DPs to managed budgets (MBs) among older people. Their findings suggest no significant differences in social care outcomes between the service types, although DP recipients scored higher for process outcomes (timing of care and satisfaction with services). Their findings are in line with official data covering all English councils, available since 2016 as part of the Adult Social Care Survey [35]. Such results sug- gest a growing mismatch between the Department of Health’s assertion that “direct payments... lead to a higher quality experience for appropriate users” and the evidence base [11, 37]. An obvious question is: why there is so much disparity between early qualitative studies [25, 38, 39] and more recent quantitative studies? © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Davey BMC Geriatrics (2021) 21:1 Davey BMC Geriatrics (2021) 21:1 Page 2 of 17 Page 2 of 17 Background The controversy is fueled by studies in which the suit- ability of “self-directed care” for older people is Some may argue that DPs were initially offered to those most likely to benefit and as the user base grew those with less to gain were drawn into the pool. Indeed, Page 3 of 17 Davey BMC Geriatrics (2021) 21:1 Fig. 1 Timeline - direct payments to personal health budgets investment roughly equal to 7% of total DP expenditure); to an approach where service users are required to indi- vidually purchase assistance from a selection of available providers [44]. This shift overlooked the once heralded role of DP support in improving outcomes [15]. in early studies of DPs to older people, almost all partici- pants knew about DPs before applying and purposefully requested them [25, 38]. That is clearly different from imposed DP use – an issue raising increasing concern. The incentives for councils to increase uptake of DPs to older people are now such that “practices to promote DPs which work against personalised care” are recog- nised [35]. This hints at the use of DPs primarily for council interests, particularly “in areas where authority- commissioned care is considered poor quality or where the choice of authority-commissioned providers is very limited …” [34, 35]. Much of this stems from efforts to control costs: between 2006 and 2016 the average unit cost for local authority commissioned home care rose only 21% [40, 41], leaving many providers struggling fi- nancially with knock on effects for recruitment and re- tention of staff. This combines with a switch from cost and volume contracts to ‘framework agreements’ for approved providers which secure potential services at a given cost but do not guarantee service volume to pro- viders [30, 42]. This practice creates such risk to pro- viders that many are opting out of council commissioned care [30]. Reduced supply has led to DPs becoming the last available option. pp p g [ ] Further changes in the implementation of DPs, have in- cluded the introduction of pre-paid card schemes with real time auditing of spending (criticized for reducing flexibility) and online PA recruitment platforms. Such de- velopments have been interpreted as circumventing the “need” for DP support, thereby mitigating its cost [44]. Background The latter are not unlike the so called ‘Uber-style’ employ- ment management schemes taking hold in Australia under the National Disability Insurance Scheme self- directed care option [45]. There has since been a signifi- cant shift in the use of PAs: predominant in the early model of DP use, now only around 1/3rd of direct pay- ments users (all ages) employ one or more PA [46]. The potential problems of hiring a PA are continuously over- emphasized [33]. Moreover, conventional homecare agen- cies, once largely disinterested in targeting DP recipients, now actively do so and have been encouraged to diversify to offer PA matching and management services [44]. All these changes to the context in which DPs are being used have gone unrecognized amidst the focus on quantifying whether DPs offer greater benefits than managed budgets (where the local authority organizes care on behalf of the person) for older people. Concerns have also been raised about the way in which DPs seem to have been pursued as a means of cost-cutting. One London council was cited in the Local Government Association Adult Social Care Efficiency re- port [43] as having made savings of £0.9 million by, i) switching from in-house domiciliary care to DPs and ii) requiring that any assistance with managing DPs or recruiting care, be paid for by the individual from their allocated funds. This led to a wave of local policy shifts in DP support, from the existing model where support was offered automatically and free at the point of use from schemes contracted by the local authority (an In the face of so much change in the context in which DPs are provided, there is a pressing need to unpick the, “apparent contradiction between [early] user-level and [re- cent] authority-level data” [7, 35]. To do so requires ex- ploring how outcomes are influenced by individual characteristics, circumstances and care packages (not just the amount but also what is purchased and with what support). Davey BMC Geriatrics (2021) 21:1 Page 4 of 17 Little data has been collected having this potential. Survey data trades off the benefits of greater sample size with the depth of information collected. It also excludes proxy responses [47], thereby excluding older people who have their DP managed by an appointee, an import- ant subsection of this user group. 3Direct payment support schemes provide support to people receiving direct payments. Services available may include support with: devising a support plan; budgeting; accountancy (and payroll, if hiring a personal assistant), recruitment and employee responsibilities. DPSS may also offer information on local homecare providers for service users who wish to purchase from a homecare agency, rather than recruit a personal assistant. Recruitment Older people receiving DPs were recruited from ten councils and interviewed between 2005 and 2007 as part of a wider national evaluation on DPs to older people conducted for the Department of Health, England. Councils were selected to represent a spread of DP take- up rates. The top and lowest performing councils were excluded; the first having already been researched, the latter because of sample size concerns. Participating councils were from the first, second and fourth quartiles for take-up. Selected councils were dotted across the whole of England, split equally between high and low population-density areas. Proxies were the unpaid carers managing direct pay- ments as there was usually no other person available with sufficient knowledge of the circumstances to complete the interview. This approach is consistent with other studies [25, 51–53]. All older people in receipt of a DP in each council were contacted via a letter, distributed by councils to en- sure anonymity. Individuals received information on the study and a freepost envelope to return if they wanted to participate. Eight service users were sought per council, roughly half the national average of older people receiv- ing DPs per council in 2007 [48]. In areas with more positive responses than required, individuals were chosen to give the widest geographical spread within each council. Recipients were chosen irrespective of whether or not they had an unpaid carer. For ethical reasons it was stipulated that the main interviewee could not be an unpaid carer remuner- ated through DP to provide care; in the only case of this a representative from the local Direct Payments Support Services3 (DPSS) [54] was called upon. A DPSS representative was also present in two other interviews with service users who lived alone, at their request. The research was undertaken prior to implementa- tion of the 2005 Mental Capacity Act which extended the scope of DPs to people who lacked capacity to consent and legitimized the practice of authorising a ‘nominated person’ to act on their behalf [55]. Where carers acted for service users unable to express their views, the assumption of responsibility to manage the Participants had a wide range of circumstances and socio-economic characteristics (Table 2). Recruitment In contrast to previous studies where older people receiving DPs had been introduced to them via direct payments support schemes or disability groups [38], or at the direct request of family members [49–52]; two-thirds of the sample had only found out about DPs through social or health service sources (Table 1). Background An exception is the detail contained in 81 face-to-face interviews with older people, undertaken as part of an early Department of Health funded study of DPs to older people immediately prior to the introduction of PBs. These data, newly ana- lysed, give unprecedented depth of view, while their his- torical nature provides distance from the complex currents in which DPs are now immersed, allowing examination of the possible reasons for the contradiction between (early) user-level and (current) authority-level data. Table 1 How service users were introduced to direct payments How aware of DPs N Percentage (%) Social Worker 46 57 Friend 8 10 Publicity (National or local) 5 6 NHS worker (nurse, GP …) 5 6 Not known 4 5 Disability group 3 4 Direct Payments Support Service (DPSS) 3 4 Relation 3 4 Older people’s advisory service 2 3 Domiciliary care agency 1 1 Housing warden 1 1 TOTAL 81 100 design and methods were reviewed by the corresponding University Research Ethics board, as per guidance at the time. Interviews were conducted face-to-face and older people with cognitive impairment were included (30% of the sample). All but one of these interviews was con- ducted by proxy with their main representative in the presence of the service user. The person receiving ser- vices was addressed, according to their capacity to participate. design and methods were reviewed by the corresponding University Research Ethics board, as per guidance at the time. Interviews were conducted face-to-face and older people with cognitive impairment were included (30% of the sample). All but one of these interviews was con- ducted by proxy with their main representative in the presence of the service user. The person receiving ser- vices was addressed, according to their capacity to participate. Measures The model was developed in line with a conceptual framework which hypothesized that outcomes would be influenced by a mixture of individual characteristics (de- pendency, how DPs where managed) and patterns of ser- vice provision (types of care received, direct payments support) (Fig. 2). Given the relatively small sample size, the model was conceived for explanatory purposes [66]. All data was obtained during face-to-face semi- structured interviews lasting between 1.5 and 2.5 h in length based on an interview schedule developed for the study (cf. supplementary material 1). The contribution of DPs to outcomes was measured using an adapted ver- sion of the Older People’s Utility Scale for Social Care (OPUS [56]), measuring expected outcomes along seven domains: food and nutrition; personal care; safety; social participation and involvement; control over daily living; control over home environment; leisure pursuits/social participation. The last two domains were added to the five-item OPUS; subsequently this tool has been devel- oped to incorporate these extra items (ASCOT [57];). ASCOT is now used in national monitoring of service outcomes [58], and has been subjected to rigorous con- struct validity testing with older people, including prox- ies [59, 60]. Explanatory variables included individuals’ characteris- tics, needs (IADL, ADL), dependency and services used. Information on types of support purchased, total care in- put and proportion contributed to total care input by each support type were included. Total care input repre- sents the weekly sum of hours of: DP support, self- funded care and unpaid care. Hours of care were gener- ally recorded as per the care plan/DP records, but if these differed from the daily diary, the latter took prece- dence, although the ‘official’ care package amount was recorded separately. Although data on cognitive impairment was collected (by observation), it was not included as a variable in the model, as it was outside the capacity of the research to include a formal assessment of cognitive impairment, and because of its potential impact on other variables. The interviewer asked to evaluate expected level of need (none, low-level or high-level) in each domain in the absence of publicly funded social care (but not ex- cluding freely provided unpaid care) to determine base- line need. As all individuals were receiving a service at the time of interview, evaluation was based either on ex- periences directly prior to receiving the service or, on experiences of short-term breakdown in care support. Results A third of the sample of 81 people were aged under 71, half 71–85, and 19% over 85 (Table 2); 46% lived alone and 63% were female. Approximately 73% of the sample received unpaid care support to manage their DP to varying degrees, while 43% had their DP fully controlled by an unpaid carer owing to their inability to do so (ad- vanced frailty, limited speech and/or cognitive impairment). All measures used in the model are described in the supplementary material (cf. supplementary file 2). Measures A number of variables initially included in the model were later discarded as not statistically significant. These included age > 80; PA turnover, package size (as hours per week and as £ per week), purchased care from a home care agency, percentage of package spent on/ total care input (for all care categories), use of and signifi- cance of accountancy service, IADL score and individual scores for the following IADL items: telephone, house- hold tasks shopping, transport. The final set of variables included was a result of a step-wise process, in which at- tention was paid to avoid collinearity. Risks of overfitting were reduced due to the fact that there were almost no missing data points [67]. Overdispersion was discounted performing the likelihood ratio test of the over- dispersion parameter alpha using a negative binominal distribution. A second need measure for each domain in the pres- ence of publicly funded social care input was recorded, related to net outcome of all care inputs (Table 1). The analyses in this study focus on the difference between baseline and service impact assessments: hereafter the DP outcome gain (DPOG). Other data obtained included: reliance on DP support services and/or unpaid carers to manage DPs; how the DP-supported care package was used throughout the week (based on diaries cf. [61]); total care input (includ- ing unpaid carer), self-funded care and any sup- port commissioned directly by the council and not part of the DPspackage; activities of daily living (ADL) and instrumental activities of daily living (IADL) scores [62, 63] and dependency level [64] - categorised as low, mod- erate, moderate-high (2–4 personal activities of daily liv- ing (PADLs), high (5 PADLs) or highest dependency on the basis of ADL/IADL item scores and observation dur- ing interview. Ethical considerations The research was undertaken before implementation of the Research Governance Framework (2005–2007); its Page 5 of 17 Page 5 of 17 Page 5 of 17 Davey BMC Geriatrics (2021) 21:1 DP took place under the auspice of lasting power of attorney. DP took place under the auspice of lasting power of attorney. low mean and were positively skewed; therefore the Poisson log-functional form with a GLM command was used [65]. Analysis Individual-level analysis of DPOG was conducted using multiple regression analysis. Outcome gain scores had a Page 6 of 17 Davey BMC Geriatrics (2021) 21:1 Davey BMC Geriatrics Fig. 2 Factors influencing outcomes from direct payments Fig. 2 Factors influencing outcomes from direct payments Most individuals exhibited significant levels of disabil- ity: one-third were immobile or chair-bound, two-fifths required assistance with five PADLs and either used a wheelchair or were unable to walk > 2 m (Table 2). Ap- proximately 85% (n = 69) of sample members were un- able to bath alone, 32% could not use the toilet independently (n = 26), and 21% (n = 17) and 30% (n = 24) were regularly incontinent of faeces and urine, re- spectively. More than three-fifths were unable to manage finances on their own (n = 49), hence particularly likely to require support with DP management. Around 30% of the sample had some degree of cognitive impairment (Table 2); half of which was advanced. These people re- lied entirely on unpaid care for DP management. Some individuals were in the so-called “grey area” for continuing care funding. However, to receive a DP they had to be solely funded by social care, a situ- ation now altered by availability of personal health budgets (PHBs) [68]. Unsurprisingly, DP care packages significantly exceeded ten hours support per week, the Department of Health & Social Care (DHSC) threshold defining intensive commu- nity care. Levels of care were particularly intense for the most dependent users, averaging 30 h per week of support (Table 2). Unpaid care inputs were positively associated with de- pendency, and varied with nature of relationship be- tween carer and service user: spouses of individuals with high or highest dependency typically provided > 20 h support per week (DHSC threshold for intensive unpaid care) and often > 40 h (Table 2). Spouses (both male and female) represented one third of unpaid carers present (n = 27); others were daughters (24%, n = 20) and sons (22%, n = 20). Outcomes Net outcomes of all care inputs were generally high, varying by domain (Table 2). Levels of met need were greatest for domains prioritised by state-funded social care, such as food and nutrition and personal care and outcomes were significantly higher than for “supplemen- tary” domains, such as social participation and leisure activities. Needs associated with the home environment (lower-priority domain) were also largely met. Outcomes for the safety domain were especially affected by depend- ency level, with 28% of the most dependent reporting some unmet need, versus only 10% among the moder- ately dependent (Table 2). Although the high dependency of sample members reflected the increasing dependency of older people in receipt of state-funded social care, the sample was par- ticularly skewed towards the very dependent. In a 2005 home care sample of 365 people, [69], highest depend- ency service users comprised 10% of the sample, versus 44% in the current sample. According to social workers interviewed as part of the wider study, this reflected the composition of older DP users at the time, dominated by very complex cases. Page 7 of 17 Davey BMC Geriatrics (2021) 21:1 To put these results into a wider context, the sam- ple outcomes were compared to national outcome d f h Ad l S i l C F k national outcome data was first collected (Table 3). Outcomes This was a complex task and several factors need to b k i i h i i f h Table 2 Sample characteristics Variable n Sample all Moderate dependency Moderate-high dependency High dependency Highest dependency n 81 10 13 32 26 (%) 100 12 16 39 44 Socio-economic characteristics % % % % % Age (years) < 70 25 31 80 24 28 40 70–85 40 49 20 12 45 23 85+ 16 20 – 25 31 44 Gender Male 30 37 50 38 22 50 Female 51 63 50 61 78 50 Lives alone 38 48 50 57 53 31 Cognitive impairment+ 24 41 40 15 34 65 Interviewed by proxy 23 28 30 23 22 38 Unpaid carer helps to manage DP 53 73 50 57 75 88 Ethnicity: BME 17 22 30 23 22 19 Care package values Hourly DP rate (£) 81 9.46 7.65 11.04 8.06 11.12 Weekly allocation (hours) 81 20 20 11 19 30 Weekly care package value (£) 81 189 153 121 153 333 Unpaid care (hours) 70 33 19 26 30 45 Care suppliers Unpaid carer 70 86 70 85 87 92 Personal assistant(s) 64 86 100 82 80 84 Home care agency 18 22 – 31 25 23 Privately funded care 20 25 – 31 21 35 Level of met needs Food and nutrition 79 93 90 100 92 90 Personal care 79 92 90 100 93 85 Safety 79 76 90 77 70 65 Social participation 79 70 80 62 60 77 Control over daily living 79 83 80 84 93 73 Home environment 79 85 100 77 83 80 Social and leisure 79 65 70 62 66 61 Other outcomes Feels confident in the event of an emergency 81 71 70 85 56 73 Feels more confident in event of an emergency than when using standard services 48 95 100 100 85 95 Hospitalized unexpectedly in previous 12 months 81 40 30 38 50 42 + Suspected or diagnosed xt, the sam- al outcome Framework 0/11 when national outcome data was first collected (Table 3). Outcomes This was a complex task and several factors need to be taken into account in the interpretation of the results: n Sample all Moderate dependency Moderate-high dependency High dependency Highest dependency 81 10 13 32 26 100 12 16 39 44 % % % % % 25 31 80 24 28 40 40 49 20 12 45 23 16 20 – 25 31 44 30 37 50 38 22 50 51 63 50 61 78 50 38 48 50 57 53 31 24 41 40 15 34 65 23 28 30 23 22 38 53 73 50 57 75 88 17 22 30 23 22 19 81 9.46 7.65 11.04 8.06 11.12 81 20 20 11 19 30 81 189 153 121 153 333 70 33 19 26 30 45 70 86 70 85 87 92 64 86 100 82 80 84 18 22 – 31 25 23 20 25 – 31 21 35 79 93 90 100 92 90 79 92 90 100 93 85 79 76 90 77 70 65 79 70 80 62 60 77 79 83 80 84 93 73 79 85 100 77 83 80 79 65 70 62 66 61 81 71 70 85 56 73 48 95 100 100 85 95 81 40 30 38 50 42 Other outcomes national outcome data was first collected (Table 3). This was a complex task and several factors need to be taken into account in the interpretation of the results: To put these results into a wider context, the sam- ple outcomes were compared to national outcome data from the Adult Social Care Framework (ASCOF) returns published since 2010/11 when Davey BMC Geriatrics (2021) 21:1 Page 8 of 17 Page 8 of 17 1) National data for all domains, except one, merge the results of two response options (option one: “no need/ ideal state” and option two: “trivial needs”). This combination provides, “the measure on those individuals achieving the best outcomes, identifying no or limited need” [11, 70], a lower threshold than applied for the DP sample which only reports the percentage of service users who declared that all their needs were met (i.e. option one). For simplicity, the terms ‘medium’ and ‘maximum’ threshold are used when comparing the two sets of results (national data versus the DP sample). 1) National data for all domains, except one, merge the results of two response options (option one: “no need/ ideal state” and option two: “trivial needs”). This combination provides, “the measure on those individuals achieving the best outcomes, identifying no or limited need” [11, 70], a lower threshold than applied for the DP sample which only reports the percentage of service users who declared that all their needs were met (i.e. option one). For simplicity, the terms ‘medium’ and ‘maximum’ threshold are used when comparing the two sets of results (national data versus the DP sample). weighted measure for all domains as a single figure to compare local authority performance. From this date onwards ASCOF returns only detail three domains separately, ‘safety’, ‘social participation’ and ‘control over daily living’ (Table 3). Starting with the results which are directly compar- able, levels of met needs for the domain of ‘social par- ticipation’ were 26 percentage points greater (95% [CI 24.1–26.2], p. < 0.001) for the DP sample than nationally recorded averages throughout the past decade. Where the comparison of results is between the ‘max- imum threshold’ DP sample responses with the ‘medium threshold’ national results, the comparative performance of DP is understandably compressed. Other outcomes It is particularly striking therefore that met needs among the sample of DP users for the domain of ‘control over daily living’ and ‘safety’ outperformed national average outcome 2) There is one exception to this rule. National scores for ‘social participation’ are directly comparable with the results of the DP sample as both refer solely to responses to option one. 3) From 2016 to 2017 onwards only three domains are covered. This coincides with the introduction of a Table 3 Comparison of levels of met needs between DP service users sample and adult social care users according to national data Average percentage of service users reporting met needs, by working definition1 Average diff. Between sample score and ASCOF scores for all user groups for all time periodsh Sample Adult Social Care Outcome Framework (ASCOF) results DP Users (2005–2007) 2010– 2011 (1) 2011– 2012 (2) 2012– 2013 (3) 2013– 2014 (4) 2014– 2015 (5) 2015– 2016 2016– 2017 2017– 2018 2018– 2019 Food and nutrition 93 93 93 93 93 92 92 – – – 0.2 Personal care 92 93 93 92 93 92 93 – – – −0.7* Safety 76 61 62 63 64 67 67 71 a 71 a 71 a 8.0*** Social participation 70 43 43 43 43 b 44 c 45d 43e 44f 43g 26.5*** Control over daily living 83 73 73 75 74 75 74 75 a 75 a 74 a 9.0*** Home environment 85 93 93 93 93 93 94 – – – −8.2*** Leisure/ occupation 65 61 63 64 65 66 67 – – – 0.7 1,2,3,4,5,6 Sources are: 70,71 aSources are: 72, 73 b,c,d,e,f,g Sources are:75,76,77,78,79,80, respectively. National average outcomes for social participation for the years 2010–2013 are estimates h Results of a paired samples T-test (alpha level 0.05) *p = < 0.05 ***p = < 0.001 S 187 188 Table 3 Comparison of levels of met needs between DP service users sample and adult social care users according to national data Average percentage of service users reporting met needs, by working definition1 Average diff. Other outcomes Between sample score and ASCOF Sample Adult Social Care Outcome Framework (ASCOF) results DP Users (2005–2007) 2010– 2011 (1) 2011– 2012 (2) 2012– 2013 (3) 2013– 2014 (4) 2014– 2015 (5) 2015– 2016 2016– 2017 2017– 2018 2018– 2019 periods Food and nutrition 93 93 93 93 93 92 92 – – – 0.2 Personal care 92 93 93 92 93 92 93 – – – −0.7* Safety 76 61 62 63 64 67 67 71 a 71 a 71 a 8.0*** Social participation 70 43 43 43 43 b 44 c 45d 43e 44f 43g 26.5*** Control over daily living 83 73 73 75 74 75 74 75 a 75 a 74 a 9.0*** Home environment 85 93 93 93 93 93 94 – – – −8.2*** Leisure/ occupation 65 61 63 64 65 66 67 – – – 0.7 1,2,3,4,5,6 Sources are: 70,71 aSources are: 72, 73 b,c,d,e,f,g Sources are:75,76,77,78,79,80, respectively. National average outcomes for social participation for the years 2010–2013 are estimates h Results of a paired samples T-test (alpha level 0.05) *p = < 0.05 ***p = < 0.001 Sources: 187, 188 Notes National average outcomes for the domain of ‘control over daily living’, the domain of ‘safety’ from 2016 onwards and ‘social participation’ report actual figures for over 65’s from 2014 to 2015 onwards. All other figures are adjusted for over 65’s with a 2% reduction of the published national average, to adjust for differences between reported levels of met need between under and over 65’s using values for ‘control over daily living’ from 2015 to 2016 onwards as the reference There appears to be a slight upward trend in adult social are users reporting some or complete unmet needs from 2014/15 onwards. Data from this point onwards includes service users who fully fund the cost of services themselves Prior to this time these clients were not included Notes National average outcomes for the domain of ‘control over daily living’, the domain of ‘safety’ from 2016 onwards and ‘social participation’ report actual figures for over 65’s from 2014 to 2015 onwards. Other outcomes All other figures are adjusted for over 65’s with a 2% reduction of the published national average, to adjust for differences between reported levels of met need between under and over 65’s using values for ‘control over daily living’ from 2015 to 2016 onwards as the reference the reference There appears to be a slight upward trend in adult social are users reporting some or complete unmet needs from 2014/15 onwards. Data from this point onwards includes service users who fully fund the cost of services themselves. Prior to this time these clients were not included Davey BMC Geriatrics (2021) 21:1 Page 9 of 17 Page 9 of 17 would almost certainly outperform national average scores across all domains. scores at any time since data were first recorded by an average 9 and 8 percentage points respectively (95% [CI 8.1–9.9], p. < 0.00195%; [CI 5.8–10.7], p. < 0.001). Finally, in relation to other measures of quality (Table 2), 83% of the sample with previous experience of stand- ard services felt that services received through DP were much better, and 91% felt more confident in the event of an emergency since using DP. For those purchasing care from a home care agency (n = 18), 87% felt the agency responded better to their needs as a result of being the direct purchaser. Rates of hospital admission in the pre- ceding 12 months were similar to the general population of older people, rather than those with chronic health problems, for whom rates are usually much higher [80]. For the ‘food and nutrition’ and ‘leisure/occupation’ domains the sample result was roughly equal to the re- ported ASCOF averages, even though this too compares the maximum needs threshold (DP sample) to the medium needs threshold (ASCOT sample averages). Finally, the sample averages for the domains of home environment, and personal care, were slightly lower than the ASCOF averages, both of which were statistically sig- nificant differences. For the latter the difference was less than one percentage point. Again this compares unequal thresholds (maximum versus medium). Uniquely for the domain of ‘social participation’ we have some insight into the difference between reported national averages for “no need/ ideal state” and “trivial needs” (maximum/ medium) as results are published by two different sources, one using the medium threshold, and one the high threshold [54, 70–79]. Other outcomes Using this method (which is limited to the years 2013–2014 to 2018–2019), there was a large 31 percentage point dif- ference in the average achievement of only “trivial needs” remaining, versus “no need/ ideal state” for social care recipients at the national level. On this basis it seems fair to conclude that if ‘like-for-like’ national out- comes were available across all domains, the DP sample GLM model; Link function: Log, Variance function: Poisson Observations = 79 Pseudo R2 = 30% Observations = 79 Pseudo R2 = 30% Factors contributing to outcomes Service user characteristics Factors associated with DPOG were examined (Table 4). A strongly significant factor was dependency, consistent with previous findings: those with greatest need derived less benefit from the same amount of service than those with lower needs [81]. Older people living alone re- ported outcome gains 23% lower than older people living with others (Table 4). Living alone is frequently referred to by social workers as a factor limiting potential bene- fits of DPs [25]. Living alone and having sufficient ADL difficulties to receive state-funded care can cause social Table 4 Factors associated with direct payments outcome gain scores among older people Coeff Prob 95% CI lower limit 95% CI upper limit Highest Dependency −0.75 0.00 −0.93 −0.55 High Dependency −0.58 0.00 −0.71 −0.45 Moderate- high Dependency −0.27 0.00 −0.40 −0.15 Lives alone −0.22 0.00 −0.29 −0.15 Adapted IADL: medication use 0.13 0.00 0.08 0.18 Unpaid carer helps to manage DP 0.13 0.00 0.04 0.21 Chose & received recruitment support service(s) 0.07 0.00 0.05 0.09 Adapted IADL: handling finances 0.08 > 0.01 0.03 0.13 Activities of Daily Living Score −0.06 0.00 −0.08 −0.05 Significance of recruitment support (critical) 0.017 0.01 0.004 0.03 Length of time using direct payments 0.003 0.00 0.002 0.0045 Difference between package size and total care input −0.004 0.00 −0.005 −0.002 Percentage of total care input composed of self-funded care 0.003 > 0.01 > 0.001 0.005 Percentage of total care input composed of unpaid care 0.006 0.00 0.004 0.008 Percentage of package spent on combination household care/ personal care 0.002 0.00 0.001 0.003 Percentage of package spent on combination household care/ social and leisure care 0.004 0.00 0.002 0.007 Percentage of package spent on therapeutic management −0.003 < 0.01 −0.005 −0.001 Constant 4.62 0.00 4.30 4.95 Observations = 79 Pseudo R2 = 30% Davey BMC Geriatrics (2021) 21:1 Davey BMC Geriatrics (2021) 21:1 Page 10 of 17 Page 10 of 17 DP support explored (accountancy services and recruit- ment services), only recruitment services were signifi- cantly associated with greater DPOG (Table 4). Receipt of such services was fairly widespread: 69% (n = 56) of the sample received ongoing DP support. Of these, 41% (n = 23) received both accountancy support and recruit- ment support, while 36% (n = 20) opted for accountancy support only; the remainder relied solely on recruitment support (23% n = 13). Factors contributing to outcomes Service user characteristics These services were mainly free at the point of use: only 12% (n = 10) of those who used ongoing DPSS support paid towards the cost of the ser- vice. Service users were typically referred to the service by the local authority. Referral to DP support was high - in other research it has been found that only one third of DP users ever had contact with a DPSS due to poor referral rates [16]. isolation, while older adults living alone are simultan- eously more likely to have limited access to unpaid care. y y p Alongside dependency level, single IADL items were included. A standard IADL score of 4 and above is a re- liable predictor of 1-year incidence of dementia [82]. Scores for each item were adapted so that being autono- mous for medication was scored lowest and incapacity for medication scored highest (range 1–5). Individuals with largest adapted IADL scores were more likely to achieve greater outcome gains from DPs. This finding was counter-intuitive: cognitive impairment is a risk fac- tor for package breakdown [83]. This finding probably reflects how individuals lacking these capacities received support by unpaid carers in planning support arrange- ments, which may therefore indicate the added value as- sociated with ‘managerial care’ performed by unpaid carers [84]. Of the purchasing choices made, using funds to pur- chase “therapeutic care” (n = 5) was associated with lower outcome gains possibly due to the incidence of cognitive impairment among those purchasing care for this purpose (100%). Care packages National statistics show that DPs to older people are less generous than packages to younger adults with physical or learning disabilities, which has raised concerns [26]. Package size was close to significance but exerted little influence rela- tive to other variables and was therefore excluded. However, there was a significant negative association between package size and total care input (Table 4), which may point to a negative impact where there is inequity in social care provision relative to unpaid care input, usually in cases of cognitive impairment and/or extreme dependency. At the time, such individuals were unable to receive health funds as cash payments, a situation now reversed by the 2014 Care Act which permits contribution from NHS continuing care funding to DPs [68]. DP’s were also applied to purchase “combinations of personal care and home (household) care”. This combin- ation, which was quite frequent (42%, n = 34), repre- sented flexible care and contrasted with purchasing care which was solely for home (household) care. The later was not associated with improved outcome gains while the combination purchase was. Purchasing a combin- ation of personal care and home (household) care was linked to hiring a PA: 84% of individuals who received combined personal/ household care hired a PA (n = 32); versus only 5% of those that recruited via a home care agency (n = 44). A high proportion of service users who recruited a PA (n = 64), had received some form of DP support (76%, n = 48), with 60% of this group (n = 29) re- ceiving recruitment support. Service users who viewed recruitment support as critical also achieved better out- comes (Table 4). Surprisingly, 50% of those who did not recruit a PA (n = 12), also used recruitment support. In these cases, DPSS acted as brokers for individuals pur- chasing care from home care agencies. Experience with DPs Deriving greater outcome gain from DPs was linked to time using the service (Table 4). Using an agency to pur- chase care was not statistically significant (possibly due to low uptake– only 22% (n = 18) of service users pur- chased care from an agency). Impacts of care worker characteristics were investigated qualitatively: individuals were asked about continuity, flexibil- ity, reliability, communication, staff attitudes, staff skills and knowledge. Individuals with longest experience using DPs had, for obvious reasons, greatest experience and compe- tence in finding staff. Staff turnover was not relevant to out- come gain (hence excluded from the model). g g These findings help to better understand the role of DP support as an ‘intermediate output’ in the production of DPOGs [85]. Previous research has noted that ‘third- party organisations’ support improves outcomes for indi- viduals with and without unpaid care [30, 86]. Backed by qualitative research it has been widely accepted that DP support is critical to take-up of DPs [87], that absence of payroll support can put people off using DPs [38] and that DP support can ease the burden felt by unpaid carers [36, 88] but the lack of a clear association be- tween the role of support services and particularly sup- port for recruiting care (as demonstrated in this study), has weakened the priority given to DP support. 4This context includes rigorous limitations on funding relative to need and consideration of available unpaid care prior to allocation of funds. Importance of unpaid care A major thread running through the results is the posi- tive influence of unpaid care on DPOG. This corrobo- rates the views of social workers [25, 90], but the analyses presented identify how and why unpaid care is so influential. It has been speculated that the responsibility for man- aging care may overburden already stretched caregivers [98] but equally involvement in coordinating care (facili- tated by availability of DPs) may increase the ‘process utility’ of caregiving [99]. Attributes such as ‘control over the caring’, ‘fulfillment’ [100], and “a sense of control and mastery” [101], are known to promote carer well- being. It has also been found that unpaid carers can sim- ultaneously perceive both moderate burden and great satisfaction [102]. None of these aspects have yet been adequately explored in relation to DP management. Dependency on an unpaid carer to manage the DP Dependency on an unpaid carer to manage the DP Research on situations where the unpaid carer manages a DP making proxy decisions, has mainly focused on how this role comes about [49, 50, 52], and whether practitioners are confident at assessing when this ar- rangement is in the person’s best interest [49, 50]. These results are the first to offer quantitative evidence linking DP management by an unpaid carer with better out- comes for the cared-for person. This discounts concerns that care may become ‘carer-centered’ [95] and validates previous suggestions that there is often considerable overlap between the needs and goals of the cared-for and the carer [96, 97]. Influence of the type of inputs received Influence of the type of inputs received The findings also highlight the influence of the type of inputs received (Fig. 2); throwing light on the inputs characteristic of more flexible care, and on the positive impact of direct payments support (DPS). Types of care received Compared to the characteristics and circumstances of people using DPs, care inputs had less impact on out- come gains, but there were some notable findings. Input of a Direct Payment Support Service (DPSS) was the most influential on outcome gain. Of the two forms of Page 11 of 17 Page 11 of 17 Davey BMC Geriatrics (2021) 21:1 Last but not least, individuals receiving privately-funded care (25% of sample) had better outcomes. Overall self- funded care was marginal to total care input received but exceeded 25% of total care input in the following sub- groups: highly-dependent users who either lived alone (re- gardless of whether or not they had some form of unpaid care); people who did not live alone but self-managed their DP, and people who received no unpaid care. In es- sence, self-funded care offered a substitute to unpaid care. Despite the term, ‘self-funded care’ was predominantly publicly funded, albeit indirectly by service users employ- ing their Attendance Allowance to purchase extra care. This is a social security benefit widely available to older people requiring regular care or supervision. Around 1.24 million older people in England receive Attendance Allowance, compared to around 411,000 who receive some form of local authority adult social care support [89]. Attendance Allowance (AA) was used equally among those with and without unpaid care, often prompted by advice from support workers. At the individual level the benefit of DPs depends upon whether or not DPs offer what carers are lacking, such as the ability to coordinate care to fit in with their other responsibilities [93]. There is largely consensus that DPs to the person being cared for can assist unpaid carers in gaining more control over their time and daily lives and improve their quality of life [38, 94, 95]. How- ever, managing a DP should not be imposed due to a lack of alternatives [95]; crucially the pre-existing rela- tionship between carer and recipient should be taken into account when considering the option of DPs. Unpaid care as a function of total care A positive association between DPOG and receiving a higher fraction of total care input from unpaid care may seem unsurprising but actually the situation is complex. Unpaid care as a fraction of total care can limit potential outcome gain from state-funded care, as need in the ab- sence of a service may be reduced. There is a longstanding debate as to whether unpaid care complements or substitutes for formal care [91]. Cash payments may decrease unpaid caregiving if fam- ilies have greater license to organize care to suit their priorities [60]. The results challenge these concerns and strongly suggest that in the context of DPs in England4 unpaid care not only complements formal care, but pro- motes its efficacy. Flexible care arrangements Individuals purchasing flexible care, (i.e. marginally devi- ating from standard home care), achieved greater gains. This was most prevalent among service users who used a PA which is unsurprising, as employing a PA has long been considered the best route to greater autonomy [103] but this is the first study to demonstrate quantita- tively that flexibility can improve outcomes. The Care Act (2014) expressly aims to reduce carer burden; a question then arises about the appropriateness of a service indirectly promoting unpaid care. Evidence for recent increases in intensive caregiving among over 65 s is available [92]. Within the sample, unpaid care contributed on average 42% of the total care input when available [44]. Research has reported a decrease in the use of PAs [46, 104] and increasingly narrow interpretations of what would be “appropriate use of funds” [25, 105]. The Page 12 of 17 Page 12 of 17 Page 12 of 17 Davey BMC Geriatrics (2021) 21:1 Davey BMC Geriatrics (2021) 21:1 majority of those that recruited a PA had done so with some form of support from a DPSS. variance (±65%) [20, 107–109] within which there is ground for concern. It is debatable whether the rise in funding is sufficient to fund sustainable care from the home care sector [110]. Support structures Recruitment support provided by DPPS significantly al- tered outcomes. Those that used recruitment support had better outcomes. Furthermore, those who considered re- cruitment support as critical to their success – had even better outcomes. These findings are important given the way that recruitment support has been reconfigured in many areas with reductions on the ‘associated expend- iture’ of DP support by decommissioning and a shift to- wards online platforms. In an increasing number of councils service users are expected to make a choice about whether they should dedicate a portion of their DP to pay for a potentially beneficial support service, without know- ing in advance what that might mean for them [44]. This scenario contrasts with the access to DP support that many of the service users in this sample had: free at the point of use, 1:1 and allowing service users to explore options regardless of the means by which they eventually recruited care. The results suggest that these changes are likely implicated in the increasing failure of DPs to achieve better outcomes than standard services. Focusing on what can be asserted from the findings, it is evident that the sufficiency of DP packages can only really be understood in relation to other factors. Whilst variations in outcome gain were not significantly associ- ated directly to DP package values, outcome gains were reduced where there was a larger discrepancy between the total care input (which could include unpaid care and/or self-funded care), and the funded package. Larger discrepancies were observed where (a) individual alloca- tions of DPs had been capped (b) service users were physically able but cognitively impaired and received DP amounts that were minimal relative to their needs. These effects were not a direct result of shifting a greater burden onto unpaid care, or of a greater respon- sibility to self-fund. In fact, service users’ for whom ei- ther unpaid care or self-funded care represented a higher fraction of the total care input had greater DP- related outcome gains. It appears that DP’s were less ef- fective simply for being out of line with individuals’ cir- cumstances, as a consequence of legal constraints (extra funding from health was still not legally permitted, hence the cap) or lack of fit with existing resource allo- cation practices. Financing DPs: sufficient? For some time researchers have argued that DPs to older people may be of insufficient value to achieve optimal outcomes [26]. The results challenge this argument in that package size was not statistically linked to DPOG but this only has weight if the intensity of care packages for the sample were consistent with practices at the time, and comparable to recent levels of per capita ex- penditure. This is difficult to ascertain given wide varia- tions in expenditure between councils, both then and now, but some observations can be made. The results suggest therefore that DP package values do influence outcomes, but the effect is weak against other factors, provided funding is set at an appropriate level (for which the current sample might give a benchmark value, if properly uprated). Certainly, large variations in per capita expenditure would result in major (negative) devia- tions from benchmark values and in packages likely to be misaligned with individuals’ circumstances. There also appears to be significant potential for optimizing DPOG in mobilizing NHS contributions where applicable. In terms of the overall sample, we see that average per capita expenditure was £189 (Table 1) in 2006. Cur- rently, the average per capita expenditure on DP among the over 65 s is £266 [19, 20]. Taking into account current hourly home care costs, (£16.04, 157b) this equates to roughly 16.5 h of state funded social care per week in 2018–2019, versus 17 h a week for the sample based on average unit home care costs in 2006 (£11, 158). The average weekly DP value for those of highest dependency (44% of the sample) was £333. This averages to 30 h of state-funded social care per week, consistent with the intensity of package size at the time for those levels of dependency [106]. Limitations The data used for the analysis was cross-sectional and some caution needs to be taken in its interpretation in the absence of longitudinal data. The analysis also com- bines proxy with non-proxy responses. While this is not unusual it has some limitations. Separating the two sets of responses would be a complex issue, requiring a much larger sample. Proxy responses were for obvious reasons biased towards the most dependent thus making it difficult to control for differences. The potential influ- ence of unpaid carers on outcomes scoring was also not just limited to proxies. Just under a third or the inter- views were conducted by proxy - but the majority of the interviewees received some degree of support from an unpaid carer to manage their DP (73%) and in most of these cases their unpaid carer was also present in the interview. The findings are historical – based on interviews con- ducted between 2005 and 2007. The revisiting of this data is justified on two counts. The data offers more de- tail than previous studies – but also the very fact that it predated the main wave of personalisation is an advan- tage. Personalisation has radically altered the context in which DP are used by older people and reports of de- creasing success of DPs to older people coincide with the period associated both with the implementation of personalisation and radical austerity [42]. The richness of the data provides the opportunity to explore possible reasons for this. The use of proxies was paramount to achieving a sam- ple better matched to the levels of dependency currently supported by publicly-funded social care than survey data. It is a widely used method for collecting data, “preferable to the systematic exclusion of individuals who are unable to self-report based primarily on the principles of equity and inclusion, as well as the poten- tial methodological issues associated with missing data and bias” [2, 59]. Two particular aspects stand out: flexible care and support structures. Inputs characteristic of more flexible care were associated with achieving greater outcome gain from receiving DPs. (Conversely using DPs to pur- chase “mainstream” support would not be expected to do so.) Also individualized support provided by a dedi- cated DPSS increased the benefit associated with DPs. This is where the major changes in DP implementation and support that have occurred in recent years [44], may be relevant. Living alone and “resource-poor” g p As expected, living alone was associated with worse DPOG. Social networks have also been associated with better outcomes from PBs [31]. The different mecha- nisms by which unpaid care influenced outcome gains show that those without a carer were resource-poor in various ways. Unpaid care was influential both as a func- tion of total care received as a commodity, and from a ‘capabilities’ perspective [111] with unpaid carers acting as agents. There were also other inequalities between service users. People receiving care from other sources gained more from the DP funded part of their care, than those that did not. Care from ‘other sources’ included self- funded care, financed mainly by Attendance Allowance, often prompted by advice from support workers. While this parity underlines the relevance of the re- sults to current practice, it does not rule out concern re- garding today’s funding levels. Average DP package values for older people have generally risen over the past four years, with a median increase of 19% but with large Davey BMC Geriatrics (2021) 21:1 Page 13 of 17 Page 13 of 17 DPs had their limitations in outcomes for certain do- mains (Table 1). Like recent reports of unmet needs in self-directed HCBS programs [112], qualitative interview data suggested other relevant social issues – such as in- ability to use transport, lack of interest in attending or- ganized groups or lack of acceptable meeting places – coupled frequently with a general demotivation, related to the loss of siblings and peers. Also, there were signifi- cant needs in the domain of home environment, from basic decoration to adaptations that social care funds would not meet. It is unlikely that these needs may have been met simply by access to more generous care pack- ages, but might have been eased by other social care in- terventions [113, 114]. Still there are now increased opportunities for using DPs as vehicles for tackling these issues: home equipment and adaptations now lie within the realm of DP. outcomes was also strengthened by independent obser- vation [25]. Conclusion The work presented has explored how outcomes are in- fluenced by the types and quantities of care purchased; external support to manage DPs (from DPSS and from unpaid carers), as well as individual characteristics. Un- like previous survey data which excludes proxy re- sponses [23, 31], service users in the sample were skewed towards the most highly dependent. The sample therefore better reflects the profile of older people cur- rently receiving publicly-funded social care. The pay- ments received by the sample were also in line with current norms. Outcomes of DPs for the sample were compared with national average outcome scores across a nine year period (since reporting began), and tested for statistically significant differences. This was a complex task owing to different methods of coding met needs; for most domains the DP sample compares “all needs met” (maximum threshold) with national results which com- bine “no needs” and “only trivial needs” (medium thresh- old). Despite these threshold differences there were strong statistically significant differences in the extent to which the DP sample felt safe and in control of their lives and achieved as much social participation as they wanted. If data was available to compare the two at the same threshold, the DP sample results would have likely outperformed national average outcome scores for all domains. Limitations Such changes are likely to have impacted upon the inputs received and the characteristics of people receiving DPs. This is likely to have occurred The strong positive impact on outcomes associated with the presence of an unpaid carer who helped to manage DPs clearly prompts reflection on the potential of positive bias linked to proxy responses but, “the ma- jority of studies that directly compare self-report and proxy-report have found an underestimation of quality of life by proxy respondents compared to patient self- report” [12, 59]. It therefore seems unlikely that proxies overestimated outcomes. Proxy evaluation of DP Davey BMC Geriatrics (2021) 21:1 Davey BMC Geriatrics (2021) 21:1 Page 14 of 17 Page 14 of 17 Finally, this work demonstrates for the first time that the freedom to combine care package allocations with self-funding is associated with achieving better out- comes. DPs remain the only mechanism by which ser- vice users and families can choose to add to their funded package, but in the past this has provoked heated de- bates about the risk of a two-tiered service [116]. In this study, self-funded care was a small but pivotal factor in optimizing outcomes. It was also predominantly funded by the social security benefit Attendance Allowance. This benefit remains surrounded by controversy amidst discussions on the future funding of social care [117]. Its proponents point to its wide coverage; ability to com- pensate for unmet need among people who remain ineli- gible for social care funding and the value of it being centrally administered at set rates, thus offering some in- dependence from the highly variable practices of local councils. directly (i.e. excessive limitations on use of funds causing reduced flexibility; reduced access to face-to-face recruit- ment support akin to the support received by the sample in this study), as well as indirectly (such as by creating environments where employing a PA is more difficult, or influencing who gets DPs). A major concern surrounding the uptake of DPs in the wave of personalisation and austerity is that current pressures and incentive structures promote the ‘easiest’ rather than the best route of care. This, for an increasing number of councils, equates to DPs being supplied as the ‘default’ option. Due to the pressures on social work teams this often precludes access to DPs in so called ‘complex-cases’. Acknowledgements The author would like to thank the following various people for their contribution to this work; Ms. Margaret Perkins from the Personal Social Services Research Unit (PSSRU) at the London School of Economics and Political Science (LSE) for her role in conducting some of the interviews with older people receiving direct payments that are analysed here, Professor Martin Knapp from the PSSRU at the LSE for his supervision with my doctoral work which included the research presented here and for his comments on earlier drafts of the paper, and Dr. Roshni Mangalore (previously PSSRU at the LSE) for her assistance with preliminary analyses. Abbreviations Consistent with earlier qualitative studies, the work found positive impacts of unpaid care on older DP recipi- ents but this is the first study that quantifies this, and demonstrates separate effects for unpaid care as a function of the total care received, and unpaid care as managerial care. The findings provide an incentive to recognise the often overlooked impact of unpaid carers on the outcomes of DPs [23]. Assuming that “if the service user [is] unable to manage a DP, then the carer [will] be asked to manage it for them”, [52] really is the wrong approach. We know this can negatively affect carer wellbeing [115]. This study also shows that just having an unpaid carer is not neces- sarily sufficient: it is the time and effort that they invest in caring that is significant. This insight helps with the di- lemma regarding overreliance on unpaid carers. Unpaid carers’ commitment and capability can (and should) be readily observed at the outset. PB: Personal budget; DP: Direct payment; MB: Managed budget; DPSS: Direct payments support scheme; DPOG: Direct payment outcome gain; DH: Department of Health Supplementary Information pp y The online version contains supplementary material available at https://doi. org/10.1186/s12877-020-01943-8. Additional file 1. Additional file 2. Limitations These include: services users requiring indirect payments (managed by a nominated person), particularly people with dementia, individuals requiring health funding and people for whom including funds to purchase home equipment and adaptations may be beneficial. The results of the DP sample support the pro- motion of DPs for complex-cases but highlight the need to pay attention to the discrepancy between total care input (which could include unpaid care and/or self- funded care) and DP-funded support. This information is not routinely collected but could be required as a means of monitoring – particularly given concerns that DPs offer a convenient route to councils to further shift caregiving costs to unpaid carers. The work presented provides an urgent reminder that it is not access to DPs per se that improves outcomes but DPs with support to identify and realise the potential they offer. It is said that personalisation has not worked for older people [118]. Others argue that suggesting that personal budgets are unsuitable for older people is, in it- self, a form of ageism [33]. This work offers insights into the tools at councils’ disposal to improve the potential of DPs, as well as lessons for other countries implementing consumer-directed care. Providing adequately sized care packages for complex cases requires an increased role for funding from NHS continuing care, made legal as part of the Care Act 2014 [68]. Implementation of Personal Health Budgets (where direct payments combine social and health care funding) has been marred by the unwillingness of NHS commis- sioning groups to release funds to councils with social services responsibilities. As a result, service users at the high end of the need spectrum, as represented in the sample, are less likely to access DPs. Supplementary Information References 1. Needham C. The Boundaries of Budgets: why should individuals make spending choices about their health and social care? University of Birmingham. Birmingham: Centre for Health & Public Interest; 2013. 27. Netten A, Jones K, Knapp M, Fernández JL, Challis D, Glendinning C, Jacobs S, Moran N, Stevens M, Wilberforce M. Personalisation through individual budgets: does it work and for whom? Br J Soc Work. 2012;42(8):1556–73. 2. Power A. Personalisation and austerity in the crosshairs: government perspectives on the remaking of adults social Care. J Soc Policy. 2014;43(4): 829–46. 2. Power A. Personalisation and austerity in the crosshairs: government perspectives on the remaking of adults social Care. J Soc Policy. 2014;43(4): 829–46. 28. FitzGerald Murphy M, Kelly C. Questioning ‘choice’: A multinational metasynthesis of research on directly-funded home care programs for older people. Health Soc Care Commun. 2019;27(3):37–56. 3. Benjamin AE, Matthias RE. Age, consumer direction, and outcomes of supportive services at home. The Gerontologist. 2001;4(5):632–42. 3. Benjamin AE, Matthias RE. Age, consumer direction, and outcomes of supportive services at home. The Gerontologist. 2001;4(5):632–42. 4. Bulamu N, Kaambwa B, Gill L, McKechnie S, Fiebig J, Grady R, Ratcliffe J. Impact of consumer-directed care on quality of life in the community aged care sector. Geriatr Gerontol Int. 2016;17:1399–405. 29. Ottman G, Allen J, Feldman P. A systematic narrative review of consumer- directed care for older people: implications for model development. Health Soc Care Commun. 2013;21(6):563–81. 5. Carlson BL, Foster L, Dale SB, Brown R. Effects of cash and counseling on personal Care and well-being. Health Serv Res. 2007;42(1 Pt 2):467–87. 5. Carlson BL, Foster L, Dale SB, Brown R. Effects of cash and counseling on personal Care and well-being. Health Serv Res. 2007;42(1 Pt 2):467–87. 30. Baxter K. The personalization and marketization of home care services for older people in England. In: Christensen K, Pilling D, editors. The Routledge handbook of social Care work around the world. Oxford: Routledge; 2018. p. 88–101. 6. Coe NB, Guo J, Konetzka RT, Harold Van Houtven C. What is the marginal benefit of payment-induced family care? Impact on Medicaid spending and health of care recipients. Health Econ. 2019;28(5):678–92. 6. Coe NB, Guo J, Konetzka RT, Harold Van Houtven C. What is the marginal benefit of payment-induced family care? Impact on Medicaid spending and health of care recipients. Health Econ. 2019;28(5):678–92. 31. Hatton C, Waters J. The Third POET Survey of Personal Budget Holders and Carers. Funding 18. Hunt J. We need to do better on social care. Speech. 20th March 2018. Retrieved from: https://www.gov.uk/government/speeches/we-need-to-do- better-on-social-care. Accessed 30th March 2018. The author received no financial support for the research, authorship, and/or publication of this article. 19. NHS Digital. Measures from the Adult Social Care Outcomes Framework (ASCOF), England 2018–19. Final release. Retrieved from:https://digital.nhs. uk/data-and-information/publications/clinical-indicators/adult-social-care- outcomes-framework-ascof/current . Accessed 29th May 2020. Competing interests The author declares no competing interests. The author declares no competing interests. 25. Glendinning C, Challis D, Fernandez JL, Jacobs S, Jones K, Knapp M, Manthorpe J, Moran N, Netten A, Stevens M, Wilberforce M. Evaluation of the Individual Budgets Pilot Programme: Final Report. University of York. York: Social Policy Research Unit; 2008. Received: 16 May 2019 Accepted: 1 December 2020 Received: 16 May 2019 Accepted: 1 December 2020 Received: 16 May 2019 Accepted: 1 December 2020 26. Moran N, Glendinning C, Wilberforce M, Stevens M, Netten A, Jones K, Manthorpe J, Knapp M, Fernandez JL, Challis D, Jacobs S. Older people’s experiences of cash-for-care schemes: evidence from the individual budgets pilot projects. Ageing Soc. 2013;33(5):826–51. Author’s contributions h h ( ) f The author (VD) confirms sole responsibility for the following: study conception and design, data collection, analysis and interpretation of results, and manuscript preparation. The author read and approved the final manuscript. Page 15 of 17 Page 15 of 17 Davey BMC Geriatrics (2021) 21:1 Davey BMC Geriatrics (2021) 21:1 Davey BMC Geriatrics Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. 20. NHS Digital. Adult Social Care Activity and Finance: England 2018–19. Retrieved from https://digital.nhs.uk/data-and-information/publications/ statistical/adult-social-care-activity-and-finance-report/2018-19. Accessed 30th March 2020. Ethics approval and consent to participate The research design and methods were reviewed and approved by the LSE Research Ethics board, as per guidance at the time. The work was conducted shortly prior to the introduction of the Research Governance Framework, now superseded by the UK Policy Framework for Health and Social Care Research. Written consent to participate was obtained from participants – or where necessary, their proxies. 21. Pozzoli F. Personalisation as vision and toolkit. A case study. Int Rev Sociol. 2018;28(1):62–85. 22. Fernandez J, Kendall J, Davey V, Knapp M. Direct payments in England: factors linked to variations in provision. J Soc Policy. 2007;36(1):97–121. 23. Woolham J, Daly G, Sparks T, Ritters K, Steils N. Do direct payments improve outcomes for people who receive social care? Differences in outcome between people aged 75+ who have a managed budget or a direct payment. Ageing Soc. 2017;37(5):961–84. Consent for publication Not applicable. Consent for publication Not applicable. 24. Foster L, Brown R, Phillips B, Schore J, Carlson BL. Improving the quality of Medicaid Personal Assistance through consumer direction. Health Affairs. 2003; 1(22):W3-162–75. https://www.healthaffairs.org/doi/full/10.1377/hlthaff.W3.162. References London: Think Local Act Personal (TLAP); 2014. 7. Gill L, Bradley SL, Cameron ID, Ratcliffe J. How do clients in Australia experience consumer directed Care? BMC Geriatr. 2018. https://doi.org/10. 1186/s12877-018-0838-8. 7. Gill L, Bradley SL, Cameron ID, Ratcliffe J. How do clients in Australia experience consumer directed Care? BMC Geriatr. 2018. https://doi.org/10. 1186/s12877-018-0838-8. 32. OPM. Briefing paper 3: Ways to improve the impact of personal budgets. In: Findings from the third round of a three-year longitudinal study in Essex. London: Office for Public Management; 2012. 8. Ottman G, Mohebi M. Self-directed community care services for older Australians: a stepped capacity approach. Health Soc Care Commun. 2014; 22(6):598–611. 8. Ottman G, Mohebi M. Self-directed community care services for older Australians: a stepped capacity approach. Health Soc Care Commun. 2014; 22(6):598–611. Australians: a stepped capacity approach. Health Soc Care Commun. 2014; 22(6):598–611. 9. Mahoney KJ, Mahoney EK, Morano C, DeVellis A. Unmet needs in self- directed HCBS programs. J Gerontol Soc Work. 2018;62(2):1540. 10. Malbon E, Carey G, Meltzer A. Personalisation schemes in social care: are they growing social and health inequalities. BMC Public Health. 2019;19:805. 11. Da Roit B, Le Bihan B. Similar and yet so different: cash-for-Care in six European Countries’ long-term Care policies. Milbank Q. 2010;88(3):286–309. 12. Department of Health. Making personal budgets work for older people: developing experience. London: Department of Health; 2008. 13. Department of Health. Moving forward: Using the Learning from the Individual Budgets Pilots. Response to the IBSEN Evaluation from the Department of Health. London: Department of Health; 2008. 14. Department of Health. Personal health budgets guide – Third Party Organisations. The Families’ Perspective. London: Department of Health; 2012. 15. Carr S. Improving personal budgets for older people: A research overview. Adult services report 63. London: Social Care Institute for Excellence; 2013. 16. Newbronner L, Chamberlain R, Bosanquet K, Bartlett C, Sass B, Glendinning C. Keeping persona budgets personal: learning from the experiences of older people, people with mental health problems and their Carers. Adult services report 40. London: Social Care Institute for Excellence; 2011. 17. Routledge M, Parkin T, Gollins T, Beckford C, Lewis J. Getting Better Outcomes for Older People Using Personal Budgets. London: Think Local Act Personal (TLAP); 2015. 33. Glasby J, Littlechild R. Direct payments and personal budgets. Bristol: Policy Press; 2016. 9. Mahoney KJ, Mahoney EK, Morano C, DeVellis A. Unmet needs in self- directed HCBS programs. 17. Routledge M, Parkin T, Gollins T, Beckford C, Lewis J. Getting Better Outcomes for Older People Using Personal Budgets. London: Think Local Act Personal (TLAP); 2015. References Page 16 of 17 Page 16 of 17 Davey BMC Geriatrics (2021) 21:1 Davey BMC Geriatrics (2021) 21:1 People, PSSRU Discussion Paper 2265/3. University of Kent, Canterbury. Canterbury: Personal Social Services Research Unit; 2006. People, PSSRU Discussion Paper 2265/3. University of Kent, Canterbury. Canterbury: Personal Social Services Research Unit; 2006. 42. Glendinning C. Long-term care and austerity in the UK: a growing crisis. In: Greve B, editor. Long-term Care for the Elderly in Europe. Oxford: Routledge; 2017. p. 39–41. 70. NHS Digital. Measures from the Adult Social Care Outcomes Framework 2016/17. Retrieved from https://digital.nhs.uk/data-and-information/ publications/statistical/adult-social-care-outcomes-framework-ascof/archive/ measures-from-the-adult-social-care-outcomes-framework-england%2D%2 D-2016-17. Accessed 30th March 2020. 43. LGA. Adult Social Care Efficiency (ASCE) Final Report: Annex Review of Saving for each Council in the Programme. Retrieved from https://www. local.gov.uk/sites/default/files/documents/lga-adult-social-care-eff-424.pdf. Accessed 30th May 2020. 71. HSCIC. Personal Social Services Adult Social Care Survey 2013–14, Final Release. 2014. Health & Social Care Information Centre, London [Contains data for 2010–11, 2011–12, 2012–13 and 2013–14]. Retrieved from https:// files.digital.nhs.uk/publicationimport/pub16xxx/pub16162/pss-ascs- eng-1314-fin-annx.xlsx. Accessed 30th March 2020. 44. Davey V. Social Care for Older People: the role and function of direct payments. (doctoral dissertation): London School of Economics & political science; 2018, 2018. 45. David C, West R. NDIS self-management approaches: opportunities for choice and control or an Uber-style wild west? Aust J Soc Issues. 2017;52(4):331–46. David C, West R. NDIS self-management approaches: opportunities for c 46. Skills for Care. Individual employers and the personal assistant workforce. Leeds: Skills for Care; 2020. 72. NHS Digital. Personal Social Services Adult Social Care Survey England 2015–16. NHS Digital. [Contains data for 2014–15 and 2015–16]. Retrieved from: http://content.digital.nhs.uk/catalogue/PUB21630. Accessed 30th March 2020. 47. Malley J, Fernández J-L. Patterns and Effects of Nonresponse in the English Adult Social Care Survey Full report, QORU working paper 2841. Canterbury: University of Kent PSSRU; 2012. 73. NHS Digital. Measures from the Adult Social Care Outcomes Framework 2017/18. Retrieved from https://digital.nhs.uk/data-and-information/ publications/statistical/adult-social-care-outcomes-framework-ascof/current. Accessed 30th March 2020. 48. Davey V, Fernández J-L, Knapp M, Vick N, Jolly D, Swift P, Tobin R, Kendall J, Ferrie J, Pearson C, Mercer G, Priestley M. Direct payments survey: A National Survey of direct payments policy and practice. London: Personal Social Services Research Unit, London School of Economics and Political Science; 2007. 74. NHS Digital (2019) Measures from the Adult Social Care Outcomes Framework 2018/19. Retrieved from https://digital.nhs.uk/data-and- information/publications/statistical/adult-social-care-outcomes-framework- ascof/upcoming. Accessed 30th March 2020. 49. References Laybourne A, Jepson M, Williamson T, Robotham D, Cyharova E, Williams V. Beginning to explore the experience of a direct payment for someone with dementia: the perspective of suitable people and adult social care practitioners. Dementia. 2016;15(1):125–40. 75. Public Health England. Public Health Outcomes Framework: Indicators at a Glance, February 2014. Public Health England. Retrieved from https://assets. publishing.service.gov.uk/government/uploads/system/uploads/attachment_ data/file/383436/PHOF_at_a_glance_November_2014_v5.pdf. Accessed 30th March 2020. 50. Jepson M, Laybourne A, Williams V, Chylarova E, Williamson T, Rowbotham D. Indirect payments: when the mental capacity Act interacts with the personalisation agenda. Heath Soc Care Commun. 2016;24(5):623–30. 76. Public Health England. Public Health Outcomes Framework: Indicators at a Glance, February 2014. Public Health England. Retrieved fromhttps://assets. publishing.service.gov.uk/government/uploads/system/uploads/attachment_ data/file/400155/PHOF_at_a_glance_February_2015.pdf. Accessed 30th March 2020. 51. Glendinning C, Halliwell S, Jacobs S, Rummery K, Tyer J. Buying independence. Bristol/ York: The Policy Press/Joseph Rowntree Foundation; 2000. 52. Mitchell W, Brooks J, Glendinning C. Carers’ roles in personal budgets: tensions and dilemmas in front line practice. Br J Soc Work. 2014;45(5):433–1450. 53. Coles B. A ‘suitable person’: an ‘insider’ perspective. Health Soc Care Commun. 2015;43(2):135–41. 77. Public Health England. Public Health Outcomes Framework: Indicators at a Glance, February 2016. Public Health England. Retrieved from https://www. gov.uk/government/statistics/public-health-outcomes-framework-february-2 016-data-update. Accessed 30th March 2020. 54. Public Health England. Public Health Outcomes Framework: Indicators at a Glance, February 2019. Public Health England. Retrieved from https://www. gov.uk/government/statistics/public-health-outcomes-framework-february-2 019-data-update. Accessed 30th March 2020. 78. Public Health England. Public Health Outcomes Framework: Indicators at a Glance, February 2017. Public Health England. Retrieved from https://www. gov.uk/government/statistics/public-health-outcomes-framework-february-2 017-data-update. Accessed 30th March 2020. 55. Department for Constitutional Affairs. Mental Capacity Act 2005 Code of Practice. London: TSO (The Stationery Office); 2007. 56. Netten A, Ryan M, Smith P, Skatun D, Healey A, Knapp M, Wykes T. The development of a measure of social care outcome for older people [DP1690/2]. Canterbury: PSSRU, University of Kent; 2002. 79. Public Health England. Public Health Outcomes Framework: Indicators at a Glance, February 2018. Public Health England. Retrieved from https://www. gov.uk/government/statistics/public-health-outcomes-framework-february-2 018-data-update. Accessed 30th March 2020. 57. Netten A, Beadle-Brown J, Caiels J, Forder J, Malley J, Smith N, Towers A, Trukeschitz B, Welch E, Windle K. ASCOT Adult Social Care Outcomes Toolkit: Main Guidance v2.1. PSSRU Discussion Paper 2716/3. Canterbury: PSSRU, University of Kent; 2011. 80. Purdy S. Avoiding Hospital Admissions. London: The Kings Fund; 2010. 80. Purdy S. Avoiding Hospital Admissions. Londo 81. Malley J, Netten A. Putting People First. References Development of the Putting People First User Experience Survey. PSSRU Discussion Paper 2637~2. Canterbury: University of Kent PSSRU: 2009. 58. Care DH. Support Act Statutory Guidance. London: Department of Hea 59. Rand S, Caiels J, Collins G, Forder J. Developing a proxy version of the adult social care outcome toolkit (ASCOT). Health Qual Life Outcomes. 2017;15:108. 82. Barberger-Gateau P, Dartigues JF, Letenneur L. Four instrumental activities of daily living score as a predictor of one year incident dementia. Age Ageing. 1993;22(6):457–63. 60. Malley JN, Towers AM, Netten AP, Brazier JE, Forder JE, Flyn T. An assessment of the construct validity of the ASCOT measure of social care-related quality of life with older people. Health Qual Life Outcomes. 2012;10:21. 83. Rowlett N, Deighton S. Direct Payments Case Study. A Simplified Service for Lincolnshire. Lincolnshire County Council. Retrieved from https://www. thinklocalactpersonal.org.uk/Latest/A-simplified-system-for-Lincolnshire/. Accessed 30th March 2020. 61. Van de Berg B, Spauwen P. Measurement of informal care: an empirical study into the valid measurement of time spent on informal caregiving. Health Econ. 2006;15:447–60. 62. Collin C, Wade DT, Davies S, Horne V. The Barthel ADL index: a reliability study. Int Disabil Stud. 1998;10:61–3. 84. Knapp M. The economics of social care. Basingstoke: Palgrave Macmillan; 1984. 63. Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179–86. 85. Rosenthal CJ, Matthews-Martin A, Keefe JM. Care management and care provision for older relatives amongst employed informal care-givers. Ageing Soc. 2007;27(5):755–78. y g g ; ( ) 64. Henderson S. Time and Other Inputs for High Quality Social Care. Wanless Social Care Review Background Paper London: Kings Fund Publishing; 2006 64. Henderson S. Time and Other Inputs for High Quality Social Care. Wanless 64. Henderson S. Time and Other Inputs for High Quality Social Care. Wanless Social Care Review Background Paper. London: Kings Fund Publishing; 2006. 64. Henderson S. Time and Other Inputs for High Quality Social Care. Wanless Social Care Review Background Paper. London: Kings Fund Publishing; 2006 86. Forder J, Jones K, Glendinning C, Caiels J. Welch E, Davidson J, Windle K, Irvine A, King D, Dolan P. Evaluation of the personal health budget programme. Discussion Paper 2840_2. Canterbury: University of Kent PSSRU; 2012. 65. Colin Cameron A, Trivedi PK. Microeconometrics using Stata. Texas: Stata Press; 2010. 66. Schmueli G. To explain or to predict? Stat Sci. 2010;25(3):289–310. 87. Arksey H, Baxter K. References J Gerontol Soc Work. 2018;62(2):1540. 34. Rabiee P, Glendinning C. Choice and control for older people using home care services: how far have council-managed personal budgets helped? Qual Ageing Older Adults. 2014;15(4):210–9. 10. Malbon E, Carey G, Meltzer A. Personalisation schemes in social care: are they growing social and health inequalities. BMC Public Health. 2019;19:805. 35. National Audit Office. Personalised Commissioning in Adult Social Care. London: National Audit Office; 2016. 11. Da Roit B, Le Bihan B. Similar and yet so different: cash-for-Care in six European Countries’ long-term Care policies. Milbank Q. 2010;88(3):286–309. 36. Woolham J, Steils N, Daly G, Ritters K. The impact of personal budgets on unpaid carers of older people. J Soc Work. 2018;18(2):119–41. 12. Department of Health. Making personal budgets work for older people: developing experience. London: Department of Health; 2008. 37. House of Commons. Personal Budgets in Social Care. London: House of Commons; 2016. 13. Department of Health. Moving forward: Using the Learning from the Individual Budgets Pilots. Response to the IBSEN Evaluation from the Department of Health. London: Department of Health; 2008. 38. Clark H, Gough H, Mcfarlane A. Direct payments and older people. York: Joseph Rowntree Foundation; 2004. 14. Department of Health. Personal health budgets guide – Third Party Organisations. The Families’ Perspective. London: Department of Health; 2012. 39. London Borough of Richmond upon Thames. Your support, your way. The story so far of Self-directed Support in the London Borough of Richmond upon Thames. 2010. Retrieved from http://www.in-control.org.uk/resources/ research-and-evaluation/your-support,-your-way-richmond.aspx. Accessed 30th May 2020. 15. Carr S. Improving personal budgets for older people: A research overview. Adult services report 63. London: Social Care Institute for Excellence; 2013. 16. Newbronner L, Chamberlain R, Bosanquet K, Bartlett C, Sass B, Glendinning C. Keeping persona budgets personal: learning from the experiences of older people, people with mental health problems and their Carers. Adult services report 40. London: Social Care Institute for Excellence; 2011. 40. Curtis L, Netten A. Unit costs of health and social Care: Personal Social Services Research Unit, University of Kent; 2006. 41. HSCIC. Personal Social Services Expenditure and Unit Costs, England – 2015- 16, Final release. Retrieved from http://content.digital.nhs.uk/pubs/ pssexpcosts1516. Accessed 30th May 2020. 17. Routledge M, Parkin T, Gollins T, Beckford C, Lewis J. Getting Better Outcomes for Older People Using Personal Budgets. London: Think Local Act Personal (TLAP); 2015. 88. Larkin M. Developing the knowledge base about carers and personalisation: contributions made by an exploration of carers’ perspectives and the carer- service relationship. Health Soc Care Commun. 2015;23(1):33–41. References Exploring the temporal aspects of direct payments. Br J Soc Work. 2012;42(1):147–64. 67. Santos Silva JMC, Tenreyo S. On the existence of the maximum likelihood estimates in Poisson regression. Econ Lett. 2010;107:310–2. 68. Act C. c.23. London: The Stationary Office; 2014. 88. Larkin M. Developing the knowledge base about carers and personalisation: contributions made by an exploration of carers’ perspectives and the carer- service relationship. Health Soc Care Commun. 2015;23(1):33–41. 69. Darton R, Forder J, Bebbington A, Netten A, Towers AM, Williams J. Analysis to support the development of the Relative Needs Formula for Older Page 17 of 17 Page 17 of 17 Davey BMC Geriatrics (2021) 21:1 Davey BMC Geriatrics (2021) 21:1 114. Leeuwen van KM, Malley J, Ostelo RW, Bosmans JE, Jansen APD, Horst Van Der HE, Netten A. What can local authorities do to improve the social care- related quality of life of older adults living at home? Evidence from the adult social Care survey. Health Place. 2014;29:104–13. 89. Lloyd J. Attendance Allowance and Local Government. London: The strategic society Centre; 2016. 90. OPM. Briefing Paper 4: Family, Friends and Personal Budgets. London: Office for Public Management; 2012. 115. Rand S, Malley J, Forder J. Are reasons for care-giving related to carers’ care- related quality of life and strain? Evidence from a survey of carers in England. Health Soc Care Commun. 2019;27(1):151–60. 91. Pickard L. Substitution between formal and informal care: a “natural experiment” in social policy in Britain between 1985 and 2000. Ageing Soc. 2012;32(7):1147–75. 116. Leece D, Leece J. Direct payments: creating a two-tiered system in social Care? Br J Soc Work. 2006;36(8):1379–93. 92. Carers UK. Facts about Carers. 2019. Retrieved from https://www.carersuk. org/news-and-campaigns/press-releases/facts-and-figures. Accessed 30 Mar 2020. 117. Corden A, Sainsbury R, Irvine A, Clarke S. The impact of disability living allowance and attendance allowance: findings from exploratory qualitative research. Research report no 649. London: Department for Work and Pensions; 2010. 93. Glendinning C, Arksey H, Jones K, Moran N, Netten A, Rabiee P. The individual budget pilot projects: impact and outcomes for carers: University of York: Social Policy Research Unit; 2009. 118. Leahy A. Too many ‘false dichotomies’? Investigating the division between ageing and disability in social care services in Ireland: A study with statutory and non-statutory organisations. J Aging Stud. 2018;44:34–44. 94. Brooks J, Mitchell W, Glendinning C. Personalisation, personal budgets and family carers. Whose assessment? Whose budget? J Soc Work. References 2017;17(2): 147–66. 95. Moran N, Arksey H, Glendinning C, Jones K, Rabiee P. Personalisation and Carers: whose rights? Whose benefits? Br J Soc Work. 2013;42(3):461–71. Publisher’s Note 96. Manthorpe J, Samsi K. ‘Inherently risky?’: Personal budgets for people with dementia and the risks of financial abuse: findings from an interview-based study with adult safeguarding coordinators. Br J Soc Work. 2013;43(5):889–903. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 97. Jones K, Netten A, Rabiee P, Gendinning C, Arksey H, Moran N. Can individual budgets have an impact on carers and the caring role? Ageing Soc. 2012;34(1):157–75. 98. Milne A, Larkin M. Knowledge generation about care-giving in the UK: a critical review of research paradigms. Health Soc Care Commun. 2014;23(1): 4–13. 99. Brouwer BF, Van Exel A, Job N, Van den Berg B, Van den Bos GAM, Koopmanschap MA. Process utility from providing informal care: the benefit of caring. Health Policy. 2005;74(1):85–99. 100. Al-Janabi H, Coast J, Flynn T. What do people value when they provide unpaid care for an older person? A meta ethnography with interview follow-up. Soc Sci Med. 2008;67(1):111–21. 100. Al-Janabi H, Coast J, Flynn T. What do people value when they provide unpaid care for an older person? A meta ethnography with interview follow-up. Soc Sci Med. 2008;67(1):111–21. 101. Muratore AM, Earl JK. Improving retirement outcomes: the role of resources, pre-retirement planning and transition characteristics. Ageing Soc. 2015; 35(10):2100–40. 101. Muratore AM, Earl JK. Improving retirement outcomes: the role of resources, pre-retirement planning and transition characteristics. Ageing Soc. 2015; 35(10):2100–40. 102. Andrén S, Elmståhl S. Family caregivers’ subjective experiences of satisfaction in dementia care: aspects of burden, subjective health and sense of coherence. Scand J Caring Sci. 2005;19:157–68. 102. Andrén S, Elmståhl S. Family caregivers’ subjective experiences of satisfaction in dementia care: aspects of burden, subjective health and sense of coherence. Scand J Caring Sci. 2005;19:157–68. 103. Leece J, Peace S. Developing New Understandings of Independence and Autonomy in the Personalised Relationship. Br J Soc Work. 2010;40(6):1847–65. 103. Leece J, Peace S. Developing New Understandings of Independence and Autonomy in the Personalised Relationship. Br J Soc Work. 2010;40(6):1847–65. 104. Slasberg, C. Personal budgets: the two legged stool that doesn’t add up. In, Beresford, P. Personalisation. Bristol: Policy Press; 2014. 104. Slasberg, C. Personal budgets: the two legged stool that doesn’t add up. In, Beresford, P. Personalisation. Bristol: Policy Press; 2014. 105. Kotokova S. Direct payments: the law and the reality. Publisher’s Note London: Think Local Act Personal; 2019. 106. Davey V. Direct payment rates in England. In Curtis L, Netten A (eds) Units Costs of Health and Social Care 2006, University of Kent. Canterbury: Personal Social Services Research Unit; 2006. 107. NHS Digital. Adult Social Care Activity and Finance: England 2017–18. Retrieved from https://digital.nhs.uk/data-and-information/publications/ statistical/adult-social-care-activity-and-finance-report/2017-18. Accessed 30th March 2020. 108. NHS Digital. Adult Social Care Activity and Finance: England 2016–17. Retrieved from https://digital.nhs.uk/data-and-information/publications/ statistical/adult-social-care-activity-and-finance-report/2016-17. Accessed 30th March 2020. 109. NHS Digital. Adult Social Care Activity and Finance: England 2015–16. Retrieved from https://digital.nhs.uk/data-and-information/publications/ statistical/adult-social-care-activity-and-finance-report/2015-16. Accessed 30th March 2020. 110. Rodrigues R, Glendinning C. Choice, competition and Care – developments in English social Care and the impacts on providers and older users of home Care services. Soc Policy Adm. 2015;49(5):649–64. 111. Tanner D, Ward L, Ray M. ‘Paying our own way’; application of the capability approach to explore older people’s experiences of self-funding social care. Crit Soc Policy. 2018;38(2):262–82. 112. Mahoney KJ, Mahoney EK, Morano C, DeVellis A. Unmet needs in self- directed HCBS programs. J Gerontol Soc Work. 2018;62(2):195–215. 113. Mead N, Lester H, Chew-Grantham C, Gask L, Bower P. Effects of befriending on depressive symptoms and distress: systematic review and meta-analysis. Br J Psychiatry. 2010;196(2):96–101.
https://openalex.org/W2754618462
https://europepmc.org/articles/pmc5614643?pdf=render
English
null
Phylogeographic, genomic, and meropenem susceptibility analysis of Burkholderia ubonensis
PLoS neglected tropical diseases
2,017
cc-by
10,806
OPEN ACCESS OPEN ACCESS Citation: Price EP, Sarovich DS, Webb JR, Hall CM, Jaramillo SA, Sahl JW, et al. (2017) Phylogeographic, genomic, and meropenem susceptibility analysis of Burkholderia ubonensis. PLoS Negl Trop Dis 11(9): e0005928. https://doi. org/10.1371/journal.pntd.0005928 Editor: Alfredo G. Torres, University of Texas Medical Branch, UNITED STATES Received: February 26, 2017 Accepted: September 3, 2017 Published: September 14, 2017 Copyright: © 2017 Price et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. * eprice@usc.edu.au (EPP); dave.wagner@nau.edu (DMW) Citation: Price EP, Sarovich DS, Webb JR, Hall CM, Jaramillo SA, Sahl JW, et al. (2017) Phylogeographic, genomic, and meropenem susceptibility analysis of Burkholderia ubonensis. PLoS Negl Trop Dis 11(9): e0005928. https://doi. org/10.1371/journal.pntd.0005928 RESEARCH ARTICLE Phylogeographic, genomic, and meropenem susceptibility analysis of Burkholderia Erin P. Price1,2*, Derek S. Sarovich1,2, Jessica R. Webb1, Carina M. Hall3, Sierra A. Jaramillo3, Jason W. Sahl3, Mirjam Kaestli1, Mark Mayo1, Glenda Harrington1, Anthony L. Baker4,5, Lindsay C. Sidak-Loftis3, Erik W. Settles3, Madeline Lummis3, James M. Schupp6, John D. Gillece6, Apichai Tuanyok3¤, Jeffrey Warner4, Joseph D. Busch3, Paul Keim3,6, Bart J. Currie1, David M. Wagner3* a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 1 Global and Tropical Health Division, Menzies School of Health Research, Darwin, Northern Territory, Australia, 2 Centre for Animal Health Innovation, Faculty of Science, Health, Education and Engineering, University of the Sunshine Coast, Sippy Downs, Queensland, Australia, 3 The Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America, 4 Environmental and Public Health Microbiology Research Group, Microbiology and Immunology, James Cook University, Townsville, Queensland, Australia, 5 Tasmanian Institute of Agriculture, University of Tasmania, Hobart, Tasmania, Australia, 6 Translational Genomics Research Institute, Flagstaff, Arizona, United States of America ¤ Current address: Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America * eprice@usc.edu.au (EPP); dave.wagner@nau.edu (DMW) ¤ Current address: Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America * i @ d (EPP) d @ d (DMW) Population biology of Burkholderia ubonensis model via a subcutaneous route of infection. Our results provide several new insights into the biology of this understudied species. model via a subcutaneous route of infection. Our results provide several new insights into the biology of this understudied species. the Defense Threat Reduction Agency (grant ID HDTRA1-12-C-0066; www.dtra.mil/), the Australian Research Council (grant ID LP110100691; www.arc.gov.au/), the US Centers for Disease Control and Prevention (grant ID NU50CK000480; www.cdc.gov), and the Northern Territory government (grant IDs NTRIB06 and NTRIB09; https://nt.gov.au/). EPP is funded by a USC Research Fellowship (http://usc.edu.au/), DSS is funded by an Advance Queensland Fellowship (AQRF13016-17RD2; http://advance.qld.gov.au/) and MK is supported by a Swiss National Science Foundation fellowship (PBBSB-111156; http:// www.snf.ch/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Author summary The pathogenic bacterium Burkholderia pseudomallei causes the disease melioidosis, which occurs in most tropical regions across the globe. The true burden of melioidosis is unknown but has been predicted to affect 165,000 people every year, resulting in 89,000 deaths. B. pseudomallei is easily confused with its close relative B. ubonensis as both species are frequently found in the same environmental niche and can appear phenotypically identical using serotyping and laboratory culture methods. B. ubonensis is a poorly charac- terised species but has recently gained interest in the research community as a potential biocontrol agent in B. pseudomallei-endemic regions, and for production of unusual and versatile biocompounds that are now being exploited for industrial applications. B. ubo- nensis is thought to be non-pathogenic, although other members of the B. cepacia complex to which it belongs are known for their ability to cause clinical disease that can be fatal in immunocompromised patients and people with cystic fibrosis. In this study, we investi- gated the biology of B. ubonensis to better understand its genetics, genomics, global distri- bution, virulence potential and antibiotic resistance. We show that this organism is highly genetically diverse, is avirulent in the mouse model, and can naturally encode high levels of meropenem resistance. We also identify B. ubonensis in the Caribbean for the first time, with phylogenomic analysis revealing distinct clades corresponding to geographic origin. Competing interests: The authors have declared that no competing interests exist. Abstract The bacterium Burkholderia ubonensis is commonly co-isolated from environmental speci- mens harbouring the melioidosis pathogen, Burkholderia pseudomallei. B. ubonensis has been reported in northern Australia and Thailand but not North America, suggesting similar geographic distribution to B. pseudomallei. Unlike most other Burkholderia cepacia complex (Bcc) species, B. ubonensis is considered non-pathogenic, although its virulence potential has not been tested. Antibiotic resistance in B. ubonensis, particularly towards drugs used to treat the most severe B. pseudomallei infections, has also been poorly characterised. This study examined the population biology of B. ubonensis, and includes the first reported isolates from the Caribbean. Phylogenomic analysis of 264 B. ubonensis genomes identified distinct clades that corresponded with geographic origin, similar to B. pseudomallei. A small proportion (4%) of strains lacked the 920kb chromosome III replicon, with discordance of presence/absence amongst genetically highly related strains, demonstrating that the third chromosome of B. ubonensis, like other Bcc species, probably encodes for a nonessential pC3 megaplasmid. Multilocus sequence typing using the B. pseudomallei scheme revealed that one-third of strains lack the “housekeeping” narK locus. In comparison, all strains could be genotyped using the Bcc scheme. Several strains possessed high-level meropenem resistance (32 μg/mL), a concern due to potential transmission of this phenotype to B. pseudomallei. In silico analysis uncovered a high degree of heterogeneity among the lipo- polysaccharide O-antigen cluster loci, with at least 35 different variants identified. Finally, we show that Asian B. ubonensis isolate RF23-BP41 is avirulent in the BALB/c mouse Editor: Alfredo G. Torres, University of Texas Medical Branch, UNITED STATES Received: February 26, 2017 Accepted: September 3, 2017 Published: September 14, 2017 Copyright: © 2017 Price et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: Raw sequences or assembled genomes for the 264 B. ubonensis genomes are available from the NCBI GenBank and/or SRA databases. Accession numbers are listed in S1 Table. Funding: This study was made possible by funding from the Australian National Health and Medical Research Council (grant IDs 236216, 383504, 605820, 1046812 and 1098337; https://www. nhmrc.gov.au/), the US Department of Defense Chemical and Biological Defense Program through 1 / 18 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 Population biology of Burkholderia ubonensis We have previously demonstrated that B. ubonensis is the most commonly co-isolated species when using B. pseudomallei enrichment methods in the melioidosis-endemic “Top End” of the Northern Territory, Australia, in part due to the indistinguishable nature of certain B. ubonen- sis and B. pseudomallei morphotypes [7]. In addition, it has been reported that the atypical B. pseudomallei O-antigen type B is found in 25% of B. ubonensis strains from Australia [12], fur- ther complicating the differentiation between these species due to their immunological cross- reactivity. Little is currently known about the population biology and genomics of B. ubonensis, although a clearer picture is emerging. The first B. ubonensis isolate (“B. uboniae” EY 3383, iso- lated from soil in Ubon Ratchathani in 1989) was reported in 2000 [13], and the first B. ubo- nensis genome (MSMB0022, isolated from soil in Darwin, Australia, in 2001) was sequenced to closure in 2015 [14]. The MSMB0022 genome encodes three circular replicons totalling ~7.2Mbp, which is approximately the same size as the two-chromosome B. pseudomallei genome. In Bcc species, the third replicon, a megaplasmid called pC3 (formerly chromosome III), has been shown to be important for stress resistance, virulence, and antifungal and pro- teolytic activity in several strains [15, 16]. This replicon is not essential for survival, with ~4% of tested Bcc isolates having spontaneously lost pC3, and additional strains able to be cured of this replicon either by plasmid incompatibility or by removal or toxin-antitoxin systems [15]. Although pC3 loss in B. ubonensis has been achieved in vitro, pC3 loss in wild-type B. ubonen- sis strains has not yet been identified. Previous work has shown that Bcc species can encode for innate high-level resistance towards many clinically relevant antibiotics, including the carbapenem antibiotic meropenem [17]. Meropenem is a critical antibiotic for melioidosis therapy, being considered the treat- ment of choice for those with life-threatening sepsis [18, 19]. To date, the vast majority of B. pseudomallei isolates have been fully susceptible to meropenem [20], although recent evidence has shown that decreased susceptibility towards meropenem can occur after prolonged use of this antibiotic in melioidosis patients with severe sepsis [21]. Certain Bcc species such as B. vietnamiensis, B. cepacia and B. cenocepacia [22], as well as B. pseudomallei [23, 24], exhibit high rates of intra-species recombination. This observation raises the concern that antibiotic resistance genes may spread amongst Burkholderia species in the environment and potentially to the globally important pathogen B. pseudomallei. The current study describes the first comprehensive analysis of the population biology of B. ubonensis from Australia and Asia. In addition, we identify the first B. ubonensis isolates from the Caribbean. Using large-scale comparative genome analysis, we interrogated 264 B. ubonen- sis genomes to better understand the geographic distribution and genetic diversity of this spe- cies, including potential loss of the pC3 megaplasmid. We also explored rates of meropenem resistance in Asian and Australian B. ubonensis strains, lipopolysaccharide (LPS) O-antigen cluster prevalence and diversity, and the virulence potential of an Asian B. ubonensis strain in the BALB/c mouse model. Introduction The Gram-negative soil- and water-dwelling bacterium B. ubonensis is a member of the Burkholderia cepacia complex (Bcc) [1], a genetically related group of metabolically diverse, highly adaptable and widely dispersed environmental species [2]. The Bcc, which comprises at least 20 species, includes some members known for their ability to cause clinical disease, such as severe sepsis in the immunocompromised and progressive pulmonary disease in cystic fibrosis patients [3]. Many Bcc species are also recognised for their unique biotechnological potential, particularly in bioremediation applications and in the production of antibiotic and antifungal compounds [4]. Novel compounds produced by B. ubonensis have been proposed as potential agents in biocontrol against Burkholderia pseudomallei [5] and in biodiesel cataly- sis [6]. B. pseudomallei, the causative agent of the tropical infectious disease melioidosis, is fre- quently isolated from the same soil samples as B. ubonensis in regions where both species are endemic [7]. Melioidosis is a diagnostically challenging and often deadly disease that affects humans and many animals, and remains underdiagnosed in many regions across the globe [8]. As B. pseudomallei is not a part of the healthy human flora, the ‘gold standard’ method for melioidosis confirmation is growth of B. pseudomallei from clinical specimens. For maximum isolation of B. pseudomallei from non-sterile sites such as sputum and pus, clinical laboratories require selective culture methods such as Ashdown’s agar containing gentamicin [9] and Ash- down’s broth containing colistin [10]. These media have also been used to successfully isolate B. pseudomallei from microbiologically complex environmental samples such as soil and sur- face water, which would otherwise yield growth and dominance of many other species [11]. PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 2 / 18 Genome sequencing, assemblies and annotation Genomic data were already publicly available for 230 of the 264 isolates [14, 27]. For complete- ness, we performed paired-end sequencing of the remaining 34 isolates using a HiSeq2000 instrument (Illumina Inc., San Diego, CA) at the Translational Genomics Research Institute (Phoenix and Flagstaff; AZ, USA). Assemblies were performed with the Microbial Genome Assembler Pipeline (MGAP; https://github.com/dsarov/MGAP---Microbial-Genome- Assembler-Pipeline), which incorporates Trimmomatic [28], Velvet [29], VelvetOptimiser (https://github.com/tseemann/VelvetOptimiser), GapFiller [30], PAGIT [31] and SSPACE [32] into its workflow, using the closed B. ubonensis MSMB0022 genome [14] as a reference for aligning, reordering and orientating contigs. All assemblies were quality-assessed by BLAST against phiX, with any contigs corresponding to this bacteriophage removed. Assem- blies were annotated using PGAP [33]. Reference accessions for all 264 genomes are listed in S1 Table. Isolates and species determination The 264 B. ubonensis isolates examined in this study originated from northern Australia (n = 238), Central Australia (n = 4), Ubon Ratchathani, Thailand (n = 15), Papua New Guinea (PNG; n = 1), and Puerto Rico (n = 6), and were obtained from samples of soil (n = 160), water (n = 15), or plant material (n = 2) (S1 Table). DNA was extracted using protocols optimised for B. pseudomallei [26], and quality-checked using a NanoDrop UV spectrophotometer. Prior to WGS, all isolates were verified as B. ubonensis using the Bu550 real-time PCR [7], which tar- gets the conserved iron-containing redox enzyme family protein encoded by BW23_5472 on chromosome II of MSMB0022 (also referred to as MSMB22 [14]). Population biology of Burkholderia ubonensis Ethics statement Procedures and ethics approval for collection of the environmental specimens from which the B. ubonensis isolates were recovered has been previously described [7, 25]. The murine chal- lenge work was conducted according to the specific guidelines provided by the United States Department of Agriculture Animal Welfare Act under approved protocols from the Northern Arizona University IACUC (Protocol 14–011) and the USA Department of Defense Animal Care and Use Review Office (ACURO approval for HDTRA1-12-C-0066_Wagner). PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 3 / 18 Population biology of Burkholderia ubonensis RF23-BP17, and RF32-BP11. Sequence coordinates for these LPS O-antigen clusters were extracted from MGAP-assembled genomes based on Mega BLAST analysis against the MSMB0057 O-antigen biosynthesis cluster [12]. Minimum inhibitory concentration (MIC) determination Etests (bioMe´rieux, Baulkham Hills, NSW, Australia) were used to determine meropenem MICs in 40 B. ubonensis strains (S1 Table). This subset of strains was chosen to represent geo- graphically and phylogenetically diverse taxa, and to identify potential MIC differences among strains of the same ST. Isolates were grown on Mueller Hinton agar for 24h at 37˚C in an oxy- genated environment prior to MIC assessment. Phylogenetic analysis The maximum parsimony function of PAUP v4.0a153 [38] was used for phylogenetic recon- struction of genome-wide variants. The Ortho_SNP_matrix.nex output automatically gener- ated by SPANDx was used as the PAUP input. Trees were constructed based on a heuristic search and bootstrapped using 100 replicates. FigTree (http://tree.bio.ed.ac.uk/software/ figtree/) was used to visualise PAUP outputs. Laboratory passaging for pC3 megaplasmid loss To promote pC3 loss in vitro, phylogenetically unrelated B. ubonensis strains MSMB0782 and MSMB1215 were passaged five times on Ashdown’s agar (37˚C for 24-48h), and strains INT1-BP274 and RF23-BP41 were passaged 10 times. MSMB0782 and INT1-BP274 were also subjected to five freeze/thaws ranging from -80˚C to room temperature, and INT1-BP274 was passaged seven times at 42˚C or room temperature. Eighteen colonies of MSMB2036, which is the same ST as the pC3-negative strain MSMB2035, were then examined for pC3 loss by pas- saging once on Luria-Bertani agar and growing at 37˚C for 48h. DNA from all laboratory-pas- saged strains was extracted using a chelex heat soak procedure [39] and diluted 1:10 prior to PCR. pC3 detection was carried out with primers Bu_pC3_For1 (5’-CGATGAGCTATTCG TTCGATCT) and Bu_ pC3_Rev1 (5’-AACGTGATCCGGTACAGCAC) to generate a 52bp amplicon, using a slowdown PCR for GC-rich templates [40]. MSMB2035 was included as the pC3-negative control. All DNA was verified for quality using the Bu550 assay [7]. Multilocus sequence typing (MLST) In silico MLST was carried out on all isolates using the Bcc scheme (http://pubmlst.org/bcc/), and on 173 of the 264 B. ubonensis isolates based on the B. pseudomallei scheme (http:// pubmlst.org/bpseudomallei/). Ninety-one strains could not be genotyped using the B. pseudo- mallei scheme as they lack the narK housekeeping locus [36]. Sequence types (STs) were deter- mined from assemblies using the BIGSdb tool, which is integrated into these MLST websites [37]. ST assignments for both schemes are listed in S1 Table and are also searchable on the online databases. Comparative genome analysis The default settings of SPANDx v3.0 [34] were used to identify biallelic single-nucleotide poly- morphisms (SNPs) from the 264 B. ubonensis genomes for phylogenetic analysis. B. ubonensis MSMB0022 was used as a reference genome for paired-end read alignment. BEDTools [35], which is run by default in SPANDx, was used to determine gene presence/absence relative to MSMB0022 using a 1kb locus ‘window’ size. Loci were considered variable if they had 99% read coverage in one or more strains, and conserved otherwise. To confirm the loss of pC3 (previously called chromosome III) in 10 isolates and to rule out alternative replicons being present in these strains, the unmapped reads from SPANDx for each strain were assembled using MGAP. BEDTools was also used to determine LPS O-antigen type based on mapping quality against both known and novel LPS O-antigen clusters. Known clusters included B. pseudomallei K96243 (Type A LPS; GenBank reference BX571965.1; coordinates 3196645–3215231), B. ubo- nensis MSMB0057 (Type B LPS; GenBank reference JF745807), B. pseudomallei 576 (Type B LPS; GenBank reference NZ_CP008777.1; coordinates 1383179–1418799), B. ubonensis MSMB0122 (Type B2 LPS; GenBank reference HQ908420.1), B. pseudomallei MSHR0840 (Type B2 LPS; GenBank reference GU574442.1), B. thailandensis 82172 (Type B2 LPS; GenBank reference JQ783347.1) and B. humptydooensis MSMB0043 (novel LPS; GenBank reference CP013380.1; coordinates 971381–996024). B. ubonensis type strains for determ- ining the prevalence of novel LPS O-antigen genotypes were: A21, BDU9, BDU12, BDU14, INT1-BP158, MSMB0022, MSMB0054, MSMB0063, MSMB0083, MSMB0103, MSMB0268a, MSMB0609, MSMB0742, MSMB0782, MSMB0827, MSMB1058, MSMB1137, MSMB1172, MSMB1173, MSMB1178, MSMB1189, MSMB1206, MSMB1304, MSMB1471, MSMB1517, MSMB1586, MSMB1591, MSMB2105, MSMB2123, MSMB2166, MSMB2180, MSMB2207, PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 4 / 18 Phylogeographic analysis of B. ubonensis The true global distribution of B. ubonensis is not known. To date, strains have only been reported from the environment in Wuhan, China [6], Ubon Ratchathani, Thailand [13], north- ern and Central Australia [7], and PNG [5]. In this study, we identified B. ubonensis in the Caribbean environment for the first time, with six isolates retrieved from soil obtained from the north-central and north-eastern regions of Puerto Rico (Juncos, Ceiba and Barceloneta). A recent study of soil samples in the southern United States to determine the presence of Burkhol- deria spp., and particularly B. pseudomallei, did not yield a single B. ubonensis or B. pseudomallei isolate, although several other Bcc species were retrieved [40]. It is thus probable that neither B. ubonensis nor B. pseudomallei are naturally found in the environment in North America. It remains to be determined whether B. ubonensis is found in other melioidosis-endemic regions such as Africa, Central America, the Indian Ocean islands, South America or South Asia. A B. ubonensis phylogeny was reconstructed from 264 genomes derived from Australian, Thai, PNG and Puerto Rican isolates to determine the existence of a continental phylogeo- graphic signal, a phenomenon that has been described in B. pseudomallei [23, 46, 47]. Based on 589,433 biallelic SNPs, six distinct and well-supported clades were identified. Clades II, IV, V and VI solely contained Australian B. ubonensis isolates (n = 240), whereas Clade I contained all isolates from Thailand (n = 15), the PNG isolate A21, and two Australian strains from the tropical “Top End” region of the Northern Territory, and Clade III was comprised of the six Puerto Rican isolates (Fig 1; S1 Fig). Subclades within Clade I showed that the Thai strains clustered most closely with one another (Fig 1), with A21 residing on its own branch and the two Australian strains, MSMB2035 and MSMB2036, sharing a node with the PNG isolate. The Puerto Rican isolates share a node with the Clade IV Australian isolates (Fig 1). Due to limited availability of B. ubonensis from PNG, it could not be determined whether other PNG isolates group with A21, although we hypothesise that PNG B. ubonensis strains will be related based on the relatively narrow genetic diversity observed in PNG B. pseudomallei populations [47, 48]. Phylogeographic analysis of B. ubonensis Within Clade IV, four isolates from the arid region of Central Australia (MSMB2166, MSMB2167, MSMB2185 and MSMB2186), which were obtained from the same soil sample, grouped with other Australian strains, with the most closely related isolates originating from the “Top End” region. Taken together, these results demonstrate that, like B. pseudomallei, B. ubonensis populations exhibit a continental phylogeographic signal, although more samples from Asia and PNG would be needed to improve resolution of subclades within Clade I. Population biology of Burkholderia ubonensis intranasal [42, 43] or aerosol [44] routes. Virulence testing was performed in a similar manner as previously described [45]. After shipping, mice were acclimatised for five days before the experiment; food and water were provided ad libitum throughout the study. Mice were lightly anaesthetised with vaporised isoflurane and injected via a single 100μL sc injection in the scruff of the neck. All mice in a single cage received the same infectious dose (B. ubonensis: 1.71 x 104, 105 or 106 CFU). Three infection control mice were injected in an identical way, but with 100μL of sterile 1x PBS instead of bacterial culture. Mice were monitored daily for health status and euthanased on day 21 post-injection with CO2 gas followed by exsanguination. B. ubonensis murine challenge The ability of B. ubonensis to cause disease via the subcutaneous (sc) route of infection was examined in a murine BALB/c model using a Thai environmental isolate, RF23-BP41 (S1 Table), collected by Northern Arizona University in 2007. We compared the results to sc infec- tion with B. thailandensis type strain E264, which is known to cause death in mice at high doses (>106 colony forming units, or CFU) when delivered via the intraperitoneal [41], PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 5 / 18 Comparison of phylogenomic structure and MLST We compared B. ubonensis MLST genotypes obtained using both the B. pseudomallei and Bcc MLST schemes with phylogenomic assignment to determine whether the STs reflected isolate relatedness on the genome level [49], or whether homoplasy was evident among STs as has been observed with certain B. pseudomallei STs [50, 51]. For both MLST schemes, the ST and PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 6 / 18 Population biology of Burkholderia ubonensis Fig 1. Phylogenomic analysis of 264 Burkholderia ubonensis genomes. A midpoint-rooted maximum parsimony phylogeny was constructed using 589,433 biallelic core-genome SNPs. A) Strains lacking the B. pseudomallei multilocus sequence typing (MLST) gene narK are labelled with blue branches, and those lacking pC3 (previously known as chromosome III) are in bold italics. Highly related strains retrieved from single environmental samples are outlined by green boxes. Red branches indicate instances where isolates could be differentiated by the B. pseudomallei MLST scheme, but not the Bcc scheme. B) Heatmap of the meropenem minimum inhibitory concentration values for 40 tested B. ubonensis isolates. In both trees, the six distinct clades (I, II, III, IV, V and VI) are labelled. Consistency index = 0.25. Bootstrap values below 80% are labelled on their corresponding branches. https://doi org/10 1371/journal pntd 0005928 g001 Fig 1. Phylogenomic analysis of 264 Burkholderia ubonensis genomes. A midpoint-rooted maximum parsimony phylogeny was constructed using 589,433 biallelic core-genome SNPs. A) Strains lacking the B. pseudomallei multilocus sequence typing (MLST) gene narK are labelled with blue branches, and those lacking pC3 (previously known as chromosome III) are in bold italics. Highly related strains retrieved from single environmental samples are outlined by green boxes. Red branches indicate instances where isolates could be differentiated by the B. pseudomallei MLST scheme, but not the Bcc scheme. B) Heatmap of the meropenem minimum inhibitory concentration values for 40 tested B. ubonensis isolates. In both trees, the six distinct clades (I, II, III, IV, V and VI) are labelled. Consistency index = 0.25. Bootstrap values below 80% are labelled on their corresponding branches. https://doi.org/10.1371/journal.pntd.0005928.g001 genomic data showed excellent concordance and no evidence of ST homoplasy, with all identi- cal STs clustering closely on the phylogeny (Fig 1A; green box outlines) and non-identical STs residing on separate branches. Unlike the Bcc scheme, where STs could be assigned from all genomes, STs were not able to be determined for 91 (35%) isolates using the B. Comparison of phylogenomic structure and MLST pseudomallei MLST scheme due to these strains lacking the “housekeeping” locus narK [36]. We identified five separate clusters within our phylogeny that lacked narK (Fig 1A; blue branches). The first included all the Thai isolates (n = 15), with the remaining four comprising all Puerto Rican (Clade III; n = 6) and Clade IV (n = 14) isolates, plus 57 isolates within Clade VI that were iso- lated from various “Top End” locales. These results show that certain B. ubonensis strains cannot be fully genotyped with the B. pseudomallei MLST scheme. However, in three instances where strains could be genotyped, the B. pseudomallei scheme was superior at differentiating strains that were related yet distinct on a genomic level (Fig 1, red branches; S1 Table). MSMBs 1225 and 1559 were both ST-1187 using the Bcc scheme but were different STs using the B. pseudo- mallei scheme; MSMB2013 was assigned ST-1235 by both schemes but the other Bcc ST-1235 strains were found to be ST-1226 according to the B. pseudomallei scheme; and the Bcc ST-1148 strains were separated into ST-1266 and ST-1267 based on the B. pseudomallei alleles. In all cases where additional STs were found, the isolates were obtained from distinct soil samples, indicating greater resolving power of the B. pseudomallei MLST scheme in these cases. Comparison of phylogenomic structure and meropenem MICs We mapped meropenem MICs for 40 strains against the genome phylogeny to ascertain whether meropenem-resistant, meropenem-intermediate or meropenem-sensitive strains PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 7 / 18 Population biology of Burkholderia ubonensis Fig 2. Example Etest results in Burkholderia ubonensis towards meropenem. Left, sensitive isolate MSMB2152 at a minimum inhibitory concentration (MIC) of 3 μg/mL; centre, intermediate isolate MSMB1183 at an MIC of 6 μg/mL; right, resistant isolate MSMB1162 at an MIC of 32 μg/mL. https://doi.org/10.1371/journal.pntd.0005928.g002 Fig 2. Example Etest results in Burkholderia ubonensis towards meropenem. Left, sensitive isolate MSMB2152 at a minimum inhibitory concentration (MIC) of 3 μg/mL; centre, intermediate isolate MSMB1183 at an MIC of 6 μg/mL; right, resistant isolate MSMB1162 at an MIC of 32 μg/mL. https://doi.org/10.1371/journal.pntd.0005928.g002 belonged to a single clade. Eleven strains (Bp8955, Bp8958, Bp8960, Bp8961, Bp8962, Bp8964, MSMB1162, MSMB1471, MSMB2166, RF32-BP11 and RF32-BP3) showed high-level resis- tance (32 μg/mL) towards this antibiotic, including all six Puerto Rican strains. In contrast, two Australian strains (MSMB1215 and MSMB2152) exhibited the lowest MICs at 2–3 μg/mL (Fig 2). Both highly resistant and highly sensitive (2–6 μg/mL) strains were found in the Asian and Australian populations, demonstrating that these phenotypes are not restricted to a certain clade and that B. ubonensis populations from these two geographic regions encode for a range of meropenem MICs (Fig 1B). Although our testing was not comprehensive, we did observe similar MICs for closely related strains. For example, the closely related Thai strains RF23- BP93, RF32-BP4 and RF32-BP6 all exhibited MICs of 24 μg/mL (Fig 1B). The lack of phyloge- netic congruence of high-level meropenem-resistant strains supports the hypothesis that the genetic mechanism conferring resistance is laterally transferred among strains. Alternatively, resistance may have arisen multiple times or through multiple mechanisms during the evolu- tion of B. ubonensis due to similar environmental pressures. belonged to a single clade. Eleven strains (Bp8955, Bp8958, Bp8960, Bp8961, Bp8962, Bp8964, MSMB1162, MSMB1471, MSMB2166, RF32-BP11 and RF32-BP3) showed high-level resis- tance (32 μg/mL) towards this antibiotic, including all six Puerto Rican strains. In contrast, two Australian strains (MSMB1215 and MSMB2152) exhibited the lowest MICs at 2–3 μg/mL (Fig 2). Both highly resistant and highly sensitive (2–6 μg/mL) strains were found in the Asian and Australian populations, demonstrating that these phenotypes are not restricted to a certain clade and that B. PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 Population biology of Burkholderia ubonensis other Bcc species should be a focus of future studies to not only promote a better understand- ing of resistance mechanisms in these species, but to also provide a basis for proactive moni- toring of B. pseudomallei populations in the event of carbapenamase acquisition. Genetic diversity of B. ubonensis MLST revealed that B. ubonensis is a highly diverse species. We found 128 STs among the 173 strains that could be genotyped using the B. pseudomallei MLST scheme, and 182 STs among the 264 strains based on the Bcc scheme, although these numbers underestimate diversity due to multiple related isolates being tested from single environmental specimens in our study (S1 Table). Among the 33 Bcc scheme STs represented by two or more B. ubonensis isolates, 27 (82%) of these STs were found within a single sample; such samples are likely to be identical or clonally related due to their physical proximity. We next examined B. ubonensis diversity within our environmental samples. Of the 51 samples where two or more B. ubonensis isolates were retrieved, 26 (51%) exhibited two or more STs, revealing that multiple B. ubonensis geno- types commonly exist within single environmental samples. This result reflects similar obser- vations made in studies examining B. pseudomallei diversity in environmental samples from Thailand [57, 58], B. vietnamiensis in the United States [40], and B. cepacia genomovar III (now known as B. cenocepacia) in the United States, Canada and Australia [59]. Whilst isola- tion of multiple colonies from a single sample is a laborious endeavour, these studies reinforce the need to collect multiple isolates from individual samples to maximise capture of population diversity. Comparison of phylogenomic structure and meropenem MICs ubonensis populations from these two geographic regions encode for a range of meropenem MICs (Fig 1B). Although our testing was not comprehensive, we did observe similar MICs for closely related strains. For example, the closely related Thai strains RF23- BP93, RF32-BP4 and RF32-BP6 all exhibited MICs of 24 μg/mL (Fig 1B). The lack of phyloge- netic congruence of high-level meropenem-resistant strains supports the hypothesis that the genetic mechanism conferring resistance is laterally transferred among strains. Alternatively, resistance may have arisen multiple times or through multiple mechanisms during the evolu- tion of B. ubonensis due to similar environmental pressures. Many other Bcc species strains can exhibit high-level meropenem resistance [17, 52], indi- cating that this trait is not specific to B. ubonensis, although the basis for this resistance and its persistence in Bcc populations is not clear. In comparison, the highest meropenem MICs recorded for B. pseudomallei to date are ~4 μg/mL [53, 54], with wild-type strains consistently exhibiting MICs of 0.75–1 μg/mL. Unlike B. pseudomallei, where human-to-human transmis- sion is exceptionally rare and where infections are almost always acquired from the environ- ment [55], Bcc species can transmit between individuals, and indeed this a major clinical issue in the management of cystic fibrosis cohorts [56]. The selective forces acting upon Bcc strains in patients receiving meropenem or other antibiotics may encourage this phenotype to persist in the population, although the lack of human B. ubonensis infections and the identification of high-level meropenem resistance in environmental samples argue against this route of selec- tion in the context of B. ubonensis. B. pseudomallei does not encode a carbapenamase, which likely explains why high-level resistance has not been reported. However, it is conceivable that B. pseudomallei may acquire a carbapenamase whilst residing in the environment, especially from closely related species that share this niche, such as B. ubonensis or other Bcc species. Determining the molecular basis for high-level meropenem resistance in B. ubonensis and in 8 / 18 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 The megaplasmid pC3 is nonessential to B. ubonensis replication Green = 100% mapped reads; red = 0% mapped reads. Taxa are in rows and the 1kb windows are in columns. Only regions containing <80% window coverage for at least one strain are shown, representing 2.78Mbp of the MSMB0022 B. ubonensis genome. The absence of pC3 in 4% of strains demonstrates that this megaplasmid can occasionally segregate, a finding consistent with pC3 in other Bcc species [15]. https://doi org/10 1371/journal pntd 0005928 g003 Fig 3. Heatmap of variably present Burkholderia ubonensis genes across the MSMB0022 genome. A presence/absence matrix was constructed across 1kb windows of the MSMB0022 reference genome for each of the 264 taxa. Green = 100% mapped reads; red = 0% mapped reads. Taxa are in rows and the 1kb windows are in columns. Only regions containing <80% window coverage for at least one strain are shown, representing 2.78Mbp of the MSMB0022 B. ubonensis genome. The absence of pC3 in 4% of strains demonstrates that this megaplasmid can occasionally segregate, a finding consistent with pC3 in other Bcc species [15]. Fig 3. Heatmap of variably present Burkholderia ubonensis genes across the MSMB0022 genome. A presence/absence matrix was constructed across 1kb windows of the MSMB0022 reference genome for each of the 264 taxa. Green = 100% mapped reads; red = 0% mapped reads. Taxa are in rows and the 1kb windows are in columns. Only regions containing <80% window coverage for at least one strain are shown, representing 2.78Mbp of the MSMB0022 B. ubonensis genome. The absence of pC3 in 4% of strains demonstrates that this megaplasmid can occasionally segregate, a finding consistent with pC3 in other Bcc species [15]. https://doi.org/10.1371/journal.pntd.0005928.g003 varying conditions, including multiple freeze/thaws, growth at 42˚C and room temperature, or multiple passages. Despite these attempts, none were successful at segregating pC3. To exam- ine whether an insufficient number of colonies were being tested, we next attempted passage of 18 colonies of MSMB2036, which is closely related to the pC3-lacking strain MSMB2035. Four (22%) colonies lost pC3 after a single passage on Luria-Bertani agar at 37˚C for 48h, as observed by a lack of amplification using the Bu_pC3 primers. This finding demonstrates that, as with other Bcc species, the third replicon of B. ubonensis is not necessary for the organism’s survival, at least in a laboratory setting. It remains to be determined whether pC3 replicates independently of the two chromosomes in B. ubonensis. The megaplasmid pC3 is nonessential to B. ubonensis replication Gene presence/absence analysis of the 264 B. ubonensis genomes against the MSMB0022 refer- ence showed that 2.78Mbp (39%) of the B. ubonensis reference genome was variably present, with the remaining 4.41Mbp conserved across these strains. Ten phylogenetically unrelated strains (A21, MSMB0312a, MSMB0668, MSMB0705, MSMB1080, MSMB1509, MSMB1520, MSMB1809, MSMB2035 and MSMB2108) failed to map reads against the entire sequence for pC3, equating to one-third of the variable regions observed in our dataset (Fig 3). Certain closely related strains did not share this pattern: for example, MSMB2035 and MSMB2036 are clonal according to the two MLST schemes and the WGS phylogeny, yet only MSMB2035 lacked this replicon. Phylogenetic reconstruction using just pC3 as the reference showed no evidence of lateral transfer, with the topology of the tree being highly similar to the phyloge- netic tree constructed for chromosomes I and II (Fig 1). This result suggests that pC3 is proba- bly ubiquitous in B. ubonensis strains found in the environment and that it largely follows a vertical path of evolution, but, when propagated under certain conditions, segregation of this replicon can occur spontaneously; in our study, segregation occurred in 4% of strains. Agnoli and coworkers (2014) also observed that four of 110 Bcc isolates tested in their study (4%) had lost pC3, with one of these events having been confirmed to have occurred following labora- tory passage [15]. In the type strain MSMB0022, pC3 encodes for 669 genes that are involved in myriad functions (S2 Table). When excluding this replicon, 1.86Mbp (26%) of the B. ubo- nensis reference genome was variable among the 264 strains. The conservation of pC3 and its phylogenetic relatedness to chromosomes I and II confirms that pC3 is under strong selection pressure to be maintained in Bcc species, including B. ubo- nensis. However, certain growth conditions appear to encourage pC3 segregation, raising the possibility that this replicon may be a megaplasmid [60]. Based on the earlier work of Agnoli and colleagues [15, 16], we attempted to cure B. ubonensis strains MSMB0782, MSMB1215, INT1-BP274 and RF23-BP41 of pC3 by performing laboratory passage and growth under PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 9 / 18 Population biology of Burkholderia ubonensis Fig 3. Heatmap of variably present Burkholderia ubonensis genes across the MSMB0022 genome. A presence/absence matrix was constructed across 1kb windows of the MSMB0022 reference genome for each of the 264 taxa. B. ubonensis exhibits high levels of LPS O-antigen diversity Earlier work has shown that 25% of Australian B. ubonensis strains possess the unusual B. pseudomallei type B LPS O-antigen [12]. Using our larger dataset, we examined LPS diver- sity among the 264 strains in silico. Due to insufficient contig coverage across the LPS clus- ter, 19 strains could not be fully genotyped using this approach; however, these strains did not possess clusters matching to other LPS types. Of the remaining 245 strains that could be genotyped, type B LPS was identified in 20 (8%). In total, 35 different LPS types were found, compared with only four LPS types among 477 global B. pseudomallei strains using the same in silico approach. The most abundant LPS type in the B. ubonensis cohort was MSMB0063 Type Novel, with 28 strains having this genotype; in contrast, eleven LPS types were seen in only a single isolate (S1 Table). LPS genotypes were not restricted to particular STs or geo- graphic regions. For example, the Thai strains RF25-BP1 and RF32-BP3 possessed an LPS cluster that was also found in Australian strains MSMB0782, MSMB0783, MSMB1188, MSMB1562, MSMB1603, and MSMB1635, and among these eight isolates, seven different STs were present. Our findings are consistent with the presence of similar LPS types among Burkholderia species. In addition, we show that B. ubonensis LPS is highly variable and is not associated with the genetic relatedness or geographic origin of an isolate, and would thus be a poor marker for such purposes. Population biology of Burkholderia ubonensis VecScreen tools; however, we found that these tools also failed to identify the B. vietnamiensis megaplasmid pBVIE01, possibly because PlasmidFinder has been optimised for plasmid iden- tification in Enterobacteriaceae [64]. BLAST analysis of parA and parB genes from B. vietna- miensis G4 pBVIE01 showed weak evidence of these partitioning system genes in MSMB0022 pC3, although more solid BLAST hits were obtained with chromosome I genes. This result does not rule out the presence of plasmid maintenance loci encoded on this replicon, but rather demonstrates the difficulties in identifying genetic homology across distantly related species. Similarly, the presence of 5S, 16S and 23S ribosomal RNA-encoding genes on pC3 does not necessarily rule out this replicon as being a megaplasmid [16, 60]. Read depth cover- age analysis of pC3 showed similar depth to the two chromosomes (e.g. MSMB0011: 108x for pC3 vs 123x for chromosome I and 124x for chromosome II), indicating that this megaplasmid is at a low or single copy number, a finding that is consistent with the generally low copy num- ber of larger plasmids [65]. The megaplasmid pC3 is nonessential to B. ubonensis replication It has been proposed that the second (and where applicable) third ‘chromosomes’ found in approximately 10% of bacterial genomes are in fact ‘chromids’, a term used to define replicons that are not strictly chromosomes or plasmids [61]. To maintain consistency with the work of Agnoli and colleagues [15, 16], we have chosen to refer to this replicon as a pC3 megaplasmid. At 920kb, the B. ubonensis pC3 megaplasmid is unusually large, although such size is not unprecedented, with B. cenocepacia H111 encoding a curable 1.04Mbp pC3 megaplasmid [16]. Larger megaplasmids have been identified in other soil- and rhizosphere-dwelling organisms including a 1.8Mbp linear megaplasmid identified in the actinomycete Streptomyces clavuli- gerus [62], and a 1.59Mbp megaplasmid in Azospirillum brasilense [63]. The pC3 replicon of B. ubonensis MSMB0022 failed to be detected as a plasmid using the online PlasmidFinder and 10 / 18 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 Population biology of Burkholderia ubonensis several reasons. First, its Thai origin maximises the probability of genetic relatedness to the putatively pathogenic LMG 24263 strain. Second, RF23-BP41 was isolated from a region where individuals (particularly rice farmers) regularly come into contact with soil bacteria, increasing the likelihood of successful human infection. Third, this strain demonstrated resis- tance towards meropenem (MIC 16μg/mL), which would potentially confer a selective advan- tage during antibiotic treatment. Finally, this strain harbours pC3, which has been shown to impart virulence capacity in other Bcc species [15, 16]. Even at the highest dose of 1.7x106 CFU, no mice exhibited weight loss or lethargy during the 21-day challenge experiment, with their health status identical to that of the three control mice. The same result was observed in the BALB/c mice subcutaneously injected with B. thailandensis E264 at a similar dosage range [45]. Certain B. thailandensis strains are capable of infecting immunocompromised humans [67–69], and can be lethal in murine models when administered at high doses via other routes [41–44]. In contrast, in other studies the 10-day LD50 of B. pseudomallei in BALB/c mice was ~1x103 CFU when delivered via the sc route [70], and between 10 and 6x104 CFU when administered via the intraperitoneal route, with virulence reduced but not abolished in highly laboratory-passaged strains [71, 72]. Other mouse model studies have shown that virulence of Bcc species can vary; for example, the epidemic B. cenocepacia strain J2315 caused universal mortality when inoculated at 103 cfu into gp91phox−/−mice via an intratracheal route, whereas other B. cenocepacia strains were less virulent and B. vietnamiensis strain R2 was avirulent [73]. Another study using intranasal inoculation of leukopaenic BALB/c mice with ~104 cfu also showed differential virulence within Bcc species, with some mice clearing their infections [74], indicating that virulence potential varies among strains. Based on the findings of these earlier studies, pathogenicity may also vary among B. ubo- nensis strains. Characterising the virulence potential of other B. ubonensis strains may identify unusual pathogenic strains, although we deem this unlikely based on the lack of verified human infections caused by B. ubonensis. In consideration of the IACUC guidelines, we chose not to carry out testing of further strains using the mouse model. We acknowledge that our study only tested B. ubonensis in immunocompetent BALB/c mice via a sc route. The use of immunocompromised or immune-deficient mouse models or infection via different routes may reveal that B. ubonensis can cause disease in such cases. Bcc species carry various virulence factors that are thought to contribute to their pathogenic potential, including extracellular lipases, metalloproteases, serine proteases, flagella, pili, adhesins, toxins, siderophores and lipo- polysaccharides [75]. We did not investigate the presence of virulence genes in B. ubonensis compared with other Bcc species but doing so may shed further light on its potential virulence capacity. It may be possible to use such in silico methods rather than further animal experi- ments to determine whether B. ubonensis is unusual compared with other Bcc species due to a lack of key virulence loci or pathways in its genome. B. ubonensis RF23-BP41 does not cause disease in the immunocompetent BALB/c mouse model Unlike other Bcc species or B. pseudomallei, B. ubonensis is thought to rarely, if ever, cause dis- ease in humans [66], as evidenced by B. ubonensis being the only Bcc species not yet retrieved from cystic fibrosis sputum [52]. Indeed, there is only a single report of B. ubonensis being iso- lated from a human infection, a Thai nosocomial case (strain LMG 24263 [1]). Given the absence of other reported B. ubonensis infections to date, the role of B. ubonensis as the aetiolo- gic agent in this Thai case should be treated with scepticism; for instance, testing for the pres- ence of known pathogens in the same clinical specimen was not stated. However, another possibility is that certain B. ubonensis strains are in fact capable of causing disease, with such cases remaining unreported due to insufficient or inaccurate differentiation of B. ubonensis from other Bcc species. To further examine the virulence potential of B. ubonensis, we inoculated BALB/c mice via sc injection using 1.7x 104, 105, and 106 CFU of the Thai strain RF23-BP41. To our knowledge, B. ubonensis virulence has not yet been tested in the mouse model. RF23-BP41 was chosen for PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 11 / 18 Population biology of Burkholderia ubonensis laboratory setting. Like other Bcc species, we show that B. ubonensis strains exhibit variable levels of meropenem resistance. Determining the molecular mechanism underpinning high- level meropenem resistance in certain B. ubonensis strains will provide a better understanding of the potential transmission of this phenotype to the melioidosis bacterium B. pseudomallei, which frequently co-resides with B. ubonensis in the environment. Finally, using the immuno- competent BALB/c mouse model, we show that an Asian B. ubonensis strain is not likely to cause disease, providing evidence that at least some members of this species are probably avir- ulent in immunocompetent individuals. Further studies are needed to confirm the avirulent nature of B. ubonensis across a greater strain set using both immunocompetent and immuno- compromised or immunodeficient animal models, or in silico analysis of the B. ubonensis genome to identify intact virulence determinants. The apparent non-pathogenic nature of cer- tain B. ubonensis strains may make them amenable to large-scale biotechnological applications, such as biocontrol and biofuel production. Acknowledgments We wish to thank Ian Harrington and Vanessa Theobald (Menzies School of Health Research) for isolate collection and laboratory assistance, Jay E. Gee and Alex R. Hoffmaster (US Centers for Disease Control and Prevention) for helpful discussions in planning and organising the environmental sampling of Burkholderia spp. in Puerto Rico, and Dr Charlotte Peeters (Ghent University) and Keith Jolley (University of Oxford) for B. cepacia complex MLST database assistance. Supporting information S1 Fig. Whole-genome maximum parsimony phylogeny of Burkholderia ubonensis relative to other Burkholderia species based on 296,578 biallelic SNPs. B. ubonensis Clades I-VI are labelled, and B. ubonensis strains from regions other than Australia are noted. Consistency index = 0.36. The tree was rooted with the B. pseudomallei complex species. In total, 277 taxa were used to reconstruct this phylogeny, of which 264 were B. ubonensis. (PDF) Conclusions The metabolic diversity of Bcc species continues to spur interest in this highly adaptable group of bacteria. Our study provides important new insights into the biology of B. ubonensis, a largely neglected member of the Bcc due to its ostensibly avirulent nature. Genomic analysis of 264 B. ubonensis strains from Australia, PNG, Puerto Rico and Thailand revealed that B. ubo- nensis is a genetically highly diverse organism, with at least 26% of its chromosomal DNA vari- ably present among strains. Like B. pseudomallei, B. ubonensis has a distinct phylogeographic signature that can be distinguished at the genomic level. It remains to be determined whether B. ubonensis is found on other continents. ‘Chromosome III’ encodes a ubiquitous yet appar- ently dispensable pC3 megaplasmid, similarly to other Bcc species, and can segregate in the PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 12 / 18 Writing – original draft: Erin P. Price, Derek S. Sarovich. Writing – original draft: Erin P. Price, Derek S. Sarovich. Writing – original draft: Erin P. Price, Derek S. Sarovich. Writing – review & editing: Erin P. Price, Derek S. Sarovich, Jessica R. Webb, Carina M. Hall, Sierra A. Jaramillo, Jason W. Sahl, Mirjam Kaestli, Mark Mayo, Glenda Harrington, Anthony L. Baker, Lindsay C. Sidak-Loftis, Erik W. Settles, Madeline Lummis, James M. Schupp, John D. Gillece, Apichai Tuanyok, Jeffrey Warner, Joseph D. Busch, Paul Keim, Bart J. Currie, David M. Wagner. Population biology of Burkholderia ubonensis Investigation: Erin P. Price, Derek S. Sarovich, Jessica R. Webb, Carina M. Hall, Sierra A. Jara- millo, Jason W. Sahl, Mirjam Kaestli, Mark Mayo, Glenda Harrington, Anthony L. Baker, Lindsay C. Sidak-Loftis, Erik W. Settles, Madeline Lummis, Joseph D. Busch. Methodology: Erin P. Price, Derek S. Sarovich, Jessica R. Webb, Carina M. Hall, Sierra A. Jara- millo, Jason W. Sahl, Mirjam Kaestli, Glenda Harrington, Lindsay C. Sidak-Loftis, Erik W. Settles, Madeline Lummis, James M. Schupp, John D. Gillece, Joseph D. Busch. Project administration: Erin P. Price, Derek S. Sarovich, Carina M. Hall, Mirjam Kaestli, Mark Mayo, James M. Schupp, John D. Gillece, Apichai Tuanyok, Jeffrey Warner, Joseph D. Busch, David M. Wagner. Resources: Erin P. Price, Derek S. Sarovich, Mirjam Kaestli, Mark Mayo, Glenda Harrington, Anthony L. Baker, James M. Schupp, John D. Gillece, Apichai Tuanyok, Jeffrey Warner, Paul Keim, Bart J. Currie, David M. Wagner. Software: Erin P. Price, Derek S. Sarovich, Jason W. Sahl. Supervision: Erin P. Price, Derek S. Sarovich, Carina M. Hall, Erik W. Settles, Apichai Tua- nyok, Jeffrey Warner, Joseph D. Busch, Paul Keim, Bart J. Currie, David M. Wagner. Validation: Erin P. Price, Derek S. Sarovich, Jessica R. Webb, Carina M. Hall, Erik W. Settles, John D. Gillece, Joseph D. Busch. Visualization: Erin P. Price, Derek S. Sarovich, Carina M. Hall. Author Contributions Conceptualization: Erin P. Price, Mirjam Kaestli, Mark Mayo, Bart J. Currie, David M. Wagner. Data curation: Erin P. Price, Derek S. Sarovich, Jessica R. Webb, Carina M. Hall, Jason W. Sahl, Mirjam Kaestli, Mark Mayo, Glenda Harrington, Anthony L. Baker. Data curation: Erin P. Price, Derek S. Sarovich, Jessica R. Webb, Carina M. Hall, Jason W. Sahl, Mirjam Kaestli, Mark Mayo, Glenda Harrington, Anthony L. Baker. Formal analysis: Erin P. Price, Derek S. Sarovich, Jessica R. Webb, Carina M. Hall, Jason W. Sahl, Lindsay C. Sidak-Loftis, Erik W. Settles, Joseph D. Busch. Funding acquisition: Erin P. Price, Derek S. Sarovich, Mirjam Kaestli, Mark Mayo, Apichai Tuanyok, Jeffrey Warner, Paul Keim, Bart J. Currie, David M. Wagner. 13 / 18 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 Population biology of Burkholderia ubonensis 8. Limmathurotsakul D, Golding N, Dance DA, Messina JP, Pigott DM, Moyes CL, et al. Predicted global distribution of Burkholderia pseudomallei and burden of melioidosis. Nat Microbiol. 2016; 1(1). https:// doi.org/10.1038/nmicrobiol.2015.8 PMID: 26877885 9. Ashdown LR. An improved screening technique for isolation of Pseudomonas pseudomallei from clini- cal specimens. Pathology. 1979; 11(2):293–297. PMID: 460953 10. Walsh AL, Wuthiekanun V, Smith MD, Suputtamongkol Y, White NJ. Selective broths for the isolation of Pseudomonas pseudomallei from clinical samples. Trans R Soc Trop Med Hyg. 1995; 89(1):124. PMID: 7538232 11. Ashdown LR, Clarke SG. Evaluation of culture techniques for isolation of Pseudomonas pseudomallei from soil. Appl Environ Microbiol. 1992; 58(12):4011–4015. PMID: 16348827 12. Stone JK, Mayo M, Grasso SA, Ginther JL, Warrington SD, Allender CJ, et al. Detection of Burkholderia pseudomallei O-antigen serotypes in near-neighbor species. BMC Microbiol. 2012; 12:250. https://doi. org/10.1186/1471-2180-12-250 PMID: 23126230 13. Yabuuchi E, Kawamura Y, Ezaki T, Ikedo M, Dejsirilert S, Fujiwara N, et al. Burkholderia uboniae sp. nov., L-arabinose-assimilating but different from Burkholderia thailandensis and Burkholderia vietna- miensis. Microbiol Immunol. 2000; 44(4):307–317. PMID: 10832977 14. Johnson SL, Bishop-Lilly KA, Ladner JT, Daligault HE, Davenport KW, Jaissle J, et al. Complete genome sequences for 59 Burkholderia isolates, both pathogenic and near neighbor. Genome Announc. 2015; 3(2):e00159–15. https://doi.org/10.1128/genomeA.00159-15 PMID: 25931592 15. Agnoli K, Frauenknecht C, Freitag R, Schwager S, Jenul C, Vergunst A, et al. The third replicon of mem- bers of the Burkholderia cepacia complex, plasmid pC3, plays a role in stress tolerance. Appl Environ Microbiol. 2014; 80(4):1340–1348. https://doi.org/10.1128/AEM.03330-13 PMID: 24334662 16. Agnoli K, Schwager S, Uehlinger S, Vergunst A, Viteri DF, Nguyen DT, et al. Exposing the third chromo- some of Burkholderia cepacia complex strains as a virulence plasmid. Mol Microbiol. 2012; 83(2):362– 378. https://doi.org/10.1111/j.1365-2958.2011.07937.x PMID: 22171913 17. Zhou J, Chen Y, Tabibi S, Alba L, Garber E, Saiman L. Antimicrobial susceptibility and synergy studies of Burkholderia cepacia complex isolated from patients with cystic fibrosis. Antimicrob Agents Che- mother. 2007; 51(3):1085–1088. https://doi.org/10.1128/AAC.00954-06 PMID: 17158942 18. Cheng AC, Fisher DA, Anstey NM, Stephens DP, Jacups SP, Currie BJ. Outcomes of patients with melioidosis treated with meropenem. Antimicrob Agents Chemother. 2004; 48(5):1763–5. https://doi. org/10.1128/AAC.48.5.1763-1765.2004 PMID: 15105132 19. Currie BJ. Melioidosis: evolving concepts in epidemiology, pathogenesis, and treatment. Semin Respir Crit Care Med. 2015; 36(1):111–125. https://doi.org/10.1055/s-0034-1398389 PMID: 25643275 20. Crowe A, McMahon N, Currie BJ, Baird RW. References 1. Vanlaere E, Lipuma JJ, Baldwin A, Henry D, De Brandt E, Mahenthiralingam E, et al. Burkholderia lat- ens sp. nov., Burkholderia diffusa sp. nov., Burkholderia arboris sp. nov., Burkholderia seminalis sp. nov. and Burkholderia metallica sp. nov., novel species within the Burkholderia cepacia complex. Int J Syst Evol Microbiol. 2008; 58(Pt 7):1580–1590. https://doi.org/10.1099/ijs.0.65634-0 PMID: 18599699 2. De Smet B, Mayo M, Peeters C, Zlosnik JE, Spilker T, Hird TJ, et al. Burkholderia stagnalis sp. nov. and Burkholderia territorii sp. nov., two novel Burkholderia cepacia complex species from environmental and human sources. Int J Syst Evol Microbiol. 2015; 65(7):2265–2271. https://doi.org/10.1099/ijs.0. 000251 PMID: 25872960 3. Peeters C, Depoorter E, Praet J, Vandamme P. Extensive cultivation of soil and water samples yields various pathogens in patients with cystic fibrosis but not Burkholderia multivorans. J Cyst Fibros. 2016; 15(6):769–775. https://doi.org/10.1016/j.jcf.2016.02.014 PMID: 26996269 4. Depoorter E, Bull MJ, Peeters C, Coenye T, Vandamme P, Mahenthiralingam E. Burkholderia: an update on taxonomy and biotechnological potential as antibiotic producers. Appl Microbiol Biotechnol. 2016; 100(12):5215–5229. https://doi.org/10.1007/s00253-016-7520-x PMID: 27115756 5. Marshall K, Shakya S, Greenhill AR, Padill G, Baker A, Warner JM. Antibiosis of Burkholderia ubonen- sis againist Burkholderia pseudomallei, the causative agent for melioidosis. Southeast Asian J Trop Med Public Health. 2010; 41(4):904–912. PMID: 21073065 6. Yang W, He Y, Xu L, Zhang H, Yan Y. A new extracellular thermo-solvent-stable lipase from Burkhol- deria ubonensis SL-4: Identification, characterization and application for biodiesel production. J Mol Catal B Enzym. 2016; 126:76–89. 7. Price EP, Sarovich DS, Webb JR, Ginther JL, Mayo M, Cook JM, et al. Accurate and rapid identification of the Burkholderia pseudomallei near-neighbour, Burkholderia ubonensis, using real-time PCR. PLoS One. 2013; 8(8):e71647. https://doi.org/10.1371/journal.pone.0071647 PMID: 23967229 14 / 18 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 Population biology of Burkholderia ubonensis 28. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinfor- matics. 2014; 30(15):2114–2120. https://doi.org/10.1093/bioinformatics/btu170 PMID: 24695404 29. Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008; 18(5):821–829. https://doi.org/10.1101/gr.074492.107 PMID: 18349386 30. Boetzer M, Pirovano W. Toward almost closed genomes with GapFiller. Genome Biol. 2012; 13(6):R56. https://doi.org/10.1186/gb-2012-13-6-r56 PMID: 22731987 31. Swain MT, Tsai IJ, Assefa SA, Newbold C, Berriman M, Otto TD. A post-assembly genome-improve- ment toolkit (PAGIT) to obtain annotated genomes from contigs. Nat Protoc. 2012; 7(7):1260–1284. https://doi.org/10.1038/nprot.2012.068 PMID: 22678431 32. Boetzer M, Henkel CV, Jansen HJ, Butler D, Pirovano W. Scaffolding pre-assembled contigs using SSPACE. Bioinformatics. 2011; 27(4):578–579. https://doi.org/10.1093/bioinformatics/btq683 PMID: 21149342 33. Tatusova T, DiCuccio M, Badretdin A, Chetvernin V, Nawrocki EP, Zaslavsky L, et al. NCBI prokaryotic genome annotation pipeline. Nucleic Acids Res. 2016; 44(14):6614–6624. https://doi.org/10.1093/nar/ gkw569 PMID: 27342282 34. Sarovich DS, Price EP. SPANDx: a genomics pipeline for comparative analysis of large haploid whole genome re-sequencing datasets. BMC Res Notes. 2014; 7:618. https://doi.org/10.1186/1756-0500-7- 618 PMID: 25201145 35. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformat- ics. 2010; 26(6):841–842. https://doi.org/10.1093/bioinformatics/btq033 PMID: 20110278 36. Price EP, MacHunter B, Spratt BG, Wagner DM, Currie BJ, Sarovich DS. Improved multilocus sequence typing of Burkholderia pseudomallei and closely related species. J Med Microbiol. 2016. 37. Jolley KA, Maiden MC. BIGSdb: Scalable analysis of bacterial genome variation at the population level. BMC Bioinformatics. 2010; 11:595. https://doi.org/10.1186/1471-2105-11-595 PMID: 21143983 38. Swofford DL. PAUP*. Phylogenetic Analysis Using Parsimony (*and Other Methods). Version 4. Sun- derland, Massachusetts: Sinauer Associates; 2002. 39. de Lamballerie X, Zandotti C, Vignoli C, Bollet C, de Micco P. A one-step microbial DNA extraction method using "Chelex 100" suitable for gene amplification. Res Microbiol. 1992; 143(8):785–790. PMID: 1298031 40. Hall CM, Busch JD, Shippy K, Allender CJ, Kaestli M, Mayo M, et al. Diverse Burkholderia species iso- lated from soils in the southern United States with no evidence of B. pseudomallei. PLoS One. 2015; 10 (11):e0143254. https://doi.org/10.1371/journal.pone.0143254 PMID: 26600238 41. DeShazer D. Virulence of clinical and environmental isolates of Burkholderia oklahomensis and Bur- kholderia thailandensis in hamsters and mice. FEMS Microbiol Lett. 2007; 277(1):64–69. https://doi.org/ 10.1111/j.1574-6968.2007.00946.x PMID: 17986086 42. Morici LA, Heang J, Tate T, Didier PJ, Roy CJ. Differential susceptibility of inbred mouse strains to Bur- kholderia thailandensis aerosol infection. Microbial Pathogenesis. Current antimicrobial susceptibility of first-episode melioi- dosis Burkholderia pseudomallei isolates from the Northern Territory, Australia. Int J Antimicrob Agents. 2014; 44(2):160–162. https://doi.org/10.1016/j.ijantimicag.2014.04.012 PMID: 24924662 21. Price EP, Laird Smith M, Paxinos EE, Tallon LJ, Sadzewicz L, Sengamalay N, et al. Whole-genome sequences of Burkholderia pseudomallei isolates exhibiting decreased meropenem susceptibility. Genome Announc. 2017; 5(14):e00053–17. https://doi.org/10.1128/genomeA.00053-17 PMID: 28385830 22. Baldwin A, Mahenthiralingam E, Thickett KM, Honeybourne D, Maiden MC, Govan JR, et al. Multilocus sequence typing scheme that provides both species and strain differentiation for the Burkholderia cepa- cia complex. J Clin Microbiol. 2005; 43(9):4665–4673. https://doi.org/10.1128/JCM.43.9.4665-4673. 2005 PMID: 16145124 23. Pearson T, Giffard P, Beckstrom-Sternberg S, Auerbach R, Hornstra H, Tuanyok A, et al. Phylogeo- graphic reconstruction of a bacterial species with high levels of lateral gene transfer. BMC Biol. 2009; 7:78. https://doi.org/10.1186/1741-7007-7-78 PMID: 19922616 24. Nandi T, Holden MT, Didelot X, Mehershahi K, Boddey JA, Beacham I, et al. Burkholderia pseudomallei sequencing identifies genomic clades with distinct recombination, accessory, and epigenetic profiles. Genome Res. 2015; 25(4):608. PMID: 25834186 25. Warner JM, Pelowa DB, Gal D, Rai G, Mayo M, Currie BJ, et al. The epidemiology of melioidosis in the Balimo region of Papua New Guinea. Epidemiol Infect. 2008; 136(7):965–71. https://doi.org/10.1017/ S0950268807009429 PMID: 17714600 26. Currie BJ, Gal D, Mayo M, Ward L, Godoy D, Spratt BG, et al. Using BOX-PCR to exclude a clonal out- break of melioidosis. BMC Infect Dis. 2007; 7:68. https://doi.org/10.1186/1471-2334-7-68 PMID: 17603903 27. Sahl JW, Vazquez AJ, Hall CM, Busch JD, Tuanyok A, Mayo M, et al. The effects of signal erosion and core genome reduction on the identification of diagnostic markers. MBio. 2016; 7(5). 15 / 18 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 Population biology of Burkholderia ubonensis 49. Peeters C, Cooper VS, Hatcher PJ, Verheyde B, Carlier A, Vandamme P. Comparative genomics of Burkholderia multivorans, a ubiquitous pathogen with a highly conserved genomic structure. PLoS One. 2017; 12(4):e0176191. https://doi.org/10.1371/journal.pone.0176191 PMID: 28430818 50. De Smet B, Sarovich DS, Price EP, Mayo M, Theobald V, Kham C, et al. Whole-genome sequencing confirms that Burkholderia pseudomallei multilocus sequence types common to both Cambodia and Australia are due to homoplasy. J Clin Microbiol. 2015; 53(1):323–326. https://doi.org/10.1128/JCM. 02574-14 PMID: 25392354 51. Aziz A, Sarovich DS, Harris T, Kaestli M, McRobb E, Mayo M, et al. Suspected cases of intracontinental Burkholderia pseudomallei sequence type homoplasy resolved using whole-genome sequencing. Microb Genom. 2017;Submitted for publication. 52. Peeters E, Nelis HJ, Coenye T. In vitro activity of ceftazidime, ciprofloxacin, meropenem, minocycline, tobramycin and trimethoprim/sulfamethoxazole against planktonic and sessile Burkholderia cepacia complex bacteria. J Antimicrob Chemother. 2009; 64(4):801–809. https://doi.org/10.1093/jac/dkp253 PMID: 19633000 53. Sarovich DS, Price EP, Von Schulze AT, Cook JM, Mayo M, Watson LM, et al. Characterization of cef- tazidime resistance mechanisms in clinical isolates of Burkholderia pseudomallei from Australia. PLoS One. 2012; 7(2):e30789. https://doi.org/10.1371/journal.pone.0030789 PMID: 22363490 54. Hayden HS, Lim R, Brittnacher MJ, Sims EH, Ramage ER, Fong C, et al. Evolution of Burkholderia pseudomallei in recurrent melioidosis. PLoS One. 2012; 7(5):e36507. https://doi.org/10.1371/journal. pone.0036507 PMID: 22615773 55. Dance DAB. Ecology of Burkholderia pseudomallei and the interactions between environmental Bur- kholderia spp. and human-animal hosts. Acta Trop. 2000; 74(2–3):159–168. PMID: 10674645 56. Vinion-Dubiel AD, Spilker T, Dean CR, Monteil H, LiPuma JJ, Goldberg JB. Correlation of wbiI geno- type, serotype, and isolate source within species of the Burkholderia cepacia complex. J Clin Microbiol. 2004; 42(9):4121–4126. https://doi.org/10.1128/JCM.42.9.4121-4126.2004 PMID: 15364998 57. Chantratita N, Wuthiekanun V, Limmathurotsakul D, Vesaratchavest M, Thanwisai A, Amornchai P, et al. Genetic diversity and microevolution of Burkholderia pseudomallei in the environment. PLoS Negl Trop Dis. 2008; 2(2):e182. https://doi.org/10.1371/journal.pntd.0000182 PMID: 18299706 58. Wuthiekanun V, Limmathurotsakul D, Chantratita N, Feil EJ, Day NP, Peacock SJ. Burkholderia pseu- domallei is genetically diverse in agricultural land in Northeast Thailand. PLoS Negl Trop Dis. 2009; 3 (8):e496. https://doi.org/10.1371/journal.pntd.0000496 PMID: 19652701 59. Coenye T, LiPuma JJ. Population structure analysis of Burkholderia cepacia genomovar III: varying degrees of genetic recombination characterize major clonal complexes. Microbiology. 2003; 149(Pt 1):77–88. https://doi.org/10.1099/mic.0.25850-0 PMID: 12576582 60. Bentley SD, Parkhill J. Comparative genomic structure of prokaryotes. Annu Rev Genet. 2004; 38:771– 792. https://doi.org/10.1146/annurev.genet.38.072902.094318 PMID: 15568993 61. 2010; 48(1):9–17. https://doi.org/10. 1016/j.micpath.2009.10.004 PMID: 19853031 43. Wiersinga WJ, de Vos AF, de Beer R, Wieland CW, Roelofs JJ, Woods DE, et al. Inflammation patterns induced by different Burkholderia species in mice. Cell Microbiol. 2008; 10(1):81–87. https://doi.org/10. 1111/j.1462-5822.2007.01016.x PMID: 17645551 44. West TE, Frevert CW, Liggitt HD, Skerrett SJ. Inhalation of Burkholderia thailandensis results in lethal necrotizing pneumonia in mice: a surrogate model for pneumonic melioidosis. Trans R Soc Trop Med Hyg. 2008; 102 Suppl 1:S119–S126. 45. Tuanyok A, Mayo M, Scholz H, Hall CM, Allender CJ, Kaestli M, et al. Burkholderia humptydooensis sp. nov., a new species related to Burkholderia thailandensis and the fifth member of the Burkholderia pseudomallei complex. Appl Environ Microbiol. 2017; 83(5):e02802–16. https://doi.org/10.1128/AEM. 02802-16 PMID: 27986727 46. Price EP, Sarovich DS, Smith EJ, MacHunter B, Harrington G, Theobald V, et al. Unprecedented melioi- dosis cases in northern Australia caused by an Asian Burkholderia pseudomallei strain identified by using large-scale comparative genomics. Appl Environ Microbiol. 2016; 82(3):954–963. https://doi.org/ 10.1128/AEM.03013-15 PMID: 26607593 47. Sarovich DS, Garin B, De Smet B, Kaestli M, Mayo M, Vandamme P, et al. Phylogenomic analysis reveals an Asian origin for African Burkholderia pseudomallei and further supports melioidosis endemic- ity in Africa. mSphere. 2016; 1(2):e00089–15. https://doi.org/10.1128/mSphere.00089-15 PMID: 27303718 48. Baker A, Pearson T, Price EP, Dale J, Keim P, Hornstra H, et al. Molecular phylogeny of Burkholderia pseudomallei from a remote region of Papua New Guinea. PLoS One. 2011; 6(3):e18343. https://doi. org/10.1371/journal.pone.0018343 PMID: 21483841 16 / 18 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 Harrison PW, Lower RP, Kim NK, Young JP. Introducing the bacterial ’chromid’: not a chromosome, not a plasmid. Trends Microbiol. 2010; 18(4):141–148. https://doi.org/10.1016/j.tim.2009.12.010 PMID: 20080407 62. Medema MH, Trefzer A, Kovalchuk A, van den Berg M, Muller U, Heijne W, et al. The sequence of a 1.8-Mb bacterial linear plasmid reveals a rich evolutionary reservoir of secondary metabolic pathways. Genome Biol Evol. 2010; 2:212–224. https://doi.org/10.1093/gbe/evq013 PMID: 20624727 63. Acosta-Cruz E, Wisniewski-Dye F, Rouy Z, Barbe V, Valdes M, Mavingui P. Insights into the 1.59-Mbp largest plasmid of Azospirillum brasilense CBG497. Arch Microbiol. 2012; 194(9):725–36. https://doi. org/10.1007/s00203-012-0805-2 PMID: 22481309 64. Carattoli A, Zankari E, Garcia-Fernandez A, Voldby Larsen M, Lund O, Villa L, et al. In silico detection and typing of plasmids using PlasmidFinder and plasmid multilocus sequence typing. Antimicrob Agents Chemother. 2014; 58(7):3895–3903. https://doi.org/10.1128/AAC.02412-14 PMID: 24777092 65. Smith MA, Bidochka MJ. Bacterial fitness and plasmid loss: the importance of culture conditions and plasmid size. Can J Microbiol. 1998; 44(4):351–355. PMID: 9674107 66. Levy A, Merritt AJ, Aravena-Roman M, Hodge MM, Inglis TJ. Expanded range of Burkholderia species in Australia. Am J Trop Med Hyg. 2008; 78(4):599–604. PMID: 18385355 67. Lertpatanasuwan N, Sermsri K, Petkaseam A, Trakulsomboon S, Thamlikitkul V, Suputtamongkol Y. Arabinose-positive Burkholderia pseudomallei infection in humans: case report. Clin Infect Dis. 1999; 28(4):927–928. 68. Dharakul T, Tassaneetrithep B, Trakulsomboon S, Songsivilai S. Phylogenetic analysis of Ara+ and Ara- Burkholderia pseudomallei isolates and development of a multiplex PCR procedure for rapid dis- crimination between the two biotypes. J Clin Microbiol. 1999; 37(6):1906–1912. PMID: 10325345 17 / 18 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0005928 September 14, 2017 Population biology of Burkholderia ubonensis 69. Glass MB, Gee JE, Steigerwalt AG, Cavuoti D, Barton T, Hardy RD, et al. Pneumonia and septicemia caused by Burkholderia thailandensis in the United States. J Clin Microbiol. 2006; 44(12):4601–4604. https://doi.org/10.1128/JCM.01585-06 PMID: 17050819 70. Barnes JL, Ketheesan N. Route of infection in melioidosis. Emerg Infect Dis. 2005; 11(4):638–639. https://doi.org/10.3201/eid1104.041051 PMID: 15834987 71. Welkos SL, Klimko CP, Kern SJ, Bearss JJ, Bozue JA, Bernhards RC, et al. Characterization of Bur- kholderia pseudomallei strains using a murine intraperitoneal infection model and in vitro macrophage assays. PLoS One. 2015; 10(4):e0124667. https://doi.org/10.1371/journal.pone.0124667 PMID: 25909629 72. Challacombe JF, Stubben CJ, Klimko CP, Welkos SL, Kern SJ, Bozue JA, et al. Interrogation of the Bur- kholderia pseudomallei genome to address differential virulence among isolates. PLoS One. 2014; 9 (12):e115951. https://doi.org/10.1371/journal.pone.0115951 PMID: 25536074 73. Sousa SA, Ulrich M, Bragonzi A, Burke M, Worlitzsch D, Leitao JH, et al. Virulence of Burkholderia cepacia complex strains in gp91phox-/- mice. Cell Microbiol. 2007; 9(12):2817–2825. https://doi.org/10. 1111/j.1462-5822.2007.00998.x PMID: 17627623 74. Chu KK, Davidson DJ, Halsey TK, Chung JW, Speert DP. Differential persistence among genomovars of the Burkholderia cepacia complex in a murine model of pulmonary infection. Infect Immun. 2002; 70 (5):2715–2720. https://doi.org/10.1128/IAI.70.5.2715-2720.2002 PMID: 11953418 75. Leitão JH, Sousa SA, Ferreira AS, Ramos CG, Silva IN, Moreira LM. Pathogenicity, virulence factors, and strategies to fight against Burkholderia cepacia complex pathogens and related species. Appl Microbiol Biotechnol. 2010; 87(1):31–40. https://doi.org/10.1007/s00253-010-2528-0 PMID: 20390415 18 / 18
https://openalex.org/W2016159480
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0110504&type=printable
English
null
Stabilization of Homoserine-O-Succinyltransferase (MetA) Decreases the Frequency of Persisters in Escherichia coli under Stressful Conditions
PloS one
2,014
cc-by
8,733
Introduction and concluded that persistence was far more complex than dormancy [14]. The bacterial stress response to unfavorable environmental factors (nutrient, oxidative, heat and envelope stresses) also promotes reduced antibiotic susceptibility [15]. For example, the survival of heat-stressed Acinetobacter baumannii and P. aeruginosa increased in the presence of aminoglycosides or b- lactams [16,17]. E. coli cells exposed to thermal stress accumu- lated a large number of aggregated proteins [18]. Leszczynska et al. showed that an increased level of protein aggregates in E. coli stationary-phase cells was strongly correlated with a higher frequency of persister formation [19]. In this context, we asked whether the inherently unstable MetA affects the formation of E. coli persisters under normal or stressful conditions. Homoserine o- succinyltransferase (MetA), the first enzyme in the methionine biosynthetic pathway [20], starts unfolding at 25uC in vitro and completely aggregates at temperatures of 44uC and higher, resulting in methionine limitation of E. coli growth [21]. MetA was found to be extremely sensitive to many stress conditions (e.g., thermal, oxidative or weak-organic-acid stress) [22,23]. A small subpopulation of bacterial cells, designated persisters, which are able to survive lethal antibiotic treatment and produce a new population of antibiotic-sensitive cells genetically identical to the originals was first described by Joseph W. Bigger [1]. Persistence as a phenomenon of multi-drug tolerance without genetic changes has been found in various bacterial species: Escherichia coli, Bacillus anthracis, Pseudomonas aeruginosa, Staphylococcus aureus, Gardnerella vaginalis, Salmonella enterica, Acinetobacter baumannii, Bordetella petrii and Mycobacterium tuberculosis [2,3,4,5,6,7,8]. Because of the potentially harmful role of these bacteria in acute and chronic infections, an understanding of the nature of persistence is important to increase the efficiency of antibiotic treatment. Persistence arises from the dormant state when the bacterial cells are metabolically inactive [3]; the level of translation is greatly reduced [9], resulting in arrested protein biosynthesis [10]. The frequency of persisters varies depending on the growth phase (from 0.0001–0.001% in exponential-phase to 1% in stationary-phase cultures), the age of the inoculum and the medium [11,12,13]; however, the ‘‘dormant’’ status of persisters was challenged by Orman and Brynildsen, who showed that dividing cells also gave rise to persisters, though to a lesser extent than non-dividing cells, In this study, we have shown that exogenous methionine reduced the frequency of persister cells in the strain E. coli K-12 WE at mild (37uC) or elevated (42uC) temperatures, as well as in the presence of sodium acetate. Elena A. Mordukhova, Jae-Gu Pan* uperbacteria Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Korea Abstract Bacterial persisters are a small subpopulation of cells that exhibit multi-drug tolerance without genetic changes. Generally, persistence is associated with a dormant state in which the microbial cells are metabolically inactive. The bacterial response to unfavorable environmental conditions (heat, oxidative, acidic stress) induces the accumulation of aggregated proteins and enhances formation of persister cells in Escherichia coli cultures. We have found that methionine supplementation reduced the frequency of persisters at mild (37uC) and elevated (42uC) temperatures, as well as in the presence of acetate. Homoserine-o-succinyltransferase (MetA), the first enzyme in the methionine biosynthetic pathway, is prone to aggregation under many stress conditions, resulting in a methionine limitation in E. coli growth. Overexpression of MetA induced the greatest number of persisters at 42uC, which is correlated to an increased level of aggregated MetA. Substitution of the native metA gene on the E. coli K-12 WE chromosome by a mutant gene encoding the stabilized MetA led to reduction in persisters at the elevated temperature and in the presence of acetate, as well as lower aggregation of the mutated MetA. Decreased persister formation at 42uC was confirmed also in E. coli K-12 W3110 and a fast-growing WErph+ mutant harboring the stabilized MetA. Thus, this is the first study to demonstrate manipulation of persister frequency under stressful conditions by stabilization of a single aggregation-prone protein, MetA. Editor: Valerie de Cre´cy-Lagard, University of Florida, United States of America Received May 15, 2014; Accepted September 15, 2014; Published October 17, 2014 Copyright:  2014 Mordukhova, Pan. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information files. Funding: This work was financially supported by the Superbacteria Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB) Innovation Grant. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * Email: jgpan@kribb.re.kr Competing Interests: The authors have declared that no competing interests exist. * Email: jgpan@kribb.re.kr Competing Interests: The authors have declared that no competing interests exist. * Email: jgpan@kribb.re.kr Stabilization of Homoserine-O-Succinyltransferase (MetA) Decreases the Frequency of Persisters in Escherichia coli under Stressful Conditions Elena A. Mordukhova, Jae-Gu Pan* October 2014 | Volume 9 | Issue 10 | e110504 Introduction Overexpression of MetA resulted October 2014 | Volume 9 | Issue 10 | e110504 1 PLOS ONE | www.plosone.org Stabilized MetA Reduces the Persister Frequency measured every 10 min in an exponentially growing culture for 1 h. in increased persister formation at 42uC and an enhanced level of aggregated MetA. Stabilized MetA mutant accelerated growth in the WE strain at the higher temperature (44uC) and in the presence of sodium acetate, decreased the frequency of persisters under heat and weak-acidic conditions and was less aggregation- prone. Strain W3110 and fast-growing mutants of strain WE expressing the wild-type and stabilized MetAs yielded similar results. Construction of the fast-growing strains WErph+ and WE- LYDrph+ The native rph-1 gene in the WE strain was replaced with the chloramphenicol-resistance gene using the l Red recombination system [26]. A disruption cassette was synthesized through PCR with forward primer RG1 (GGAAGTCCGTATAATGCGCAGC- CACATTTGTTTCAAGCCGGAGATTTCAATATGGTTGG- CAGCATCACCCGAC), reverse primer RG2 (GCGACTCAT- CAGTCGCCTTAAAAATCAGTTTGC- We showed the influence of a single aggregation-prone protein on persister formation in E. coli K-12 cells. Generally, our experiments confirmed that the stress response and dormancy appeared to be alternative strategies for cell survival [24]. CAGCGCCGCCTTCTGCGTCGCGTAGCACCAGGCGTT- TAAGG), Vent polymerase (NEB, Ipswich, USA) and the plasmid pACYC184 (NEB, Ipswich, USA) as a template (homologous sequences are shown in italics). The Drph::cat mutant of strain WE-LYD was obtained through transduction with P1vir using the WEDrph donor strain. For the rph-kan cassette construction, the kanamycin-resistance gene from the plasmid pKD13 [26] was cloned in the HindIII/AccI sites of pUC18 to generate the pUC18-Kan plasmid. The rph gene was amplified from E. coli ATCC 9637 genomic DNA using the primers RG3 (CGCCTCGGATCCGGAAGAAAAATGCCGCTCTG) and RG4 (GTTAAAGCAGTACGGCAGGTC) and cloned in the BamH1 site of pUC18-Kan resulted in the pUC18Rph-Kan plasmid which was used for the rph-kan cassette amplification with the primers RG5 (CGTTCATTGCCCACTCCATGTG) and RG6 (GAATCCACCAACGCTTCAGC). The 3.5-kb PCR Bacterial strains, media and culture conditions The strains and plasmids employed in this study are listed in Table 1. E. coli strains were grown in minimal M9 medium [25] supplemented with glucose (0.2%) or in rich LB medium (Difco, San Jose, USA). Antibiotics were used at the following concen- trations: ampicillin, 100 mg/ml, ofloxacin, 5 mg/ml, and kanamy- cin, 25 mg/ml. L-methionine was added to the medium to a final concentration of 50 mg/ml. Growth of E. coli strains in M9 glucose medium at different temperatures was studied in a TVS126MB automatic growth-measuring incubator (Advantec MFS Inc., Tokyo, Japan). The specific growth rate (m, h21) was calculated through linear regression analysis of ln(X/X0) data using Sigma Plot software, where the initial OD600 (X0) was 0.15 at the zero time point and X represents the OD600 values Table 1. Strains and plasmids used in this study. Strain or plasmid Relevant description Source or reference Escherichia coli DH5a F-,supE44 hsdR17 recA1 gyrA96 endA1 thi-1 relA1 deoR l- [25] W3110 F-, l2, IN(rrnD-rrnE)1, rph-1 KCTC ATCC 9637 (W) Wild -type ATCC JW3973 F-, D(araD-araB)567, DlacZ4787(::rrnB-3), l2, rph-1, DmetA780::kan, D(rhaD-rhaB)568, hsdR514 Keio collection National Institute of Genetics, Japan JW0195 F-, D(araD-araB)567, DlacZ4787(::rrnB-3), l2, rph-1, DmetN724::kan, D(rhaD-rhaB)568, hsdR514 Keio collection National Institute of Genetics, Japan WE JW3973 carrying the wild-type metA gene [27] WE-LYD WE carrying the metA gene with I124L, I229Y and N267D substitutions [29] W3110-LYD W3110 carrying the metA gene with I124L, I229Y and N267D substitutions This study WE- PBADMetA WE carrying the wild-type metA gene under PBAD promoter, kan This study WErph+ WE carrying the rph gene from the strain E. coli ATCC 9637 This study WE-LYDrph+ WE-LYD carrying the rph gene from the strain E. coli ATCC 9637 This study BL21(DE3) F- ompT hsdSB(r-Bm-B) gal dcm(DE3) Novagen (Billerica, USA) Plasmids pCP20 ts rep,[cI857] (l; ts), Apr, cat, [FLP] [26] pKD13 oriR6c, tL3LAM(Ter), Apr, rgnB(Ter), kan [26] pKD46 l Red (gam bet exo) ara C rep101(Ts), Apr [26] pUC18 Cloning vector, Apr Laboratory stock pET22b/MetA Expression vector contains the wild-type metA gene, Apr [24] pET22b/MetA-LYD Expression vector contains the metA gene with I124L,I229Y and N267D substitutions, Apr This study pBAD/HisA Expression vector, Apr Invitrogen (Grand Island, USA Apr, ampicillin resistance; kan, kanamycin resistance gene. doi:10.1371/journal.pone.0110504.t001 PLOS ONE | www.plosone.org 2 October 2014 | Volume 9 | Issue 10 | e110504 Table 1. Strains and plasmids used in this study. Table 1. Strains and plasmids used in this study. Bacterial strains, media and culture conditions PLOS ONE | www.plosone.org PLOS ONE | www.plosone.org Stabilized MetA Reduces the Persister Frequency Stabilized MetA Reduces the Persister Frequency TAATTCCTCCTGTTAGC). The metA gene was synthesized using a second pair of primers, bad3 (GCTAACAGGAGGAAT- TAACCATGCCGATTCGTGTGCCGGAC) and bad4 (CGCCTCAGATCTCGTATGGCGTGATCTGGTAGAC), with E. coli WE genomic DNA as a template. The PCR products from the two first reactions were then used as templates in a second PCR with the primers bad1 and bad4. The resulting PCR product was digested with BglII and cloned into HincII-BamHI sites of the plasmid pUC18-Kan. The kan-PBAD-metA cassette was synthesized through PCR with the template plasmid pUC18- Kan-PBAD-metA, Vent polymerase (NEB, Ipswich, USA) and a pair of primers, bad5 (GAATACTAATAAC- CATTTTCTCTCCTTTTAGTCATTCTTATATTCTAACG CTTGAGCGATTGTGTAGGCTG) and bad6 (CGTATGGCGTGATCTGGTAGACGTAATAGTTGAGC- CAG), then gel-purified and transferred into freshly prepared E. coli WE (pKD46) cells via electroporation, as described previously [26]. The kan-PBAD-metA cassette was synthesized from the genomic DNA of kanamycin-resistant clones and sequenced. product was transferred into WEDrph(pKD46) using the l Red recombination system [26]. Strain WE-LYDrph+ was generated by P1vir phage transduction with the WErph+ donor strain. The kanamycin-resistance gene was eliminated from strains WErph+ and WE-LYDrph+ upon exposure to plasmid pCP20-encoded FLP recombinase [26]. The rph gene from the genomic DNA of strains WErph+ and WE-LYDrph+ was synthesized using the primers RG7 (GTCATACTGCGGATCATAGACG) and RG8 (GTTAAAGCAGTACGGCAGGTC), followed by sequencing with the primers RG9 (GGAGAGGTGGAAGGATTATAGC) and RG10 (GAATCCACCAACGCTTCAGC). product was transferred into WEDrph(pKD46) using the l Red recombination system [26]. Strain WE-LYDrph+ was generated by P1vir phage transduction with the WErph+ donor strain. The kanamycin-resistance gene was eliminated from strains WErph+ and WE-LYDrph+ upon exposure to plasmid pCP20-encoded FLP recombinase [26]. The rph gene from the genomic DNA of strains WErph+ and WE-LYDrph+ was synthesized using the primers RG7 (GTCATACTGCGGATCATAGACG) and RG8 (GTTAAAGCAGTACGGCAGGTC), followed by sequencing with the primers RG9 (GGAGAGGTGGAAGGATTATAGC) and RG10 (GAATCCACCAACGCTTCAGC). Substitution of the native s32 and s7u promoters drove metA gene expression by the arabinose-inducible PBAD promoter on the E. coli WE-strain chromosome A two-step PCR procedure was used to construct the PBAD- metA cassette. The PBAD promoter was amplified from the template plasmid pBAD/HisA (Invitrogen, Grand Island, USA) using Vent polymerase (NEB, Ipswich, USA) with a first pair of primers, bad1 (CATACTCCCGCCATTCAGAGAAG) and bad2 (GTCCGGCACACGAATCGGCATGGT- Figure 1. Effect of L-methionine on the frequency of persisters at different temperatures. Bacterial strains, media and culture conditions The 16-h cultures of the strains WE (A, B) and JW0195 (C) grown in M9 glucose medium with or without L-methionine (50 mg/ml) at 37 or 42uC were diluted to an OD600 of 0.1 in fresh M9 glucose medium supplemented with ampicillin (A, C) or ofloxacin (B) and incubated at 37uC for 10 hours. Samples were analyzed as described in the Materials and Methods. doi:10.1371/journal.pone.0110504.g001 Figure 1. Effect of L-methionine on the frequency of persisters at different temperatures. The 16-h cultures of the strains WE (A, B) and JW0195 (C) grown in M9 glucose medium with or without L-methionine (50 mg/ml) at 37 or 42uC were diluted to an OD600 of 0.1 in fresh M9 glucose medium supplemented with ampicillin (A, C) or ofloxacin (B) and incubated at 37uC for 10 hours. Samples were analyzed as described in the Materials and Methods. doi:10 1371/journal pone 0110504 g001 Figure 1. Effect of L-methionine on the frequency of persisters at different temperatures. The 16-h cultures of the strains WE (A, B) and JW0195 (C) grown in M9 glucose medium with or without L-methionine (50 mg/ml) at 37 or 42uC were diluted to an OD600 of 0.1 in fresh M9 glucose medium supplemented with ampicillin (A, C) or ofloxacin (B) and incubated at 37uC for 10 hours. Samples were analyzed as described in the Materials and Methods. doi:10.1371/journal.pone.0110504.g001 October 2014 | Volume 9 | Issue 10 | e110504 PLOS ONE | www.plosone.org 3 3 Stabilized MetA Reduces the Persister Frequency Figure 2. Effect of the MetA overexpression on persister formation at different temperatures. Strain WE harboring the metA gene under pBAD promoter was grown in LB medium at 37 or 42uC with or without arabinose (10 mM) for 24 h, diluted to an OD600 of 0.1 in fresh LB medium supplemented with ampicillin and incubated at 37uC for 10 hours. Samples were analyzed as described in the Materials and Methods (A). Soluble and insoluble protein fractions were isolated from the late-stationary phase cultures (24 h) grown in LB medium, subjected to 12% SDS-PAGE followed by Western blotting using rabbit anti-MetA antibody (B). The MetA in the samples was quantified through densitometry using WCIF ImageJ software. The MetA amount from the cells grown at 37uC without arabinose was set to 1 (C). The error bars represent the standard deviations of duplicate independent cultures. doi:10.1371/journal.pone.0110504.g002 Figure 2. Purification of soluble and insoluble protein fractions Purification of soluble and insoluble protein fractions Cultures were grown in 50 ml of M9 glucose medium for 16 h or in LB medium for 24 h at 37uC or 42uC. Soluble and insoluble protein fractions were purified as previously described [21,28] in the presence of EDTA-free Halt protease-inhibitor cocktail (Pierce, Rockford, USA). Three micrograms of total protein from the soluble fraction and 10 ml of the insoluble fraction were subjected to 12% SDS-PAGE, followed by Western blotting using Purification of MetA and differential scanning calorimetry rabbit anti-MetA antibody [29]. The MetA in the samples was quantified through densitometry using WCIF ImageJ software. Purification of MetA and differential scanning calorimetry g y The MetAs were purified as described previously [27] in the presence of an EDTA-free Halt protease-inhibitor cocktail (Pierce, Rockford, USA). The thermal stabilities of the MetAs were measured calorimetrically over a temperature interval of 15–90uC at a scan rate of 90uC/h with a VP-DSC calorimeter (MicroCal, LLC, Northampton, USA) using 50 mM of protein in a 50 mM K- phosphate buffer (pH 7.5). Three scans were obtained using independent protein preparations. Persister detection assay Bacteria grown overnight in M9 glucose medium for 16 h or in LB medium for 24 h were diluted to an OD600 of 0.1 in fresh medium (M9 glucose or LB) supplemented with ampicillin (200 mg/ml) or ofloxacin (5 mg/ml) and incubated at 37uC for 10 hours. Samples were taken every hour and plated on LB agar for colony counting. The values represent the means of three independent experiments. The frequency of persister formation was determined as the relationship between the CFU of surviving bacteria and the total CFU before the addition of antibiotics. The error bars indicate the standard errors. Bacterial strains, media and culture conditions Effect of the MetA overexpression on persister formation at different temperatures. Strain WE harboring the metA gene under pBAD promoter was grown in LB medium at 37 or 42uC with or without arabinose (10 mM) for 24 h, diluted to an OD600 of 0.1 in fresh LB medium supplemented with ampicillin and incubated at 37uC for 10 hours. Samples were analyzed as described in the Materials and Methods (A). Soluble and insoluble protein fractions were isolated from the late-stationary phase cultures (24 h) grown in LB medium, subjected to 12% SDS-PAGE followed by Western blotting using rabbit anti-MetA antibody (B). The MetA in the samples was quantified through densitometry using WCIF ImageJ software. The MetA amount from the cells grown at 37uC without arabinose was set to 1 (C). The error bars represent the standard deviations of duplicate independent cultures. d i 10 1371/j l 0110504 002 doi:10.1371/journal.pone.0110504.g002 Exogenous methionine decreased frequency of persisters in the E. coli cells at mild and elevated temperatures Previous findings have revealed that E. coli growth in the defined medium was impaired at elevated temperatures due to methionine limitation resulting from the extreme inherent instability of the first enzyme in the methionine biosynthetic pathway, MetA [20,30]. Because the MetA was completely aggregated at 44uC [21], we studied the effect of temperature and methionine supplementation on persister formation in E. coli K-12 WE cells. Strain WE of E. coli K-12 grown in M9 glucose medium at 37 and 42uC for 16 h was treated with ampicillin, and the frequency of persisters was determined by plating samples on LA plates (Figure 1A). To distinguish persisters from resistant mutants, the colonies were replica plated on LA plates supple- mented with ampicillin. No colonies grew in the presence of ampicillin. To confirm the effect of exogenous L-methionine on persister- cell formation, we obtained the time-kill curves of the mutant JW0195 (DmetN) lacking the L-methionine ABC transporter MetN [37]. As seen in Figure 1C, provision of exogenous methionine to the JW0195(DmetN) mutant did not affect the number of persister cells tolerant to ampicillin at 37uC. At 42uC, however, the number of persisters was 6–15 times lower in the presence of L-methionine than in methionine-free medium (p, 0.05) (Figure 1C). We assume that at elevated temperature, E. coli cells defective in MetN biosynthesis may activate another L- methionine transport system, the genetically uncharacterized MetP system, [37,38] to compensate for methionine deficiency, resulting in a lower persister level. As seen in Figure 1A, the time-kill curves of the cells grown at 37uC and at 42uC were typically biphasic, representing exponen- tial death of the non-persistent cells, followed by a slower death rate for the persisters [31]. Because an increased frequency of persisters is linked to a slow-growing state [32], we compared the specific growth rates of the WE strain at mild vs. higher temperatures and did not detect slower growth at 42uC (Table S1). We hypothesized that more than 150-fold increase in the frequency of persisters at 42uC (p,0.05) resulted from an increased level of aggregated proteins. As homoserine O-succinyl- transferase (MetA), which catalyzes the first unique step in the de novo methionine biosynthetic pathway, is inherently unstable and prone to aggregation [21–23], we determined the number of persisters in cultures in the presence of methionine (Figure 1A) when the genes involved in methionine biosynthesis were repressed [33]. Exogenous methionine decreased frequency of persisters in the E. coli cells at mild and elevated temperatures Methionine supplementation reduced the frequen- cy of persisters tolerant to ampicillin by 6–9 times at 37uC and by 9–15 times at 42uC (p,0.05) compared to methionine-free Thus, these results showed that the formation of persisters was dependent on the availability of methionine and might be linked to the solubility of MetA. Statistical analyses The significance of differences between mean values of two measured parameters was assessed using two-tailed t test with October 2014 | Volume 9 | Issue 10 | e110504 PLOS ONE | www.plosone.org 4 Stabilized MetA Reduces the Persister Frequency Figure 3. Influence of stabilized MetA protein on the E.coli WE strain growth under stressful conditions. The WE and WE-LYD strains were incubated in M9 glucose medium at 44uC for 10 h (A) or in M9 glucose medium (pH 6.0) supplemented with 20 mM sodium acetate at 37uC for 28 h (B) in an automatic growth-measuring incubator. The average of two independent experiments is presented. doi:10.1371/journal.pone.0110504.g003 Figure 3. Influence of stabilized MetA protein on the E.coli WE strain growth under stressful conditions. The WE and WE-LYD strains were incubated in M9 glucose medium at 44uC for 10 h (A) or in M9 glucose medium (pH 6.0) supplemented with 20 mM sodium acetate at 37uC for 28 h (B) in an automatic growth-measuring incubator. The average of two independent experiments is presented. doi:10.1371/journal.pone.0110504.g003 unequal variances. Differences were considered significant when the P value was ,0.05. medium (Figure 1A). Because bacterial killing and persister formation with ampicillin as a beta-lactam antibiotic depend on the growth rate [32,34], which would be affected by exogenous methionine [27], we examined the frequency of persisters tolerant to another antibiotic, ofloxacin, in cultures grown with or without methionine supplementation at 37uC and 42uC (Figure1B). Ofloxacin is a fluoroquinolone antibiotic that binds DNA gyrase and topoisomerase IV, leading to inhibition of bacterial cell division and cell growth [35]. Ofloxacin effectively kills bacteria regardless of the growth phase [36]. At elevated temperature (42uC), strain WE produced 16-fold more cells tolerant to ofloxacin than at 37uC (p,0.05) (Figure 1B). Methionine supple- mentation decreased the number of ofloxacin persisters 5–6 times at 37uC and 8 times at 42uC (p,0.05) (Figure 1B). Thus, exogenous methionine reduced the number of persisters at both higher and lower temperatures, regardless of the type of antibiotic used. The frequency of persister formation is correlated to the aggregation of the MetA One possible explanation is that the expression of methionine-biosynthetic genes was repressed by methionine [33], whose concentration in LB medium was estimated at approxi- mately 6 mM [39], approximately 17 times higher than the amount used to supplement the M9 glucose medium. Secondly, deletion of the metA gene, like deletion of rmf, relE, or mazF, did not affect persister production [40]. Therefore, we examined the frequency of persistence when MetA was over-expressed. gene [27], in LB medium at 37 and 42uC. The strains produced similar numbers of persister cells at each temperature (data not shown). One possible explanation is that the expression of methionine-biosynthetic genes was repressed by methionine [33], whose concentration in LB medium was estimated at approxi- mately 6 mM [39], approximately 17 times higher than the amount used to supplement the M9 glucose medium. Secondly, deletion of the metA gene, like deletion of rmf, relE, or mazF, did not affect persister production [40]. Therefore, we examined the frequency of persistence when MetA was over-expressed. s7u [43], were deleted from the chromosome. The frequency of persisters and MetA aggregation were studied in 24-h WE- pBADMetA culture grown in LB medium at 37 and 42uC with or without L-arabinose. At 37uC, we did not detect any difference in the numbers of persisters produced by induced and non-induced cultures (Figure 2A). At an elevated temperature (42uC), the WE- pBADMetA strain demonstrated 3-6-fold-higher persister frequen- cy when the culture was non-induced (p,0.05), but arabinose induction increased the number of persisters approximately 10–25 times in comparison to culture at 37uC induced (p,0.05) (Figure 2A). Strain JW3973, which lacked the metA gene, was examined in terms of persister formation under the conditions described above. The frequency of persisters detected in the JW3973 strain was similar to that obtained in the non-induced culture of the WE-pBADMetA strain (data not shown). Previous investigations have shown that metA gene expression increased up to 50 times during heat shock within 5 min of induction and increased 3–4 times in the presence of acetate [41,42]. Expression of metE and metC remained unchanged during heat shock [41]. Evidence later showed that MetA had a strong tendency to unfold and aggregate at elevated temperatures [21,22]. To test whether MetA over-expression and aggregation affect persister formation, the metA gene on the WE strain chromosome was placed under tight control of the arabinose- regulated pBAD promoter. The frequency of persister formation is correlated to the aggregation of the MetA To determine whether the MetA participates in persistence, we compared the level of persistence to ampicillin in a pair of isogenic strains, JW9673(DmetA) and WE harboring the wild-type metA October 2014 | Volume 9 | Issue 10 | e110504 PLOS ONE | www.plosone.org 5 Stabilized MetA Reduces the Persister Frequency Figure 4. Dependence of persister formation on stabilized MetA protein. Overnight cultures of the strains WE and WE-LYD grown for 16 h in M9 glucose medium at 37 or 42uC were diluted to an OD600 of 0.1 in fresh M9 glucose medium supplemented with ampicillin (A) or ofloxacin (B) and incubated at 37uC for 10 hours. Samples were analyzed as described in the Materials and Methods. Soluble and insoluble protein fractions were purified from the cultures grown in M9 glucose medium at 37 or 42uC to an OD600 = 1.0, subjected to 12% SDS-PAGE followed by Western blotting using rabbit anti-MetA antibody (C). The MetA in the samples was quantified through densitometry using WCIF ImageJ software. The MetA amount from the WE cells grown at 37uC was set to 1 (D). The data are presented as the average of two independent experiments. doi:10.1371/journal.pone.0110504.g004 Figure 4. Dependence of persister formation on stabilized MetA protein. Overnight cultures of the strains WE and WE-LYD grown for 16 h in M9 glucose medium at 37 or 42uC were diluted to an OD600 of 0.1 in fresh M9 glucose medium supplemented with ampicillin (A) or ofloxacin (B) and incubated at 37uC for 10 hours. Samples were analyzed as described in the Materials and Methods. Soluble and insoluble protein fractions were purified from the cultures grown in M9 glucose medium at 37 or 42uC to an OD600 = 1.0, subjected to 12% SDS-PAGE followed by Western blotting using rabbit anti-MetA antibody (C). The MetA in the samples was quantified through densitometry using WCIF ImageJ software. The MetA amount from the WE cells grown at 37uC was set to 1 (D). The data are presented as the average of two independent experiments. doi:10.1371/journal.pone.0110504.g004 gene [27], in LB medium at 37 and 42uC. The strains produced similar numbers of persister cells at each temperature (data not shown). October 2014 | Volume 9 | Issue 10 | e110504 The frequency of persister formation is correlated to the aggregation of the MetA The native metA promoters, s32 and Leszczynska et al. found that the number of persisters corre- sponded to the level of protein aggregation [19]. We detected increased aggregation in the cultures grown at 42uC compared to cells grown at 37uC (Figure 2B). This result may partially explain the higher persister frequency at the elevated temperature. We October 2014 | Volume 9 | Issue 10 | e110504 October 2014 | Volume 9 | Issue 10 | e110504 PLOS ONE | www.plosone.org 6 Stabilized MetA Reduces the Persister Frequency Figure 5. Stabilized MetA decreases the frequencies of persisters in different E. coli strains at elevated temperature. Cells of the strains W3110 and W3110-LYD (A), WErph+ and WErph+-LYD (B), grown overnight for 16 h in M9 glucose medium at 37 or 42uC, were diluted to an OD600 of 0.1 in fresh M9 glucose medium supplemented with ampicillin and incubated at 37uC for 10 hours. Samples were analyzed as described in the Materials and Methods. doi:10.1371/journal.pone.0110504.g005 Figure 5. Stabilized MetA decreases the frequencies of persisters in different E. coli strains at elevated temperature. Cells of the strains W3110 and W3110-LYD (A), WErph+ and WErph+-LYD (B), grown overnight for 16 h in M9 glucose medium at 37 or 42uC, were diluted to an OD600 of 0.1 in fresh M9 glucose medium supplemented with ampicillin and incubated at 37uC for 10 hours. Samples were analyzed as described in the Materials and Methods. doi:10.1371/journal.pone.0110504.g005 MetA (p,0.05) (Figure 4A). A similar tendency was observed in the formation of persisters tolerant to ofloxacin; however, the difference in the number of persisters between the two strains decreased up to 5–8 times at 42uC (p,0.05) (Figure 4B). also examined the levels of soluble and insoluble MetA at 37 and 42uC in the non-induced and induced cultures (Figure 2B and 2C). At 37uC, the amount of soluble MetA was 4-fold higher in the arabinose-induced culture compared to the non-induced culture, whereas the relative amount of insoluble MetA was almost the same (Figure 2B and 2C). At 42uC, the soluble MetA content was 1.2 times that of both cultures at 37uC, but the aggregated MetA amount was 3.8 times higher in the presence of arabinose and 2 times lower without arabinose (Figure 2B and 2C). An insoluble protein that showed an intensive band around 15kDa in the SDS- PAGE gel (Figure 2B) was recognized with antibodies specific to MetA (data not shown). The frequency of persister formation is correlated to the aggregation of the MetA This protein is perhaps a product of MetA degradation that is carried out by ATP-dependent proteases [22]. Thus, these results showed the direct impact of MetA aggregation on persister-cell formation. also examined the levels of soluble and insoluble MetA at 37 and 42uC in the non-induced and induced cultures (Figure 2B and 2C). At 37uC, the amount of soluble MetA was 4-fold higher in the arabinose-induced culture compared to the non-induced culture, whereas the relative amount of insoluble MetA was almost the same (Figure 2B and 2C). At 42uC, the soluble MetA content was 1.2 times that of both cultures at 37uC, but the aggregated MetA amount was 3.8 times higher in the presence of arabinose and 2 times lower without arabinose (Figure 2B and 2C). An insoluble protein that showed an intensive band around 15kDa in the SDS- PAGE gel (Figure 2B) was recognized with antibodies specific to MetA (data not shown). This protein is perhaps a product of MetA degradation that is carried out by ATP-dependent proteases [22]. Thus, these results showed the direct impact of MetA aggregation on persister-cell formation. We have detected 12.5-fold more aggregated wild-type MetA at 42uC compared to 37uC, but the level of stabilized MetA increased only 9.5 times (Figure 4C and 4D). The relative amount of soluble MetA was 1.5 times higher at 42uC (Figure 4C and 4D), consistent with previous findings that showed activation of metA transcription at elevated temperatures [41]. Strains WE and WE-LYD did not exhibit any difference in their specific growth rates at 37 and 42uC (Table S1), linking the finding that the highest level of persisters was formed by the WE strain at 42uC to an increase in the aggregate level of wild-type MetA. A stabilized MetA mutant decreases the frequency of persisters at elevated temperatures To test whether the MetA stabilization influences the frequency of persisters in other E. coli strains, we substituted the native metA gene on the W3110 chromosome with the metA-LYD mutant and constructed fast-growing mutants of the WE and WE-LYD strains. Previous studies have shown that the genomes of E. coli K-12 strains MG1655 and W3110 harbor a GC deletion within the 39- terminal part of the rph gene that causes partial auxotrophy for pyrimidines, resulting in a growth defect for K-12 strains [44]. As the rph gene from E. coli strain ATCC 9637 (W) does not contain this mutation, we substituted the defective rph gene in the K-12 WE and WE-LYD strains with the rph gene from the ATCC 9637 strain. The resulting WErph+ and WE-LYDrph+ mutant strains grew 13–15% faster at 37u and at 42uC than the parental strains (Table S1). As MetA aggregation increased persister production, we studied the effect of MetA stabilization on the persister frequency at mild (37uC) and elevated temperatures (42uC). Strain WE-LYD, which harbors three stabilizing mutations in MetA (I124L, I229Y and N267D), had been constructed previously [29] and showed accelerated growth at an elevated temperature (44uC) or in the presence of sodium acetate (Figure 3, Table S1). We measured the melting temperatures (Tm) of the wild-type and mutant proteins using differential scanning calorimetry (DSC). Both of these proteins contain a C-terminal six-histidine tag and were purified as described in the Materials and Methods. Mutated MetA-LYD had a higher Tm than wild-type MetA (52.6560.06uC and 47.0760.01uC, respectively), evidence of the increased thermal stability of the MetA-LYD mutant. Persister formation by two other pairs of isogenic strains, W3110/W3110-LYD, and WErph+/WE-LYDrph+ grown in M9 glucose medium at 37uC and 42uC followed the same tendency demonstrated earlier: no difference was detected at 37uC and more persisters were produced by the strain harboring wild-type MetA at 42uC (Figure 5A and 5B). Thus, these results confirmed our hypothesis that stabilization of highly unstable MetA reduces A pair of isogenic strains, WE and WE-LYD, was used for the study of persister formation at 37uC and 42uC in M9 glucose medium. Both strains displayed similar numbers of persisters at 37uC (Figure 4A). A stabilized MetA mutant decreases the frequency of persisters at elevated temperatures coli strains at an elevated temperature. in the presence of acetate formed almost 2–4 times fewer persisters than the WE strain (p,0.05) (Figure 6A). Supplementation of the acetate-enriched medium with exogenous methionine reduced the frequency of persisters to a similar level in both tested strains compared to the methionine-free medium (Figure 6B). Increased numbers of persisters in acetate-enriched medium were accompa- nied by a higher aggregate level (Figure 6C). The amount of aggregated wild-type MetA increased 5-fold with acetate supple- mentation, and the amount of the MetA-LYD mutant increased 4- fold (Figure 6C and 6D). Thus, methionine enhances the susceptibility of E. coli to antibiotics, and an increase in stability of one protein (MetA) affects persister formation under weak- acidic conditions. Stabilized MetA reduces persister formation in the presence of acetate A previous study reported that acetate induced protein aggregation and increased the frequency of persisters in E. coli MC4100 culture [19]. Acetate treatment was found to alter significantly the expression of 86 genes including the metA gene whose expression was increased 3–4 times [42]. Supplementation of the medium with methionine partially relived the growth inhibition of E.coli caused by acetate [45,46]. Because the stabilized-MetA mutant facilitated growth of the WE-LYD strain in the presence of acetate (Figure 3B), we tested persister formation by WE and WE-LYD cultures grown overnight in the M9 glucose medium (pH 6.0) supplemented with sodium acetate (20 mM) at 37uC. As seen in Figure 6A, acetate enhanced the frequency of persisters in both WE and WE-LYD cultures compared to acetate-free medium; however, the WE-LYD strain A stabilized MetA mutant decreases the frequency of persisters at elevated temperatures At 42uC, the frequency of increased in both strains (Figure 4A); however, the WE-LYD mutant strain formed 15–22 times fewer persisters than the WE harboring the wild-type October 2014 | Volume 9 | Issue 10 | e110504 PLOS ONE | www.plosone.org 7 Stabilized MetA Reduces the Persister Frequency Figure 6. Effect of the stabilized MetA on the persister cell frequency under acidic conditions. Cultures of WE and WE-LYD grown for 16 h in M9 glucose medium (pH 6.0) at 37uC with or without sodium acetate (20 mM; A); with or without L-methionine (50 mg/ml) and in the presence of sodium acetate (20 mM; B) were diluted in fresh M9 glucose medium to an OD600 of 0.1, supplemented with ampicillin and incubated at 37uC for 10 hours. Samples were analyzed as described in the Materials and Methods. Soluble and insoluble protein fractions were purified from the 16 h-cultures grown in M9 glucose medium (pH 6.0) with or without sodium acetate (20 mM), and subjected to 12% SDS-PAGE, followed by Western blotting using rabbit anti-MetA antibody (C). The MetA in the samples was quantified through densitometry using WCIF ImageJ software. The amount of MetA in the WE cells grown without sodium acetate was set to 1 (D). The data are presented as the average of two independent experiments. doi:10.1371/journal.pone.0110504.g006 Figure 6. Effect of the stabilized MetA on the persister cell frequency under acidic conditions. Cultures of WE and WE-LYD grown for 16 h in M9 glucose medium (pH 6.0) at 37uC with or without sodium acetate (20 mM; A); with or without L-methionine (50 mg/ml) and in the presence of sodium acetate (20 mM; B) were diluted in fresh M9 glucose medium to an OD600 of 0.1, supplemented with ampicillin and incubated at 37uC for 10 hours. Samples were analyzed as described in the Materials and Methods. Soluble and insoluble protein fractions were purified from the 16 h-cultures grown in M9 glucose medium (pH 6.0) with or without sodium acetate (20 mM), and subjected to 12% SDS-PAGE, followed by Western blotting using rabbit anti-MetA antibody (C). The MetA in the samples was quantified through densitometry using WCIF ImageJ software. The amount of MetA in the WE cells grown without sodium acetate was set to 1 (D). The data are presented as the average of two independent experiments. d i /j l doi:10.1371/journal.pone.0110504.g006 the frequency of persisters in E. Stabilized MetA Reduces the Persister Frequency growing cells were highly persistent under antibiotic treatment, a phenomenon associated with decreased biosynthetic activity [9,10]. Bacteria also recruit resistance determinants and induce antimicrobial-resistance mechanisms in response to diverse envi- ronmental stresses [15]. The genes involved in the heat and cold stress responses (cspH, htrA, ibpAB, htpX, and clpB) were upregulated in the cell samples with the higher frequencies of persisters [40]. These genes are overexpressed under stress conditions, but their role in antibiotic tolerance still has not been clearly explained [40]. Lon protease (annotated as the ATP- dependent heat shock protein) enhances the number of persisters when overexpressed [47]. In turn, cells lacking Lon protease, as well as the chaperones DnaK and DnaJ, reduced the formation of persistent cells [47,48]. Overproduction of DnaJ stimulated the persistence of E. coli cells [49]. Increased expression of the heat- shock proteins DnaK, DnaJ and Lon was found at elevated temperatures and under other stressful conditions [50,51,52]. The DnaK system, consisting of the chaperones DnaK, DnaJ and GrpE together with ClpB, maintains proper protein folding, and the proteases Lon, Clp and HtrA degrade the protein aggregates that form at higher temperatures [18,53]. Therefore, enhanced protein misfolding and aggregation resulted in overexpression of the heat-shock proteins, which may be linked to a higher persister frequency. protein fractions under stressful conditions was also significantly higher compared to the amounts produced by normally growing cells (Figures 2B, 2C, 4C, 4D, 6C and 6D). We found that the stabilized-MetA mutant had notably reduced persister frequency at the elevated temperature independent of strain (Figures 4A, 4B, 5A and 5B), as also seen in the presence of acetate (Figure 6A). The level of mutated MetA in the insoluble protein fractions from heat- and acid-treated cells was lower than the level of wild-type protein (Figures 4C, 4D, 6C and 6D). We suggest two causes of the decreased frequency of persisters generated by the strain with stabilized MetA. First, the stabilized-MetA mutant requires less assistance from chaperones to refold the misfolded protein and less Lon protease to degrade the aggregates, resulting in lower expression of these enzymes and thus in a reduced number of persisters under stress. Second, refolding and/or proteolysis of the denatured/aggregated MetA might be facilitated by inorganic polyphosphate (PolyP), a product of the polyphosphate kinase [23]. Supporting Information Table S1 Effect of stabilized MetA protein on E.coli growth at different temperatures or in the presence of sodium acetate. Strains were grown in M9 glucose medium (pH 7.0 or 6.0) with or without sodium acetate (20 mM) in an automatic growth-measuring incubator at indicated temperatures for 24 h. The specific growth rate m (h21) was calculated through linear regression analysis of ln(X/X0) data with Sigma Plot software, where the initial OD600 (X0) was 0.1–0.15 at the zero time point, and X represents the OD600 values measured every 10 min in an exponentially growing culture over 1 h. (DOC) Methionine added to the culture medium to repress transcrip- tion of the methionine-biosynthetic genes [33] reduced the number of persisters at mild and elevated temperatures (Figure 1A and B). This result might be explained by the absence of two aggregation-prone proteins, MetA and MetE, from the methio- nine-biosynthesis pathway [18]. Methionine also stimulates E. coli growth in defined medium [27], decreasing persistence [55]. The higher cultivation temperature in the absence of methionine significantly increased the frequency of persisters, independent of the medium (Figures 1A and 2A). A similar effect was observed when the cells were grown in the acetate–enriched defined medium at the mild temperature (37uC; Figure 6A). In each case, increased persistence was associated with a higher level of protein aggregation (Figures 2B, 4C and 6C), which is consistent with a previous report by Leszczynska et al. [19], who have shown a correlation between the level of protein aggregates and the frequency of persisters. The amount of MetA in the insoluble Stabilized MetA Reduces the Persister Frequency Lower levels of mutated MetA aggregates compared to the wild-type protein might cause a decrease in PolyP production, followed by reduced persister formation [56]. Increased persister formation with inherently unstable MetA raises an intriguing question: ‘Does inherently instable MetA favor E. coli survival under antibiotic challenge?’ If unstable MetA offers a selective advantage, more stable MetA may not evolve. q y MetA is a heat-shock protein [41] that is highly unstable at elevated temperatures [21–23]. The MetA started to unfold in vitro at temperatures of approximately 25uC, with the maximum level of unfolding at 44uC, resulting in complete aggregation with any subsequent rise in temperature [21]. Indirect evidence suggests that MetA requires folding assistance from the DnaK chaperone system at mild and elevated temperatures [29,54]. Aggregated MetA is also a substrate for the ATP- dependent cytosolic proteases Lon, ClpPX/PA and HslVU [22]. Thus, an accumulation of misfolded and/or aggregated MetA associated with increased expression of the chaperones and proteases may increase the level of persisters. In summary, we found that the first enzyme in the methionine biosynthetic pathway, MetA, affects the level of persisters in E. coli under stressful conditions. A higher frequency of persisters was correlated with an increased amount of aggregated MetA. Stabilization of the unstable MetA enzyme resulted in decreased aggregation and thus in reduced persister formation at elevated temperature and in the presence of acetate. Thus, we have shown a possibility to correct persister formation by manipulating the thermostability of the single enzyme, MetA. Author Contributions Conceived and designed the experiments: EAM JGP. Performed the experiments: EAM JGP. Analyzed the data: EAM JGP. Contributed reagents/materials/analysis tools: EAM JGP. Contributed to the writing of the manuscript: EAM JGP. 5. Barat S, Steeb B, Maze A, Bumann D (2013) Extensive in vivo resilience of persistent Salmonella. PLoS One 7(7): e42177. 1. Bigger JW (1944) Treatment of staphylococcal infections with penicillin by intermittent sterilisation. The Lancet 244: 497–500. 6. Barth VC Jr, Rodrigues BA, Bonatto GD, Gallo SW, Pagnussatti VE, et al. (2013) Heterogeneous persister cells formation in Acinetobacter baumannii. PLoS One 8(12): e84361. 4. Jenkins SA, Xu Y (2013) Characterization of Bacillus anthracis persistence in vivo. PLoS One 8(6): e66177. 3. Wood TK, Knabel SJ, Kwan BW (2013) Bacterial persister cell formation and dormancy. Appl Environ Microbiol 79: 7116–7121. 8. Rao SPS, Alonso S, Rand L, Dick T, Pethe K (2008) The protonmotive force is required for maintaining ATP homeostasis and viability of hypoxic, nonreplicat- ing Mycobacterium tuberculosis. Proc Natl Acad Sci USA 105: 11945–11950. 2. Lewis K (2010) Persister cells. Annu Rev Microbiol 64: 357–372. 7. Zelazny AM, Ding L, Goldberg, Mijares LA, Conlan S, et al. (2013) Adaptability and persistence of the emerging pathogen Bordetella petrii. PLoS One 8(6): e65102. y 9. Shah D, Zhang Z, Khodursky AB, Kaldalu N, Kurg K, et al. (2006) Persisters: a distinct physiological state of E. coli. BMC Microbiol 6: 53. Discussion Interest in microbial persistence is rising; however, the mechanisms underlying persister formation are not fully under- stood. Populations containing higher numbers of dormant or slow- October 2014 | Volume 9 | Issue 10 | e110504 October 2014 | Volume 9 | Issue 10 | e110504 PLOS ONE | www.plosone.org 8 Stabilized MetA Reduces the Persister Frequency 1. Bigger JW (1944) Treatment of staphylococcal infections with penicillin by intermittent sterilisation. The Lancet 244: 497–500. 2. Lewis K (2010) Persister cells. Annu Rev Microbiol 64: 357–372. 3. Wood TK, Knabel SJ, Kwan BW (2013) Bacterial persister cell formation and dormancy. Appl Environ Microbiol 79: 7116–7121. 4. Jenkins SA, Xu Y (2013) Characterization of Bacillus anthracis persistence in vivo. PLoS One 8(6): e66177. 5. Barat S, Steeb B, Maze A, Bumann D (2013) Extensive in vivo resilience of persistent Salmonella. PLoS One 7(7): e42177. Stabilized MetA Reduces the Persister Frequency Biran D, Brot N, Weissbach H, Ron EZ (1995) Heat shock-dependent transcriptional activation of the metA gene of Escherichia coli. J Bacteriol 177: 1374–1379. 18. Mogk A, Tomoyasu T, Goloubinoff P, Rudiger S, Roder D, et al. (1999) Identification of thermolabile Escherichia coli proteins: Prevention and reversion of aggregation by DnaK and ClpB. EMBO J. 18: 6934–6949. 42. Arnold CN, McElhanon J, Lee A, Leonhart R, Siegele DA (2001) Global analysis of Escherichia coli gene expression during the acetate-induced acid tolerance response. J Bacteriol 183: 2178–2186. 19. Leszczynska D, Matuszewska E, Kuczynska-Wisnik D, Furmanek-Blaszk B, Laskowska E (2013) The formation of persister cells in stationary –phase cultures of Escherichia coli is associated with aggregation of endogenous proteins. PLoS One 8(1): e54737. 43. Michaeli S, Mevarech M, Ron EZ (1984) Regulatory region of the metA gene of Escherichia coli K-12. J Bacteriol 160: 1158–1162. ( ) 20. Flavin M, Slaughter C (1967) Enzymatic synthesis of homocysteine or methionine directly from O-succinylhomoserine. Biochim Biophys Acta 132: 400–405. 44. Jensen KF (1993) The Escherichia coli K-12 ‘‘wild types’’ W3110 and MG1655 have an rph frameshift mutation that leads to pyrimidine starvation due to low pyrE expression levels. J Bacteriol 175: 3401–3407. 21. Gur E, Biran D, Gazit E, Ron EZ (2002) In vivo aggregation of a single enzyme limits growth of Escherichia coli at elevated temperature. Mol Microbiol 46: 1391–1397. py p 45. Roe AJ, O’Byrne C, McLaggan D, Booth IR (2002) Inhibition of Escherichia coli growth by acetic acid: a problem with methionine biosynthesis and homocysteine toxicity. Microbiology 148: 2215–2222. 22. Biran D, Gur E, Gollan L, Ron EZ (2000) Control of methionine biosynthesis in Escherichia coli by proteolysis. Mol Microbiol 37: 1436–1443. 46. Han K, Hong J, Lim HC (1993) Relieving effects of glycine and methionine from acetic acid inhibition in Escherichia coli fermentation. Biotechnol. Bioeng. 41: 316–324. 23. Price-Carter M, Fazzio TG, Vallbona EI, Roth JR (2005) Polyphosphate kinase protects Salmonella enterica from weak organic acid stress. J Bacteriol 187: 3088–3099. 47. Maisonneuve E, Shakespeare LJ, Jørgensen MG, Gerdes K (2011) Bacterial persistence by RNA endonucleases. Proc Natl Acad Sci USA 108: 13206–13211. 24. Do¨rr T, Vulic M, Lewis K (2010) Ciprofloxacin causes persister formation by inducing the TisB toxin in Escherichia coli. PLoS One 8(2): e1000317. 48. Hansen S, Lewis K, Vulic´ M (2008) Role of global regulators and nucleotide metabolism in antibiotic tolerance in Escherichia coli. Stabilized MetA Reduces the Persister Frequency 10. Gefen O, Gabay C, Mumcuoglu M, Engel G, Balaban NQ (2008) Single-cell protein induction dynamics reveals a period of vulnerability to antibiotics in persister bacteria. Proc Natl Acad Sci USA 105: 6145–6149. 34. Tuomanen E, Cozens R, Tosch W, Zak O, Tomasz A (1986) The rate of killing of Escherichia coli by beta-lactam antibiotics is strictly proportional to the rate of bacterial growth. J Gen Microbiol 132: 1297–1304. p y p y persister bacteria. Proc Natl Acad Sci USA 105: 6145–6149. g 35. Drlica K, Zhao X (1997) DNA gyrase, topoisomerase IV, and the 4-quinolones. Microbiol Mol Biol Rev 61: 377–92. 11. Lewis K (2007) Persister cells, dormancy and infectious disease. Nat Rev Microbiol 5: 48–56. 12. Lewis K (2008) Multidrug tolerance of biofilms and persister cells. Curr Top Microbiol Immunol 322: 107–131. 36. Eng RH, Padberg FT, Smith SM, Tan EN, Cherubin CE (1991) Bactericidal effects of antibiotics on slowly growing and nongrowing bacteria. Antimicrob Agents Chemother 35: 1824–1828. 13. Luidalepp H, Joers A, Kaldalu N, Tenson T (2011) Age of inoculum strongly influences persister frequency and can effects of mutations implicated in altered persistence. J Bacteriol 193: 3598–3605. 37. Merlin C, Gardiner G, Durand S, Masters M (2002) The Escherichia coli metD locus encodes an ABC transporter which includes Abc (MetN), YaeE (MetI), and YaeC (MetQ). J Bacteriol 184: 5513–5517. p J 14. Orman M, Brynilsen MP (2013) Dormancy is not necessary or sufficient for bacterial persistence. Antimicrob Agents Chemother 57: 3230–3239. 38. Kadner RJ, Watson WJ (1974) Methionine transport in Escherichia coli: physiological and genetic evidence for two uptake systems. J Bacteriol 119: 401– 409. 15. Poole K (2012) Bacterial stress responses as determinants of antimicrobial resistance. J Antimicrob Chemother 67: 2069–2089. 16. Cardoso K, Gandra RF, Wisniewski ES, Osaku CA, Kadowaki MK, et al. (2010) DnaK and GroEL are induced in response to antibiotic and heat shock in Acinetobacter baumannii. J Med Microbiol 59: 1061–1068. 39. Sezonov G, Joseleau-Petit D, D’Ari R (2007) Escherichia coli physiology in Luria-Bertani broth. J Bacteriol 189: 8746–8749. 40. Keren I, Shah D, Spoering A, Kaldalu N, Lewis K (2004) Specialized persister cells and the mechanism of multidrug tolerance in Escherichia coli. J Bacteriol 186: 8172–8180. 17. Murakami K, Ono T, Viducic D, Kayama S, Mori M, et al. (2005) Role of rpoS gene of Pseudomonas aeruginosa in antibiotic tolerance. FEMS Microbiol Letters 242: 161–167. 41. Stabilized MetA Reduces the Persister Frequency Antimicrob Agents Chemother 52: 2718–2726. 25. Sambrook J, Fritsch EF, Maniatis T (1989) Molecular Cloning: a Laboratory Manual. 2nd edition. New York: Cold Spring Harbor Laboratory Press C.S.H. 49. Vazquez-Laslop N, Lee H, Neyfakh AA (2006) Increased persistence in Escherichia coli caused by controlled expression of toxins and other unrelated proteins. J Bacteriol 188: 3494–3497. p g y 26. Datsenko KA, Wanner BL (2000) One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proc Natl Acad Sci U S A 97: 6640–6645. 50. Paek, Walker GC (1987) Escherichia coli dnaK null mutant are inviable at high temperature. J Bacteriol 169, 283–290. 27. Mordukhova EA, Lee, Pan J-G (2008) Improved thermostability and acetic acid tolerance of Escherichia coli via directed evolution of homoserine o- succinyltransferase. Appl Environ Microbiol. 74: 7660–7668. 51. Philipps TA, VanBolegen RA, Neidhardt FC (1984) lon gene product of Escherichia coli is a heat-shock protein. J Bacteriol 159, 283–287. 28. Tomoyasu T, Mogk A, Langen H, Goloubinoff P, Bukau B (2001) Genetic dissection of the roles of chaperones and proteases in protein folding and degradation in the Escherichia coli cytosol. Mol Microbiol 40: 397–413. 52. Mager WH, de Kruijff AJJ (1995) Stress-induced transcriptional activation. Microbiol Rev 59: 506–531. 53. Laskowska E, Kuczynska-Wisnik D, Sko´rko-Glonek J, Taylor A (1996) Degradation by proteases Lon, Clp and HtrA, of Escherichia coli proteins aggregated in vivo by heat shock; HtrA protease action in vivo and in vitro. Mol Microbiol 22: 555–571. 29. Mordukhova EA, Kim D, Pan J-G (2013) Stabilized homoserine o-succinyl- transferases (MetA) or L-Methionine partially recover the growth defect in Escherichia coli lacking ATP-dependent proteases or the DnaK chaperone. BMC Microbiol 13: 179. 54. Winkler J, Seybert A, Ko¨nig L, Pruggnaller S, Haselmann U, et al. (2010) Quantitative and spatio-temporal features of protein aggregation in and consequences on protein quality control and cellular ageing. EMBO J 29: 910–923. 30. Ron EZ, Davis BD (1971) Growth rate of Escherichia coli at elevated temperatures: limitation by methionine. J Bacteriol 107: 391–396. 31. Gefen O, Balaban NQ (2009) The importance of being persistent: heterogeneity of bacterial population under antibiotic stress. FEMS Microbiol Rev 33: 707– 714. 55. Gilbert P, Collier PJ, Brown MRW (1990) Influence of growth rate on susceptibility to antimicrobial agents: biofilms, cell cycles, dormancy and stringent response. Antimicrob Agents Chemother 34: 1865–1868. 32. References PLOS ONE | www.plosone.org 9 October 2014 | Volume 9 | Issue 10 | e110504 Stabilized MetA Reduces the Persister Frequency Balaban NQ, Merrin J, Chait R, Kowalik L, Leibler S (2004) Bacterial persistence as a phenotypic switch. Science 305: 1622–1625. g p g 56. Maisonneuve E, Castro-Camargo M, Gerdes K (2013) (p)ppGpp controls bacterial persistence by stochastic induction of toxin-antitoxin activity. Cell 154: 1140–1150. 33. Greene RC (1996) Biosynthesis of methionine. In: Neidhardt FC, editor. Escherichia coli and Salmonella: Cellular and molecular biology, 2nd ed. Washington (DC): ASM Press. 542–560. October 2014 | Volume 9 | Issue 10 | e110504 PLOS ONE | www.plosone.org 10
https://openalex.org/W1554752194
https://www.scielo.br/j/jbn/a/x5kj9YrD3dgHRkzrQj6bSJq/?lang=pt&format=pdf
Portuguese
null
Uremic serum inhibits<i>in vitro</i>expression of chemokine SDF-1: impact of uremic toxicity on endothelial injury
Brazilian Journal of Nephrology
2,014
cc-by
6,795
Artigo Original | Original Article Artigo Original | Original Article 1 Universidade Federal do Paraná. 2 Pontifícia Universidade Católica do Paraná. 3 Universidade de São Paulo. 4 Universidade Estadual de Campinas (UNICAMP). Soro urêmico inibe a expressão in vitro da quimiocina SDF-1: possível impacto da toxicidade urêmica na lesão endotelial Uremic serum inhibits in vitro expression of chemokine SDF-1: impact of uremic toxicity on endothelial injury Autores Vanessa Ribeiro1 Bruna Bosquetti1 Simone Mikosz Gonçalves2 Sérgio Gardano Elias Bucharles2 Lisienny Rempel1 Rayana Ariane Pereira Maciel1 Rodrigo Bueno de Oliveira3,4 Roberto Pecoits-Filho2 Andréa Emilia Marques Stinghen1 Resumo Results: The study included 26 hemodialysis (HD) patients (17 ± 3 months on dialysis, 52 ± 2 years, 38% men and 11% diabetic). Serum concentrations of CRP, IL-6, SDF-1 and IL-8 were 4.9 ± 4.8 mg/ml, 6.7 ± 8.1 pg/ml, 2625.9 ± 1288.6 pg/ ml and 128.2 ± 206.2 pg/ml, respectively. There was a positive correlation between CRP and IL-6 (ρ = 0.57, p < 0.005) and between SDF-1 and IL-8 (ρ = 0.45, p < 0.05). In vitro results showed that after 6 hours treatment, SDF-1 expression by HUVEC treated with uremic media is lower compared to cells treated with healthy media (p < 0.05). After 12 hours of treatment there was an increase in IL-8 when HUVECs were exposed to uremic media (p < 0.005). Conclusion: We suggest that SDF-1 and IL-8 in HD patients can be used to measure the extent of damage and subsequent vascular activation in uremia. Introduction: Endothelial dysfunction is important in the pathogenesis of cardiovascular disease (CVD) related to chronic kidney disease (CKD). Stromal cell-derived factor-1 (SDF-1) is a chemokine which mobilizes endothelial progenitor cells (EPC) and together with interleukin-8 (IL-8) may be used as markers of tissue injury and repair. Objective: This study investigated in vivo and in vitro the effect of uremic media on SDF-1 and IL-8 expression. Methods: Systemic inflammation was assessed by C-reactive protein (CRP) and interleukin-6 (IL-6). IL-8 and SDF-1 were measured as markers of endothelial dysfunction and tissue repair, respectively, by ELISA. In vitro studies were performed on human umbilical vein endothelial cells (HUVEC) exposed to healthy or uremic media. Results: The study included 26 hemodialysis (HD) patients (17 ± 3 months on dialysis, 52 ± 2 years, 38% men and 11% diabetic). Serum concentrations of CRP, IL-6, SDF-1 and IL-8 were 4.9 ± 4.8 mg/ml, 6.7 ± 8.1 pg/ml, 2625.9 ± 1288.6 pg/ ml and 128.2 ± 206.2 pg/ml, respectively. There was a positive correlation between CRP and IL-6 (ρ = 0.57, p < 0.005) and between SDF-1 and IL-8 (ρ = 0.45, p < 0.05). In vitro results showed that after 6 hours treatment, SDF-1 expression by HUVEC treated with uremic media is lower compared to cells treated with healthy media (p < 0.05). After 12 hours of treatment there was an increase in IL-8 when HUVECs were exposed to uremic media (p < 0.005). Resumo Introdução: A disfunção endotelial é importante na patogênese da doença cardiovascular (DCV) relacionada à doença renal crônica (DRC). Stromal cell-derived factor-1 (SDF-1) é uma quimiocina que mobiliza células endoteliais progenitoras (EPC) e em conjunto com a interleucina-8 (IL-8) podem ser usadas como marcadores de reparo e lesão tecidual. Objetivo: Neste trabalho, foi investigado o efeito do meio urêmico na expressão de SDF-1 e IL-8 in vivo e in vitro. Métodos: A inflamação sistêmica foi avaliada por meio da proteína C-reativa (PCR) e interleucina-6 (IL-6). IL-8 e SDF-1 foram avaliados por ELISA como marcadores de disfunção endotelial e reparo tecidual, respectivamente. Os estudos in vitro foram realizados em células endoteliais umbilicais humanas (HUVEC) expostas ao meio urêmico ou saudável. Resultados: Foram incluídos nesse estudo 26 pacientes em hemodiálise (HD) (17 ± 3 meses em diálise, 52 ± 2 anos, 38% homens e 11% diabéticos). As concentrações séricas de PCR, IL-6, SDF-1 e IL-8 foram 4,9 ± 4,8 mg/ml, 6,7 ± 8,1 pg/ml, 2625,9 ± 1288,6 pg/ml e 128,2 ± 206,2 pg/ml, respectivamente. Hou­ ve correlação positiva entre PCR e IL-6 (ρ = 0,57; p < 0,005) e entre SDF-1 e IL-8 (ρ = 0,45; p < 0,05). Os resultados in vitro demonstraram que a expressão de SDF-1 pelas HUVEC após 6 horas de tratamento com meio urêmico é menor comparada ao tratamento com meio saudável (p < 0,05). Após 12 horas de tratamento, ocorreu aumento de IL-8 quando as HUVECs foram expostas ao meio urêmico (p < 0,005). Conclusão: Sugerimos que SDF-1 e IL-8 nos pacientes em HD podem ser usados para mensurar a extensão do dano e consequente ativação vascular na uremia. Introduction: Endothelial dysfunction is important in the pathogenesis of cardiovascular disease (CVD) related to chronic kidney disease (CKD). Stromal cell-derived factor-1 (SDF-1) is a chemokine which mobilizes endothelial progenitor cells (EPC) and together with interleukin-8 (IL-8) may be used as markers of tissue injury and repair. Objective: This study investigated in vivo and in vitro the effect of uremic media on SDF-1 and IL-8 expression. Methods: Systemic inflammation was assessed by C-reactive protein (CRP) and interleukin-6 (IL-6). IL-8 and SDF-1 were measured as markers of endothelial dysfunction and tissue repair, respectively, by ELISA. In vitro studies were performed on human umbilical vein endothelial cells (HUVEC) exposed to healthy or uremic media. Correspondência para: Andréa Emilia Marques Stinghen. Universidade Federal do Paraná. Departamento de Patologia Básica. Centro Politécnico, Jardim das Américas. Curitiba, PR, Brasil. CEP: 81531-980. E-mail: andreastinghen@ufpr.br Tel: (41) 3361-1691. Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) e Fundação Araucária. DOI: 10.5935/0101-2800.20140021 DOI: 10.5935/0101-2800.20140021 Autores Vanessa Ribeiro1 Bruna Bosquetti1 Simone Mikosz Gonçalves2 Sérgio Gardano Elias Bucharles2 Lisienny Rempel1 Rayana Ariane Pereira Maciel1 Rodrigo Bueno de Oliveira3,4 Roberto Pecoits-Filho2 Andréa Emilia Marques Stinghen1 Resumo Conclusion: We suggest that SDF-1 and IL-8 in HD patients can be used to measure the extent of damage and subsequent vascular activation in uremia. Data de submissão: 13/03/2013. Data de aprovação: 06/02/2014. Data de submissão: 13/03/2013. Data de aprovação: 06/02/2014. Palavras-chave: endotélio vascular; insufi­ ciência renal crônica; interleucina-8; qui­ miocina SDF-1; quimiocinas; toxicidade urêmica. Keywords: chemokine CXCL12; chemo­ kines; endothelium, vascular; interleu­ kin-8; renal insufficiency, chronic; ure­ mia. 123 Soro urêmico inibe a expressão in vitro de SDF-1 Estudos demonstram que quimiocinas como a SDF-1 e IL-8 possivelmente facilitem a migração de EPC para o endotélio lesionado. De fato, a SDF-1 tem sido descrita como indutora de neovascularização e em conjunto com a IL-8 responsável pelo recrutamento de EPC para o tecido isquêmico em DCV, tais como infarto agudo do miocárdio.14,15 Recentemente, alguns trabalhos vêm demonstrando que na DRC níveis plasmáticos de SDF-1 estão aumentados, correlacionando-se com níveis diminuídos de EPCs.16 Estes achados apontam para um possível papel benéfico da SDF-1 no reparo da lesão endotelial. Introdução Em estágios avançados de doença renal crônica (DRC), grande parte dos pacientes é acometida por complicações, na maioria das vezes correlacionadas às doenças cardiovasculares (DCV), incluindo calcificação vascular e disfunção endotelial.1,2 Acredita-se que a alta concentração de toxinas urêmicas circulantes nesta população pode desencadear uma resposta inflamatória sistêmica e vascular e, desta forma, induzir a disfunção endotelial,3 fator reconhecidamente associado ao desenvolvimento e progressão da DCV. Estudos desenvolvidos por nosso grupo demonstram que marcadores plasmáticos de ativação endotelial tais como monocyte chemoattractant protein-1 (MCP-1) e vascular adhesion molecule-1 (VCAM-1) estão aumentados e intimamente associados a outros marcadores de inflamação sistêmica nos estágios mais avançados de DRC, como PCR e IL-6. Além disso, estudos in vitro demonstram que a exposição de células endoteliais ao ambiente urêmico aumenta a expressão de MCP-1, interleucina-8 (IL-8) e VCAM-1, sugerindo uma relação entre lesão vascular, inflamação sistêmica e toxicidade urêmica.4 Em estágios avançados de doença renal crônica (DRC), grande parte dos pacientes é acometida por complicações, na maioria das vezes correlacionadas às doenças cardiovasculares (DCV), incluindo calcificação vascular e disfunção endotelial.1,2 Acredita-se que a alta concentração de toxinas urêmicas circulantes nesta população pode desencadear uma resposta inflamatória sistêmica e vascular e, desta forma, induzir a disfunção endotelial,3 fator reconhecidamente associado ao desenvolvimento e progressão da DCV. Estudos desenvolvidos por nosso grupo demonstram que marcadores plasmáticos de ativação endotelial tais como monocyte chemoattractant protein-1 (MCP-1) e vascular adhesion molecule-1 (VCAM-1) estão aumentados e intimamente associados a outros marcadores de inflamação sistêmica nos estágios mais avançados de DRC, como PCR e IL-6. Além disso, estudos in vitro demonstram que a exposição de células endoteliais ao ambiente urêmico aumenta a expressão de MCP-1, interleucina-8 (IL-8) e VCAM-1, sugerindo uma relação entre lesão vascular, inflamação sistêmica e toxicidade urêmica.4 A partir deste panorama, hipoteticamente sugerimos que, na DRC a exposição constante do endotélio às toxinas urêmicas, com consequente dano vascular, leve a liberação de quimiocinas envolvidas na sinalização e reparo tecidual. Desta forma, o objetivo do presente trabalho foi investigar os efeitos do soro urêmico na expressão in vitro de SDF-1 e IL-8 e estudo clínico envolvendo pacientes com DRC em estágio 5 em hemodiálise (HD). Seleção de pacientes As células endoteliais têm papel importante na regulação do tônus vascular, homeostase, pressão sanguínea e remodelamento vascular, e a habilidade do endotélio em sintetizar e liberar óxido nítrico (NO) constitui um importante regulador destes processos fisiológicos.5 Células endoteliais progenitoras derivadas da medula óssea (EPC) constituem um sistema endotelial endógeno de reparo, protegendo o endotélio do desenvolvimento de aterosclerose. Evidências sugerem que na uremia ocorra uma diminuição na disponibilidade e função das EPC, levando à perda da capacidade de reparo e regeneração do endotélio, contribuindo, desta forma, para o desenvolvimento de DCV.6 Os pacientes objetos do estudo foram selecionados a partir de uma amostra populacional que contava com 104 pacientes renais crônicos em tratamento por HD de um único centro de terapia renal substitutiva na cidade de Curitiba - PR. Após a aplicação de critérios de inclusão e exclusão listados abaixo, foram finalmente selecionados 26 pacientes para participarem do estudo. Todos os pacientes estavam em programa crônico de HD e realizavam três sessões de HD por semana (3,5 a 4 horas por sessão), utilizando membranas de diálise de polissulfona, e dialisato com concentração final de bicarbonato de sódio de 32 mEq/L e cálcio 3,5 mEq/L. Foram excluídos pacientes em programa de diálise peritoneal, pacientes que realizavam sessões de HD por meio de cateter venoso central como acesso vascular, portadores de doença infecciosa ou inflamatória crônica grave, doenças malignas, doença hepática ativa, doenças autoimunes, uso de imunossupressores ou anti-inflamatórios nos últimos 3 meses antes da inclusão no estudo, e aqueles que apresentaram evento cardiovascular (i.e., infarto agudo do miocárdio, angina instável, acidente vascular cerebral ou revascularização do miocárdio) 3 meses antes do início do estudo. A stromal cell-derived factor-1 (SDF-1) é uma quimiocina de ação pleiotrópica e expressa por vários tecidos, tais como rins, medula óssea, coração, fígado, timo, baço, músculo liso e esquelético, células endoteliais e macrófagos.7-9 Originalmente, a ação da SDF-1 foi relacionada à estimulação de linfócitos T, linfócitos B e monócitos.10 Entretanto, descobriu-se que esta quimiocina desempenha também papel fundamental na patofisiologia de processos como inflamação, angiogênese, cicatrização e agregação plaquetária.9,11-13 J Bras Nefrol 2014;36(2):123-131 124 Soro urêmico inibe a expressão in vitro de SDF-1 Todos os pacientes assinaram termo de consentimento informado aceitando participar do presente estudo e o protocolo foi aprovado pelo Comitê de Ética de Pesquisa em Seres Humanos da Universidade Federal do Paraná (registro CEP/SD: 974.079.10.07). Experimentos in vitro Extração e caracterização de células endoteliais humanas de veia de cordão umbilical (HUVEC) Os cordões umbilicais foram coletados logo após o nascimento e processados dentro de 24 horas. As células endoteliais foram extraídas e cultivadas de acordo com Jaffe et al.17 adaptado.4 Brevemente, o cordão umbilical foi canulado, lavado com tampão salino fosfato (PBS) (Sigma-Aldrich, USA) e perfundido com colagenase tipo II (Sigma-Aldrich, USA) a 0,3% em PBS por 7 minutos, a 37 ºC. A suspenção foi centrifugada e ressuspendida e o pellet ressuspendido em meio 199 (Gibco, Grand Island, NY, USA), suplementado com glutamina 2 mM (Gibco, Grand Island, NY, USA), soro fetal bovino (SFB) (Gibco, Grand Island, NY, USA) 10%, heparina 5.000 UI/ml (Sigma-Aldrich, USA), hidrocortisona 0,5 mg/ml (Sigma-Aldrich, USA), endothelial cell growth suplement 15 g/ml (Sigma-Aldrich, USA), β-endothelial cell growth factor human 25 μg/ml (Sigma-Aldrich, USA), penicilina 10.000 UI/ml e estreptomicina 50 μg/ml (Gibco, Grand Island, NY, USA). As HUVEC foram cultivadas até subconfluência em frascos de cultivo de 25 cm2 pré-tratados com gelatina 1% (Sigma-Aldrich, USA) e incubados a 37 ºC em atmosfera de 5% de CO2. As células foram utilizadas para os experimentos entre as passagens 3 e 4, quando então foram tripsinizadas com tripsina-EDTA 0,25% (Sigma-Aldrich, USA) e subcultivadas em placas de 96 poços (10.000 células/ml/poço) pré-tratadas com gela­ tina 1% nas mesmas condições descritas acima. A ori­ gem endotelial foi confirmada pela morfologia celular e através de imunocitoquímica com o anticorpo monoclonal anti-CD31 (Dako Cytomation, Glostrup, Dinamarca). Coleta de dados laboratoriais As amostras de sangue foram coletadas imediatamente antes da primeira sessão de HD da semana, centrifugadas e estocadas a -80 ºC. No início do estudo, foram mensurados os níveis séricos de colesterol total, colesterol frações LDL e HDL, triglicérides, hemoglobina, albumina, cálcio total, fósforo, hormônio da paratireoide (PTH), fosfatase alcalina e PCR em todos os pacientes. Coleta de dados clínicos Durante o recrutamento dos pacientes, foram coletados os dados clínicos e demográficos por meio da entrevista e exame físico realizados no dia da avaliação inicial e análise dos registros do prontuário médico. Os seguintes dados foram utilizados: idade, sexo, raça, comorbidades, etiologia primária de DRC, tempo de diálise, % de pacientes em uso de estatina, vitamina D e aspirina. Níveis séricos de marcadores de inflamação sistêmica, SDF-1 e IL-8 A avaliação de proteína-C reativa (PCR) foi realizada pelo método imunoturbidimétrico automatizado de ultrassensibilidade (ADVIA Sistema Química 1200, Siemens Healthcare, Deerfield, Illinois, EUA), com limite de detecção de 0,5 a 15 mg/L. A dosagem de IL-6 foi realizada pelo método de Enzyme Linked Immuno Sorbent Assay (ELISA) sandwich (R&D Systems, Minneapolis, USA), com limite de detecção do método de 0,5 a 15 mg/L. As dosagens de SDF-1 foram realizadas utilizando-se o método de ELISA (R&D Systems, Minneapolis, EUA), com limite de detecção do método de 1,0 pg/ml a 47 pg/ml. As absorbâncias foram detectadas em leitor de microplaca (Tecan, North, Caroline, USA) a 570 nm. As dosagens de IL-8 foram realizadas utilizando-se o método de ELISA in house (anticorpos R&D Systems, Minneapolis, USA), com limite de detecção de 31,25 Experimentos in vitro Experimentos in vitro Extração e caracterização de células endoteliais humanas de veia de cordão umbilical (HUVEC) Experimentos in vitro Extração e caracterização de células endoteliais humanas de veia de cordão umbilical (HUVEC) Seleção de pacientes Para efeito de comparação, utilizou-se como grupo controle amostras de soro de indivíduos adultos saudáveis (n = 10). a 2.000 pg/ml. As absorbâncias foram detectadas em leitor de microplaca (Tecan, North, Caroline, USA) a 570 nm. Os coeficientes de variação intra e interensaio para IL-8 foram de 8,0% e 7,7%, respectivamente. Análises estatísticas A análise estatística foi realizada usando os pacotes estatísticos para Windows JMP versão 7.0 (SAS Institut Inc, USA) e SigmaStat versão 3.5 (Systat software, Inc., Germany). Os dados foram apresentados como médias ± erro padrão médio (EPM) ou mediana (percentis 25 e 75) para dados clínicos e laboratoriais de cada parâmetro analisado, conforme simetria ou não dos dados. Os resultados foram analisados pelo teste t ou one-way ANOVA para dados paramétricos e Mann-Whitney para dados não paramétricos. Para comparações múltiplas entre os grupos, foi utilizado o teste de ANOVA on Rank’s seguido pelo teste de Dunnett. As análises de correlações foram efetuadas pelo teste de Spearman (ρ). Um p ≤ 0,05 foi considerado como significativo. Resultados As principais características clínicas e laboratoriais dos 26 pacientes incluídos no estudo estão descritas nas Tabelas 1 e 2, respectivamente. A média de idade foi de 52 ± 2 anos, sendo 38% de homens. Nefroesclerose hipertensiva foi a principal causa de DRC, e todos os pacientes da amostra eram hipertensos. Somente 11% dos pacientes apresentavam o diagnóstico de diabetes mellitus como comorbidade associada. Os pacientes estavam em tratamento com estatinas, aspirina e anti-hipertensivos em 30%, 43% e 100% dos casos, respectivamente. Ensaio de viabilidade pelo 3-[4,5-dimetiazol-2yl]-2,5- ifeniltetrazolium bromide (MTT) Cultivo de células endoteliais com soro humano Para preparo do meio urêmico e do meio saudável, foram utilizados os soros dos pacientes/indivíduos na forma de pool. Para tanto, volumes iguais de soro de todos os pacientes da amostra (i.e., n = 26) formaram um único pool urêmico, assim como volumes iguais de soro de indivíduos saudáveis (i.e., n = 10) formaram um único pool controle. J Bras Nefrol 2014;36(2):123-131 125 Soro urêmico inibe a expressão in vitro de SDF-1 As HUVEC foram inicialmente cultivadas em placas de 96 poços até atingirem subconfluência quando, então, foram mantidas por um período de 12 horas em meio de supressão (meio 199 acrescido de 3% de SFB), sem a presença de fatores de crescimento. Posteriormente, foram incubadas com o meio saudável (meio 199 + 10% de pool saudável) e ou meio urêmico (meio 199 + 10% de pool urêmico). Foram realizados cinco experimentos em duplicata. Os sobrenadantes foram coletados nos tempos: 0, 6 e 12 horas de cultivo e em seguida estocados a -80 ºC até o processamento. A média de cada duplicata foi utilizada nas análises estatísticas. Níveis de sdf-1 e il-8 em sobrenadante celular As amostras de sobrenadante foram coletadas nos tempos: 0, 6 e 12 horas de incubação e estocadas a -80 ºC até o processamento. Os níveis de SDF-1 e IL-8 foram mensurados por ELISA como descrito acima. As amostras de sobrenadante foram coletadas nos tempos: 0, 6 e 12 horas de incubação e estocadas a -80 ºC até o processamento. Os níveis de SDF-1 e IL-8 foram mensurados por ELISA como descrito acima. As amostras de sobrenadante foram coletadas nos tempos: 0, 6 e 12 horas de incubação e estocadas a -80 ºC até o processamento. Os níveis de SDF-1 e IL-8 foram mensurados por ELISA como descrito acima. Ensaio de viabilidade pelo método de exclusão com azul de Trypan O número de células endoteliais foi determinado pela contagem direta em câmara de Neubauer pelo método de exclusão de azul de Trypan (Sigma-Aldrich, USA). Basicamente, após cultivo as células endoteliais foram tratadas com meio urêmico e meio saudável nas mesmas condições descritas aci­ ma, tripsinizadas e ressuspendidas em 1 ml de meio 199. Em seguida, 10 μL da suspensão foram acres­ cidos de 10 μL de solução de azul de Trypan 0,4%, quando, então, foi realizada a contagem em câma­ ra de Neubauer com auxílio de microscopia de luz (Nikon, Tokyo, Japan). As células que assimilavam o corante eram consideradas inviáveis e o núme­ ro de células viáveis era calculado por subtração do número de células inviáveis do total de células contadas.18 Ensaio de viabilidade pelo 3-[4,5-dimetiazol-2yl]-2,5- ifeniltetrazolium bromide (MTT) Neste ensaio as HUVEC (104 células/ml/poço) foram cultivadas em placa de cultivo de 96 poços e submetidas aos mesmos tratamentos anteriormente descritos com volume final de tratamento de 100 µL/poço. O MTT (Sigma-Aldrich, USA) foi solubilizado em PBS na concentração de 5 mg/ml. Posteriormente, a solução de MTT foi diluída na proporção de 1:10 com meio MEM 199 (concentração final de 0,5 mg/ml), e adi­ cionada às células (100 µL/poço). A placa foi incubada por 4 horas a 37 °C. Após este período, 100 µL de dimetilsulfoxido (DMSO) (Sigma-Aldrich, USA) foram adicionados em cada poço e a absorbância foi mensurada em 570 nm.19 A mediana dos valores observados para cálcio total, PTH, kt/V, albumina e colesterol total encontrou-se dentro dos valores de referência para pacientes com DRC estágio 5. Marcadores de inflamação sistêmica e quimiocinas As medianas das concentrações séricas dos marcadores de inflamação sistêmica PCR e IL-6 foram, respectivamente, 4,9 ± 4,8 mg/ml e 6,7 ± 8,1 pg/ml. Houve correlação po­ sitiva entre PCR e IL-6 (ρ = 0,57, p < 0,005). Para SDF-1 e IL-8, as concentrações foram, respectivamente, 2.625,9 ± J Bras Nefrol 2014;36(2):123-131 126 Soro urêmico inibe a expressão in vitro de SDF-1 Parâmetros Número de pacientes 26 Idade (anos) 52 ± 2 Sexo (% homens) 38 Raça (% caucasianos) 81 Comorbidades (%) Diabete mellitus 11 Doenças cardiovasculares 15 Hipertensão 100 Doença renal primária (%) Nefrosclerose hipertensiva 30 Nefropatia diabética 11 Glomerulopatia crônica 50 Outras 9 Vitamina D (% de uso) 45 Estatinas (% de uso) 30 Aspirina (% de uso) 43 Anti-hipertensivos (% de uso) 100 Tempo de diálise (meses) 17 ± 3 Valores expressos em média ± DP. Tabela 1 Principais características clínicas da população estudada Tabela 2 Principais características laboratoriais da população estudada Parâmetros Colesterol (mg/dL) 180 (108-248) Colesterol LDL (mg/dL) 106 (42-176) Colesterol HDL (mg/dL) 44 (21-80) Triglicérides (mg/dL) 150 (73-240) Hemoglobina (g/dL) 11,5 (10,8-12,0) Albumina (g/dL) 3,9 (3,3-4,7) Cálcio (mg/dL) 9,0 (7,6-10,3) Fósforo (mg/dL) 6,7 (4,1-9,6) PTH (pg/ml) 446 (11-1.666) Fosfatase alcalina (UI/L) 149 (65-602) kt/V 1,5 (1,1-1,8) PCR (mg/ml) 4,9 ± 4,8 IL-6 (pg/ml) 6,7 ± 8,1 IL-8 (pg/ml) 128,2 ± 206,2 SDF-1 (pg/ml) 2.625,9 ± 1.288,6 Valores expressos em média ± EPM ou mediana (percentis 25 a 75). LDL: Low density lipoprotein; HDL: High density lipoprotein; PTH: Hormônio paratiroideo; PCR: Proteina-C reativa; IL-6: Interleucina-6; IL-8: Interleucina-8; SDF-1: Stromal cell-derived factor-1. Parâmetros Número de pacientes 26 Idade (anos) 52 ± 2 Sexo (% homens) 38 Raça (% caucasianos) 81 Comorbidades (%) Diabete mellitus 11 Doenças cardiovasculares 15 Hipertensão 100 Doença renal primária (%) Nefrosclerose hipertensiva 30 Nefropatia diabética 11 Glomerulopatia crônica 50 Outras 9 Vitamina D (% de uso) 45 Estatinas (% de uso) 30 Aspirina (% de uso) 43 Anti-hipertensivos (% de uso) 100 Tempo de diálise (meses) 17 ± 3 Valores expressos em média ± DP. Tabela 1 Principais características clínicas da população estudada 1.288,6 pg/ml e 128,2 ± 206,2 pg/ml. A correlação en­ tre as duas quimiocinas está apresentada na Figura 1 (ρ = 0,455, p < 0,05). Não foram encontradas diferenças significativas entre as medianas das concentrações séricas de SDF-1 e IL-8 considerando as variáveis sexo, ra­ ça, doença renal primária e comorbidades. (dados não mostrados). Ensaio de viabilidade pelo método de exclusão com azul de Trypan Ensaio de viabilidade pelo método de exclusão com azul de Trypan A análise da viabilidade celular através do método de exclusão pelo Azul de Trypan mostrou 95% de viabilidade para as HUVEC sem tratamento (grupo controle, células cultivadas com meio normal), 90% de viabilidade para as HUVEC tratadas com meio saudável e 84% de viabilidade para as células tratadas com meio urêmico. Não houve diferença significativa entre os tratamentos quando comparados ao grupo controle. Marcadores de inflamação sistêmica e quimiocinas Para o grupo controle, os valores séricos de SDF-1 e IL-8 foram 1.996,6 ± 259,7 pg/ml e 55,1 ± 33,9 pg/ml, respectivamente. Não houve diferença significativa entre os níveis séricos destas duas quimiocinas entre os pacientes em HD e o grupo controle. Figura 1. Correlação entre os níveis séricos de IL-8 e SDF-1 em pacientes urêmicos em tratamento hemodialítico. IL-8: Interleucina 8; SDF-1: Stromal cell-derived factor-1. Experimentos in vitro Ensaio de viabilidade pelo método de exclusão com azul de Trypan Tabela 2 Principais características laboratoriais da população estudada Parâmetros Colesterol (mg/dL) 180 (108-248) Colesterol LDL (mg/dL) 106 (42-176) Colesterol HDL (mg/dL) 44 (21-80) Triglicérides (mg/dL) 150 (73-240) Hemoglobina (g/dL) 11,5 (10,8-12,0) Albumina (g/dL) 3,9 (3,3-4,7) Cálcio (mg/dL) 9,0 (7,6-10,3) Fósforo (mg/dL) 6,7 (4,1-9,6) PTH (pg/ml) 446 (11-1.666) Fosfatase alcalina (UI/L) 149 (65-602) kt/V 1,5 (1,1-1,8) PCR (mg/ml) 4,9 ± 4,8 IL-6 (pg/ml) 6,7 ± 8,1 IL-8 (pg/ml) 128,2 ± 206,2 SDF-1 (pg/ml) 2.625,9 ± 1.288,6 Valores expressos em média ± EPM ou mediana (percentis 25 a 75). LDL: Low density lipoprotein; HDL: High density lipoprotein; PTH: Hormônio paratiroideo; PCR: Proteina-C reativa; IL-6: Interleucina-6; IL-8: Interleucina-8; SDF-1: Stromal cell-derived factor-1. Expressão in vitro de SDF-1 E IL-8 Expressão in vitro de SDF-1 E IL-8 A Figura 2 mostra o efeito do ambiente urêmico na expressão in vitro de SDF-1 (A) e IL-8 (B) (pg/ml) pelas HUVEC. Após 6 horas de tratamento, há uma menor expressão de SDF-1 quando as HUVEC são tratadas com meio urêmico (p < 0,05) em comparação ao tratamento com meio saudável (teste t ou one-way ANOVA). Para IL-8 após 12 horas de tratamento, há um aumento significativo de IL-8 quando as HUVEC são tratadas com meio urêmico em comparação ao tratamento com meio saudável (p < 0,005). Ensaios de viabilidade pelo MTT A análise da viabilidade celular por meio do MTT não mostrou diferenças significativas (teste t ou one-way ANOVA) entre os tratamentos com meio de cultivo normal, meio saudável ou meio urêmico para todos os tratamentos aplicados. J Bras Nefrol 2014;36(2):123-131 127 Soro urêmico inibe a expressão in vitro de SDF-1 A população incluída neste estudo compreendia pacientes em HD, com glomerulopatia crônica, nefrosclerose e nefropatia diabética como principais causas de DRC, e alta prevalência de fatores de risco para DCV, tais como hipertensão. Quanto ao uso de medicamentos, 45% estavam em uso de vitamina D, 30% em uso de estatinas, 43% em uso de aspirina e 100% em uso de anti-hipertensivos. Não foram observadas diferenças significativas entre a população estudada e outros estudos prévios desenvolvidos em pacientes em HD,24,25 excetuando-se a baixa prevalência de diabetes mellitus e dislipidemia observada em nosso estudo. Os níveis séricos de marcadores de inflamação sistêmica, tais como PCR e IL-6, estavam aumentados, e também foram similares aos encontrados em outros estudos, demonstrando que a inflamação sistêmica é um achado comum nos pacientes em HD.26,27 Ainda, os níveis das quimiocinas SDF-1 e IL-8 também estavam em concordância com outros estudos prévios.4,16,28,29 Figura 2. A: Expressão in vitro de SDF-1 (pg/ml) pelas HUVEC antes e após (0 e 6 horas) tratamento com meio urêmico (HD). * p < 0,05 - Controle 6 horas vs. HD 6 horas (teste t); B: Expressão in vitro de IL-8 (pg/ml) pelas HUVECs antes e após (0 e 12 horas) tratamento com meio urêmico (HD). * p < 0,005 - Controle 12 horas vs. HD 12 horas (teste t). Discussão Em concordância com nossos dados, Jie et al.,6 em estudos envolvendo pacientes com diferentes graus de DRC, sugeriram que mesmo nos estágios iniciais de DRC, a regeneração vascular é deficiente, com níveis de células musculares progenitoras aumentadas de acordo com o declínio da função renal; isto se dá concomitantemente a um aumento nos níveis plasmáticos de SDF-1. Ainda trabalhos demonstram que após transplante renal os níveis de EPC se restabelecem em paralelo ao declínio dos níveis de SDF-1, demonstrando claramente o papel da uremia na injuria celular e na regulação nos níveis de SDF-1.37 No que se refere à ativação da resposta vascular e produção de IL-8, nossos dados in vitro confirmam os resultados in vivo, e verificamos que as células endoteliais expostas ao ambiente urêmico respondem aumentando os níveis desta quimiocina, confirmando a uremia como efetora da injúria celular. De forma oposta, os resultados in vitro demonstram que a expressão de SDF-1 é diminuída em células endoteliais após exposição ao meio urêmico quando comparada às células expostas ao meio saudável, sugerindo que a uremia atue de certa forma inibindo a expressão desta quimiocina. De fato, Noh et al.,36 verificaram a interferência da uremia na transcrição do gene CXCL12 (SDF-1), inibindo a síntese de RNA mensageiro (mRNA) O SDF-1 é um importante fator angiogênico liberado na circulação em processos inflamatórios e responsável pela mobilização de EPC da medula óssea para a circulação. O presente estudo demonstra que em pacientes em HD os níveis séricos de SDF-1 estão aumentados quando comparados a controles saudáveis, correlacionando-se positivamente com a IL-8. Tal correlação ocorre em paralelo ao aumento dos marcadores de inflamação sistêmica PCR e IL-6. Em concordância com nossos dados, Jie et al.,6 em estudos envolvendo pacientes com diferentes graus de DRC, sugeriram que mesmo nos estágios iniciais de DRC, a regeneração vascular é deficiente, com níveis de células musculares progenitoras aumentadas de acordo com o declínio da função renal; isto se dá concomitantemente a um aumento nos níveis plasmáticos de SDF-1. Discussão Durante a última década, vários trabalhos vêm demonstrando a ação das toxinas urêmicas como efetoras da disfunção endotelial, contribuindo para a progressão da DCV nos pacientes com DRC.20-22 Pacientes com DRC apresentam um desequilíbrio na vasodilatação endotélio dependente e níveis circulantes aumentados de marcadores de disfunção endotelial e estresse oxidativo. Além disso, apresentam um balanço anormal entre lesão celular ocasionada pela toxicidade urêmica e reparo tecidual (representado pela diminuição de migração de EPC), ocasionando grave injúria endotelial.23 Os principais achados do presente trabalho demonstram níveis séricos aumentados das quimiocinas IL-8 e SDF-1, marcadores de lesão e regeneração tecidual respectivamente, em pacientes em HD. De forma oposta, demonstrou-se, ainda, que in vitro, quando células endoteliais são tratadas com soro urêmico, apresentam expressão diminuída de SDF-1, porém, aumentada de IL-8, sugerindo uma possível ligação entre ativação vascular e reparo tecidual nestes pacientes. O endotélio vascular tem sido reconhecido como um órgão endócrino complexo, que regula diversas funções fisiológicas, tais como tônus vascular, migração e crescimento de células de músculo liso, permeabilidade vascular a solutos e células sanguíneas, regulação da homeostase, entre outras funções.30,31 A disfunção endotelial pode ser mais amplamente definida como um estado pró-inflamatório e pró-trombótico32 e é um achado frequente nos pacientes com DRC em virtude da constante exposição do endotélio a toxinas urêmicas, sendo considerada como precursora na patogênese da aterosclerose e doença arterial obstrutiva33,34 Desta forma, pode-se dizer que nestes pacientes tais patologias são intimamente relacionadas, mas, J Bras Nefrol 2014;36(2):123-131 Figura 2. A: Expressão in vitro de SDF-1 (pg/ml) pelas HUVEC antes e após (0 e 6 horas) tratamento com meio urêmico (HD). * p < 0,05 - Controle 6 horas vs. HD 6 horas (teste t); B: Expressão in vitro de IL-8 (pg/ml) pelas HUVECs antes e após (0 e 12 horas) tratamento com meio urêmico (HD). * p < 0,005 - Controle 12 horas vs. HD 12 horas (teste t). Discussão Ainda trabalhos demonstram que após transplante renal os níveis de EPC se restabelecem em paralelo ao declínio dos níveis de SDF-1, demonstrando claramente o papel da uremia na injuria celular e na regulação nos níveis de SDF-1.37 Concluindo, com base em nossos resultados in vivo demonstramos que a ação da uremia em pacientes em HD pode estar associada a danos vasculares intensos, refletindo os níveis circulantes aumentados das quimiocinas IL-8 e SDF-1, o que sugere uma correlação entre disfunção endotelial e reparo tecidual. Entretanto, nosso estudo limitou-se a um número pequeno de pacientes e entendemos que estudos com um maior número de pacientes e ensaios adicionais in vitro são necessários para avaliar quais a possíveis causas na diminuição nos níveis in vitro de SDF-1. No que se refere à ativação da resposta vascular e produção de IL-8, nossos dados in vitro confirmam os resultados in vivo, e verificamos que as células endoteliais expostas ao ambiente urêmico respondem aumentando os níveis desta quimiocina, confirmando a uremia como efetora da injúria celular. De forma oposta, os resultados in vitro demonstram que a expressão de SDF-1 é diminuída em células endoteliais após exposição ao meio urêmico quando comparada às células expostas ao meio saudável, sugerindo que a uremia atue de certa forma inibindo a expressão desta quimiocina. De fato, Noh et al.,36 verificaram a interferência da uremia na transcrição do gene CXCL12 (SDF-1), inibindo a síntese de RNA mensageiro (mRNA) Discussão J Bras Nefrol 2014;36(2):123-131 128 Soro urêmico inibe a expressão in vitro de SDF-1 sobretudo, mutuamente afetadas uma pela outra.35 De fato, em resposta a injúria celular, recentemente demonstramos em estudos in vivo e in vitro, que a exposição do endotélio ao plasma urêmico em tempo e níveis de uremia dependentes, aumenta a expressão de MCP-1, VCAM-1 solúvel (sVCAM-1) e IL-8, sugerindo uma ligação entre ativação vascular e toxicidade urêmica.4 Alguns estudos, ainda, sugerem que em pacientes com DRC, ocorra uma resposta angiogênica deficiente em virtude da diminuição da produção de células tronco mesenquimais mediada pela quimiocina SDF-1, vascular endothelial growth factor (VEGF) e VEGF receptor 1 (VEGFR1).36 e consequentemente diminuindo a produção da proteína SDF-1. Ainda, Zaza et al.38 observaram em estudos genômicos em células polimorfonucleares (PMN) de pacientes em HD, que a expressão do gene CXCL12 está diminuída, o que poderia resultar em acúmulo de células PMN senescentes na circulação. Nossos resultados in vitro demonstram que após 6 horas de exposição ao meio urêmico as células endoteliais apresentam níveis de SDF-1 diminuídos quando comparados às células tratadas com meio saudável. Em parte, este resultado pode ser explicado em virtude da SDF-1 ser produzida também por outras células, tais como células de medula óssea, coração, fígado, timo, baço, músculo liso e esquelético, macrófagos e rins, além de células endoteliais, atuando de forma pleiotrópica;7,8,39 esta produção múltipla certamente reflete os níveis séricos de SDF-1 encontrados nos pacientes. Ainda, alguns estudos demonstram que após infarto agudo do miocárdio, grande parte do processo angiogênico subsequente é devido à ação conjunta de SDF-1 e IL-8 no recrutamento de EPC para o local da lesão.14,15 Estes achados poderiam explicar a má adaptação vascular encontrada nos pacientes com DRC após eventos isquêmicos.40,41 factor (VEGF) e VEGF receptor 1 (VEGFR1).36 O SDF-1 é um importante fator angiogênico liberado na circulação em processos inflamatórios e responsável pela mobilização de EPC da medula óssea para a circulação. O presente estudo demonstra que em pacientes em HD os níveis séricos de SDF-1 estão aumentados quando comparados a controles saudáveis, correlacionando-se positivamente com a IL-8. Tal correlação ocorre em paralelo ao aumento dos marcadores de inflamação sistêmica PCR e IL-6. Referências 18. Chitalia VC, Murikipudi S, Indolfi L, Rabadi L, Valdez R, Franses JW, et al. Matrix-embedded endothelial cells are protected from the uremic milieu. Nephrol Dial Transplant 2011;26:3858-65. DOI: http://dx.doi.org/10.1093/ndt/ gfr337 1. Drüeke TB, Massy ZA. Atherosclerosis in CKD: differences from the general population. Nat Rev Nephrol 2010;6:723-35. DOI: http://dx.doi.org/10.1038/nrneph.2010.143 2. de Oliveira RB, Okazaki H, Stinghen AE, Drüeke TB, Massy ZA, Jorgetti V. Vascular calcification in chronic kidney disease: a review. J Bras Nefrol 2013;35:147-61. DOI: http://dx.doi. org/10.5935/0101-2800.20130024 g 19. Mosmann T. Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J Immunol Methods 1983;65:55-63. PMID: 6606682 DOI: http://dx.doi.org/10.1016/0022-1759(83)90303-4 3. Stinghen AE, Pecoits-Filho R. Vascular damage in kidney disease: beyond hypertension. Int J Hypertens 2011;2011:232683. PMID: 21876786 DOI: http://dx.doi.org/10.4061/2011/232683 20. de la Sierra A, Larrousse M. Endothelial dysfunction is associated with increased levels of biomarkers in essential hypertension. J Hum Hypertens 2010;24:373-9. DOI: http:// dx.doi.org/10.1038/jhh.2009.91 4. Stinghen AE, Gonçalves SM, Martines EG, Nakao LS, Riella MC, Aita CA, et al. Increased plasma and endothelial cell expression of chemokines and adhesion molecules in chronic kidney disease. Nephron Clin Pract 2009;111:c117-26. PMID: 19147993 DOI: http://dx.doi.org/10.1159/000191205 21. Burger D, Levin A. 'Shedding' light on mechanisms of hyperphosphatemic vascular dysfunction. Kidney Int 2013;83:187-9. DOI: http://dx.doi.org/10.1038/ki.2012.416 p g 22. Stenvinkel P. Endothelial dysfunction and inflammation-is there a link? Nephrol Dial Transplant 2001;16:1968-71. 5. Naseem KM. The role of nitric oxide in cardiovascular diseases. Mol Aspects Med 2005;26:33-65. DOI: http://dx.doi. org/10.1016/j.mam.2004.09.003 23. Jourde-Chiche N, Dou L, Cerini C, Dignat-George F, Brunet P. Vascular incompetence in dialysis patients-protein-bound uremic toxins and endothelial dysfunction. Semin Dial 2011;24:327-37. DOI: http://dx.doi. org/10.1111/j.1525-139X.2011.00925.x 6. Jie KE, Zaikova MA, Bergevoet MW, Westerweel PE, Rastmanesh M, Blankestijn PJ, et al. Progenitor cells and vascular function are impaired in patients with chronic kidney disease. Nephrol Dial Transplant 2010;25:1875-82. DOI: http://dx.doi.org/10.1093/ndt/gfp749 24. de Moraes TP, Fortes PC, Ribeiro SC, Riella MC, Pecoits-Filho R. Comparative analysis of lipid and glucose metabolism biomarkers in non-diabetic hemodialysis and peritoneal dialysis patients. J Bras Nefrol 2011;33:173-9. DOI: http://dx.doi.org/10.1590/S0101-28002011000200009 p p http://dx.doi.org/10.1093/ndt/gfp749 7. Braunersreuther V, Mach F, Steffens S. The specific role of chemokines in atherosclerosis. Thromb Haemost 2007;97:714-21. PMID: 17479181 8. Ghadge SK, Mühlstedt S, Ozcelik C, Bader M. SDF-1 α as a therapeutic stem cell homing factor in myocardial infarction. Pharmacol Ther 2011;129:97-108. DOI: http://dx.doi. org/10.1016/j.pharmthera.2010.09.011 25. Bucharles S, Barberato SH, Stinghen AE, Gruber B, Piekala L, Dambiski AC, et al. Referências Impact of cholecalciferol treatment on biomarkers of inflammation and myocardial structure in hemodialysis patients without hyperparathyroidism. J Ren Nutr 2012;22:284-91. DOI: http://dx.doi.org/10.1053/j. jrn.2011.07.001 9. Karin N. The multiple faces of CXCL12 (SDF-1alpha) in the regulation of immunity during health and disease. J Leukoc Biol 2010;88:463-73. 26. Rattanasompattikul M, Molnar MZ, Zaritsky JJ, Hatamizadeh P, Jing J, Norris KC, et al. Association of malnutrition-inflammation complex and responsiveness to erythropoiesis-stimulating agents in long-term hemodialysis patients. Nephrol Dial Transplant 2013;28:1936-45. DOI: http://dx.doi.org/10.1093/ndt/gfs368 10. Barbieri F, Bajetto A, Porcile C, Pattarozzi A, Schettini G, Florio T. Role of stromal cell-derived factor 1 (SDF1/CXCL12) in regulating anterior pituitary function. J Mol Endocrinol 2007;38:383-9. DOI: http://dx.doi.org/10.1677/JME-06-0014 11. Abi-Younes S, Sauty A, Mach F, Sukhova GK, Libby P, Luster AD. The stromal cell-derived factor-1 chemokine is a potent platelet agonist highly expressed in atherosclerotic. Circ Res 2000;86:131-8. DOI: http://dx.doi.org/10.1161/01. RES.86.2.131 27. Stenvinkel P, Heimbürger O, Jogestrand T. Elevated interleukin-6 predicts progressive carotid artery atherosclerosis in dialysis patients: association with Chlamydia pneumoniae seropositivity. Am J Kidney Dis 2002;39:274-82. DOI: http:// dx.doi.org/10.1053/ajkd.2002.30546 12. Bonavia R, Bajetto A, Barbero S, Pirani P, Florio T, Schettini G. Chemokines and their receptors in the CNS: expression of CXCL12/SDF-1 and CXCR4 and their role in astrocyte proliferation. Toxicol Lett 2003;139:181-9. PMID: 12628753 DOI: http://dx.doi.org/10.1016/S0378-4274(02)00432-0 28. Jie KE, van der Putten K, Bergevoet MW, Doevendans PA, Gaillard CA, Braam B, et al. Short- and long-term effects of erythropoietin treatment on endothelial progenitor cell levels in patients with cardiorenal syndrome. Heart 2011;97:60-5. DOI: http://dx.doi.org/10.1136/hrt.2010.194654 13. Apostolakis S, Papadakis EG, Krambovitis E, Spandidos DA. Chemokines in vascular pathology (review). Int J Mol Med 2006;17:691-701. 29. Stenvinkel P, Lindholm B, Heimbürger M, Heimbürger O. Elevated serum levels of soluble adhesion molecules predict death in pre-dialysis patients: association with malnutrition, inflammation, and cardiovascular disease. Nephrol Dial Transplant 2000;15:1624-30. DOI: http://dx.doi.org/10.1093/ ndt/15.10.1624 14. Gössl M, Mödder UI, Gulati R, Rihal CS, Prasad A, Loeffler D, et al. Coronary endothelial dysfunction in humans is associated with coronary retention of osteogenic endothelial progenitor cells. Eur Heart J 2010;31:2909-14. DOI: http://dx.doi.org/10.1093/ eurheartj/ehq373 30. Cines DB, Pollak ES, Buck CA, Loscalzo J, Zimmerman GA, McEver RP, et al. Endothelial cells in physiology and in the pathophysiology of vascular disorders. Blood 1998;91:3527-61. j q 15. Elmadbouh I, Haider HKh, Jiang S, Idris NM, Lu G, Ashraf M. Ex vivo delivered stromal cell-derived factor-1alpha promotes stem cell homing and induces angiomyogenesis in the infarcted myocardium. Agradecimentos Este trabalho foi financiado pelo Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), processo nº 471282/2010-3 e pela Fundação Araucária, convenio 183-10, protocolo 19488. Os autores gostariam de expressar sua gratidão a Liandra Kondrat, Guilherme Fabri Pereira e Júlio César Francisco por suas contribuições neste estudo. J Bras Nefrol 2014;36(2):123-131 Soro urêmico inibe a expressão in vitro de SDF-1 Referências J Mol Cell Cardiol 2007;42:792-803. PMID: 17350033 31. Malyszko J. Mechanism of endothelial dysfunction in chronic kidney disease. Clin Chim Acta 2010;411:1412-20. PMID: 20598675 DOI: http://dx.doi.org/10.1016/j.cca.2010.06.019 16. Chen YT, Cheng BC, Ko SF, Chen CH, Tsai TH, Leu S, et al. Value and level of circulating endothelial progenitor cells, angiogenesis factors and mononuclear cell apoptosis in patients with chronic kidney disease. Clin Exp Nephrol 2013;17:83-91. DOI: http://dx.doi.org/10.1007/s10157-012-0664-9 32. Moody WE, Edwards NC, Madhani M, Chue CD, Steeds RP, Ferro CJ, et al. Endothelial dysfunction and cardiovascular disease in early-stage chronic kidney disease: cause or association? Atherosclerosis 2012;223:86-94. 17. Jaffe EA, Nachman RL, Becker CG, Minick CR. Culture of human endothelial cells derived from umbilical veins. Identification by morphologic and immunologic criteria. J Clin Invest 1973;52:2745- 56. PMID: 4355998 DOI: http://dx.doi.org/10.1172/JCI107470 33. Shlipak MG, Massie BM. The clinical challenge of cardiorenal syndrome. Circulation 2004;110:1514-7. PMID: 15381655 DOI: http://dx.doi.org/10.1161/01. CIR.0000143547.55093.17 J Bras Nefrol 2014;36(2):123-131 130 Soro urêmico inibe a expressão in vitro de SDF-1 34. Cai H, Harrison DG. Endothelial dysfunction in cardiovascular diseases: the role of oxidant stress. Circ Res 2000;87:840-4. DOI: http://dx.doi.org/10.1161/01.RES.87.10.840 38. Zaza G, Pontrelli P, Pertosa G, Granata S, Rossini M, Porreca S, et al. Dialysis-related systemic microinflammation is associated with specific genomic patterns. Nephrol Dial Transplant 2008;23:1673-81. DOI: http://dx.doi.org/10.1093/ndt/gfm804 35. Ronco C, Chionh CY, Haapio M, Anavekar NS, House A, Bellomo R. The cardiorenal syndrome. Blood Purif 2009;27:114- 26. DOI: http://dx.doi.org/10.1159/000167018 p g g 39. Karin N. The multiple faces of CXCL12 (SDF-1alpha) in the regulation of immunity during health and disease. J Leukoc Biol 2010;88:463-73. DOI: http://dx.doi.org/10.1189/jlb.0909602 36. Noh H, Yu MR, Kim HJ, Jeon JS, Kwon SH, Jin SY, et al. Uremia induces functional incompetence of bone marrow-derived stromal cells. Nephrol Dial Transplant 2012;27:218-25. DOI: http://dx.doi.org/10.1093/ndt/gfr267 40. Becherucci F, Mazzinghi B, Ronconi E, Peired A, Lazzeri E, Sagrinati C, et al. The role of endothelial progenitor cells in acute kidney injury. Blood Purif 2009;27:261-70. DOI: http:// dx.doi.org/10.1159/000202005 37. Herbrig K, Gebler K, Oelschlaegel U, Pistrosch F, Foerster S, Wagner A, et al. Kidney transplantation substantially improves endothelial progenitor cell dysfunction in patients with end-stage renal disease. Am J Transplant 2006;6:2922-8. DOI: http://dx.doi. org/10.1111/j.1600-6143.2006.01555.x 41. Yuen DA, Kuliszewski MA, Liao C, Rudenko D, Leong-Poi H, Chan CT. Nocturnal hemodialysis is associated with restoration of early-outgrowth endothelial progenitor-like cell function. Clin J Am Soc Nephrol 2011;6:1345-53. DOI: http://dx.doi.org/10.2215/ CJN.10911210 J Bras Nefrol 2014;36(2):123-131 131
https://openalex.org/W3213302600
https://bmcbiol.biomedcentral.com/counter/pdf/10.1186/s12915-021-01178-y
English
null
Formation of nuclear condensates by the Mediator complex subunit Med15 in mammalian cells
BMC biology
2,021
cc-by
14,203
© The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Shi et al. BMC Biology (2021) 19:245 https://doi.org/10.1186/s12915-021-01178-y Shi et al. BMC Biology (2021) 19:245 https://doi.org/10.1186/s12915-021-01178-y Open Access Abstract Background: The Mediator complex is an evolutionarily conserved multi-subunit protein complex that plays major roles in transcriptional activation and is essential for cell growth, proliferation, and differentiation. Recent studies revealed that some Mediator subunits formed nuclear condensates that may facilitate enhancer-promoter interactions and gene activation. The assembly, regulation, and functions of these nuclear condensates remain to be further understood. Results: We found that Med15, a subunit in the tail module of the Mediator complex, formed nuclear condensates through a novel mechanism. Nuclear foci of Med15 were detected by both immunostaining of endogenous proteins and live cell imaging. Like Med1 foci and many other biomolecular condensates, Med15 foci were sensitive to 1, 6-Hexanediol and showed rapid recovery during fluorescence recovery after photobleaching. Interestingly, overexpressing DYRK3, a dual-specificity kinase that controls the phase transition of membraneless organelles, appeared to disrupt Med1 foci and Med15 foci. We identified two regions that are required to form Med15 nuclear condensates: the glutamine-rich intrinsically disordered region (IDR) and a short downstream hydrophobic motif. The optodroplet assay revealed that both the IDR and the C-terminal region of Med15 contributed to intracellular phase separation. Conclusions: We identified that the Mediator complex subunit Med15 formed nuclear condensates and characterized their features in living cells. Our work suggests that Med15 plays a role in the assembly of transcription coactivator condensates in the nucleus and identifies Med15 regions that contribute to phase separation. Keywords: Nuclear condensates, Mediator, Med15, Transcription, Cell imaging Formation of nuclear condensates by the Mediator complex subunit Med15 in mammalian cells Yuanyuan Shi1, Jian Chen1, Wei-Jie Zeng1, Miao Li1, Wenxue Zhao1, Xing-Ding Zhang1* and Jie Yao1,2* Yuanyuan Shi1, Jian Chen1, Wei-Jie Zeng1, Miao Li1, Wenxue Zhao1, Xing-Ding Zhang1* and Jie * Correspondence: zhangxd39@mail.sysu.edu.cn; jie.yao@alleninstitute.org 1Molecular Cancer Research Center, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, China Full list of author information is available at the end of the article Background organelles often involves liquid-liquid phase-separation (LLPS), a process that is regulated by multivalency and weak interactions among the protein and RNA constitu- ents and is concentration-dependent [1, 2]. Recent stud- ies have started to reveal the underlying principles of LLPS and suggested that LLPS may serve as a funda- mental mechanism linking cell physiology and disease [3–5]. Proteins that undergo LLPS often contain intrin- sically disordered regions (IDRs) consisting of low- complexity amino acid sequences [6–8]. Many membra- neless organelles are dissolved during mitosis through Membraneless organelles are specialized subcellular compartments that enrich an ensemble of macromole- cules and play important roles in cell physiology. Some well-characterized examples of membraneless organelles include the nucleolus, nuclear speckles, Cajal bodies, and stress granules. Assembly of membraneless * Correspondence: zhangxd39@mail.sysu.edu.cn; jie.yao@alleninstitute.org 1Molecular Cancer Research Center, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, China Full list of author information is available at the end of the article Med1 nuclear foci are sensitive to 1, 6-Hexanediol and are dissolved during mitosis g Immunofluorescence staining revealed that Med1 formed numerous, well-distinguishable nuclear foci in U2OS cells (Fig. 1a), consistent with results with imaging GFP-Med1 in CRISPR knock-in mouse embryonic stem (ES) cells [13]. The specificity of this antibody against endogenous Med1 proteins was confirmed by western blot (Additional file 1: Fig. S1a). Next, we performed Med1 immunostaining in cells treated with 1, 6- Hexanediol, an aliphatic alcohol that has been frequently used to study biomolecular condensates in cells. Distinct Med1 foci became invisible in most cells after 1 min of Hexanediol treatment (Additional file 1: Fig. S1b). Med1 foci reappeared in most cells at 10 min and 30 min after Hexanediol withdrawal (Additional file 1: Fig. S1b). Be- cause Med1 foci could be distinguished as individual fluorescence spots in a 3D image stack (Fig. 1a), we used the AirLocalize program [22] to obtain the number of Med1 foci in cells. The median number of Med1 foci per nucleus decreased from ~ 150 in untreated cells to less than 50 in Hexanediol-treated cells and increased to 200–300 in cells recovered for 10 min and 30 min (Add- itional file 1: Fig. S1c). We note that fluorescence inten- sities of Med1 foci were generally higher in recovered cells than in untreated cells (Additional file 1: Fig. S1b), which might explain the higher number of Med1 foci in recovered cells because the same intensity threshold was used for quantification. Recent findings on biomolecular condensates formed by eukaryotic transcription machineries suggested a role of phase separation in gene expression [10]. For ex- ample, biomolecular condensates were observed to form in vitro and in vivo by the C-terminal domain of RNA polymerase II (Pol II) [11, 12], the Mediator complex [13, 14], or by multiple sequence-specific transcription factors (TFs) containing disordered amino acid regions at their activation domains [6, 15]. Furthermore, diverse TFs can form phase-separated condensates with Medi- ator, suggesting that nuclear condensates may function in gene activation [15]. These new findings complement the conventional view of eukaryotic gene regulation that Mediator transduces signals from enhancer-bound TFs to the core transcriptional machinery [16]. Further stud- ies are needed to better understand the mechanisms of condensate formation and their proposed functions in gene expression. The Mediator complex is an evolutionarily conserved multi-subunit transcription coactivator complex that is essential for growth and survival of all cells [16]. Med1 nuclear foci are sensitive to 1, 6-Hexanediol and are dissolved during mitosis Medi- ator has a flexible structure and is organized into head, middle, tail, and Cdk8 modules [17]. Recent studies found that the Mediator subunit Med1 formed nuclear foci in mouse embryonic stem cells [13] and yeast Med15 protein could form condensates with transcrip- tion activator GCN4 in vitro [15]. Med1 and Med15 be- long to the middle module and the tail module of the Mediator complex, respectively. Med15 contains a glutamine-rich IDR and interacts with multiple tran- scription activators through its structured or unstruc- tured domains [18–20]. Previous work indicated that Med3 and Med15 could form amyloid-like aggregates in yeast cells upon H2O2 stress [21], but whether Med15 forms condensates in mammalian cells is unclear. Many well-known membraneless organelles, such as nuclear speckles, nucleoli, and Cajal bodies, are dissolved during mitosis [23–25]. Nonetheless, the status of Med1 nuclear foci in mitotic cells has not been described. By immunofluorescence staining, we found a more homo- geneous localization of Med1 in mitotic cells than in interphase cells (Fig. 1b). The median number of Med1 foci decreased from ~ 150 in interphase cells to less than 50 in mitotic cells (Fig. 1c). Thus, Med1 nuclear foci re- semble other membraneless organelles in their ability to dissolve during mitosis. In this work, we provided experimental evidence that Med15 forms nuclear condensates in mouse and human cells. Med15 foci mimicked Med1 foci in the sensitivity to 1, 6-Hexanediol and rapid FRAP recov- ery. Med1 foci and Med15 foci were largely abolished in mitotic cells and upon overexpressing DYRK3 kin- ase. Interestingly, formation of Med15 nuclear con- densates required both its glutamine-rich IDR region and a short sequence of hydrophobic amino acids. Upon blue light induction, either the N-terminal IDR or the C-terminal region of Med15 was sufficient to form optodroplets in living cells. We also found concentration-dependent effects of 1, 6-Hexanediol on the activation of immediate early genes upon serum stimulation. Shi et al. BMC Biology (2021) 19:245 Shi et al. BMC Biology (2021) 19:245 Page 2 of 17 Page 2 of 17 Page 2 of 17 actions of protein kinases including DYRK3 [9]. Despite many previous studies, much remains to be discovered on the formation, regulation, and functions of membra- neless organelles in cells. Results Med1 nuclear foci are sensitive to 1, 6-Hexanediol and are dissolved during mitosis Med1 nuclear foci are sensitive to 1, 6-Hexanediol and are dissolved during mitosis Characterization of nuclear condensates formed by Med15 The Mediator complex consists of over 30 protein sub- units, many of which contain IDR sequences [26] that might contribute to phase separation. Thus, it would be interesting to study whether additional Mediator sub- units might participate in the formation of nuclear con- densates. In this study, we focused on a single subunit, Med15, which contains a large IDR including multiple Glutamine (Q) residues (Additional file 1: Fig. S2a). First, we found that GFP-tagged human Med15 or RFP-tagged mouse Med15 formed multiple nuclear foci in U2OS Page 3 of 17 Shi et al. BMC Biology (2021) 19:245 Shi et al. BMC Biology Fig. 1 (See legend on next page.) Fig. 1 (See legend on next page.) Page 4 of 17 Shi et al. BMC Biology (2021) 19:245 (See figure on previous page.) Fig. 1 Distributions of Med1 nuclear foci in interphase and mitotic human cells. a Wide-field fluorescence images of a human U2OS cell nucleus stained with an anti-Med1 antibody. The z-interval between individual images is 0.3 μm. Scale bar: 5 μm. b Interphase and mitotic U2OS cells co- stained with an anti-Med1 antibody (green) and Hoechst33342 (blue). Scale bar: 10 μm. The yellow arrow indicates a cell undergoing mitosis. Insets 1 and 2 show the enlarged images of Med1 foci in interphase and mitotic cells, respectively. Scale bars: 5 μm. Similar results were obtained from three independent experiments. c The number of Med1 foci quantified in individual interphase or mitotic U2OS cells by AirLocalize program [22] (Intensity threshold: 450). The numbers of analyzed cells were 46 and 17, respectively. Student’s t test: p < 0.001 (indicated by ***) cells, respectively (Fig. 2a, Additional file 1: Fig. S2b). Consistently, immunofluorescence staining using a Med15 antibody revealed numerous nuclear foci in U2OS cells (Fig. 2b), and Med15 foci detected by im- munofluorescence were colocalized with TagRFP- mMed15 (Additional file 1: Fig. S2b). We performed western blot to confirm the specificity of this antibody in detecting endogenous Med15 proteins in U2OS cells (Additional file 1: Fig. S2c). To further characterize the properties of Med15 nuclear condensates, we generated a T24 stable cell line expressing GFP-hMed15. GFP- tagged human Med15 formed multiple nuclear foci (Additional file 1: Fig. S2d) and were colocalized with Med15 foci detected by immunofluorescence (Additional file 1: Fig. S2e). Characterization of nuclear condensates formed by Med15 Furthermore, we found that all promin- ent GFP-hMed15 foci were colocalized with nuclear foci formed by endogenous Med1 in this stable cell line (Fig. 2c). Therefore, we concluded that both endogenous and overexpressed Med15 formed nuclear condensates in human cells. cells (Additional file 1: Fig. S4a, b). Our results thus suggested Med15 was important for both maintaining Med1 protein level and forming Med1 nuclear foci. Additionally, GFP-hMed15 expressed in Med15 knockdown cells formed nuclear foci similarly as in control cells (Additional file 1: Fig. S4e). ( g ) Furthermore, we examined the response of GFP- Med15 nuclear foci to Hexanediol treatment by live cell imaging. Because high concentrations of Hexane- diol likely introduce non-specific effects to cells [27], we tested Hexanediol concentrations lower than pre- viously used to examine nuclear condensates in the GFP-Med15 stable cell line. Interestingly, application of 0.5% 1, 6-Hexanediol resulted in rapid and sub- stantial decrease of fluorescence intensities of GFP- Med15 nuclear foci (Fig. 2d, Additional file 1: Fig. S5, Additional file 2: Video S1), and withdrawing Hexanediol from the growth media resulted in the reassembly of GFP-Med15 foci that plateaued in about 15 min (Fig. 2d, Additional file 1: Fig. S5, Additional file 2: Video S1). Therefore, rapid disrup- tion/reassembly upon 1,6-Hexanediol treatment/with- drawal is a property shared between Med15 foci and Med1 foci. Our results indicated that low concentra- tions of Hexanediol (i.e., 0.5%) could dissolve nuclear condensates that have small sizes (such as GFP- Med15 foci). We attempted to determine the state of Med15 foci in mitotic cells but did not obtain conclusive results. Med15 immunofluorescence staining revealed multiple foci in mitotic U2OS cells (Additional file 1: Fig. S3a) and Med15 foci numbers per cell were higher in mi- totic cells than in interphase cells (Additional file 1: Fig. S3b). In the stable T24 cell line expressing GFP- Med15, however, prominent Med15 foci observed in interphase cells were absent in most mitotic cells (Additional file 1: Fig. S3c, d). We suggest that prom- inent GFP-Med15 foci in the stable cell line that were colocalized with anti-Med1 (Fig. 2c) may be more consistent markers of Mediator condensates reported in previous studies [13, 14]. Dynamics of Med15 foci in living cells y g A characteristic feature of liquid-like nuclear con- densates is the rapid exchange of their molecular components with the nucleoplasm [13, 14]. We next examined the association of Med15 with nuclear foci in living cells by fluorescence recovery after photo- bleaching (FRAP). In NIH3T3 cells expressing AcGFP-Med15, we observed that fluorescence inten- sities of nuclear foci recovered to approximately ini- tial levels within 10 s after initial photobleaching (Fig. 3a, b). Similar results were obtained from NIH3T3 cells expressing TagRFP-Med15 (Additional file 1: Fig. S6). Furthermore, we observed fusion events and fission events of GFP-Med15 foci on the timescale of several minutes (Fig. 3c, Additional file 1: Fig. S7, Additional file 3: Video S2, Additional file 4: Video S3). Therefore, our results indicated that Med15 exchanged between nuclear condensates and Next, we examined the state of Mediator conden- sates in U2OS cells where Med15 was depleted by RNAi. Both Med15 and Med1 protein levels appeared to be reduced in Med15 knockdown cells (Additional file 1: Fig. S4c), and Med15 mRNA level was substan- tially lower (Additional file 1: Fig. S4d). Anti-Med15 staining was reduced to background levels in Med15 knockdown cells (Additional file 1: Fig. S4a), confirm- ing the specificity of this antibody in immunostaining experiments. Notably, anti-Med1 staining intensity was diminished and the numbers of Med1 nuclear foci were significantly decreased in Med15 knockdown Page 5 of 17 Shi et al. BMC Biology (2021) 19:245 Shi et al. BMC Biology the nucleoplasm at a rate comparable with that mea- sured on Med1 [13], and suggested that Med15 mol- ecules within these nuclear condensates were in a DYRK3 overexpression disrupts Med1 nuclear foci and Med15 nuclear foci. Recent studies revealed that the dual-specificity tyrosine Fig. 2 Med15 forms nuclear foci that are disrupted by Hexanediol treatment. a Fluorescence image of a U2OS cell transfected with AcGFP- hMed15. b Fluorescence images of U2OS cells stained with Hoechst33342 (blue) and an anti-Med15 antibody (green). Similar results were obtained from three independent experiments. c Fluorescence images of a human T24 cell line stably expressing GFP-hMed15 (green) and co- stained with an anti-Med1 antibody (red) and Hoechst33342 (blue). Yellow arrowheads indicate sites of colocalization. Similar results were obtained from three independent experiments. d Time-lapse fluorescence images of a cell from human T24 stable cell line expressing AcGFP- hMed15 during treatment with 0.5% 1, 6-Hexanediol and subsequent recovery. Dynamics of Med15 foci in living cells Yellow arrows indicate the time points of Hexanediol addition and withdrawal. Noted time points on the images are in mm:ss format. Similar results were obtained from three independent experiments. All scale bars: 5 μm Fig. 2 Med15 forms nuclear foci that are disrupted by Hexanediol treatment. a Fluorescence image of a U2OS cell transfected with AcGFP- hMed15. b Fluorescence images of U2OS cells stained with Hoechst33342 (blue) and an anti-Med15 antibody (green). Similar results were obtained from three independent experiments. c Fluorescence images of a human T24 cell line stably expressing GFP-hMed15 (green) and co- stained with an anti-Med1 antibody (red) and Hoechst33342 (blue). Yellow arrowheads indicate sites of colocalization. Similar results were obtained from three independent experiments. d Time-lapse fluorescence images of a cell from human T24 stable cell line expressing AcGFP- hMed15 during treatment with 0.5% 1, 6-Hexanediol and subsequent recovery. Yellow arrows indicate the time points of Hexanediol addition and withdrawal. Noted time points on the images are in mm:ss format. Similar results were obtained from three independent experiments. All scale bars: 5 μm the nucleoplasm at a rate comparable with that mea- sured on Med1 [13], and suggested that Med15 mol- ecules within these nuclear condensates were in a liquid-like phase. DYRK3 overexpression disrupts Med1 nuclear foci and Med15 nuclear foci. DYRK3 overexpression disrupts Med1 nuclear foci and Med15 nuclear foci. Recent studies revealed that the dual-specificity tyrosine kinase DYRK3 played a key role in dissolving multiple, Page 6 of 17 Shi et al. BMC Biology (2021) 19:245 Shi et al. BMC Biology but not all membraneless organelles during mitosis [9]. Moreover, overexpressing DYRK3 disrupted several nu- clear organelles (such as nuclear speckle and Cajal body) i i h ll [9] W h h i d h DYRK3 might play a role in the dissolution of Med1 foci during mitosis. As expected, Med1 foci were mostly dissolved in cells synchronized at mitotic stage by thymidine- d l bl k (Addi i l fil 1 Fi S8 ) N bl Fig. 3 Dynamics of Med15 nuclear foci in living cells. a Time-lapse images of an NIH3T3 cell nucleus expressing AcGFP-mMed15 during a FRAP experiment. Yellow boxes indicate the photobleached area. t = 0.00 s indicates the time point immediately after photobleaching. b Plot of GFP- mMed15 fluorescence intensity at the photobleached area within 42 s after photobleaching. Time intervals between individual frames in the first 20 cycles and the last 20 cycles of post-bleach were 655 ms and 5 s, respectively. Data are presented as the mean ± SEM, n = 3. c Time-lapse images of GFP-mMed15 foci that exhibited fusion and fission events (highlighted in yellow boxes and enlarged at upper-right insets). All scale bars: 5 μm Fig. 3 Dynamics of Med15 nuclear foci in living cells. a Time-lapse images of an NIH3T3 cell nucleus expressing AcGFP-mMed15 during a FRAP experiment. Yellow boxes indicate the photobleached area. t = 0.00 s indicates the time point immediately after photobleaching. b Plot of GFP- mMed15 fluorescence intensity at the photobleached area within 42 s after photobleaching. Time intervals between individual frames in the first 20 cycles and the last 20 cycles of post-bleach were 655 ms and 5 s, respectively. Data are presented as the mean ± SEM, n = 3. c Time-lapse images of GFP-mMed15 foci that exhibited fusion and fission events (highlighted in yellow boxes and enlarged at upper-right insets). All scale Fig. 3 Dynamics of Med15 nuclear foci in living cells. a Time-lapse images of an NIH3T3 cell nucleus expressing AcGFP-mMed15 during a FRAP experiment. Yellow boxes indicate the photobleached area. t = 0.00 s indicates the time point immediately after photobleaching. DYRK3 overexpression disrupts Med1 nuclear foci and Med15 nuclear foci. b Plot of GFP- mMed15 fluorescence intensity at the photobleached area within 42 s after photobleaching. Time intervals between individual frames in the first 20 cycles and the last 20 cycles of post-bleach were 655 ms and 5 s, respectively. Data are presented as the mean ± SEM, n = 3. c Time-lapse images of GFP-mMed15 foci that exhibited fusion and fission events (highlighted in yellow boxes and enlarged at upper-right insets). All scale bars: 5 μm but not all membraneless organelles during mitosis [9]. Moreover, overexpressing DYRK3 disrupted several nu- clear organelles (such as nuclear speckle and Cajal body) in interphase cells [9]. We hypothesized that DYRK3 might play a role in the dissolution of Med1 foci during mitosis. As expected, Med1 foci were mostly dissolved in cells synchronized at mitotic stage by thymidine- nocodazole block (Additional file 1: Fig. S8a). Notably, Shi et al. BMC Biology (2021) 19:245 Page 7 of 17 Shi et al. BMC Biology (2021) 19:245 Shi et al. BMC Biology (2021) 19:245 Page 7 of 17 Med1 foci reappeared in a portion of mitotic cells upon treatment with GSK626616, a small molecule inhibitor of DYRK3 (Additional file 1: Fig. S8b-d), suggesting that DYRK3 kinase activity plays a role in dissolving Med1 foci in mitotic cells. transfected cells (Additional file 1: Fig. S10b), and GFP- Med15 foci were still present in most lentivirus-infected cells (Additional file 1: Fig. S10a, c). Likewise, transfected cells containing GFP-Med15 foci had significantly lower mean intensity of TagRFP-NLS*-DYRK3 compared to those without visible GFP-Med15 foci (Additional file 1: Fig. S10d). Taken together, our work revealed that Med1 foci and GFP-Med15 foci can be dissolved by overexpress- ing DYRK3 kinase, which provides a likely explanation for the dissolution of Med1 foci and GFP-Med15 foci in mi- totic cells. Next, we examined the effects of DYRK3 overexpression on Med1 and Med15 nuclear foci in interphase cells. We expressed mCherry or mCherry-NLS*-DYRK3 (NLS*: SV40 nuclear localization signal) in U2OS cells and per- formed immunofluorescence staining against Med1. Most cells overexpressing DYRK3 showed diffuse Med1 localization in the nucleoplasm, in which the numbers of Med1 nuclear foci were substantially decreased (Fig. 4a, b, e). The same results were obtained in NIH3T3 cells (Add- itional file 1: Fig. S9). DYRK3 overexpression disrupts Med1 nuclear foci and Med15 nuclear foci. In the T24 cell line stably expressing GFP-Med15, most cells transfected with TagRFP-NLS*- DYRK3 lost prominent GFP-Med15 foci that were ob- served in untransfected interphase cells (Fig. 4c, d, f). Interestingly, dissolution of GFP-Med15 foci was affected by relative expression levels of TagRFP-NLS*-DYRK3. The mean intensity of TagRFP-NLS*-DYRK3 in lentivirus-infected cells was ~ 7 fold lower than that in Because the Serine-rich IDR region of Med1 was shown to mediate its phase separation in vitro [13], we tested whether overexpressing DYRK3 could affect nuclear con- densates formed by Med1 IDR in cells. Interestingly, when GFP-tagged Med1 IDR region (amino acid residues 948- 1568) was expressed in NIH3T3 cells, it was enriched in the nucleolar regions and colocalized with Nucleophosmin (NPM1), an abundant nucleolar protein (Additional file 1: Fig. S11a). Notably, expressing TagRFP-NLS*-DYRK3 re- sulted in the redistribution of GFP-Med1 (948-1568) to the nucleoplasm (Additional file 1: Fig. S11b). Fig. 4 DYRK3 overexpression disrupts Med1 foci and Med15 foci. a, b Fluorescence images of U2OS cells transfected with mCherry (a) or mCherry-NLS*-DYRK3 (b) and stained with anti-Med1 (green). c, d Fluorescence images of human T24 cells that stably expressed GFP-Med15 (green) and were transfected with TagRFP (c) or TagRFP-NLS*-DYRK3 (d). All scale bars are 10 μm. In b and d, red arrowheads indicate the transfected cells. Similar results were obtained from three independent experiments. e The number of Med1 clusters quantified in individual U2OS cells after transfection with mCherry (n = 29) or mCherry-NLS*-DYRK3 (n = 44) (Intensity threshold: 600). Student’s t test: p < 0.001 (indicated by ***). f The percentage of cells displaying clusters of GFP-Med15 or diffuse localizations in the nucleoplasm after transfection with TagRFP (n = 28) or TagRFP-NLS*-DYRK3 (n = 57). Fisher’s exact test: p < 0.001 (indicated by ***) Fig. 4 DYRK3 overexpression disrupts Med1 foci and Med15 foci. a, b Fluorescence images of U2OS cells transfected with mCherry (a) or mCherry-NLS*-DYRK3 (b) and stained with anti-Med1 (green). c, d Fluorescence images of human T24 cells that stably expressed GFP-Med15 (green) and were transfected with TagRFP (c) or TagRFP-NLS*-DYRK3 (d). All scale bars are 10 μm. In b and d, red arrowheads indicate the transfected cells. Similar results were obtained from three independent experiments. e The number of Med1 clusters quantified in individual U2OS cells after transfection with mCherry (n = 29) or mCherry-NLS*-DYRK3 (n = 44) (Intensity threshold: 600). DYRK3 overexpression disrupts Med1 nuclear foci and Med15 nuclear foci. Student’s t test: p < 0.001 (indicated by ***). f The percentage of cells displaying clusters of GFP-Med15 or diffuse localizations in the nucleoplasm after transfection with TagRFP (n = 28) or TagRFP-NLS*-DYRK3 (n = 57). Fisher’s exact test: p < 0.001 (indicated by ***) Shi et al. BMC Biology (2021) 19:245 Page 8 of 17 The Q-rich IDR and a hydrophobic amino acid region of Med15 are both required to form nuclear condensates Next, we sought to identify the amino acid regions respon- sible for the formation of Med15 nuclear condensates. We generated a series of mouse Med15 truncation mutants fused to TagRFP at its C-terminus and compared their The Q-rich IDR and a hydrophobic amino acid region of Med15 are both required to form nuclear condensates The Q-rich IDR and a hydrophobic amino acid region of Med15 are both required to form nuclear condensates abilities to form nuclear foci (Fig. 5a). Med15 contains a KIX domain at its N-terminus, followed by a long glutamine-rich IDR (71-617) and a structured C-terminal domain that also contains its NLS (661-670). Surprisingly, Med15 (100-600) and Med15 (1-617) fragment fused to TagRFP and SV40 NLS (NLS*) were diffusely localized in Next, we sought to identify the amino acid regions respon- sible for the formation of Med15 nuclear condensates. We generated a series of mouse Med15 truncation mutants fused to TagRFP at its C-terminus and compared their Fig. 5 Formation of Med15 nuclear foci is mediated by its IDR and a hydrophobic amino acid sequence. a Diagrams of mouse Med15 truncation mutants examined in this study. TagRFP was fused to the N-terminus of each protein fragment. SV40 NLS (NLS*, orange) was inserted before the coding regions of several Med15 truncation mutants at their N-termini. The endogenous NLS (blue) of mouse Med15 is located at amino acid residues 661-670. b Representative images of NIH3T3 cells expressing each mouse Med15 truncation mutant fused to TagRFP. Scale bar: 5 μm. c Percentages of NIH3T3 cells that display no nuclear clusters, small nuclear clusters (diameter < 1 μm), and large nuclear clusters (diameter > 1 μm) of mouse Med15 (WT) or truncation mutants. The numbers of analyzed cells were 90, 88, 96, 117, 92, and 85, respectively. DYRK3 overexpression disrupts Med1 nuclear foci and Med15 nuclear foci. The numbers of cells without clusters and the numbers of cells with clusters (including small and large) were obtained for each construct and subject to Fisher’s exact test: *** indicates p < 0.001. d Percentages of cells that display no clusters or nuclear clusters among NIH3T3 cells expressing GFP-mMed15 (WT) (n = 73) or GFP-mMed15 (mutant) (n = 164). This Med15 mutant contains eight point mutations within the 639-660 region which convert hydrophobic amino acids into hydrophilic amino acids (shown in the sequence comparison above the plot). Fisher’s exact test: p < 0.001 (indicated by ***). e Representative images of NIH3T3 cells expressing AcGFP-tagged mMed15 (WT) protein and the Med15 mutant described in d. The right columns contain the enlarged images of cells marked with dashed white borders. Scale bars: 5 μm. Similar results were obtained from two independent experiments Fig. 5 Formation of Med15 nuclear foci is mediated by its IDR and a hydrophobic amino acid sequence. a Diagrams of mouse Med15 truncation mutants examined in this study. TagRFP was fused to the N-terminus of each protein fragment. SV40 NLS (NLS*, orange) was inserted before the coding regions of several Med15 truncation mutants at their N-termini. The endogenous NLS (blue) of mouse Med15 is located at amino acid residues 661-670. b Representative images of NIH3T3 cells expressing each mouse Med15 truncation mutant fused to TagRFP. Scale bar: 5 μm. c Percentages of NIH3T3 cells that display no nuclear clusters, small nuclear clusters (diameter < 1 μm), and large nuclear clusters (diameter > 1 μm) of mouse Med15 (WT) or truncation mutants. The numbers of analyzed cells were 90, 88, 96, 117, 92, and 85, respectively. The numbers of cells without clusters and the numbers of cells with clusters (including small and large) were obtained for each construct and subject to Fisher’s exact test: *** indicates p < 0.001. d Percentages of cells that display no clusters or nuclear clusters among NIH3T3 cells expressing GFP-mMed15 (WT) (n = 73) or GFP-mMed15 (mutant) (n = 164). This Med15 mutant contains eight point mutations within the 639-660 region which convert hydrophobic amino acids into hydrophilic amino acids (shown in the sequence comparison above the plot). Fisher’s exact test: p < 0.001 (indicated by ***). e Representative images of NIH3T3 cells expressing AcGFP-tagged mMed15 (WT) protein and the Med15 mutant described in d. DYRK3 overexpression disrupts Med1 nuclear foci and Med15 nuclear foci. The right columns contain the enlarged images of cells marked with dashed white borders. Scale bars: 5 μm. Similar results were obtained from two independent experiments Shi et al. BMC Biology (2021) 19:245 Page 9 of 17 Page 9 of 17 in vivo would benefit from a cellular assay that can visualize condensate formation in real time. We applied the optodroplet assay to analyze how Med15 IDR, Med15 C-terminal domain, or Med1 IDR contribute to phase separation in cells. In this assay, protein domains of interest were fused to a fluorescent protein and the coding sequence of cryptochrome2 (Cry2), a blue light- sensitive protein from Arabidopsis thaliana, and the for- mation of optodroplets after blue light stimulation was visualized in real time [29]. First, we transiently expressed mCherry-Cry2 in NIH3T3 cells and did not observe optodroplet formation after illumination with blue light for 90 s (Fig. 6a). In contrast, mCherry-Cry2 fused to a Serine-rich IDR region of Med1 (amino acid 948-1157) formed optodroplets within 30 s of blue light stimulation (Fig. 6b), consistent with a previous study [13]. Next, we generated constructs of mCherry-Cry2 fused to NLS*-Med15 IDR (amino acid 71-617) or Med15 C-terminal region (amino acid 618-789) and ex- amined optodroplet formation in living cells. Optodro- plets formed by Med15 IDR appeared in spherical shape but were smaller in size than those formed by Med1 IDR after the same duration of blue light stimulation (Fig. 6b, c). Remarkably, Med15 C-terminal region formed optodroplets within 5 s after blue light stimula- tion (Fig. 6d), considerably faster than Med1 or Med15 IDR. The apparently lower efficiency of Med1 IDR in optodroplet formation (Fig. 6e) could arise from the shorter length of Med1 IDR or from our experimental conditions. Therefore, the optodroplet assay confirmed that both Med15 IDR and Med15 C-terminal region contributed to phase separation in cells. the nucleus (Fig. 5b, c). Med15 (100-600) and Med15 (1- 617) fused to TagRFP only were localized in the cytoplasm and formed several large aggregates (Fig. 5b) distinct from numerous small nuclear foci formed by full-length Med15 (Fig. 2a, Fig. 3c). These results suggested that the glutamine-rich IDR of Med15 was not sufficient to form condensates in the nucleus. These observations were also consistent with previous findings on several prion-like RNA-binding proteins that formed condensates in the cyto- plasm while remained soluble in the nucleus [28]. DYRK3 overexpression disrupts Med1 nuclear foci and Med15 nuclear foci. p Interestingly, both Med15 (1-670) and Med15 (1-680) formed multiple small nuclear foci (Fig. 5b, c) resembling those formed by full-length Med15. Because the 661-670 amino acid region is the native NLS of Med15, we exam- ined TagRFP-NLS*-Med15 (1-660) and found that it also formed multiple nuclear foci (Fig. 5b, c). Importantly, both TagRFP-NLS*-Med15(1-660) and TagRFP-Med15(1-680) were colocalized with GFP-Med15 foci (Additional file 1: Fig. S12a). Thus, Med15 (618-660) region likely plays a role in condensate formation. Meanwhile, a C-terminal trunca- tion of Med15 (amino acid 618-789) failed to form nuclear foci (Fig. 5b), suggesting that the N-terminal region (1-617) containing the Q-rich IDR also contributed to nuclear con- densate assembly. Furthermore, we generated human Med15 truncation mutants according to the alignment be- tween human and mouse Med15 protein sequences and observed a strong effect of the 616-659 amino acid region in condensate assembly in both wild-type cells (Additional file 1: Fig. S13a, b) and in Med15 knockdown cells (Add- itional file 1: Fig. S13c, d). Therefore, the mechanisms underlying nuclear condensate formation are likely con- served between mouse and human Med15 proteins. p p FRAP revealed that optodroplets formed by Med1 IDR or Med15 IDR rapidly recovered with t1/2 < 10 s, and about 80% recovery was reached at 60 s after photo- bleaching (Additional file 1: Fig. S14a, b, d), consistent with measurement on optodroplets formed by Med1 IDR in a previous study [13]. In contrast, only about 20% FRAP recovery was observed on optodroplets formed by Med15 C-terminal region at 60 s after photo- bleaching (Additional file 1: Fig. S14c, d). Thus, Med15 C-terminal domain appeared to drive phase separation more efficiently than Med15 IDR or Med1 IDR in the optodroplet assay and might provide a strong adhesive force for maintaining the Mediator condensates. We next sought to identify the motifs within this region that contribute to the formation of Med15 nuclear con- densates. We noticed that mouse Med15 (637-660) region contained eight hydrophobic amino acid residues (Fig. 5d), raising the possibility that hydrophobic interactions may in part mediate the formation of Med15 nuclear con- densates. Seven out of the eight hydrophobic amino acid residues are conserved in human Med15. DYRK3 overexpression disrupts Med1 nuclear foci and Med15 nuclear foci. To test this hy- pothesis, we mutated all eight hydrophobic amino acids in AcGFP-mMed15 to their hydrophilic mimics and found that the mutated protein formed visibly fewer nuclear foci than wild-type Med15 and that a lower fraction of cells showed Med15 foci (Fig. 5d, e). Taken together, although either the glutamine-rich IDR or the hydrophobic amino acid region (637-660) of Med15 was insufficient to form nuclear condensates, synergistic functions from both re- gions likely resulted in condensate formation. Testing the effects of Hexanediol treatment in transcriptional activation of immediate early genes (IEGs) during the serum response. Although recent studies have revealed phase separation phenomena of multiple key components of transcrip- tional machineries [6, 11, 15], roles of these nuclear con- densates in transcriptional regulation were less well understood. We explored the roles of nuclear Both IDR and C-terminal domain of Med15 contribute to phase separation in optodroplet assays Determining the capacity of Med15 IDR or Med15 C- terminal region (618-789) in promoting phase separation Page 10 of 17 Page 10 of 17 Shi et al. BMC Biology (2021) 19:245 Shi et al. BMC Biology Fig. 6 Med1 and Med15 regions induce the formation of optodroplets upon illumination by blue light. a–d Representative images during optodroplet activation in NIH3T3 cells expressing the following constructs: mCherrry-Cry2 (a), Med1(948-1157)-mCherry-Cry2 (b), NLS*-Med15(71-617)-mCherry-Cry2 (c), and Med15(618-789)-mCherry- Cry2 (d). t = 0 s indicates the starting point of blue light illumination. Time intervals between illuminating blue light and image acquisition are noted on each image. All scale bars are 5 μm. Similar results were obtained from three independent experiments. e Percentage of cells forming optodroplets after 30 s blue light stimulation at the same intensity. Numbers of cells observed were the following: mCherry-Cry2: 19; Med1(948-1157): 42; Med15(1-617): 18; Med15 (618-789): 26. * and *** indicates p < 0.05 and p < 0.001 in Fisher’s exact test, respectively We examined a few well-characterized IEGs (c-Fos, c- Jun, and Egr-1) in this study. NIH3T3 cells were ana- lyzed in two groups. In Group I, cells were serum starved for 24 h and treated with media containing 20% serum. In Group II, cells were serum starved for 24 h, treated with 0.5% or 10% Hexanediol diluted in serum starvation media for 1 min and then stimulated with media containing 20% serum but no Hexanediol. IEG expression at distinct time points was analyzed by RT- qPCR (Fig. 7a, Additional file 1: Fig. S17a). By immuno- staining, we found that Med1 and Med15 nuclear foci were both abolished after 1 min treatment with 10% Hexanediol and were restored to pre-treatment levels after 30 min serum induction (Additional file 1: Fig. S15). In a T24 cell line stably expressing GFP-Med15, Med15 foci were rapidly diminished upon 0.5% Hexane- diol treatment and restored upon serum induction/Hex- anediol withdrawal (Additional file 1: Fig. S16, Additional file 5: Video S4). We found that transcriptional activation of c-Fos, c- Jun, and Egr-1 genes was significantly delayed in cells pretreated with 10% Hexanediol but minimally affected in cells pretreated with 0.5% Hexanediol. Highest levels of IEG expression were found at about 30 min after serum induction in Group I cells but instead at 60 min or 120 min after serum induction in cells pretreated with 10% Hexanediol (Additional file 1: Fig. S17b-d). Both IDR and C-terminal domain of Med15 contribute to phase separation in optodroplet assays How- ever, disruption of Mediator condensates by 0.5% Hexa- nediol prior to serum induction (Additional file 1: Fig. S16, Additional file 5: Supplementary Video S4) did not result in a delay in IEG expression (Fig. 7b–d). Whether the presence of 0.5% Hexanediol during serum stimula- tion can affect IEG activation remains to be tested. Ideally, molecular reagents with improved specificity would help to better understand the functions of Medi- ator condensates in inducible gene expression. Fig. 6 Med1 and Med15 regions induce the formation of optodroplets upon illumination by blue light. a–d Representative images during optodroplet activation in NIH3T3 cells expressing the following constructs: mCherrry-Cry2 (a), Med1(948-1157)-mCherry-Cry2 (b), NLS*-Med15(71-617)-mCherry-Cry2 (c), and Med15(618-789)-mCherry- Cry2 (d). t = 0 s indicates the starting point of blue light illumination. Time intervals between illuminating blue light and image acquisition are noted on each image. All scale bars are 5 μm. Similar results were obtained from three independent experiments. e Percentage of cells forming optodroplets after 30 s blue light stimulation at the same intensity. Numbers of cells observed were the following: mCherry-Cry2: 19; Med1(948-1157): 42; Med15(1-617): 18; Med15 (618-789): 26. * and *** indicates p < 0.05 and p < 0.001 in Fisher’s exact test, respectively Fig. 6 Med1 and Med15 regions induce the formation of Fig. 6 Med1 and Med15 regions induce the formation of optodroplets upon illumination by blue light. a–d Representative images during optodroplet activation in NIH3T3 cells expressing the following constructs: mCherrry-Cry2 (a), Med1(948-1157)-mCherry-Cry2 (b), NLS*-Med15(71-617)-mCherry-Cry2 (c), and Med15(618-789)-mCherry- Cry2 (d). t = 0 s indicates the starting point of blue light illumination. Time intervals between illuminating blue light and image acquisition are noted on each image. All scale bars are 5 μm. Similar results were obtained from three independent experiments. e Percentage of cells forming optodroplets after 30 s blue light stimulation at the same intensity. Numbers of cells observed were the following: mCherry-Cry2: 19; Med1(948-1157): 42; Med15(1-617): 18; Med15 (618-789): 26. * and *** indicates p < 0.05 and p < 0.001 in Fisher’s exact test, respectively Importantly, Med15 knockdown attenuated IEG acti- vation. We found that expression of c-Fos and Egr-1 in Med15 knockdown cells after 30 min serum induction was 2–3 fold lower than wild-type U2OS cells (Add- itional file 1: Fig. S18a, c). Both IDR and C-terminal domain of Med15 contribute to phase separation in optodroplet assays Most substantial decrease in expression levels of all three IEGs upon Med15 knock- down was found at 60 min serum induction (Additional file 1: Fig. S18a-c). Thus, Med15 knockdown impairs the functions of the Mediator complex in regulating IEG ac- tivation upon serum induction. condensates during rapid gene activation by examining the effects of Hexanediol treatment and withdrawal on IEG expression during the serum response. IEGs re- spond very rapidly to a variety of cell-extrinsic and cell- intrinsic signals, including serum, growth factors, cyto- kines, and UV radiation [30, 31]. Given that Hexanediol treatment at high concentrations leads to inhibition of kinase and phosphatase activities [27], we compared the effects of 0.5% and 10% Hexanediol on IEG activation. Discussion 7 Testing the effects of Hexanediol treatment on IEG activation during serum response. a The experimental diagram. In Group I, NIH3T3 cells were serum starved for 24 h and then stimulated with growth media containing 20% serum. In Group II, cells were serum starved for 24 h, treated with 0.5% 1,6-Hexanediol for 1 min and then stimulated with media containing 20% serum but no Hexanediol. IEG expression was measured before adding serum (Group I), before and after Hexanediol treatment (Group II) and at distinct time points after adding 20% serum (Group I & II) by RT-qPCR. b–d Fold change of c-Fos (b), c-Jun (c), and Egr-1 (d) mRNA expression after serum stimulation in Group I cells (blue bars) and in 0.5% Hexanediol-treated cells (orange bars). Three experimental replicates were performed. In b–g, data are presented as mean ± SEM, and y-axes are plotted in log2 scale to facilitate comparison between time points. GAPDH mRNA expression was used for internal controls foci showed a rapid FRAP recovery (Fig. 3a, b). Like many nuclear organelles, Med1 foci and GFP-Med15 foci were dissolved in mitotic cells (Fig. 1b, c, Additional file 1: Fig. S3c, d) and presumably reassembled as cells exit mitosis. This was consistent with the notion that intracellular organelles were dissolved in mitosis by in- creased DYRK3 kinase activities and with the findings that DYRK3 overexpression dissolved some nuclear or- ganelles [9], Med1 foci and GFP-Med15 foci in inter- phase cells (Fig. 4, Additional file 1: Fig. S9). We also found that dissolution of GFP-Med15 foci was affected by the expression levels of TagRFP-NLS*-DYRK3 (Fig. 4d, Additional file 1: Fig. S10). Additional insights may be obtained by measuring subcellular concentrations of Mediator subunits and DYRK3. Our study revealed interesting new insights on nuclear condensate formation. The Q-rich IDR of Med15 was unable to form condensates when expressed in the nu- cleus alone, while a short hydrophobic motif was re- quired to assist in condensate assembly (Fig. 5). This finding was consistent with the notion that hydrophobic residues could serve as adhesive elements in phase- separating IDR and promote condensate formation [3]. Moreover, C-terminal region of Med15 could rapidly form optodroplets, which had a much slower FRAP re- covery compared with optodroplets formed by Med15 or Med1 IDRs (Additional file 1: Fig. S14a-d) and appeared as irregular shapes in some cases (Additional file 1: Fig. Discussion Our study revealed several common features of nuclear condensates formed by Med1 and Med15 (Fig. 8). Nu- clear condensates formed by Med1 and Med15 were dis- solved upon treatment with 1,6-Hexanediol and reassembled upon withdrawal (Fig. 2d, Additional file 1: Fig. S1, S5, S15, S16). Both Med1 foci [13] and Med15 Page 11 of 17 Shi et al. BMC Biology (2021) 19:245 Shi et al. BMC Biology Fig. 7 Testing the effects of Hexanediol treatment on IEG activation during serum response. a The experimental diagram. In Group I, NIH3T3 cells were serum starved for 24 h and then stimulated with growth media containing 20% serum. In Group II, cells were serum starved for 24 h, treated with 0.5% 1,6-Hexanediol for 1 min and then stimulated with media containing 20% serum but no Hexanediol. IEG expression was measured before adding serum (Group I), before and after Hexanediol treatment (Group II) and at distinct time points after adding 20% serum (Group I & II) by RT-qPCR. b–d Fold change of c-Fos (b), c-Jun (c), and Egr-1 (d) mRNA expression after serum stimulation in Group I cells (blue bars) and in 0.5% Hexanediol-treated cells (orange bars). Three experimental replicates were performed. In b–g, data are presented as mean ± SEM, and y-axes are plotted in log2 scale to facilitate comparison between time points. GAPDH mRNA expression was used for internal controls Fig. 7 Testing the effects of Hexanediol treatment on IEG activation during serum response. a The experimental diagram. In Group I, NIH3T3 cells were serum starved for 24 h and then stimulated with growth media containing 20% serum. In Group II, cells were serum starved for 24 h, treated with 0.5% 1,6-Hexanediol for 1 min and then stimulated with media containing 20% serum but no Hexanediol. IEG expression was measured before adding serum (Group I), before and after Hexanediol treatment (Group II) and at distinct time points after adding 20% serum (Group I & II) by RT-qPCR. b–d Fold change of c-Fos (b), c-Jun (c), and Egr-1 (d) mRNA expression after serum stimulation in Group I cells (blue bars) and in 0.5% Hexanediol-treated cells (orange bars). Three experimental replicates were performed. In b–g, data are presented as mean ± SEM, and y-axes are plotted in log2 scale to facilitate comparison between time points. GAPDH mRNA expression was used for internal controls Fig. Fig. 8 Characteristics of Med1 foci and Med15 foci. Formation of Med1 foci is mediated by the serine-rich IDR (blue circle). Formation by Med15 foci requires both the glutamine-rich IDR (green circle) and a short hydrophobic motif (orange dot). Shared and distinct features between Med1 foci and Med15 foci are described diagram that could transition from a fully mobile liquid- like state into a less mobile gel-like state [29]. like state into a less mobile gel like state [29]. Both Med1 and Med15 foci exhibited features shared by many biomolecular condensates, such as sensitivity to 1,6-Hexanediol and rapid FRAP recovery. Nonetheless, these are not definitive diagnostics that a cellular struc- ture was formed by LLPS [3]. As a thermodynamic principle, phase separation is exhibited by unmixing of components due to biomolecular interactions within two distinct phases that outweigh the increase in entropy by mixing the two phases and result in a lower free energy state [1]. Modulating interaction modules or protein concentrations clearly altered phase separation outcomes in vitro [32]. Consistent with these principles, interac- tions within the Mediator complex, between Mediator subunits, or between Mediator and TFs might lead to phase separation. Nonetheless, formation of Mediator condensates does not necessarily exclude affinity-based macromolecular assembly as an alternative explanation. It is of interest to note that DNA-mediated compartmentalization distinct from LLPS occurred dur- ing viral infection [33]. As recently discussed [34], the roles of LLPS vs other biochemical processes in nuclear condensate formation would need to be further studied. The tail module of the Mediator complex interacts with multiple transcription activators and participates in various signal-induced gene expression programs [16, 19]. As expected, Med15 knockdown by RNAi substan- tially reduced IEG activation during the serum response (Additional file 1: Fig. S18). Med15 knockdown reduced Med15 and Med1 protein levels (Additional file 1: Fig. S4a, c) and abolished both Med15 foci and Med1 foci (Additional file 1: Fig. S4a, b). Surprisingly, Med15 C- Both Med1 and Med15 foci exhibited features shared by many biomolecular condensates, such as sensitivity to 1,6-Hexanediol and rapid FRAP recovery. Nonetheless, these are not definitive diagnostics that a cellular struc- ture was formed by LLPS [3]. As a thermodynamic principle, phase separation is exhibited by unmixing of components due to biomolecular interactions within two distinct phases that outweigh the increase in entropy by mixing the two phases and result in a lower free energy state [1]. Modulating interaction modules or protein concentrations clearly altered phase separation outcomes in vitro [32]. Consistent with these principles, interac- tions within the Mediator complex, between Mediator subunits, or between Mediator and TFs might lead to phase separation. Nonetheless, formation of Mediator condensates does not necessarily exclude affinity-based macromolecular assembly as an alternative explanation. It is of interest to note that DNA-mediated compartmentalization distinct from LLPS occurred dur- ing viral infection [33]. As recently discussed [34], the roles of LLPS vs other biochemical processes in nuclear condensate formation would need to be further studied. Th il d l f h M di l i Methods The tail module of the Mediator complex interacts with multiple transcription activators and participates in various signal-induced gene expression programs [16, 19]. As expected, Med15 knockdown by RNAi substan- tially reduced IEG activation during the serum response (Additional file 1: Fig. S18). Med15 knockdown reduced Med15 and Med1 protein levels (Additional file 1: Fig. S4a, c) and abolished both Med15 foci and Med1 foci (Additional file 1: Fig. S4a, b). Surprisingly, Med15 C- Conclusions Understanding the formation, regulation and functions of nuclear condensates has become an exciting research field. We have revealed the Mediator complex subunit Med15 formed nuclear condensates in mammalian cells and characterized their features using multiple imaging- based approaches. Med15 condensates shared several features with Med1 condensates, such as sensitivity to Hexanediol, rapid FRAP recovery, and dissolution by DYRK3. Interestingly, the formation of Med15 conden- sates requires not only the glutamine-rich IDR but also a hydrophobic amino acid motif. Both IDR and C-terminal region of Med15 contributed to phase separation in the optodroplet assay. Our work has therefore reported mul- tiple novel features of Med15 nuclear condensates and identified a bipartite formation mechanism. Discussion S14e), suggesting that Med15 C-terminal domain could drive formation of condensates “deep” in the phase Page 12 of 17 Page 12 of 17 Page 12 of 17 Shi et al. BMC Biology (2021) 19:245 Shi et al. BMC Biology Fig. 8 Characteristics of Med1 foci and Med15 foci. Formation of Med1 foci is mediated by the serine-rich IDR (blue circle). Formation by Med15 foci requires both the glutamine-rich IDR (green circle) and a short hydrophobic motif (orange dot). Shared and distinct features between Med1 foci and Med15 foci are described terminal domain exhibited higher efficiency than Med15 IDR or Med1 IDR in promoting phase separation in the optodroplet assay (Fig. 6, Additional file 1: Fig. S14). Thus, Med15 exhibits several interesting features and might provide clues for better understanding the forma- tion and regulation of transcription coactivator conden- sates in mammalian cells. Formation of nuclear condensates provides potential explanations for interactions between Mediators and ac- tivation domains of multiple TFs [15] or between RNA Pol II C-terminal domain and splicing machineries [12]. These microenvironments formed within the cell nu- cleus were thought to facilitate cooperative interactions between transcription components and might enable rapid gene activation upon environmental signaling [35]. We explored the roles of Mediator condensates in rapid IEG activation by treating cells with Hexanediol prior to serum stimulation. The effects of Hexanediol on IEG ac- tivation during the serum response were concentration- dependent and could not be unambiguously associated with Mediator condensates (Fig. 7, Additional file 1: Fig. S17). For better understanding the roles of Mediator condensates in gene expression, it would be helpful to develop new perturbation approaches and to examine genomic regions closely associated with these condensates. Cell culture and transfection The next day, cells were washed three times with PBST for 30 min at room temperature and were then incubated with Alexa Fluor 488 goat anti-rabbit IgG(H+L) (Invitrogen, A11008) di- luted by 1:1000 in PBST with 2% BSA. Cells were then washed three times with PBST for 30 min at room temperature and stained with 1 μg/mL Hoechst33342 (Novon Scientific, China, SS0160) for 5 min at room temperature in the dark. Cells were mounted with Vectashield antifade mounting medium (VectorLabs, Burlingame, CA, USA) and slides were stored at a -20 °C freezer until image acquisition. Z-stack images were acquired at a Nikon Eclipse Ti2-E wide-field fluorescence microscope using a 60× oil-immersion objective (numerical aperture 1.4) and a DS-Qi2 CMOS camera. The Z-interval was 0.3–0.5 μm. A 1.5× magnifier lens was placed in the light path during imaging. Fisher, C11995500) supplemented with 10% newborn calf serum (NCS, Thermo Fisher, 16010-159) and 100 U/ml penicillin-streptomycin (Thermo Fisher, 15140- 122) at 37 °C with 5% CO2 in a humidified incubator. U2OS cells were cultured in low glucose Dulbecco’s modified Eagle’s medium (DMEM, Thermo Fisher, C11885500) supplemented with 10% fetal bovine serum (FBS, Hyclone), 1× GlutaMAX supplement (Thermo Fisher, 35050-061), 100 U/ml penicillin-streptomycin at 37 °C with 5% CO2 in a humidified incubator. T24 cells were cultured in RPMI-1640 medium (Gibco, C11875500BT) supplemented with 10% FBS (AusgeneX, FBSSA500-S) and 100 U/ml penicillin-streptomycin at 37 °C with 5% CO2 in a humidified incubator. HEK 293T cells were cultured in high-glucose DMEM (Gibco, C11995500BT) supplemented with 10% FBS (AusgeneX, FBSSA500-S). Transfection was performed using Lipo- fectamine 3000 Transfection Kit (Thermo Fisher, L3000- 015) following the manufacturer’s instructions. Molecular cloning Mouse Med15, human Med15, and human DYRK3 cDNA were amplified by RT-PCR from total RNA ex- tracted from NIH3T3 cells and U2OS cells, respectively. cDNAs were synthesized by RevertAid First Strand cDNA synthesis kit (Thermo Fisher, K1266) and ampli- fied by Phusion DNA polymerase (Thermo Fisher, F530L). Amplified Med15 full-length cDNA and trun- cated cDNA fragments were then digested by EcoRI and KpnI restriction enzymes and cloned into pAcGFP-C1 or pTagRFP-C vectors. DYRK3 cDNA was linked to the DNA sequence encoding SV40 nuclear localization sig- nal (CCGAAGAAGAAGCGAAAGGTC) at its N- Image and statistical analysis All images were post-processed using ImageJ (https:// imagej.net/Fiji). Changes in fluorescence intensities at Med15 nuclear foci during FRAP were measured by ImageJ. The numbers of nuclear foci per cell were gener- ated by the AirLocalize program in MATLAB (The Mathworks Inc., Natick, MA). For statistical analysis, Fisher’s exact test was performed using GraphPad Prism 9 (https://www.graphpad.com/quickcalcs/contingency1. cfm) and Student’s t test was performed using GraphPad Prism 7.0.4. p < 0.05 was considered to be statistically significant. Cell culture and transfection NIH3T3 cells and U2OS cells were obtained from Chin- ese Academy of Sciences, Kunming Cell Bank (www. kmcellbank.com). T24 (ATCC HTB-4) human urinary bladder cancer cells were kindly provided by Prof. Tie- bang Kang (Sun Yat-sen University Cancer Center). HEK 293 T cells were obtained from ATCC. NIH3T3 cells were cultured in high-glucose Dulbecco’s modified Eagle’s medium (DMEM, Thermo NIH3T3 cells were cultured in high-glucose Dulbecco’s modified Eagle’s medium (DMEM, Thermo Shi et al. BMC Biology (2021) 19:245 Shi et al. BMC Biology (2021) 19:245 Page 13 of 17 Page 13 of 17 PBS. Fixed cells were washed with 1× PBS, perme- abilized with 0.05% Triton X-100 in PBST (1× PBS + 0.05% Tween-20) for 10 min at room temperature, washed with 1× PBS again, and blocked with 2% BSA (Sigma, B2064) in PBST. Cells were then incubated with an anti-TRAP220/MED1 antibody (Abcam, ab64965) di- luted by 1:1000, an anti-GFP antibody (Cell Signaling Technology, 2956) diluted by 1:500, or an anti-PCQAP/ MED15 antibody (Abcam, ab181158) diluted by 1:75 in PBST with 2% BSA at 4 °C overnight. The next day, cells were washed three times with PBST for 30 min at room temperature and were then incubated with Alexa Fluor 488 goat anti-rabbit IgG(H+L) (Invitrogen, A11008) di- luted by 1:1000 in PBST with 2% BSA. Cells were then washed three times with PBST for 30 min at room temperature and stained with 1 μg/mL Hoechst33342 (Novon Scientific, China, SS0160) for 5 min at room temperature in the dark. Cells were mounted with Vectashield antifade mounting medium (VectorLabs, Burlingame, CA, USA) and slides were stored at a -20 °C freezer until image acquisition. Z-stack images were acquired at a Nikon Eclipse Ti2-E wide-field fluorescence microscope using a 60× oil-immersion objective (numerical aperture 1.4) and a DS-Qi2 CMOS camera. The Z-interval was 0.3–0.5 μm. A 1.5× magnifier lens was placed in the light path during imaging. PBS. Fixed cells were washed with 1× PBS, perme- abilized with 0.05% Triton X-100 in PBST (1× PBS + 0.05% Tween-20) for 10 min at room temperature, washed with 1× PBS again, and blocked with 2% BSA (Sigma, B2064) in PBST. Cells were then incubated with an anti-TRAP220/MED1 antibody (Abcam, ab64965) di- luted by 1:1000, an anti-GFP antibody (Cell Signaling Technology, 2956) diluted by 1:500, or an anti-PCQAP/ MED15 antibody (Abcam, ab181158) diluted by 1:75 in PBST with 2% BSA at 4 °C overnight. Western blot U2OS cells were lysed in cold lysis buffer (150 mM NaCl, 1% NP-40, 0.5% Sodium deoxycholate, 0.1% SDS, 25 mM Tris, and 1 mM PMSF). Cell lysates were then prepared by a sonicator (Fisher Scientific, FB120) at 35% power for 1 min and cleared by centrifugation at 12,000g for 20 min. 1/4 volume of SDS-PAGE loading buffer was added to the supernatant and boiled for 10 min in a dry thermostat. Cell lysates were separated on an 8% poly- acrylamide gel by SDS-PAGE and transferred to a nitro- cellulose membrane. The membrane was then blocked with 5% non-fat milk and incubated with an anti- TRAP220/MED1 antibody (Abcam, ab64965) at 1:1000 dilution or an anti-PCQAP/Med15 antibody (Abcam, ab181158) at 1:1500 dilution overnight at 4 °C. The membrane was then incubated with a goat anti-rabbit IgG (H + L) horseradish peroxidase secondary antibody (Invitrogen, A16110) diluted by 1:10,000 in 1× PBST with 5% non-fat milk at room temperature for 1 h. Chemiluminescence signals were detected by Super- Signal West Pico PLUS Chemiluminescent Substrate (Thermo Fisher, 34577) and visualized on a Tanon-5200 Chemiluminescence Imaging System (Tanon Science and Technology, Shanghai, China). Original western blot images are provided in Additional file 1: Fig. S19. Immunofluorescence staining NIH3T3 and U2OS cells were cultured as described above. Prior to immunostaining experiments, cells were plated on Lab-Tek CC2 chamber slides (Thermo Fisher, 154852) at approximately 50% confluency. 12–20 h after plating or after transfection, cells were subject to treat- ment and fixed for 15 min at room temperature using 4% paraformaldehyde (Thermo Fisher, 28908) in 1× Page 14 of 17 Shi et al. BMC Biology (2021) 19:245 Shi et al. BMC Biology (2021) 19:245 GGGUGUUGUUAGAGCGUCU–3′, 5′–GGUCAGU- CAAAUCGAGGAU–3′, and 5′–CCGGACAAGCA- CUCGGUCA–3′. A non-targeting scrambled siRNA was used as the negative control: 5′–UUCUCCGAACGU- GUCACGUTT–3′. terminus and cloned into pAcGFP-C1, pTagRFP-C, or pmCherry-C1 using EcoRI and BamHI restriction en- zymes. The IDR region (amino acid 948-1568) of mouse Med1 cDNA was amplified by RT-PCR and inserted into pAcGFP-C1 vector using EcoRI and ApaI restriction en- zymes. Cry2 cDNA was synthesized by Genscript (Nan- jing, China). mCherry-Cry2 and Med1(948-1157)-mCherry- Cry2 optodroplet constructs were generated by PCR of Cry2 cDNA and cloning into mCherry-C1 vector. NLS*- Med15(71-617)-mCherry-Cry2 and Med15(618-789)- mCherry-Cry2 optodroplet constructs were generated with ClonExpress MultiS One Step Cloning Kit (Vazyme Biotech, C113) according to the manufacturer’s instruc- tions. Primers used to clone each cDNA and mutants are provided in Additional file 6: Table S1, S2. terminus and cloned into pAcGFP-C1, pTagRFP-C, or pmCherry-C1 using EcoRI and BamHI restriction en- zymes. The IDR region (amino acid 948-1568) of mouse Med1 cDNA was amplified by RT-PCR and inserted into pAcGFP-C1 vector using EcoRI and ApaI restriction en- zymes. Cry2 cDNA was synthesized by Genscript (Nan- jing, China). mCherry-Cry2 and Med1(948-1157)-mCherry- Cry2 optodroplet constructs were generated by PCR of Cry2 cDNA and cloning into mCherry-C1 vector. NLS*- Med15(71-617)-mCherry-Cry2 and Med15(618-789)- mCherry-Cry2 optodroplet constructs were generated with ClonExpress MultiS One Step Cloning Kit (Vazyme Biotech, C113) according to the manufacturer’s instruc- tions. Primers used to clone each cDNA and mutants are provided in Additional file 6: Table S1, S2. Lentivirus production and stable cell line generation Lentivirus production and stable cell line generation GFP-human Med15 and TagRFP-human DYRK3 fusion protein were subcloned into the lentiviral expression vector pSin-EF2 [36] by ClonExpress II One Step Clon- ing Kit (Vazyme Biotech, C112). Primers used to clone lentiviral vectors are provided in Additional file 6: Table S3. The human embryonic kidney 293T cell line was used as a host for virus packaging. The recombinant plasmid pSin-EF2-GFP-hMed15 or pSin-EF2-TagRFP- NLS*-DYRK3 was mixed with psPAX2 and pMD2.G plasmids (at a mass ratio of 3: 2: 1) and co-transfected into HEK 293T cells at 50–60% confluency in a 6-well plate using Lipofectamine 3000 Transfection Kit follow- ing the manufacturer’s instructions. Lentivirus was har- vested 48 h post-transfection and used to transduce T24 cells. Then, 48 h after transduction, T24 cells were se- lected with RPMI-1640 medium containing 10% fetal bovine serum and 0.5 μg/mL puromycin (InvivoGen, ant-pr-1) for 2 weeks. Hexanediol treatment and withdrawal We prepared a stock solution of 30% 1, 6-Hexanediol dissolved in ultrapure water and filtrated with 0.22 μm microporous membrane. For immunofluorescence stain- ing, the old culture medium was first removed, and cells were washed three times with 1× PBS. We then carefully added 10% Hexanediol (diluted with the old culture media) along the side wall of the dish and immediately placed in a 37 °C incubator for 1 min. Finally, Hexanediol-containing medium was replaced with nor- mal growth medium after gently washing the cells twice with 1× PBS and once with culture medium. Cells were fixed at each described time point and processed for im- munostaining. For live cell imaging of Med15 foci, the culture medium was replaced with growth medium con- taining 0.5% Hexanediol by a custom-made injection de- vice after acquiring baseline images for about 5 min. Cells were then imaged in 0.5% Hexanediol for about 10 min. Hexanediol-containing medium was replaced by normal growth medium and image acquisition was con- tinued until Med15 foci visibly recovered. Time interval between each frame was 10 s and the exposure time was 200 ms. All images were analyzed with ImageJ. Live cell imaging For all live cell imaging experiments, cells were plated onto 35 mm glass bottom dishes (Cellvis, D35-20-1-N). Time-lapse images of each GFP- or TagRFP-fusion pro- tein in NIH3T3 cells were acquired using a Nikon Eclipse Ti2-E Inverted Microscope equipped with a stage top incubator (Tokai Hit model STX) at 37 °C, 5% CO2, and humidity control. All live cell images were acquired with a 60× oil-immersion objective (CFI Plan Apochro- mat Lambda, numerical aperture 1.4) while using the TI2-N-ND-P perfect focus unit (Nikon) to maintain image focus during acquisition. A 1.5× magnifier lens was placed in the light path to obtain the pixel size of 81.4 nm. A 32× neutral density filter was applied after the fluorescence mercury lamp (C-HGFI, Nikon) to at- tenuate the excitation light. GFP or mCherry/TagRFP fluorescence was collected through a C-FL-C FITC filter cube (MBE44725, Nikon) or a C-FL-C Texas Red filter cube (MBE46105, Nikon), respectively. The 8-amino acid point mutant of mouse Med15 was generated by Phusion Site-Directed Mutagenesis Kit (Thermo Fisher, F541) following the manufacturer’s in- structions. Multiple rounds of mutagenesis were per- formed to obtain the Med15 mutant with 8 hydrophobic amino acids mutated to hydrophilic ones (Fig. 5d). The resulting colonies were then screened by sequencing to identify the correct mutants. RNAi Small interfering RNA (siRNA) sequences targeting hu- man Med15 were designed and synthesized by Gene- pharma Company (Shanghai, china). To obtain a transient Med15 knockdown, U2OS cells were trans- fected with 200 nmol/L siRNA targeting Med15 for 72 hours using Lipofectamine 3000 Transfection Kit follow- ing the manufacturer’s instructions. Sequences for hu- man Med15 siRNA pool were as follows: 5′– CCAAGA CCCGGGACGAAUA–3′, 5′– Fluorescence recovery after photobleaching (FRAP) Fluorescence recovery after photobleaching (FRAP) NIH3T3 cells were plated on 35 mm glass bottom dishes and transfected with GFP-Med15 or TagRFP-Med15 plasmid for 24 h before imaging. Next, FRAP was Shi et al. BMC Biology (2021) 19:245 Page 15 of 17 Page 15 of 17 performed at a Leica SP8 STED confocal microscope with a 93× glycerol-immersion objective (numerical aperture 1.3). Cells were maintained at 37 °C and 5% CO2 in a humidified stage top incubator during experi- ment. Five iterations of bleaching were performed with a 488 nm laser or a 561 nm laser at 100% laser power and images were collected every 655 ms. Two and four im- ages were acquired before bleaching for GFP-Med15 and TagRFP-Med15, respectively. Forty images were ac- quired after bleaching, and the time intervals for the first 20 cycles and the last 20 cycles were 655 ms and 5 s, re- spectively. Imaging settings were as follows: 8-bit image depth, × 4 zoom (122.55 nm pixel size), 256 × 256 frame size. Fluorescence intensities at the bleached locus (IL), unbleached nuclear area (IN) and at area without cells (IB) were measured at each time point using ImageJ. Pre-bleaching fluorescence intensities at the locus IL(pre), unbleached area IN(pre), and area without cells IB(pre) were determined by averaging first two image frames. Normalized fluorescence intensities of Med15 foci during FRAP were determined using the following equation: formation. Before activation, we took images at the TxRed channel at 10 s intervals for 2 min. We then switched to the GFP channel and illuminated cells with blue light for 30 s, 60 s, and 90 s or 2 s, 5 s, and 10 s, as indicated in Fig. 6. After each noted duration of illumin- ation, we acquired images of mCherry-fusion proteins in the TxRed channel. FRAP of optodroplets was performed at an Olympus FV3000 confocal microscope with a 100× oil-immersion objective. Med1(948-1157)-mCherry-Cry2 and NLS*- Med15(71-617)-mCherry-Cry2 optodroplets were induced with blue light for 2 min, while Med15(618-789)-mCherry- Cry2 optodroplets were induced with blue light for 30 s. Optodroplets were photobleached with a 561 nm laser at 3% laser power for 1 s and post-bleach images were acquired at 3.22 s intervals for 30–40 cycles in the ab- sence of 488 nm laser stimulation. Imaging settings were as follows: 12-bit image depth, 1024 × 1024 frame size. Abbreviations FRAP: Fluorescence recovery after photobleaching; IDR: Intrinsically disordered region; IEG: Immediate early genes; LLPS: Liquid-liquid phase separation; NLS: Nuclear localization signal; Pol II: RNA polymerase II; TF: Transcription factor Fluorescence recovery after photobleaching (FRAP) Gene expression analysis of IEGs during serum starvation NIH3T3 cells under serum starvation were obtained by replacing the normal culture medium with DMEM medium containing 0.2% NCS and culturing for 24 h. Serum-starved cells were treated with 10% or 0.5% 1, 6- Hexanediol diluted in the starvation media for 1 min. Serum-starved cells with or without Hexanediol treat- ment were stimulated with DMEM medium containing 20% NCS for 15 min, 30 min, 60 min and 120 min. For Med15 knockdown experiment, U2OS cells were plated on 6-well plates at a density of 1 × 105 cells/well and transfected with 200 nmol/L control siRNA or Med15 siRNA for 48 h. Transfected cells were incubated in growth medium containing 0.2% FBS and cultured for 24 h, and then stimulated with growth medium contain- ing 20% FBS for 30 min or 60 min. F tð Þ ¼ IL tð Þ−IB tð Þ ½ =IL pre ð Þ−IB pre ð Þ IN tð Þ−IB tð Þ ½ = IN pre ð Þ−IB pre ð Þ ½  F tð Þ ¼ ð Þ ð Þ ½ = p ð Þ p ð Þ IN tð Þ−IB tð Þ ½ = IN pre ð Þ−IB pre ð Þ ½  F tð Þ ¼ IN tð Þ−IB tð Þ ½ = IN pre ð Þ−IB pre ð Þ ½  F(t) was measured from multiple cells in each FRAP experiment, and comparable results were obtained from three independent experiments. F(t) was measured from multiple cells in each FRAP experiment, and comparable results were obtained from three independent experiments. Optodroplet assay y NIH3T3 cells were grown on 35 mm glass bottom dishes and transfected with mCherry-Cry2, Med1(948-1157)-mCherry-Cry2, NLS*-Med15(71-617)- mCherry-Cry2, and Med15(618-789)-mCherry-Cry2 plas- mid for 24 h using Lipofectamine 3000 Transfection Kit. Live cell imaging was performed as described above with the following modifications. Cells were illuminated in the GFP channel for Cry2 activation by blue light and imaged in the TxRed channel to monitor optodroplet Cell synchronization and DYRK3 inhibition Cell synchronization and DYRK3 inhibition U2OS cells growing at log phase were plated at ap- proximately 30% confluency. 16 h after plating, Thy- midine was added at a final concentration of 2 mM to block the cell cycle for 24 h. Cells were then washed three times with pre-warmed 1× PBS and were re- placed with complete growth medium to release the block. After 4 h, Nocodazole (dissolved in DMSO) was added at a final concentration of 25 ng/mL to the medium and cells were incubated for 12 h. 1 μM GSK626616 (dissolved in DMSO) was added to the media at 6 h after starting the Nocodazole block and incubation was continued for 6 h. Total RNA was collected from about 5 × 106 cells at each time point using the ReliaPrep RNA Miniprep Sys- tem (Promega, Z6011). RNA was reverse transcribed using RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher, K1622) following the manufacturer’s in- structions. Quantitative real-time PCR was performed using SYBR Green master mix. Glyceraldehyde-3- phosphate dehydrogenase (GAPDH) mRNA was used as an internal control and IEG expression was measured before serum induction and at 15 min, 30 min, 60 min, and 120 min after serum induction. Primer sequences used for real-time PCR are described in Additional file 6: Table S4. References 1 H Additional file 2: Video S1. Time lapse images of a cell from T24 stable cell line expressing GFP-hMed15 that was treated with 0.5% 1,6- Hexanediol and upon Hexanediol withdrawal. Images were taken every 10 s. Time points on the video are in mm:ss format. 0.5% Hexanediol was added at 3:40 and was replaced with fresh growth media at 12:40. References 1. Hyman AA, Weber CA, Julicher F. Liquid-liquid phase separation in biology. Annu Rev Cell Dev Biol. 2014;30(1):39–58. https://doi.org/10.1146/annurev- cellbio-100913-013325. 2. Gomes E, Shorter J. The molecular language of membraneless organelles. J Biol Chem. 2019;294(18):7115–27. https://doi.org/10.1074/jbc.TM118.001192. 2. Gomes E, Shorter J. The molecular language of membraneless organelles. J Biol Chem. 2019;294(18):7115–27. https://doi.org/10.1074/jbc.TM118.001192. Additional file 3: Video S2. Time lapse images of a T24 cell transfected with GFP-Med15 in which Med15 foci were observed to undergo fusion events. Images were taken every 10 s. Time points on the video are in mm:ss format. 3. Alberti S, Gladfelter A, Mittag T. Considerations and challenges in studying liquid-liquid phase separation and biomolecular condensates. Cell. 2019; 176(3):419–34. https://doi.org/10.1016/j.cell.2018.12.035. 4. Banani SF, Lee HO, Hyman AA, Rosen MK. Biomolecular condensates: organizers of cellular biochemistry. Nat Rev Mol Cell Biol. 2017;18(5):285–98. https://doi.org/10.1038/nrm.2017.7. 4. Banani SF, Lee HO, Hyman AA, Rosen MK. Biomolecular condensates: organizers of cellular biochemistry. Nat Rev Mol Cell Biol. 2017;18(5):285–98. https://doi.org/10.1038/nrm.2017.7. Additional file 4: Video S3. Time lapse images of a T24 cell transfected with GFP-Med15 in which Med15 foci were observed to undergo fission events. Images were taken every 10 s. Time points on the video are in mm:ss format. 5. Shin Y, Brangwynne CP. Liquid phase condensation in cell physiology and disease. Science. 2017;357(6357):eaaf4382. https://doi.org/10.1126/science.aa f4382 5. Shin Y, Brangwynne CP. Liquid phase condensation in cell physiology and disease. Science. 2017;357(6357):eaaf4382. https://doi.org/10.1126/science.aa f4382 Additional file 5: Video S4. Time lapse images of a cell from T24 stable cell line expressing GFP-hMed15 that was treated with 0.5% 1,6- Hexanediol followed by 20% serum stimulation. Images were taken every 10 s. Time points on the video are in mm:ss format. 0.5% Hexanediol was added at 4:00 and was replaced with growth media containing 20% serum at 16:10. 6. Chong S, Dugast-Darzacq C, Liu Z, Dong P, Dailey GM, Cattoglio C, et al. Imaging dynamic and selective low-complexity domain interactions that control gene transcription. Science. 2018;361(6400):eaar2555. https://doi. org/10.1126/science.aar2555 6. Chong S, Dugast-Darzacq C, Liu Z, Dong P, Dailey GM, Cattoglio C, et al. Availability of data and materials Additional file 1: Fig. S1-S19. Fig. S1 Med1 nuclear foci were disrupted by Hexanediol treatment and restored upon withdrawal. Fig. S2 Characterization of Med15 nuclear foci. Fig. S3 Med15 foci in mitotic cells. Fig. S4 Response of Med1 and Med15 nuclear foci to Med15 deple- tion. Fig. S5 Time lapse images of a T24 cell stably expressing GFP- hMed15 upon Hexanediol treatment and withdrawal. Fig. S6 Dynamics of TagRFP-Med15 at nuclear foci in living cells. Fig. S7 Time lapse images of GFP-hMed15 foci undergoing fusion and fission events. Fig. S8 DYRK3 inhibition restores Med1 foci in some mitotic cells. Fig. S9 Effects of DYRK3 overexpression on Med1 nuclear foci in NIH3T3 cells. Fig. S10 Ex- pression levels of TagRFP-DYRK3 affect the dissolution of GFP-Med15 foci. Fig. S11 Displacement of overexpressed Med1 IDR from nucleolar re- gions upon expressing DYRK3. Fig. S12 Representative images of NIH3T3 cells displaying nuclear foci formed by Med15 mutants. Fig. S13 Forma- tion of nuclear condensates by human Med15 truncation mutants in U2OS cells. Fig. S14 Dynamics of optodroplets formed by Med1 and Med15 regions. Fig. S15 Response of Med1 and Med15 nuclear foci to 10% Hexanediol treatment and withdrawal in the serum response experi- ment. Fig. S16 Time lapse images of serum-starved T24 cells stably ex- pressing GFP-hMed15 upon 0.5% Hexanediol treatment followed by 20% serum stimulation without Hexanediol. Fig. S17 Effects of 10% Hexane- diol treatment on IEG activation during serum response. Fig. S18 Effects of Med15 knockdown on IEG activation during serum response in U2OS cells. Fig. S19 Original western blot images. All data analyzed in this study are included in this article and additional files. All data analyzed in this study are included in this article and additional files Supplementary Information S6 Dynamics of TagRFP-Med15 at nuclear foci in living cells. Fig. S7 Time lapse images of GFP-hMed15 foci undergoing fusion and fission events. Fig. S8 DYRK3 inhibition restores Med1 foci in some mitotic cells. Fig. S9 Effects of DYRK3 overexpression on Med1 nuclear foci in NIH3T3 cells. Fig. S10 Ex- pression levels of TagRFP-DYRK3 affect the dissolution of GFP-Med15 foci. Fig. S11 Displacement of overexpressed Med1 IDR from nucleolar re- gions upon expressing DYRK3. Fig. S12 Representative images of NIH3T3 cells displaying nuclear foci formed by Med15 mutants. Fig. S13 Forma- tion of nuclear condensates by human Med15 truncation mutants in U2OS cells. Fig. S14 Dynamics of optodroplets formed by Med1 and Med15 regions. Fig. S15 Response of Med1 and Med15 nuclear foci to 10% Hexanediol treatment and withdrawal in the serum response experi- ment. Fig. S16 Time lapse images of serum-starved T24 cells stably ex- pressing GFP-hMed15 upon 0.5% Hexanediol treatment followed by 20% serum stimulation without Hexanediol. Fig. S17 Effects of 10% Hexane- diol treatment on IEG activation during serum response. Fig. S18 Effects of Med15 knockdown on IEG activation during serum response in U2OS cells. Fig. S19 Original western blot images. Abbreviations FRAP Fl Page 16 of 17 Page 16 of 17 Page 16 of 17 Shi et al. BMC Biology (2021) 19:245 Shi et al. BMC Biology Acknowledgements We thank Prof. Tiebang Kang for providing the T24 cell line and pSin-EF2 len- tiviral expression vector, Prof. Robert Singer and Prof. Timothee Lionnet for sharing the AirLocalize program. We thank Olympus (Beijing) CO., LTD. Guangzhou Branch for help with FRAP experiments. 10. Hnisz D, Shrinivas K, Young RA, Chakraborty AK, Sharp PA. A phase separation model for transcriptional control. Cell. 2017;169(1):13–23. https:// doi.org/10.1016/j.cell.2017.02.007. 11. Lu H, Yu D, Hansen AS, Ganguly S, Liu R, Heckert A, et al. Phase-separation mechanism for C-terminal hyperphosphorylation of RNA polymerase II. Nature. 2018;558(7709):318–23. https://doi.org/10.1038/s41586-018-0174-3. References 1 H Imaging dynamic and selective low-complexity domain interactions that control gene transcription. Science. 2018;361(6400):eaar2555. https://doi. org/10.1126/science.aar2555 7. Kato M, Han TW, Xie S, Shi K, Du X, Wu LC, et al. Cell-free formation of RNA granules: low complexity sequence domains form dynamic fibers within hydrogels. Cell. 2012;149(4):753–67. https://doi.org/10.1016/j.cell.2012.04.017. 7. Kato M, Han TW, Xie S, Shi K, Du X, Wu LC, et al. Cell-free formation of RNA granules: low complexity sequence domains form dynamic fibers within hydrogels. Cell. 2012;149(4):753–67. https://doi.org/10.1016/j.cell.2012.04.017. Additional file 6: Table S1-S4.Table S1 Primer sequences used to clone cDNA and mouse Med15 truncation mutants. Table S2 Primer sequences used to clone human Med15 and truncation mutants Table Additional file 6: Table S1-S4.Table S1 Primer sequences used to clone cDNA and mouse Med15 truncation mutants. Table S2 Primer sequences used to clone human Med15 and truncation mutants. Table S3 Primer sequences used to clone the lentiviral vectors. Table S4 Primer sequences used for real-time PCR. Additional file 6: Table S1-S4.Table S1 Primer sequences used to clone cDNA and mouse Med15 truncation mutants. Table S2 Primer sequences used to clone human Med15 and truncation mutants Table 8. Lin Y, Currie SL, Rosen MK. Intrinsically disordered sequences enable modulation of protein phase separation through distributed tyrosine motifs. J Biol Chem. 2017;292(46):19110–20. https://doi.org/10.1074/jbc.M117.8004 66. 8. Lin Y, Currie SL, Rosen MK. Intrinsically disordered sequences enable modulation of protein phase separation through distributed tyrosine motifs. J Biol Chem. 2017;292(46):19110–20. https://doi.org/10.1074/jbc.M117.8004 66. sequences used to clone human Med15 and truncation mutants. Table S3 Primer sequences used to clone the lentiviral vectors. Table S4 Primer sequences used for real-time PCR. sequences used to clone human Med15 and truncation mutants. Table S3 Primer sequences used to clone the lentiviral vectors. Table S4 Primer sequences used for real-time PCR. Primer sequences used for real-time PCR. 9. Rai AK, Chen JX, Selbach M, Pelkmans L. Kinase-controlled phase transition of membraneless organelles in mitosis. Nature. 2018;559(7713):211–6. https://doi.org/10.1038/s41586-018-0279-8. Authors’ contributions l Conceptualization: JY; Methodology: YS, JC, WZ1, ML; Formal analysis and investigation: YS, XZ, JY; Writing—original draft preparation: YS, JY; Writing—review and editing: YS, WZ2, XZ, JY; Funding acquisition: ML, XZ, JY; Supervision: XZ, JY. All authors read and approved the final manuscript. Conceptualization: JY; Methodology: YS, JC, WZ1, ML; Formal analysis and investigation: YS, XZ, JY; Writing—original draft preparation: YS, JY; Writing—review and editing: YS, WZ2, XZ, JY; Funding acquisition: ML, XZ, JY; Supervision: XZ, JY. All authors read and approved the final manuscript. 12. Guo YE, Manteiga JC, Henninger JE, Sabari BR, Dall'Agnese A, Hannett NM, et al. Pol II phosphorylation regulates a switch between transcriptional and splicing condensates. Nature. 2019;572(7770):543–8. https://doi.org/10.1038/ s41586-019-1464-0. 13. Sabari BR, Dall'Agnese A, Boija A, Klein IA, Coffey EL, Shrinivas K, et al. Coactivator condensation at super-enhancers links phase separation and gene control. Science. 2018;361(6400):eaar3958. https://doi.org/10.1126/ science.aar3958. 13. Sabari BR, Dall'Agnese A, Boija A, Klein IA, Coffey EL, Shrinivas K, et al. Coactivator condensation at super-enhancers links phase separation and gene control. Science. 2018;361(6400):eaar3958. https://doi.org/10.1126/ science.aar3958. Author details 1 1Molecular Cancer Research Center, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, China. 2Present Address: Allen Institute for Cell Science, Seattle, WA 98109, USA. p p ment. Fig. S16 Time lapse images of serum-starved T24 cells stably ex- pressing GFP-hMed15 upon 0.5% Hexanediol treatment followed by 20% serum stimulation without Hexanediol. Fig. S17 Effects of 10% Hexane- diol treatment on IEG activation during serum response. Fig. S18 Effects of Med15 knockdown on IEG activation during serum response in U2OS cells. Fig. S19 Original western blot images. Received: 17 May 2021 Accepted: 28 October 2021 Consent for publication Not applicable Consent for publication Not applicable Supplementary Information to XZ), and grants from Shenzhen Science and Technology Innovation Com- mission, China (JCYJ20190807160209294 to XZ, JCYJ20190807160813467 to ML). to XZ), and grants from Shenzhen Science and Technology Innovation Com- mission, China (JCYJ20190807160209294 to XZ, JCYJ20190807160813467 to ML). The online version contains supplementary material available at https://doi. org/10.1186/s12915-021-01178-y. The online version contains supplementary material available at https://doi. org/10.1186/s12915-021-01178-y. The online version contains supplementary material available at https://doi. org/10.1186/s12915-021-01178-y. Additional file 1: Fig. S1-S19. Fig. S1 Med1 nuclear foci were disrupted by Hexanediol treatment and restored upon withdrawal. Fig. S2 Characterization of Med15 nuclear foci. Fig. S3 Med15 foci in mitotic cells. Fig. S4 Response of Med1 and Med15 nuclear foci to Med15 deple- tion. Fig. S5 Time lapse images of a T24 cell stably expressing GFP- hMed15 upon Hexanediol treatment and withdrawal. Fig. S6 Dynamics of TagRFP-Med15 at nuclear foci in living cells. Fig. S7 Time lapse images of GFP-hMed15 foci undergoing fusion and fission events. Fig. S8 DYRK3 inhibition restores Med1 foci in some mitotic cells. Fig. S9 Effects of DYRK3 overexpression on Med1 nuclear foci in NIH3T3 cells. Fig. S10 Ex- pression levels of TagRFP-DYRK3 affect the dissolution of GFP-Med15 foci. Fig. S11 Displacement of overexpressed Med1 IDR from nucleolar re- gions upon expressing DYRK3. Fig. S12 Representative images of NIH3T3 cells displaying nuclear foci formed by Med15 mutants. Fig. S13 Forma- tion of nuclear condensates by human Med15 truncation mutants in U2OS cells. Fig. S14 Dynamics of optodroplets formed by Med1 and Med15 regions. Fig. S15 Response of Med1 and Med15 nuclear foci to 10% Hexanediol treatment and withdrawal in the serum response experi- ment. Fig. S16 Time lapse images of serum-starved T24 cells stably ex- pressing GFP-hMed15 upon 0.5% Hexanediol treatment followed by 20% serum stimulation without Hexanediol. Fig. S17 Effects of 10% Hexane- diol treatment on IEG activation during serum response. Fig. S18 Effects of Med15 knockdown on IEG activation during serum response in U2OS cells. Fig. S19 Original western blot images. Additional file 1: Fig. S1-S19. Fig. S1 Med1 nuclear foci were disrupted by Hexanediol treatment and restored upon withdrawal. Fig. S2 Characterization of Med15 nuclear foci. Fig. S3 Med15 foci in mitotic cells. Fig. S4 Response of Med1 and Med15 nuclear foci to Med15 deple- tion. Fig. S5 Time lapse images of a T24 cell stably expressing GFP- hMed15 upon Hexanediol treatment and withdrawal. Fig. Declarations Ethics approval and consent to participate Not applicable Ethics approval and consent to participate Not applicable Funding Thi k This work was supported by Hundred Talent Plan of Sun Yat-sen University (to JY), a grant from National Natural Science Foundation of China (32170789 Page 17 of 17 Page 17 of 17 Shi et al. BMC Biology (2021) 19:245 Shi et al. BMC Biology (2021) 19:245 Publisher’s Note 14. Cho WK, Spille JH, Hecht M, Lee C, Li C, Grube V, et al. Mediator and RNA polymerase II clusters associate in transcription-dependent condensates. Science. 2018;361(6400):412–5. https://doi.org/10.1126/science.aar4199. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 15. Boija A, Klein IA, Sabari BR, Dall'Agnese A, Coffey EL, Zamudio AV, et al. Transcription factors activate genes through the phase-separation capacity of their activation domains. Cell. 2018;175(7):1842–55 e1816. https://doi. org/10.1016/j.cell.2018.10.042. 16. Soutourina J. Transcription regulation by the Mediator complex. Nat Rev Mol Cell Biol. 2018;19(4):262–74. https://doi.org/10.1038/nrm.2017.115. 16. Soutourina J. Transcription regulation by the Mediator complex. Nat Rev Mol Cell Biol. 2018;19(4):262–74. https://doi.org/10.1038/nrm.2017.115. 17. Harper TM, Taatjes DJ. The complex structure and function of Mediator. J Biol Chem. 2018;293(36):13778–85. https://doi.org/10.1074/jbc.R117.794438. 17. Harper TM, Taatjes DJ. The complex structure and function of Mediator. J Biol Chem. 2018;293(36):13778–85. https://doi.org/10.1074/jbc.R117.794438. 18. Yang F, Vought BW, Satterlee JS, Walker AK, Jim Sun ZY, Watts JL, et al. An ARC/ Mediator subunit required for SREBP control of cholesterol and lipid homeostasis. Nature. 2006;442(7103):700–4. https://doi.org/10.1038/nature04942. 18. Yang F, Vought BW, Satterlee JS, Walker AK, Jim Sun ZY, Watts JL, et al. An ARC/ Mediator subunit required for SREBP control of cholesterol and lipid homeostasis Nature. 2006;442(7103):700–4. https://doi.org/10.1038/nature04942. p g 19. Cooper DG, Fassler JS. Med15: glutamine-rich mediator subunit with potential for plasticity. Trends Biochem Sci. 2019;44(9):737–51. https://doi. org/10.1016/j.tibs.2019.03.008. 19. Cooper DG, Fassler JS. Med15: glutamine-rich mediator subunit with potential for plasticity. Trends Biochem Sci. 2019;44(9):737–51. https://doi. org/10.1016/j.tibs.2019.03.008. 20. Tuttle LM, Pacheco D, Warfield L, Luo J, Ranish J, Hahn S, et al. Gcn4- mediator specificity is mediated by a large and dynamic fuzzy protein- protein complex. Cell Rep. 2018;22(12):3251–64. https://doi.org/10.1016/j. celrep.2018.02.097. 21. Zhu X, Chen L, Carlsten JO, Liu Q, Yang J, Liu B, et al. Mediator tail subunits can form amyloid-like aggregates in vivo and affect stress response in yeast. Nucleic Acids Res. 2015;43(15):7306–14. https://doi.org/10.1093/nar/gkv629. 22. Lionnet T, Czaplinski K, Darzacq X, Shav-Tal Y, Wells AL, Chao JA, et al. A transgenic mouse for in vivo detection of endogenous labeled mRNA. Nat Methods. 2011;8(2):165–70. https://doi.org/10.1038/nmeth.1551. 23. Spector DL, Fu XD, Maniatis T. Associations between distinct pre-mRNA splicing components and the cell nucleus. EMBO J. 1991;10(11):3467–81. https://doi.org/10.1002/j.1460-2075.1991.tb04911.x. 24. Nizami Z, Deryusheva S, Gall JG. The Cajal body and histone locus body. Cold Spring Harb Perspect Biol. 2010;2(7):a000653. Publisher’s Note https://doi.org/10.1101/ cshperspect.a000653. 24. Nizami Z, Deryusheva S, Gall JG. The Cajal body and histone locus body. Cold Spring Harb Perspect Biol. 2010;2(7):a000653. https://doi.org/10.1101/ cshperspect.a000653. 25. Hernandez-Verdun D. Assembly and disassembly of the nucleolus during the cell cycle. Nucleus. 2011;2(3):189–94. https://doi.org/10.4161/nucl.2.3.16246. 26. Nagulapalli M, Maji S, Dwivedi N, Dahiya P, Thakur JK. Evolution of disorder in Mediator complex and its functional relevance. Nucleic Acids Res. 2016; 44(4):1591–612. https://doi.org/10.1093/nar/gkv1135. 27. Duster R, Kaltheuner IH, Schmitz M, Geyer M. 1,6-Hexanediol, commonly used to dissolve liquid-liquid phase separated condensates, directly impairs kinase and phosphatase activities. J Biol Chem. 2021;296:100260. https://doi. org/10.1016/j.jbc.2021.100260. 28. Maharana S, Wang J, Papadopoulos DK, Richter D, Pozniakovsky A, Poser I, et al. RNA buffers the phase separation behavior of prion-like RNA binding proteins. Science. 2018;360(6391):918–21. https://doi.org/10.1126/science.aar7366. 29. Shin Y, Berry J, Pannucci N, Haataja MP, Toettcher JE, Brangwynne CP. Spatiotemporal control of intracellular phase transitions using light-activated optoDroplets. Cell. 2017;168(1-2):159–71 e114. https://doi.org/10.1016/j.cell.2 016.11.054. 30. Bahrami S, Drablos F. Gene regulation in the immediate-early response process. Adv Biol Regul. 2016;62:37–49. https://doi.org/10.1016/j.jbior.2016.05.001. 31. Healy S, Khan P, Davie JR. Immediate early response genes and cell transformation. Pharmacol Ther. 2013;137(1):64–77. https://doi.org/10.1016/j. pharmthera.2012.09.001. 32. Li P, Banjade S, Cheng HC, Kim S, Chen B, Guo L, et al. Phase transitions in the assembly of multivalent signalling proteins. Nature. 2012;483(7389):336– 40. https://doi.org/10.1038/nature10879. 33. McSwiggen DT, Hansen AS, Teves SS, Marie-Nelly H, Hao Y, Heckert AB, et al. Evidence for DNA-mediated nuclear compartmentalization distinct from phase separation. Elife. 2019;8:e47098. https://doi.org/10.7554/eLife.47098. 34. Narlikar GJ, Myong S, Larson D, Maeshima K, Francis N, Rippe K, et al. Is transcriptional regulation just going through a phase? Mol Cell. 2021;81(8): 1579–85. https://doi.org/10.1016/j.molcel.2021.03.046. 35. Sawyer IA, Bartek J, Dundr M. Phase separated microenvironments inside the cell nucleus are linked to disease and regulate epigenetic state, transcription and RNA processing. Semin Cell Dev Biol. 2019;90:94–103. https://doi.org/10.1016/j.semcdb.2018.07.001. 36. Zhong L, Liao D, Zhang M, Zeng C, Li X, Zhang R, et al. YTHDF2 suppresses cell proliferation and growth via destabilizing the EGFR mRNA in hepatocellular carcinoma. Cancer Lett. 2019;442:252–61. https://doi.org/10.1 016/j.canlet.2018.11.006.
https://openalex.org/W4362493566
https://figshare.com/articles/journal_contribution/Figure_S1_from_Multifunctional_APJ_Pathway_Promotes_Ovarian_Cancer_Progression_and_Metastasis/22512841/1/files/39974860.pdf
English
null
Figure S2 from Multifunctional APJ Pathway Promotes Ovarian Cancer Progression and Metastasis
null
2,023
cc-by
304
B. C. D. E. A. Supplemental Figure S1. APJ/Apelin pathway is pathologically relevant in ovarian cancer and correlates with worsened prognosis in OvCa patients. (A) ELISA assay for apelin levels in a panel of OvCa cells and FTE188 (fallopian tube epithelial) cells under normoxic and hypoxic conditions. (B-D) Comparison of APJ expression in primary ovarian tumors and metastasis sites in publically available OvCa datasets using Oncomine. (E,F) Kaplan-Meier survival plots showing higher APJ expression is associated with shorter (E) progression-free survival and (F) post-progression survival in patients with serous ovarian cancer. Plots were created in KM Plotter (http://kmplot.com). F. B. C. D. E. A. Supplemental Figure S1. APJ/Apelin pathway is pathologically relevant in ovarian cancer and correlates with worsened prognosis in OvCa patients. (A) ELISA assay for apelin levels in a panel of OvCa cells and FTE188 (fallopian tube epithelial) cells under normoxic and hypoxic conditions. (B-D) Comparison of APJ expression in primary ovarian tumors and metastasis sites in publically available OvCa datasets using Oncomine. (E,F) Kaplan-Meier survival plots showing higher APJ expression is associated with shorter (E) progression-free survival and (F) post-progression survival in patients with serous ovarian cancer. Plots were created in KM Plotter (http://kmplot.com). F. B. A. B. C. A. E. F. E. F. D. F. E. D. Supplemental Figure S1. APJ/Apelin pathway is pathologically relevant in ovarian cancer and correlates with worsened prognosis in OvCa patients. (A) ELISA assay for apelin levels in a panel of OvCa cells and FTE188 (fallopian tube epithelial) cells under normoxic and hypoxic conditions. (B-D) Comparison of APJ expression in primary ovarian tumors and metastasis sites in publically available OvCa datasets using Oncomine. (E,F) Kaplan-Meier survival plots showing higher APJ expression is associated with shorter (E) progression-free survival and (F) post-progression survival in patients with serous ovarian cancer. Plots were created in KM Plotter (http://kmplot.com).
https://openalex.org/W2766304453
https://www.nature.com/articles/cddis2017560.pdf
English
null
C-X-C motif chemokine ligand 10 produced by mouse Sertoli cells in response to mumps virus infection induces male germ cell apoptosis
Cell death and disease
2,017
cc-by
11,701
C-X-C motif chemokine ligand 10 produced by mouse Sertoli cells in response to mumps virus infection induces male germ cell apoptosis Mumps virus (MuV) infection usually results in germ cell degeneration in the testis, which is an etiological factor for male infertility. However, the mechanisms by which MuV infection damages male germ cells remain unclear. The present study showed that C-X-C motif chemokine ligand 10 (CXCL10) is produced by mouse Sertoli cells in response to MuV infection, which induces germ cell apoptosis through the activation of caspase-3. CXC chemokine receptor 3 (CXCR3), a functional receptor of CXCL10, is constitutively expressed in male germ cells. Neutralizing antibodies against CXCR3 and an inhibitor of caspase-3 activation significantly inhibited CXCL10-induced male germ cell apoptosis. Furthermore, the tumor necrosis factor-α (TNF-α) upregulated CXCL10 production in Sertoli cells after MuV infection. The knockout of either CXCL10 or TNF-α reduced germ cell apoptosis in the co-cultures of germ cells and Sertoli cells in response to MuV infection. Local injection of MuV into the testes of mice confirmed the involvement of CXCL10 in germ cell apoptosis in vivo. These results provide novel insights into MuV-induced germ cell apoptosis in the testis. Cell Death and Disease (2017) 8, e3146; doi:10.1038/cddis.2017.560; published online 26 October 2017 CXCL10 was initially identified as an IFN-γ-inducible cytokine,13 and functions by binding to CXC chemokine receptor 3 (CXCR3).14 CXCL10 is a pleiotropic cytokine capable of exerting various functions, including chemotactic homing of leukocytes, induction of cell apoptosis and regulation of cell proliferation.15 Moreover, CXCL10 is involved in the pathogenesis of various autoimmune and infectious diseases.16,17 Notably, CXCL10 upregulation in simian immu- nodeficiency virus (SIV) encephalitis induces neuronal apoptosis.18 The downregulation of CXCR3 expression reduced neuronal apoptosis in a mouse model of West Nile virus encephalitis.19 Increased CXCL10 level in the cere- brospinal fluid of individuals infected with human immunode- ficiency virus (HIV) has been associated with the progression of neuropsychiatric impairment.20 These studies indicated that CXCL10 upregulation is involved in the pathogenesis of viral encephalitis. Mumps is a contagious disease caused by the mumps virus (MuV) and is characterized by painful parotitis. 1Department of Cell Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China; 2Joint International Research Laboratory of Agriculture and Agri-product Safety, Institute of Epigenetics and Epigenomics, College of Animal Science and Technology, Yangzhou University, Yangzhou, China and 3Institute of Medical Biology, Chinese Academy of Medical Sciences, Kunming, China *Corresponding author: H Wu or D Han, Department of Cell Biology, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, 5 Dong Dan San Tiao, Beijing 100005, China. Tel: +86 10 6915 6457; Fax: +86 10 6915 6466; E-mail: yzwuhan@hotmail.com or dshan@ibms.pumc.edu.cn Received 04.6.17; revised 12.9.17; accepted 20.9.17; Edited by A Oberst Citation: Cell Death and Disease (2017) 8, e3146; doi:10.1038/cddis.2017.560 Macmillan Publishers Limited, part of Springer Nature. www.nature.com/cddis Citation: Cell Death and Disease (2017) 8, e3146; doi:10.1038/cddis.2017.560 Macmillan Publishers Limited, part of Springer Nature. www.nature.com/cddis Citation: Cell Death and Disease (2017) 8, e3146; doi:10.1038/cddis.2017.560 Macmillan Publishers Limited, part of Springer Nature. OPEN www.nature.com/cddis Corrected: Correction Results Insets in the upper right corners of the images represent negative controls, in which the preimmune rabbit sera were used as the first antibodies. (b) CXCR3 mRNA. Cells were cultured in the absence (Ctrl) and presence of 107 PFU/ml MuV for 24 h. Total RNA was extracted from the testicular cells, and relative mRNA level of CXCR3 was determined using real- time qRT-PCR by normalizing to β-Actin. The lowest CXCR3 mRNA level in SC was set as ‘1’. The fold increases in LC and GC compared to SC were presented. (c) CXCR3 protein. Testicular cell lysates were subjected to western blot analysis to probe CXCR3 using specific antibodies. β-Actin was probed as loading controls. (d) CXCR3 distribution in the testis. Immunohistochemistry was performed to localize CXCR3 on the paraffin sections of the testis from 5-week-old C57BL/6J mice. The inset in the upper right corner of the image in the right panel represents negative control, in which the preimmune goat serum was used as the first antibody. Black arrows, black arrowheads, white arrows, white arrowheads and asterisk indicate round spermatids, SC, spermatogonia, spermatocytes and interstitial cells, respectively. (e) CXCR3 locations in GC and SC co-cultures. IF co- staining with CXCR3 (green) and MVH (red) for GC and SC co-cultures. Scale bar = 20 μm. Images are the representatives of at least three experiments. Real-time qRT-PCR data are the means ± S E M of three experiments Figure 1 Expression of CXCR3 in mouse testicular cells. (a) Identification of testicular cells. Major testicular cells, including Leydig cells (LC), Sertoli cells (SC) and germ cells (GC), were isolated from 4-week-old C57BL/6J mice. Each cell type was identified by immunostaining for respective markers: LHR for LC, WT1 for SC and MVH for GC. Insets in the upper right corners of the images represent negative controls, in which the preimmune rabbit sera were used as the first antibodies. (b) CXCR3 mRNA. Cells were cultured in the absence (Ctrl) and presence of 107 PFU/ml MuV for 24 h. Total RNA was extracted from the testicular cells, and relative mRNA level of CXCR3 was determined using real- time qRT-PCR by normalizing to β-Actin. The lowest CXCR3 mRNA level in SC was set as ‘1’. The fold increases in LC and GC compared to SC were presented. (c) CXCR3 protein. Testicular cell lysates were subjected to western blot analysis to probe CXCR3 using specific antibodies. C-X-C motif chemokine ligand 10 produced by mouse Sertoli cells in response to mumps virus infection induces male germ cell apoptosis cells in response to viral infections might be detrimental to male germ cells. This study examined the role of MuV-induced CXCL10 production by mouse Sertoli cells in inducing male germ cell apoptosis. cells in response to viral infections might be detrimental to male germ cells. This study examined the role of MuV-induced CXCL10 production by mouse Sertoli cells in inducing male germ cell apoptosis. C-X-C motif chemokine ligand 10 produced by mouse Sertoli cells in response to mumps virus infection induces male germ cell apoptosis Orchitis is the most common extra-parotid gland complication of mumps that affects up to 30% of mumps cases in post-pubertal men.1 More than 50% of patients with bilateral mumps orchitis experience infertility.2 Moreover, a major pathological mani- festation of mumps orchitis is germ cell degeneration.3 Mumps orchitis is associated with the presence of MuV in the testis, thereby suggesting that MuV should directly induce pathogenesis.4 However, the mechanisms underlying MuV- induced male germ cell degeneration remain unknown. Spermatogenesis and steroidogenesis are two major functions of the testis. Several inflammatory cytokines are involved in testis pathophysiology.5 Interleukin 1 (IL-1), IL-6 and tumor necrosis factor-α (TNF-α) have important roles in regulating spermatogenesis under physiological conditions.6 However, these cytokines can be upregulated and impair testicular functions under inflammatory conditions.7 High levels of IL-1, IL-6 and TNF-α inhibit steroidogenesis in Leydig cells.8–10 Moreover, TNF-α upregulation induced male germ cells apoptosis in an experimental autoimmune orchitis model.11 We recently demonstrated that the C-X-C motif chemokine ligand 10 (CXCL10) expression is remarkably upregulated in Leydig and Sertoli cells in response to MuV infection,12 but the effect of the increased CXCL10 on testicular function remains unknown. CXCL10 is expressed in rat Leydig cells and can be upregulated by TNF-α and IFN-γ.21 Sendai viral infection induces CXCL10 expression in rat testicular somatic cells, including testicular macrophages, Sertoli, Leydig and peri- tubular myoid cells.22 By contrast, the Sendai virus does not induce CXCL10 expression in rat male germ cells. We recently demonstrated that MuV dramatically induces CXCL10 expres- sion in mouse Leydig and Sertoli cells but not in germ cells.12 We speculated that CXCL10 production by testicular somatic Mumps virus damages male germ cells Q Jiang et al 2 and germ cells were identified by staining with luteinizing hormone receptor (LHR), Wilms tumor nuclear protein 1 (WT1) and mouse VASA homolog (MVH), respectively (Figure 1a). The purity of each cell types was 495%. Real-time quantitative RT-PCR (qRT-PCR) results showed that the CXCR3 mRNA level was considerably higher in male germ cells than in Leydig and Sertoli cells (Figure 1b). MuV infection did not significantly affect CXCR3 expression in testicular cells. Western blot analysis demonstrated that CXCR3 protein was abundantly detected in germ cells in the absence and presence of MuV (Figure 1c). Moreover, CXCR3 protein was faintly detected in Leydig cells. By contrast, CXCR3 protein was not detected in Sertoli cells. Results Expression of CXCR3 in testicular cells. CXCL10 is significantly produced by mouse Leydig and Sertoli cells in response to MuV infection.12 To reveal the potential role of MuV-induced CXCL10 in the testis, we examined CXCR3 expression in major testicular cells. Leydig, Sertoli Figure 1 Expression of CXCR3 in mouse testicular cells. (a) Identification of testicular cells. Major testicular cells, including Leydig cells (LC), Sertoli cells (SC) and germ cells (GC), were isolated from 4-week-old C57BL/6J mice. Each cell type was identified by immunostaining for respective markers: LHR for LC, WT1 for SC and MVH for GC. Insets in the upper right corners of the images represent negative controls, in which the preimmune rabbit sera were used as the first antibodies. (b) CXCR3 mRNA. Cells were cultured in the absence (Ctrl) and presence of 107 PFU/ml MuV for 24 h. Total RNA was extracted from the testicular cells, and relative mRNA level of CXCR3 was determined using real- time qRT-PCR by normalizing to β-Actin. The lowest CXCR3 mRNA level in SC was set as ‘1’. The fold increases in LC and GC compared to SC were presented. (c) CXCR3 protein. Testicular cell lysates were subjected to western blot analysis to probe CXCR3 using specific antibodies. β-Actin was probed as loading controls. (d) CXCR3 distribution in the testis. Immunohistochemistry was performed to localize CXCR3 on the paraffin sections of the testis from 5-week-old C57BL/6J mice. The inset in the upper right corner of the image in the right panel represents negative control, in which the preimmune goat serum was used as the first antibody. Black arrows, black arrowheads, white arrows, white arrowheads and asterisk indicate round spermatids, SC, spermatogonia, spermatocytes and interstitial cells, respectively. (e) CXCR3 locations in GC and SC co-cultures. IF co- staining with CXCR3 (green) and MVH (red) for GC and SC co-cultures. Scale bar = 20 μm. Images are the representatives of at least three experiments. Real-time qRT-PCR data are the means ± S.E.M. of three experiments Figure 1 Expression of CXCR3 in mouse testicular cells. (a) Identification of testicular cells. Major testicular cells, including Leydig cells (LC), Sertoli cells (SC) and germ cells (GC), were isolated from 4-week-old C57BL/6J mice. Each cell type was identified by immunostaining for respective markers: LHR for LC, WT1 for SC and MVH for GC. Results β-Actin was probed as loading controls. (d) CXCR3 distribution in the testis. Immunohistochemistry was performed to localize CXCR3 on the paraffin sections of the testis from 5-week-old C57BL/6J mice. The inset in the upper right corner of the image in the right panel represents negative control, in which the preimmune goat serum was used as the first antibody. Black arrows, black arrowheads, white arrows, white arrowheads and asterisk indicate round spermatids, SC, spermatogonia, spermatocytes and interstitial cells, respectively. (e) CXCR3 locations in GC and SC co-cultures. IF co- staining with CXCR3 (green) and MVH (red) for GC and SC co-cultures. Scale bar = 20 μm. Images are the representatives of at least three experiments. Real-time qRT-PCR data are the means ± S.E.M. of three experiments Cell Death and Disease Mumps virus damages male germ cells Q Jiang et al 3 apoptosis during culture in vitro. By contrast, CXCL10 did not induce the apoptosis of Leydig (Figure 2a, middle panels) or Sertoli cells (right panels). The dose-dependent (Figure 2b, left panel) and time-dependent (right panel) effects of CXCL10 on male germ cell apoptosis were quantitatively analyzed. Furthermore, flow cytometry analysis confirmed that apoptotic germ cells were significantly increased at 24 h in the presence of 5 ng/ml CXCL10 (Figure 2c). Notably, both AO/EB staining and flow cytometry analysis showed comparable results, indicating that these two approaches are reliable in determining germ cell apoptosis. Immunohistochemistry (Figure 1d) and immunofluorescence (IF) co-staining of CXCR3 and MVH (Figure 1e) confirmed that CXCR3 protein was obviously located in male germ cells. A weak CXCR3 signal was observed in interstitial cells (asterisk) (Figure 1d), but not detected in Sertoli cells (Figure 1e). CXCL10-induced germ cell apoptosis. Considering that CXCL10 induces neuronal apoptosis,18 we examined the apoptosis of testicular cells in the presence of recombinant mouse CXCL10. Acridine orange/ethidium bromide (AO/EB) staining results showed that apoptotic male germ cells (arrows) were significantly increased at 24 h in the presence of 5 ng/ml CXCL10 (Figure 2a, lower left panel). However, certain apoptotic germ cells were also observed in control cells in the absence of CXCL10 (Figure 2a, upper left panel), suggesting that the male germ cells underwent spontaneous Activation of caspase-3 in germ cell apoptosis. To further understand the mechanism by which CXCL10 induced germ cell apoptosis, we examined the activation of the caspase cascade, an important apoptotic pathway.23 CXCL10 induced Figure 2 Germ cell apoptosis. Results (a) AO/EB staining. Testicular cells, including GC, LC and SC, were isolated from 4-week-old mice and cultured in vitro in the absence of XCL10 (upper panels) or presence of 5 ng/ml CXCL10 (lower panels) for 24 h. AO/EB solution was added to cultures at a dilution of 1:1000. After 1 min, apoptotic cells were tained as ‘orange’ (arrows) and living cells were stained as ‘green.’ (b) Dose- and time-dependent effects of CXCL10 on germ cell apoptosis. Germ cells were cultured in the resence of the indicated doses of CXCL10 for 24 h (left panel) or in the presence of 5 ng/ml CXCL10 for specific durations (right panel). Percentages of apoptotic cells were alculated based on AO/EB staining results. At least 500 cells were spontaneously counted. (c) Flow cytometry. Germ cells were cultured in the presence of 5 ng/ml CXCL10 for 4 h. Cells were labeled with Annexin V (AnxV)-FITC for 15 min and analyzed using BD Accuri C6 flow cytometer. Images are the representatives of at least three independent xperiments, scale bar = 20 μm. Data are the means ± S.E.M. of three experiments. *Po0.05 and **Po0.01 Cell Death a Figure 2 Germ cell apoptosis. (a) AO/EB staining. Testicular cells, including GC, LC and SC, were isolated from 4-week-old mice and cultured in vitro in the absence of CXCL10 (upper panels) or presence of 5 ng/ml CXCL10 (lower panels) for 24 h. AO/EB solution was added to cultures at a dilution of 1:1000. After 1 min, apoptotic cells were stained as ‘orange’ (arrows) and living cells were stained as ‘green.’ (b) Dose- and time-dependent effects of CXCL10 on germ cell apoptosis. Germ cells were cultured in the presence of the indicated doses of CXCL10 for 24 h (left panel) or in the presence of 5 ng/ml CXCL10 for specific durations (right panel). Percentages of apoptotic cells were calculated based on AO/EB staining results. At least 500 cells were spontaneously counted. (c) Flow cytometry. Germ cells were cultured in the presence of 5 ng/ml CXCL10 for 24 h. Cells were labeled with Annexin V (AnxV)-FITC for 15 min and analyzed using BD Accuri C6 flow cytometer. Images are the representatives of at least three independent experiments, scale bar = 20 μm. Data are the means ± S.E.M. of three experiments. *Po0.05 and **Po0.01 Figure 2 Germ cell apoptosis. (a) AO/EB staining. Results The cleavage of caspase-3 was at 5 and 8 h after the presence of CXCL10 essential to activate caspase-3. We found t was significantly cleaved in germ cells (Figure 3b). DEVD-fmk, an inhibitor of caspas aspase activation. (a) Caspase 3 activation. Germ cells were cultured in the absence (−) and presence (+) of 5 ng/ml CXCL10 for the speci ) of caspase 3 (Casp-3) and cleaved Casp-3 (17 kDa) in cell lysates were determined by western blot analysis. β-Actin was used as loa uantified by densitometry (right panel). (b) Caspase 8 activation. Germ cells were treated as described in (a), full length and cleavage of Cas analysis. (c) Inhibition of Casp-3 activation. Germ cells were treated with CXCL10 or with CXCL10 in the presence of 10 μM DEVD-fmk, a h. Casp-3 was determined by western blot analysis. (d) Germ cell apoptosis. Germ cells were cultured in the presence of CXCL10 along CL10 and DEVD-fmk (right panel) for 24 h. Apoptotic cells were labeled with AnxV-FITC and analyzed using flow cytometry. Images are the pendent experiments. Data of flow cytometry are the means ± S.E.M. of three experiments. **Po0.01 Figure 3 Caspase activation. (a) Caspase 3 activation. Germ cells were cultured in the absence (−) and presence (+) of 5 ng/ml CXCL10 for the specific durations. The full lengths (35 kDa) of caspase 3 (Casp-3) and cleaved Casp-3 (17 kDa) in cell lysates were determined by western blot analysis. β-Actin was used as loading controls. Signal densities were quantified by densitometry (right panel). (b) Caspase 8 activation. Germ cells were treated as described in (a), full length and cleavage of Casp-8 were determined by western blot analysis. (c) Inhibition of Casp-3 activation. Germ cells were treated with CXCL10 or with CXCL10 in the presence of 10 μM DEVD-fmk, an inhibitor of Casp-3 activation, for 8 h. Casp-3 was determined by western blot analysis. (d) Germ cell apoptosis. Germ cells were cultured in the presence of CXCL10 along (left panel) or in the presence of CXCL10 and DEVD-fmk (right panel) for 24 h. Apoptotic cells were labeled with AnxV-FITC and analyzed using flow cytometry. Images are the representatives of at least three independent experiments. Data of flow cytometry are the means ± S.E.M. of three experiments. **Po0.01 caspase-3 activation in germ cells in a time-dependent manner (Figure 3a). Results Testicular cells, including GC, LC and SC, were isolated from 4-week-old mice and cultured in vitro in the absence of CXCL10 (upper panels) or presence of 5 ng/ml CXCL10 (lower panels) for 24 h. AO/EB solution was added to cultures at a dilution of 1:1000. After 1 min, apoptotic cells were stained as ‘orange’ (arrows) and living cells were stained as ‘green.’ (b) Dose- and time-dependent effects of CXCL10 on germ cell apoptosis. Germ cells were cultured in the presence of the indicated doses of CXCL10 for 24 h (left panel) or in the presence of 5 ng/ml CXCL10 for specific durations (right panel). Percentages of apoptotic cells were calculated based on AO/EB staining results. At least 500 cells were spontaneously counted. (c) Flow cytometry. Germ cells were cultured in the presence of 5 ng/ml CXCL10 for 24 h. Cells were labeled with Annexin V (AnxV)-FITC for 15 min and analyzed using BD Accuri C6 flow cytometer. Images are the representatives of at least three independent experiments, scale bar = 20 μm. Data are the means ± S.E.M. of three experiments. *Po0.05 and **Po0.01 Cell Death and Disease Mumps virus damages male germ cells Q Jiang et al Figure 3 Caspase activation. (a) Caspase 3 activation. Germ cells were cultured in the absence (−) and presence (+) of 5 ng/ml CXCL10 for the specific durations. The full lengths (35 kDa) of caspase 3 (Casp-3) and cleaved Casp-3 (17 kDa) in cell lysates were determined by western blot analysis. β-Actin was used as loading controls. Signal densities were quantified by densitometry (right panel). (b) Caspase 8 activation. Germ cells were treated as described in (a), full length and cleavage of Casp-8 were determined by western blot analysis. (c) Inhibition of Casp-3 activation. Germ cells were treated with CXCL10 or with CXCL10 in the presence of 10 μM DEVD-fmk, an inhibitor of Casp-3 activation, for 8 h. Casp-3 was determined by western blot analysis. (d) Germ cell apoptosis. Germ cells were cultured in the presence of CXCL10 along (left panel) or in the presence of CXCL10 and DEVD-fmk (right panel) for 24 h. Apoptotic cells were labeled with AnxV-FITC and analyzed using flow cytometry. Images are the representatives of at least three independent experiments. Data of flow cytometry are the means ± S.E.M. of three experiments. **Po0.01 Q Jiang et al 4 activation in germ cells in a time-dependent igure 3a). Results Apoptotic cells (arrows) were determined using AO/EB staining at 24 h after MuV infection. Percentages of apoptotic germ cells were calculated based on AO/EB staining (right panel). At least 500 cells were spontaneously counted. (b) Caspase activation. The co-cultures of Sertoli and germ cells were infected as described in a. Germ cells were collected by treatment with hypotonic solution (20 mM Tris-HCl, pH 7.4) for 1 min. Cell lysates were subject to western blot analysis to probe caspases 3 and 8. (c) Apoptosis of male germ cells cultured alone. Male germ cells of 4-week-old mice were cultured in the absence (left panel) and presence (right panel) of MuV for 24 h. Apoptotic germ cells were determined using flow cytometry after labeling cells with AnxV-FITC. (d) Apoptosis of male germ cells in the conditional medium (CM). CM was collected by a centrifugation of the supernatant of Sertoli cells 24 h post MuV infection. Germ cells were cultured in CM for 24 h and apoptotic germ cells were analyzed by flow cytometry. The supernatant of Sertoli cells without MuV infection served as the control (ctrl). Images are the representatives of at least three experiments. Scale bar = 20 μm. Data are the means ± S.E.M. of three experiments. **Po0.01 Figure 4 MuV-induced male germ cell apoptosis. (a) MuV-induced apoptosis of male germ cells co-cultured with Sertoli cells. Sertoli and germ cells were isolated from 4-week-old mice and co-cultured at a ratio of 1:5 for 24 h. The co-cultures were infected with 1 ×107 PFU/ml MuV (middle panel). Cells without MuV infection served as controls (left panel). Apoptotic cells (arrows) were determined using AO/EB staining at 24 h after MuV infection. Percentages of apoptotic germ cells were calculated based on AO/EB staining (right panel). At least 500 cells were spontaneously counted. (b) Caspase activation. The co-cultures of Sertoli and germ cells were infected as described in a. Germ cells were collected by treatment with hypotonic solution (20 mM Tris-HCl, pH 7.4) for 1 min. Cell lysates were subject to western blot analysis to probe caspases 3 and 8. (c) Apoptosis of male germ cells cultured alone. Male germ cells of 4-week-old mice were cultured in the absence (left panel) and presence (right panel) of MuV for 24 h. Apoptotic germ cells were determined using flow cytometry after labeling cells with AnxV-FITC. (d) Apoptosis of male germ cells in the conditional medium (CM). Results The cleavage of caspase-3 was remarkable at 5 and 8 h after the presence of CXCL10 (Figure 3a, left panel). Band intensity was quantified by densitometry (Figure 3a, right panel). Caspase-8 cleavage is essential to activate caspase-3. We found that caspase-8 was significantly cleaved in germ cells by CXCL10 (Figure 3b). DEVD-fmk, an inhibitor of caspase-3 activation, efficiently inhibited caspase-3 cleavage at 8 h in the presence of CXCL10 (Figure 3c). Accordingly, DEVD-fmk significantly Cell Death and Disease Cell Death and Disease Mumps virus damages male germ cells Q Jiang et al uV-induced male germ cell apoptosis. (a) MuV-induced apoptosis of male germ cells co-cultured with Sertoli cells. Sertoli and germ cells were isolated from e and co-cultured at a ratio of 1:5 for 24 h. The co-cultures were infected with 1 ×107 PFU/ml MuV (middle panel). Cells without MuV infection served as controls optotic cells (arrows) were determined using AO/EB staining at 24 h after MuV infection. Percentages of apoptotic germ cells were calculated based on AO/EB anel). At least 500 cells were spontaneously counted. (b) Caspase activation. The co-cultures of Sertoli and germ cells were infected as described in a. Germ cells by treatment with hypotonic solution (20 mM Tris-HCl, pH 7.4) for 1 min. Cell lysates were subject to western blot analysis to probe caspases 3 and 8. (c) Apoptosis ells cultured alone. Male germ cells of 4-week-old mice were cultured in the absence (left panel) and presence (right panel) of MuV for 24 h. Apoptotic germ cells d using flow cytometry after labeling cells with AnxV-FITC. (d) Apoptosis of male germ cells in the conditional medium (CM). CM was collected by a centrifugation ant of Sertoli cells 24 h post MuV infection. Germ cells were cultured in CM for 24 h and apoptotic germ cells were analyzed by flow cytometry. The supernatant of hout MuV infection served as the control (ctrl). Images are the representatives of at least three experiments. Scale bar = 20 μm. Data are the means ± S.E.M. of nts. **Po0.01 g 5 Figure 4 MuV-induced male germ cell apoptosis. (a) MuV-induced apoptosis of male germ cells co-cultured with Sertoli cells. Sertoli and germ cells were isolated from 4-week-old mice and co-cultured at a ratio of 1:5 for 24 h. The co-cultures were infected with 1 ×107 PFU/ml MuV (middle panel). Cells without MuV infection served as controls (left panel). Results CM was collected by a centrifugation of the supernatant of Sertoli cells 24 h post MuV infection. Germ cells were cultured in CM for 24 h and apoptotic germ cells were analyzed by flow cytometry. The supernatant of Sertoli cells without MuV infection served as the control (ctrl). Images are the representatives of at least three experiments. Scale bar = 20 μm. Data are the means ± S.E.M. of three experiments. **Po0.01 reduced apoptotic germ cell numbers 24 h after the presence of CXCL10 (Figure 3d). response to MuV infection. AO/EB staining showed that MuV remarkably increased apoptotic germ cells (arrows) 24 h after infection (Figure 4a, middle panel). In controls, only a few apoptotic germ cells were observed in the co-cultures of germ cells and Sertoli cells without MuV infection (Figure 4a, left panel). Percentages of apoptotic germ cells were quantitatively analyzed based on AO/EB staining (Figure 4a, right panel). In accordance with germ cell apoptosis, MuV evidently induced the activation of caspase-3 and caspase-8 in the co-cultures response to MuV infection. AO/EB staining showed that MuV remarkably increased apoptotic germ cells (arrows) 24 h after infection (Figure 4a, middle panel). In controls, only a few apoptotic germ cells were observed in the co-cultures of germ cells and Sertoli cells without MuV infection (Figure 4a, left panel). Percentages of apoptotic germ cells were quantitatively analyzed based on AO/EB staining (Figure 4a, right panel). In accordance with germ cell apoptosis, MuV evidently induced the activation of caspase-3 and caspase-8 in the co-cultures MuV-induced apoptosis of male germ cells co-cultured with Sertoli cells. MuV induces CXCL10 production in Sertoli cells,12 thus, we speculated that CXCL10 produced by Sertoli cells might induce germ cell apoptosis in a paracrine fashion. Therefore, we analyzed germ cell apoptosis in the co-cultures of germ cells and Sertoli cells in Cell Death and Disease Mumps virus damages male germ cells Q Jiang et al 6 Figure 5 Role of CXCL10 in MuV-induced germ cell apoptosis. (a) MuV-induced CXCL10 production. Sertoli and germ cells from WTand CXCL10−/ −mice were co-cultured in the absence (Ctrl) or presence (+ MuV) of 107 PFU/ml MuV. At 24 h after MuV infection, CXCL10 levels in media were measured using ELISA. (b) MuV-induced germ cell apoptosis. The co-cultures of Sertoli and germ cells were infected with MuVor with MuV in the presence of neutralizing antibodies against CXCR3 (Ab-CXCR3) for 24 h. Results Apoptotic cells were quantitatively analyzed based on AO/EB staining. (c) Caspase activation. Co-cultures were treated as described in (b). The activation of caspases 3 and 8 in germ cells was determined by western blot analysis. Images are the representatives of at least three experiments. Data are the means ± S.E.M. of three experiments. **Po0.01 Figure 5 Role of CXCL10 in MuV-induced germ cell apoptosis. (a) MuV-induced CXCL10 production. Sertoli and germ cells from WTand CXCL10−/ −mice were co-cultured in the absence (Ctrl) or presence (+ MuV) of 107 PFU/ml MuV. At 24 h after MuV infection, CXCL10 levels in media were measured using ELISA. (b) MuV-induced germ cell apoptosis. The co-cultures of Sertoli and germ cells were infected with MuVor with MuV in the presence of neutralizing antibodies against CXCR3 (Ab-CXCR3) for 24 h. Apoptotic cells were quantitatively analyzed based on AO/EB staining. (c) Caspase activation. Co-cultures were treated as described in (b). The activation of caspases 3 and 8 in germ cells was determined by western blot analysis. Images are the representatives of at least three experiments. Data are the means ± S.E.M. of three experiments. **Po0.01 TNF-α-induced CXCL10 production. Given that MuV infec- tion upregulates TNF-α production in mouse Sertoli cells and TNF-α induces CXCL10 expression,12,21 we examined the role of autocrine TNF-α in inducing CXCL10 expression in Sertoli cells after MuV infection. Enzyme-linked immunosor- bent assay (ELISA) results confirmed that MuV infection significantly increased the TNF-α (Figure 6a, left panel) and CXCL10 (right panel) levels in the co-cultures of WT cells. An inhibitor of TNF-α secretion, pomalidomide,24 significantly reduced the TNF-α level. TNF-α was abolished in TNF-α−/ − cells (Figure 6a, left panel). MuV significantly increased CXCL10 levels in the media of both WT and TNF-α−/ −cells (Figure 6a, right panel); however, the CXCL10 level in TNF- α−/ −cells was significantly lower than that in WT cells in response to MuV infection. Notably, pomalidomide signifi- cantly inhibited MuV-induced CXCL10 production in WT cells but not in TNF-α−/ −cells. MuV significantly induced germ cell apoptosis and caspase activation in the co-cultures of WT cells (Figure 6b). By contrast, MuV did not significantly induce germ cell apoptosis in TNF-α−/ −cells. Recombinant mouse TNF-α induced CXCL10 production at comparable levels in Sertoli and germ cell co-cultures of WTand TNF-α−/ −mice in a dose-dependent manner (Figure 6c). Results WTor TNF-α−/ −cell co-cultures were treated with 5 ng/ml TNF-α or with TNF- α in the presence of Ab-CXCR3 for 24 h. Apoptotic germ cells were determined based on AO/EB staining and caspase activation was assessed by western blot analysis. Data are the means ± S.E.M. of three independent experiments. *Po0.05 and **Po0.01 Figure 6 Role of TNF-α in inducing CXCL10 expression. (a) MuV-induced TNF-α and CXCL10 production. Sertoli and germ cells of 4-week-old WTor TNF-α−/ −mice were co-cultured and infected with MuV or with MuV in the presence of pomalidomide (POM), an inhibitor of TNF-α secretion for 24 h. Co-cultures without MuV infection served as controls (Ctrl). TNF-α (left panel) and CXCL10 (right panel) levels in the culture media were measured using ELISA. (b) MuV-induced germ cell apoptosis. Co-cultures were treated as described in a. Apoptotic germ cells were determined based on AO/EB staining and confirmed by determination of caspase cleavages by Western blot analysis. (c) Induction CXCL10 production by recombinant TNF-α. WTor TNF-α−/ −cells were co-cultured in the presence of the indicated doses of recombinant mouse TNF-α for 24 h. CXCL10 levels in media were determined using ELISA. (d) TNF-α-induced germ cells apoptosis. WTor TNF-α−/ −cell co-cultures were treated with 5 ng/ml TNF-α or with TNF- α in the presence of Ab-CXCR3 for 24 h. Apoptotic germ cells were determined based on AO/EB staining and caspase activation was assessed by western blot analysis. Data are the means ± S.E.M. of three independent experiments. *Po0.05 and **Po0.01 that TNF-α upregulates CXCL10 production in Sertoli cells in an autocrine manner and CXCL10 induces germ cell apoptosis. testicular lysates of WT mice 24 h after MuV injection (Figure 7b). CXCL10 was not detected in the testes of CXCL10−/ −mice. Co-staining results demonstrated that MuV injection significantly increased apoptotic germ cells (arrows) in WT mice after 48 h, while only a few apoptotic germ cells were observed in the testes of control WT mice (Figure 7c, left panels). By contrast, apoptotic germ cells were not increased in CXCL10−/ −mice 48 h post MuV injection (Figure 7c, left panels). Apoptotic germ cell numbers per tubular section were quantitatively analyzed based on Terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) assay (Figure 7d). These results suggested that the increased CXCL10 level in the testis is MuV-induced CXCL10 production and germ cell apopto- sis in the testis. Results Accordingly, TNF-α induced germ cell apoptosis and caspase activation in WT and TNF-α−/ −cell co-cultures, which were significantly reduced by ab-CXCR3 (Figure 6d). These results indicated (Figure 4b). By contrast, flow cytometry analysis showed that MuV did not significantly induce apoptosis of male germ cells cultured alone in vitro (Figure 4c). However, apoptotic germ cells were significantly increased in the conditional medium from Sertoli cells 24 h after MuV infection (Figure 4d). Role of CXCL10 in MuV-induced germ cell apoptosis. To examine the role of CXCL10 produced by Sertoli cells in MuV-induced germ cell apoptosis, we compared the apopto- sis of germ cells co-cultured with Sertoli cells from wild-type (WT) and CXCL10−/ −mice. CXCL10 levels in the media of WT cells were significantly increased 24 h after MuV infection (Figure 5a). By contrast, CXCL10 was not detectable in the media of CXCL10−/ −cells. MuV significantly induced germ cell apoptosis in co-cultures of WT cells 24 h after infection (Figure 5b). Notably, neutralizing antibodies against CXCR3 (ab-CXCR3) significantly reduced MuV-induced germ cell apoptosis in co-cultures of WT cells. By contrast, MuV and ab-CXCR3 did not significantly affected germ cell apoptosis in CXCL10−/ −cells. Accordingly, MuV-induced cleavages of caspase-3 and caspase-8 were inhibited by ab-CXCR3 in WT germ cells (Figure 5c, left panels). MuV did not induce the cleavages of caspase-3 and caspase-8 in CXCL10−/ −germ cells (Figure 5c, right panels). Cell Death and Disease Mumps virus damages male germ cells Q Jiang et al Figure 6 Role of TNF-α in inducing CXCL10 expression. (a) MuV-induced TNF-α and CXCL10 production. Sertoli and germ cells of 4-week-old WTor TNF-α−/ −mice were co-cultured and infected with MuV or with MuV in the presence of pomalidomide (POM), an inhibitor of TNF-α secretion for 24 h. Co-cultures without MuV infection served as controls (Ctrl). TNF-α (left panel) and CXCL10 (right panel) levels in the culture media were measured using ELISA. (b) MuV-induced germ cell apoptosis. Co-cultures were treated as described in a. Apoptotic germ cells were determined based on AO/EB staining and confirmed by determination of caspase cleavages by Western blot analysis. (c) Induction CXCL10 production by recombinant TNF-α. WTor TNF-α−/ −cells were co-cultured in the presence of the indicated doses of recombinant mouse TNF-α for 24 h. CXCL10 levels in media were determined using ELISA. (d) TNF-α-induced germ cells apoptosis. Results Insets in upper right corners represent the higher resolution for dotted box areas (lower panels). (d) A time-dependent germ cell apoptosis. The testes of WTand CXCL10−/ −mice were injected with MuV for the indicated durations. Apoptotic germ cells were quantitatively analyzed based on the co-staining of TUNEL and IF. Apoptotic germ cell numbers per tubular section were presented. One hundred tubules per testis were counted. Images are the representatives of three mice. Scale bar = 40 μm. Data represent the means ± S.E.M. of three mice. *Po0.05 and **Po0.01 MuV-mediated impairment of spermatogenesis. (a) Histological analysis. MuV (1 × 107 PFU) in 10 μl of PBS was injected into the testis of 5-week-old C57BL/J6 anels). Equal volume of PBS alone was injected into the contralateral testis for the control (upper panels). Histological analysis was performed on the paraffin hematoxylin and eosin (HE) staining. Asterisk indicate seminiferous tubules (ST) without elongated spermatids. (b) Quantification of spermatogenesis impairment. e were treated as described in a. The ratio of the STwith elongated spermatids in lumen was determined based on histological analysis. A total of 200 tubules in were spontaneously counted for spermatogenesis examination. (c) Spermatogenesis impairment in TNF-α−/ −and CXCL10−/ −mice. 5-week-old TNF-α−/ −and as well as respective control mice, were treated as described in (a). The ratio of ST with elongated spermatids in lumen was determined at 2 weeks after MuV ges are the representatives of three mice. Scale bar = 100 μm. Data represent the means ± S.E.M. of three mice. **Po0.01 Figure 8 MuV-mediated impairment of spermatogenesis. (a) Histological analysis. MuV (1 × 107 PFU) in 10 μl of PBS was injected into the testis of 5-week-old C57BL/J6 mice (lower panels). Equal volume of PBS alone was injected into the contralateral testis for the control (upper panels). Histological analysis was performed on the paraffin sections after hematoxylin and eosin (HE) staining. Asterisk indicate seminiferous tubules (ST) without elongated spermatids. (b) Quantification of spermatogenesis impairment. C57BL/J6 mice were treated as described in a. The ratio of the STwith elongated spermatids in lumen was determined based on histological analysis. A total of 200 tubules in three sections were spontaneously counted for spermatogenesis examination. (c) Spermatogenesis impairment in TNF-α−/ −and CXCL10−/ −mice. 5-week-old TNF-α−/ −and CXCL10−/ −, as well as respective control mice, were treated as described in (a). Results The ratio of ST with elongated spermatids in lumen was determined at 2 weeks after MuV injection. Images are the representatives of three mice. Scale bar = 100 μm. Data represent the means ± S.E.M. of three mice. **Po0.01 mutation of TNF-α or CXCL10 significantly increased the seminiferous tubules with elongated spermatids at 2 weeks after MuV injection (Figure 8c). demonstrated that the CXCL10 produced by Sertoli cells in response to MuV infection induces germ cell apoptosis and TNF-α upregulates CXCL10 production in an autocrine manner. These results provide novel insights into the mechanisms underlying MuV-impaired spermatogenesis. We recently found that mouse Leydig and Sertoli cells remarkably produced CXCL10 in response to MuV infection.12 To determine the potential role of CXCL10 in the MuV-infected demonstrated that the CXCL10 produced by Sertoli cells in response to MuV infection induces germ cell apoptosis and TNF-α upregulates CXCL10 production in an autocrine manner. These results provide novel insights into the mechanisms underlying MuV-impaired spermatogenesis. Results Local injection of MuV remarkably reduced the seminiferous Cell Death and Disease Mumps virus damages male germ cells Q Jiang et al Mumps virus damages male germ cells Q Ji t l 9 Figure 7 MuV-induced CXCL10 production and germ cell apoptosis in the testis. MuV (1 × 107 PFU) in 10 μl of PBS was injected into the testis of 5-week-old WT and CXCL10−/ −mice. The contralateral testis that was injected with an equal volume of PBS alone served as Ctrl. (a) MuV detection. MuV-NP in testicular lysates was detected by western blot analysis at 24 h after MuV injection. (b) CXCL10 level. The testis was lysed by grinding in PBS at 24 h after MuV injection. CXCL10 levels in the lysates were measured using ELISA. (c) Apoptosis of male germ cells. The testis of WT (left panels) and CXCL10−/ −(right panels) mice were injected with PBS or MuV. After 24 h, apoptotic germ cells in paraffin sections were detected using co-staining of TUNEL and IF with antibodies to MVH. Insets in upper right corners represent the higher resolution for dotted box areas (lower panels). (d) A time-dependent germ cell apoptosis. The testes of WTand CXCL10−/ −mice were injected with MuV for the indicated durations. Apoptotic germ cells were quantitatively analyzed based on the co-staining of TUNEL and IF. Apoptotic germ cell numbers per tubular section were presented. One hundred tubules per testis were counted. Images are the representatives of three mice. Scale bar = 40 μm. Data represent the means ± S.E.M. of three mice. *Po0.05 and **Po0.01 Figure 7 MuV-induced CXCL10 production and germ cell apoptosis in the testis. MuV (1 × 107 PFU) in 10 μl of PBS was injected into the testis of 5-week-old WT and CXCL10−/ −mice. The contralateral testis that was injected with an equal volume of PBS alone served as Ctrl. (a) MuV detection. MuV-NP in testicular lysates was detected by western blot analysis at 24 h after MuV injection. (b) CXCL10 level. The testis was lysed by grinding in PBS at 24 h after MuV injection. CXCL10 levels in the lysates were measured using ELISA. (c) Apoptosis of male germ cells. The testis of WT (left panels) and CXCL10−/ −(right panels) mice were injected with PBS or MuV. After 24 h, apoptotic germ cells in paraffin sections were detected using co-staining of TUNEL and IF with antibodies to MVH. Results To examine the involvement of CXCL10 in MuV-induced germ cell apoptosis in vivo, the testes of 5-week-old WT and CXCL10−/ −mice were locally injected with 1 × 107 plaque forming unit (PFU) MuV in 10 μl PBS. MuV nucleoprotein (MuV-NP) was detected in the testes of both WT and CXCL10−/ −mice 24 h after MuV injection (Figure 7a). In the controls, MuV-NP was not detected in the testes that were injected with PBS alone. ELISA results showed that the CXCL10 level was dramatically increased in Cell Death and Disease Mumps virus damages male germ cells Q Jiang et al 8 8 associated with male germ cell apoptosis in response to MuV injection. Effect of MuV on spermatogenesis. To evaluate patholo- gical consequences of MuV infection in male infertility/ subfertility, we examined the spermatogenesis status. Local injection of MuV remarkably reduced the seminiferous tubules with elongated spermatids in the lumen at 2 week after injection (Figure 8a, lower panels). However, th impaired spermatogenesis was observed 1 and 3 week after MuV injection. The spermatogenesis status wa quantitatively analyzed (Figure 8b). Further, we examine the roles of TNF-α and CXCL10 in the MuV-mediate impairment of spermatogenesis. We showed that eithe th and Disease associated with male germ cell apoptosis in response to MuV injection. tubules with elongated spermatids in the lumen at 2 weeks after injection (Figure 8a, lower panels). However, the impaired spermatogenesis was observed 1 and 3 weeks after MuV injection. The spermatogenesis status was quantitatively analyzed (Figure 8b). Further, we examined the roles of TNF-α and CXCL10 in the MuV-mediated impairment of spermatogenesis. We showed that either tubules with elongated spermatids in the lumen at 2 weeks after injection (Figure 8a, lower panels). However, the impaired spermatogenesis was observed 1 and 3 weeks after MuV injection. The spermatogenesis status was quantitatively analyzed (Figure 8b). Further, we examined the roles of TNF-α and CXCL10 in the MuV-mediated impairment of spermatogenesis. We showed that either Effect of MuV on spermatogenesis. To evaluate patholo- gical consequences of MuV infection in male infertility/ subfertility, we examined the spermatogenesis status. Local injection of MuV remarkably reduced the seminiferous Effect of MuV on spermatogenesis. To evaluate patholo- gical consequences of MuV infection in male infertility/ subfertility, we examined the spermatogenesis status. Discussion Notably, Zika virus infection induces CXCL10 production in mouse testicular somatic cells and leads to leukocyte infiltration in the testes, resulting in orchitis.31,32 These results suggest that CXCL10 production might be involved in the pathogenesis of the testes after MuV and Zika virus infection. p p To further understand the mechanisms underlying CXCL10- induced male germ cell apoptosis, we examined the activation of caspase-3 in male germ cells. Caspase-3 activation, which is induced by caspase-8 activation, is a critical pathway in executing cell apoptosis.26 We demonstrated that CXCL10 activated caspase-3 and caspase-8 in male germ cells. Notably, DEVD-fmk, a caspase-3 inhibitor,27 protected germ cells from CXCL10-induced apoptosis. These observations suggested that CXCL10 induces germ cell apoptosis via the activation of caspase cascades. In accordance with the in vitro results, we confirmed the association between CXCL10 upregulation and germ cell apoptosis in the testes after MuV infection in vivo. We recently found that MuV infection suppresses testosterone synthesis in mouse Leydig cells.12 However, whether the inhibition of testosterone synthesis contributes to MuV-impaired spermatogenesis remains to be clarified. Understanding the mechanisms by which MuV induces CXCL10 production in the testes would be helpful for the development of therapeutic interventions in MuV orchitis. The present study shows that TNF-α induces CXCL10 expression in an autocrine manner in Sertoli cells after MuV infection. This observation corresponds to a previous report, which showed that TNF-α upregulates CXCL10 expression in rat Leydig cells.21 However, CXCL10 expression was not completely abolished in TNF-α−/ −cells, suggesting that TNF-α-indepen- dent mechanisms should be also involved in MuV-induced CXCL10 expression in Sertoli cells. Although IFN-γ induces CXCL10 expression,13 this mechanism cannot be involved in MuV-induced CXCL10 production, because MuV did not induce IFN-γ expression in co-cultures of Sertoli and germ cells (data not shown). Moreover, CXCL10 mRNA was significantly upregulated as early as 6 h after MuV infection, when TNF-α was not detected at the protein level. These observations suggested that MuV may also directly induce CXCL10 expression independently of TNF-α and IFN-γ in Sertoli cells. In support of this speculation, an early study showed that HIV envelope glycoprotein gp120 induces CXCL10 expression independent of IFN-γ in the mouse brain.44 Whether MuV envelope glycoprotein directly induces CXCL10 expression in Sertoli cells is worthy of clarification. We further analyzed spermatogenesis status in response to MuV injection. Discussion We recently found that mouse Leydig and Sertoli cells remarkably produced CXCL10 in response to MuV infection.12 To determine the potential role of CXCL10 in the MuV-infected MuV infection usually impairs spermatogenesis, but the underlying mechanisms remain to be clarified. This study Cell Death and Disease Cell Death and Disease Mumps virus damages male germ cells Q Jiang et al Mumps virus damages male germ cells Q Jiang et al 10 testes, we examined the CXCR3 distribution in testicular cells. CXCR3 was predominantly expressed in male germ cells, suggesting that CXCL10 acts on germ cells. Moreover, CXCL10 induced germ cell apoptosis in vitro. Flow cytometry is a common approach for quantitatively analyzing the apoptosis of suspended cells after labeling with Annexin V-FITC. In the present study, the apoptosis of male germ cells cultured alone was analyzed by flow cytometry. However, we determined germ cell apoptosis using AO/EB staining in co- cultures of Sertoli and germ cells, because the germ cells firmly bound to Sertoli cells and could not be collected for flow cytometry. AO/EB staining approach has been used to detect cell apoptosis.25 We found that both flow cytometry and AO/ EB staining gave comparable results, confirming that these two approaches are consistent for measuring male germ cell apoptosis. such as rhinovirus, respiratory syncytial virus, hepatitis virus and Ebola virus, induce CXCL10 expression.37–40 These studies suggested that CXCL10 might be involved in the pathogenesis of different infectious diseases. CXCL10 facil- itates the recruitment of CXCR3-positive immune cells, including macrophages, dendritic cells and activated T lymphocytes, to infected sites, which has an important role in initiating inflammatory responses against the invading microbial pathogens.41,42 Moreover, several studies have shown that CXCL10 upregulation induces cell apoptosis in certain viral infectious diseases. CXCL10 induces neuronal apoptosis in SIV and West Nile virus encephalitis.18,19 In addition, it promotes cancer cell apoptosis in human papillomavirus-associated cervical carcinoma.43 We recently demonstrated that MuV significantly induces CXCL10 expres- sion in mouse testicular somatic cells.12 The present study showed that MuV-induced CXCL10 in Sertoli cells triggered the apoptosis of male germ cells in a paracrine manner. Whether CXCL10 upregulation facilitates the development of orchitis by recruiting leukocytes to the testes after MuV infection requires clarification in vivo. Discussion Quantitative PCR was performed in a 20 μl reaction mixture containing 0.2 μl cDNA, 0.5 μM forward and reverse primers, and 10 μl Power SYBR Green PCR Master Mix (Applied Biosystems, Foster City, CA, USA) on an ABI PRISM 7300 real-time cycler (Applied Biosystems). The transcript levels of target genes were determined using the comparative 2-ΔΔCT method as described in the Applied Biosystems User Bulletin No.2 (P/N 4303859). The following specific primer sequences (forward and reverse) were used: for CXCR3, 5′-ACAGCACCTCTCCCTACGAT-3′ and 5′-TGACTCAGTAGCACAGCAGC-3′; and β-actin, 5′-GAAATCGTGCGTGACATCAAAG-3′ and 5′-TGTAGTTTCATGGATGC CACAG-3′. Reagents. Goat polyclonal anti-CXCR3 (sc-9901), rabbit polyclonal anti-LHR (sc-25828) and anti-WT1 (sc-192) antibodies were purchased from Santa Cruz Biotechnology (Santa Cruz, CA, USA). Rabbit polyclonal anti-Caspase-3 (9662S) and mouse monoclonal anti-Caspase-8 (9746S) antibodies were purchased from Cell Signaling Technology (Beverly, MA, USA). Mouse monoclonal anti-MuV nucleoprotein (ab9876) and rabbit polyclonal anti-MVH (ab13840) antibodies were purchased from Abcam (Cambridge, UK). Mouse monoclonal anti-β-actin antibody (A5316) was purchased from Sigma (St. Louis, MO, USA). Horseradish-peroxidase (HRP)-conjugated secondary antibodies were purchased from Zhongshan Biotechnology Co. (Beijing, China). Recombinant mouse CXCL10 (250-16) and TNF-α (315-01A) were purchased from Peprotech (Rocky Hill, CT, USA). DEVD-fmk (264156), an inhibitor of caspase-3, was purchased from Calbiochem (La Jolla, CA, USA). Pomalidomide (S1567), an inhibitors of TNF-α, was purchased from Selleckchem (Houston, TX, USA). Annexin V-FITC apoptosis detection kit (FXP018) and ELISA kit for detecting mouse TNF-α (CME0004) were purchased from Beijing 4A Biotech Company (Beijing, China). ELISA kit for detecting mouse CXCL10 (BMS6018) was purchased from eBioscience (San Diego, CA, USA). Western blot analysis. Cells or tissues were lysed using RIPA lysis buffer containing protease inhibitor cocktail (Sigma). The protein concentration was determined using the bicinchonic acid protein assay kit (Applygen Technologies Inc., Beijing, China). The proteins (20 μg/lane) were separated on 10% SDS-PAGE gel and electrotransferred onto PVDF membranes (Millipore, Bedford, MA, USA). The membranes were blocked on Tris-buffered saline (pH 7.4) containing 5% non-fat milk at room temperature for 1 h and incubated with the primary antibodies overnight at 4 °C. The membranes were washed twice with appropriate HRP- conjugated secondary antibodies (Zhongshan Biotechnology Co.) at room temperature for 1 h. Antigen/antibody complexes were visualized using an enhanced chemiluminescence detection kit (Zhongshan Biotechnology Co.). Cell isolation. Testicular cells were isolated from 4-week-old mice based on previously described procedures.45 In brief, mice were anesthetized with CO2 and then killed by cervical dislocation. Discussion In summary, the present study demonstrates that MuV- induced TNF-α upregulates CXCL10 expression in Sertoli cells in an autocrine manner, and that CXCL10 induces male germ cell apoptosis though the activation of caspase-3. The results provide novel insights into the mechanism underlying MuV-impaired spermatogenesis. The CXCL10/CXCR3 sys- tem in testicular cells might be considered as a therapeutic target for male infertility caused by MuV infection. MuV infection. MuV (SP-A strain) was isolated from a mumps patient50 and obtained from the Institute of Medical Biology, Chinese Academy of Medical Sciences (Kunming, China). MuV was amplified and titrated in Vero cells. MuV preparations were diluted in 1 × PBS at a density of 1 × 109 PFU/ml and stored at −80 °C. MuV was added to cell cultures at a multiplicity of infection of 5 for in vitro infection. For in vivo infection, 5-week-old mice were anesthetized with pentobarbital sodium (50 mg/kg) and the testis were surgically exposed. The testis was locally injected with 1 × 107 PFU MuV in 10 μl of PBS using 30-gauge needles. The testis of control mice was injected with an equal volume of PBS. Materials and Methods Animals. C57BL/6J strain mice were obtained from the Laboratory Animal Center of Peking Union Medical College (Beijing, China). TNF-α knockout (TNF-α−/ −) mice (B6/129S6-TNFtm1GK1/J) with C57BL/6J background and CXCL10−/ −mice (B6.129S4-CXCL10tm1Adl/J) with C57BL/6 background were purchased from the Jackson Laboratory (Bar Harbor, Maine, USA). WT control mice were generated by backcrossing knockout mice to C57BL/6J mice. All of the mice were maintained in a pathogen-free facility on a 12 h/12 h light/dark cycle with access to food and water ad libitum. All mice were handled in compliance with the Guidelines (permit number: SCXK (Jing) 2007-0001) for the Care and Use of Laboratory Animals established by the Chinese Council on Animal Care (Beijing, China). All experimental procedures were approved by Institutional Animal Care and Use Committee of the Institute of Basic Medical Sciences in China. Real-time qRT-PCR. Total RNA was extracted using Trizol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. After treatment with RNase-free DNase I (Invitrogen) to remove genomic DNA contamination, RNA (1 μg) was reverse transcribed into cDNA in a volume of 20 μl containing 2.5 μM random hexamers, 2 μM dNTP and 200 U Moloney murine leukemia virus reverse transcriptase (Promega, Madsion, WI, USA). Discussion The ratio of the seminiferous tubules containing elongated spermatids was significantly reduced at 2 weeks after local MuV injection in WT mice; however, this phenotype was recovered at 3 weeks. We did not observe permanent impairment of spermatogenesis in vivo after MuV infection. These results agreed with the previous observations that mice are resistant to MuV infection.28 Several aspects may be responsible for the resistance to MuV in mice: (1) mice adopt efficient antiviral ability. A previous study showed that murine Leydig cells exhibit higher efficient antiviral response than their human counterparts.29 Accordingly, various viral infec- tions lead to orchitis in human beings, but natural viral orchitis has not been observed in murine animals.30 (2) MuV does not efficiently proliferate in mice after infection in vivo. MuV was significantly removed from the testis several days after local injection (data not shown). Therefore, MuV only transiently affects the mouse testis. (3) Although the detrimental effect of few virus, such as Zika virus, on the mouse testis has been investigated, the testicular damage only occurred in mice lacking interferon signaling.31–33 These studies indicated that the antiviral system in mice inhibits virus-mediated testicular damage. Therefore, whether MuV infection permanently disrupts spermatogenesis in mice lacking interferon signaling is worthy of determination. In addition to Sertoli cells, Leydig cells in the testicular interstitial spaces also produce CXCL10 in response to MuV infection.12 Increased CXCL10 levels in the testicular inter- stitial spaces may facilitate the migration of leukocytes into the testis, which remains to be tested. By contrast, CXCL10 produced by Leydig cells should not induce the apoptosis of germ cells behind the blood–testis barrier. Therefore, MuV- induced CXCL10 production by Sertoli and Leydig cells may play different roles in the pathogenesis within the testis. CXCL10 expression can be upregulated by bacterial and parasitic infections.34–36 In particular, various viral infections, Cell Death and Disease Mumps virus damages male germ cells Q Jiang et al Mumps virus damages male germ cells Q Jiang et al 11 Co-cultures of Sertoli and germ cells. Sertoli cells were seeded in six- well plates at a density of 1 × 105 cells per well. After 24 h, 1 × 106 germ cells were added to Sertoli cells in each well. Twenty four hours later, non-adherent germ cells were removed by washing twice with culture media and the co-cultures were infected with MuV. Discussion The testes were decapsulated and incubated with 0.5 mg/ml collagenase type I (Sigma) in PBS at room temperature for 15 min with gentle oscillation. The suspensions were filtered using 80 μm copper meshes to separate interstitial cells and seminiferous tubules. Interstitial cells were cultured in F12/DMEM (Life Technologies, Grand Island, NY, USA) supplemented with 100 U/ml penicillin, 100 mg/ml streptomycin and 10% fetal calf serum (FCS, Life Technologies). After 24 h, Leydig cells were detached by treatment with 0.125% trypsin for 5 min. Testicular macrophages were not detached in this treatment. The purity of Leydig cells were more than 95% based on staining for LHR (a maker of Leydig cells).46 Macrophages in Leydig cell preparations were less than 3% based on the immunostaining for F40/80 (a marker of macrophages).47 Histological analysis and IF staining. For histological analysis, the testis of 5-week-old mice was fixed in 4% paraformaldehyde for 24 h and embedded in paraffin. The paraffin sections (5 μm in thickness) were cut with a rotary microtome Reichert 820 HistoSTAT (Reichert Technologies, Depew, NY, USA). The sections were stained with hematoxylin and eosin for histological analysis on spermatogenesis. For IF staining, the slides were soaked in citrate buffer and then heated in a microwave at 100 °C for 10 min to retrieve the antigens or the cells were fixed with pre-cooled methanol for 3 min and then permeabilized with 0.2% Triton X-100 in PBS for 15 min. After blocking with 5% preimmune goat sera in PBS for 1 h at room temperature, the sections were incubated with primary antibodies overnight at 4 °C. After washing twice with PBS, the sections were incubated with FITC- or TRITC- conjugated secondary antibodies at room temperature for 1 h. The slides were mounted by antifade mounting medium with DAPI (Zhongshan Biotechnology Co.). Negative controls were incubated with preimmune animal serum instead of the primary antibodies. The sections were counterstained with hematoxylin and mounted with neutral balsam (Zhongshan Biotechnology Co.). The seminiferous tubules were recovered and suspended in collagenase type 1 at room temperature for an additional 15 min to remove the peritubular myoid cells. The tubules were cut into small pieces (~1 mm) and incubated with 0.5 mg/ml hyaluronidase (Sigma) at room temperature for 10 min with gentle pipetting to dissociate Sertoli and germ cells. Cell suspensions were cultured in F12/DMEM medium supplemented with 10% FCS at 32 °C for 6 h. Publisher’s Note 30. Dejucq N, Jegou B. Viruses in the mammalian male genital tract and their effects on the reproductive system. Microbiol Mol Biol Rev 2001; 65: 208–231 first and second pages, table of contents. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 31. Ma W, Li S, Ma S, Jia L, Zhang F, Zhang Y et al. Zika virus causes testis damage and leads to male infertility in mice. Cell 2017; 168: 542. y 32. Govero J, Esakky P, Scheaffer SM, Fernandez E, Drury A, Platt DJ et al. Zika virus infection damages the testes in mice. Nature 2016; 540: 438–442. 1. Masarani M, Wazait H, Dinneen M. Mumps orchitis. J R Soc Med 2006; 99: 573–575. 1. Masarani M, Wazait H, Dinneen M. Mumps orchitis. J R Soc Med 2006; 99: 573–575. 2. Casella R, Leibundgut B, Lehmann K, Gasser TC. Mumps orchitis: report of a mini-epidemic. J Urol 1997; 158: 2158–2161. 2. Casella R, Leibundgut B, Lehmann K, Gasser TC. Mumps orchitis: report of a mini-epidemic. J Urol 1997; 158: 2158–2161. 33. Uraki R, Hwang J, Jurado KA, Householder S, Yockey LJ, Hastings AK et al. Zika virus causes testicular atrophy. Sci Adv 2017; 3: e1602899. 3. Davis NF, McGuire BB, Mahon JA, Smyth AE, O'Malley KJ, Fitzpatrick JM. The increasing incidence of mumps orchitis: a comprehensive review. BJU Int 2010; 105: 1060–1065. 34. Azzurri A, Sow OY, Amedei A, Bah B, Diallo S, Peri G et al. IFN-gamma-inducible protein 10 and pentraxin 3 plasma levels are tools for monitoring inflammation and disease activity in Mycobacterium tuberculosis infection. Microbes Infect 2005; 7: 1–8. 4. Bjorvatn B. Mumps virus recovered from testicles by fine-needle aspiration biopsy in cases of mumps orchitis. Scand J Infect Dis 1973; 5: 3–5. 35. Jain V, Armah HB, Tongren JE, Ned RM, Wilson NO, Crawford S et al. Plasma IP-10, apoptotic and angiogenic factors associated with fatal cerebral malaria in India. Malar J 2008; 7: 83. 5. Hedger MP, Meinhardt A. Cytokines and the immune-testicular axis. J Reprod Immunol 2003; 58: 1–26. 6. Bornstein SR, Rutkowski H, Vrezas I. Cytokines and steroidogenesis. Mol Cell Endocrinol 2004; 215: 135–141. 36. Campanella GS, Tager AM, El Khoury JK, Thomas SY, Abrazinski TA, Manice LA et al. Author contributions DH, HW and QJ designed the project and wrote the paper. QJ, FW, LS, XZ, MG and WL carried out all of the experiments and generated data. CS, QL and YC carried out statistical analysis and revised the manuscript. 28. Xu P, Huang Z, Gao X, Michel FJ, Hirsch G, Hogan RJ et al. Infection of mice, ferrets, and rhesus macaques with a clinical mumps virus isolate. J Virol 2013; 87: 8158–8168. 29. Le Tortorec A, Denis H, Satie AP, Patard JJ, Ruffault A, Jegou B et al. Antiviral responses of human Leydig cells to mumps virus infection or poly I:C stimulation. Hum Reprod (Oxford, England) 2008; 23: 2095–2103. Discussion Liu M, Guo S, Hibbert JM, Jain V, Singh N, Wilson NO et al. CXCL10/IP-10 in infectious diseases pathogenesis and potential therapeutic implications. Cytokine Growth Factor Rev 17. Liu M, Guo S, Hibbert JM, Jain V, Singh N, Wilson NO et al. CXCL10/IP-10 in infectious 17. Liu M, Guo S, Hibbert JM, Jain V, Singh N, Wilson NO et al. CXCL10/IP-10 in infectious diseases pathogenesis and potential therapeutic implications. Cytokine Growth Factor Rev 2011; 22: 121–130. diseases pathogenesis and potential therapeutic implications. Cytokine Growth Factor Rev 2011; 22: 121–130. 18. Sui Y, Potula R, Dhillon N, Pinson D, Li S, Nath A et al. Neuronal apoptosis is mediated by CXCL10 overexpression in simian human immunodeficiency virus encephalitis. Am J Pathol 2004; 164: 1557–1566. Terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling. Paraffin sections of the testis were prepared for analyzing germ cell apoptosis. Apoptotic germ cells in situs were detected using a TUNEL kit (Maibio Biotechnology Co., Shanghai, China) according to the manufacturer’s instruction. The sections were stained by IF staining with antibodies to MVH, a germ cell marker. 19. Zhang B, Patel J, Croyle M, Diamond MS, Klein RS. TNF-alpha-dependent regulation of CXCR3 expression modulates neuronal survival during West Nile virus encephalitis. J Neuroimmunol 2010; 224: 28–38. 20. Kolb SA, Sporer B, Lahrtz F, Koedel U, Pfister HW, Fontana A. Identification of a T cell chemotactic factor in the cerebrospinal fluid of HIV-1-infected individuals as interferon- gamma inducible protein 10. J Neuroimmunol 1999; 93: 172–181. Statistical analysis. All data are presented as the mean ± S.E.M. of at least three independent experiments. Statistical significance between individual comparisons was determined by Student’s t-test. One-way ANOVA with Bonferroni’s (selected pairs) post hoc test was used for multiple comparisons. The calculations were performed using SPSS Version 13.0 (SPSS Inc., Chicago, IL, USA) and Po0.05 was considered statistically significant. 21. Hu J, You S, Li W, Wang D, Nagpal ML, Mi Y et al. Expression and regulation of interferon- gamma-inducible protein 10 gene in rat Leydig cells. Endocrinology 1998; 139: 3637–3645. 22. Le Goffic R, Mouchel T, Aubry F, Patard JJ, Ruffault A, Jegou B et al. Production of the chemokines monocyte chemotactic protein-1, regulated on activation normal T cell expressed and secreted protein, growth-related oncogene, and interferon-gamma-inducible protein-10 is induced by the Sendai virus in human and rat testicular cells. Endocrinology 2002; 143: 1434–1440. Conflict of Interest The authors declare no conflict of interest. 23. Kaufmann T, Strasser A, Jost PJ. Fas death receptor signalling: roles of Bid and XIAP. Cell Death Differ 2012; 19: 42–50. 24. Zhu YX, Braggio E, Shi CX, Bruins LA, Schmidt JE, Van Wier S et al. Cereblon expression is required for the antimyeloma activity of lenalidomide and pomalidomide. Blood 2011; 118: 4771–4779. Acknowledgements. This work was supported by the National Natural Science Foundation of China (Grant Numbers 31261160491 and 31371518) and the Major State Basic Research Project of China (Grant Numbers 2015CB943001 and 2016YFA0101001). 25. Liu K, Liu PC, Liu R, Wu X. Dual AO/EB staining to detect apoptosis in osteosarcoma cells compared with flow cytometry. Med Sci Monit Basic Res 2015; 21: 15–20. 26. Cohen GM. Caspases: the executioners of apoptosis. Biochem J 1997; 326(Pt 1): 27. Maimaitili A, Shu Z, Cheng X, Kaheerman K, Sikandeer A, Li W. Arctigenin, a natural lignan compound, induces G0/G1 cell cycle arrest and apoptosis in human glioma cells. Oncol Lett 2017; 13: 1007–1013. Discussion Germ cells were recovered by collecting non-adherent cells. The purity of the germ cells was 495% based on immunostaining for MVH, a marker of germ cells.48 Enzyme-linked immunosorbent assay. Cells were cultured in six-well plates. Culture media were collected at 24 h after MuV infection. The testis was lysed by grinding in 1 × PBS and the supernatants of the lysates were collected after centrifugation at 1000 × g for 5 min. TNF-α and CXCL10 levels were measured using ELISA kits in accordance with the manufacturer’s instructions. g g Sertoli cells were cultured at 37 °C for another 24 h and treated with a hypotonic solution (20 mM Tris, pH 7.4) for 1 min to remove the germ cells that adhered to Sertoli cells. Sertoli cells purity was495% based on immunostaining for WT1, a marker of Sertoli cells.49 Cell Death and Disease Mumps virus damages male germ cells Q Jiang et al Mumps virus damages male germ cells Q Jiang et al 12 Flow cytometry. Male germ cells were washed twice in 1 × PBS and labeled with Annexin V-FITC using apoptosis detection kit (FXP018, Beijing 4A Biotech Company) following the manufacturer’s instructions. The cells were analyzed with a BD Accuri C6 flow cytometer (BD Biosciences, Franklin lakes, NJ, USA). 13. Luster AD, Ravetch JV. Biochemical characterization of a gamma interferon-inducible cytokine (IP-10). J Exp Med 1987; 166: 1084–1097. 14. Loetscher M, Gerber B, Loetscher P, Jones SA, Piali L, Clark-Lewis I et al. Chemokine receptor specific for IP10 and mig: structure, function, and expression in activated T-lymphocytes. J Exp Med 1996; 184: 963–969. 15. Neville LF, Mathiak G, Bagasra O. The immunobiology of interferon-gamma inducible protein 10 kD (IP-10): a novel, pleiotropic member of the C-X-C chemokine superfamily. Cytokine Growth Factor Rev 1997; 8: 207–219. AO/EB staining. Testicular cells were cultured in six-well plates with 2 ml media. At 24 h after MuV infection, 2 μl fluorescent staining solution containing 100 μg/ml AO and 100 μg/ml EB (Sigma) was added to each well and incubated for 1 min at room temperature. Cells were observed under a fluorescent microscope (BX51, Olympus, Tokyo, Japan). Apoptotic cells were shown as ‘orange’ and living cells as ‘green’. 16. Antonelli A, Ferrari SM, Giuggioli D, Ferrannini E, Ferri C, Fallahi P. Chemokine (C-X-C motif) ligand (CXCL)10 in autoimmune diseases. Autoimmun Rev 2014; 13: 272–280. 17. Publisher’s Note Chemokine receptor CXCR3 and its ligands CXCL9 and CXCL10 are required for the development of murine cerebral malaria. Proc Natl Acad Sci USA 2008; 105: 4814–4819. 7. Guazzone VA, Jacobo P, Theas MS, Lustig L. Cytokines and chemokines in testicular inflammation: a brief review. Microsc Res Tech 2009; 72: 620–628. 8. Hales DB. Interleukin-1 inhibits Leydig cell steroidogenesis primarily by decreasing 17 alpha- 8. Hales DB. Interleukin-1 inhibits Leydig cell steroidogenesis primarily by decreasing 17 alpha- hydroxylase/C17-20 lyase cytochrome P450 expression. Endocrinology 1992; 131: 2165–2172. 37. Schneider D, Ganesan S, Comstock AT, Meldrum CA, Mahidhara R, Goldsmith AM et al. Increased cytokine response of rhinovirus-infected airway epithelial cells in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2010; 182: 332–340. 9. Tsigos C, Papanicolaou DA, Kyrou I, Raptis SA, Chrousos GP. Dose-dependent effects of recombinant human interleukin-6 on the pituitary-testicular axis. J Interferon Cytokine Res 1999; 19: 1271–1276. 38. Haeberle HA, Kuziel WA, Dieterich HJ, Casola A, Gatalica Z, Garofalo RP. Inducible expression of inflammatory chemokines in respiratory syncytial virus-infected mice: role of MIP-1alpha in lung pathology. J Virol 2001; 75: 878–890. 10. Xiong Y, Hales DB. The role of tumor necrosis factor-alpha in the regulation of mouse Leydig cell steroidogenesis. Endocrinology 1993; 132: 2438–2444. 39. Mihm S, Schweyer S, Ramadori G. Expression of the chemokine IP-10 correlates with the accumulation of hepatic IFN-gamma and IL-18 mRNA in chronic hepatitis C but not in hepatitis B. J Med Virol 2003; 70: 562–570. 11. Theas MS, Rival C, Jarazo-Dietrich S, Jacobo P, Guazzone VA, Lustig L. Tumour necrosis factor-alpha released by testicular macrophages induces apoptosis of germ cells in autoimmune orchitis. Hum Reprod (Oxford, England) 2008; 23: 1865–1872. 40. Mahanty S, Gupta M, Paragas J, Bray M, Ahmed R, Rollin PE. Protection from lethal infection is determined by innate immune responses in a mouse model of Ebola virus infection. Virology 2003; 312: 415–424. 12. Wu H, Shi L, Wang Q, Cheng L, Zhao X, Chen Q et al. Mumps virus-induced innate immune responses in mouse Sertoli and Leydig cells. Sci Rep 2016; 6: 19507. Cell Death and Disease Mumps virus damages male germ cells Q Jiang et al Mumps virus damages male germ cells Q Jiang et al 13 49. Sharpe RM, McKinnell C, Kivlin C, Fisher JS. Proliferation and functional maturation of Sertoli cells, and their relevance to disorders of testis function in adulthood. Reproduction 2003; 125: 769–784. Publisher’s Note 41. Nie CQ, Bernard NJ, Norman MU, Amante FH, Lundie RJ, Crabb BS et al. IP-10-mediated T cell homing promotes cerebral inflammation over splenic immunity to malaria infection. PLoS Pathog 2009; 5: e1000369. 50. Liang Y, Ma J, Li C, Chen Y, Liu L, Liao Y et al. Safety and immunogenicity of a live attenuated mumps vaccine: a phase I clinical trial. Hum Vaccines Immunother 2014; 10: 1382–1390. 50. Liang Y, Ma J, Li C, Chen Y, Liu L, Liao Y et al. Safety and immunogenicity of a live attenuated mumps vaccine: a phase I clinical trial. Hum Vaccines Immunother 2014; 10: 1382–1390. 42. Vasquez RE, Xin L, Soong L. Effects of CXCL10 on dendritic cell and CD4+ T-cell functions during Leishmania amazonensis infection. Infect Immun 2008; 76: 161–169. 43. Wang LL, Chen P, Luo S, Li J, Liu K, Hu HZ et al. CXC-chemokine-ligand-10 gene therapy efficiently inhibits the growth of cervical carcinoma on the basis of its anti-angiogenic and antiviral activity. Biotechnol Appl Biochem 2009; 53: 209–216. Cell Death and Disease is an open-access journal published by Nature Publishing Group. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ 44. Asensio VC, Maier J, Milner R, Boztug K, Kincaid C, Moulard M et al. Interferon-independent, human immunodeficiency virus type 1 gp120-mediated induction of CXCL10/IP-10 gene expression by astrocytes in vivo and in vitro. J Virol 2001; 75: 7067–7077. 45. Wu H, Wang H, Xiong W, Chen S, Tang H, Han D. Expression patterns and functions of toll- like receptors in mouse sertoli cells. Endocrinology 2008; 149: 4402–4412. like receptors in mouse sertoli cells. Endocrinology 2008; 149: 4402–4412. 46. Klinefelter GR, Hall PF, Ewing LL. Effect of luteinizing hormone deprivation in situ on steroidogenesis of rat Leydig cells purified by a multistep procedure. Biol Reprod 1987; 36: 769–783. 47. Hume DA, Perry VH, Gordon S. The mononuclear phagocyte system of the mouse defined by immunohistochemical localisation of antigen F4/80: macrophages associated with epithelia. Anat Rec 1984; 210: 503–512. p 48. Encinas G, Zogbi C, Stumpp T. r The Author(s) 2017 Publisher’s Note Detection of four germ cell markers in rats during testis morphogenesis: differences and similarities with mice. Cells Tissues Organs 2012; 195: 443–455. r The Author(s) 2017 Cell Death and Disease Cell Death and Disease
https://openalex.org/W4207013633
https://researchonline.jcu.edu.au/74458/1/74458.pdf
English
null
Inequalities in prevalence of birth by caesarean section in Ghana from 1998-2014
BMC pregnancy and childbirth
2,022
cc-by
7,066
Abstract Background:  Caesarean section (CS) is an intervention to reduce maternal and perinatal mortality, for complicated pregnancy and labour. We analysed trends in the prevalence of birth by CS in Ghana from 1998 to 2014. Methods:  Using the World Health Organization’s (WHO) Health Equity Assessment Toolkit (HEAT) software, data from the 1998-2014 Ghana Demographic and Health Surveys (GDHS) were analysed with respect of inequality in birth by CS. First, we disaggregated birth by CS by four equity stratifiers: wealth index, education, residence, and region. Second, we measured inequality through simple unweighted measures (Difference (D) and Ratio (R)) and complex weighted measures (Population Attributable Risk (PAR) and Population Attributable Fraction (PAF)). A 95% confidence interval was constructed for point estimates to measure statistical significance. Results:  The proportion of women who underwent CS increased significantly between 1998 (4.0%) and 2014 (12.8%). Throughout the 16-year period, the proportion of women who gave birth by CS was positively skewed towards women in the highest wealth quintile (i.e poorest vs richest: 1.5% vs 13.0% in 1998 and 4.0% vs 27.9% in 2014), those with secondary education (no education vs secondary education: 1.8% vs 6.5% in 1998 and 5.7% vs 17.2% in 2014) and women in urban areas (rural vs urban 2.5% vs 8.5% in 1998 and 7.9% vs 18.8% in 2014). These disparities were evident in both complex weighted measures of inequality (PAF, PAR) and simple unweighted meas‑ ures (D and R), although some uneven trends were observed. There were also regional disparities in birth by CS to the advantage of women in the Greater Accra Region over the years (PAR 7.72; 95% CI 5.86 to 9.58 in 1998 and PAR 10.07; 95% CI 8.87 to 11.27 in 2014). Conclusion:  Ghana experienced disparities in the prevalence of births by CS, which increased over time between 1998 and 2014. Our findings indicate that more work needs to be done to ensure that all subpopulations that need medically necessary CS are given access to maternity care to reduce maternal and perinatal deaths. Nevertheless, given the potential complications with CS, we advocate that the intervention is only undertaken when medically indicated. Keywords:  Caesarean section, Inequality, Ghana, Demographic and health surveys, Global health remains high despite significant advances that have been initiated to enhance maternal health outcomes [2]. © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​ mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Abstract Hence, in the year 2015, the world adopted 17 Sustain- able Development Goals [SDGs] of which one, SDG-3, focused on improving maternal health. This goal envi- sions to reduce the global maternal mortality ratio (MMR) to less than 70 per 100,000 live births by 2030 [3]. In spite of this global commitment to mitigate MMR, it remains high in sub-Saharan Africa (sSA) [4]. WHO Background Maternal mortality is a public health concern across the globe for many years with the highest ratios occurring in resource-poor countries [1]. Particularly in low- and middle-income countries [LMICs], maternal mortality *Correspondence: duahhenryofori@gmail.com 2 Research Department, FOCOS Orthopaedic Hospital, Accra, Ghana Full list of author information is available at the end of the article *Correspondence: duahhenryofori@gmail.com 2 Research Department, FOCOS Orthopaedic Hospital, Accra, Ghana Full list of author information is available at the end of the article Okyere et al. BMC Pregnancy and Childbirth (2022) 22:64 https://doi.org/10.1186/s12884-022-04378-8 Okyere et al. BMC Pregnancy and Childbirth (2022) 22:64 https://doi.org/10.1186/s12884-022-04378-8 Open Access © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​ mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Okyere et al. BMC Pregnancy and Childbirth (2022) 22:64 Page 2 of 9 reports that about 66% of the world’s maternal deaths happens in sSA [5]. For that matter, it is imperative that there is equality and equity in the availability of basic and comprehensive emergency obstetric care such as caesar- ean section [CS] [3]. selection of enumeration areas (EAs) is the first step and takes cognisance of rural and urban locations in Ghana. This is ensued by household selection in the EAs. The complete sampling procedure has been elaborated in the final reports of the 1998, 2003, 2008 and 2014 GDHS. The sample for this study consisted of women with live births in the 5 years preceding the survey who were answerable to questions pertaining to CS (n = 15,432). Focus of the analysis was on recent births of women of reproductive age. CS is regarded as life-saving intervention that ought to be accessible to all women who need it [6]. It is interesting to note the benefits of CS transcend beyond the mother’s health; it also enhances the health of the child [7]. Abso- lute and relative indications for CS vary and these include cephalopelvic disproportion, pelvic deformity, eclampsia, umbilical cord prolapse, threatening uterine rupture, pla- centa previa and fetal distress [8]. Results Data from Ghana Demographic and Health Surveys (GDHS) in 1998, 2003, 2008 and 2014 were analysed. GDHS forms part of global surveys implemented by Measure DHS in about 85 LMICs worldwide. Overarch- ing focus of DHS is to collate information on children, women and men. Among the cardinal issues captured are CS, fertility and family planning. When sampling, Trends in the prevalence of births by CS by different inequality dimensions, 1998‑2014h Variables of interest d Study outcome was whether mode of birth was by CS or not. Women who reported having given live birth by CS were categorised as “1”, whilst those without birth by CS were classified otherwise as “0”. Four stratifiers were used to assess inequality in births by CS: economic sta- tus measured by wealth quintile (quintile 1-5), education (no education, primary, secondary and above), residence (rural, urban) and region of residence (Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper West, Upper East). Wealth index is derived by employing Principal Component Analysis (PCA). Education is measured by highest level of formal education completed. Generally, there is consensus in the literature that the optimal population-based CS rate should lie between 10 and 15% [11–13]. Very low population-based CS rates imply that women in need of CS in that country lack access [13, 14]. Nonetheless, there are inequities in the prevalence of CS in almost every country across the globe but more profound in LMICs, with some countries hav- ing as low as 3% and as high as 58% [6, 15, 16]. Evidence indicates that inequities in the prevalence of CS do not only occur between countries, but also within countries [16]. In a recent analysis of global, regional and national CS trends, Betran et al. found an increase in CS except for sSA [13]. However, further multi-country studies in Africa showed that indeed there were inequities within countries [16]. Statistical analysis We used the 2019 updated WHO’s HEAT version 3.1 software for all analyses [18]. Estimates and confidence intervals of birth by caesarean section with respect to the aforementioned stratifiers were computed. Four meas- ures were used to compute inequality namely Differ- ence (D), Population Attributable risk (PAR), Population Attributable Fraction (PAF) and Ratio (R). Two of these are simple unweighted measures (D, R) and two are com- plex weighted measures (PAR, PAF). At the same time, R and PAF are relative measures whereas D and PAR are absolute measures. Summary measures were considered because WHO has indicated that both absolute and relative summary measures are essential for generating policy driven findings [18]. Unlike simple measures, the complex ones take size of categories inherent in a sub- population into account. WHO has extensively elabo- rated the procedure for generating summary measures [19]. Ghana, like many sub-Saharan African countries, has a MMR of about 310 per 100,000 live births at the end of 2017 [17]. Given the fact that there are inequities in the prevalence of CS within countries, it is quintessential to focus attention on monitoring these in order to improve maternal health. To this end, we analysed trends in the prevalence of birth by CS in Ghana from 1998 to 2014. Inasmuch as there are benefits of birth by CS when demanded by indication, it is worth noting that birth by CS was also associated with severe adverse events including intraoperative and post- operative bleeding, as well as increased risks of maternal mortality, especially in regions like sSA where there are huge obstetric morbidities [8–10]. Nevertheless, there is a growing, unnecessary prevalence of elective CS as an alternative to spontaneous vaginal birth in recent years [11]. Inequality indices on factors associated with the prevalence of births by caesarean section, 1998‑2014 In Table 2, absolute (D, PAR) and relative (R, PAF) sum- mary measures are presented. A pattern of simple abso- lute (D) and relative (R) economic inequality in births by CS persisted throughout the period. The complex absolute measure (PAR) revealed increasing inequal- ity from 1998 to 2014. The complex relative measure (PAF) showed an increase in disparity between 1998 and 2003 and subsequently a decline until 2014. Trends in the prevalence of births by CS by different inequality dimensions, 1998‑2014h The proportion of women who underwent CS increased significantly between 1998 (4.0%) and 2014 (12.8%). Throughout the 16-year period, CS was skewed towards women in the highest wealth quintile and the gap Okyere et al. BMC Pregnancy and Childbirth (2022) 22:64 Okyere et al. BMC Pregnancy and Childbirth (2022) 22:64 Page 3 of 9 Okyere et al. BMC Pregnancy and Childbirth (2022) 22:64 Figures 1, 2 and 3 depict the economic, educational and rural-urban disparities in birth by CS in Ghana over the period 1998-2014 . increased as the years went by (i.e poorest vs richest: 1.5% vs 13.0% in 1998 and 4.0% vs 27.9% in 2014). Just as observed across economic status, births by CS were dominant among women who had secondary or higher education relative to those who had no formal educa- tion between 1998 [6.5, 95% CI = 5.13, 8.19 vs 1.8, 95% CI = 1.11, 2.92] and 2014 [17.2, 95% CI = 15.43, 19.18 vs 5.7, 95% CI = 4.26, 7.66]. The analysis also indicated that CS was highly concentrated among urban residents compared to their rural counterparts in 1998 [8.5% vs 2.5%] and increased to 18.8% vs 7.9% in 2014. Across the erstwhile ten adminstrative regions, we observed that CS was higher among women in the Greater Accra region across all different survey points. Meanwhile, as of 2014, the proportion of women in the Central Region who underwent CS had increased dramatically (15.7%) relative to the proportion 3.6% in 1998 (Table  1). Inequality indices on factors associated with the prevalence of births by caesarean section, 1998‑2014 Signifi- cant absolute and relative education-related inequality existed from 1998 to 2014 to the advantage of women Table 1  Trends in the prevalence of births by caesarean section by different inequality dimensions, 1998-2014 CI Confidence Interval Inequality dimension 1998 (3.97) 2003 (3.69) 2008 (6.90) 2014 (12.79) Sample Percentage [95% CI] Sample Percentage [95% CI] Sample Percentage [95% CI] Sample Percentage [95% CI] Economic status   Quintile 1 (poorest) 865 1.47 [0.80, 2.67] 941 1.48 [0.84, 2.60] 743 1.31 [0.72, 2.36] 1263 4.01 [2.99, 5.36]   Quintile 2 684 1.55 [0.76, 3.12] 809 1.73 [1.00, 2.97] 641 5.01 [3.11, 7.98] 1195 6.79 [4.97, 9.22]   Quintile 3 660 3.31 [1.98, 5.47] 720 1.90 [1.11, 3.24] 548 8.39 [5.56, 12.47] 1113 10.65 [8.59, 13.15]   Quintile 4 552 4.66 [3.11, 6.91] 616 4.14 [2.51, 6.75] 560 9.07 [6.41, 12.70] 1073 17.31 [13.80, 21.48]   Quintile 5 (richest) 431 12.96 [9.78, 16.98] 551 12.18 [8.84, 16.56] 414 14.97 [10.76, 20.44] 1048 27.88 [23.70, 32.48] Education   No education 1228 1.81 [1.11, 2.92] 1466 1.68 [1.06, 2.65] 951 3.43 [2.13, 5.47] 1561 5.72 [4.26, 7.66]   Primary school 648 2.93 [1.78, 4.78] 843 2.86 [1.68, 4.83] 722 4.52 [3.02, 6.72] 1140 10.85 [7.68, 15.14]   Secondary school + 1317 6.49 [5.13, 8.19] 1329 6.43 [4.84, 8.51] 1235 10.98 [8.83, 13.56] 2992 17.22 [15.43, 19.18] Place of residence   Rural 2420 2.52 [1.88, 3.36] 2435 1.77 [1.26, 2.49] 1805 4.67 [3.52, 6.17] 3131 7.89 [6.09, 10.17]   Urban 773 8.51 [6.62, 10.86] 1203 7.57 [5.67, 10.04] 1103 10.56 [8.19, 13.50] 2562 18.79 [16.59, 21.20] Region   Western Region 412 4.43 [2.24, 8.57] 366 2.24 [0.97, 5.06] 270 5.40 [2.82, 10.09] 573 14.57 [10.86, 19.28]   Central Region 379 3.58 [1.80, 7.00] 303 1.05 [0.32, 3.39] 292 10.01 [5.67, 17.06] 622 15.74 [11.00, 22.03]   Greater Accra Region 329 11.68 [9.06, 14.94] 389 11.98 [8.03, 17.50] 345 10.23 [6.59, 15.54] 880 22.86 [18.37, 28.08]   Volta Region 337 1.40 [0.44, 4.43] 298 3.67 [2.00, 6.63] 244 6.04 [3.41, 10.48] 435 8.82 [6.31, 12.19]   Eastern Region 430 5.68 [3.62, 8.80] 362 3.89 [1.87, 7.88] 254 7.62 [4.71, 12.09] 532 9.46 [6.63, 13.33]   Ashanti Region 513 2.27 [1.07, 4.73] 684 4.36 [2.50, 7.52] 544 10.65 [7.50, 14.90] 1064 15.61 [12.46, 19.38]   Brong Ahafo Region 259 3.14 [1.94, 5.05] 400 2.56 [1.23, 5.25] 271 4.91 [2.24, 10.45] 497 9.58 [7.48, 12.18]   Northern Region 232 1.41 [0.47, 4.14] 499 1.57 [0.65, 3.75] 455 2.55 [0.93, 6.76] 709 2.66 [1.53, 4.56]   Upper West Region 100 2.03 [0.66, 6.09] 117 1.85 [0.55, 6.04] 147 1.13 [0.22, 5.57] 226 7.56 [5.54, 10.25]   Upper East Region 198 1.05 [0.37, 2.89] 215 0.49 [0.06, 3.78] 81 3.46 [1.48, 7.91] 152 4.69 [3.07, 7.10] Okyere et al. Inequality indices on factors associated with the prevalence of births by caesarean section, 1998‑2014 BMC Pregnancy and Childbirth (2022) 22:64 Page 4 of 9 Fig. 1  Trends in economic disparities in live births by caesarean section (CS) in Ghana from 1998 to 2014 Trends in economic disparities in live births by caesarean section (CS) in Ghana from 1998 to 2014 Discussion 2  Trends in educational disparities in live births by caesarean section (CS) in Ghana from 1998 to 2014 cannot rule out the possibility of rising cases of unneces- sary CS which need further investigation. decrease maternal mortality. These show the existence of TLTL (more prevalent in lower wealth quintiles, rural areas and more peripheral regions) and TMTS (more prevalent in richer quintiles, urban areas and the Great Accra and Ashanti regions). Notwithstanding, our find- ings suggest that the observed increase in the preva- lence of CS may be associated with some decreases in MMR from 501 per 100,000 live births in 1998 to 308 in 2017 [17]. Therefore, further studies will need to exam- ine with empirical evidence whether MMR decrease is a result of increased CS prevalence in Ghana. The cur- rent prevalence of 12.8% is higher than the average CS rate of 7.3% in sSA and the average of 3% in West Africa [14, 25]. With this favourable trend per WHO standards, the challenge now lies on the equality gaps in access for all women in Ghana. It is also important to look at the increase in births by CS as a function of improved acceptability of CS over the years coupled with gradual improvement in health system readiness to perform CS. In addition, while this finding may be a good sign for women who need CS when it is medically indicated, we decrease maternal mortality. These show the existence of TLTL (more prevalent in lower wealth quintiles, rural areas and more peripheral regions) and TMTS (more prevalent in richer quintiles, urban areas and the Great Accra and Ashanti regions). Notwithstanding, our find- ings suggest that the observed increase in the preva- lence of CS may be associated with some decreases in MMR from 501 per 100,000 live births in 1998 to 308 in 2017 [17]. Therefore, further studies will need to exam- ine with empirical evidence whether MMR decrease is a result of increased CS prevalence in Ghana. The cur- rent prevalence of 12.8% is higher than the average CS rate of 7.3% in sSA and the average of 3% in West Africa [14, 25]. With this favourable trend per WHO standards, the challenge now lies on the equality gaps in access for all women in Ghana. Discussion with higher levels of education as revealed by all four summary measures. For instance, in 2014, R and PAR measures of 3.0% (95% CI; 2.07-3.95) and 4.4% (95% CI; 3.35-5.51), respectively, revealed significant inequality in births by CS to the disadvantage of women who had no formal education. Socioeconomic inequalities in birth by CS still exist in Ghana and in fact have increased, despite the intro- duction of a free maternal health care policy in 2008 to bridge the gaps [20, 21]. The proportion of women who gave birth by CS increased substantially from 4.0% in 1998 to 12.8% in 2014 implying a percentage point increase of 8.8. Although a higher proportion of women may have benefitted from CS in 2014 compared to 1998, studies have shown that CS rates above 10% do not necessarily decrease maternal and perinatal mortal- ity [5, 22, 23]. Recent evidence has shown that birth by CS increased risks of maternal mortality [10]. This is a reflection of Miller et al.’s “too little, too late” (TLTL) and “too much, too soon” (TMTS) care [24]. In their study, Miller et al. indicate that TMTS denotes the ‘unneces- sary use of non-evidence-based interventions, as well as use of interventions that can be lifesaving when used appropriately, but harmful when applied routinely or overused’. Our findings of CS rates greater than 10% suggest the occurrence of TMTS and do not necessarily The results also showed substantial rural-urban inequality in favour of urban residents throughout the 16-year period. In 1998, both complex absolute meas- ure (PAR 4.5; 95% CI 4.09-4.99) and relative measure (PAF 114.4; 95% CI 103.08-125.71) showed signifi- cant urban-rural disparities in births by CS, however, the magnitude of the disparity declined in 2014 (PAF 46.8; 95% CI 40.91-52.76). In 1998, the complex abso- lute measure (D, PAR) revealed significant inequality in CS in favour of women in Greater Accra region as revealed by the PAR measure of 7.7% (95% CI 5.86- 9.58). There was an uneven trend with this observation in PAR, having increased to 8.3% in 2003, then subse- quently reducing to 3.8% in 2008 and rising again to 10.1% in 2014. Okyere et al. BMC Pregnancy and Childbirth (2022) 22:64 Page 5 of 9 Fig. 2  Trends in educational disparities in live births by caesarean section (CS) in Ghana from 1998 to 2014 Fig. Discussion It is also important to look at the increase in births by CS as a function of improved acceptability of CS over the years coupled with gradual improvement in health system readiness to perform CS. In addition, while this finding may be a good sign for women who need CS when it is medically indicated, we We observed that the prevalence of CS was high among women who were in the highest wealth quin- tile compared to those in the lowest quintile and this gap increased as the years went by. This is supported by many other studies [7, 21, 26–31]. Caesarean sections are profitable for physicians, especially considering that it takes shorter time than vaginal birth, allowing many procedures to be performed within that time [32]. Unap- proved fees charged by health professionals, indirect costs such as transport costs and other expenses outside the National Health Insurance Scheme (NHIS) and Free Maternal Healthcare Policy could serve as barriers for women in the lower wealth quintiles [33–35]. Women from high income families are more likely to afford addi- tional costs associated with CS and thus are more open to elective CS as an alternative to spontaneous birth, which without a well-established indication is a form of “too much, too soon” [24]. A more worrying finding is the widening of the pro-rich inequalities as the years go Okyere et al. BMC Pregnancy and Childbirth (2022) 22:64 Page 6 of 9 Fig. 3  Trends in rural-urban disparities in live births by caesarean section (CS) in Ghana from 1998 to 2014 Fig. 3  Trends in rural-urban disparities in live births by caesarean section (CS) in Ghana from 1998 to 2014 owing to fears of resulting pain and possible risks of infection, even when there are medical indications for CS, and would rather resort to spiritual interventions like prayers, hoping to eventually have vaginal birth [1, 39].h by. This prompts for evaluation of programs and policies such as the NHIS established in 2003 and the Free Mater- nal Health Care Program inaugurated in 2008 by the gov- ernment of Ghana with the aim of drastically reducing inequalities in health care including maternal health. The fact that CS was more prevalent among women in urban areas from 1998 to 2014 was not surprising, because availability of advanced health facilities and skilled birth attendants are more present in urban areas. Women in rural areas often have less equipped and dis- tant health facilities with few skilled birth attendants, making them more dependent on traditional births attendants. These lack technical expertise and license to perform CS, making access impossible [40]. Policies and programs must take into consideration this skewness and ensure that rural women are not discriminated when it comes to access to modern maternity care. The health system should thus have a well-functioning referral track in place.f While previous studies in Egypt [36] and Ghana [37] have reported a low likelihood of CS among women with at least secondary school education, other studies in Ghana [21], China [26] and Bangladesh [29] reported findings in support of our study. A plausible explana- tion for this finding could be that women with higher education wrongly tend to perceive CS to be a safer way of childbirth, and partly because they believe it interef- eres less with their work demands and leisure [38]. Another possible justification for the high patronage of CS by women with at least secondary school education could be related to increased autonomy and decision- making ability of educated women which allows them to recognise the relevance of CS when it is medically indicated [1, 4]. Women with low levels or no formal education are more likely to delay or refuse birth by CS, Regional differences in CS showed the highest preva- lence in the predominantly urban Greater Accra and Okyere et al. BMC Pregnancy and Childbirth (2022) 22:64 Page 7 of 9 Table 2  Inequality indices estimates of the factors associated with the prevalence of births by caesarean section, 1998-2014 (%) D Difference, R Ratio, PAR Population Attributable Risk, PAF Population Attributable Fraction, LB Lower Bound, UB Upper Bound Inequality dimension 1998 2003 2008 2014 Estimate LB UB Estimate LB UB Estimate LB UB Estimate LB UB Economic status   D 11.49 7.83 15.16 10.70 6.80 14.60 13.66 8.80 18.52 23.87 19.33 28.40   PAF 226.64 206.65 246.64 230.05 209.46 250.64 116.79 104.54 129.04 117.88 109.66 126.11   PAR 8.99 8.20 9.79 8.49 7.73 9.25 8.06 7.22 8.91 15.08 14.03 16.13   R 8.82 3.03 14.62 8.21 2.93 13.49 11.42 3.77 19.08 6.95 4.65 9.25 Education   D 4.68 2.94 6.43 4.75 2.79 6.71 7.55 4.70 10.40 11.50 8.99 14.01   PAF 63.65 46.24 81.06 74.32 57.92 90.73 58.97 43.46 74.48 34.61 26.17 43.05   PAR 2.53 1.83 3.22 2.74 2.14 3.35 4.07 3.00 5.14 4.43 3.35 5.51   R 3.59 1.68 5.50 3.83 1.79 5.87 3.20 1.55 4.86 3.01 2.07 3.95 Place of residence   D 5.99 3.77 8.20 5.80 3.57 8.04 5.88 2.94 8.82 10.90 7.84 13.96   PAF 114.39 103.08 125.71 105.21 93.46 116.97 52.87 42.18 63.56 46.84 40.91 52.76   PAR 4.54 4.09 4.99 3.88 3.45 4.32 3.65 2.91 4.39 5.99 5.23 6.75   R 3.38 2.10 4.66 4.28 2.38 6.18 2.26 1.41 3.10 2.38 1.71 3.06 Region   D 10.64 7.54 13.73 11.49 6.72 16.25 9.52 5.44 13.60 20.21 15.16 25.26   PAF 194.50 147.59 241.41 224.53 181.34 267.71 54.25 19.31 89.19 78.70 69.29 88.11   PAR 7.72 5.86 9.58 8.29 6.69 9.88 3.75 1.33 6.16 10.07 8.87 11.27   R 11.17 0.54 22.87 24.28 26.36 74.92 9.43 6.16 25.01 8.61 3.59 13.63 dices estimates of the factors associated with the prevalence of births by caesarean section, 1998-2014 (%) Central Regions, while the Northern, Upper East, Upper West and Volta regions are predominantly rural and have lower CS-rates. It is also noteworthy that there are higher poverty rates in the three Northern, Upper East, and Upper West regions compared to the regions in the south [41]. The magnitude of inequalities between rural and urban areas with regard to CS prevalence, however, was reduced between 2003 and 2014, when the NHIS and Free Maternal Health Policy in Ghana were intro- duced. Nevertheless, one cannot conclude that this is mainly attributable to the introduction of the NHIS. Fur- ther studies could explore this association to inform the literature. recommend that women whose condition requires CS, get the necessary support for safe CS without any sys- temic disparities based on socio-economic status. Given that we used existing data from the HEAT soft- ware, we were unable to account for singleton and mul- tiple births separately. Moreover, while there was an overall increase in the proportion of birth by CS over the years, we saw an uneven trend in the dimension of ine- qualities signifying the need for sustained policy action despite transient challenges that may be encountered in advocacy for safe and appropriate birth by CS among women who have an indication for CS. The findings of persistent inequities in CS among women in Ghana is a microcosm of the inequities in access to CS globally where extremes of access to CS have been documented with some women having it “too much, too soon” whiles others have it “too little”, “too late” [24]. While we advocate for the reduction of dispari- ties in birth by CS, it is also worth noting that complica- tions of CS exist. Women should undergo CS only when there is a genuine indication for it. Although we are aware of the growing popularity of elective CS among women, it is equally important to communicate those potential complications with pregnant women for informed deci- sion making. Despite potential complications, we would Consent for publication Not applicable. Consent for publication Not applicable. CS: Caesarean section; CI: Confidence Intervals; GDHS: Ghana Demo‑ graphic and Health Survey; GHS: Ghana Health Service; GSS: Ghana Statistical Service; HEAT: Health Equity Assessment Toolkit; LMICs: Low and Middle Income Countries; MMR: Maternal mortality ratio; NHIS: National Health Insurance; PAF: Population Attributable Fraction; PAR: Population Attributable Risks; SDGs: Sustainable Development Goals; WHO: World Health Organization. Availability of data and materials The datasets generated and/or analysed (including figures) are available in the WHO’s HEAT version 3 [https://​www.​who.​int/​gho/​health_​equity/​asses​sment_​ toolk​it/​en/]. Funding We recommend the use of decomposition analysis to assess factors that could explain disparities in CS across various dimensions of inequality observed in this study. We were unable to differentiate emergency CS from elec- tive CS which would have helped to situate our discussion in context. We were also unable to account for multiple pregnancies, which is an important risk factor for birth by CS. In addition, the study used secondary data with- out any influence over the selection and measurement of the variables. The effects of key variables such as place of birth (i.e., Health Centre, Polyclinic or Hospital) and type of health facility (public vs private) could not be investi- gated. Moreover, there has not been a recent DHS survey in Ghana making the last estimate in 2014 as the most recent one for discussion. Thus, the findings may not necessarily reflect current trends. No funding was received for this work. Acknowledgments reliability of our findings. Nonetheless, there are some limitations that need to be acknowledged. Also, consid- ering that the focus of our sample was on women with live births, our study excluded women with stillbirths who have been found to experience higher prevalence of CS. Given that the DHS estimates of the rate of birth by CS exclude women who underwent CS with a still- birth in the samples, our findings may underreport the actual rate of birth by CS among women at reproduc- tive age in Ghana. We acknowledge WHO for making HEAT software available to the public domain for free. Authors’ contributions AS, JO, EB, HOD and BOA contributed to the conception and design of the study, interpreted data, and prepared the first draft. AS, JO, EB, HOD and BOA contributed to the design, interpreted data and critically reviewed the manuscript for intellectual content. AS, JO, EB, HOD and BOA helped with data interpretation and critically reviewed the manuscript for intellectual content. JO and HOD had final responsibility to submit the manuscript for publication. All authors read and revised drafts of the paper and approved the final version. Received: 18 December 2020 Accepted: 3 January 2022 Received: 18 December 2020 Accepted: 3 January 2022 Received: 18 December 2020 Accepted: 3 January 2022 Strengths and limitations Our study has several strengths. First, to the best of our knowledge, this study is the first to examine inequali- ties in prevalence of CS in Ghana. Findings thus can be essential in guiding both policy and future research on CS in Ghana. Secondly, the use of both simple and complex measures of inequity contributes to the qual- ity of our results as the limitations of one measure is compensated by combination with others. Thirdly, by presenting the findings for each subgroup, we provide a benchmark for the government to identify where atten- tion is more needed in the midst of limited resources. Finally, using WHO’s HEAT software confirms the Okyere et al. BMC Pregnancy and Childbirth (2022) 22:64 Page 8 of 9 References 1. Ushie BA, Udoh EE, Ajayi AI. Examining inequities in access to delivery by caesarean section in Nigeria. PLoS One. 2019;14(8):e0221778. 2. WHO: Trends in maternal mortality: 1990–2014: estimates from WHO, UNICEF, UNFPA, World Bank Group and the United Nations population division: executive summary. 2014. 3. Waniala I, Nakiseka S, Nambi W, et al. Prevalence, indications, and community perceptions of caesarean section delivery in Ngora district, eastern Uganda: mixed method study. Obstet Gynecol Int. 2020;2020:1–11. 4. Yaya S, Bishwajit G, Shah V. Wealth, education and urban–rural inequality and maternal healthcare service usage in Malawi. BMJ Glob Health. 2016;1(2):1–12. 5. World Health Organization. Trends in maternal mortality: 1990-2015: estimates from WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. Geneva: World Health Organization; 2015. 6. Boerma T, Ronsmans C, Melesse DY, et al. Global epidemiology of use of and disparities in caesarean sections. Lancet. 2018;392:1341–8. 1. Ushie BA, Udoh EE, Ajayi AI. Examining inequities in access to delivery by caesarean section in Nigeria. PLoS One. 2019;14(8):e0221778. 2. WHO: Trends in maternal mortality: 1990–2014: estimates from WHO, UNICEF, UNFPA, World Bank Group and the United Nations population division: executive summary. 2014. 3. Waniala I, Nakiseka S, Nambi W, et al. Prevalence, indications, and community perceptions of caesarean section delivery in Ngora district, eastern Uganda: mixed method study. Obstet Gynecol Int. 2020;2020:1–11. 4. Yaya S, Bishwajit G, Shah V. Wealth, education and urban–rural inequality and maternal healthcare service usage in Malawi. BMJ Glob Health. 2016;1(2):1–12. Declarations Ethics approval and consent to participate pp p p All GDHS survey data are freely available to the public. All surveys were approved by ICF international and the Ghana Health Service. The Measure DHS Program also ensured that the survey protocols complied with the U.S. Department of Health and Human Services regulations for protection of human subjects. Ethical approval was thus not required since the data are available in the public domain. Author details 1 1 Department of Population and Health, University of Cape Coast, Cape Coast, Ghana. 2 Research Department, FOCOS Orthopaedic Hospital, Accra, Ghana. 3 College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, QLD, Australia. 4 Department of Estate Management, Takoradi Technical University, Takoradi, Ghana. 5 School of Public Health, Fac‑ ulty of Health, University of Technology Sydney, Ultimo, Australia. Ghana experienced disparity in the proportion of birth by CS, which increased over time between 1998 and 2014. Our findings indicate that more work needs to be done to ensure that all subpopulations that need medically necessary CS are given access to maternity care to avoid unnecessary maternal and perinatal deaths. Nevertheless, provision of CS should also be done accurately to reduce deaths associated with complications of unnecessary CS. Given the increase in the proportion of birth by CS over the years, it is important that we begin to explore adverse events as well as effects on MMR in Ghana. Therefore, we recommend that future studies should concentrate on reasons of increased birth by CS and advocate the audit cycle in maternity care to reduce maternal and perinatal mortality and morbidity in Ghana. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in pub‑ lished maps and institutional affiliations. Springer Nature remains neutral with regard to jurisdictional claims in pub‑ lished maps and institutional affiliations. 19. World Health Organization. Handbook on health inequality monitoring: with a special focus on low-and middle-income countries. Geneva: World Health Organization; 2013. g 20. Dankwah E, Kirychuk S, Zeng W, et al. Socioeconomic inequities in the use of caesarean section delivery in Ghana: a cross-sectional study using nationally representative data. Int J Equity Health. 2019;18:162. 21. Manyeh AK, Amu A, Akpakli DE, Williams J, Gyapong M. Socioeconomic and demographic factors associated with caesarean section delivery in southern Ghana: evidence from INDEPTH network member site. BMC Pregnancy Childbirth. 2018;18(1):405. 22. Ye J, Zhang J, Mikolajczyk R, Torloni MR, Gülmezoglu AM, Betran AP. Asso‑ ciation between rates of caesarean section and maternal and neonatal mortality in the 21st century: a worldwide population-based ecological study with longitudinal data. BJOG. 2016;123(5):745–53. 23. World Data Atlas. Ghana – maternal mortality ratio: Knoema; 2020. https://​knoema.​com/​atlas/​Ghana/​Mater​nal-​morta​lity-​ratio Accessed 8 Sept 2020 24. Miller S, Abalos E, Chamillard M, et al. Beyond too little, too late and too much, too soon: a pathway towards evidence-based, respectful mater‑ nity care worldwide. Lancet. 2016;388:2176–92. • fast, convenient online submission • thorough peer review by experienced researchers in your field • rapid publication on acceptance • support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations maximum visibility for your research: over 100M website views per year • At BMC, research is always in progress. Learn more biomedcentral.com/submissions Ready to submit your research Ready to submit your research ? Choose BMC and benefit from: ? Choose BMC and benefit from: • fast, convenient online submission • thorough peer review by experienced researchers in your field • rapid publication on acceptance • support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations maximum visibility for your research: over 100M website views per year • At BMC, research is always in progress. Learn more biomedcentral.com/submissions Ready to submit your research Ready to submit your research ? Choose BMC and benefit from: ? Choose BMC and benefit from: 25. Prah J, Kudom A, Afrifa A, Abdulai M, Sirikyi I, Abu E. Abbreviations CS: Caesarean section; CI: Confidence Intervals; GDHS: Ghana Demo‑ graphic and Health Survey; GHS: Ghana Health Service; GSS: Ghana Statistical Service; HEAT: Health Equity Assessment Toolkit; LMICs: Low and Middle Income Countries; MMR: Maternal mortality ratio; NHIS: National Health Insurance; PAF: Population Attributable Fraction; PAR: Population Attributable Risks; SDGs: Sustainable Development Goals; WHO: World Health Organization. 5. World Health Organization. Trends in maternal mortality: 1990-2015: estimates from WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. Geneva: World Health Organization; 2015. 5. World Health Organization. Trends in maternal mortality: 1990-2015: estimates from WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. Geneva: World Health Organization; 2015. 6. Boerma T, Ronsmans C, Melesse DY, et al. Global epidemiology of use of and disparities in caesarean sections. Lancet. 2018;392:1341–8. 6. Boerma T, Ronsmans C, Melesse DY, et al. Global epidemiology of use of and disparities in caesarean sections. Lancet. 2018;392:1341–8. Page 9 of 9 Okyere et al. BMC Pregnancy and Childbirth (2022) 22:64 Okyere et al. BMC Pregnancy and Childbirth (2022) 22:64 7. Yaya S, Uthman OA, Amouzou A, Bishwajit G. Disparities in caesarean sec‑ tion prevalence and determinants across sub-Saharan Africa countries. Glob Health Res Policy. 2018;3(1):19. 29. Ghosh S. Increasing trend in caesarean section delivery in India: role of medicalisation of maternal health. Bangalore: Institute for Social and Economic Change; 2010. 8. Bishop D, Dyer RA, Maswime S, et al. Maternal and neonatal outcomes after caesarean delivery in the African Surgical Outcomes Study: a 7-day prospective observational cohort study. Lancet Glob Health. 2019;7(4):e513–22. 30. Begum T, Rahman A, Nababan H, et al. Indications and determinants of caesarean section delivery: evidence from a population-based study in Matlab, Bangladesh. PLoS One. 2017;12(11):e0188074. 31. Long Q, Kempas T, Madede T, Klemetti R, Hemminki E. Caesarean section rates in Mozambique. BMC Pregnancy Childbirth. 2015;15(1):253. 9. Sobhy S, Arroyo-Manzano D, Murugesu N, et al. Maternal and perinatal mortality and complications associated with caesarean section in low- income and middle-income countries: a systematic review and meta- analysis. Lancet. 2019;393:1973–82. 32. Rebelo F, Da Rocha CM, Cortes TR, Dutra CL, Kac G. High cesarean preva‑ lence in a national population-based study in Brazil: the role of private practice. Acta Obstet Gynecol Scand. 2010;89(7):903–8. 10. Dikete M, Coppieters Y, Trigaux P, et al. Variation of caesarean section rates in sub-Saharan Africa: a literature review. J Gynecol Res Obstet. 2019;5(2):042–7. 33. Abbreviations Trends and inequi‑ ties in use of maternal health care services in Bangladesh, 1991-2011. PLoS One. 2015;10(3):e0120309. 17. Ghana Statistical Service (GSS), Ghana Health Service (GHS), & ICF. Ghana maternal health survey 2017. Accra: GSS, GHS, and ICF; 2018. Available at https://​dhspr​ogram.​com/​pubs/​pdf/​FR340/​FR340.​pdf. Accessed 24 Nov 2020 41. Ghana Statistical Service. Ghana poverty mapping report. Accra: Ghana Statistical Service; 2015. 41. Ghana Statistical Service. Ghana poverty mapping report. Accra: Ghana Statistical Service; 2015. 18. WHO. Health Equity Assessment Toolkit (HEAT): software for exploring and comparing health inequities in countries; 2019. Available at http://​ bmcme​dresm​ethod​ol.​biome​dcent​ral.​com.​proxy.​bib.​uotta​wa.​ca/​artic​les/​ 10.​1186/​s12874-​016-​0229-9%​3e%​3e. Accessed 6 Sept 2020. Abbreviations Ravit M, Philibert A, Tourigny C, Traore M, Coulibaly A, Dumont A, et al. The hidden costs of a free caesarean section policy in West Africa (Kayes Region, Mali). Mat Child Health J. 2015;19(8):1734–43. 34. Lange IL, Kanhonou L, Goufodji S, Ronsmans C, Filippi V. The costs of ‘free’: experiences of facility-based childbirth after Benin’s caesarean section exemption policy. Soc Sci Med. 2016;168:53–62. 11. Belizán JM, Minckas N, McClure EM, et al. An approach to identify a minimum and rational proportion of caesarean sections in resource-poor settings. Lancet Glob Health. 2018;6(8):e894–901. 12. Gibbons L, Belizán JM, Lauer JA, Betrán AP, Merialdi M, Althabe F. The global numbers and costs of additionally needed and unnecessary caesarean sections performed per year: overuse as a barrier to universal coverage. World Health Rep. 2010;30(1):1–31. 35. Asante FA, Chikwama C, Daniels A, Armar-Klemesu M. Evaluating the economic outcomes of the policy of fee exemption for maternal delivery care in Ghana. Ghana Med J. 2007;41(3):110–7. 36. Yassin K, Saida G. Levels and determinants of caesarean deliveries in Egypt: pathways to rationalization. Int J World Health Soc Polit. 2012;7(2):1–3. 13. Betrán AP, Torloni MR, Zhang JJ, et al. WHO statement on caesarean sec‑ tion rates. BJOG. 2016;123(5):667–70. 14. Lauer JA, Betrán AP, Merialdi M, Wojdyla D. Determinants of caesarean section rates in developed countries: supply, demand and opportunities for control. World Health Rep. 2010;29:1–22. 37. Apanga PA, Awoonor-Williams JK. Predictors of caesarean section in northern Ghana: a case-control study. Pan Afr Med J. 2018;29(1):1–1. 38. Dickson KS, Darteh EK, Kumi-Kyereme A. Providers of antenatal care ser‑ vices in Ghana: evidence from Ghana demographic and health surveys 1988–2014. BMC Health Serv. 2017;17(1):203. 15. Wise J. Alarming global rise in caesarean births, figures show. BMJ. 2018;363:k4319. 39. Sunday-Adeoye I, Kalu CA. Pregnant Nigerian women’s view of cesarean section. Nig J Clin Pract. 2011;14(3):276–9. 16. Boatin AA, Schlotheuber A, Betran AP, et al. Within country inequities in caesarean section rates: observational study of 72 low and middle income countries. BMJ. 2018;360:k55. 39. Sunday-Adeoye I, Kalu CA. Pregnant Nigerian women’s view of cesarean section. Nig J Clin Pract. 2011;14(3):276–9. 40. Anwar I, Nababan HY, Mostari S, Rahman A, Khan JA. Trends and inequi‑ ties in use of maternal health care services in Bangladesh, 1991-2011. PLoS One. 2015;10(3):e0120309. 40. Anwar I, Nababan HY, Mostari S, Rahman A, Khan JA. 28. Kamal SM. Preference for institutional delivery and caesarean sections in Bangladesh. J Health Popul Nutr. 2013;31(1):96. Publisher’s Note Caesarean section in a primary health facility in Ghana: clinical indications and feto-maternal outcomes. J Public Health Afr. 2017;8(2):704. 26. Feng XL, Xu L, Guo Y, Ronsmans C. Factors influencing rising caesarean section rates in China between 1988 and 2008. Bull World Health Organ. 2012;90:30–9A. 27. Hou X, Rakhshani NS, Iunes R. Factors associated with high Cesarean deliveries in China and Brazil-a call for reducing elective surger‑ ies in moving towards Universal Health Coverage. J Hospital Admin. 2014;3(5):67–78. 28. Kamal SM. Preference for institutional delivery and caesarean sections in Bangladesh. J Health Popul Nutr. 2013;31(1):96.
https://openalex.org/W4311921491
https://www.researchsquare.com/article/rs-2329802/latest.pdf
English
null
Oral Health Status and Hygiene Practices Among Visually Impaired Adolescents From a School in Kenya
Research Square (Research Square)
2,022
cc-by
6,012
Oral Health Status and Hygiene Practices Among Visually Impaired Adolescents From a School in Kenya Maureen Macharia  (  mmaureen778@gmail.com ) Maureen Macharia  (  mmaureen778@gmail.com ) University of Nairobi Mary Masiga  University of Nairobi Nathan Psiwa  University of Nairobi Janella Bermudez  Advanced Education in General Dentistry Program Ana Lucia Seminario  University of Washington Arthur Kemoli  University of Nairobi Results There were 69 (43.4%) and 90 (56.6%) participants in Category I and II visual impairment respectively, 85 (53.5%) were male and 74 (46.5%) were female. Study participants were divided into three age categories: 10–12 years (30.2%), 13–15 years (42.1%), and 16–19 years (27.7%), with an overall mean age of 13.9 ±  2.3. There was a statistically significant difference between visual impairment and age (p = 0.04). All participants brushed their teeth, majority (67.3%) brushed two or more times daily. Only 41.5% of the participants replaced their toothbrushes at 3 months. Sex and age influenced frequency of toothbrush replacement (p = 0.04). The average plaque score and gingival score index was 0.95 ± 0.45 and 0.28 ±  0.25 respectively, with gingivitis prevalence of 88.1%. Plaque score index had a statistically significant association with the gingival score index (p = 0.01). Overall dental caries prevalence was 44.7%, [42.1%)] permanent dentition and [8.2%] deciduous dentition. Mean DMFT was 0.44 ± 0.60 with a statistically significant association with age (p = 0.03), sex (p = 0.05) and visual impairment (p = 0.04). Mean dmft was 0.12 ± 0.32 with a statistically significant association with plaque score index (p = 0.04). Oral hygiene practices did not influence oral hygiene and dental caries status. However, a statistically significant association was reported between frequency of toothbrush replacement and gingival score index (p =  0.00). Background Visual impairment afflicts a significant population globally. The aim of this study was to determine the oral health status and oral hygiene practices among visually impaired adolescents from a school in Kenya. Research Article Keywords: Oral health status, Oral hygiene practices, Visual impairment, Adolescents, Kenya Posted Date: December 19th, 2022 DOI: https://doi.org/10.21203/rs.3.rs-2329802/v1 License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Version of Record: A version of this preprint was published at BMC Oral Health on October 7th, 2023. See the published version at https://doi.org/10.1186/s12903-023-03428-7. Page 1/16 Methods A descriptive cross-sectional study was carried out among 159 adolescents aged 10–19 years attending the largest public primary boarding school for the blind in Kenya. A questionnaire was used to record participants’ social demographic variables and oral hygiene practices. Clinical examination was undertaken to assess oral health status which consisted of oral hygiene, gingival health, and dental caries. Background Visual impairment is a sensory deterioration recognized as a major public health concern and is ranked sixth in the global burden of disease in relation to disability-adjusted life-years. It ranges from low vision to total blindness, and the World Health Organization (WHO) has classified it in terms of visual acuity as mild (< 6/12 − 6/18), moderate (< 6/18 − 6/60), severe (< 6/60 − 3/30), and blind (< 3/60). This means that a blind person with a visual acuity of < 3/60 would have to stand 3 meters to see what a person with normal vision would see at 60 meters. Globally, a total of 2.2 billion people are afflicted by visual impairment (1), of these, 14 million children are blind (2). The majority (75%) of these children live in the poorest regions in Africa and Asia(3) .In Kenya, the prevalence of pediatric visual impairment has been reported to be 3.1% (4). Accurate measurements of visual acuity are important as they serve to determine eligibility for government support in some countries (5). A good example is an access to education in the United States of America for children with special health needs that focuses on self-care, social skills, and vocational training (5). However, in school, it is more useful for educators to classify visual impairment based on students’ ability to use their visual and other channels, such as tactile and auditory senses for learning (6). The Low Vision Project – Kenya classifies students with visual impairment into five groups (7). Students in category I are totally blind, have no perception of light, and are educated in braille. Students in category II have low vision, which is not adequate to read print, hence, are educated in Braille. Students in category III have low vision and can be trained to use optical low-vision devices such as magnifying glasses to read and write print. Students in category IV have low vision and can be educated in print using special methods such as the use of large print but without the use of optical low-vision devices. Students in category V are not low visioned as their sight is above 6/18 and do not need special education if their sight remains constant (7). Good oral health constitutes a key aspect of general health and the quality of life of the individual (8). Conclusions The study reported general good oral hygiene, prevalent gingivitis (88.1%), and almost half of the study population affected by dental caries (44.7%). Most participants were unaware of using fluoridated Page 2/16 Page 2/16 toothpaste and of needing to change toothbrushes within 3 months. Frequency of toothbrush replacement was reported to influence gingival score index. Methods This was a descriptive cross-sectional study conducted at the Thika Primary School for the Blind in Kiambu County, Central Kenya. The school is the largest of the four institutionalized public primary schools serving children with visual impairment in the country. Kenya is comprised of 47 counties, however, for purposes of this study, the counties were stratified into 10 regions according to their geographical units (Fig. 1): region 1 (Coast), region 2 (North Eastern), region 3 (Upper Eastern), region 4 (Lower Eastern), region 5 (Central), region 6 (Upper Rift Valley), region 7 (Lower Rift Valley), region 8 (Western), region 9 (Nyanza), and region 10 (Nairobi) (14) The study participants were aged 10–19 years old based on the definition of adolescents by the United Nations Children’s Fund (UNICEF). The sample size was determined using the formula proposed by Fisher et al (15). Assuming the children with dental caries to be 50% and considering a 95% confidence level and 5% degree of accuracy. An estimated population size of 209 was used and the minimum sample size was computed to 152 after adjusting for 10% attrition. However, all participants who met the inclusion criteria were included in the study and the final sample size was 159, representing 60% of the school population. Proportionate, stratified random sampling was employed in the recruitment of study participants. The study population was stratified into three age groups: mixed dentition consisting of 10–12 years old and permanent dentition consisting of 13–15 and 16–19 years old. In each stratum, an alphabetical listing of names was obtained and numbered serially, and random numbers were generated by the computer that was used to select the requisite number of individuals in each stratum. Subjects eligible for the study inclusion were adolescents aged 10–19 years with visual educational categories I and II, who used braille as their mode of learning, assented to the study, and whose parents consented to the study. Subjects were excluded from the study enrolment if they had physically or mentally debilitating conditions (E.g., Cerebral Palsy or syndromes such as Down’s syndrome) which may have impacted oral health status and skill to carry out oral hygiene practices. Cerebral Palsy or syndromes such as Down’s syndrome) which may have impacted oral health status and skill to carry out oral hygiene practices. Background Oral hygiene practices are associated with oral diseases, such as dental caries, and play a major role in the overall dental health of an individual. Nonetheless, maintenance of good oral health is particularly challenging for the visually impaired and has been reported to be poor in comparison to the general population (3, 9). Related factors include difficulty in attaining good oral hygiene and the inapplicability of visual aids used in the demonstration of oral hygiene instructions (10, 11). Challenges for maintaining adequate oral health among visually impaired children can be aggravated in low- and middle-income countries due to limited access to oral healthcare. In Kenya, there is a high burden of oral diseases among the pediatric population. Dental caries and gingival bleeding prevalence among children and adolescents (5,12, and 15 year - olds) have been reported to be 23.9% and 75.7%, respectively (12). However, there is scarce evidence, especially in Sub-Saharan countries, including Kenya, on oral health status and oral hygiene practices among visually impaired children and adolescents (13). Page 3/16 Page 3/16 The purpose of the study was to answer the following question: ‘Among adolescents with category I and II visual impairment who attended the largest public primary boarding school for the Blind in Kenya, did oral hygiene practices influence oral hygiene status’. We hypothesized that good oral hygiene practices were associated with a lower prevalence of oral diseases. The specific aim of the study was to determine the oral health status and oral hygiene practices among visually impaired adolescents attending Thika Primary School for the Blind in Kiambu County, Kenya. Results from this study will inform relevant health planners in the formulation of oral health programs for visually impaired children with the aim of promoting and providing continuous and sustainable oral health care. Data Collection Calibration for the principal investigator (PI) was carried by an experienced pediatric dentist at Lady Northey Dental Hospital. A modified questionnaire adopted from the Simplified Oral Health Questionnaire Page 4/16 Page 4/16 for Children World Health Organization was used (16). The questionnaire contained both open and close- ended questions and was used to record participants’ social demographic variables and oral hygiene practices. It was pre-tested on adolescents aged between 10–19 years at the University of Nairobi Dental Hospital, to check the suitability, simplicity, and ease of understanding, as well as to estimate the time taken to complete the questionnaire. It was then administered by the PI to the study participants before a clinical examination of the participants was done. A clinical examination was undertaken by the PI to assess oral health status which consisted of oral hygiene, gingival health, and dental caries. The clinical findings were recorded in a modified WHO Oral Health Assessment Form for Children by a trained data clerk assistant (16). Oral hygiene status was assessed first using the plaque index score described by Silness and Löe (17). Plaque score findings were classified as 0- no plaque; 1- film of plaque adhering to the free gingival margin and adjacent area of the tooth; 2- moderate accumulation of the soft deposits within the gingival pocket or the tooth and gingival margin; 3-abundance of soft matter within the gingival pocket and or on the tooth and gingival margin. Gingival health was assessed after the plaque score, using the Community Periodontal Index (CPI) Modified (16). Briefly, the WHO CPI dental probe was gently inserted between the gingiva and the tooth to explore the full extent of the sulcus. Gingival score findings were categorized as presence or absence of bleeding.Dental caries was determined using visual and tactile examination. Individual teeth were isolated and dried using sterile gauze in a systematic pattern from one tooth to the adjacent one in each quadrant. Each tooth was recorded as decayed/Decayed, missing/Missing, or filled/Filled due to caries; [dmft (for primary dentition) /DMFT (for permanent dentition)] (16) Data analysis The data which had been recorded on paper forms was later entered into a computer database and analyzed using Statistical Package for Social Sciences (SPSS) version 23.0 of Windows. Characteristics of the study population were summarized using descriptive statistics. Analysis of Variance (ANOVA) was used to test differences between oral health status (plaque and gingival scores and dental caries) by age group. An Independent t-test was used to test for a statistically significant difference between oral health status by the category of visual impairment and by sex. Pearson’s Chi-square was used to assess bivariate relationships between oral hygiene practices by sex, age group and category of visual impairment and between category of visual impairment by sex and age group. Spearman’s correlation was used to assess associations between oral hygiene practices and oral health status. The critical value was set at 5%. General characteristics An estimated population size of 209 was used during the study and the sample size was computed to 152 after adjusting for 10% attrition. There were 69 (43.4%) and 90 (56.6%) participants in Category I and Page 5/16 Page 5/16 II visual impairment respectively. Of the total participants, 85 (53.5%) were male and 74 (46.5%) were female. The participants were divided into three age categories: 10–12 years (30.2%), 13–15 years (42.1%), and 16–19 years (27.7%), with an overall mean age of 13.9 ± 2.3) (Table 1). There was a statistically significant difference between visual impairment and age (p = 0.04). The Central region of the country had the largest representation (54 or 32.7%), while the Coastal and North-Eastern regions had the least representation (1 or 0.6%) (Fig. 1). Demographic N = 159 (%) Table 1 Demographic characteristics of the study population Visual impairment   Category I 69 (43.4%) Category II 90 (56.6%) Sex   Male 85 (53.5%) Female 74 (46.5%) Age   10–12 yrs. 48 (30.2%) 13–15 yrs. 67 (42.1%) 16–19 yrs. 44 (27.7%) Mean Age (SD) 13.9 ± 2.3 Oral Hygiene practice All participants reported to brush their teeth, majority (67.3%) brushed two or more times daily, while (32.7%) brushed less than twice a day. All participants utilized commercial toothbrushes, with (41.5%) replacing the toothbrushes at 3 months. There was a statistically significant association between frequency of toothbrush replacement, age and sex (p = 0.04). Other adjunct devices used included wooden toothpicks (62.9%) and chew sticks/"mswaki” (25.2%). Most (99.4%) of the participants reported using toothpaste with the majority (93.1%) unaware if the toothpaste they used contained fluoride. Most of the participants (86.7%) rinsed their mouth with water after meals, while (6.3%) seldom rinsed, and (7%) did not rinse at all. (Table 2). Page 6/16 Table 2 Oral hygiene practices in relation to the visual impairment Oral hygiene practices in relation to the visual impairment Oral Hygiene practices Type of visual impairment p-value Category I Category II   N (%) N (%)   Frequency of tooth brushing Two or more times a day 49(71.0%) 58(64.4%) 0.06 Less than twice daily 20(27.9%) 32(35.6%)   Adjunct toothbrush devices Wooden toothpicks 41(59.4%) 60(66.7%) 0.41 Plastic Toothpicks 1(1.4%) 2(2.2%) 1.00* Dental Floss 5(7.2%) 5(5.6%) 0.75 Charcoal 9(13.0%) 8(9.0%) 0.42 Chew stick/mswaki 28(41.2%) 40(44.9%) 0.38 Use of fluoridate toothpaste Yes 2 (2.9%) 2(2.2%) 0.96 No 3 (4.3%) 4 (4.4%) Don’t know 64(92.8%) 84(93.3%)   Mouth rinsing after meals Yes 61(89.7%) 76(84.4%) 0.62 No 4 (5.9%) 7(7.8%) Seldom 3 (4.4%) 7(7.8%) *Fisher exact test Oral hygiene status and gingival health The average plaque score among all participants was 0.95 ± 0.45. Female participants had a lower plaque score (0.88 ± 0.44) compared with the males (1.02 ± 0.45) (p = 1.88). The plaque score was higher (0.99 ± 0.47) among participants in category 13–15-year-old and lowest (0.87 ± 0.44) among those in category 10–12 years old. The overall prevalence of gingivitis was 88.1% with a mean gingival score index of 0.28 ± 0.25. Gingival scores significantly varied by age (p = 0.02). Adolescents aged 16–19 years had the highest gingival score index (0.34 + 0.28), while those aged 10–12 years had the least gingival score index (0.20 + 0.21) (Table 3). The overall Plaque score index of 0.95 + 0.45 showed a statistically significant association when related to the gingival score index (p = 0.01). This is suggestive of the fact that poor oral hygiene contributed to Page 7/16 Page 7/16 an increase in the gingival score index. Table 3. Distribution of participants by oral hygiene status and gingival inflammation Table 3. Distribution of participants by oral hygiene status and gingival inflammation Dental caries The overall prevalence of dental caries was 44.7% (n = 71), and it was higher among participants in permanent dentition [42.1% (n = 67)] compared to those in deciduous dentition [8.2% (n = 13)]. In the case of participants in permanent dentition, dental caries prevalence was slightly higher at [21.9% (n = 35)] among male participants compared to female participants at [20.2% (n = 31)]. Among the different age categories, the prevalence of dental caries was highest at [17.6% (n = 28)] among the 10–12-year-olds. Three participants (1.9%) in the permanent dentition had missing teeth secondary to dental caries while no filled teeth were reported across the sample population. The mean DMFT was 0.44 ± 0.60 with the “D” component being higher (0.42 ± 0.50) than the “M” component (0.02 ± 0.14). There was a statistically significant association between DMFT and sex (p = 0.03) and DMFT and age (p = 0.05). Adolescents in category I visual impairment, but in permanent dentition had a mean DMFT of 0.44 ± 0.67 while those in Category II had a mean DMFT of 0.40 ± 0.61. The difference between the mean DMFT in the two categories of visual impairment was statistically significant (p = 0.04) (Table 4). In the deciduous dentition, the dental caries prevalence was slightly higher [4.4% (n = 7)] among male children compared to female children [3.8% (n = 6)], while in the different age categories, children aged 10–12 years had the highest dental caries prevalence [7.4% (n = 9)]. The mean dmft was 0.12 ± 0.32 composed solely of the “d” component (Table 4). There was a statistically significant association between dmft and plaque score index (p = 0.04). Page 8/16 Page 8/16 Table 4. Dental caries Dental caries prevalence and experience in permanent and primary dentition Characteristic Permanent Dentition Primary Dentition Dental caries prevalence DMFT p- value* Dental caries prevalence dmft p- value* Sex Male Female 35(21.9%) 31(20.2%) 0.42 ± 0.65 0.46 ± 0.62 0.03 7 (4.4%) 6 (3.8%) 0.08 ±  0.28 0.08 ±  0.27 0.53 Age 10–12 yrs 13–15 yrs 16–19 yrs 28(17.6%) 22(13.8%) 17(10.6%) 0.42 ± 0.20 0.40 ± 0.00 0.38 ± 0.15 0.05 9 (7.4%) 4 (0.8%) 0 (0.0%) 0.19 ±  0.39 0.06 +  0.24 0.00 +  0.00 0.38 Visual impairment Category I Category II 27 (42%) 40(44.4%) 0.40 ± 0.67 0.44 ± 0.61 0.04 11 (12.3%) 2 (1.0%) 0.01 ±  0.12 0.13 +  0.34 0.33 Overall   67(42.1%) 0.44 ± 0.60   13 (8.2%) 0.12 ±  0.32   *Difference in DMFT/dmft values ntal caries prevalence and experience in permanent and primary dentition Table 4. Dental caries prevalence and experience in permanent and primary dentition *Difference in DMFT/dmft values *Difference in DMFT/dmft values *Difference in DMFT/dmft values Discussion The goal of this study was to determine the oral health status and oral hygiene practices among visually impaired adolescents attending the largest public primary boarding school for the blind in Kenya. It was hypothesized that good oral hygiene practices were associated with a lower prevalence of oral diseases. This study aimed at determining the prevalence of dental caries and gingivitis, evaluating oral hygiene status, investigating oral hygiene practices, and determining the association between oral hygiene practices and oral health status. In the current study, we found gingivitis to be highly prevalent (88.1%), almost half of the study population to be affected by dental caries (44.7%), and the frequency of toothbrush replacement to be significantly associated with age and gender. Null hypothesis was tested for association between oral hygiene practices and oral health status. Oral hygiene practices did not influence oral hygiene status and dental caries status, however, an association was reported between frequency of toothbrush replacement and gingival index score (p = 0.00). The study participants were grouped into Category I (43.4%) and II (56.6%) visual impairment and educated using Braille. A statistically significant association was found between the category of visual impairment and age (p = Page 9/16 0.04), with more of the older and younger participants grouped in category I and category II respectively. This could have been a result of the natural course of visual impairment, which worsens over time if left untreated (18). In our study, the Central Region of the country had the largest representation (32.7%) of the study population, which may have been attributed to the geographic proximity of the region to the school. Nairobi, the capital city of Kenya, had low representation (1.26%), and perhaps this was due to its higher concentration of schools with integrated learning that include special units for visually impaired children (19). This is indicative of a school model that could be expanded to other regions for the benefit of the visually impaired and could be a relief to the burden of education for the Central Region. We found that all the participants in the study brushed their teeth using commercial toothbrushes and toothpaste (99.4%), a finding that is similar to previous studies by Azrina (20)and Ali (21). Discussion Even though the majority of our surveyed children (93.1%) did not know if the toothpaste they used contained fluoride, most of the commercially available toothpastes in Kenya are fluoridated, and hence the deduction that most of the children could be experiencing the protective benefit against caries conferred by fluoride. In the current study, most (67.3%) participants brushed two or more times daily, perhaps tooth brushing habits could be attributed to the institutionalized nature of the school, providing standardized enforcement of oral hygiene measures. This attribute is in line with the WHO guidelines where instilling school oral health programs and preventive habits like daily tooth brushing in children, are advocated (22). We also found that study participants used adjunct devices in cleaning their teeth. Modified wooden toothpicks obtained from trees within the school compound had the highest application (62.9%) of all the devices. These results contrast with those in a study carried out in Malaysia where the use of conventional toothpicks was low (14.9%) (20). Almost half (42.7%) of the participants in the current study used “Mswaki”, a traditional toothbrush made from tree twigs. “Mswaki” trees have been reported to have antibacterial properties and may have contributed to the low prevalence of dental decay in the study (23). In the current study, 41.5% of the participants replaced their toothbrushes at 3 months. Socioeconomic factors as well as the lack of knowledge of ideal oral hygiene practices may have contributed to not changing toothbrushes according to the recommended 3-month timeline. In contrast, a Malaysian study reported 30% of the study participants changed toothbrushes before 3 months, raising a concern that they may have been employing incorrect brushing techniques (20). In this study, gender was shown to influence the frequency of toothbrush replacement (p = 0.04), with more female participants replacing toothbrushes at 3 months. It has been suggested that women practice stricter hygiene norms compared to men, and this might have informed their decision on toothbrush replacement (24). An association was also reported between toothbrush replacement and age (p = 0.04), with older children more likely to change toothbrushes at three months compared to younger children. Possibly, the level of psychological development could have influenced this. Other observations were that most participants (86.1%) rinsed their mouths with water after meals, a practice that could aid in cleansing the oral cavity. Discussion We also found that study participants used adjunct devices in cleaning their teeth. Modified wooden toothpicks obtained from trees within the school compound had the highest application (62.9%) of all the devices. These results contrast with those in a study carried out in Malaysia where the use of The mean plaque score for the participants was 0.95 ± 0.45 depicting good oral hygiene. Good oral hygiene could have been associated with the frequency of tooth brushing, with the majority (67.3%) of Page 10/16 Page 10/16 the participants reporting brushing two or more times daily. This finding is comparable to results obtained in other studies (10, 25) but differed from several other studies where fair to poor oral hygiene among visually impaired individuals were observed (9, 26, 27). Perhaps, the adjustment in behavior where most participants deliberately rinsed their mouth prior to the dental examination could have also affected the oral health outcome reported here. Despite the children having a high prevalence of gingivitis (88.1%), the mean gingival score was low (0.28 ± 0.25), indicative of mild gingival disease. These findings contrast with other studies where moderate to severe gingivitis was reported (3, 28). The gingival score index was influenced by the participant's age (p = 0.02), indicating that gingivitis increased with age. This could have been due to the child's transition into adolescence, a phase where children tend to lack consistency in oral hygiene practice as instructed by their caregivers, and the influence of sex hormones in the pathogenesis of periodontal disease in the peak age (12 years for females and 13years for males) (29). These factors along with the increase in plaque score, significantly (p = 0.01) influenced the gingival score. In the current study, the overall prevalence of dental caries was 44.7%. It was higher among participants in permanent dentition (42.1%) compared to those in deciduous dentition (8.2%). These findings varied with a study in Khartoum State, Sudan where the prevalence of dental caries was 19.6% among participants in permanent dentition and 23.9% among those in the primary dentition (9)A slightly higher dental caries prevalence was reported among female participants in permanent dentition compared to their male counterparts (p = 0.03). This aligns with a previous study in China(30), where the prevalence of dental caries was higher in girls than in boys (p < 0.05). Discussion Higher dental caries rate in women has been postulated as multifactorial, caused by social factors, hormonal changes, differing salivary composition and flow rate, and variants of the AMELX gene (31, 32). No restored teeth were reported in this study suggesting a high unmet treatment need, with participants suffering from dental decay receiving dental extraction as the treatment option. Among participants in permanent dentition, an association was reported between age and dental caries (p = 0.05), with the younger age group having the highest disease burden. Visual impairment was also shown to influence dental caries experience with a higher disease burden reported among participants in Category I (p = 0.04). In contrast, other studies did not report a significant association between dental decay and visual impairment (10, 26, 33). In the deciduous dentition, an association was reported between dental caries experience and plaque score (p = 0.04). This agrees with findings in Indian studies by Ahmad(26) and Prashanth (10). Conclusions This study reported a generally good oral hygiene among the participants, with gingivitis being highly prevalent (88.1%), and almost half of the study population being affected by dental caries (44.7%). The frequency of toothbrush replacement was significantly associated with age and gender. The majority of the participants were unaware of using fluoridated toothpaste and of needing to change toothbrushes within 3 months. Oral hygiene practices did not influence oral hygiene status and dental caries status. However, an association was reported between frequency of toothbrush replacement and gingival index Page 11/16 Page 11/16 score. The study findings provide evidence for policy change that can lead to the incorporation of an expanded school model for the visually impaired to other regions of the country to relieve the burden of education off the Central Region. Further, the findings inform policy change that ensures oral health education is instituted in the schools to cater to visually impaired children, cognizant of age and its role in the ideal practice of oral hygiene. The high unmet treatment need should inform the formulation and implementation of preventive oral health school programs and continuous screening assessments with the aim of early diagnosis and treatment of oral disease. Guidelines on maintenance of oral hygiene should also be formulated and continuously communicated to visually impaired children with special consideration to involve both tactile and verbal communication. A comparative case-control study with sighted peers, children with other categories of visual impairment and children from other schools for visually impaired is recommended. A longitudinal study is further recommended to assess oral hygiene practices over time. Funding This study was fully funded by the corresponding author. Support for publishing this manuscript was provided by the University of Washington Global Innovation Fund 2021. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request Acknowledgments We sincerely thank the school children, guardians, and teachers of Thika Primary School for the blind for their participation and support. Prof L. Gathece and Prof F. Macigo of the Department of Community & Preventive Dentistry, University of Nairobi who helped with data analysis and presentation. Author contributions MM, conceptualized, designed the study, and wrote the research protocol in collaboration with MM and NP, who also provided inputs in data collection and analysis of the larger study. MM, AK, JB, and ALS conceptualized and designed the initial draft of the current manuscript, verified the data acquisition and analysis adapted from the original larger study. All the authors, reviewed, revised, and approved the final MS prior to submission. manuscript, verified the data acquisition and analysis adapted from the original larger study. All the authors, reviewed, revised, and approved the final MS prior to submission. Author details 1Dental Department, Mathari National Teaching and Referral Hospital, Nairobi, Kenya. 2Department of Dental Sciences, University of Nairobi, Nairobi, Kenya. 3 Department of Dental Sciences, University of Nairobi, Nairobi, Kenya. 4Advanced Education in General Dentistry Program, Yakima, WA, USA. 5School of Dentistry, School of Public Health, University of Washington, Seattle, USA. 6Department of Dental Sciences, University of Nairobi, Nairobi, Kenya. Consent for publication Not applicable. Competing interests All authors declared that they have no competing interests Ethics approval and consent to participate Page 12/16 This study was approved by the University of Nairobi-Kenyatta National Hospital ethics review committee. The ethical approval number is P693/11/2017. Written informed consent was obtained from the parents and guardians of the study participants and assent from the children. All methods were carried out in accordance with relevant guidelines and regulations. the parents and guardians of the study participants and assent from the children. All methods were carried out in accordance with relevant guidelines and regulations. References 1. World Health Organization. Blindness and vision impairment [Internet]. 2022 [cited 2022 Nov 2]. Available from: https://www.who.int/news-room/fact-sheets/detail/blindness-and-visual- impairment. 1. World Health Organization. Blindness and vision impairment [Internet]. 2022 [cited 2022 Nov 2]. Available from: https://www.who.int/news-room/fact-sheets/detail/blindness-and-visual- impairment. 1. World Health Organization. Blindness and vision impairment [Internet]. 2022 [cited 2022 Nov 2]. Available from: https://www.who.int/news-room/fact-sheets/detail/blindness-and-visual- impairment. 2. Solebo AL, Teoh L, Rahi J. Epidemiology of blindness in children. Arch Dis Child. 2017 Sep 1;102(9):853–7. 2. Solebo AL, Teoh L, Rahi J. Epidemiology of blindness in children. Arch Dis Child. 2017 Sep 1;102(9):853–7. 3. Shetty V, Hegde A, Bhandary S, Rai K. Oral health status of the visually impaired children - A south Indian study. Journal of Clinical Pediatric Dentistry. 2010;34(3):213–6. 3. Shetty V, Hegde A, Bhandary S, Rai K. Oral health status of the visually impaired children - A south Indian study. Journal of Clinical Pediatric Dentistry. 2010;34(3):213–6. 4. Kenya Institute of Special Education. National Survey on Children with Disabilities and Special Needs in Education [Internet]. 2018 [cited 2022 Oct 2]. Available from: https://www.kise.ac.ke/ 5. Willings C. Individuals with Disabilities Education Act and Vision Impairments [Internet]. 2019 Jun [cited 2022 Oct 3]. Available from: https://www.teachingvisuallyimpaired.com/idea-and-vision.html 6. Kiarie MW. Education of students with visual impairments in Kenya:Trends and issues. Vol. 19, International Journal of Special Education. 2004. 7. Verweyen P, Hyvarinen L. The Impact of Low Vision Project-Kenya In the Education of the Visually Impaired Children. 1999. 8. Baiju RM PEVNSR. Dentistry Section Oral Health and Quality of Life: Current Concepts. J Clin Diagn Res [Internet]. 2017;11(6). Available from: www.jcdr.net 9. Tagelsir et al. Oral health of visually impaired schoolchildren in Khartoum State, Sudan. BMC Oral Health . 2013;13(1). Page 13/16 Page 13/16 10. Prashanth ST, Bhatnagar S, Das UM, Gopu H. Oral health knowledge, practice, oral hygiene status, and dental caries prevalence among visually impaired children in Bangalore. J Indian Soc Pedod Prev Dent. 2011;29(2):102–5. 11. Gautam K, Ali AR, Agrawal D, Choudhary A, Shekhawat A, Jain RL. New vision for improving oral hygiene status of visually impaired students aged from 9 to 17 years. J Family Med Prim Care . 2020;9(10):5303. 12. Ministry of Health. Kenya National Oral Health Survey report [Internet]. 2015 [cited 2022 Sep 2]. Available from: https://profiles.uonbi.ac.ke/gathece/files/kenya_national_oral_health_survey_report_2015.pdf 13. Fantaye W, Nur A, Kifle G, Engida F. Oral health knowledge and oral hygiene practice among visually impaired subjects in Addis Ababa, Ethiopia. BMC Oral Health. 2022 Dec 1;22(1). 14. References Gwillim Law. Counties of Kenya [Internet]. 2015. [cited 2022 Sep 11]. Available from: http://www.statoids.com/uke.html 15. Jung SH. Stratified Fisher’s exact test and its sample size calculation. Biometrical Journal. 2014 Jan;56(1):129–40. 16. WHO. Oral Health Surveys: Basic Methods - 5th Edition. World Health Organization. 2013. 16. WHO. Oral Health Surveys: Basic Methods - 5th Edition. World Health Org 17. Loe H. The gingival Index, the Plaque Index and Retention Index systems. J Periodontol. 1967;38(6):610–6. 18. Gogate P, Gilbert C, Zin A. Severe visual Impairment and blindness in infants: Causes and opportunities for control. Middle East Afr J Ophthalmol. 2011 Apr;18(2):109–14. 19. David Kavinje Chikati, Lydiah Njoki Wachira, Joseph Munyoki Mwinz. Development of special education for the visually impaired learners in Kenya: A historical perspective. European Journal of Special Education Research. 2019;4. 20. Azrina AN, Norzuliza G, Saub R, Saub R. Oral hygiene practices among the visually impaired adolescents. Annal Dent Univ Malaya. 2007;14:1–6. 21. Ali SH, Hamad AM, Zardawi FM, Arif AN. Oral health knowledge, practice, oral hygiene status, among visually impaired students in Sulaimani city/Iraq. IOSR Journal of Dental and Medical Sciences . 2015;14:2279–861. 22. World Health Organization Regional Office for Africa. Promoting Oral Health in Africa [Internet]. 2016. Available from: http://www.afro.who.int/ 23. Sukkarwalla A, Ali SM, Lundberg P, Tanwir F. Efficacy of miswak on oral pathogens. Dent Res J (Isfahan). 2013 May;10(3):314–20. 24. Erikssonid K, Dickinsid TE, Strimling P. Global sex differences in hygiene norms and their relation to sex equality. PLOS Global Public Health . 2022;2(6). 25. James et al. Prevalence of Dental Caries, Oral Hygiene Knowledge, Status, and Practices among Visually Impaired Individuals in Chennai, Tamil Nadu. Int J Dent. 2017;(9419648):6. Page 14/16 Page 14/16 26. Ahmad MS, Jindal MK, Khan S, Hashmi SH. Oral health knowledge , practice , oral hygiene status and dental caries prevalence among visually impaired students in residential institute of Aligarh. J Dent Oral Hyg. 2009;1(2):22–6. 27. Reddy K, Sharma A. Prevalence of oral health status in visually impaired children. J Indian Soc Pedod Prev Dent. 2011;29(1):25–7. 28. Nandini NS. New insights into improving the oral health of visually impaired children. J Indian Soc Pedod Prev Dent. 2004;21(4):142–3. 29. Hosadurga R, Nabeel Althaf M, Hegde S, Rajesh K, Arun Kumar M. Influence of sex hormone levels on gingival enlargement in adolescent patients undergoing fixed orthodontic therapy: A pilot study. Contemp Clin Dent. 2016 Oct 1;7(4):506–11. 30. References Liu L, Zhang Y, Wu W, He M, Lu Z, Zhang K, et al. Oral health status among visually impaired schoolchildren in Northeast China. BMC Oral Health. 2019 Apr 27;19(1). 31. Ferraro M, Vieira AR. Explaining Gender Differences in Caries: A Multifactorial Approach to a Multifactorial Disease. Int J Dent. 2010;2010:1–5. 32. Lukacs JR, Largaespada LL. Explaining sex differences in dental caries prevalence: Saliva, hormones, and “life history” etiologies. American Journal of Human Biology. 2006 Jul;18(4):540–55. 33. N. B, N. A, B. K, Bekiroglu N, Acar N, Kargul B. Caries experience and oral hygiene status of a group of visually impaired children in Istanbul, Turkey. Oral Health Prev Dent. 2012; Figures Page 15/16 Figure 1 Map of Kenya showing the distribution of participants by regions igure 1 Map of Kenya showing the distribution of participants by regions Figure 1 Map of Kenya showing the distribution of participants by regions Map of Kenya showing the distribution of participants by regions Map of Kenya showing the distribution of participants by regions Page 16/16
https://openalex.org/W4387137464
https://www.frontiersin.org/articles/10.3389/fonc.2023.1185530/pdf?isPublishedV2=False
English
null
The second docetaxel rechallenge for metastatic castration-resistant prostate cancer: a case report
Frontiers in oncology
2,023
cc-by
4,608
OPEN ACCESS Wei Ning 1, Pengkang Chang 1, Ji Zheng 1* and Fan He 1,2* 1Department of Urology, Second Affiliated Hospital, Army Medical University, Chongqing, China, 2Urology Department, Institute of Urology (Laboratory of Reconstructive Urology), West China Hospital, Sichuan University, Chengdu, Sichuan, China Background: Docetaxel combined with prednisone plus androgen deprivation therapy (ADT) is the preferred treatment option for metastatic hormone- sensitive prostate cancer (mHSPC) or metastatic castration-resistant prostate cancer (mCRPC). With the development of next-generation hormonal agents (NHAs) and poly (ADP-ribose) polymerase (PARP) inhibitors, more aggressive first-line or later-line treatment strategies have been added to the treatment of mHSPC and mCRPC. However, docetaxel rechallenge (DR) has special clinical significance in patients with “docetaxel-sensitive” prostate cancer. There are no reports on the efficacy and safety of the second DR in mCRPC patients. COPYRIGHT © 2023 Ning, Chang, Zheng and He. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Case presentation: We report one patient diagnosed with mCRPC who showed progression-free survival (PFS) and overall survival (OS) benefits and safety and good lower urinary tract function after the second DR. Conclusion: The second DR as a potential alternative later-line treatment strategy should be considered for patients with mCRPC who worry about the high economic burden of multigene molecular testing and PARP inhibitors as well as repeated prostate needle biopsy. prostate cancer (PCa), metastatic castration-resistant prostate cancer (mCRPC), second docetaxel rechallenge (DR), later-line treatment, case report The second docetaxel rechallenge for metastatic castration-resistant prostate cancer: a case report OPEN ACCESS EDITED BY Ran Xu, Central South University, China REVIEWED BY Masayoshi Nagata, Juntendo University, Japan Martina Maggi, Sapienza University of Rome, Italy *CORRESPONDENCE Ji Zheng Jizheng@tmmu.edu.cn Fan He 785517193@qq.com RECEIVED 13 March 2023 ACCEPTED 05 September 2023 PUBLISHED 27 September 2023 CITATION Ning W, Chang P, Zheng J and He F (2023) The second docetaxel rechallenge for metastatic castration-resistant prostate cancer: a case report. Front. Oncol. 13:1185530. doi: 10.3389/fonc.2023.1185530 prostate cancer (PCa), metastatic castration-resistant prostate cancer (mCRPC), second docetaxel rechallenge (DR), later-line treatment, case report TYPE Case Report PUBLISHED 27 September 2023 DOI 10.3389/fonc.2023.1185530 TYPE Case Report PUBLISHED 27 September 2023 DOI 10.3389/fonc.2023.1185530 Introduction The patient has become resistant to ADT with progression to mCRPC, despite serum testosterone remaining at castrate levels (< 50 ng/dL). For decades, hormonal therapy, also known as androgen deprivation therapy (ADT), has played an important role in the treatment of patients with advanced PCa and is aimed at lowering testosterone levels. With the development of next-generation hormonal agents (NHAs) and chemotherapy, a more aggressive first-line treatment strategy has been added to the treatment of metastatic hormone-sensitive prostate cancer (mHSPC) (6). Although most patients suffering from mHSPC primarily respond to ADT, the duration of response is uncertain, and all patients ultimately develop metastatic castration-resistant prostate cancer (mCRPC) (7). The standard treatment of mCRPC refers to the combination of ADT and NHA (abiraterone acetate, enzalutamid) or chemotherapy (docetaxel or cabazitaxel). In addition, radium- 223, an alpha emitter, can be considered as a treatment for symptomatic bone metastases of patients with PCa (8). Several therapies have been proven to improve the progression-free survival (PFS) and overall survival (OS) of patients with mCRPC. However, most patients eventually die from mCRPC within a few years (7). Currently, docetaxel is approved for first-line treatment of mHSPC or mCRPC. Reintroduction of docetaxel, which is also known as docetaxel rechallenge (DR), lacks enough supporting evidence in patients with mCRPC (9). The concept of DR represents a special clinical significance in patients with “docetaxel-sensitive” PCa (10). Nevertheless, more high-level evidence is needed for DR as a potential alternative treatment in later lines. Here, we report one mCRPC patient with a second DR as an alternative to poly (ADP-ribose) polymerase (PARP) inhibitors or platinum- based chemotherapy. From 18 June to 23 October 2020, the patient accepted and started six cycles of docetaxel (75 mg/m2, Day 1, intravenous injection, every 21 days) combined with prednisone (5 mg, oral administration, twice daily) plus goserelin. After six cycles of chemotherapy, the PSA level of the patient dropped to 0.97 ng/ mL. Prostate-enhanced MRI on 15 March 2021, suggested an enlarged prostate with a maximum cross-sectional size of 50 ×3 7 mm and a significantly reduced volume of the prostate and left pelvic sidewall lesions compared to before treatment (Figure 1D). The patient had good lower urinary tract function and clinical efficacy and safety. However, he was still afraid of the adverse events of docetaxel chemotherapy and refused to accept chemotherapy sequentially. Introduction The first case of prostate cancer (PCa) was described as a very rare disease by J. Adams at the London Hospital in 1853 (1). Currently, PCa ranks second in the incidence of male cancer and sixth in male cancer mortality worldwide (2). In China, the incidence and mortality of PCa have been rising rapidly for decades. In particular, Chinese patients with PCa have unique epidemiological characteristics, such as higher grading and staging of tumors and a worse disease prognosis (3). Malignant transformation of the normal Frontiers in Oncology 01 frontiersin.org Ning et al. 10.3389/fonc.2023.1185530 10.3389/fonc.2023.1185530 prostatic epithelium follows a complicated process (4). Metastatic spread of tumors is the main cause of death for patients with PCa. Bone metastases of patients with PCa always manifest as osteoblastic and osteolytic lesions, mainly osteoblastic features, which can lead to severe pain, pathological fractures, hypercalcemia, and nerve compression syndromes (5). On 30 December 2019, the patient underwent TURP plus transperineal biopsy of the prostate, and invasion of the left wall of the bladder was observed during the operation. The postoperative pathological diagnosis showed prostate adenocarcinoma, Gleason score (GS) 5 + 4 = 9 (Figure 1B). Positron emission tomography/computed tomography (PET/ CT) on 7 January 2020, revealed that the mass in the pelvic region was considered a malignant tumor, and enlarged pelvic and retroperitoneal lymph nodes were considered metastatic carcinoma. The patient was eventually diagnosed with PCa (pT4N1M1a). Because of worrying about the adverse events of docetaxel chemotherapy and the high economic burden of NHA, at the beginning, the patient received ADT (goserelin, 3.6 mg, subcutaneous injection, per 28 days plus bicalutamide 50 mg, oral administration, once daily). To his disappointment, the reduction in the PSA level was unsatisfactory, dropping to only 7.04 ng/mL. Prostate-enhanced magnetic resonance imaging (MRI) on 18 June 2020 revealed an enlarged prostate with a maximum cross-sectional size of 50 × 37 mm, PCa with invasion of the left pelvic sidewall and left side of the bladder, unclearly displayed bilateral seminal vesicles, and enlarged left external and internal iliac lymph nodes (Figure 1C). According to the official definition of mCRPC by the European Association of Urology (EAU) guideline as well as Response Evaluation Criteria in Solid Tumors (RECIST) (11, 12), the patient showed radiological progression (an enlarged soft tissue lesion using RECIST), while the PSA level was more than three times as high as 2 ng/mL. Introduction After 6 months of follow-up and maintenance ADT, the PSA level of the patient rose to 19.48 ng/mL. Prostate-enhanced MRI on 24 May 2021 revealed a significantly increased lesion volume in the left pelvic sidewall and new metastasis in the left femoral neck, sacrum, and bilateral iliac crest (Figure 1E). Frontiers in Oncology Case presentation A 70-year-old man was admitted to the Second Affiliated Hospital, Army Medical University on 27 December 2019, with the chief complaint of pollakiuria and urgent urination for half a year and dysuria for 13 days. The patient had urinary incontinence, nocturia, and intermittent hematuria but did not have other clinical symptoms or signs. The patient received transurethral resection of the prostate (TURP) at the local hospital 6 months prior, and the postoperative pathological diagnosis was uncertain. Urinary tract computed tomography (CT) on 14 December 2019, revealed a mass with mixed density in the pelvic region, unclearly displayed prostate and bladder, enlarged pelvic and retroperitoneal lymph nodes, and mildly dilated bilateral renal pelvis and ureter (Figure 1A). The prostate-specific antigen (PSA) level of the patient was 198 ng/mL. An enlarged prostate and a hard enlarged mass were palpated by digital rectal examination (DRE). The personal history, family history, and physical examination of the patient were not exceptional. We further analyzed the homologous recombination repair (HRR) gene panel of the patient by genetic testing of circulating tumor DNA (ctDNA), and the presence of HRR gene mutations (HRRm) was not found. Therefore, from 25 May to 7 December 2021, the patient accepted and started 10 cycles of docetaxel combined with prednisone (the first DR) plus goserelin and the addition of abiraterone acetate (1,000 mg, oral administration, once daily). Prostate-enhanced MRI on 17 November 2021 revealed a prostate with a maximum cross-sectional size of 37 × 29 mm and a 02 Frontiers in Oncology frontiersin.org Ning et al. 10.3389/fonc.2023.1185530 FIGURE 1 Images of the patient throughout the treatment. (A) Before treatment, urinary tract CT showed a localized mass with mixed density in the pelvic region, unclearly displayed prostate and bladder, enlarged pelvic and retroperitoneal lymph nodes, and mildly dilated bilateral renal pelvis and ureter. (B) The postoperative pathological diagnosis showed prostate adenocarcinoma, Gleason score (GS) 5 + 4 = 9. (C) On 18 June 2020, prostate- enhanced MRI cross-sectional DWI showed an enlarged prostate with a maximum cross-sectional size of 50 × 37 mm, prostate cancer with invasion of the left pelvic sidewall and left side of the bladder, unclearly displayed bilateral seminal vesicles, and enlarged left external and internal iliac lymph nodes. Case presentation (D) On 15 March 2021, prostate-enhanced MRI cross-sectional DWI showed an enlarged prostate with a maximum cross-sectional size of 50 × 37 mm and a significantly reduced volume of the prostate and left pelvic sidewall lesions compared to before treatment. (E) On 24 May 2021, prostate-enhanced MRI cross-sectional DWI showed a significantly increased lesion volume in the left pelvic sidewall and new metastasis in the left femoral neck, sacrum, and bilateral iliac crest. (F) On 17 November 2021, prostate-enhanced MRI cross-sectional DWI showed prostate with a maximum cross-sectional size of 37 × 29 mm and significantly reduced volume of lesion of prostate and left pelvic sidewall. Except for the left femoral neck, no bone metastases were found in the other parts of the body. (G) On 23 March 2022, prostate-enhanced MRI cross-sectional DWI showed that the volume of the lesion of the left pelvic sidewall was significantly increased, and rectal invasion was not ruled out. (H) On 8 September 2022, prostate-enhanced MRI cross-sectional DWI did not show new confirmed progression of imaging. FIGURE 1 Images of the patient throughout the treatment. (A) Before treatment, urinary tract CT showed a localized mass with mixed density in the pelvic region, unclearly displayed prostate and bladder, enlarged pelvic and retroperitoneal lymph nodes, and mildly dilated bilateral renal pelvis and ureter. (B) The postoperative pathological diagnosis showed prostate adenocarcinoma, Gleason score (GS) 5 + 4 = 9. (C) On 18 June 2020, prostate- enhanced MRI cross-sectional DWI showed an enlarged prostate with a maximum cross-sectional size of 50 × 37 mm, prostate cancer with invasion of the left pelvic sidewall and left side of the bladder, unclearly displayed bilateral seminal vesicles, and enlarged left external and internal iliac lymph nodes. (D) On 15 March 2021, prostate-enhanced MRI cross-sectional DWI showed an enlarged prostate with a maximum cross-sectional size of 50 × 37 mm and a significantly reduced volume of the prostate and left pelvic sidewall lesions compared to before treatment. (E) On 24 May 2021, prostate-enhanced MRI cross-sectional DWI showed a significantly increased lesion volume in the left pelvic sidewall and new metastasis in the left femoral neck, sacrum, and bilateral iliac crest. (F) On 17 November 2021, prostate-enhanced MRI cross-sectional DWI showed prostate with a maximum cross-sectional size of 37 × 29 mm and significantly reduced volume of lesion of prostate and left pelvic sidewall. Case presentation Except for the left femoral neck, no bone metastases were found in the other parts of the body. (G) On 23 March 2022, prostate-enhanced MRI cross-sectional DWI showed that the volume of the lesion of the left pelvic sidewall was significantly increased, and rectal invasion was not ruled out. (H) On 8 September 2022, prostate-enhanced MRI cross-sectional DWI did not show new confirmed progression of imaging. 03 Frontiers in Oncology frontiersin.org Ning et al. 10.3389/fonc.2023.1185530 rate of 48%, especially in patients with good PSA responses to first- line treatment with docetaxel. significantly reduced lesion volume in the prostate and left pelvic sidewall. Except for the left femoral neck, no bone metastases were found in the other parts of the body (Figure 1F). After 10 cycles of chemotherapy, the PSA level of the patient dropped to 0.61 ng/mL again. Unfortunately, after less than 3 months of follow-up and maintenance goserelin plus abiraterone combined with prednisone, the PSA level of the patient rose to 21.78 ng/mL. In addition, prostate-enhanced MRI on 23 March 2022 revealed that the volume of the lesion on the left pelvic sidewall was significantly increased, and rectal invasion was not ruled out (Figure 1G). Because of radiographic progress after ADT, the patient had become resistant to ADT with progression to mCRPC. According to the guidelines, the first-line treatment of docetaxel was administered to the patient with mCRPC, including six cycles of docetaxel combined with prednisone plus goserelin. The PSA level of the patient dropped to 0.97 ng/mL. Prostate-enhanced MRI suggested that the volume of the prostate and left pelvic sidewall lesions was significantly reduced compared to that before treatment. After 6 months of follow-up and maintenance ADT, the PSA level of the patient rose to 19.48 ng/mL. Metastasis of the left femoral neck, sacrum, and bilateral iliac crest was revealed by prostate- enhanced MRI at follow-up. After multidisciplinary team (MDT) discussion regarding the worries about the high economic burden of multigene molecular testing by tissue biopsy and PARP inhibitors as well as repeated prostate needle biopsy, on 30 March 2022, the patient accepted and started eight cycles of docetaxel combined with prednisone (the second DR) as well as maintenance goserelin plus abiraterone. Although the PSA response cannot reach a 97% PSA reduction as the first DR, the PSA level of the patient can still be maintained at 19–27 ng/mL. Case presentation Full- body bone scan and prostate-enhanced MRI (Figure 1H) of follow-up did not show new confirmed progression of imaging. The changes in the PSA and serum testosterone levels throughout the treatment are shown in Figure 2. The E3805 CHAARTED trial revealed significant differences in the transcriptional profile of patients with mPCa, including luminal B subtype, basal subtype, lower androgen receptor activity (AR-A), and high Decipher risk disease. Patients with the luminal B subtype showed a significant OS benefit from ADT + docetaxel (HR 0.45, p = 0.007), whereas patients with the basal subtype showed no OS benefit (HR 0.85, p = 0.58). Lower AR-A and high Decipher risk were significantly related to poorer prognosis. In addition, patients with high Decipher risk had greater OS improvement from ADT + Docetaxel (HR 0.41, p = 0.015) (15). There was a retrospective study of 270 mCRPC patients with good response to first-line docetaxel. The median progression-free interval (PFI) was 6 months from the last chemotherapy of docetaxel. When it recurred, 223 patients received DR, and 47 received other therapy. The median OS for DR and other therapies was 18.2 vs. 16.8, respectively (p = 0.35). However, over 6 months of PFI indicated longer OS. Moreover, a good PSA response was more distinct on DR (40.4% vs. 10.6%, p < 0.001) (16). Another study showed that DR had OS improvement Discussion Currently, metastatic PCa (mPCa) remains incurable worldwide. Docetaxel was the first systemic therapy showing a survival benefit to patients with mHSPC or mCRPC (13). Before NHA became available in clinical practice, several studies showed the clinical efficacy of DR in selected patients with mCRPC (14). DR provided moderate clinical efficacy and a maximum PSA response B A FIGURE 2 The PSA and serum testosterone levels of the patient throughout the treatment. (A) Change in the PSA level after docetaxel chemotherapy, the first DR, and the second DR. (B) Change in the serum testosterone level. FIGURE 2 The PSA and serum testosterone levels of the patient throughout the treatment. (A) Change in the PSA level after docetaxel chemotherapy, the first DR, and the second DR. (B) Change in the serum testosterone level. 04 04 Frontiers in Oncology frontiersin.org Ning et al. 10.3389/fonc.2023.1185530 and safety in patients with a good response to docetaxel initially and more than 3 months of PFI (16). In addition, DR did not seem to increase the risk of adverse events, especially grade 3–4 events (14, 17). However, the GETUG-AFU 15 Phase 3 Trial suggested that only a limited number of patients who received first-line treatment with ADT + docetaxel for mHSPC benefited from DR at mCRPC. At this stage, NHAs such as abiraterone or enzalutamide can be used as a later-line treatment strategy (18). Because of the failure of HRRm testing, the patient received the first DR plus goserelin along with the addition of abiraterone acetate. The PSA level of the patient dropped to 0.61 ng/mL again. The volume of lesions of the prostate and left pelvic sidewall was significantly reduced by prostate- enhanced MRI. Except for the left femoral neck, no bone metastases were found in the other parts of the body. Unfortunately, after less than 3 months of follow-up and maintenance goserelin plus abiraterone, the PSA level of the patient rose to 21.78 ng/mL. In addition, the volume of the lesion of the left pelvic sidewall was significantly increased, and rectal invasion was not ruled out. biopsy are advised to consider this later-line treatment strategy. We also believe that this strategy should be popularized by urological clinicians in hospitals. Data availability statement The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding The current work was partly supported by the Natural Science Foundation of Chongqing [CSTC2020JCYJ-msxmX0513] and the Key Project for Clinical Innovation of Army Medical University [CX2019LC107]. Author contributions FH and JZ revised the manuscript. WN was responsible for data collection, data analysis, data interpretation, and writing the manuscript. PC was responsible for image design. All authors contributed to the article and approved the submitted version. Ethics statement The studies involving humans were approved by Ethics Committee of Second Affiliated Hospital, Army Medical University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article. Written informed consent was obtained from the participant/patient(s) for the publication of this case report. In the management of patients with mCRPC, regular MDT discussions can provide a more valuable and individualized treatment strategy, while patients can gain a more prolonged OS and better prognosis (19). After MDT discussion, because of the high economic burden of multigene molecular testing by tissue biopsy and PARP inhibitors, the patient could not receive the combination treatment of olaparib and abiraterone. Moreover, the patient refused prostate needle biopsy again; in turn, he could not confirm the pathological type of neuroendocrine prostate cancer (NEPC) and used platinum-based chemotherapy (20). PCa is a significantly increasing cause of mortality around the world and can also bring about a significantly increasing social and economic burden in modern society. FIRSTANA suggested that the median OS and PFS of patients with mCRPC were 24.3 months and 5.3 months, respectively, with docetaxel combined with prednisone (21). In the end, the patient received eight cycles of docetaxel combined with prednisone (the second DR) as well as maintenance goserelin plus abiraterone. To our excitement, although the PSA response cannot reach a 97% PSA reduction as the first DR, the PSA level of the patient can still be maintained at 19–27 ng/mL. Full- body bone scan and prostate-enhanced MRI during follow-up did not show new confirmed progression on imaging. More importantly, after a total of 24 cycles of docetaxel, the patient was still well-tolerated. Frontiers in Oncology Publisher’s note Overall, we demonstrated that the second DR was associated with further prolonged OS and PFS in patients with mCRPC. The PSA level, MRI progression of the lesion, and adverse events of the patient did not increase significantly. Therefore, this result can be added to the later-line treatment strategy of patients with mCRPC. In the future, more patients who worry about the high economic burden of testing and treatment as well as repeated prostate needle All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. 05 frontiersin.org 10.3389/fonc.2023.1185530 Ning et al. 21. Oudard S, Fizazi K, Sengeløv L, Daugaard G, Saad F, Hansen S, et al. Cabazitaxel versus docetaxel as first-line therapy for patients with metastatic castration-resistant prostate cancer: A randomized phase III trial-FIRSTANA. J Clin Oncol (2017) 35 (28):3189–97. doi: 10.1200/JCO.2016.72.1068 References 13. Sweeney CJ, Chen YH, Carducci M, Liu G, Jarrard DF, Eisenberger M, et al. Chemohormonal therapy in metastatic hormone-sensitive prostate cancer. N Engl J Med (2015) 373(8):737–46. doi: 10.1056/NEJMoa1503747 1. Nader R, El Amm J, Aragon-Ching JB. Role of chemotherapy in prostate cancer. Asian J Androl (2018) 20(3):221–9. doi: 10.4103/aja.aja_40_17 2. BrayF,FerlayJ,SoerjomataramI,SiegelRL,TorreLA,JemalA.Globalcancerstatistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin (2018) 68(6):394–424. doi: 10.3322/caac.21492 14. Thomas C, Brandt MP, Baldauf S, Tsaur I, Frees S, Borgmann H, et al. Docetaxel-rechallenge in castration-resistant prostate cancer: defining clinical factors for successful treatment response and improvement in overall survival. Int Urol Nephrol (2018) 50(10):1821–7. doi: 10.1007/s11255-018-1963-1 14. Thomas C, Brandt MP, Baldauf S, Tsaur I, Frees S, Borgmann H, et al. Docetaxel-rechallenge in castration-resistant prostate cancer: defining clinical factors for successful treatment response and improvement in overall survival. Int Urol Nephrol (2018) 50(10):1821–7. doi: 10.1007/s11255-018-1963-1 3. Liu J, Dong L, Zhu Y, Dong B, Sha J, Zhu HH, et al. Prostate cancer treatment- China's perspective. Cancer Lett (2022) 550:215927. doi: 10.1016/j.canlet.2022.215927 15. Hamid AA, Huang HC, Wang V, Chen YH, Feng F, Den R, et al. Transcriptional profiling of primary prostate tumor in metastatic hormone-sensitive prostate cancer and association with clinical outcomes: correlative analysis of the E3805 CHAARTED trial. Ann Oncol (2021) 32(9):1157–66. doi: 10.1016/ j.annonc.2021.06.003 4. Swami U, McFarland TR, Nussenzveig R, Agarwal N. Advanced prostate cancer: treatment advances and future directions. Trends Cancer (2020) 6(8):702–15. doi: 10.1016/j.trecan.2020.04.010 5. Achard V, Putora PM, Omlin A, Zilli T, Fischer S. Metastatic prostate cancer: treatment options. Oncology (2022) 100(1):48–59. doi: 10.1159/000519861 16. Oudard S, Kramer G, Caffo O, Creppy L, Loriot Y, Hansen S, et al. Docetaxel rechallenge after an initial good response in patients with metastatic castration- resistant prostate cancer. BJU Int (2015) 115(5):744–52. doi: 10.1111/bju.12845 6. Barata PC, Sartor AO. Metastatic castration-sensitive prostate cancer: Abiraterone, docetaxel, or…. Cancer (2019) 125(11):1777–88. doi: 10.1002/cncr.32039 7. Kyriakopoulos CE, Chen YH, Carducci MA, Liu G, Jarrard DF, Hahn NM, et al. Chemohormonal therapy in metastatic hormone-sensitive prostate cancer: long-term survival analysis of the randomized phase III E3805 CHAARTED trial. J Clin Oncol (2018) 36(11):1080–7. doi: 10.1200/JCO.2017.75.3657 17. Assi T, Rassy E, Farhat F, Kattan C, Kattan J. Docetaxel rechallenge in patients with metastatic prostate cancer: A comprehensive review. Oncol Res Treat (2020) 43 (6):299–306. doi: 10.1159/000506693 17. References Assi T, Rassy E, Farhat F, Kattan C, Kattan J. Docetaxel rechallenge in patients with metastatic prostate cancer: A comprehensive review. Oncol Res Treat (2020) 43 (6):299–306. doi: 10.1159/000506693 18. Lavaud P, Gravis G, Foulon S, Joly F, Oudard S, Priou F, et al. Anticancer activity and tolerance of treatments received beyond progression in men treated upfront with androgen deprivation therapy with or without docetaxel for metastatic castration-naïve prostate cancer in the GETUG-AFU 15 phase 3 trial. Eur Urol (2018) 73(5):696–703. doi: 10.1016/j.eururo.2017.09.022 18. Lavaud P, Gravis G, Foulon S, Joly F, Oudard S, Priou F, et al. Anticancer activity and tolerance of treatments received beyond progression in men treated upfront with androgen deprivation therapy with or without docetaxel for metastatic castration-naïve prostate cancer in the GETUG-AFU 15 phase 3 trial. Eur Urol (2018) 73(5):696–703. doi: 10.1016/j.eururo.2017.09.022 8. von Amsberg G, Merseburger AS. Therapie des metastasierten kastrationsresistenten Prostatakarzinoms [Treatment of metastatic, castration-resistant prostate cancer]. Urologe A (2020) 59(6):673–9. doi: 10.1007/s00120-020-01187-9 9. Tucci M, Caffo O, Buttigliero C, Cavaliere C, D'aniello C, Di Maio M, et al. Therapeutic options for first-line metastatic castration-resistant prostate cancer: Suggestions for clinical practise in the CHAARTED and LATITUDE era. Cancer Treat Rev (2019) 74:35–42. doi: 10.1016/j.ctrv.2019.01.002 19. Zhu S, Chen J, Ni Y, Zhang H, Liu Z, Shen P, et al. Dynamic multidisciplinary team discussions can improve the prognosis of metastatic castration-resistant prostate cancer patients. Prostate (2021) 81(11):721–7. doi: 10.1002/pros.24167 19. Zhu S, Chen J, Ni Y, Zhang H, Liu Z, Shen P, et al. Dynamic multidisciplinary team discussions can improve the prognosis of metastatic castration-resistant prostate cancer patients. Prostate (2021) 81(11):721–7. doi: 10.1002/pros.24167 10. Byeon S, Kim H, Kim J, Kwon M, Hur JY, Jeon HG, et al. Docetaxel rechallenge in metastatic castration-resistant prostate cancer: A retrospective, single-center study. Investig Clin Urol (2020) 61(6):588–93. doi: 10.4111/icu.20200214 10. Byeon S, Kim H, Kim J, Kwon M, Hur JY, Jeon HG, et al. Docetaxel rechallenge in metastatic castration-resistant prostate cancer: A retrospective, single-center study. Investig Clin Urol (2020) 61(6):588–93. doi: 10.4111/icu.20200214 20. Pandya D, Shah M, Kaplan F, Martino C, Levy G, Kazanjian M, et al. Treatment- emergent neuroendocrine prostate cancer with a germline BRCA2 mutation: identification of a candidate reversion mutation associated with platinum/PARP- inhibitor resistance. Cold Spring Harb Mol Case Stud (2021) 7(1):a005801. doi: 10.1101/mcs.a005801 20. Pandya D, Shah M, Kaplan F, Martino C, Levy G, Kazanjian M, et al. References Treatment- emergent neuroendocrine prostate cancer with a germline BRCA2 mutation: identification of a candidate reversion mutation associated with platinum/PARP- inhibitor resistance. Cold Spring Harb Mol Case Stud (2021) 7(1):a005801. doi: 10.1101/mcs.a005801 11. Heidenreich A, Bastian PJ, Bellmunt J, Bolla M, Joniau S, van der Kwast T. EAU guidelines on prostate cancer. Part II: treatment of advanced, relapsing, and castration- resistant prostate cancer. Eur Urol (2014) 65:467–79. doi: 10.1016/j.eururo.2013.11.002 11. Heidenreich A, Bastian PJ, Bellmunt J, Bolla M, Joniau S, van der Kwast T. EAU guidelines on prostate cancer. Part II: treatment of advanced, relapsing, and castration- resistant prostate cancer. Eur Urol (2014) 65:467–79. doi: 10.1016/j.eururo.2013.11.002 21. Oudard S, Fizazi K, Sengeløv L, Daugaard G, Saad F, Hansen S, et al. Cabazitaxel versus docetaxel as first-line therapy for patients with metastatic castration-resistant prostate cancer: A randomized phase III trial-FIRSTANA. J Clin Oncol (2017) 35 (28):3189–97. doi: 10.1200/JCO.2016.72.1068 12. Vullierme MP, Ruszniewski P, de Mestier L. Are recist criteria adequate in assessing the response to therapy in metastatic NEN? Rev Endocr Metab Disord (2021) 22(3):637–45. doi: 10.1007/s11154-021-09645-1 12. Vullierme MP, Ruszniewski P, de Mestier L. Are recist criteria adequate in assessing the response to therapy in metastatic NEN? Rev Endocr Metab Disord (2021) 22(3):637–45. doi: 10.1007/s11154-021-09645-1 06 Frontiers in Oncology frontiersin.org
https://openalex.org/W2590664148
https://zenodo.org/record/896497/files/article.pdf
English
null
Revisiting the Kronecker Array Transform
IEEE signal processing letters
2,017
cc-by-sa
5,805
I. INTRODUCTION The time-domain samples of each microphone are segmented into frames of K samples, and each frame is converted to the frequency domain using the fast Fourier transform (FFT). In the presence of additive noise, the M × 1 array output vector for a single frequency ωk (0 < k < K/2) on a single frame can be modeled, according to [12], as M M ICROPHONE arrays are commonly used either as su- perdirective microphones [1] or as acoustic cameras [2]. They differ in the fact that the first provides an estimate of the time signal arriving from a given direction while the second uses the estimate of the sound pressure levels at a number of directions to generate a noise map (presented as a color map). x(ωk) = V (ωk) y(ωk) + η(ωk), (1) (1) The standard algorithm for array processing is the delay- and-sum beamformer (DAS) [1], [2]. Despite its simplicity, the angular resolution obtained with this method is rather low, which prompted several authors to propose improved estimation algorithms [3]–[5]. As a tradeoff, these algorithms have a higher computational complexity and, for a large number of micro- phones, the computational cost may become prohibitive [6]. where y(ωk) = [f0(ωk) f1(ωk) · · · fN−1(ωk)]T represents the source signals in the frequency domain, and η(ωk) repre- sents additive noise in frequency-domain. The array manifold matrix V (ωk) = [v(q0, ωk) v(q1, ωk) · · · v(qN−1, ωk)], of size M × N, describes the transfer function between each source n and each sensor m at frequency ωk. Assuming that the point sources are in the far field, we define the look direction for source n as un = −qn/ ∥qn∥. The array manifold vector for source n, according to [6], is modelled as v(un, ωk) = h ej(ωk/c)uT n p0 · · · ej(ωk/c)uT n pM−1 iT , where c is the speed of sound. The Kronecker Array Transform (KAT) was introduced in [6], [7] to accelerate the calculation of acoustic images, essentially, by reorganizing the matrix-vector multiplication structure for a special case of separable arrays. The original KAT [6] was designed for acoustic camera applications. This was latter extended to superdirective microphone algorithms in [8]. In this letter, we present two main contributions. II. PRELIMINARIES We consider a sensor array composed of M microphones at Cartesian coordinates p0, · · · , pM−1 ∈R3 being irradiated by an arbitrary sound field which we wish to estimate. We model the sound field as the superposition of the wave fields generated by N acoustic point sources located at coordinates q0, · · · , qN−1 ∈R3, where N is usually a large number in order to obtain an accurate model. Index Terms—Kronecker array transform, Khatri-Rao identity, fast acoustic imaging, microphone array Revisiting the Kronecker Array Transform Bruno Masiero, Member, IEEE, V´ıtor H. Nascimento, Senior Member, IEEE the use of a new relation developed between the Kronecker [9] and the Khatri-Rao [10], [11] matrix products. Abstract—It is known that the calculation of a matrix-vector product can be accelerated if this matrix can be recast (or approximated) by the Kronecker product of two smaller matrices. In array signal processing the manifold matrix can be described as the Kronecker product of two other matrices if the sensor array displays a separable geometry. This forms the basis of the Kronecker Array Transform (KAT), which was previously introduced to speed up calculations of acoustic images with microphone arrays. If, however, the array has a quasi-separable geometry, e.g. an otherwise separable array with a missing sensor, then the KAT acceleration can no longer be applied. In this letter, we review the definition of the KAT and provide a much simpler derivation that relies on an explicit new relation developed between Kronecker and Khatri-Rao matrix products. Additionally, we extend the KAT to deal with quasi-separable ar- rays, alleviating the restriction on the need of perfectly separable arrays. Furthermore, the KAT was originally only applicable to arrays with separable geometry [6]–[8]. The second main contribution we present in this letter is to relax this restriction, generalizing the KAT to deal with quasi-separable arrays, i.e., separable arrays in which some positions in the grid may be left empty. We conclude by analyzing the efficiency of the generalized KAT. This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at http://dx.doi.org/10.1109/LSP.2017.2674969 This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at http://dx.doi.org/10.1109/LSP.2017.2674969 This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at http://dx.doi.org/10.1109/LSP.2017.2674969 This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to pu The final version of record is available at http://dx.doi.org/10.1109/LSP.2017.2674969 SIGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 2017 SIGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 2017 This work was partly supported by FAPESP (Grants #14/06066-6 and #14/04256-2) and CNPq (Grant #306268/2014-0). Copyright c⃝2017 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to pubs-permissions@ieee.org. B. Masiero is with the Department of Communications, University of Campinas, SP, Brazil (e-mail: masiero@unicamp.br). V Nascimento is with the University of S˜ao Paulo SP Brazil This work was partly supported by FAPESP (Grants #14/06066-6 and #14/04256-2) and CNPq (Grant #306268/2014-0). ) 2017 IEEE. Personal use is permitted. For any other purposes, permission must be obtained from the IEEE by emailing pubs-permissions@ieee.org. q Copyright c⃝2017 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to pubs-permissions@ieee.org. p ( p ) V. Nascimento is with the University of S˜ao Paulo, SP, Brazil. B. Masiero is with the Department of Communications, University of Campinas, SP, Brazil (e-mail: masiero@unicamp.br). III. KRONECKER ARRAY TRANSFORM The same is valid for the sensor signal matrix X ∈CMy×Mx, which contains the values of x arranged in the same geometrical disposition as the sensors in the array. y Let us first specify the enumeration p0, · · · , pM−1 of the sensing positions. Suppose the arrays is designed as an Mx × My rectangular grid (M = MxMy). We enumerate the sensing positions ordered from top to bottom and from left to right. Breaking pm into its Cartesian components results in pm = h px (⌊m/My⌋) py(mod(m, My)) 0 iT , where px(m) and py(m) are the x and y coordinates of the m-th microphone, ⌊m⌋represents the largest integer smaller than m, and mod(·) represents the modulo operation. For simplicity, we assumed the array to be horizontally oriented. The same enumeration is used for the look directions u0, · · · , uN−1 distributed in a Nx × Ny rectangular grid (N = NxNy) with coordinates ux(n) and uy(n) in the parametrized U-space [6]. We now discuss why the form in (7) is said to be a fast transform of the adjoint matrix-vector product (5). We can readily verify that calculation of the adjoint product V H s x re- quires MxMyNxNy complex multiply-and-accumulate (MAC) operations. On the other hand, using (7) the required number of operations reduces to MyNxNy + MxMyNx complex MACs when XV ∗ x is computed first, or to MxNxNy + MxMyNy complex MACs when V H y X is computed first. The elements of a far-field manifold matrix associated to the above listed separable array and U-space parametrized rectangular scan grid are then given by y If we assume that Nx = Ny = √ N and Mx = My = √ M , and additionally, that the number of microphones contained in the array is substantially smaller than the number of scan points, i.e. M ≪N, than a rough estimate of the acceleration provided by the KAT lies in the order of √ M , which is in agreement with the acceleration estimated in [14]. Further acceleration might be achieved using the NFFT and NNFFT algorithms together with the KAT, as discussed in [2], [8]. However, for the sake of brevity, we will refrain from this discussion here. vs(m, n) = ej ωk c ux(⌊n/Ny⌋)px(⌊m/My⌋) × ej ωk c uy(mod(n,Ny))py(mod(m,My)). III. KRONECKER ARRAY TRANSFORM direction from ˆy = V Hx/M. Given that the KAT conditions are met, we can substitute V by V s and apply (4) to the adjoint matrix-vector product, resulting in (apart from a constant M) The KAT was introduced in [6] as a method to speed up calculation of a class of acoustic imaging algorithms (as discussed in Sec. IV). However, the reorganization of Kronecker products can be used to speed up any problem modeled as a matrix-vector product, as long as the matrix can be described as the Kronecker product of two smaller matrices [14]. In [8], the KAT was extended to be used with a larger group of acoustic imaging and superdirective microphone algorithms, as we show next. ˆy ∝V H s x = (V x ⊗V y)Hx. (5) (5) Using the well-known Kronecker product identity [9] vec(BQAT ) = (A ⊗B) vec (Q) , (6) (6) where A, B and Q are given matrices and vec(·) denotes vectorization by stacking the columns of a matrix, we rewrite where A, B and Q are given matrices and vec(·) denotes vectorization by stacking the columns of a matrix, we rewrite As its name suggests, the KAT is obtained by applying the above acceleration strategy to sensor arrays, more specifically, to sensor arrays of separable geometry, which, as shown below, guarantees that its separable manifold matrix V s can be recast as a Kronecker product V s = V x ⊗V y. bY = V H y XV ∗ x, (7) (7) where ˆy = vec( bY ) and x = vec(X). The source signal matrix bY ∈CNy×Nx contains all values of ˆy arranged in the same geometrical disposition as the scan grid, with the columns of the matrix representing the vertical y-axis and the rows of the matrix representing the horizontal x-axis. The same is valid for the sensor signal matrix X ∈CMy×Mx, which contains the values of x arranged in the same geometrical disposition as the sensors in the array. where ˆy = vec( bY ) and x = vec(X). The source signal matrix bY ∈CNy×Nx contains all values of ˆy arranged in the same geometrical disposition as the scan grid, with the columns of the matrix representing the vertical y-axis and the rows of the matrix representing the horizontal x-axis. I. INTRODUCTION First, we develop a general formulation for the KAT, which extends the derivation for superdirective microphones proposed in [8] to the original KAT for acoustic cameras. This results in a much more compact derivation than the original in [6], through There exist several techniques (e.g. [3], [4], [7], [13]) for estimating ˆy(ωk) (for superdirective microphone applications) or the average value of |ˆyi(ωk)|2 (for acoustic camera applica- tions, where ˆyi(ω) is the i-th entry of ˆy(ωk), i = 0 . . . N −1) from the array output vector x(ωk), all of them requiring the calculation of certain matrix-vector products involving V (ωk). Reference [6] argues that, especially for iterative algo- rithms and for large arrays, these matrix-vector products are a calculation bottleneck. To speed up these calculations, [6] proposes, based on the discussion in [14], to decompose the manifold matrix V (ωk) in the Kronecker product of two smaller matrices, which can be used to reorganize the computations and significantly accelerate the above listed operations. This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at http://dx.doi.org/10.1109/LSP.2017.2674969 SIGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 2017 This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prio The final version of record is available at http://dx.doi.org/10.1109/LSP.2017.2674969 SIGNAL PROCESSING LETTERS VOL ? NO ? ??? 2017 This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at http://dx.doi.org/10.1109/LSP.2017.2674969 SIGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 2017 This is the author's version of an article that has been published in this j The final version of record is availa SIGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 2017 2 SIGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 2017 IV. KAT FOR CSM-BASED METHODS Acoustic imaging algorithms generaly extract information not from the raw data x, but from the array’s narrow-band cross spectral matrix (CSM), defined as Rx = E{xxH}. The KAT, as presented in [6], was applicable only to this class of algorithms. We now present a new derivation for the KAT with CSM-based methods (CSM-KAT), relying upon the more general definition of the KAT presented in the previous section. We achieve a more compact and less cumbersome derivation then the derivation presented in [6] through the use of a, to the best of the authors knowledge, new relation developed between the Kronecker and the Khatri-Rao matrix products, presented in Appendix A. The horizontal array manifold matrix V x has size Mx × Nx, and the vertical array manifold matrix V y has size My × Ny. By comparing the inner structure of (2) with the inner structure of (3), it can be verified that V s = V x ⊗V y. (4) (4) Recapitulating, as long as we have a planar sensor array with separable geometry and we define a separable scan grid, we guarantee that the corresponding far-field manifold matrix can be decomposed as the Kronecker product of two more compact manifold matrices, which will allow a speed up in calculations, as discussed in [8]. For better comprehension, we repeat the derivation of the Adjoint Fast Transform below. Ignoring the presence of noise and defining Ry to be the CSM of y, we verify from (1) that Rx = V RyV H. (8) (8) III. KRONECKER ARRAY TRANSFORM (2) (2) We now define two new manifold matrices V x and V y, whose elements are given below vx(mx, nx) = e jωkux(nx)px(mx)/c, (3a) vy(my, ny) = e jωkuy(ny)py(my)/c. (3b) E. Personal use is permitted. For any other purposes, permission must be obtained from the IEEE by emailing pubs-permissions@ieee.org. V. GENERALIZED KAT FOR QUASI-SEPARABLE ARRAYS The matrix Γ ∈RM ′×M is a selection matrix built by setting [Γ]m,n = 1 when the mth element of x is equivalent to the nth element of xs and [Γ]m,n = 0 otherwise. m,n From (19) we can easily verify that the generalized direct fast transform is now given by We now define vec{Y} = vecd (Ry), where Y ∈RNy×Nx is the acoustic image sensed by a separable array. To conclude, we apply identity (6) to matrix Z, defined in (12), resulting in Xs = V yY V T x , x = Γ vec {Xs} . (20) x = Γ vec {Xs} . (20) (20) Z = eV yY eV T x , vec (Rx) = Ξ vec (Z) , (13) Note that Xs contains M −M ′ dummy entries, that are com- puted by the KAT, but are discarded when computing x. As we show below, this procedure is efficient when M ′ is large enough. which is exactly the CSM fast direct transform presented in [6]. p g g The adjoint transform y = [Γ (V x ⊗V y)]Hx results in the generalized adjoint fast transform We can further verify that the CSM adjoint transform vecd( bRy) = [Ξ( eV x ⊗eV y)]H vec(Rx), (14) (14) vec {Xs} = ΓT x, bY = V H y XsV ∗ x. (21) (21) can be recast as the CSM fast adjoint transform [6], allowing us to efficiently obtain the estimated acoustic image bY from Finally, combining (20) and (21) results in the generalized direct-adjoint fast transform Finally, combining (20) and (21) results in the generalized direct-adjoint fast transform vec(Z) = ΞT vec (Rx) , bY = eV H y Z eV ∗ x. (15) (15) Xs = V yY V T x , c Xs = G ◦Xs, bY =V H y c XsV ∗ x, (22) (22) By combining (12) and (14) and using the Kronecker “mixed product rule” [16]—note that ΞT Ξ equals the identity matrix as the permutation matrix is an orthogonal matrix—we obtain the direct-adjoint transform in the form where ◦is the Hadamard-Schur matrix product, and vec{G} = vecd{ΓT Γ}. Please note it is not possible to inlay the influence of Γ into V x or V y to arrive in a formulation similar to (17). V. GENERALIZED KAT FOR QUASI-SEPARABLE ARRAYS vecd( bRy) = ( eV x ⊗eV y)H( eV x ⊗eV y) vecd (Ry) = [( eV H x eV x) ⊗( eV H y eV y)] vecd (Ry) , (16) (16) V. GENERALIZED KAT FOR QUASI-SEPARABLE ARRAYS A ⊙B =  a1 ⊗b1 a2 ⊗b2 · · · aq ⊗bq  , (10) A ⊙B =  a1 ⊗b1 a2 ⊗b2 · · · aq ⊗bq  , (10) where aq and bq, represent the q-th column of A and B, respectively. A ⊙B =  a1 ⊗b1 a2 ⊗b2 · · · aq ⊗bq  , (10) where aq and bq, represent the q-th column of A and B, respectively. The KAT was developed under the assumption that the microphone array possesses separable geometry, as discussed in section III. However, an array with separable geometry may not be available, e.g., because some elements of a separable array were damaged and, thus, need to be discarded, resulting in an array with quasi-separable geometry. where aq and bq, represent the q-th column of A and B, respectively. Assuming that the KAT conditions are met, we substitute V by V s and apply equality (4) into (8). Furthermore, we assume that Ry is a diagonal matrix and apply identity (9) to the previous result, which leads to To apply the KAT in such cases, we define a “virtual” output vector xs = V sy generated from a “virtual” separable array with the least number of sensors M that contain all M ′ elements of the non-separable array of interest (with output vector x), such that vec (Rx) =  (V x ⊗V y)∗⊙(V x ⊗V y)  vecd (Ry) . (11) vec (Rx) =  (V x ⊗V y)∗⊙(V x ⊗V y)  vecd (Ry) . (11) We use the Kronecker Khatri-Rao identity (28) and the definitions eV x ≡(V ∗ x ⊙V x) and eV y ≡ V ∗ y ⊙V y  to rewrite (11) as (19) x = Γxs = ΓV sy = Γ (V x ⊗V y) y. (19) vec (Rx) = Ξ [( eV x ⊗eV y) vecd (Ry)] ∆= Ξ vec (Z) , (12) where Z is such that vec (Z) is the term between brackets, and Ξ is a permutation matrix. vec (Rx) = Ξ [( eV x ⊗eV y) vecd (Ry)] ∆= Ξ vec (Z) , (12) where Z is such that vec (Z) is the term between brackets, and Ξ is a permutation matrix. A. Adjoint Fast Transform Usually, CSM-based methods assume that all sources present in the sound field are mutually uncorrelated [3], [13]. This Usually, CSM-based methods assume that all sources present in the sound field are mutually uncorrelated [3], [13]. This The simplest algorithm for superdirectional microphones is the DAS beamformer [1] that estimates the signals at each look- This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at http://dx.doi.org/10.1109/LSP.2017.2674969 3 SIGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 2017 3 SIGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 2017 of V y, the (i, j)-th element of eV y is assumption results in Ry being diagonal, and greatly simplifies the calculations. We take advantage of the fact that Ry is assumed to be diagonal in the new derivation of the CSM-KAT by using the identity [11] h eV H y eV y i i,j = v∗ y,i ⊗vy,i H v∗ y,j ⊗vy,j  = vH y,ivy,j ∗⊗ vH y,ivy,j  = vH y,ivy,j 2 . (18) (18) vec  BP AT  = (A ⊙B) vecd (P ) , (9) (9) where P is a given diagonal matrix, vecd (·) is the vector formed from the diagonal elements of a square matrix, and A ⊙B is the columnwise Khatri-Rao product [15], defined as Note that in the last equality, we used the fact that vH y,ivy,j is a scalar, so the Kronecker product reduces to a regular product. Note that in the last equality, we used the fact that vH y,ivy,j is a scalar, so the Kronecker product reduces to a regular product. ) 2017 IEEE. Personal use is permitted. For any other purposes, permission must be obtained from the IEEE by emailing pubs-permissions@ieee.org. where Ξ is a permutation matrix. where Ξ is a permutation matrix. where Ξ is a permutation matrix. M ′ √ M + M/ √ N ≤ M ′ 2 max n√ M , M/ √ N o. (27) (27) Proof: Using the definitions of the Kronecker product and the Khatri-Rao product we verify that If we assume that M ≪N, we see that the obtained acceleration is roughly in the order of M ′/(2 √ M ). This suggests that it is preferable to use the generalized adjoint fast transform as long as L ≲M −2 √ M . (A ⊗B) ⊙(C ⊗D) =  (a1 ⊗b1) ⊗(c1 ⊗d1) · · · (a1 ⊗b2) ⊗(c1 ⊗d2) · · · (a1 ⊗bq) ⊗(c1 ⊗dq) · · · (a2 ⊗b1) ⊗(c2 ⊗d1) · · · (a2 ⊗bq) ⊗(c2 ⊗dq) · · · (ap ⊗b1) ⊗(cp ⊗d1) · · · (ap ⊗bq) ⊗(cp ⊗dq)  . (29) It is important to observe that the generalized KAT will likely not be effective if applied to a generic non-separable array. If we repeat the previous simulation with a random array containing M ′ sensors placed with no repetition in both x- and y-coordinates we will need a “virtual” separable array with M = M ′ × M ′ positions. Direct calculation still requires M ′N operations while the generalized KAT will now require M ′N + M ′2√ N complex MAC operations. This shows that for general non-separable arrays the use of the generalized KAT would not be advisable, as no acceleration is achieved. The Kronecker product is associative but not commutative. However, according to [10], (a ⊗b) = P (b ⊗a), (30) (30) where P is a permutation matrix. Therefore, we verify that where P is a permutation matrix. Therefore, we verify that (ai ⊗bj) ⊗(ci ⊗dj) = Iai ⊗P (ci ⊗bj) ⊗Idj = = (I ⊗P ⊗I)[ai ⊗(ci ⊗bj) ⊗dj] ≡ ≡Ξ[(ai ⊗ci) ⊗(bj ⊗dj)]. (31 (31) 1All MATLAB files necessary to recreate this simulation are available at http://ieeexplore.ieee.org, provided by the authors. SIGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 2017 SIGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 201 SIGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 2017 0.01 0.1 1 Time [ms] 0 10 20 30 40 50 60 L Nx = Ny = 64 Nx = Ny = 32 Nx = Ny = 16 to the calculations with a separable array by the selection matrix W ≡Γ∗⊗Γ = Γ ⊗Γ. This result allows the use of the CSM-KAT with quasi-separable arrays, resulting in the generalized CSM fast direct transform 0.01 0.1 Time [ms] 0 10 20 30 40 50 60 L Nx = Ny = 16 Z = eV yY eV T x , vec (Rx) = W Ξ vec (Z) , (24) the generalized CSM fast adjoint transform Z = eV yY eV T x , vec (Rx) = W Ξ vec (Z) , (24) the generalized CSM fast adjoint transform the generalized CSM fast adjoint transform vec(Z) = ΞT W T vec (Rx) , bY = eV H y Z eV ∗ x, (25) and the generalized CSM fast direct-adjoint transform (25) Z = eV yY eV T x , vec(bZ) = ΞT W T W Ξ vec (Z) , bY = eV H y bZ eV ∗ x. (26) (26) Fig. 1. Average calculation time for the DAS algorithm when applied to a separable array with Mx = My = 8 sensors positions and L (randomly chosen) missing sensors. The dashed line represents calculation with the adjoint matrix-vector product (5) while the straight line represents calculation with the generalized adjoint fast transform (21). Simulation was done in Matlab R2014a using a Intel Core2 Duo PC (3.16 GHz) with 1000 realizations per point. Here, again, we cannot eliminate the influence of ΞT W T W Ξ, nor inlay its influence in eV x or eV y, being necessary to use a composition of the previously presented direct and adjoint transforms to calculate the direct-adjoint transform. Here, again, we cannot eliminate the influence of ΞT W T W Ξ, nor inlay its influence in eV x or eV y, being necessary to use a composition of the previously presented direct and adjoint transforms to calculate the direct-adjoint transform. VII. CONCLUSION The contributions presented in this letter are twofold: (i) a new (shorter) derivation of the CSM-KAT, linking it with APPENDIX A PROOF OF THE KRONECKER KHATRI-RAO IDENTITY Theorem 1. Let the matrices A =  a1 a2 · · · ap  , B =  b1 b2 · · · bq  , C =  c1 c2 · · · cp  , and D =  d1 d2 · · · dq  be compatibly partitioned matrices, then Theorem 1. Let the matrices A =  a1 a2 · · · ap  , B =  b1 b2 · · · bq  , C =  c1 c2 · · · cp  , and D =  d1 d2 · · · dq  be compatibly partitioned matrices, then Theorem 1. Let the matrices A =  a1 a2 · · · ap  , B =  b1 b2 · · · bq  , C =  c1 c2 · · · cp  , and D =  d1 d2 · · · dq  be compatibly partitioned matrices, then Analytically, we verify that the matrix-vector calculation requires M ′N complex MAC operations, while the generalized KAT requires √ M N + M √ N complex MAC operations. The acceleration obtained with the generalized KAT is estimated as (A ⊗B) ⊙(C ⊗D) = Ξ [(A ⊙C) ⊗(B ⊙D)] , (28) (28) ) 2017 IEEE. Personal use is permitted. For any other purposes, permission must be obtained from the IEEE by emailing pubs-permissions@ieee.org. A. Generalized CSM-KAT In the same manner described in the previous section, we can also generalize the application of the CSM-KAT for quasi- separable arrays. To do so, we observe that which can be recast in the CSM fast direct-adjoint transform which can be recast in the CSM fast direct-adjoint transform bY = eV H y eV yY eV T x eV ∗ x. (17) (17) (17) vec (Rx) = (V ∗⊗V ) vec (Ry) =  (ΓV s)∗⊗(ΓV s)  vec (Ry) = (Γ∗⊗Γ) (V ∗ s ⊗V s) vec (Ry) . (23) As discussed in [6], implementing the direct-adjoint transform as bY = ( eV H y eV y)Y( eV T x eV ∗ x) can be much faster than using a composition of the direct and adjoint CSM-KAT as for large problems one can precompute eV H y eV y and eV T x eV ∗ x, which are real-valued matrices. In fact, letting vy,i denote the i-th column (23) Equation (23) shows us that, for CSM based methods, the calculation with a quasi-separable array can be directly related Equation (23) shows us that, for CSM based methods, the calculation with a quasi-separable array can be directly related 4 0.01 0.1 1 Time [ms] 0 10 20 30 40 50 60 L Nx = Ny = 64 Nx = Ny = 32 Nx = Ny = 16 Fig. 1. Average calculation time for the DAS algorithm when applied to a separable array with Mx = My = 8 sensors positions and L (randomly chosen) missing sensors. The dashed line represents calculation with the adjoint matrix-vector product (5) while the straight line represents calculation with the generalized adjoint fast transform (21). Simulation was done in Matlab R2014a using a Intel Core2 Duo PC (3.16 GHz) with 1000 realizations per point. al. Changes were made to this version by the publisher prior to publication. t http://dx.doi.org/10.1109/LSP.2017.2674969 This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at http://dx.doi.org/10.1109/LSP.2017.2674969 This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at http://dx.doi.org/10.1109/LSP.2017.2674969 IGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 2017 4 VI. EFFICIENCY OF THE GENERALIZED KAT the (more general) KAT through an explicit new relation between Kronecker and Khatri-Rao matrix products; and (ii) a generalization of the KAT to deal with quasi-separable arrays, which allows the use of the fast transforms when microphones in a separable array go defective. To evaluate the performance improvement obtained with the generalized KAT we simulate1 a directional microphone using DAS beamformer and compare calculation time of V Hx and (21). We define a separable scan grid with Nx = Ny = √ N directions and use an array with M sensors placed on a grid with separable geometry where L random sensors are defective, thus resulting in an array with M ′ = M −L sensors placed in a quasi-separable geometry. Fig. 1 compares the average calculation time for an array with Mx = My = 8, making evident the advantage of the generalized KAT. REFERENCES [1] J. Bitzer and K. U. Simmer, “Superdirective Microphone Arrays,” in Microphone Arrays. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001, pp. 19–38. pp [2] V. H. Nascimento, B. S. Masiero, and F. P. Ribeiro, “Acoustic Imaging Using the Kronecker Array Transform,” in Signals and Images: Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing, R. F. Coelho, V. H. Nascimento, R. L. de Queiroz, J. M. T. Romano, and C. C. Cavalcante, Eds. CRC Press, 2015, pp. 153–178. [3] T. F. Brooks and W. M. Humphreys, “A deconvolution approach for the mapping of acoustic sources (DAMAS) determined from phased microphone arrays,” Journal of Sound and Vibration, vol. 294, no. 4, pp. 856–879, 2006. [4] T. Yardibi, J. Li, P. Stoica, N. S. Zawodny, and L. N. Cattafesta, “A covariance fitting approach for correlated acoustic source mapping.” The Journal of the Acoustical Society of America, vol. 127, no. 5, pp. 2920–2931, 2010. [5] A. Xenaki, P. Gerstoft, and K. Mosegaard, “Compressive beamforming.” The Journal of the Acoustical Society of America, vol. 136, no. 1, pp. 260–271, 2014. [6] F. P. Ribeiro and V. H. Nascimento, “Fast transforms for acoustic imaging—part I: Theory,” IEEE Transactions on Image Processing, vol. 20, no. 8, pp. 2229–2240, 2011. [7] ——, “Fast transforms for acoustic imaging—part II: Applications,” IEEE Transactions on Image Processing, vol. 20, no. 8, pp. 2241–2247, 2011. [8] V. H. Nascimento, M. C. Silva, and B. S. Masiero, “Acoustic image estimation using fast transforms,” in 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM). IEEE, jul 2016, pp. 1–5. [9] R. A. Horn and C. R. Johnson, Topics in Matrix Analysis. Cambridge, MA: Cambridge University Press, 1991. [10] H. V. Henderson and S. R. Searle, “The vec-permutation matrix, the vec operator and Kronecker products: a review,” Linear and Multilinear Algebra, vol. 9, no. 4, pp. 271–288, jan 1981. g pp j [11] H. Lev-Ari, “Efficient solution of linear matrix equations with application to multistatic antenna array processing,” Communications in Information & Systems, vol. 5, no. 1, pp. 123–130, 2005. [12] D. H. Johnson and D. E. Dudgeon, Array Signal Processing: Concepts and Techniques. Prentice Hall, Englewood-Cliffs N.J., 1993. [13] H. Krim and M. Viberg, “Two decades of array signal processing research: the parametric approach,” IEEE Signal Processing Magazine, vol. 13, no. 4, pp. 67–94, 1996. [14] C. F. van Loan and N. Applying equality (31) to (29) results in (28). Applying equality (31) to (29) results in (28). Starting from [(A ⊙C) ⊗(B ⊙D)] and applying identity (31) will also result into (28), which concludes the proof. 1All MATLAB files necessary to recreate this simulation are available at http://ieeexplore.ieee.org, provided by the authors. Copyright (c) 2017 IEEE. Personal use is permitted. For any other purposes, permission must be obtained from the IEEE by emailing pubs-permissions@ieee.org. This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at http://dx.doi.org/10.1109/LSP.2017.2674969 5 5 SIGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 2017 SIGNAL PROCESSING LETTERS, VOL. ?, NO. ?, ??? 2017 [16] J. Brewer, “Kronecker products and matrix calculus in system theory,” IEEE Transactions on Circuits and Systems, vol. 25, no. 9, pp. 772–781, sep 1978. Copyright (c) 2017 IEEE. Personal use is permitted. For any other purposes, permission must be obtained from the IEEE by emailing pubs-permissions@ieee.org. REFERENCES Pitsianis, “Approximation with Kronecker Products,” in Linear Algebra for Large Scale and Real Time Applications, M. S. Moonen, G. H. Golub, and B. L. R. Moor, Eds. Dordrecht: Springer Netherlands, 1993, no. 1991, pp. 293–314. [15] C. G. Khatri and C. R. Rao, “Solutions to Some Functional Equations and Their Applications to Characterization of Probability Distributions,” Sankhy: The Indian Journal of Statistics, Series A (1961-2002), vol. 30, no. 2, pp. 167–180, 1968. [16] J. Brewer, “Kronecker products and matrix calculus in system theory,” IEEE Transactions on Circuits and Systems, vol. 25, no. 9, pp. 772–781, sep 1978. Copyright (c) 2017 IEEE. Personal use is permitted. For any other purposes, permission must be obtained from the IEEE by emailing pubs-permissions@ieee.org.
https://openalex.org/W2969099453
https://periodicos.ufmg.br/index.php/permusi/article/download/5176/3215
English
null
Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano
Per Musi
2,018
cc-by
6,958
1 A Brazilian serenade genre. MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. SCIENTIFIC ARTICLE Interpretando o imaginário de seresta na 7ª Valsa de Esquina para piano de Francisco Mignone Sigridur Malaguti Universidade Federal do Estado do Rio de Janeiro, Rio de Janeiro, Brazil simalagu@centroin.com.br Sigridur Malaguti Universidade Federal do Estado do Rio de Janeiro, Rio de Janeiro, Brazil simalagu@centroin.com.br Sérgio Barrenechea Sérgio Barrenechea (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. 4 Choro (weeping): A popular urban music genre from Rio de Janeiro that started to develop around 1870. Choro can be looked upon as a style, since it is characterized by a way of playing: by improvisation, by virtuoso instrumental approach, and by melancholic inflexions that justify the name of the genre. The term regional (regional) was later on instituted for the group of choro musicians. 1 – Introduction When the Brazilian composer Francisco Mignone (1897-1986) returned from Italy in 1929, after studying composition for nine years, he was fully equipped as a composer. That moment in Brazil was imbued with nationalist ideology, referred to amongst artists and intellectuals as Brazilian Modernism, and the quest was for a Brazilian national identity. The words of writer, journalist and musicologist Mário de Andrade indicated a formula2 to create a Brazilian musical art work: it should be based on musical elements that carried the idiosyncrasies of Brazilian folklore or popular music, which should then be developed into sophisticated art work through compositional techniques acquired from the Western musical tradition. Mignone adhered to the modernist movement and established a strong and productive friendship with Mário de Andrade. Much of Mignone’s nationalist production is inspired by his youth in the city of São Paulo when he participated in street-serenades, playing with popular instrumental groups called chorões3. This source of inspiration is present in his 12 Valsas de Esquina (12 Corner Waltzes) for piano, composed between 1938 and 1943. The title of the waltzes is by itself an invitation to the imagination. What impact should the metaphor of a ‘corner’, indicating the street as a musical scenario, have on the performer’s imagination? How do the character descriptive markings in the score such as: soturno e seresteiro (grim and serenade-like) or imitando a flauta seresteira (imitating the serenading flute), influence the performer’s creation of an interpretive concept? And how to perform the idiomatic elements of choro4 - embodied into serenade music in Brazil by choro-musicians - that are quoted by Mignone in the 12 Valsas de Esquina? With abundant references to the serenade scenery, 7ª Valsa de Esquina (Corner Waltz Nr.7), composed in 1940, appears to be a fitting piece to approach these questions. 5 Modinha: Derived from moda, an ancient Portuguese song type. Historically it is the most characteristic and most traditional Brazilian song genre. Sérgio Barrenechea Sérgio Barrenechea Universidade Federal do Estado do Rio de Janeiro, Rio de Janeiro, Brazil sergio.barrenechea@unirio.br g Universidade Federal do Estado do Rio de Janeiro, Rio de Janeiro, Brazil sergio.barrenechea@unirio.br Abstract: The imagery of the Brazilian seresta is a prominent trait of Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz Nr.7) for piano. It is first evoked by the title of the piece itself but then also by the composer’s markings in the score, his idiomatic references to the instruments traditionally played in serenades in Brazil, as well as to musical features easily identifiable as belonging to a specific Brazilian music universe. The tradition of a serenade performance style still prevails in small cities, like Conservatória in the State of Rio de Janeiro. The question arises of how to translate the composer’s references to the seresta tradition into interpretation. To approach this problem, recordings of different renditions of the piece were analyzed, with a focus on the varied ways in which the interpreters have used ‘shaping of tempo’ in their performance to achieve the nostalgic and amorous atmosphere of the serenade in Brazil. Keywords: serenade-imagery; Francisco Mignone; interpretation of 7ª Valsa de Esquina (Corner Waltz Nr.7); tempo rubato; shaping of tempo. Resumo: O imaginário de seresta é um aspecto proeminente na 7ª Valsa de Esquina para piano de Francisco Mignone: primeiro é indicado no próprio título da peça, que convida para um cenário de rua; em seguida é também evocado pelas indicações na partitura e por referências idiomáticas do compositor a instrumentos tocados em serestas no Brasil; e ainda por fartas referências a feições musicais facilmente identificadas como pertencentes a um universo musical brasileiro. Um estilo específico de tocar música de seresta ainda pode ser encontrado em pequenas cidades como Conservatória/RJ, onde a tradição de seresta se mantém até hoje. Como traduzir essas referências do compositor à tradição de seresta em interpretação? Para abordar este problema, gravações de diferentes interpretações da peça foram analisadas, observando as variadas maneiras com que os intérpretes moldaram o tempo na busca por uma atmosfera saudosa e amorosa, emblemática da seresta no Brasil. Palavras-chave: imaginário de seresta; Francisco Mignone; interpretação da 7ª Valsa de Esquina; tempo rubato; moldagem do tempo. Submission date: 24 January 2018 Final approval date: 17 April 2018 Submission date: 24 January 2018 Final approval date: 17 April 2018 1 MALAGUTI, Sigridur; BARRENECHEA, Sérgio. 2 See ANDRADE (1972). 3 Chorões: Musicians who play choro. 4 Choro (weeping): A popular urban music genre from Rio de Janeiro that started to develop around 1870. Choro can be looked upon as a style, since it is characterized by a way of playing: by improvisation, by virtuoso instrumental approach, and by melancholic inflexions that justify the name of the genre. The term regional (regional) was later on instituted for the group of choro musicians. 5 Modinha: Derived from moda, an ancient Portuguese song type. Historically it is the most characteristic and most traditional Brazilian song genre. 2.1 – Converging with modinha5 and choro The practice of singing beneath the beloved maiden’s window seems to have been present in Western cultures since the Middle Ages. In Brazil, however, the first account of serenades comes from the beginning of the 18th century. The Brazilian song genre modinha makes its appearance during the same century and after evolving in both high society salons and popular music practices, it is found as the sentimental-romantic modinha in the repertory of the late 19th century serenade singer. The nostalgic and sentimental atmosphere of the Brazilian serenade may be an influence from the expressive features of the modinha but these features may also be traced to the cultural inheritance of the colonizing country Portugal. According to the choro- 2 MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. specialist CAZES (2010, p.15), nostalgic and sentimental expression can be detected in the music of all countries colonized by Portugal. During the golden age of the serenade in Brazil, in the late 19th century and the beginning of the 20th, the instrumental style of choro was being molded in the Brazilian capital. This event in the history of Rio de Janeiro is well described by an amateur musician PINTO, who was active in the choro-scene of this time. He describes the chorões and their serenades: specialist CAZES (2010, p.15), nostalgic and sentimental expression can be detected in the music of all countries colonized by Portugal. During the golden age of the serenade in Brazil, in the late 19th century and the beginning of the 20th, the instrumental style of choro was being molded in the Brazilian capital. This event in the history of Rio de Janeiro is well described by an amateur musician PINTO, who was active in the choro-scene of this time. 8Topics: As denominated by authors of the Topic Theory, like RATNER, AGAWU and HATTEN. Derives from the Greek topoi and deals with musical expression and meaning. “The topic theory is a tool for musical analysis that surpasses mere formalism, as it involves both musical knowledge and historical-cultural interpretation, it operates as the access to the meaning and the nexus at work in Brazilian music” (PIEDADE, p.6, authors’ translation). 2.1 – Converging with modinha5 and choro He describes the chorões and their serenades: They composed music full of inspiration and melodies that satisfied the audience of the splendid moonlight serenades, where the guitar arpeggios, the resonant flute notes, and the vibrations of the cavaquinho, woke up the habitants of the entire block, windows were opened, as well as the doors of the homes, inviting the choro-group to enter (PINTO, 1978, p.97). The instrumental style of choro - the core instrumentation being guitars, cavaquinhos6 and solo instruments, most often the flute - marks the serenade tradition with its stylistic features. The chorões adopted into their style musical genres imported from Europe, such as polka, schottisch7 and waltz. Modinha, on the other hand, acquired “national characterization amongst musicians of popular music, the serenade singers” (ALVARENGA, 1982, p.329) through the output of serenade modinhas that these singers produced in partnership with lettered romantic poets (TINHORÃO, 1998). During the Second Brazilian Empire (1840-1889) modinha gradually incorporated the meter of the waltz and the binary meter of tempo de schottisch that were already being danced in high society balls, abandoning the 2/4 and C previously used in the ‘salon’-modinha (modinha de salão) of the First Brazilian Empire (1822-1840) (ALVARENGA, 1982, p.329-330). The serenade became popular during the 19th century in the big cities of the country but in smaller cities like Campinas in São Paulo State, it was only with the installation of public street-lights in 1870 that “the youth started the serenade strolls for their beloved ones (TINHORÃO, 1976, p.27). With the arrival of the radio and rapid urbanization after the Second World War, the serenade tradition fell into decline being maintained solely in some smaller cities like Conservatória in Rio de Janeiro State. There, 137 years of serenade tradition have gone by, and today it is the city’s principal source of income: the serenades that take place every Friday and Saturday at 11pm, with the nostalgic waltzes and songs in minor keys, have even become a tourist attraction. 7 Schottisch: In Brazil, it appeared around 1850 as a salon dance in binary meter that resembled the polka, even though slightly slower. It does not have any known link with Scotland. It is the origin of the dance xote from Northeast-Brazil, traditionally played with accordion at popular balls. 6 Cavaquinho: A characteristic Brazilian four string instrument, of Portuguese origin. It is normally tuned on D-B-G-D. 6 Cavaquinho: A characteristic Brazilian four string instrument, of Portuguese origin. It is normally tuned on D-B-G-D. 2.2 – A universe of Brazilian music codes Derived from this evolution in Brazil’s musical scenario is a selection of music codes that the Brazilian researcher PIEDADE (2005) has denominated ‘golden age topics’8 (tópicas época de ouro). This is a group of topics 7 Schottisch: In Brazil, it appeared around 1850 as a salon dance in binary meter that resembled the polka, even though slightly slower. It does not have any known link with Scotland. It is the origin of the dance xote from Northeast-Brazil, traditionally played with accordion at popular balls. 8Topics: As denominated by authors of the Topic Theory, like RATNER, AGAWU and HATTEN. Derives from the Greek topoi and deals with musical expression and meaning. “The topic theory is a tool for musical analysis that surpasses mere formalism, as it involves both musical knowledge and historical-cultural interpretation, it operates as the access to the meaning and the nexus at work in Brazilian music” (PIEDADE, p.6, authors’ translation). 3 MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. in which the mannerisms of ancient Brazilian waltzes and serenades reign, where nostalgia of the epoch of simplicity and lyricism, countryside and fairness, rules. A little of the Lusitanian world is present […], together with evocation of fado9 and in the naivety of the modinhas. As in a myth, a deep Brazil from the past manifests itself through melodic spins and ornaments […], rhythmic patterns […] and certain motivic patterns […] that are strongly present in the world of choro and several other repertories of Brazilian music, not only on the more superficial level but as well in the more profound structures. [In the] Valsas de Esquina by Francisco Mignone […] golden- age topics are present with melodies in the front, in cantabile style, always with lyricism and nostalgia (PIEDADE, 2005, p.5, authors’ translation). In the opinion of the Finnish theorist TARASTI topics reside in the communicative structure of music. He identifies two levels of structure in music. Firstly the communicative structure, habited by musical mechanisms that the composer uses to communicate his ideas. This level is a style-breeder since the composer follows certain stylistic norms. 2.2 – A universe of Brazilian music codes In a space generated by the communicative structure lies the other structural level, structure of meaning, and here “... the true aesthetic moment of music is to be found”, says TARASTI (1994, p.18). In the opinion of the Finnish theorist TARASTI topics reside in the communicative structure of music. He identifies two levels of structure in music. Firstly the communicative structure, habited by musical mechanisms that the composer uses to communicate his ideas. This level is a style-breeder since the composer follows certain stylistic norms. In a space generated by the communicative structure lies the other structural level, structure of meaning, and here “... the true aesthetic moment of music is to be found”, says TARASTI (1994, p.18). Let us suppose, as suggested by PIEDADE (2005, p.5), that cantabile melodies that sound “with lyricism and nostalgia” in 7ª Valsa de Esquina are a golden age topic. This kind of melody, normally assigned to the pianist’s right hand, is not simply a melody rich with lyricism. On the contrary, it refers to a specific universe of Brazilian musicality, full of sociocultural significance. Moreover, the markings of character in the musical score, like soturno e seresteiro, leave no doubt as to the communicative intentions of the composer. Similarly, we can point baixaria10, a stylistic phenomenon of choro, as another golden age topic of 7ª Valsa de Esquina. This is a part played by the accompanying acoustic guitar that has the role to keep the beat and provide the harmony, besides creating a bass line that interacts with the main melody in moments of low activity. The left-hand part of 7ª Valsa de Esquina frequently makes reference to this practice. 10 Baixaria: A specific kind of improvised bass line played by the choro guitar, often a 7 stringed one. Countermelodies are created by the guitar player to enhance the main melodic line, often resulting in a rich dialogue. 9 Fado: A Portuguese song genre, melancholic and fatalistic. and they are invisible, like the rules of grammar, to the native speaker) (BOWEN, 1996, p.32). According to this author there are two difficulties to be faced when one takes on the task of performing earlier styles: firstly, it is necessary to adopt an interpretive path that offers stylistically adequate options for expressiveness; secondly, it is necessary to become deeply involved with the stylistic conventions of the epoch in question. These criteria can be applied to the interpretation of 7ª Valsa de Esquina, in spite of its more recent location in the timeline. In examining musical discourse, the aforementioned author TARASTI reaches the conclusion that there are two different models: ideological and technological discourse. The ideological model is related to concepts and norms that consider music with the parameter of aesthetic values predominant in society. The technological one attends aspects related to the composition and the interpretation of the music. TARASTI believes that in traditional music cultures, technological knowledge is transmitted orally. Such is the case in our own music tradition with regard to musical interpretation and teaching. The models guiding these activities can be regarded as special means of manipulation or modes of persuasion (TARASTI, 1994, p.17). In fact, this statement is likely to be true in the area of musical interpretation. Frequently a lineage of performance styles and know-how can be observed descending successively from teacher to pupil. In the words of BOWEN (1996), different features of a given performance can derive from a variety of styles that as a whole establish the general style of the performance. Styles can stem from institutions, instrument-traditions, epochs, places, repertories and genres. In the process of creating a performance concept of 7ª Valsa de Esquina, keeping in mind the piece’s reference to communicative structures that refer to a specific Brazilian cultural-musical phenomena, let us now pursue expressive options suitable to the piece and engage with the piece’s stylistic conventions. Many authors in the area of theory of performance practice have suggested that a good way to do that is to conduct an aural analysis of a selection of different recordings of the piece. GERLING (2008, p.8) believes that “what interests us in recordings is that, since they are a representation of the musical sound of the work, they can also be used as an additional tool to the actual reading of the score”. According to him a comparative analysis of available recordings should not have the objective of imitating any interpretive concept. 3.1 – The quest for an interpretive concept Music exists in the composer’s mind before it is translated to the musical score, which is limited in terms of precision in dynamics, tempo and articulation. The performer translates the score into an interpretation of the work (TARASTI, 1994), frequently unaware of the fact that the stylistic conventions of his/her time or geographic region characterize the performance (BOWEN, 1996). The theorist BOWEN comments about first experiences of earlier performance styles: We realize that many of the ‘rules’ which we take for granted—like ‘Don't speed up when you get louder,’ ‘Always play with a singing tone,’ are conventions which were drilled into us at an early age. (These conventions essentially define our home ‘style,’ 4 MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. and they are invisible, like the rules of grammar, to the native speaker) (BOWEN, 1996, p.32). Instead, this kind of comparison gives the interpreter “greater flexibility in the search for his/her own expression” (GERLING, 2008, p.19, authors’ translation). Francisco Mignone was a skillful pianist and he recorded the whole set of his 12 Valsas de Esquina, leaving the legacy of his performance for posterity. Again quoting BOWEN (1996, p.18), “the composer's performance is privileged in some way and this performance adds to our information about the work […] in the same way as metronome marks or other directions or annotations on the score”. In Mignone’s recording of 7ª Valsa de Esquina, a strong serenade- mood prevails. This is a very subjective statement: How can one measure or evaluate the ‘serenade-ness’ of a piece of music that is out of any contextual setting of a serenade, and, in addition, wears the garb of concert music? The Brazilian music universe, to which the aforementioned golden age topics belong, hosts a peculiar way of note-grouping inside the phrase. A culturally fluent listener will easily decipher these codes of expression, set off by a 5 MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. melody sung with rhythmic flexibility. This tempo flexibility transferred to the piano, together with other parameters like timbre, articulation and dynamics, are the agents responsible for the serenade-atmosphere à la Mignone. melody sung with rhythmic flexibility. This tempo flexibility transferred to the piano, together with other parameters like timbre, articulation and dynamics, are the agents responsible for the serenade-atmosphere à la Mignone. Visiting a serenade in Conservatória in December 2014, it was possible to confirm that the melodic rendition of the serenade singers ‘floats’ above the steady rhythmic flow of the accompanying instruments. Moreover, when there are words loaded with sentimental significance, they are often sustained in a rubato and the accompanists follow these expressive events accordingly. The songs always end with a very expressive molto rallentando. Of course, there is no guarantee, and it is even unlikely, that the serenade played in Conservatória nowadays has the same stylistic characteristics as Mignone experienced in the street serenades in São Paulo city at the beginning of the 20th century. and they are invisible, like the rules of grammar, to the native speaker) (BOWEN, 1996, p.32). However, the sentimental and nostalgic content, at least partly inherited from the modinha, and the expressive devices like the melodic rubato, most certainly are common to both epochs. The ethnomusicologist ULHÔA (2006) created the concept “malleable meter” (métrica derramada) which accounts for the flexibility and independence of the sung melody in Brazilian popular music, an aspect that is at the root of its expressiveness: [In] the malleable meter, a superposition of syllable-division and a loose “Brazilianized” synchronization of the Portuguese accentuation with the regular musical meter of the Western tradition, takes place (ULHÔA, 2006, p.2, authors’ translation). Singing is the performance practice analyzed by ULHÔA to demonstrate her concept of ‘malleable meter’. However, the concept may be transferred to instrumental music. TARASTI, whilst discussing the ideas of the theorist Roland Barthes concerning the music of Robert Schumann, says: In music the body starts to ‘speak’, as suggested by the quasiparlando directive so often used by Schumann. The human voice is referred to as a gesture which, particularly in Romantic music, was internalized into instrumental pieces as well (even Hugo Riemann believed that song was the origin of all music) (TARASTI, 1994, p.13). In this way, the musical discourse of singing, its gestures, can be, and is often and naturally, transferred to instrumental music. In this way, the musical discourse of singing, its gestures, can be, and is often and naturally, transferred to instrumental music. 3.2 – Seresta-atmosphere and the shaping of time The 7ª Valsa de Esquina has the structure ABA and coda. In Section A the left hand is assigned the baixaria - the idiomatic bass melody played by the choro guitar - and the right hand in Section B has a melody addressed with the written description: ‘imitating the serenade flute’ (imitando a flauta seresteira). To investigate the shaping of tempo in a performance that intends to translate the serenade-imagery involved, we observe the first 16 measures of Section A (1st Ending) in the performance of five artists: Francisco Mignone, Arnaldo Estrella, Arthur Moreira Lima, Maria Josephina Mignone and Duo Barrenechea. As may be observed in Figure 1, there 6 MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. are abundant tempo and dynamic markings for these 16 measures: from m.8-16 there are changes in tempo in every measure. Figure 1: 7ª Valsa de Esquina m.1-16: tempo and dynamic indications marked in the score. Compasso 8 9 10 15 16 Tempo Moderadamente poco affrett a tempo poco affrett a tempo poco affrett a tempo-poco ritard affrett.-rit Dinâmica p cresc. pouco a pouco mf dim Outros Com sonoridade apagada 1 a 7 11 a 12 13 a 14 Figure 1: 7ª Valsa de Esquina m.1-16: tempo and dynamic indications marked in the score. In the first 6 measures, on the other hand, no tempo indications other than moderadamente (moderately) appear and here the performers’ expressive intention to establish a serenade- ambience through tempo shaping becomes more explicit. Spectrograms and graphics were created with the computer software Sonic Visualizer that demonstrate the tempo in bpm11 in each measure of m.1-16 in all five performances. To create the graphics, a key on the computer is struck at the start of each measure during the playing of the recording. Thus, the difference of tempo from one measure to the other becomes clear and considerations can be made about what effect this has on the performance. In a Valsa de Esquina which has all three beats articulated, this method could be applied to measure the tempo relation between the 3 beats of the triple meter. The 7ª Valsa de Esquina has notes with the duration of 2 beats (see m.1-6 in Figure 2) that make this kind of graph difficult to accomplish. 11 Bpm: abbreviation for ‘beats per minute’. 3.2 – Seresta-atmosphere and the shaping of time Such measurement could provide some information about the performer’s concept of the waltz-meter. Moreover, it could possibly shed some light on the metric characteristics of the Brazilian waltz. As may be seen in the musical example in Figure 2, the bass line - or baixaria - at the beginning of the 7ª Valsa de Esquina presents a motif of an ascending third: a G (dotted minim) ascends to Bb (a minim added up to a double-dotted quaver, followed by an ornamental note that links to the next phrase) in a two measure long phrase. This two-note motif is repeated twice in a sequential reiteration, each starting note - approached from below by an ornamental semitone - being a second higher than the previous one. The ascending third is responded by the right hand, with a kind of inversion of the original motif: a descending third that resolves chromatically into the succeeding chord: Figure 2: 7ª Valsa de Esquina, m.1-6. Figure 2: 7ª Valsa de Esquina, m.1-6. 7 7 MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. In his recording (1958), Mignone anticipates the attack of the ascending third (down beat of the second measure of each phrase). This extends the length of the second measure of each of the 2 measure phrases in his performance of m.1-6, as may be seen in the graph of Figure 3 (m.1-2: 37 and 29 bpm; m.3-4:61 and 46 bpm; m.5-6:-64 and 49 bpm). Figure 3: 7ª Valsa de Esquina, m.1-16, performed by Francisco Mignone: white graph – dynamic shape; blue graph – tempo in each measure (bpm). Figure 3: 7ª Valsa de Esquina, m.1-16, performed by Francisco Mignone: white graph – dynamic shape; blue graph – tempo in each measure (bpm). Arnaldo Estrella (1908-1981) seems to have conceived the phrases in a similar manner. In his performance (1950) the middle of each phrase, the ascending third, is emphasized. Figure 4 demonstrates his relatively constant tempo in m.1-16. Figure 4: 7ª Valsa de Esquina m.1-16, performed by Arnaldo Estrella: white graph – dynamic shape; orange graph – tempo in each measure (bpm). 3.2 – Seresta-atmosphere and the shaping of time Figure 4: 7ª Valsa de Esquina m.1-16, performed by Arnaldo Estrella: white graph – dynamic shape; orange graph – tempo in each measure (bpm). 8 MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. Mignone and Estrella, besides contemporaries, had a close relationship, since Estrella debuted many of Mignone’s piano works, some of which were composed in his honour. Very likely this conceptual similarity in phrasing derives from this familiarity and the fact that they breathed in the musical tendencies of the same epoch. In Estrella’s case, however, this concept in phrasing does not seem to alter the tempo balance (see Figure 4). It is interesting to observe in a choro-version of Waltz Op.64 Nr.7 in C# Major by Chopin12 that the guitar players of Jacob do Bandolim13 (Bandolin-Jacob) display a similar concept of tempo shaping inside the metric feel of the waltz. In spite of keeping a steady pulse, there is an impression of anticipated arrival on the down beat of the triple meter. Arthur Moreira Lima (born 1940), who recorded the 12 Valsas de Esquina in 1982, has a different concept of the beginning of the 7ª Valsa de Esquina. He emphasizes the Bb of the middle of the first phrase but plays it as if it was the beginning of a phrase and the response in the right hand on the second beat is intensified, and consequently resolved, on the downbeat of the next measure. This phrasing does not affect the tempo in his performance much, as may be seen in Figure 5. Figure 5: 7ª Valsa de Esquina, m.1-16, performed by Arthur Moreira Lima: white graph – dynamic shape; green graph – tempo in each measure (bpm). Figure 5: 7ª Valsa de Esquina, m.1-16, performed by Arthur Moreira Lima: white graph – dynamic shape; green graph – tempo in each measure (bpm). Maria Josephina Mignone, who also recorded the complete set of the 12 Valsas de Esquina (1997), shows a concept of phrasing similar to that of Moreira Lima. 13 Jacob do Bandolim (1918-1969): One of the most important players of the instrument bandolim, originally developed from the mandola in Italy in the 18th century and diffused in Brazil via Portugal. 12 The recording can be accessed on Youtube <https://www.youtube.com/watch?v=arYFnSr559s> 3.2 – Seresta-atmosphere and the shaping of time She, on the other hand, demonstrates a concept of tempo shaping in which a longer measure keeps alternating with a shorter measure (see Figure 6). This model of tempo shaping was seen in Francisco Mignone’s performance, even though in Maria Josephina’s performance the 1st of each two measures is the longer one (m.1-2: 21 and 36 bpm; m.3-4: 33 and 50 bpm; m.5-6:39 and 40 bpm), contrary to what happened in the composer’s performance. Maria Josephina is Francisco Mignone’s widow 9 MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. and second wife. One may presume, and in interviews Maria Josephina herself has confirmed, that through the proximity of their life together she assimilated much of his musicality and his concept of performing the pieces. She was the main interpreter of his piano works and they performed a great deal together on 2 pianos. and second wife. One may presume, and in interviews Maria Josephina herself has confirmed, that through the proximity of their life together she assimilated much of his musicality and his concept of performing the pieces. She was the main interpreter of his piano works and they performed a great deal together on 2 pianos. Figure 6: 7ª Valsa de Esquina, m.1-16, performed by Maria Josephina Mignone: white graph– dynamic shape; red graph – tempo in each measure (bpm). Figure 6: 7ª Valsa de Esquina, m.1-16, performed by Maria Josephina Mignone: white graph– dynamic shape; red graph – tempo in each measure (bpm). Figure 7 shows the first four measures of a transcription of the 7ª Valsa de Esquina for flute and piano, made by Mignone himself in 1967. In this transcription, the piano has the role of rhythmic and harmonic accompaniment, commonly played by the guitar in a choro-group. Surprisingly, the flute is responsible for the baixaria melody which in the original version of this waltz is played by the pianist’s left hand. It is worth mentioning that in the second part of Section A (2nd Ending) Mignone writes a virtuoso part for the flute, in an improvisational style, supposedly referring to the flute of the choro, while the piano takes over the baixaria part. Figure 7: 7ª Valsa de Esquina, m.1-4. Mignone’s transcription for flute and piano. The flute plays the part of the baixaria. 3.2 – Seresta-atmosphere and the shaping of time Figure 7: 7ª Valsa de Esquina, m.1-4. Mignone’s transcription for flute and piano. The flute plays the part of the baixaria. 10 10 MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. Figure 8 shows a graph made of a rather recent recording (2010) by Sérgio and Lúcia Barrenechea - Duo Barrenechea - of this transcription (m.1-16) of the 7ª Valsa de Esquina. In the context of an ensemble the shaping of tempo has the perspective of the steady pulse being maintained by the accompanying instrument whilst the solo instrument is rather free to play with melodic rubato. Figure 8: 7ª Valsa de Esquina, m.1-16, performed by Sérgio Barrenechea (flute) and Lúcia Barrenechea (piano): white graph – dynamic shape; purple graph – tempo in each measure (bpm). Figure 8: 7ª Valsa de Esquina, m.1-16, performed by Sérgio Barrenechea (flute) and Lúcia Barrenechea (piano): white graph – dynamic shape; purple graph – tempo in each measure (bpm). Figure 9 demonstrates the tempo in each measure (m.1-16) of all recordings analyzed: Figure 9: 7ª Valsa de Esquina, mm.1-16. Tempo (bpm) in each measure of all recordings analyzed. Measure 1º 2º 3º 4º 5º 6º 7º 8º 9º 10º 11º 12º 13º 14º 15º 16º Tempo Moderadamente poco affrett a tempo poco affrett a tempo poco affrett a tempo affrett. Dynamics p cresc. pouco a pouco mf dim poco ritard rit. F.Mignone 37 29 61 46 64 49 35 50 49 58 46 54 67 72 73 36 A.Estrella 36 40 51 53 52 49 49 63 52 86 48 71 75 82 85 34 A.M.Lima 32 32 36 42 46 32 26 75 45 63 37 55 69 86 55 45 M.J.Mignone 21 36 33 50 39 40 27 61 35 46 40 52 53 75 52 31 Duo Barrenechea 35 39 40 40 43 38 36 53 35 52 36 40 43 41 32 28 Tempo per measure (bpm) Figure 9: 7ª Valsa de Esquina, mm.1-16. Tempo (bpm) in each measure of all recordings analyzed. 3.2 – Seresta-atmosphere and the shaping of time From Figure 9 it can be concluded that in the recordings analyzed the shaping of tempo in m.7- 16 generally is according to the tempo indications written in the score. On the other hand, in the first 6 measures, with no tempo indications made by the composer, a more intuitive tempo shaping takes place: Francisco Mignone shortens the 1st measure of each pair of measures (speeds up the tempo), while Maria Josephina does the opposite. Estrella has the tempo per measure varying somewhere between 36 and 53 bpm, whilst the variation in the tempo of 11 MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. Moreira Lima is between 32 and 46 bpm. The smallest span between the slowest and fastest measure is observed in the performance of Duo Barrenechea (slowest 35 - fastest 43 bpm). In all performances a tempo peak is observed, an intuitive one, not written in the score, towards the 4th (Maria Josephina Mignone and Estrella) or 5th measure (Mignone, Moreira Lima and Duo Barrenechea). 4 – Final Considerations Imagery of seresta is present in many of the 12 Valsas de Esquina for piano by Francisco Mignone: in the word Esquina (Corner), used in the title, indicating an out-door music event; in the character indications written in the score; and in the ‘echos’, inside the musical texture, of instruments commonly used in serenades in Brazil. Shaping of tempo is an essential parameter for establishing what can be considered a serenade-atmosphere. The ‘malleable meter’ applied to a melody (ULHÔA, 2006) – equally found in serenades in Conservatória/RJ, in the rendition of Chopin by choro players, as well as in the historical recordings by Francisco Mignone and Arnaldo Estrella discussed in this article - engenders the tender, sentimental and nostalgic atmosphere of the Brazilian serenade. This melodic rubato, in the case of a pianist playing without accompaniment, often diffuses the meter of the waltz. Each one of the performers of the recordings analyzed created their own interpretation of the elements of the seresta and the comparison of their renditions does not offer any conclusions as to what is the most correct or best path. Nevertheless, it gives a historical picture of the tendencies in these recordings, pointing to the alternatives of possible and convincing ways of rendering the 7ª Valsa de Esquina. References 1. ANDRADE, M.de. (1972) Ensaio sobre a música brasileira, 3rd ed. São Paulo, Livraria Martins Ed.\Instituto Nacional do Livro- MEC. 1. ANDRADE, M.de. (1972) Ensaio sobre a música brasileira, 3rd ed. São Paulo, Livraria Martins Ed.\Instituto Nacional do Livro- MEC. 2. BOWEN, J. A. (1996) “Performance practice versus performance analysis: Why should performers study performance?” Performance Practice Review. v.9/1, p.16-35. References of recordings 1. BARRENECHEA, Sérgio; BARRENECHEA, Lúcia; and others. (2010) In: A Música para Flauta de Francisco Mignone. Triple CD. Rio de Janeiro: Independent/UNIRIO/FAPERJ. 2. ESTRELLA, Arnaldo. (1950) Francisco Mignone - Valsa de Esquina nº 7 https://www.youtube.com/watch?v=6FFvAlbJgY4 [accessed on 25/05/2015]. 2. ESTRELLA, Arnaldo. (1950) Francisco Mignone - Valsa de Esquina nº 7 https://www.youtube.com/watch?v=6FFvAlbJgY4 [accessed on 25/05/2015]. 3. JACOB DO BANDOLIM and group. Valsa de Chopin op.64 Nº7 em Dó#-menor. https://www.youtube.com/watch?v=arYFnSr559s [accessed on 25/05/2015]. 4. LIMA, Arthur Moreira. (1982) In: As 12 Valsas de Esquina de Francisco Mignone. LP. Rio de Janeiro: Kuarup Discos. 5. MIGNONE, Francisco. (1958) In: Valsas de Esquina. LP. Rio de Janeiro: Festa Discos. 6. MIGNONE, Maria Josephina. (1997) In: Valsas Imortais. CD. Ceará: Nordeste Digital Line S/A. 3. CAZES, H. (2010) Choro do quintal ao municipal, 4thed. São Paulo: Editora 34. 3. CAZES, H. (2010) Choro do quintal ao municipal, 4thed. São Paulo: Editora 34. 4. GERLING, F. V. (2008) “O tempo rubato na Valsa de Esquina Nº2 de Francisco Mignone”. Claves. João Pessoa: Universidade Federal da Paraíba. Nr.5, p.7-19. 5. PIEDADE, A. T. de C. (2005) “Música Popular, Expressão e Sentido: Comentários sobre as tópicas na análise da música brasileira”. DAPesquisa, UDESC, Florianópolis, v.1/2. 6. PINTO, A.G. (1978) O Choro: reminiscências dos chorões antigos. Rio de Janeiro: Funarte. (1ª 7. TARASTI, E. (1994) A Theory of Musical Semiotics. Indianopolis: Indiana University Press. 8. TINHORÃO, J. R. (1976) Música Popular: os sons que vem da rua. Rio de Janeiro: Ed.Tinhorão. 9._______________. (1998) História Social da Música Popular Brasileira. São Paulo: Editora 34 Ltda. 12 MALAGUTI, Sigridur; BARRENECHEA, Sérgio. (2018) Performing the Imagery of Seresta in Francisco Mignone’s 7ª Valsa de Esquina (Corner Waltz No.7) for Piano. Per Musi. Belo Horizonte: UFMG. p.1-13. 10. ULHÔA, M. T. de. (2006) “A pesquisa e análise da música popular gravada”. VII Congresso da IASPM-AL. Havana, Cuba. p.1-9. http://www.unirio.br/mpb/ulhoatextos [accessed on 06/09/2012]. 11. ZAHAR. Dicionário de Música (1985). Rio de Janeiro, Brazil: Zahar Editores, Editoria de HORTA, L.P. 1. MIGNONE, Francisco. (1940) 7ª Valsa de Esquina. São Paulo: E. S. Mangione, p.1-5. 1. MIGNONE, Francisco. (1940) 7ª Valsa de Esquina. São Paulo: E. S. Mangione, p.1-5. 2. _______________. (2016) 7ª Valsa de Esquina. In: A Música para Flauta e Piano de Francisco Mignone. Ed. by Sérgio Barrenechea. Rio de Janeiro: Ed. FAPERJ, p.32-38. 2. _______________. (2016) 7ª Valsa de Esquina. In: A Música para Flauta e Piano de Francisco Mignone. Ed. by Sérgio Barrenechea. Rio de Janeiro: Ed. FAPERJ, p.32-38. 2. _______________. (2016) 7ª Valsa de Esquina. In: A Música para Flauta e Piano de Francisco Mignone. Ed. by Sérgio Barrenechea. Rio de Janeiro: Ed. FAPERJ, p.32-38. Notes on the authors Sigridur Malaguti obtained a Bachelor Degree in piano performance at the New England Conservatory/Boston, her Master’s Degree at the Federal University of Rio de Janeiro and her PhD at The Federal University of Rio de Janeiro State-UNIRIO/Rio de Janeiro, the title of her thesis being: The seresta-imagery and the interpretation of the 12 Valsas de Esquina (12 Corner Waltzes) for piano by Francisco Mignone. She has performed in concerts in the United States, Canada, Brazil and in Iceland, her homeland, where she has debuted piano works by Brazilian composers. Sérgio Barrenechea is an associate professor at the Villa-Lobos Institute/UNIRIO. With a Bachelor Degree in flute performance from Brasilia University, he obtained his Master’s Degree at the Boston Conservatory and his PhD at the University of Iowa. He has recorded CDs with Duo Barrenechea and the Quinteto Brasília, including a triple CD A Música para Flauta de Francisco Mignone (The Complete Works for Flute by Francisco Mignone) (2010) and the CD and DVD Brasileiríssimo: Encontros (Brazilianity: Rendezvous) (2015). 13
W3127701093.txt
https://iiste.org/Journals/index.php/JBAH/article/download/54030/55837
en
Multi-location Based Evaluation of tef Genotypes for Grain Yield Stability and Agronomic Performance in Western Ethiopian High Lands
null
2,020
cc-by
2,463
Journal of Biology, Agriculture and Healthcare ISSN 2224-3208 (Paper) ISSN 2225-093X (Online) Vol.10, No.17, 2020 www.iiste.org Multi-location Based Evaluation of tef Genotypes for Grain Yield Stability and Agronomic Performance in Western Ethiopian High Lands Girma Chemeda Bako Agricultural Research Center, P.O. Box 3, Bako, Ethiopia Abstract Tef [Eragrostis tef (Zucc.) Trotter] is extensively cultivated and most important cereal crop in Ethiopia in terms of production, consumption and cash crop value and grown on about 3 million hectares annually. Because of its gluten-free proteins and slow release carbohydrate constituents, tef is recently being advocated and promoted as health crop at the global level. However, the productivity of tef is very low compared to other cereals mainly due to lack of high yielding and lodging tolerant cultivars. For this purpose, several genotypes were evaluated under different breeding stages in multi-locations so as to screen and reach at stable, high yielding and stress tolerant varieties. Accordingly, the year 2017/18 twenty five recombinant inbred- lines were tested in preliminary variety trial out of which sixteen genotypes were advanced to regional variety trial and tested in 2018/19 and 2019/20 in multi-locations. Finally the combined analysis of variance across the three locations revealed highly significant (p<0.01) difference among genotypes for grain yield, days to mature, plant height, panicle length, lodging %, effective tiller, and crop stand. Among tested genotypes three, RIL 76B, RIL 46 and RIL 43A found to be stable, high yielder and lodging tolerant across the tasted locations with grain yield advantage of 26.62%, 19.77% and 12.72% over the standard check respectively. Therefore based on their high yield and stable performance, genotypes RIL 76B, RIL 46 and RIL 43A were promoted to Variety Verification Trial (VVT) evaluation and for possible release. Keywords: Eragrostis, Genotypes, stability, tef DOI: 10.7176/JBAH/10-17-06 Publication date:September 30th 2020 1. Introduction Tef [Eragrostis tef (Zucc.) Trotter] is a self pollinated warm season annual grass with the advantage of C4 photosynthetic pathway (Miller, 2010). Tef is among the major Ethiopian cereal crops grown on over 3 million hectares annually (CSA, 2018), and serving as staple food grain for over 70 million people. Tef grain is primarily used for human consumption after baking the grain flour into popular cottage bread called "injera". Tef has an attractive nutritional profile, being high in dietary fiber, iron, calcium and carbohydrate and also has high level of phosphorus copper, aluminum, barium, thiamine and excellent composition of amino acids essential for humans (Hager et al.,2012; Abebe et al.,2007; USDA 2015). The straw (chid) is an important source of feed for animals. Generally, the area devoted to tef cultivation is increased because both the grain and straw fetch high domestic market prices. Tef is also a resilient crop adapted to diverse agro-ecologies with reasonable tolerance to both low (especially terminal drought) and high (water logging) moisture stresses. Tef, therefore, is useful as a low-risk crop to farmers due to its high potential of adaptation to climate change and fluctuating environmental conditions (Balsamo et al., 2005). Nevertheless, until recently, tef was considered as “orphan” crop: one receiving no international attention regarding research on breeding, agronomic practices or other technologies applicable to smallholder farmers. The continued cultivation of tef in Ethiopia is accentuated by the following relative merits: 1) as the predominant crop, tef is grown in a wide array of agro-ecologies, cropping systems, soil types and moisture regimes; 2) with harvests of 4.75 million tons of grain per year from about 3 million ha. Tef constitutes about 23.85% of the total acreage and has about 17.26% contribution in grain production of cereals in Ethiopia followed by maize which accounts for about 21% of the acreage and 31% of the overall cereal grain production (CSA, 2018). 3) The values of the grain and straw contribute about four billion Birr to the national GDP; 4) it has a good export market, 5) tef grain has got relatively good nutritive value especially since it contains relatively high amounts of iron, calcium and copper compared to other cereals. Because of its gluten-free proteins and slow release carbohydrate constituents, tef is recently being advocated and promoted as health crop at the global level (Ketema S 1993: Spaenij-Dekking et al., 2005: kebebew Asefa et.; al 2013; Assefa et.; al. 2017). The most important bottlenecks constraining the productivity and production of tef in Ethiopia are: i) low yield potential of farmers’ varieties under widespread cultivation; ii) susceptibility to lodging particularly under growth and yield promoting conducive growing conditions; iii) biotic stresses such as diseases, weeds and insect pests; iv) abiotic stresses such as drought, soil acidity, and low and high temperatures; v) the culture and labor intensive nature of the tef husbandry; vi) inadequate research investment to the improvement of the crop as it lacks global attention due to 38 Journal of Biology, Agriculture and Healthcare ISSN 2224-3208 (Paper) ISSN 2225-093X (Online) Vol.10, No.17, 2020 www.iiste.org localized importance of the crop coupled with limited national attention; and vii) weak seed and extension system (kebebew Asefa et.; al 2013; Assefa et.; al. 2017). Therefore the objective of this activity was to develop and release high yielding, lodging and diseases tolerant tef varieties for potential growing areas of western parts of the country. Therefore, the objective of the current study was to develop and release high yielding, lodging, pest and acidic soils tolerant tef varieties for Western parts of tef growing areas of Ethiopia . 2. Materials and Methods The experimental materials were 89 recombinant tef inbred lines received from by Debre Zeit Agricultural Research Center. The materials were initially developed through crossing made between mutant tef inbred lines (GA-10-3) and quncho tef variety (DZ-Cr-387) after stringent selections to eight generations. The material were tested in Nursery during 2016/17 at Shambu sub-site and reduced to twenty five genotypes and evaluated in preliminary variety trial for one year during 2017/18. Eighteen genotypes including the checks were evaluated in multi-location so as to see their adaptability, stability, yield, and resistance/tolerance to major tef diseases in the main cropping season during 2018/2019 and 2019/2020 in regional variety trial. The experiment was conducted at Shambu, Gedo and Arjo sub site using Randomized Complete Block design with three replications on a plot size (experimental unit) of 2m x2m (4m2) each with 0.2m of row spacing. The distance between block was 1.5m and between plots was 1.0m. Fertilizer rate of 100/50 kg DAP/UREA at planting and 10 kg/ha of seed rate will used. Other agronomic practices were applied uniformly as required. Data on days to emergence, days to heading, days to maturity, panicle length, plant height, panicle length, shoot biomass, lodging %, effective tiller, Stand %, grain yield per plot and disease score (1-9 scale) was collected and subjected to statistical analysis using SAS statistical software. 3. Results and Discussion The combined analysis of variance across the three locations revealed highly significant (p<0.01) difference among genotypes for plant height, panicle length, shoot biomass, lodging % and grain yield qt/ha (Table 2). Genotype RIL 76B, RIL 46 and RIL 43A gave the highest grain yield (2278.97Kg/ha) followed by genotype RIL 46 (2155.71 Kg/ha) and RIL 43A (2028.68Kg/ha). The standard check variety Dursi gave 1799.81.24 Kg/ha. The three candidate genotypes had yield advantage of 26.62%, 19.77%, and 12.72% over the standard check respectively (Table 1). In agreement with this finding; previous studies of Genotype x environment on 22 tef genotypes at four locations in Southern regions of Ethiopia have indicated significant variations in grain yield for the tested genotypes (Ashamo M, Belay G 2012). Similar study on phenotypic diversity in tef germplasm in a pot experiment using 124 single panicle sample collection showed substantial variability for traits such as plant height, panicle length, maturity, seed color, seed yield, lodging and panicle type (Malak-Hail et al.; 1965). The combined analysis of variance for biomass depicted non significant (P<0.05) difference among the tested genotypes. The analysis of variance for lodging percent revealed that low percent for genotype RIL 76B (2.51%) followed by RIL 43A (2.70%) and RIL 46 (2.91%) respectively. The stability study indicated that RIL 76B, RIL46 and RIL found to be stable and high yielders across the tasted locations with grain yield advantage of 26.62%, 19.77% and 12.72% respectively over the check (Table 1). The GGE bi-plot analysis revealed that three candidate genotypes showed stable adaptability across the tested locations (Fig 1).They were also high yielders than the best check and fall relatively close to the concentric circle near to average environment axis, suggesting their potential for wider adaptability with better grain yield performance. Table 1. Mean grain yield across years and Locations RIL NO.76B RIL NO.46 RIL NO.43A RIL NO.66 Dursi (check) RIL NO.65 (RIL NO.80) RIL NO.44 RIL NO.53 RIL NO.74 RIL NO.72 RIL NO.52 Local Check RIL NO.61 RIL NO.49 RIL NO.85 RIL 91A Check RIL NO.7 2018 2422.667 2203.167 2112.5 1955.833 1865.833 1540.833 1813.167 1726.667 1637.777 1462.5 1525.833 1698.333 1607.5 1576.667 1575.833 1585 1693.333 1525.833 2019 2365.42 2234 2105.67 1976.42 1864.75 1568.67 1316.8 1490.33 1389.67 1520.83 1321.92 1141.58 1250.5 1367 1231.33 1355.33 1224 1154.42 2018 2305.83 2160 2045.83 1977.5 1812.17 1874.17 1985.17 1575.83 1784.17 1693.33 1724.17 2079.17 1759.5 1775 1864.17 1726.67 1700 1908.33 2019 2287.83 2232.75 2046.25 2068.08 1761.58 1529.42 1373.08 1423.25 1336.25 1418 1379.83 1115.5 1322.83 1352.75 1292.17 1331.5 1255.92 1179.17 39 2018 2111.67 2051.67 1884.17 1849.17 1746 1675.83 1697.5 1718.33 1628.33 1605.83 1685 1802.5 1720 1630 1663.33 1583.33 1520 1388.33 2019 2180.42 2052.67 1977.67 1958.75 1748.5 1623.67 1328.08 1520.42 1416.92 1428.17 1387.08 1111.17 1256.58 1202.5 1263.75 1275.83 1300.75 1122.08 GY Kg/ha 2278.97 2155.71 2028.68 1964.29 1799.81 1635.43 1585.62 1575.80 1532.19 1521.44 1503.97 1491.38 1486.15 1483.99 1481.76 1476.28 1449.00 1379.69 advantage 26.62 19.77 12.72 9.14 Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Journal of Biology, Agriculture and Healthcare ISSN 2224-3208 (Paper) ISSN 2225-093X (Online) Vol.10, No.17, 2020 Mean LSD CV F-test 2018 1751.63 143.54 4.94 *** 2019 1548.81 359.18 13.98 *** www.iiste.org 2018 1875.06 162.73 5.23 *** 2019 1539.23 360.89 14.13 *** 2018 1720.06 237.88 8.33 *** 2019 1508.61 377.36 15.07 *** GY Kg/ha advantage Rank Note: GY=grain yield, RIL= recombinant inbred line, ***= highly significant, LSD= least significant difference, CV= coefficient of variation Table 2. Mean Agronomic Traits across years and Locations Genotype RIL NO 76B RIL NO.46 RIL NO.43A RIL NO.66 Dursi (check) RIL NO.65 RIL NO.80 RIL NO.44 RIL NO.53 RIL NO.74 RIL NO.72 RIL NO.52 Local check RIL NO.61 RIL NO.49 RIL NO.85 RIL 91A Check RIL NO.73 Grand Mean LSD CV F.test DH 71.11 71.11 71 72.5 72.11 70.17 70.17 73.28 71.06 68.44 71.28 71.11 71 68.11 71.22 72.5 69.5 73.44 71.06 3.19 5.44 * DM 134.22 136.06 135.17 136.72 135 136.56 135.94 134.39 136.67 137.28 136.61 135.17 134.5 132.11 137.5 134 133.22 136.61 135.43 1.41 1.53 *** PH 94.28 94.81 93.24 99.32 102.23 99.13 97.87 97.98 96.57 94.9 98.13 99.54 97.48 87.64 99.44 95.57 90.78 94.06 96.28 3.96 5.31 *** ET 4.22 3.97 4.67 3.9 4.49 4.13 3.96 4.35 3.86 4.21 3.66 3.97 4.12 3.89 3.62 4.03 4.16 3.69 4.05 0.41 13.18 *** PL 36.31 35.36 34.64 37.98 39.31 37.44 35.68 36.72 35.98 35.63 37.49 38.11 37.2 30.79 38.58 36.79 33.67 35.17 36.27 1.67 6.95 *** LD 2.51 2.91 2.7 3.24 2.31 2.95 3.03 2.83 3.17 3.67 3.61 3.27 3.52 2.94 3.24 3 2.58 3.44 3.05 0.61 14.3 *** ST 2.22 2.67 3.78 2.67 1.67 2.22 3 2.78 2 2.89 2.67 2.44 2.78 2.67 2.56 2.89 3 3 2.66 0.39 22.03 *** LR 1.93 1.93 1.87 3.03 1.69 2.67 2.53 2 3.37 2.29 2.85 2.43 2.5 1.98 2.29 2.23 2.3 3.16 2.39 0.64 22.41 *** SBM 12.74 7.86 7.76 7.24 7.64 6.69 5.79 7.54 6.71 6.29 6.82 6.38 6.82 6.07 7.25 6.36 6.39 6.36 7.15 3.45 69.74 ns Note: *= significant, ***= highly significant, ns= none significant, RIL= recombinant inbred line, DH= days to heading, DM= days to maturity, plant height, ET= effective tiller, PL= panicle length, LD= lodging %, SBM= shoot biomass, ST= Stand %, LR =leaf rust, LSD=least significant difference, CV= coefficient of variation Figure1. GGE bi-plot: mean vs. stability 40 Journal of Biology, Agriculture and Healthcare ISSN 2224-3208 (Paper) ISSN 2225-093X (Online) Vol.10, No.17, 2020 www.iiste.org 4. Conclusion and Recommendation Combined analysis of variance for the genotypes portrayed highly significant differences for days to maturity, effective tillers, plant height, panicle length, lodging % , crop stand, leaf rust and grain yield kg/ha. Genotype RIL 76B, RIL 46 and RIL 43A were found stable, high yielders and lodging tolerant across the tasted locations with grain yield advantage of 26.62%, 19.77% and 12.72% over the standard check respectively. As a result of these all merits, these three genotypes were identified as candidate varieties to be verified at three locations the coming cropping season. 5. Acknowledgment The author acknowledges Oromia Agricultural Research Institute and Bako Agricultural Research Center for fulfilling all the necessary inputs to undertake this activity. I am also grateful to all research staffs and workers of Bako Agricultural research Center. 6. References Abebe Y, Bogale A, Hamgidge, KM, Stoecker BJ, Bailey K, Gibson RS, (2007). Phytate, zinc, iron, and calcium content of selected raw and prepared foods consumed in rural Sudama, Southern Ethiopia and implication of bioavailability. J food Compo Anal.20:161-168. Ashamo M, Belay G (2012). Genotype x Environment Interaction Analysis of Tef Grown in Southern Ethiopia Using Additive Main Effects and Multiplicative Interaction Model. Journal of Biology Agriculture and Healthcare 2: 66-72. Assefa K, Chanyalew S, Tadele Z (2017). Tef, Eragrostis tef (Zucc.) Trotter. In: Patil JV (ed) Millets and sorghum, biology and genetic improvement. Wiley, Hoboken, pp 226–266 Balsamo R A, Willigen C V,Boyko W, Farrent L (2005). Retention of mobile water during dehydration in the desiccation-tolerant grass Eragrostis nindeensis' . Physiol Planetarium.134:336-342. Central Statistical Agency(2015). The federal Democratic Republic of Ethiopia. Central Statistical Agency Agricultural Sample Survey 2015: Report on Area and Production of Major Crops (Private peasant Holdings, Maher Season), Volume III. Addis Ababa,Ethiopia. Hanger AS, Wolter A, JacobF, Zannini E, Arendt EK (2012). National properties and ultera-structure of commercial gluten free flours from different botanical sources compared to wheat flours. J Cereal Sci.56:239247. Kebebew Assefa, Solomon Chanyalew; and Gizaw Metaferia (2013). Conventional and Molecular Tef Breeding, Proceedings of the Second International Workshop,November 7-9, 2011, Debre Zeit, Ethiopia Ketema S (1993). Tef, Eragrostis tef (Zucc.) Trotter: breeding, Genetic Resources, Agronomy, Utilization and Role in Ethiopian Agricu Melak-Hail Mengesha,Picket R. C., Davis R. L (1965). Genetic variability and interrelationship of characters in teff, Eragrsotis tef (Zucc.) Trotter, Crop Sci. 5: 155-157. Miller, D (2010) Teff guide 3rd edition, viewed on 24 September 2012, http://www.calwestseeds.com.product/teff Spaenij-Dekking L, Kooy-Winkelaar Y and Koning F (2005).The Ethiopian cereal tef in celiac disease. N. Engl. J. Med. 353: 16 USDA (2015). National Nutrient Database for Standard Reference Release 27, United States Department of Agriculture, USA 41
https://openalex.org/W1777165774
https://pure.manchester.ac.uk/ws/files/29719091/POST-PEER-REVIEW-PUBLISHERS.PDF
English
null
An examination of the SEP candidate analogical inference rule within pure inductive logic
Journal of applied logic/Journal of applied logic (Online)
2,016
cc-by
14,330
An examination of the SEP candidate analogical inference rule within pure inductive logic E. Howarth 1, J.B. Paris ∗, A. Vencovská 2 E. Howarth 1, J.B. Paris ∗, A. Vencovská 2 School of Mathematics, The University of Manchester, Manchester M13 9PL, United Kingdom a r t i c l e i n f o a r t i c l e i n f o Article history: Available online 16 June 2015 Keywords: Analogy Inductive logic Logical probability Rationality Uncertain reasoning Within the framework of (Unary) Pure Inductive Logic we investigate four possible formulations of a probabilistic principle of analogy based on a template considered by Paul Bartha in the Stanford Encyclopedia of Philosophy [1] and give some characterizations of the probability functions which satisfy them. In addition we investigate an alternative interpretation of analogical support, also considered by Bartha, based not on the enhancement of probability but on the creation of possibility. © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). * Corresponding author. E-mail addresses: lizhowarth@outlook.com (E. Howarth), jeff.paris@manchester.ac.uk (J.B. Paris), alena.vencovska@manchester.ac.uk (A. Vencovská). 1 Supported by a UK Engineering and Physical Sciences Research Council Studentship. 2 Supported by a UK Engineering and Physical Sciences Research Council Research Grant EP/L023989/1. http://dx.doi.org/10.1016/j.jal.2015.06.002 1570-8683/© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). http://dx.doi.org/10.1016/j.jal.2015.06.002 1570-8683/© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Journal of Applied Logic 14 (2016) 22–45 Journal of Applied Logic 14 (2016) 22–45 * Corresponding author. In turn he examines a corresponding candidate analogical inference rule, CAIR for short: Suppose S and T are the source and target domains. Suppose P1 . . . , Pn (with n ≥1) represents the positive analogy, A1, . . . , Ar and ¬B1, . . . , ¬Bs represent the (possibly vacuous) negative analogy, and Q represents the hypothetical analogy. In the absence of reasons for thinking otherwise, infer that Q∗holds in the target domain with degree of support p > 0, where p is an increasing function of n and a decreasing function of r and s. The primary intention of this paper is to formulate, as principles, mathematically more precise versions of CAIR within the framework of (Unary) Pure Inductive Logic, PIL for short, where ‘degree of support’ is identified with (subjective) probability, and to determine which probability functions satisfy these versions in the presence of certain other, widely accepted, symmetry requirements. We should point out that this differs somewhat from the ‘Applied Inductive Logic’ framework in which Bartha considers and dismisses CAIR, even as a non-starter. Following that we shall suggest and investigate within this formal framework an alternative interpretation of analogical support based on the creation of possibility, also considered by Bartha as what he terms ‘the modal conception’, see [1, Section 2.3]. This (Unary) Pure Inductive Logic framework is explained in, for example, [19,20]. In short we work in a first order predicate language Lq with finitely many predicate, i.e. unary relation, symbols R1, R2, . . . , Rq, countably many constants a1, a2, a3, . . . , which are intended to name all the elements of the universe, and no function symbols nor equality. Let SLq and QFSLq denote, respectively, the sentences and quantifier free sentences of this language. A probability function on Lq is a function w : SLq →[0, 1] such that for all θ, φ A probability function on Lq is a function w : SLq →[0, 1] such that for all θ, φ, ∃x ψ(x) ∈SLq: (P1) If |= θ then w(θ) = 1 (P2) If |= ¬(θ ∧φ) then w(θ ∨φ) = w(θ) + w(φ) (P3) w(∃x ψ(x)) = limm→∞w(m i=1 ψ(ai)), this last condition reflecting the intention that the constants ai exhaust the universe. this last condition reflecting the intention that the constants ai exhaust the universe. In turn he examines a corresponding candidate analogical inference rule, CAIR for short: The primary goal of PIL, as we would present it, is to investigate which such probability functions are logical or rational in the sense of corresponding to the subjective probabilities assigned by a rational agent in the absence of any further knowledge or intended interpretation of the constant and predicate symbols. Whilst we have no precise definition of what we mean by ‘logical’ or ‘rational’ here, indeed such a clarification is essentially equivalent to the above goal, we do at least seem to have some intuitions about what constitutes being rational, or perhaps more usually what constitutes being irrational. For example in the circumstances of such zero knowledge it would seem to be irrational to treat any one constant differently from any other. Precisely then a rational probability function w should satisfy: 1. Introduction Paraphrasing his article in the Stanford Encyclopedia of Philosophy, SEP [1], Paul Bartha considers the following characterization of an individual analogical argument: with an analogical argument being: It is Source (S) Target (T) P P ∗ [positive analogy] A ¬A∗ [negative analogy] ¬B B∗ Q Q∗ (plausibly) Source (S) Target (T) P P ∗ [positive analogy] A ¬A∗ [negative analogy] ¬B B∗ Q Q∗ (plausibly) plausible that Q∗holds in the target domain because of certain known (or accepted) similarities with the source domain, despite certain known (or accepted) differences. ported by a UK Engineering and Physical Sciences Research Council Research Grant EP/L023989/1. http://dx.doi.org/10.1016/j.jal.2015.06.002 1570-8683/© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 23 In turn he examines a corresponding candidate analogical inference rule, CAIR for short: In turn he examines a corresponding candidate analogical inference rule, CAIR for short: 3 ULi alone, see [20], only requires each of the probability functions wLr to satisfy Ex + Px. The Principle of Predicate Exchangeability, Px If Ri, Rj are predicate symbols of Lq then for θ ∈SL, w(θ) = w(θ′) where θ′ is the result of transposing Ri, Rj throughout θ. The Principle of Constant Exchangeability, Ex A probability function w on SLq satisfies Constant Exchangeability if, for any permutation σ of 1, 2, . . . and θ(a1, . . . , an) ∈SLq, (1) w(θ(aσ(1), . . . , aσ(n))) = w(θ(a1, . . . , an)). (1) This principle is so widely assumed in this context that we shall henceforth take it, without further mention, that all probability functions we discuss satisfy it. This principle is so widely assumed in this context that we shall henceforth take it, without further mention, that all probability functions we discuss satisfy it. Similarly there would seem to be no rational reason to give two predicates different properties, nor even between a predicate and its negation. This leads to imposing two further requirements on a rational probability function to satisfy: E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 24 The Strong Negation Principle, SN g g p , For θ ∈SLq, w(θ) = w(θ′) where θ′ is the result of replacing each occurrence of the predicate symbol R in θ by ¬R. In what follows we shall restrict our attention to probability functions w satisfying these three principles Ex, Px, SN. There is a further principle which we will need subsequently and whose rationality may be argued for as follows. Suppose that on the basis of some considerations we have made the probability function wLq our rational choice of probability function on Lq and the probability function wLr our rational choice of probability function on Lr where r ≥q. Then since SLq ⊆SLr it would seem perverse if wLr did not agree with wLq on SLq, since it would mean that what we considered a rationally justified value for the probability of θ ∈SLq depended on the presence or absence of relation symbols in the language which were not even mentioned in θ. Given our earlier argument for the rationality of Px + SN this leads to the following ‘meta-rationality’ principle which it is desirable for a probability function wLq on Lq to satisfy, though unlike Ex, Px and SN we will not actually assume it as the default: Unary Language Invariance with Strong Negation,3 ULi + SN A probability function w on Lq satisfies Unary Language Invariance with SN if there is a family of probability functions wLr, one on each language Lr where r ∈N+ = {1, 2, 3, . . .}, satisfying Ex + Px + SN and such that w = wLq and whenever r ≤s then wLs agrees with wLr on SLr. Rϵ1 1 ∧Rϵ2 2 ∧. . . ∧Rϵq q Unary Language Invariance with Strong Negation,3 ULi + SN Whilst the rationality of observing symmetries and language invariance as expressed by the above prin- ciples seems to us hard to question, the rationality of arguments by analogy appears much less forceful. Nevertheless in the real world we often are somewhat influenced by analogies, for clear accounts of such within mathematics see [22,23], and there have been several attempts, starting with Rudolf Carnap, to capture facets of analogy as a rational or logical principle within the framework of Inductive Logic, see for example [3], Carnap and Stegmüller [4] and later Festa [5], Hesse [9,10], Maher [15,16], di Maio [17], Romeijn [24], Skyrms [25]. In each of the next four sections we will add to this list of ‘Principles of Analogy’ by proposing inter- pretations, or variants, of CAIR within the framework of PIL and, in Theorems 1, 2, 3, 4, investigating the probability functions that satisfy them (in the presence of our standing assumptions Ex, Px, SN). Sub- sequently we will broaden the remit by proposing a principle of analogy (Dolly’s Principle) based on the idea of analogy as a source of possibility (the modal conception as Bartha terms it) rather than increase of probability. Since mathematical results in these sections contain on occasions technicalities that some readers may wish to simply accept we shall now spend a little time introducing the terms that appear in their statements in order that they become directly accessible. A general overview of these results will then be given in the final section. An atom of Lq is a formula of the form Rϵ1 1 ∧Rϵ2 2 ∧. . . ∧Rϵq q E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 25 E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 25 where ϵ1, ϵ2, . . . , ϵq ∈{0, 1} and R1 i = Ri, R0 i = ¬Ri. So there are 2q atoms for Lq, which we denote α1(x), α2(x), . . . , α2q(x), corresponding to the 2q different choices for the ⃗ϵ. Notice that because we only have unary relation symbols in the language, knowing which atom a constant satisfies tells us all there is to know about that constant. where ϵ1, ϵ2, . . . , ϵq ∈{0, 1} and R1 i = Ri, R0 i = ¬Ri. So there are 2q atoms for Lq, which we denote α1(x), α2(x), . . 4 We may on occasions use b1, b2, b3 etc. for constants from {a1, a2, a3, . . .}, rather than ai1, ai2, ai3, etc., in order to avoid multiple subscripts. Unary Language Invariance with Strong Negation,3 ULi + SN . , α2q(x), corresponding to the 2q different choices for the ⃗ϵ. Notice that because we only have unary relation symbols in the language, knowing which atom a constant satisfies tells us all there is to know about that constant. Similarly for (distinct) constants4 b1, b2, . . . , bn the state description that holds for them, that is the sentence n  i=1 αhi(bi), n  i=1 αhi(bi), n  i=1 αhi(bi), tells us all there is to know about these constants. By a theorem of Gaifman, see [6] or [20, Theorem 7.1], a probability function is uniquely determined by its values on state descriptions. tells us all there is to know about these constants. By a theorem of Gaifman, see [6] or [20, Theorem 7.1], a probability function is uniquely determined by its values on state descriptions. Let D2q be the set of vectors Let D2q be the set of vectors Let D2q be the set of vectors Let D2q be the set of vectors  ⟨x1, x2, . . . , x2q⟩∈R2q | xi ≥0,  i xi = 1  . For ⃗c ∈D2q the probability function w⃗c on Lq is defined by For ⃗c ∈D2q the probability function w⃗c on Lq is defined by w⃗c  n  i=1 αhi(bi)  = n i=1 chi. In other words w⃗c treats the αhi(bi) as stochastically independent with individual probabilities chi, i = 1, . . . , n. This probability function satisfies Ex but not Px nor SN except under special circumstances. For future reference we recall (see [20, Chapter 8]) that the w⃗c are characterized by satisfying the In other words w⃗c treats the αhi(bi) as stochastically independent with individual probabilities chi, i = 1, . . . , n. This probability function satisfies Ex but not Px nor SN except under special circumstances. For future reference we recall (see [20, Chapter 8]) that the w⃗c are characterized by satisfying the The (Extended) Principle of Instantial Relevance For θ(a1, a2, . . . , an), φ(a1) ∈SL, nciple of Instantial Relevance w(φ(an+2) | φ(an+1) ∧θ(a1, a2, . . . , an)) ≥w(φ(an+2) | θ(a1, a2, . . . , an)). (3) w(φ(an+2) | φ(an+1) ∧θ(a1, a2, . . . , an)) ≥w(φ(an+2) | θ(a1, a2, . . . , an)). (3) A second important family of probability functions on Lq are the cLq λ , 0 ≤λ ≤∞, of Carnap’s Continuum of Inductive Methods which, for λ > 0, are specified by cLq λ (αj(bn+1) | n  i=1 αhi(ai)) = mj + λ2−q n + λ cLq λ (αj(bn+1) | n  i=1 αhi(ai)) = mj + λ2−q n + λ where (again) mj = |{i | hi = j}| and for λ = 0 by where (again) mj = |{i | hi = j}| and for λ = 0 by cLq 0  n  i=1 αhi(bi)  =  2−q if h1 = h2 = . . . = hn, 0 otherwise. These cLq λ satisfy Ex + Px + SN and even ULi with SN, the corresponding language invariant family being obtained by fixing the λ and letting the q range over N+. These cLq λ satisfy Ex + Px + SN and even ULi with SN, the corresponding language invariant family being obtained by fixing the λ and letting the q range over N+. Given that convex sums of probability functions are again probability functions and that probability functions are determined by their values on state descriptions it is easy to check that cLq ∞= w⟨2−q,2−q,...,2−q⟩ cLq ∞= w⟨2−q,2−q,...,2−q⟩ cLq 0 = 2−q(w⟨1,0,0,...,0⟩+ w⟨0,1,0,...,0⟩+ . . . + w⟨0,...,0,0,1⟩). cLq 0 = 2−q(w⟨1,0,0,...,0⟩+ w⟨0,1,0,...,0⟩+ . . . + w⟨0,...,0,0,1⟩). cLq 0 = 2−q(w⟨1,0,0,...,0⟩+ w⟨0,1,0,...,0⟩+ . . . + w⟨0,...,0,0,1⟩). To simplify the notation in what follows we shall omit the superscript Lq in cLq λ when q is clear from the context. To simplify the notation in what follows we shall omit the superscript Lq in cLq λ when q is clear from the context. Notice that any permutation of predicates, or transposition of Rj, ¬Rj, generates a permutation of the atoms αi. We shall say that a permutation σ of atoms is licensed by Px + SN if it can be formed as a composition of such permutations. The Constant Irrelevance Principle If θ, φ ∈QFSL have no constant symbols in common then w(θ ∧φ) = w(θ) · w(φ). w(θ ∧φ) = w(θ) · w(φ). We remark that the principle implies that w(θ ∧φ) = w(θ) · w(φ) even when θ, φ ∈SL (not necessarily quantifier free), see [20, Chapter 8]. We remark that the principle implies that w(θ ∧φ) = w(θ) · w(φ) even when θ, φ ∈SL (not necessarily quantifier free), see [20, Chapter 8]. The functions w⃗c are fundamental since any probability function satisfying Ex can be expressed from them as an integral over D2q: De Finetti’s Representation Theorem. Let w be a probability function on SLq satisfying Ex. Then there is a normalized and countably additive measure μ on the Borel subsets of D2q such that w  n  i=1 αhi(bi)  = D2q 2q j=1 xmj j dμ(⃗x) = D2q w⃗x  n  i=1 αhi(bi)  dμ(⃗x), (2) (2) where for j = 1, 2, . . . , 2q, mj = |{i | hi = j}|, the number of times that j occurs amongst h1, h2, . . . , hn. where for j = 1, 2, . . . , 2q, mj = |{i | hi = j}|, the number of times that j occurs amongst h1, h2, . . . , hn. 4 We may on occasions use b1, b2, b3 etc. for constants from {a1, a2, a3, . . .}, rather than ai1, ai2, ai3, etc., in order to avoid multiple subscripts. 26 E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 De Finetti’s Theorem finds numerous important, and slick, applications in PIL; for example Humburg’s proof (see [14], or [20, Chapter 11]) of a result of Gaifman [7], that we shall need later, that Ex implies The (Extended) Principle of Instantial Relevance For θ(a1, a2, . . . , an), φ(a1) ∈SL, Notice that if w satisfies Px + SN then for such a σ, w  n  i=1 αhi(aki)  = w  n  i=1 σ(αhi)(aki)  . (4) (4) Furthermore, since by Ex the left (and right) hand side is the same for any choice of distinct constants we shall, to simplify the notation, sometimes omit the instantiating constants and denote it simply as Furthermore, since by Ex the left (and right) hand side is the same for any choice of distinct constants we shall, to simplify the notation, sometimes omit the instantiating constants and denote it simply as w  n  i=1 αhi  w  n  i=1 αhi  or even w(αm1 1 αm2 2 . . . αm2q 2q ) w  n  i=1 αhi  w  n  i=1 αhi  or even w  n  i=1 αhi  or even or even or even or even w(αm1 1 αm2 2 . . . αm2q 2q ) w(αm1 1 αm2 2 . . . αm2q 2q ) w(αm1 1 αm2 2 . . . αm2q 2q ) where mj is the number of times that j appears in h1, h2, . . . , hn. ere mj is the number of times that j appears in h1, h2, . . . , hn. For future reference note that Atom Exchangeability is the assertion that (4) holds for any permutation σ of the set of atoms, not just those licensed by Px + SN. E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 27 6 More generally we shall identify (a/b) ≥(c/d) with ad ≥bc. 7 8 Recall the standing assumption that all probability functions considered satisfy Ex. 2. The general analogy principle The first question we might feel obliged to address vis-a-vis CAIR is what exactly the forms of the Q, P, A, B are and what exactly is being treated analogously in the relationship between Q and Q∗etc. – what we shall refer to as the carrier of the analogy. The four versions we shall consider are really centered around possible answers to these questions within the framework of Unary5 PIL. In our first attempt at a formulation the Q, P are just quantifier free sentences and it is the constants which are the carriers: For ⃗a = ⟨a3, a4, . . . , ak⟩and ψ(a1, ⃗a), φ(a1, ⃗a) ∈QFSL, (5) w(φ(a2,⃗a) | ψ(a1,⃗a) ∧ψ(a2,⃗a) ∧φ(a1,⃗a)) ≥w(φ(a2,⃗a) | φ(a1,⃗a)). (5) In this principle then ψ(a1, ⃗a) ∧ψ(a2, ⃗a) provides ‘evidence’ that a1, a2 are similar and hence should enhance (or at least not decrease) the probability that a2 should again be similar to a1 in satisfying φ(x, ⃗a) given that a1 does. In this principle then ψ(a1, ⃗a) ∧ψ(a2, ⃗a) provides ‘evidence’ that a1, a2 are similar and hence should enhance (or at least not decrease) the probability that a2 should again be similar to a1 in satisfying φ(x, ⃗a) given that a1 does. A few comments are in order here. Firstly we shall identify (5) with A few comments are in order here. Firstly we shall identify (5) with w(φ(a2,⃗a) ∧ψ(a1,⃗a) ∧ψ(a2,⃗a) ∧φ(a1,⃗a)) · w(φ(a1,⃗a)) ≥w(ψ(a1,⃗a) ∧ψ(a2,⃗a) ∧φ(a1,⃗a)) · w(φ(a2,⃗a) ∧φ(a1,⃗a)), a convenience which satisfactorily allows us to dispense with the problem of conditioning on sentences with probability zero.6 Secondly, in this formulation we have taken as vacuous the negative analogies A1, . . . , Ar and ¬B1, . . . , ¬Bs. In particular then the monotonicity element of Bartha’s representation has been reduced to a single inequality.7 Thirdly, notice that by Ex the choice of constants a1, a2 . . . , ak is not relevant since it implies the same principle for any distinct choice of constants. Finally, within this formulation we are restricting φ(a1, ⃗a), ψ(a1, ⃗a) to be quantifier free, again for reasons which will shortly become clear. GAP fails to satisfactorily capture our (presumably viable) intuitions about analogy. As we now show GAP fails to satisfactorily capture our (presumably viable) intuitio As we now show GAP fails to satisfactorily capture our (presumably viable) intuitions about analogy. Theorem 1. bsequent results will somewhat vindicate this decisio 5 Several of our results apply also to Polyadic Inductive Logic, see [19,20] for further details, but for simplicity we shall limit ourselves here to the purely unary. 6 More generally we shall identify (a/b) ≥(c/d) with ad ≥bc 5 Several of our results apply also to Polyadic Inductive Logic, see [19,20] for further details, but ourselves here to the purely unary. 6 2. The general analogy principle Then the de Finetti prior of w must have a support point ⟨c, 1 −c⟩with 0 < c < 1/2. (In other words every open set containing this point has non-zero measure.) ) Let φ(a1) = R1(a1). Then by the Extended Principle of Instantial Relevance, (3), and SN, w(φ(a2) | φ(a1)) ≥w(R1(a1)) = 1/2. (6) (6) w(φ(a2) | φ(a1)) ≥w(R1(a1)) = 1/2. Let ψ(a3, a4, . . . , ak) = R[mc] 1 (¬R1)[m(1−c)] where as usual [mc] is the integer part of mc and k = [mc] + [m(1 −c)] + 2. Then where as usual [mc] is the integer part of mc and k = [mc] + [m(1 −c)] + 2. Then where as usual [mc] is the integer part of mc and k = [mc] + [m(1 −c)] + 2. Then w(φ(a2) | φ(a1) ∧ψ(⃗a)) = w(R[mc+2] 1 (¬R1)[m(1−c)]) w(R[mc+1] 1 (¬R1)[m(1−c)]) ≈c for large m (see for example [20, Chapter 12]). Comparing with (6) we have the required counter- example. (B): Here we shall show the result even without the ⃗a being present. We first need to introduce another probability function, ϖ, on Lq. For αi an atom of Lq let αc i be that atom of Lq which disagrees with αi on every Rj(x), in other words, for j = 1, 2, . . . , q, αi(x) |= Rj(x) ⇐⇒αc i(x) |= ¬Rj(x). Now let ⃗e1, ⃗e2, . . . , ⃗e2q−1 run through all vectors in D2q which have zeros at all coordinates except for two, say the ith and jth, with αc i = αj, and in those places the entry is 1/2. Set ϖ = 21−q 2q−1  i=1 w⃗ei. ϖ = 21−q 2q−1  i=1 w⃗ei. We now show that in the case of a unary language L with q ≥2 predicates and a probability function w on L satisfying Ex, Px and SN and not of the form λϖ + (1 −λ)c0 for some 0 < λ ≤1 there are φ(a1), ψ(a1) for which (5) fails.9 We now show that in the case of a unary language L with q ≥2 predicates and a probability function w on L satisfying Ex, Px and SN and not of the form λϖ + (1 −λ)c0 for some 0 < λ ≤1 there are φ(a1), ψ(a1) for which (5) fails.9 ( ) To this end let G ⊂{1, 2, . . . 2. The general analogy principle Let w be a probability function on the unary language Lq satisfying Px + SN.8 Then (A) If q = 1 then w satisfies GAP just if w = c0. A) If q = 1 then w satisfies GAP just if w = c0. (A) If q = 1 then w satisfies GAP just if w = c0. (B) If q ≥2 then w satisfies GAP just if w = c0, even dropping the additional cons (B) If q ≥2 then w satisfies GAP just if w = c0, even dropping the additional constants ⃗a. Proof. (A): That c0 (on L1) satisfies GAP will be shown in part (B) below. If w = νc∞+ (1 −ν)c0 with 0 < ν ≤1 then one can check that for φ(a1, ⃗a), ψ(a1, ⃗a) being respectively R1(a1) ∧(R1(a3) ∨R1(a4)) ∨ ¬R1(a1) ∧(R1(a3) ∨¬R1(a4)) ∧R1(a5) ∧¬R1(a6), R1(a1) ∧(¬R1(a3) ∨R1(a4)) ∨ ¬R1(a1) ∧(¬R1(a3) ∨¬R1(a4)) ∧R1(a5) ∧¬R1(a6), Proof. (A): That c0 (on L1) satisfies GAP will be shown in part (B) below. If w = νc∞+ (1 −ν)c0 with 0 < ν ≤1 then one can check that for φ(a1, ⃗a), ψ(a1, ⃗a) being resp Proof. (A): That c0 (on L1) satisfies GAP will be shown in part (B) below. If w = νc∞+ (1 −ν)c0 with 0 < ν ≤1 then one can check that for φ(a1, ⃗a), ψ(a1, ⃗a) being respectively Proof. (A): That c0 (on L1) satisfies GAP will be shown in part (B) below. If w = νc∞+ (1 −ν)c0 with 0 < ν ≤1 then one can check that for φ(a1, ⃗a), ψ(a1, ⃗a) being respectively If w = νc∞+ (1 −ν)c0 with 0 < ν ≤1 then one can check that for φ(a1, ⃗a), ψ(a1, ⃗a) being respectively R1(a1) ∧(R1(a3) ∨R1(a4)) ∨ ¬R1(a1) ∧(R1(a3) ∨¬R1(a4)) ∧R1(a5) ∧¬R1(a6), R1(a1) ∧(¬R1(a3) ∨R1(a4)) ∨ ¬R1(a1) ∧(¬R1(a3) ∨¬R1(a4)) ∧R1(a5) ∧¬R1(a6), R1(a1) ∧(R1(a3) ∨R1(a4)) ∨ ¬R1(a1) ∧(R1(a3) ∨¬R1(a4)) ∧R1(a5) ∧¬R1(a6), R1(a1) ∧(¬R1(a3) ∨R1(a4)) ∨ ¬R1(a1) ∧(¬R1(a3) ∨¬R1(a4)) ∧R1(a5) ∧¬R1(a6), we have we have we have w(φ(a2,⃗a) | ψ(a1,⃗a) ∧ψ(a2,⃗a) ∧φ(a1,⃗a)) = 2/3 < 5/6 = w(φ(a2,⃗a) | φ(a1,⃗a)), w(φ(a2,⃗a) | ψ(a1,⃗a) ∧ψ(a2,⃗a) ∧φ(a1,⃗a)) = 2/3 < 5/6 = w(φ(a2,⃗a) | φ(a1,⃗a)), hich provides the required counter-example. which provides the required counter-example. E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 28 So now suppose that w is not of the form νc∞+ (1 −ν)c0 for any 0 ≤ν ≤1. 2. The general analogy principle , 2q}, |G| = 2q−1 and let x = w(αiαi) and yij = w(αiαj). Notice that x is independent of i since for any atoms αi, αj there is a permutation σ of atoms licensed by SN such that σ(αi) = αj. Since |G| = 2q−1 and  i∈G  i̸=j∈G yij =  i̸=j i,j∈G yij we can find i ∈G, say i = 1 (so 1 ∈G), such that 2q−1  1̸=j∈G y1j ≤  i̸=j i,j∈G yij. (7)  i∈G  i̸=j∈G yij =  i̸=j i,j∈G yij we can find i ∈G, say i = 1 (so 1 ∈G), such that we can find i ∈G, say i = 1 (so 1 ∈G), such that 2q−1  1̸=j∈G y1j ≤  i̸=j i,j∈G yij. (7) 2q−1  1̸=j∈G y1j ≤  i̸=j i,j∈G yij. (7) 9 Since probability functions satisfying Px + SN on a language L continue to satisfy these principles when restricted to smaller languages it would actually suffice here to prove this part for q = 2. However, overall, that does not seem to be any simpler. E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 29 Let φ(a1) = i∈G αi(a1), ψ(a1) = α1(a1) ∨ i/∈G αi(a1). w(α1(a1)) = 2−q = x +  1̸=j∈G y1j +  j /∈G y1j. (8) w(α1(a1)) = 2−q = x +  1̸=j∈G y1j +  j /∈G y1j. (8) Then with the above abbreviations, Then with the above abbreviations, w(φ(a1)) = 2q−12−q, w(φ(a1) ∧φ(a2)) = 2q−1x +  i,j∈G i̸=j yij, w(ψ(a1) ∧ψ(a2) ∧φ(a1)) = x +  j /∈G y1j, w(ψ(a1) ∧ψ(a2) ∧φ(a1) ∧φ(a2)) = x, w(φ(a1)) = 2q−12−q, w(φ(a1) ∧φ(a2)) = 2q−1x +  i,j∈G i̸=j yij, w(ψ(a1) ∧ψ(a2) ∧φ(a1)) = x +  j /∈G y1j, w(ψ(a1) ∧ψ(a2) ∧φ(a1) ∧φ(a2)) = x, and the inequality (5) becomes x x +  j /∈G y1j ≥ 2q−1x +  i,j∈G i̸=j yij 2q−12−q . 2. The general analogy principle Multiplying out gives 2q−12−qx ≥ ⎛ ⎝x +  j /∈G y1j ⎞ ⎠ ⎛ ⎜ ⎜ ⎝2q−1x +  i,j∈G i̸=j yij ⎞ ⎟ ⎟ ⎠ = 2q−1x2 + x ⎛ ⎜ ⎜ ⎝  i,j∈G i̸=j yij + 2q−1  j /∈G y1j ⎞ ⎟ ⎟ ⎠+  j /∈G y1j ·  i,j∈G i̸=j yij = 2q−1x2 + x ⎛ ⎜ ⎜ ⎝  i,j∈G i̸=j yij + 2q−1(2−q −x −  1̸=j∈G y1j) ⎞ ⎟ ⎟ ⎠ +  j /∈G y1j ·  i,j∈G i̸=j yij by (8). and the inequality (5) becomes Multiplying out gives Canceling out terms now gives 0 ≥x ⎛ ⎜ ⎜ ⎝  i,j∈G i̸=j yij −2q−1  1̸=j∈G y1j ⎞ ⎟ ⎟ ⎠+  j /∈G y1j ·  i,j∈G i̸=j yij. (9) E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 30 By (7) this right hand side is at least 0. We now show that for a suitable initial choice of G it must be strictly positive. By (7) this right hand side is at least 0. We now show that for a suitable initial choice of G it must be strictly positive. Since w is not of the form λϖ + (1 −λ)c0 for some 0 < λ ≤1 there must be i ̸= j such that w(αiαj) > 0 and αj ̸= αc i, say αi, αj differ on r predicates where 1 ≤r < q. Let αk(x) |= R1(x). Then there is a permutation σ licensed by SN such that σ(αi) = αk, σ(αj) differs from αk on r predicates10 and by Px + SN, w(αkσ(αj)) = w(αiαj) > 0. Suppose that σ(αj) |= R1(x). Then because 1 ≤r < q we can find a permutation τ licensed by SN + Px such that αk = τ(αk) and τσ(αj) |= ¬R1(x), and of course w(αkτσ(αj)) > 0. Similarly if σ(αj) |= ¬R1(x) we can find an atom αs differing from αk on r predicates such that αs |= R1(x) and w(αkαs) > 0. In this case then we can take G to be the set of those atoms αi such that αi |= R1(x) and obtain the required contradiction to (9). So GAP does not hold. 10 The permutations licensed by Px + SN are precisely those that preserve Hamming distance, see [11, and the inequality (5) follows immediately. 2 and the inequality (5) follows immediately. 2 It is perhaps worth remarking here that in the case of q = 1 the extra constants a3, a4, . . . , am employed in forming the counter-example to GAP cannot be dispensed with. In fact when q = 1 and the extra constants are absent GAP trivially holds for any w (and even continues to hold when φ, ψ may contain quantifiers provided w not of the form λc0 + (1 −λ)w′, with 0 < λ < 1 and w′ ̸= c0, see [18]). 2. The general analogy principle Turning now to the case where w = λϖ + (1 −λ)c0 for some 0 < λ ≤1 and q ≥2 let αi, αj, αc i, αc j be distinct atoms and take φ(a1) = αi(a1) ∨αj(a1) ∨αc j(a1), ψ(a1) = αi(a1) ∨αc i(a1). Then Then w(φ(a1)) = λϖ(φ(a1)) + (1 −λ)c0(φ(a1)) = 3λ2−q + 3(1 −λ)2−q = 3 · 2−q, = 3 · 2−q, w(φ(a1) ∧φ(a2)) = λϖ(φ(a1) ∧φ(a2)) + (1 −λ)c0(φ(a1) ∧φ(a2)) = 5λ2−q−1 + 3(1 −λ)2−q = (3 −λ/2)2−q, = (3 −λ/2)2−q, w(ψ(a1) ∧ψ(a2) ∧φ(a1)) = λϖ(ψ(a1) ∧ψ(a2) ∧φ(a1)) + (1 −λ)c0(ψ(a1) ∧ψ(a2) ∧φ(a1)) = λ2−q + (1 −λ)2−q = 2−q, w(ψ(a1) ∧ψ(a2) ∧φ(a1) ∧φ(a2)) = λϖ(ψ(a1) ∧ψ(a2) ∧φ(a1) ∧φ(a2)) + (1 −λ)c0(ψ(a1) ∧ψ(a2) ∧φ(a1) ∧φ(a2)) = λ2−q−1 + (1 −λ)2−q = (1 −λ/2)2−q, and the inequality (5) becomes 3(1 −λ/2) ≥3 −λ/2, which fails since λ > 0, and gives the required counter-example. which fails since λ > 0, and gives the required counter-example. To complete case (B) we now show that GAP holds for c0 on Lq for any q. Indeed we shall show that it holds even in the case where φ, ψ are sentences rather than just quantifier free. To this end notice (or see for example [8] where a similar result is derived) that for the unary language Lq, any sentence mentioning constants a1, . . . , an is logically equivalent to a sentence in the form s i=1 ⎛ ⎝ n  j=1 αki,j(aj) ∧ 2q  m=1 (∃x αm(x)) ϵi,m ⎞ ⎠ (10) (10) where the ϵi,m ∈{0, 1} and as usual ψϵ is ψ if ϵ = 1 and ¬ψ if ϵ = 0. 10 The permutations licensed by Px + SN are precisely those that preserve Hamming distance, see [11, Theorem 2]. 10 The permutations licensed by Px + SN are precisely those that preserve Hamming distance, see [11, Theorem 2]. E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 E. Howarth et al. 2. The general analogy principle / Journal of Applied Logic 14 (2016) 22–45 31 31 Noticing that Noticing that c0(αiαj) =  2−q if i = j 0 otherwise c0(αiαj) =  2−q if i = j 0 otherwise we can see that for each of the disjuncts in (10) either c0 αki,1(a1) ↔( n  j=1 αki,j(aj) ∧ 2q  m=1 (∃x αm(x)) ϵi,m) = 1 or c0 ⊥↔( n  j=1 αki,j(aj) ∧ 2q  m=1 (∃x αm(x)) ϵi,m) = 1. From this it follows that there are S, T ⊆{1, 2, . . . , 2q} such that From this it follows that there are S, T ⊆{1, 2, . . . , 2q} such that c0(φ(a1,⃗a) ↔ j∈S αj(a1)) = 1, c0(ψ(a1,⃗a) ↔ j∈T αj(a1)) = 1. c0(φ(a1,⃗a) ↔ j∈S αj(a1)) = 1, c0(ψ(a1,⃗a) ↔ j∈T αj(a1)) = 1. Hence c0(φ(a1,⃗a)) = c0(φ(a1,⃗a) ∧φ(a2,⃗a)) = 2−q|S| c0(ψ(a1,⃗a) ∧ψ(a2,⃗a) ∧φ(a1,⃗a)) = c0(ψ(a1,⃗a) ∧ψ(a2,⃗a) ∧φ(a1,⃗a) ∧φ(a2,⃗a)) = 2−q|S ∩T| 3. The equivalence analogy principle, EAP Then Then w((φ(a1, a3) ↔φ(a2, a3)) ∧ψ(a1,⃗a) ∧ψ(a2,⃗a)) = w((α1(a1) ↔α1(a2)) ∧α1(a3)) = w(α1(a3)) −w(¬(α1(a1) ↔α1(a2)) ∧α1(a3)) = w(α1(a3)) −2w(α1(a1) ∧¬α1(a2) ∧α1(a3)). 3. The equivalence analogy principle, EAP GAP bears a superficial resemblance to the following analogy principle suggested by [2, Section 3] (though as far as we can tell Peirce viewed this as an abduction rather than an analogy principle): The Equivalence Analogy Principle, EAP For ⃗a = ⟨a3, a4, . . . , ak⟩and ψ(a1, ⃗a), φ(a1, ⃗a) ∈QFSL, The Equivalence Analogy Principle, EAP For ⃗a = ⟨a3, a4, . . . , ak⟩and ψ(a1, ⃗a), φ(a1, ⃗a) ∈QFSL, The Equivalence Analogy Principle, EAP For ⃗a = ⟨a3, a4, . . . , ak⟩and ψ(a1, ⃗a), φ(a1, ⃗a) ∈QFSL, (11) w(φ(a1,⃗a) ↔φ(a2,⃗a) | ψ(a1,⃗a) ∧ψ(a2,⃗a)) ≥w(φ(a1,⃗a) ↔φ(a2,⃗a)). (11) As with GAP it is the constants which are the carriers of the analogy and presumably, judging from their similarity, EAP’s justification is based on the same intuitions, so one might have expected that they would again have the same solutions, or more aptly lack of solutions. This is indeed almost the case provided we E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 32 allow the additional constants ⃗a in EAP. However dropping these constants gives a somewhat different, but still very restricted, set of solutions, in contrast to any supposedly similar intuitions. allow the additional constants ⃗a in EAP. However dropping these constants gives a somewhat different, but still very restricted, set of solutions, in contrast to any supposedly similar intuitions. To start with we shall give a characterization of the probability functions satisfying EAP, in the presence of our customary additional default assumptions of Px + SN. Theorem 2. Let w be a probability function on the unary language Lq satisfying Px + SN. Then w satisfies EAP just if w = cLq 0 . Proof. Suppose that w ̸= cLq 0 satisfies EAP. Without loss of generality we may assume that w(α1α2) > 0. Using de Finetti’s representation theorem (and the fact that for ⃗c ∈D2q we have w⃗c(α1(¬α1)) ≤1 4), we can see that (12) w(α1) > w(α2 1(¬α1)) ≥w(α2 1α2 2) > 0. w(α1) > w(α2 1(¬α1)) ≥w(α2 1α2 2) > 0. (12) Let ψ(a3) = α1(a3), φ(a1, a3) = α1(a1) ∧ψ(a3). Notice that ψ does not actually depend on a1 so ψ(a1, ⃗a) = ψ(a2, ⃗a) = ψ(a3). Then ψ(a3) = α1(a3), φ(a1, a3) = α1(a1) ∧ψ(a3). Notice that ψ does not actually depend on a1 so ψ(a1, ⃗a) = ψ(a2, ⃗a) = ψ(a3). 11 There is a particular worst case here which occurs when φ(a1) = α1(a1) and ψ(a1) = ¬α2(a1). Indeed this worst case and the bound given in (13) actually applies to any probability function satisfying Atom Exchangeability – for details of this and an investigation into variations on EAP and the underlying symmetry assumptions see [13]. Similarly w(φ(a1, a3) ↔φ(a2, a3)) = 1 −2w(α1(a1) ∧¬α1(a2) ∧α1(a3)). w(φ(a1, a3) ↔φ(a2, a3)) = 1 −2w(α1(a1) ∧¬α1(a2) ∧α1(a3)). w(φ(a1, a3) ↔φ(a2, a3)) = 1 −2w(α1(a1) ∧¬α1(a2) ∧α1(a3)). Thus for EAP to hold we must have Thus for EAP to hold we must have w(α1(a3))(1 −2w(α1(a1) ∧¬α1(a2) ∧α1(a3))) ≤w(α1(a3)) −2w(α1(a1) ∧¬α1(a2) ∧α1(a3)), w(α1(a3))(1 −2w(α1(a1) ∧¬α1(a2) ∧α1(a3))) ≤w(α1(a3)) −2w(α1(a1) ∧¬α1(a2) ∧α1(a3)), equivalently w(α1(a1) ∧¬α1(a2) ∧α1(a3)) ≤w(α1(a3)) · w(α1(a1) ∧¬α1(a2) ∧α1(a3)), which by (12) fails and gives the required contradiction. Notice that we only needed the single extra constant a3 to derive this contradiction. which by (12) fails and gives the required contradiction. Notice that we only needed the single extra constant a3 to derive this contradiction. To complete the proof we need to show that w = cLq 0 satisfies EAP. To complete the proof we need to show that w = cLq 0 satisfies EAP. To this end let φ(a1, ⃗a) ∈QFSL (where as usual ⃗a = ⟨a3, a4, . . . , ak⟩) and 1 ≤j ≤2q. Since for this probability function w w(αj(a1) →αj(am)) = 1, for any m, if for any m, if αj(x) ∧ k i=3 αj(ai) |= φ(x,⃗a) E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 33 then w(αj(a1) ∧φ(a1,⃗a) ∧φ(a2,⃗a)) = 2−q, w(αj(a1) ∧¬φ(a1,⃗a) ∧¬φ(a2,⃗a)) = 0, while if then w(αj(a1) ∧φ(a1,⃗a) ∧φ(a2,⃗a)) = 2−q, w(αj(a1) ∧¬φ(a1,⃗a) ∧¬φ(a2,⃗a)) = 0, while if w(αj(a1) ∧φ(a1,⃗a) ∧φ(a2,⃗a)) = 2−q, w(αj(a1) ∧¬φ(a1,⃗a) ∧¬φ(a2,⃗a)) = 0, w(αj(a1) ∧φ(a1,⃗a) ∧φ(a2,⃗a)) = 2−q, w(αj(a1) ∧¬φ(a1,⃗a) ∧¬φ(a2,⃗a)) = 0, αj(x) ∧ k i=3 αj(ai) |= ¬φ(x,⃗a) αj(x) ∧ k i=3 αj(ai) |= ¬φ(x,⃗a) then then w(αj(a1) ∧φ(a1,⃗a) ∧φ(a2,⃗a)) = 0, w(αj(a1) ∧¬φ(a1,⃗a) ∧¬φ(a2,⃗a)) = 2−q. w(αj(a1) ∧φ(a1,⃗a) ∧φ(a2,⃗a)) = 0, w(αj(a1) ∧¬φ(a1,⃗a) ∧¬φ(a2,⃗a)) = 2− w(αj(a1) ∧φ(a1,⃗a) ∧φ(a2,⃗a)) = 0, w(αj(a1) ∧¬φ(a1,⃗a) ∧¬φ(a2,⃗a)) = 2−q. In either case, In either case, In either case, w(αj(a1) ∧(φ(a1,⃗a) ↔φ(a2,⃗a))) = w(αj(a1) ∧φ(a1,⃗a) ∧φ(a2,⃗a)) + w(αj(a1) ∧¬φ(a1,⃗a) ∧¬φ(a2,⃗a)) = 2−q and summing over 1 ≤j ≤2q gives and summing over 1 ≤j ≤2q gives w(φ(a1,⃗a) ↔φ(a2,⃗a)) = w(φ(a1,⃗a) ∧φ(a2,⃗a)) + w(¬φ(a1,⃗a) ∧¬φ(a2,⃗a)) = 1. w(φ(a1,⃗a) ↔φ(a2,⃗a)) = w(φ(a1,⃗a) ∧φ(a2,⃗a)) + w(¬φ(a1,⃗a) ∧¬φ(a2,⃗a)) = 1. Since for θ, ξ ∈SLq, w(θ ∧ξ) = w(ξ) whenever w(θ) = 1, it follows that (11) holds with equality. Similarly 2 θ, ξ ∈SLq, w(θ ∧ξ) = w(ξ) whenever w(θ) = 1, it follows that (11) holds with equalit Since for θ, ξ ∈SLq, w(θ ∧ξ) = w(ξ) whenever w(θ) = 1, it follows that (11) holds with equality. 2 Note that the solution cLq 0 to (11) actually satisfies the stronger condition ULi + SN. It is clear that in the proof of Theorem 2 the additional constants ⃗a are playing an important role, and indeed that is the case. In particular, see [13], for q ≥2 the probability functions cLq λ satisfy the weaker version of EAP without the additional constants ⃗a, when, in fact exactly when,11 cLq λ (α1α2) ≤2−q(2q −1)−2, (13) (13) cLq λ (α1α2) ≤2−q(2q −1)−2, equivalently when λ ≤ 2q 22q −3 · 2q + 1. (14) λ ≤ 2q 22q −3 · 2q + 1. (14) Consequently the only λ for which this principle can hold for all q is λ = 0. Consequently the only λ for which this principle can hold for all q is λ = 0. Condition (14) is interesting because, to our knowledge, there are currently no other ‘rational principles’ considered in Inductive Logic which differentiate between the λ in the open range (0, ∞). In this case the often preferred value for λ of 2q (which corresponds to the uniform de Finetti prior for cLq λ ) lies above the bound given in (14) (for q ≥2) so that with that somewhat popular choice this weaker version of EAP fails. Returning again to the superficial similarity between GAP and EAP one might initially have felt that Returning again to the superficial similarity between GAP and EAP one might initially have felt that (15) (16) w(φ(a1,⃗a) ↔φ(a2,⃗a) | ψ(a1,⃗a) ∧ψ(a2,⃗a)) ≥w(φ(a1,⃗a) ↔φ(a1,⃗a)), (15) w(φ(a2,⃗a) | φ(a1,⃗a) ∧ψ(a1,⃗a) ∧ψ(a2,⃗a)) ≥w(φ(a2,⃗a) | φ(a1,⃗a)), (16) (16) 11 There is a particular worst case here which occurs when φ(a1) = α1(a1) and ψ(a1) = ¬α2(a1). Indeed this worst case and the bound given in (13) actually applies to any probability function satisfying Atom Exchangeability – for details of this and an investigation into variations on EAP and the underlying symmetry assumptions see [13]. E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 34 were essentially expressing the same sentiment. The above discussion however show that (15) can hold whilst (16) fails. Similarly Conversely by taking q = 2, φ(a1, ⃗a) = α1(a1), ψ(a1, ⃗a) = ¬α2(a1) and λ > 4/5 it can be checked that in this case (16) holds but (15) fails for cL2 λ . were essentially expressing the same sentiment. The above discussion however show that (15) can hold whilst (16) fails. Conversely by taking q = 2, φ(a1, ⃗a) = α1(a1), ψ(a1, ⃗a) = ¬α2(a1) and λ > 4/5 it can be checked that in this case (16) holds but (15) fails for cL2 λ . We remark that although Theorems 1 and 2 are proved here for a unary language L it can be shown that when the additional constants ⃗a are allowed they hold too, with the standard extension of c0 (as u⟨0,1,0,0,...⟩,L, see [20, Chapter 29]), for not purely unary languages.12 4. The constant analogy principle The previous two attempts to capture even a part13 of Bartha’s representation of analogy can at best be said to tell us what is not possible in the presence of Px + SN. Perhaps there may be more probability functions satisfying these analogy principles if we dropped Px and/or SN, but given the obvious strong attraction of Px and SN on grounds of symmetry compared with the apparently hazy intuitions which begat GAP and EAP this would hardly seem a worthwhile investigation in the context. An alternative, which also seems closer to Bartha’s intention, is to restrict the P, Q, A, B etc. to having the particularly simple form of just R(a), i.e. a unary relation applied to a constant. This yields two further principles depending on whether we take the carrier of the analogy to be the constants or the relations.14 In this section we take the analogy to be between the properties of two constants, the known positive analogies being instances where a predicate agreed on these two constants and a negative analogy when it disagreed. Precisely, for φ(x) = n  i=1 Rϵi i (x), ψ(x) = n  i=1 Rδi i (x), we define the ‘distance’ between φ and ψ to be ⌈φ −ψ⌉= n  i=1 |ϵi −δi| and propose: E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 35 Given that in this principle no particular emphasis is being placed on the number of predicates R1, R2, . . . , Rn that we have at our disposal it seems natural to assume not just Px + SN but rather ULi + SN. In that case we have the following somewhat satisfying result. Given that in this principle no particular emphasis is being placed on the number of predicates R1, R2, . . . , Rn that we have at our disposal it seems natural to assume not just Px + SN but rather ULi + SN. In that case we have the following somewhat satisfying result. Theorem 3. Let the probability function w on Lq satisfy ULi + SN. Then w satisfies CAP. m 3. Let the probability function w on Lq satisfy ULi + SN. Then w satisfies CAP. Proof. Since w is part of a ULi family wLr for r ∈N+ we may take the union of all these probability functions to produce a probability function defined on sentences of the language L = ∞ r=1 Lr and extending w. To avoid introducing any additional notation, and because it will not cause any confusion, we will also use w to denote this probability function. Let β1, β2, . . . , β2n+1 denote the atoms of Ln+1, say βk(a1) = Rn+1(a1) ∧φ(a1), βj(a2) = Rn+1(a2) ∧ψ(a2), βr(a2) = ¬Rn+1(a2) ∧ψ(a2), βr(a2) = ¬Rn+1(a2) ∧ψ(a2), where φ, ψ are as in the definition of CAP. Then where φ, ψ are as in the definition of CAP. Then where φ, ψ are as in the definition of CAP. Then w(Rn+1(a2) | Rn+1(a1) ∧ψ(a2) ∧φ(a1)) = w(βk(a1) ∧βj(a2)) w(βk(a1) ∧βj(a2)) + w(βk(a1) ∧βr(a2)). The Constant Analogy Principle, CAP For φ(x) = n i=1 Rϵi i (x) and ψ(x) = n i=1 Rδi i (x), The Constant Analogy Principle, CAP For φ(x) = n i=1 Rϵi i (x) and ψ(x) = n i=1 Rδi i (x), The Constant Analogy Principle, CAP For φ(x) = n i=1 Rϵi i (x) and ψ(x) = n i=1 Rδi i (x), w(Rn+1(a2) | Rn+1(a1) ∧ψ(a2) ∧φ(a1)) w(Rn+1(a2) | Rn+1(a1) ∧ψ(a2) ∧φ(a1)) w(Rn+1(a2) | Rn+1(a1) ∧ψ(a2) ∧φ(a1)) w(Rn+1(a2) | Rn+1(a1) ∧ψ(a2) ∧φ(a1)) (17) is a decreasing (not necessarily strictly) function of ⌈φ −ψ⌉. 12 In more detail suppose that L is a polyadic language and w ̸= c0 is a probability function on L satisfying Px + SN. Then there must be some relation symbol P of L and ⃗a, ⃗b such that w(P (⃗a) ∧¬P (⃗b)) > 0. By considering w(P (⃗a) ↔¬P (⃗d)) where ⃗d are new constants (not occurring in ⃗a and ⃗b) and using Ex we can see that we must have w(P (⃗c1) ∧¬P (⃗c2)) > 0 where the ⃗c1, ⃗c2 are disjoint. Now define the probability function v on L1 by v n  i=1 Rϵi 1 (ai) = w n  i=1 P ϵi(⃗ci) where ⃗ci are disjoint blocks of constants. Since w satisfies SN and Ex so does v. Let φ, ψ ∈QFSL1 provide counter-examples required for Theorems 1 and 2 for v and let φ∗, ψ∗be the result of replacing each R1(ai) in φ, ψ respectively by P (⃗ci). Then these provide the counter-examples required for Theorems 1 and 2 for w. L where ⃗ci are disjoint blocks of constants. Since w satisfies SN and Ex so does v. Let φ, ψ ∈QFSL1 provide counter-examples required for Theorems 1 and 2 for v and let φ∗, ψ∗be the result of replacing each R1(ai) in φ, ψ respectively by P (⃗ci). Then these provide the counter-examples required for Theorems 1 and 2 for w. L p p q In the other direction to show that cL 0 is a solution notice that if L has q relation symbols P1, . . . , Pq then for θ ∈QFSL, cL 0 (θ) = c Lq 0 (θ′) where θ′ is the result of replacing each Pi(aj1, aj2, . . . , ajr ) from L by Ri(aj1). 13 Since negative analogies do not figure. 14 It is also possible to consider a formalization in which it applies to sentences as carriers, see the Counterpart Principle of [12], [20, Chapter 22]. E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 (18) (18) By using the permutations of atoms licensed by Px + SN we may suppose here that By using the permutations of atoms licensed by Px + SN we may suppose here that βk(a1) = n+1  i=1 Ri(a1), βj(a2) = Rn+1(a2) ∧ m  i=1 Ri(a2) ∧ n  i=m+1 ¬Ri(a2), βr(a2) = ¬Rn+1(a2) ∧ m  i=1 Ri(a2) ∧ n  i=m+1 ¬Ri(a2), βk(a1) = n+1  i=1 Ri(a1), βj(a2) = Rn+1(a2) ∧ m  i=1 Ri(a2) ∧ n  i=m+1 ¬Ri(a2), βr(a2) = ¬Rn+1(a2) ∧ m  i=1 Ri(a2) ∧ n  i=m+1 ¬Ri(a2), where n −m = ⌈φ −ψ⌉. From this it is clear that (17) is purely a function of ⌈φ −ψ⌉(and n). It only remains to show that it is a decreasing function of ⌈φ −ψ⌉. Assume for the moment that the where n −m = ⌈φ −ψ⌉. From this it is clear that (17) is purely a function of ⌈φ −ψ⌉(and n). It only remains to show that it is a decreasing function of ⌈φ −ψ⌉. Assume for the moment that the = ⌈φ −ψ⌉. From this it is clear that (17) is purely a function of ⌈φ −ψ⌉(and n). where n −m = ⌈φ −ψ⌉. From this it is clear that (17) is purely a function of ⌈φ −ψ⌉(and n). It only remains to show that it is a decreasing function of ⌈φ −ψ⌉. Assume for the moment that the w(βg(a1) ∧βh(a2)) w(βg(a1) ∧βh(a2)) are all non-zero. Then by dividing top and bottom by its numerator we see that (17) will be a decreasing function of ⌈φ −ψ⌉just if w(βk(a1) ∧βr(a2)) w(βk(a1) ∧βj(a2)) (19) (19) is an increasing function of ⌈φ −ψ⌉. is an increasing function of ⌈φ −ψ⌉. is an increasing function of ⌈φ −ψ⌉. To this end define a function u on the state descriptions of the language L1 (whose atoms are just R1, ¬R1) by u(¬Rs 1 Rt−s 1 ) = 2tw  t i=1 Ri(a1) ∧ s i=1 ¬Ri(a2) ∧ t i=s+1 Ri(a2)  . E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 36 Notice that by Px the particular choice of distinct predicate symbols R1, . . . , Rt here is irrelevant. Using the fact that w satisfies ULi + SN it can be checked that u is, or at least extends to, a probability function which satisfies Ex. E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 With this definition the condition (19) becomes the requirement that Notice that by Px the particular choice of distinct predicate symbols R1, . . . , Rt here is irrelevant. Using the fact that w satisfies ULi + SN it can be checked that u is, or at least extends to, a probability function which satisfies Ex. With this definition the condition (19) becomes the requirement that u((¬R1)m+1Rn−m 1 ) u((¬R1)m Rn+1−m 1 ) (20) u((¬R1)m+1Rn−m 1 ) u((¬R1)m Rn+1−m 1 ) (20) (20) (20) is an increasing function of m. This will follow once we show that is an increasing function of m. This will follow once we show that u((¬R1)m+1Rn−m 1 ) u((¬R1)m Rn+1−m 1 ) ≥ u((¬R1)mRn−m+1 1 ) u((¬R1)m−1 Rn+2−m 1 ) . (21) (21) Since u satisfies Ex we know by de Finetti’s Theorem that for some countably additive measure μ on the Borel subsets of [0, 1] that u = w⟨x,1−x⟩dμ(x). (22) u = w⟨x,1−x⟩dμ(x). (22) Using this and writing h(x) = (1 −x)m−1xn−m, (21) becomes Using this and writing h(x) = (1 −x)m−1xn−m, (21) becomes Using this and writing h(x) = (1 −x)m−1xn−m, (21) becomes  (1 −x)2 h(x) dμ(x)  x(1 −x) h(x) dμ(x) ≥  x(1 −x) h(x) dμ(x)  x2 h(x) dμ(x) .  (1 −x)2 h(x) dμ(x)  x(1 −x) h(x) dμ(x) ≥  x(1 −x) h(x) dμ(x)  x2 h(x) dμ(x) .  (1 −x) h(x) dμ(x)  x(1 −x) h(x) dμ(x) ≥  x(1 −x) h(x) dμ(x)  x2 h(x) dμ(x) . But multiplying out this reduces to h(x) dμ(x) · x2 h(x) dμ(x) ≥  x h(x) dμ(x) 2 But multiplying out this reduces to But multiplying out this reduces to But multiplying out this reduces to h(x) dμ(x) · x2 h(x) dμ(x) ≥  x h(x) dμ(x) 2 which holds by Hölder’s Inequality. which holds by Hölder’s Inequality. w c o ds by ö de s equa ty Returning now to our earlier assumption that the w(βg(a1) ∧βh(a2)) are all non-zero, if this fails then defining u as above we should have Returning now to our earlier assumption that the w(βg(a1) ∧βh(a2)) are all non-zero, if this fails then defining u as above we should have u(Rk 1(¬R1)j) = 0 for some j, k. However by considering again (22) this can only happen if for some j, k. w(β1(a1) ∧β8(a2)) w(β1(a1) ∧β4(a2)) < w(β1(a1) ∧β7(a2)) w(β1(a1) ∧β3(a2)), equirement on (19), despite w satisfying Px + SN (but not ULi + SN of course). L From Theorem 3 it follows that all the cLq λ satisfy CAP. Indeed it is quite straightforward to show, appealing to de Finetti’s Theorem again, that any probability function satisfying Atom Exchangeability will satisfy CAP, whether or not it satisfies ULi + SN. Satisfying as Theorem 3 may be however it does raise a slightly uncomfortable issue. Firstly the intuition behind it seems no different from that which initially prompted us to propose GAP. Given the failure of that principle can we really claim that Theorem 3 in some way justifies our intuition? Is it not more reasonable to conclude that this theorem is grounded not on ‘analogy’ but on some different basis? And indeed a study at the proof shows that the key step is an application of a provable version of the Strong Principle of Instantial Relevance, see [20, Chapter 21] or [21], in which case we could be said to be simply appealing to our intuitions about relevance.15 Putting it another way then it could be said that the ‘analogy’ within CAP is really just reducible to ‘relevance’, raising for a moment the question whether, within the context of PIL, analogy is anything more than a special case of relevance. 15 Or ultimately symmetry since Ex implies SPIR for L1. 16 16 The characterization for q > 2 (with Px+SN) just requires the restriction to SL2 to have the form E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 However by considering again (22) this can only happen if u = νw⟨1,0⟩+ (1 −ν)w⟨0,1⟩ for some 0 ≤ν ≤1, in which case the original requirement on (18) holds trivially. 2 Not all probability functions satisfying just Px + SN satisfy CAP. For example when n + 1 = 3 and we order the βj as (in the obvious shorthand) R1 1R1 2R1 3, R1 1R1 2R0 3, R1 1R0 2R1 3, R1 1R0 2R0 3, R0 1R1 2R1 3, R0 1R1 2R0 3, R0 1R0 2R1 3, R0 1R0 2R0 3, b = 1/10, a = 1/5 and w is b = 1/10, a = 1/5 and w is (12)−1 w⟨a,b,b,a,b,b,b,b⟩+ w⟨a,b,b,b,b,a,b,b⟩+ w⟨a,b,b,b,b,b,a,b⟩ + w⟨b,a,a,b,b,b,b,b⟩+ w⟨b,a,b,b,a,b,b,b⟩+ w⟨b,a,b,b,b,b,b,a⟩ + w⟨b,b,a,b,a,b,b,b⟩+ w⟨b,b,a,b,b,b,b,a⟩+ w⟨b,b,b,b,a,b,b,a⟩ + w⟨b,b,b,a,b,b,a,b⟩+ w⟨b,b,b,a,b,a,b,b⟩+ w⟨b,b,b,b,b,a,a,b⟩ E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 37 then it can be checked that 5. The predicate analogy principle One family of probability functions on L2 satisfying Px + SN and PAP are the being an increasing function of ⌊φ −ψ⌋, a fact that we shall use repeatedly in what follows. One family of probability functions on L2 satisfying Px + SN and PAP are the u(b) = 2−1(w⟨b,1/2−b,1/2−b,b⟩+ w⟨1/2−b,b,b,1/2−b⟩) where 0 ≤b ≤1/2. Clearly the u(b) satisfy Px + SN. To see that they also satisfy PAP notice that for φ, ψ as in the statement of PAP and m = ⌊φ −ψ⌋, where 0 ≤b ≤1/2. Clearly the u(b) satisfy Px + SN. To see that they also satisfy PAP notice that for φ, ψ as in the statement of PAP and m = ⌊φ −ψ⌋, u(b)(α2(an+1) ∧ψ(⃗a) ∧φ(⃗a)) u(b)(α1(an+1) ∧ψ(⃗a) ∧φ(⃗a)) = (1/2 −b)m+1bn−m + bm+1(1/2 −b)n−m (1/2 −b)mbn−m+1 + bm(1/2 −b)n−m+1 hand side, when defined, is increasing in m (for fixed n ≥m). and this right hand side, when defined, is increasing in m (for fixed n ≥m). and this right hand side, when defined, is increasing in m (for fixed n ≥m). A second family of probability functions on L2 satisfying PAP + Px + SN, in this case rather trivially, are those of the form v(d) = 4−1(w⟨d,0,0,1−d⟩+ w⟨1−d,0,0,d⟩+ w⟨0,d,1−d,0⟩+ w⟨0,1−d,d,0⟩) where 0 ≤d ≤1. Trivially because any φ(⃗a) ∧ψ(⃗a) containing atoms both from {α1, α4} and from {α2, α3} gets probability zero. where 0 ≤d ≤1. Trivially because any φ(⃗a) ∧ψ(⃗a) containing atoms both from {α1, α4} and from {α2, α3} gets probability zero. In fact the probability functions which satisfy PAP + Px + SN are precisely those whose restriction to SL2 is a convex mixture of probability functions from these two families. Precisely: Theorem 4. Let the probability function w on L2 satisfy Px + SN. 17 Recall the convention introduced at footnote 6 concerning zero denominators. 5. The predicate analogy principle In contrast to the three previous sections we now consider an interpretation of Bartha’s representation in which we take the predicates of the language to be the carriers of the analogy. That is we take the analogy to be between the properties of two predicates, the known positive analogies being instances where these predicates agreed on a constant and a negative analogy when they disagreed. Precisely, for φ = n  i=1 Rϵi 1 (ai), ψ = n  i=1 Rδi 2 (ai), define the ‘distance’ between φ and ψ to be ⌊φ −ψ⌋= n  i=1 |ϵi −δi| and set: The Predicate Analogy Principle, PAP For φ(⃗a) = n i=1 Rϵi 1 (ai) and ψ(⃗a) = n i=1 Rδi 2 (ai), The Predicate Analogy Principle, PAP The Predicate Analogy Principle, PAP For φ(⃗a) = n i=1 Rϵi 1 (ai) and ψ(⃗a) = n i=1 Rδi 2 (ai), gy p , For φ(⃗a) = n i=1 Rϵi 1 (ai) and ψ(⃗a) = n i=1 Rδi 2 (ai), gy p , For φ(⃗a) = n i=1 Rϵi 1 (ai) and ψ(⃗a) = n i=1 Rδi 2 (ai), gy p , For φ(⃗a) = n i=1 Rϵi 1 (ai) and ψ(⃗a) = n i=1 Rδi 2 (ai), w(R2(an+1) | R1(an+1) ∧ψ(⃗a) ∧φ(⃗a)) w(R2(an+1) | R1(an+1) ∧ψ(⃗a) ∧φ(⃗a)) (23) w(R2(an+1) | R1(an+1) ∧ψ(⃗a) ∧φ(⃗a)) (23) (23) is a decreasing function of ⌊φ −ψ⌋(for fixed n). is a decreasing function of ⌊φ −ψ⌋(for fixed n). Notice that since only two predicate symbols appear in (23) it is natural to first study this principle when q = 2.16 Setting α1(x) = R1(x) ∧R2(x), α2(x) = R1(x) ∧¬R2(x), α3(x) = ¬R1(x) ∧R2(x), α4(x) = ¬R1(x) ∧¬R2(x), 15 Or ultimately symmetry since Ex implies SPIR for L1. 16 16 The characterization for q > 2 (with Px+SN) just requires the restriction to SL2 to have the form we shall shortly be describing. 8 E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 38 this condition (23) is equivalent to17 this condition (23) is equivalent to17 w(α2(an+1) ∧φ(⃗a) ∧ψ(⃗a)) w(α1(an+1) ∧φ(⃗a) ∧ψ(⃗a)), being an increasing function of ⌊φ −ψ⌋, a fact that we shall use repeatedly in what follows. 5. The predicate analogy principle Using (24) we can make w(α2 ∧φ1 ∧ψ1) w(α1 ∧φ1 ∧ψ1) w(α2 ∧φ1 ∧ψ1) w(α1 ∧φ1 ∧ψ1) arbitrarily close to arbitrarily close to w⃗b(α2) w⃗b(α1) = b2 b1 w⃗b(α2) w⃗b(α1) = b2 b1 w⃗b(α2) w⃗b(α1) = b2 b1 by picking r suitably large. Similarly, since by Px + SN, ⟨b1, b3, b2, b4⟩must also be a support point of μ, we can make w(α2 ∧φ2 ∧ψ2) w(α1 ∧φ2 ∧ψ2) arbitrarily close to b3/b1. But since arbitrarily close to b3/b1. But since ⌊φ1 −ψ1⌋= ⌊φ2 −ψ2⌋ PAP gives that these two values b2/b1, b3/b1 must be equal. It follows that b2 = b3. If b2 = 0 then we already have that ⟨b1, b2, b3, b4⟩ ∈B. If b2 ̸= 0 a similar argument using the support points ⟨b2, b1, b4, b3⟩, ⟨b2, b4, b1, b3⟩shows that b1 = b4. From this it follows that μ(A ∪B) = 1 for A, B as above. We claim that it must be the case that μ(A) = 1 or μ(B) = 1. For otherwise we can pick support points of μ, ⟨b, 1/2 −b, 1/2 −b, b⟩ ∈A −B and, without loss of generality, ⟨d, 0, 0, 1 −d⟩ ∈B −A (with 0 < b < 1/2 and d ̸= 0, 1/2). Then by PAP we must have equality between PAP gives that these two values b2/b1, b3/b1 must be equal. It follows that b2 = b3. If b2 = 0 then we already have that ⟨b1, b2, b3, b4⟩ ∈B. If b2 ̸= 0 a similar argument using the support points ⟨b2, b1, b4, b3⟩, ⟨b2, b4, b1, b3⟩shows that b1 = b4. From this it follows that μ(A ∪B) = 1 for A, B as above. PAP gives that these two values b2/b1, b3/b1 must be equal. It follows that b2 = b3. If b2 = 0 then we already have that ⟨b1, b2, b3, b4⟩ ∈B. If b2 ̸= 0 a similar argument using the support points ⟨b2, b1, b4, b3⟩, ⟨b2, b4, b1, b3⟩shows that b1 = b4. From this it follows that μ(A ∪B) = 1 for A, B as above. We claim that it must be the case that μ(A) = 1 or μ(B) = 1. 5. The predicate analogy principle Then w satisfies PAP just if either w is a convex mixture of the u(b) or w is a convex mixture of the v(d) as above, equivalently, just if there is a countably additive measure μ on the Borel subsets of D4 such that for θ ∈SL2, w(θ) = D4 w⃗x(θ) dμ(⃗x) w(θ) = D4 w⃗x(θ) dμ(⃗x) and either μ(A) = 1 where and either μ(A) = 1 where A = {⟨x1, x2, x3, x4⟩∈D4 | x1 = x4 and x2 = x3}, or μ(B) = 1 where or μ(B) = 1 where B = {⟨x1, x2, x3, x4⟩∈D4 | x2 = x3 = 0 or x1 = x4 = 0}. B = {⟨x1, x2, x3, x4⟩∈D4 | x2 = x3 = 0 or x1 = x4 = 0}. Proof. Suppose that w satisfies PAP + Px + SN. Let ⃗b = ⟨b1, b2, b3, b4⟩be a support point of the de Finetti prior μ of w. We shall use [20, Lemma 12.1] which tells us that Proof. Suppose that w satisfies PAP + Px + SN. Let ⃗b = ⟨b1, b2, b3, b4⟩be a support point of the de Finetti prior μ of w. We shall use [20, Lemma 12.1] which tells us that lim r→∞  D4 xi 4 j=1 x[rbj] j dμ(⃗x)  D4 4 j=1 x[rbj] j dμ(⃗x) = bi, (24) (24) where as usual [rb1] is the integer part of rb1 etc. 17 Recall the convention introduced at footnote 6 concerning zero denominators. 17 Recall the convention introduced at footnote 6 concerning zero denominators. E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 39 Let φ1 ∧ψ1 = α[rb1] 1 α[rb2] 2 α[rb3] 3 α[rb4] 4 , φ2 ∧ψ2 = α[rb1] 1 α[rb3] 2 α[rb2] 3 α[rb4] 4 , φ1 ∧ψ1 = α[rb1] 1 α[rb2] 2 α[rb3] 3 α[rb4] 4 , φ2 ∧ψ2 = α[rb1] 1 α[rb3] 2 α[rb2] 3 α[rb4] 4 , where the φi, ψi only mention the predicate R1, R2 respectively. Note that where the φi, ψi only mention the predicate R1, R2 respectively. Note that w(αi ∧φ1 ∧ψ1) = D4 xi 4 j=1 x[rbj] j dμ(⃗x) w(αi ∧φ1 ∧ψ1) = D4 xi 4 j=1 x[rbj] j dμ(⃗x) First assume that b1 ̸= 0. 5. The predicate analogy principle For otherwise we can pick support points of μ, ⟨b, 1/2 −b, 1/2 −b, b⟩ ∈A −B and, without loss of generality, ⟨d, 0, 0, 1 −d⟩ ∈B −A (with 0 < b < 1/2 and d ̸= 0, 1/2). Then by PAP we must have equality between  A xk 1x2xn−k 4 dμ(⃗x) +  B−A xk 1x2xn−k 4 dμ(⃗x)  A xk+1 1 xn−k 4 dμ(⃗x) +  B−A xk+1 1 xn−k 4 dμ(⃗x) and  A xj 1x2xn−j 4 dμ(⃗x) +  B−A xj 1x2xn−j 4 dμ(⃗x)  A xj+1 1 xn−j 4 dμ(⃗x) +  B−A xj+1 1 xn−j 4 dμ(⃗x) for k, j ≤n. Since for any ⟨x1, x2, x3, x4⟩ ∈A we have x1 = x4 it must be the case that for k, j ≤n. Since for any ⟨x1, x2, x3, x4⟩ ∈A we have x1 = x4 it must be the case that A xk 1x2xn−k 4 dμ(⃗x) = A xj 1x2xn−j 4 dμ(⃗x), A xk+1 1 xn−k 4 dμ(⃗x) = A xj+1 1 xn−j 4 dμ(⃗x), E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 40 and by the existence of ⟨b, 1/2 −b, 1/2 −b, b⟩these are non-zero. Furthermore, and by the existence of ⟨b, 1/2 −b, 1/2 −b, b⟩these are non-zero. Furthermore, B−A xk 1x2xn−k 4 dμ(⃗x) = 0 = B−A xj 1x2xn−j 4 dμ(⃗x) B−A xk 1x2xn−k 4 dμ(⃗x) = 0 = B−A xj 1x2xn−j 4 dμ(⃗x) for n > 0, so it must be the case that for n > 0, so it must be the case that B−A xk+1 1 xn−k 4 dμ(⃗x) = B−A xj+1 1 xn−j 4 dμ(⃗x). Hence  B−A x[dm]+2 1 x[(1−d)m] 4 dμ(⃗x)  B−A x[dm] 1 x[(1−d)m] 4 dμ(⃗x) =  B−A x[dm]+1 1 x[(1−d)m]+1 4 dμ(⃗x)  B−A x[dm] 1 x[(1−d)m] 4 dμ(⃗x) . (25) (25) Let Let w′ = (μ(B −A))−1 B−A w⃗x dμ(⃗x) . w′ = (μ(B −A))−1 B−A w⃗x dμ(⃗x) . Using μ(A ∪B) = 1 and d ̸= 0, 1/2 we can see that ⟨d, 0, 0, 1 −d⟩is a support point of w′. Hence it follows from [20, Lemma 12.1] that for large m the integrals (25) are close to d2, d(1 −d) respectively, which is impossible. In the other direction let w satisfy Px+SN and μ(A) = 1. But that gives that either w(α2(a1) ∧α1(a2)) = 0 or But that gives that either w(α2(a1) ∧α1(a2)) = 0 or w(α2(a1) ∧α2(a2)) = w(α2(a1) ∧α3(a2)) w(α2(a1) ∧α2(a2)) = w(α2(a1) ∧α3(a2)) and with Ax the only possibilities here are c0 and c∞. 6. Analogy as possibility In the previous four sections we have looked at formulations of analogical support as enhancement of probability. However as Bartha points out in [1] analogy can act to simply engender plausibility, or as we shall call it possibility. To give an example, the fact that the commonest bird in the United States in 1814 (the passenger pigeon) was extinct by 1914 may be used as an argument that ‘by analogy’, the monarch – arguably the currently commonest butterfly in the United States, may equally regrettably be extinct a century from now. For here it seems that the argument is aimed not so much at raising the probability as creating the possibility which we will take to mean producing a non-zero probability. One explanation why we might see this as in any sense a worthwhile argument to make in a discussion on the future of the monarch is that viewed from a certain angle monarchs and passenger pigeons may be thought of as the same thing, at least as regards the features that are actually relevant here. Thus the realization that it had happened once argues that it could happen again. The example might seem to correspond to the Extended Principle of Instantial Relevance, (3). Here however we shall propose an alternative formulation which is about creating possibility, and also more obviously captures this idea of ‘being thought of as the same thing as regards the relevant features’. 5. The predicate analogy principle Define a probability function v on the language L1 with a single predicate symbol R1 by Using μ(A ∪B) = 1 and d ̸= 0, 1/2 we can see that ⟨d, 0, 0, 1 −d⟩is a support point of w′. Hence it follows from [20, Lemma 12.1] that for large m the integrals (25) are close to d2, d(1 −d) respectively, which is impossible. In the other direction let w satisfy Px+SN and μ(A) = 1. Define a probability function v on the language L1 with a single predicate symbol R1 by v  m  i=1 Rϵi 1 (ai)  = w  m  i=1 (α1(ai) ∨α4(ai))ϵi  = 2mw  m  i=1 αhi(ai)  for hi ∈{1, 4} when ϵi = 1, hi ∈{2, 3} when ϵi = 0. Then v satisfies Ex + SN and for m = ⌊φ −ψ⌋ for hi ∈{1, 4} when ϵi = 1, hi ∈{2, 3} when ϵi = 0. Then v satisfies Ex + SN and for m = ⌊φ −ψ⌋ w(α2 ∧φ ∧ψ) w(α1 ∧φ ∧ψ) = v(Rn−m 1 (¬R1)m+1) v(Rn−m+1 1 (¬R1)m), already met as (20) and shown to be increasing in m under the assumption of Ex. ave already met as (20) and shown to be increasing in m under the assumption of Ex which we have already met as (20) and shown to be increasing in m under the assumption of Ex. Finally in the case when μ(B) = 1 it is straightforward to check that PAP holds, trivially in fact. 2 Finally in the case when μ(B) = 1 it is straightforward to check that PAP holds, trivially in fact. 2 Given Ax there are only two probability functions on L2 satisfying this, c0 and c∞. For suppose w satisfies PAP and Ax and as usual let α1(x) = R1(x) ∧R2(x), α2(x) = R1(x) ∧¬R2(x), α3(x) = ¬R1(x) ∧R2(x), α4(x) = ¬R1(x) ∧¬R2(x). Then by PAP Then by PAP w(R2(a2) | R1(a2) ∧α2(a1)) = w(R2(a2) | R1(a2) ∧α3(a1)). E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 41 Dolly’s Principle, DP Dolly s Principle, DP For θ(a1, a2, . . . , am) ∈SL, if σ : {a1, a2, . . . , am} →{a1, a2, . . . , am} and w(θ(σ(a1), σ(a2), . . . , σ(am))) > 0 then w(θ(a1, a2, . . . , am)) > 0. Notice that by repeated application (and Ex) it is enough that this principle holds for σ(2) = 1, σ(i) = i for i ̸= 2. ̸ We shall now show that for the unary language Lq Ex already implies DP. First however we seem to need a (useful) lemma which applies even to a possibly polyadic language L. Lemma 5. Let θ(a1, a2, . . . , am) ≡φ(a1, a2, . . . , am). Then for σ : {a1, a2, . . . , am} →{a1, a2, . . . , am}, θ(σ(a1), σ(a2), . . . , σ(am)) ≡φ(σ(a1), σ(a2), . . . , σ(am)). Proof. Let K be a structure for the language L with the same relation symbols as L but only the constant symbols σ(a1), σ(a2), . . . , σ(am) and suppose that K |= θ(σ(a1), σ(a2), . . . , σ(am)). Then Then K |= θ(σ(a1)K, σ(a2)K, . . . , σ(am)K), K |= θ(σ(a1)K, σ(a2)K, . . . , σ(am)K), where σ(a1)K is the interpretation of the constant σ(a1) in K etc. Clearly also J |= θ(σ(a1)K, σ(a2)K, . . . , σ(am)K) J |= θ(σ(a1)K, σ(a2)K, . . . , σ(am)K) 42 E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 42 where J is a structure for L extending K in which aJ i = σ(ai)K for i ≤m. In other words J |= θ(aJ 1 , . . . , aJ m), where J is a structure for L extending K in which aJ i = σ(ai)K for i ≤m. In other words J |= θ(aJ 1 , . . . , aJ m), J |= θ(aJ 1 , . . . , aJ m), J |= θ(aJ 1 , . . . , aJ m), so J |= θ(a1, . . . , am) J |= θ(a1, . . . , am) and by logical equivalence, J |= φ(a1, . . . , am). J |= φ(a1, . . . , am). J |= φ(a1, . . . , am). Dolly’s Principle, DP Reversing the above argument with φ in place of θ now gives K |= φ(σ(a1), . . . , σ(am)), as required. 2 / Journal of Applied Logic 14 (2016) 22–45 43 So ar∈Rg(σ) xgrw⃗x ⎛ ⎝ 2q  j=1 (∃x αj(x))ϵj ⎞ ⎠ must be non-zero for a non-null (with respect to μ) set of ⃗x ∈D2q and as a result the same must hold for ar∈Rg(σ) xsr grw⃗x ⎛ ⎝ 2q  j=1 (∃x αj(x))ϵj ⎞ ⎠ ar∈Rg(σ) xsr grw⃗x ⎛ ⎝ 2q  j=1 (∃x αj(x))ϵj ⎞ ⎠ where sr is the number of ai mapped by σ to ar. Hence where sr is the number of ai mapped by σ to ar. Hence where sr is the number of ai mapped by σ to ar. Hence where sr is the number of ai mapped by σ to ar. Hence D2q ar∈Rg(σ) xsr grw⃗x ⎛ ⎝ 2q  j=1 (∃x αj(x))ϵj ⎞ ⎠dμ(⃗x) > 0. (29) (29) But the left hand side of (29) is just what we get if we apply de Finetti’s Theorem to this conjunct in the representation of θ(a1, . . . , am), so the required result follows. 2 But the left hand side of (29) is just what we get if we apply de Finetti’s Theorem to this conjunct in the representation of θ(a1, . . . , am), so the required result follows. 2 For unary languages then DP adds nothing new, it already follows from the standing assumption Ex. However this fact does not carry over to polyadic languages. For example if L is the language with a single binary relation symbol R and w is the obvious version of Carnap’s m† (equivalently c∞) on this language then w(∀x (R(a1, x) ↔R(a2, x))) = 0 whilst whilst w(∀x (R(a1, x) ↔R(a1, x))) = 1. Nevertheless there is still a wide class of polyadic probability functions which do satisfy DP, as we shall show in a forthcoming paper. as required. 2 Notice that an immediate corollary of this result is that Super Regularity, i.e. that w(ψ) > 0 whenever ψ ∈SL is consistent, already implies DP (via showing that if θ(a1, . . . , am) is inconsistent then so is θ(aσ(1), . . . , aσ(m))). Theorem 6. For the unary language Lq, Ex implies DP. Theorem 6. For the unary language Lq, Ex implies DP. Proof. Let θ(a1, . . . , am) ∈SLq. Then as at (10) θ is logically equivalent to a disjunction of sentences of the form m  i=1 αhi(ai) ∧ 2q  j=1 (∃x αj(x))ϵj. m  i=1 αhi(ai) ∧ 2q  j=1 (∃x αj(x))ϵj. If w(θ(σ(a1), σ(a2), . . . , σ(am)) > 0 then by Lemma 5 this must also hold for the image under σ of this representation of θ so for at least one such disjunct we must have w ⎛ ⎝ m  i=1 αhi(σ(ai)) ∧ 2q  j=1 (∃x αj(x))ϵj ⎞ ⎠> 0. (26) (26) The only way this is possible is if hi = hr whenever σ(ai) = σ(ar), otherwise the sentence in (26) would be inconsistent so have probability 0. So dropping repeated conjuncts (26) can equivalently be written as w ⎛ ⎝  ar∈Rg(σ) αgr(ar) ∧ 2q  j=1 (∃x αj(x))ϵj ⎞ ⎠> 0 (27) (27) where gr = hi for i such that σ(ai) = ar. where gr = hi for i such that σ(ai) = ar. From (27), de Finetti’s Theorem and the Constant Irrelevance Principle give From (27), de Finetti’s Theorem and the Constant Irrelevance Principle give From (27), de Finetti’s Theorem and the Constant Irrelevance Principle give (27), de Finetti’s Theorem and the Constant Irrelevance Principle give From (27), de Finetti’s Theorem and the Constant Irrelevance Principle give D2q ar∈Rg(σ) xgrw⃗x ⎛ ⎝ 2q  j=1 (∃x αj(x))ϵj ⎞ ⎠dμ(⃗x) > 0. (28) (28) E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 43 E. Howarth et al. 7. Conclusion Doing so would still give CAP (and DP) as a consequence but would, for q ≥2, restrict GAP, EAP and PAP down to the single probability function cLq 0 of Carnap’s Continuum. Combined with previous results in [11,12] a pattern seems to be emerging with so called ‘Analogy Prin- ciples’, namely that they either hold, almost by chance, for some small family of otherwise (apparently) undistinguished probability functions, or they are actually consequences of some already established and acceptable principles such as ULi + SN or Ax. In other words, to our knowledge we do not currently have any analogy principles which genuinely introduce new concepts without also reducing the field of ‘rational probability functions’ down to almost a triviality (and leading to the conclusion that such a version of ‘reasoning by analogy’ is both very powerful and very dangerous). Of course there are numerous further formulations and variations that one might base on CAIR and perhaps some of those might yet endorse it in the context of PIL. On the basis of what we have here however the picture of analogical support as presented in CAIR seems not to have materialized, an outcome in parallel with Bartha’s own criticisms of CAIR within what we would term Applied Inductive Logic. 7. Conclusion In short we have shown that in the presence of Ex+Px+SN the principles GAP, EAP and PAP place very severe demands on a probability function, and must now be considered dead ends, DP makes no demands at all whilst CAP is actually satisfied by a naturally attractive class of such probability functions, namely those that satisfy the somewhat stronger background condition of ULi + SN. As far as Bartha’s candidate representation is concerned then we can say that CAP seems to provide a viable formulation of it in the context of PIL whereas GAP, EAP and PAP do not. Still this raises the uncomfortable question of why they produce such different conclusions when they all appear to be based on similar intuitions about analogical support. Given that CAP follows from ULi + SN it is an interesting question to ask from where in this back- ground assumption the ‘analogical support’ originates. Inspecting the proof of Theorem 3 we see that the key inequality is (21) which derives from simply the assumption Ex via de Finetti’s Theorem. This is ex- actly similar to the derivation from Ex of the Extended Principle of Instantial Relevance from which we might reasonably question whether ‘analogy as enhancement of probability’ is really anything more than ‘relevance’, an already quite well studied notion (see [20]). E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 44 Throughout this paper we have taken Ex + Px + SN, or ULi + SN, as our background assumptions. However the rather widespread acceptance of Johnson’s Sufficientness Postulate (JSP) within Inductive Logic might on the contrary be used as an argument for strengthening these to Ax, or ULi+Ax, since these are consequences of JSP. Doing so would still give CAP (and DP) as a consequence but would, for q ≥2, restrict GAP, EAP and PAP down to the single probability function cLq 0 of Carnap’s Continuum. Throughout this paper we have taken Ex + Px + SN, or ULi + SN, as our background assumptions. However the rather widespread acceptance of Johnson’s Sufficientness Postulate (JSP) within Inductive Logic might on the contrary be used as an argument for strengthening these to Ax, or ULi+Ax, since these are consequences of JSP. References [1] P. Bartha, Analogy and analogical reasoning, in: Edward N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy (Fall 2013 Edition), http://plato.stanford.edu/archives/fall2013/entries/reasoning-analogy/. [2] Robert Burch, Charles Sanders Peirce, in: Edward N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy (Winter 2014 Edition), http://plato.stanford.edu/archives/win2014/entries/peirce/. [3] R. Carnap, A basic system of inductive logic, in: R.C. Jeffrey (Ed.), Studies in Inductive Logic and Probability, vol. II, University of California Press, 1980, pp. 7–155. [4] R. Carnap, W. Stegmüller, Induktive Logik und Wahrscheinlichkeit, Springer-Verlag, Wien, 1959 [5] R. Festa, Analogy and exchangeability in predictive inferences, Erkenntnis 45 (1996) 229– [6] H. Gaifman, Concerning measures on first order calculi, Isr. J. Math. 2 (1964) 1–18. [7] H. Gaifman, Applications of de Finetti’s theorem to inductive logic, in: R. Carnap, R.C. Jeffrey (Eds.), Studies in Inductive Logic and Probability, vol. I, University of California Press, 1971, pp. 235–251. J.Y. Halpern, D. Koller, Random worlds and maximum entropy, J. Artif. Intell. Res. 2 (1994) 33–88. [8] A.J. Grove, J.Y. Halpern, D. Koller, Random worlds and maximum entropy, J. Artif. Intell. Res [9] M.B. Hesse, The Structure of Scientific Inference, University of California Press, 1974. [9] M.B. Hesse, The Structure of Scientific Inference, University of California Press, 1974. 10] M.B. Hesse, Analogy and confirmation theory, Dialectica 17 (2–3) (September 1963) 284–292. [11] A. Hill, J.B. Paris, An analogy principle in inductive logic, Ann. Pure Appl. Log. 164 (2013) 1293–1321. [12] A. Hill, J.B. Paris, The counterpart principle of analogical support by similarity, Erkenntnis (October 2013), Online First Article. [13] E. Howarth, New rationality principles in pure inductive logic, Doctoral Thesis, The University of Manchester, Manchester, UK, 2015, to become available at http://www.maths.manchester.ac.uk/~jeff/. 14] J. Humburg, The principle of instantial relevance, in: R. Carnap, R.C. Jeffrey (Eds.), Studies Probability, vol. I, University of California Press, Berkeley and Los Angeles, 1971, pp. 225–233. [15] P. Maher, Probabilities for multiple properties: the models of Hesse, Carnap and Kemeny, Erkenntnis 55 (2001) 183–216. [16] P. Maher, A conception of inductive logic, Philos. Sci. 73 (2006) 513–520. [15] P. Maher, Probabilities for multiple properties: the models of Hesse, Carnap and Kemeny, Erkenntnis 55 (2001) 183–216. [15] P. Maher, Probabilities for multiple properties: the models of Hesse, Carn 15] P. Maher, Probabilities for multiple properties: the models of Hesse, Carnap and Kemeny, Erken [16] P. Maher, A conception of inductive logic, Philos. Sci. 73 (2006) 513–520. Maher, A conception of inductive logic, Philos. Sci. E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 [23] G. Polya, in: Geoffrey Cumberlege (Ed.), Patterns of Plausible Inference, in: Mathematics and Plausible Reasoning, vol. II, Oxford University Press, 1954. [23] G. Polya, in: Geoffrey Cumberlege (Ed.), Patterns of Plausible Inference, in: Mathematics and Plausible Reasoning, vol. II, Oxford University Press, 1954. [24] J.W. Romeijn, Analogical predictions for explicit similarity, Erkenntnis 64 (2) (2006) 253–280. [25] B. Skyrms, Analogy by similarity in hyper-Carnapian inductive logic, in: J. Earman, A.I. Janis, G. Massey, N. Rescher (Eds.), Philosophical Problems of the Internal and External Worlds, University of Pittsburgh Press, 1993, pp. 273–282. [25] B. Skyrms, Analogy by similarity in hyper-Carnapian inductive logic, in: J. Earman, A.I. Ja (Eds.), Philosophical Problems of the Internal and External Worlds, University of Pittsburgh y , [24] J.W. Romeijn, Analogical predictions for explicit similarity, Erkenntnis 64 (2) (2006) 253–280 [ ] A A [24] J.W. Romeijn, Analogical predictions for explicit similarity, Erkenntnis 64 (2) (2006) 253–280. [24] J.W. Romeijn, Analogical predictions for explicit similarity, Erkenntnis 64 (2) (2006) 253 280. [25] B. Skyrms, Analogy by similarity in hyper-Carnapian inductive logic, in: J. Earman, A.I. Janis, G. Massey, N. Rescher (Eds.), Philosophical Problems of the Internal and External Worlds, University of Pittsburgh Press, 1993, pp. 273–282. References 73 (2006) 513–520. 17] M.C. di Maio, Predictive probability and analogy by similarity, Erkenntnis 43 (3) (1995) 369–39 [17] M.C. di Maio, Predictive probability and analogy by similarity, Erkenntn to this paper, available at http://www.maths.manchester.ac.uk/~jeff/papers/jp150303A1.pdf. 18] Supplement to this paper, available at http://www.maths.manchester.ac.uk/~jeff/papers/jp1503 [19] J.B. Paris, Pure inductive logic, in: L. Horsten, R. Pettigrew (Eds.), The Continuum Companion to Philosophical Logic, Continuum International Publishing Group, London, 2011, pp. 428–449. [20] J.B. Paris, A. Vencovská, Pure inductive logic, in: Perspectives in Mathematical Logic, in: Association of Symbolic Logic Series, Cambridge University Press, 2015, DOI: http://dx.doi.org/10.1017/CBO9781107326194. 21] J.B. Paris, P. Waterhouse, Atom exchangeability and instantial relevance, J. Philos. Log. 38 (3) [21] J.B. Paris, P. Waterhouse, Atom exchangeability and instantial relevance, J. Philos. Log. 38 (3) (2009) 313–332. [22] G. Polya, in: Geoffrey Cumberlege (Ed.), Induction and Analogy in Mathematics, in: Mathematics and Plausible Reasoning, vol. I, Oxford University Press, 1954. E. Howarth et al. / Journal of Applied Logic 14 (2016) 22–45 45
https://openalex.org/W2808665243
https://dergipark.org.tr/en/download/article-file/488558
Turkish
null
Examination on the Students’ Attitudes towards Using Emoticons for Communication
Kastamonu eğitim dergisi
2,018
cc-by
6,032
Abstract The present study examines the children’s attitudes towards emoticons they frequently use both in verbal and written communication to express their feelings and ideas. The literature survey conducted shows that although emoticons have been a curious subject for researchers lately, there is still a need to study the concept further in many aspects. The fact that the place and importance of emoticons in education have not been explained completely makes the present study more essential. We developed “Attitude Scale for Using Emoticons (ASK TO)” in order to determine children’s attitudes towards emoticons they use both in school environment and other places. The scale has been completed in accordance with the comments and recommendations by authorities in the field and by assessment and evaluation specialists. Then the pilot study was implemented on fifty students. At the end of the implementation, the scale and appendix were reviewed and implemented on 297 students of eighth grade. Data from the implementation were analyzed through SPSS 17 statistics program and the validity, reliability and factor analyses of the scale were done. The result of the analyses gave a Cronbach’s Alpha value of (,844), suggesting a high reliability for the scale. In the factor analysis, KMO value was found to be (,872) and the Barlett test was (p= ,000) found significant, suggesting that the factor has a good homogeneity. At the end of the research it was determined that the students’ attitudes towards emoticones were very positive. As a result of this finding it has been suggested that emoticons can be used as a useful tool in some areas of education. Geliş Tarihi: 26.12.2016 Yayına Kabul Tarihi: 21.11.2017 Alıntı: Sönmez, H. (2018). Emoticonların iletişim aracı olarak kullanılmasına Kastamonu Education Journal, 26(4), 1081-1089. doi:10.24106 The present study examines the children’s attitudes towards emoticons they frequently use both in verbal and written communication to express their feelings and ideas. The literature survey conducted shows that although emoticons have been a curious subject for researchers lately, there is still a need to study the concept further in many aspects. The fact that the place and importance of emoticons in education have not been explained completely makes the present study more essential. We developed “Attitude Scale for Using Emoticons (ASK TO)” in order to determine children’s attitudes towards emoticons they use both in school environment and other places. Anahtar Kelimeler Anahtar Kelimeler emoticon iletişim aracı öğrenci tutumları Keywords emoticon communication tool students’ attitudes Bu çalışmada öğrencilerin duygu ve düşüncelerini yazılı olarak ifade etmek için sıklıkla kullandığı emoticonlara yönelik tutumları incelenmiştir. Yapılan literatür taraması sonucunda emoticonların son zamanlarda araştırmacıların dikkatini çekse de bu konunun birçok yönden hâlâ araştırılması gerektiği belirlenmiştir. Özellikle eğitimde emoticonların yeri ve öneminin tam olarak aydınlatılmaması bu çalışmayı daha elzem kılmıştır. Öğrencilerin okul içinde ve dışında kullandıkları emoticonlara yönelik tutumları belirlemek amacıyla “Anlamlı Suratları (Emoticon) Kullanma Tutum Ölçeği” (ASK TO) geliştirildi. Konu alanı uzmanları ve ölçme değerlendirme uzmanlarının görüş ve önerileriyle tamamlanan ölçeğin pilot uygulaması elli öğrenci ile yapıldı. Bunun sonucunda gözden geçirilen ölçek ve eki, sekizinci sınıfta eğitim-öğretim gören 297 öğrenciye uygulandı. Toplanan veriler SPSS 17 istatistik programında analiz edilerek ölçeğin geçerlilik, güvenirlik ve faktör analizleri yapıldı. Yapılan güvenirlik analizi sonucunda ölçeğin Cronbach’s Alpha değeri (,844) olarak belirlenmiş olup; ölçeğin oldukça güvenilir olduğu saptandı. Faktör analizinde ise KMO (,872) ve Barlet testi (p= ,000) anlamlı bulunarak faktör homojenliğinin iyi olduğu belirlenmiştir. Araştırmanın sonunda öğrencilerin emoticonlarla ilgili tutumlarının olumlu olduğu belirlenmiştir. Bu bulgu sonucunda emoticonların eğitimde yararlı ve etkili bir araç olarak nasıl kullanılacağı önerilmiştir. Kastamonu Education Journal Hülya SÖNMEZa aMuş Alparslan Üniversitesi, Eğitim Fakültesi, Türkçe Eğitimi Bölümü, Muş, Türkiye Original Article Original Article Alıntı: Sönmez, H. (2018). Emoticonların iletişim aracı olarak kullanılmasına yönelik öğrenci tutumlarının incelenmesi. Kastamonu Education Journal, 26(4), 1081-1089. doi:10.24106/kefdergi.433434 Extended Abstract The present study examines children’s attitudes towards emoticons they frequently use both in verbal and written communi- cation to express their feelings and ideas. The literature survey shows that the place and importance of emoticons in education have not been explained completely and this fact makes the present study more essential. The present study seeks answers for the following questions: How are the students’ attitudes towards emoticons as a means for communication? Do students find emoticons they use for communication purposes useful? Is gender an important factor in the use of emoticons? In order to de- termine children’s attitudes and perceptions towards emoticons, participants were observed in their own conditions and without any intervention to their conditions or environments. Assessment was done under those circumstances. Thus the present study is a general survey model based on identifying students’ attitudes towards emoticons without changing the present status. The development, implementation, analysis and evaluation processes of the scale were based on quantitative research analyses. i We primarily asked for the field experts’ comments in order to develop the attitude scale for using emoticons. In accordance with those experts’ comments and recommendations, we identified where the emoticons used mostly in daily life and created a pool for scale items. We drafted a form of twenty-five items considering the environments where the emoticons are used by students most in daily life. At the end of the review by two experts in Assessment and Evaluation field and two expert in Turkish Education field, twelve items were found not fit for purpose and omitted from the draft. The scale was implemented on 297 students of 8th grade at Üsküdar Selami Ali Secondary School. 153 male and 144 female students took part in the study. At the end of the implementation, the validity, reliability and factor analyses of the scale were done. In accordance with the analyses, three items were omitted from the scale. The present scale consists of ten items. Data analyses show a Kaiser- Meyer- Olkin (K.M.O.) value of (,872) and the Barlet test is significant in a good level (p= ,000), thus the factors are eligible for analyzing. Finding a Kaiser-Meyer-Olkin value over 0.50 shows that sample size is “good” for factor analysis. Based on this result, it is possible to suggest that data have been acquired from a multivariate normal distribution and the relation between variables is sufficient to conduct factor analysis. Extended Abstract During the exploratory factor analysis conducted in order to determine the structural validity of the scale, before varimax rotation, it was found that the scale consisted of three sub-dimensions . Identified factors are as follows: The first factor (5 items) is “Willingness to use emoticons as a means for communication”; the second factor (6 items) is “Willingness to use emoticons in the future and the existence of emoticons in one’s living environment”. At the end of the analysis conducted through varimax rotation, the scale was rotated in two sub-dimensions. The first factor (5 items) is “Willingness to use emoticons as a means for communication”; the second factor (6 items) is “willingness to use emoticons in the future and the existence of the emoticons in one’s living environment”. We assessed the Cronbach’s Alpha value in order to identify the reliability of the scale. Cronbach’s Alpha value was found to be (,844), which shows that the items of the scale have a high level of correlation. Kaiser- Mey- er- Olkin (K.M.O.) value was found (,872) for the data from implementation and Barlet test was found significant (p= ,000). Therefore factor analysis is applicable. i The analyses revealed curious findings with respect to children’s attitudes towards using emoticons as a means for communi- cation. First of all, there is a high level of respond for all items by the participants, which suggests participants are interested in the issue. Another remarkable point is that children are affected by time factor with respect to using emoticons. Time perception is an important factor in children’s attitudes towards emoticons. While the level of respond to items about the use of emoticons in daily communication is high (items 1, 3, 8, 11), the level of respond to items about using them in the future is low (items 9, 14 and 22). Even though children have positive attitudes towards using emoticons, they have no intention to choose it as a profession or field of expertise in the future. The main reason for this is that children do not have sufficient information on this field. Due to this lack of information, children’s attitudes towards a certain environment where creative works are conducted or ideas produced on this field were found non-positive. It is understood that gender has an important role in the use of emoticons. Abstract The scale has been completed in accordance with the comments and recommendations by authorities in the field and by assessment and evaluation specialists. Then the pilot study was implemented on fifty students. At the end of the implementation, the scale and appendix were reviewed and implemented on 297 students of eighth grade. Data from the implementation were analyzed through SPSS 17 statistics program and the validity, reliability and factor analyses of the scale were done. The result of the analyses gave a Cronbach’s Alpha value of (,844), suggesting a high reliability for the scale. In the factor analysis, KMO value was found to be (,872) and the Barlett test was (p= ,000) found significant, suggesting that the factor has a good homogeneity. At the end of the research it was determined that the students’ attitudes towards emoticones were very positive. As a result of this finding it has been suggested that emoticons can be used as a useful tool in some areas of education. Geliş Tarihi: 26.12.2016 Yayına Kabul Tarihi: 21.11.2017 1082 Extended Abstract This case is in parallel with many studies conduct- ed on the subject (Hudson et al. 2015p. 88). This shows that gender has a decisive role in the use of emoticons because female students stated that they could express their feelings and ideas more easily through emoticons. Another remarkable point came out from the study is that female students are more stable in their attitudes towards emoticons than male students are. Female students chose phrases “I highly agree, I agree, I don’t agree at all” more than male students did, which underlines their stability in their attitudes. At the end of the study, we examined that it is possible to suggest that children have got a positive attitude towards using emoticons as a means for communication. Kastamonu Eğitim Dergisi Cilt: 26 Sayı: 4 1083 2. Yöntem Araştırmanın Modeli ve Çalışma Grubu 1. Giriş Yazının icadından önceki dönemlerde mesajları aktarmak için mağara duvarlarına kazılan figürler, günümüzde biraz değişse de hâlâ yaygın olarak kullanılmaktadır. Bu yaygın kullanım, figüratif bir anlaşma dili oluşturmuştur (Gürçayır, 2009: 112-14). Tek bir yüzle çok şeyin anlatıldığı bu figürler, İngilizcedeki duygu kelimesi “emotion” ile “icon” keli- mesinin bir araya gelmesiyle oluşmuştur. Bunlar; günlük dilde anlamlı yüzler, anlamlı suratlar, gülen yüzler, pictogram (smilies), ikon, stiker veya emoje olarak adlandırılmaktadır. Fahlman, internet ortamındaki yazışmalarda oluşan yanlış anlaşmaları ve iletişim karmaşasını engellemek için ilk olarak  ikonunu daha sonra ise  ikonunu kullanarak bunları iletişime sunmuştur. Aynı zamanda Mackenzie de yazılı iletişimdeki kuru ifadeleri yumuşatmak amacıyla bu suratları ilk kullananlardandır (Akt. Gürçayır, 2009: 113). Daha sonra yaygınlaşan bu ikonlar, teknolojinin farklı alanları ile tanışmıştır. Zamanla teknolojide sık kullanılan emoticonlar, duygusal zekâyı “emotional intelligence” (EQ) doğurmuş olup duygusal zekâ için oldukça önemli bir unsur hâline gelmiştir (Goleman, 2016). İletişim amaçlı kullanılan ikonlar, günümüzde oldukça önemli bir kullanım oranına sahipler. Ito ve Fujimoto (2013), emoticonların tam olarak hangi duyguyu karşıladığı, nasıl kullanıldığı ve bunların kullanılma sıklıkları gibi birçok yönlerini incelerken bunların sözsüz (non–verbal) iletişimdeki önemine dikkat çekerler. Fakat dikkat çekilmek istenen diğer bir husus ise sözsüz iletişimde kullanılan her şeyin emoticon olmadığıdır. Örneğin, iletişimde kullanılan semboller emoticanlardan farklıdır. Bu nedenle semboller ve emoticonların (ikon) birbirine karıştırılmaması gerekir. Çünkü ikon- lar, kişisel yorumlardan bağımsız tek başına bir anlam ifade etmektedir (Akt. Gürçayır, 2009: 112-114). Emoticonların sık kullanma nedeni, birçok cümle sarf ederek aktarılacak duygu ve düşüncenin tek bir suratla ifa- de edilmesiyle ilişkilendirilebilir. Diğer bir nedeni ise bunların eğlenceli birer iletişim aracı olmasıdır. Bu yönüyle çocukların birçok alışkanlıklarında emoticonların etkisi görülmektedir. Örneğin, ilkokul çağı çocuklarının sağlıklı bes- lenme alışkanlığı kazanmalarında emoticonların ciddi bir etkisinin olduğu tespit edilmiştir (Privitera, Phillips, Zuraikat ve Paque, 2015). Aynı zamanda emoticonlar, görünüşleri itibariyle gelişimin erken dönemlerinde fark edildiği için bun- ların amblyopia hastası çocukların tedavisinde olumlu sonuçlar doğurduğu belirlenmiştir (Oto, Pelit ve Aydın, 2002). Dört yaşındaki çocuklar; mutlu, üzgün, korkmuş ve sinirli suratlardaki anlam farklılıklarını anlayabilmektedir. Özellikle mutlu suratların bir iletişim türü olarak bazı mesajlar aktarmada diğerlerinden daha fazla oranda çocuklar üzerinde etkili olduğu görülmüştür (Visser, Alant ve Harty, 2008: 305). Bu eksende yapılan bu araştırmada ise emoti- conların eğitim-öğretim sürecinde kullanımı ile ilgili öğrenci tutumlarına bakılmıştır. Bu kapsamda tutumları ölçmek için geliştirilen ölçme aracı ve ulaşılan bulgularla ilgili sonuçlar aşağıda ayrıntısıyla verilmiştir. Araştırmanın Modeli ve Çalışma Grubu Araştırmada mevcut durum, kendi koşulları içinde ve olduğu gibi belirlenmeye çalışılmıştır. Dolayısıyla bu çalışma, mevcut durum değiştirilmeden öğrencilerin emoticon kullanmaya yönelik tutumlarını belirlemeye dayalı genel bir ta- rama modelidir (Karasar, 2013: 77). Çalışmada ölçek geliştirme, uygulama, analiz etme ve değerlendirme süreçlerinde nicel araştırma yöntemleri esas alınmıştır. Araştırmanın verileri, Üsküdar Selami Ali Ortaokulu sekizinci sınıftaki 144 kız ve 153 erkek katılımcıdan oluşan 297 öğrenciden toplanmıştır. Araştırmanın Amacı Çalışmanın amacı, eğitim-öğretim sürecinde kullanılan emoticonlara yönelik öğrencilerin duygu ve düşüncelerini belirlemektir. Bu amaç doğrultusunda çalışmada şu araştırma sorularına cevap aranmıştır: 1. Öğrencilerin emoticonları kullanmaya yönelik tutumları nasıl ölçülebilir? 1. Öğrencilerin emoticonları kullanmaya yönelik tutumları nasıl ölçülebilir? 1. Öğrencilerin emoticonları kullanmaya yönelik tutumları nasıl ölçülebilir? 2. Öğrenciler, emoticonların eğitim-öğretim sürecinde bir iletişim aracı olarak kullanılmasını nasıl karşılamaktadır? 2 Yöntem Birinci Araştırma Sorusu ile İlgili Bulgular Bu bölümde birinci araştırma sorusu “Öğrencilerin emoticonları kullanmaya yönelik tutumları nasıl ölçülebilir?” ile ilgili bulgulara yer verilmiştir. Yapılan analizlere göre şu sonuçlara ulaşılmıştır: Analizlerden elde edilen verilerin Kaiser- Meyer- Olkin (K.M.O.) değerinin (,872) ve Barlet testinin iyi düzeyde anlamlı (p= ,000) bulunmasından dolayı faktörlerin analizler için uygun olduğu be- lirlenmiştir (Büyüköztürk, 2008). Analizde Kaiser-Meyer-Olkin değerinin 0.50’den büyük çıkması örneklem büyüklüğünün faktör analizi için “iyi” düzeyde olduğunu göstermektedir (Çokluk, Şekercioğlu ve Büyüköztürk, 2012: 207). Bu sonuçtan hareketle, verilerin çok değişkenli normal dağılımdan geldiği ve değişkenler arasında faktör analizi yapmak için yeterli bir ilişkinin olduğu söylenebilir. Çizelge 1: Varimax döndürme kullanılarak yapılan faktör analizi sonuçları Ç g y p ç birinci faktör ikinci faktör 8. Birisiyle e-mail veya mesaj yoluyla yazışırken anlamlı suratları (sembolleri) çok sık kullanırım. ,789 3. Düşüncelerimi anlamlı suratlarla daha iyi ve kolay ifade edebiliyorum. ,778 1. Birisiyle yazışırken ,  gibi sembolleri kullanmak bana kolaylık sağlıyor. ,739 11. İletişimde kullandığımız anlamlı suratları (sembolleri) amaçlarına uygun buluyorum. ,700 18. Duygularımı anlamlı suratlarla (sembollerle) daha iyi ve kolay ifade edebiliyorum. ,651 ,415 14. Gelecekte anlamlı suratlardan (sembollerden) oluşan bir dünya alfabesinin olması beni mutlu eder. ,769 22. Yazı yazma derslerimde anlamlı suratların (sembollerin) daha fazla kullanılmasını istiyorum. ,720 9. Gelecekte anlamlı suratların (sembollerin) çizildiği ve basıldığı bir şirkette çalışmak isterim. ,700 23. Odamın duvarına veya çalışma masamda anlamlı suratların (semboller) olması beni mutlu eder. ,625 17. Bu güne kadar kullanılmayan anlamlı suratları (sembolleri) bulup bunu insanlarla paylaşmak istiyorum. ,625 Varimax döndürme kullanılarak yapılan analiz sonucunda ölçek iki faktörlü olmuştur. Birinci faktörde “iletişim aracı olarak emoticon kullanmaya isteklilik” beş maddenin, ikinci faktörde “emoticonları gelecekte kullanmaya isteklilik ve yaşanılan ortamda emoticonların kullanımı” ise altı maddenin ortak konularına odaklanmıştır. Varimax döndürme yapılmadan önce madde-toplam korelasyonları ve faktör yüklerine ilişkin şu sonuçlara varılmıştır: Maddeler, üç faktör altında toplanmıştır. Bazı maddeler, aldığı değer nedeniyle ölçekten çıkarılmıştır. Bu maddeler şu gerekçelerden dolayı ölçekten atılmıştır: Bunlardan ilki olan madde 4, birinci faktörde (,452) ve ikinci faktörde ise (,438) düzeyinde birbirine yakın değerler almasından dolayı ölçekten atılmıştır. Aynı şekilde madde 12’nin ikinci faktörde (,410) ve üçüncü fak- törde (,452 ) düzeyinde oldukça yakın oranda yük alması nedeniyle elenmiştir. Yapılan bu elemeler sonucunda üçüncü faktörde sadece madde 6’nın kalması nedeniyle üçüncü faktör iptal edilmiştir. Çizelge 1’de madde-ölçek korelasyonlarının (,415) ile (,789) arasında değiştiği görülüyor. Birinci Araştırma Sorusu ile İlgili Bulgular Bu değer aralığında değişen maddelerin birinci ve ikinci faktörlerden aldıkları yükler ile ilgili şu bulgulara ulaşılmıştır: Birinci faktörde yer alan 1, 3, 8, 11 ve 18. madde katılımcıların anlamlı yüzlere yönelik olumlu tutumlarını kapsamaktadır. İkinci faktörden yük alan 18, 14, 22, 9, 23 ve 17. maddede ise emoticonların gelecekte ve şu anki yaşam alanlarında kullanımı ile ilgili tutumların nasıl olduğuna yer verilmiştir. İkinci faktördeki bu maddelerle katılımcıların gelecekte emoticonları duygu ve düşüncelerini aktarmak için bir araç olarak nasıl algıladıkları (olumlu-olumsuz, yararlı-yararsız ve kullanışlı-kulla- nışsız) incelenmiştir. İki faktörden oluşan ölçeğin güvenirliliğini tespit etmek için Cronbach’s Alpha değeri incelenmiştir. Cronbach’s Alfa, ölçekteki maddelerin birbirleriyle ilişkilerinin hangi ölçüde iyi olup olmadığını belirlemeyi amaçlayan istatistiksel bir testtir. Bu amaç doğrultusunda yapılan incelemeye göre Cronbach’s Alpha değeri (,844) olarak çıkmıştır. Bu değer, ölçekteki maddelerin birbiriyle yüksek düzeyde ilişkili olduğunu gösteriyor (Büyüköztürk, 2010). Yapılan bu analizler sonucunda ölçek maddelerine verilen cevaplardan hareketle katılımcı tutumları değerlendirilmiştir. Bu değerlendirme- lere göre öğrencilerin emoticonları kullanımı ile ilgili tutumları aşağıda ayrıntılı olarak ele alınmıştır. Veri Toplama Aracının Geliştirilmesi ve Verilerin Analizi Emoticonları kullanmaya yönelik tutum ölçeğini geliştirmek amacıyla konu alanı uzman görüşlerine başvurulmuştur. Alınan görüş ve öneriler doğrultusunda emoticonların günlük hayatta en çok nerelerde kullanıldığı tespit edilmiştir. Böy- lece yirmi beş maddelik bir madde havuzu oluşturulmuştur. Ölçme ve Değerlendirme Bölümü ve Türkçe Eğitimi Bölü- münden ikişer öğretim elemanının yaptığı inceleme sonucunda araştırmanın amacına uygun olmadığı belirlenen on iki madde ölçekten atılmıştır. Kalan maddeler; “Kesinlikle katılmıyorum”, “Katılmıyorum”, “Kararsızım”, “Katılıyorum” ve “Tamamen katılıyorum” şeklinde 5’li likerte göre derecelendirilmiştir (De Vellis, 2014). Toplanan verilerin analizi SPSS 17 istatistik programıyla yapılarak ölçeğin geçerlilik, güvenirlik ve faktör analizleri tamamlanmıştır. Yapılan ana- Kastamonu Eğitim Dergisi Cilt: 26 Sayı: 4 1084 liz sonuçlarına göre ölçekten üç madde daha atılarak değerlendirmeler on maddeye göre yapılmıştır. Bu maddelerden hareketle elde edilen bulgular ve bunların yorumları aşağıda ayrıntısıyla verilmiştir. liz sonuçlarına göre ölçekten üç madde daha atılarak değerlendirmeler on maddeye göre yapılmıştır. Bu maddelerden hareketle elde edilen bulgular ve bunların yorumları aşağıda ayrıntısıyla verilmiştir. Bunlarla ilgili ulaşılan sonuçlar aşağıda verildiği gibidir. Bunlarla ilgili ulaşılan sonuçlar aşağıda verildiği gibidir. Grafik 1:Öğrencilerin katılımına göre madde ortalamalarının dağılımı Çalışmanın bu bölümünde, emoticonlarla ile ilgili tutum yönlerinin maddelere göre incelenmesi amaçlanmıştır. Bu amaç doğrultusunda Grafik 1’de dikkat çeken temel özellik, madde 3’ün “Düşüncelerimi anlamlı suratlarla daha iyi ve kolay ifade edebiliyorum.” katılımcılar tarafından yüksek oranda olumlu karşılanmasıdır. Bu madde ile katılımcılardan çoğunluğunun düşüncelerini anlamlı suratlarla daha iyi ve kolay ifade ettiğini düşündükleri belirlenmiştir. Benzer bir sonuç madde 1’de görülmektedir. Çünkü çoğunluk, birisiyle yazışırken  ve  gibi emoticonları kullanmanın onlara kolaylık sağladığını düşünüyor. Aynı şekilde çoğunluk, iletişimde kullanılan anlamlı suratları amaçlarına uygun bul- maktadır (madde 11). Bu üç madde amaç ve verdiği anlam itibariyle birbirini desteklemektedir. Çünkü katılımcılar, bu üç madde için daha çok “çok katılıyorum” ve “katılıyorum” seçeneklerini tercih etmişlerdir. Dolayısıyla katılımcı- lar, düşüncelerini daha kolayca ifade ettikleri emoticonları amaca uygun buldukları için bunların iletişimde kolaylık sağladığı fikrini de desteklemiştir. Bu sonuç; Huang, Yen ve Zhang’ın ortaokul çocuklarının emoticonları kullanmayı eğlenceli, faydalı ve bilgi bakımından zengin buldukları tespitleriyle de örtüşmektedir (2008: 471). Madde 8’de katılımcıların e-mail veya mesaj yoluyla emoticonları kullanmaya yönelik tutumları incelenmiştir. Grafikte olumlu seçeneklerin daha fazla bulunmasından dolayı katılımcıların e-mail veya mesaj yoluyla emoticonları kullanmayı genel olarak olumlu karşıladıkları görülmektedir. Madde 9’da, gelecekte emoticonların çizildiği ve basıldığı bir çizim şirketinde çalışmaya yönelik katılımcı tepkilerinin nasıl olduğu incelenmiştir. Verilen cevaplara bakıldığında katılımcıların gelecekte emoticonların çizilip basıldığı bir şirkette çalışma fikrine yüksek oranda katılmadıkları görül- mektedir. Bu belirgin durumun nedeni, emoticonların bu yönüyle fazla bilinmemesiyle ilişkilendirilebilir. Bir meslek alanı olarak emoticonlarla ilgili araştırmaların yeteri kadar yapılmamasından dolayı katılımcılar, bunu bir meslek olarak değerlendirememektedir. Madde 14’te gelecekte anlamlı suratlardan oluşan bir dünya alfabesi fikrinin katılımcılar tarafından nasıl karşılan- dığı incelenmiştir. Verilen yanıtlara bakıldığında katılımcıların çoğunlukla bu durumu olumlu karşılamadığı görülüyor. Bu durum, madde 9 ile yakın ilişkilidir. Çünkü emoticonlarla ilgili bilinmezlikler nedeniyle katılımcıların gelecekte emoticonlardan oluşacak uluslararası alfabe fikrine veya bunun bir meslek olarak tercih edilmesi düşüncesine olumsuz yaklaştığı görülüyor. Madde 17’de anlamlı suratları kullanmaya yönelik katılımcıların merak düzeyleri incelenmiştir. Bu durumu belirle- mek için katılımcılara bu güne kadar kullanılmayan emoticonları bulup; bunu insanlarla paylaşmak isteyip istemedikleri soruldu. Bu maddeye verilen yanıtlar oldukça dikkat çekicidir. Çünkü katılımcıların bu madde için sergilediği beş tutum düzeyi birbirine oldukça yakındır. Bu nedenle burada belirgin bir tutumun ön plana çıktığını söylemek güçtür. Belirgin bir tutumun olmamasının nedeni, emoticonların bir meslek veya hobi olarak değerlendirilmesine yönelik farkındalıkların düşüklüğü ile ilişkilendirilebilir. İkinci Araştırma Sorusuyla İlgili Bulgular Bu bölümde ikinci araştırma sorusu “Öğrenciler, emoticonların eğitim-öğretim sürecinde bir iletişim aracı olarak kullanılmasını nasıl karşılamaktadır?” ile ilgili bulgulara yer verilmiştir. Bu kapsamda ilk olarak katılımcıların bütün maddelere verdiği cevaplar incelenmiştir. Daha sonra ise cinsiyet faktörünün tutumlar üzerindeki etkisine bakılmıştır. Kastamonu Eğitim Dergisi Cilt: 26 Sayı: 4 1085 Bunlarla ilgili ulaşılan sonuçlar aşağıda verildiği gibidir. Bunlarla ilgili ulaşılan sonuçlar aşağıda verildiği gibidir. Düşüncelerini anlamlı suratlara daha kolay ifade ettiğini düşünen katılımcılar, bu durumun onlara yazışırken kolaylık sağladığına inanıyor. Dolayısıyla bu maddeler birbirini destekler niteliktedir. Aynı şekilde katılımcılar, günlük hayatta sıklıkla kullanılan anlamlı suratları amaçlarına uygun buldukları için bunları kullanmayı güvenli buluyor. Madde 8, 18 ve 23’e verilen cevaplar vasıtasıyla emoticonlar, günlük hayatta ve iletişimin farklı alan- larında duygu ve düşünceleri daha kolay şekilde ifade ettiği düşüncesini ön plana çıkarmaktadır. Buna ek olarak madde 17’ye gösterilen olumlu katılım, yeni emoticonların bulunması ve bunların iletişimde kullanılması gerektiği düşüncesini desteklemektedir. Grafik 2: Kız ve erkek katılımcıların ölçeğe katılım oranları Grafik 2: Kız ve erkek katılımcıların ölçeğe katılım oranları Bu bölümde, emoticonlara yönelik tutumların cinsiyet faktörüne göre farklılaşıp farklılaşmadığına bakılmıştır. Bu kapsamda Grafik 2’ye bakıldığında dikkat çeken temel özellik, her iki grupta da katılımın fazla olmasıdır. Bütün madde- lerde ortalamanın ikinin üzerinde olması nedeniyle ölçeğin hem kız hem de erkek katılımcılar tarafından yüksek oranda cevaplandığı görülüyor. Bunlardan madde 1, madde 3 ve madde 11 katılımın en fazla olduğu maddelerdir. Dolayısıy- la “Birisiyle yazışırken ,  gibi sembolleri kullanmak bana kolaylık sağlıyor.”, “Düşüncelerimi anlamlı suratlarla daha iyi ve kolay ifade edebiliyorum.” ve “İletişimde kullandığımız anlamlı suratları amaçlarına uygun buluyorum.” maddeleri katılımcılar tarafından oldukça yüksek bir oranda cevaplanmıştır. Bu üç maddeyi birbiriyle ilişkilendirerek değerlendirmek gerekir. Düşüncelerini anlamlı suratlara daha kolay ifade ettiğini düşünen katılımcılar, bu durumun onlara yazışırken kolaylık sağladığına inanıyor. Dolayısıyla bu maddeler birbirini destekler niteliktedir. Aynı şekilde katılımcılar, günlük hayatta sıklıkla kullanılan anlamlı suratları amaçlarına uygun buldukları için bunları kullanmayı güvenli buluyor. Madde 8, 18 ve 23’e verilen cevaplar vasıtasıyla emoticonlar, günlük hayatta ve iletişimin farklı alan- larında duygu ve düşünceleri daha kolay şekilde ifade ettiği düşüncesini ön plana çıkarmaktadır. Buna ek olarak madde 17’ye gösterilen olumlu katılım, yeni emoticonların bulunması ve bunların iletişimde kullanılması gerektiği düşüncesini desteklemektedir. Ölçekteki madde 9’a “Gelecekte anlamlı suratların çizildiği ve basıldığı bir çizim şirketinde çalışmak isterim.” ve madde 14’e “Gelecekte anlamlı suratlardan oluşan bir dünya alfabesinin olması beni mutlu eder.” katılımın az oldu- ğu görülüyor. Bu maddelerde katılımcıların gelecekte kendilerini anlamlı suratlarla ifade etmeye yönelik tutumlarının nasıl olduğuna bakılmıştır. Madde 9’a katılımın çok az olduğu gözlemleniyor. Bu durum, katılımcıların emoticonların gelecekte kullanımı ile ilgili duygu ve düşüncelerini tam olarak belirtemediklerini ve bu konu hakkında ilgilerinin az olduğunu gösteriyor. Bu duruma benzer bir sonuç madde 22’de tespit edilmiştir. Grafik 2’de kız öğrencilerin katılım ortalamalarının genel olarak erkek öğrencilerden daha yüksek olduğu görülüyor. Bunlarla ilgili ulaşılan sonuçlar aşağıda verildiği gibidir. Çünkü katılımcılar, yeteri kadar bilmediği bu alanı gelecekte meslek olarak seçme veya bu alanla ilgili bir alfabe oluşturma fikrine ilgi duymamışlardır. Aynı nedenden dolayı bu alanda yaratıcı bir ürün ortaya koyma veya ona yeni boyutlar katma fikrine de katılımcıların ilgili olmadığı görülüyor. Madde 18’de duyguları anlamlı suratlarla ifade etme ile ilgili tutumlar incelenmiştir. Grafikte bu madde ile ilgili tutumların farklılaştığı görülüyor. Çün- Kastamonu Eğitim Dergisi Cilt: 26 Sayı: 4 1086 kü bu madde, hem birinci faktörden hem de ikinci faktörden yük almıştır. Sonuçlara bakıldığında katılımcıların büyük çoğunluğu duygularını emoticonlarla ifade etme düşüncesini olumlu karşıladıkları görülmektedir. Bu sonuç, madde 3’de düşünceleri emoticonlarla kolay ifade etme fikrini de desteklemiştir. kü bu madde, hem birinci faktörden hem de ikinci faktörden yük almıştır. Sonuçlara bakıldığında katılımcıların büyük çoğunluğu duygularını emoticonlarla ifade etme düşüncesini olumlu karşıladıkları görülmektedir. Bu sonuç, madde 3’de düşünceleri emoticonlarla kolay ifade etme fikrini de desteklemiştir. Bu bölümde, emoticonların ders materyali olarak kullanılması durumunda öğrenci tutumlarının nasıl olacağının belirlenmesi amaçlanmıştır. Bu nedenle madde 22’de katılımcıların emoticonları Türkçe dersinde kullanmaları ile ilgili duygu ve düşünceleri ele alınmıştır. Bu durumu belirlemek amacıyla katılımcılara yazma derslerinde anlamlı suratları daha fazla kullanmak isteyip istemedikleri soruldu. Verilen yanıtlar incelendiğinde çoğunluğun, yazma dersinde an- lamlı suratları daha fazla kullanmaya istekli olmadıkları görülmüştür. Dolayısıyla katılımcılar, günlük hayatta duygu ve düşüncelerini anlamlı suratlarla daha kolay ifade edeceklerini düşünmesine rağmen bunun ders ortamında bir eğitim materyali olarak kullanılması fikrini olumlu karşılamamıştır. Ölçeğin son maddesi olan 23’te ise okul dışında ve sıkça yaşanılan alanlarda emoticonların bulunması ile ilgili tutumlar incelenmiştir. Böylece çok sık bulunan mekânlarda anlamlı suratların kullanılmasıyla ilgili yaklaşımların nasıl olduğu değerlendirilmiştir. Grafikte bazı katılımcılara göre odasında ve çalışma masasında emoticonların bulunması onları mutlu edecektir. Bu düşünceye rağmen katılımcılardan bazıları emoticonların sık yaşadıkları mekânlarda olması fikrine katılmamaktadır. Grafik 2: Kız ve erkek katılımcıların ölçeğe katılım oranları Bu bölümde, emoticonlara yönelik tutumların cinsiyet faktörüne göre farklılaşıp farklılaşmadığına bakılmıştır. Bu kapsamda Grafik 2’ye bakıldığında dikkat çeken temel özellik, her iki grupta da katılımın fazla olmasıdır. Bütün madde- lerde ortalamanın ikinin üzerinde olması nedeniyle ölçeğin hem kız hem de erkek katılımcılar tarafından yüksek oranda cevaplandığı görülüyor. Bunlardan madde 1, madde 3 ve madde 11 katılımın en fazla olduğu maddelerdir. Dolayısıy- la “Birisiyle yazışırken ,  gibi sembolleri kullanmak bana kolaylık sağlıyor.”, “Düşüncelerimi anlamlı suratlarla daha iyi ve kolay ifade edebiliyorum.” ve “İletişimde kullandığımız anlamlı suratları amaçlarına uygun buluyorum.” maddeleri katılımcılar tarafından oldukça yüksek bir oranda cevaplanmıştır. Bu üç maddeyi birbiriyle ilişkilendirerek değerlendirmek gerekir. Bunlarla ilgili ulaşılan sonuçlar aşağıda verildiği gibidir. Bazı maddeler için bu fark az olsa da ölçekte yer alan bütün maddelerde kızların katılım oranları, erkeklerden daha fazladır. Bundan hareketle kızların emoticonları kullanmayla ilgili tutumlarını erkeklere göre daha çok dile getirdikleri Kastamonu Eğitim Dergisi Cilt: 26 Sayı: 4 1087 söylenebilir. Kız ve erkek öğrenciler arasındaki bu katılım farkının (tutumun) rastlantısal olup olmadığını belirlemek için One-WAY ANOVA testi yapılmıştır. One-WAY ANOVA testindeki anlamlılık değerinin (,000) p<,005’ten küçük olması nedeniyle cinsiyet ile bu maddelerin katılımı arasında anlamlı bir ilişki olduğu belirlenmiştir. Bu durum, anlamlı suratları kullanmaya yönelik tutum ile cinsiyet değişkeni arasında güçlü ve anlamlı bir ilişkinin olduğunu göstermekte- dir. Bu bulgudan hareketle anlamlı suratların kullanmasında cinsiyetin belirleyici bir rolünün olduğu söylenebilir. Grafik 2A: Kız öğrencilerin emoticonları kullanma ile ilgili tutumları 4. Tartışma ve Sonuç Bu çalışma için yapılan literatür taraması sonucunda emoticonlarla ile ilgili yeteri kadar araştırmanın yapılmadığı belirlenmiştir. Hem yurt içinde hem de yurt dışında emoticonlarla ile ilgili araştırmalara daha geniş çapta yer verilerek bunların eğitim sürecinde daha etkili kullanım yolları bulunmalıdır. Böylece öğrencilerin okul içi ve okul dışındaki ortamlarda kendilerini ifade etmek için kullandığı emoticonlar, etkili bir eğitim-öğretim aracı olarak değerlendirilebilir. Bu çalışmada emoticonların eğitim-öğretimde duygu ve düşünceleri ifade etmek için bir iletişim aracı olarak kulla- nılması ile ilgili ortaokul öğrencilerinin tutumları incelenmiştir. Yapılan incelemeler sonucunda öğrencilerin emoticon- ları etkili bir iletişim aracı olarak karşıladığı görülmüştür. Bu bulgu, önceki araştırma sonuçlarını da desteklemektedir (Siegel ve diğerleri 2015; Skovholt & Kankaanranta, 2014: 793). Araştırmaya katılanların çoğu, ölçeği cevaplayarak emoticonlara yönelik olumlu veya olumsuz tepkilerini belirtmişlerdir. Araştırmada dikkat çekici bir nokta ise katılımcıların emoticonları kullanmaya yönelik zaman algıları- dır. Ulaşılan bulgular, katılımcıların emoticonlara yönelik tutumlarında zaman algısının önemli olduğunu belirtmiştir. Çünkü emoticonların günlük iletişimdeki kullanımı ile ilgili maddelere katılım fazla iken, bunların gelecekte kullanımı ile ilgili maddelere (madde 9, 14 ve 22) ise katılımın az olduğu tespit edilmiştir. Bu nedenle katılımcılar, emoticonları kullanmaya yönelik olumlu tutuma sahip olmasına rağmen gelecekte bunları bir meslek veya uzmanlık alanı olarak seçmeyi düşünmedikleri görülüyor. Bunun temel nedeni ise bu alanla ilgili yeteri kadar bilgiye sahip olmamalarıdır. Bu bilgi eksikliği, katılımcıların gelecekte bunları bir meslek veya uzmanlık alanı olarak kullanmaya yönelik ilgilerini ve farkındalıklarını olumsuz etkilemektedir. Bu eksende emoticonlara yönelik olumlu tutumların (yaratıcı çalışmaların ya- pıldığı veya fikirlerin üretildiği) olmadığı belirlenmiştir. Bu durumun temel nedeni, eğitim-öğretim sürecinde emoticon- lara yeteri kadar yer verilmemesiyle ilişkilendirilebilir (Halvorsen, 2012: 709). Oysaki eğitim-öğretim sürecindeki zor ve sıkıcı etkinlikler, emoticonlarla daha kolay ve eğlenceli bir hâle getirilebilir. Örneğin, Türkçe dersindeki dil bilgisi konuları veya okuma ve okuduğunu anlama becerilerinde emoticonlar eğlenceli bir öğrenme aracı olarak kullanılabilir. Aynı şekilde matematik, fen bilimleri ve diğer derslerdeki soyut konular, emoticonlarla somutlaştırılarak aktarılabilir. Benzer şekilde öğrencilerin okul içi ve okul dışında yapmayı sevmediği ödevlerin daha eğlenceli ve yaratıcı olması için emoticonlardan yararlanılabilir. Öğretmenler, öğrenci ürünlerini değerlendirirken emoticonları bir pekiştirme ara- cı olarak kullanabilecekleri gibi emoticonları diğer öğrenme araçlarıyla kullanarak daha yaratıcı bir öğrenme süreci tasarlayabilirler. Burada önerilenler dışında eğitim-öğretim sürecinin birçok alanında emoticonlar etkili bir araç olarak kullanılabi- lir. Fakat bu etkinliklerin amaca uygun ve başarılı olması için emoticonların işlevi, amacı, yaygınlığı ve etkilerinin iyi saptanması gerekir. Bunu belirlemek amacıyla farklı araştırmalara ihtiyaç vardır. Grafik 2A: Kız öğrencilerin emoticonları kullanma ile ilgili tutumları Wolf (2000), kız ve erkek öğrencilerin emoticonları kullanırken farklılaştığını gözlemlemiştir. Wolf ‘a göre daya- nışma, destek, idea gibi pozitif duygular veren emoticonlar erkekler tarafından daha fazla kullanılıyor. Yapılan bu araştırmada da kızlar ve erkek katılımcıların emoticonları kullanımı ile ilgili farklı tutumlara sahip oldukları belirlen- miştir. Çünkü grafiğe bakıldığında kız öğrencilerin genelde “katılıyorum” ve “çok katılıyorum” (Grafik 2A-2B) gibi olumlu yargılar içeren maddelere cevap verdiği görülmektedir. Aşağıdaki grafikle karşılaştırıldığında kız öğrencilerin olumlu yargılardaki cevaplama oranları erkek katılımcıların cevaplarından daha fazladır. Bu durum, kız öğrencilerin emoticonlara ilişkin tutumlarında daha olumlu olduğunu gösteriyor. Aynı zamanda yukarıdaki grafikte kızların emoti- conları kullanmaya yönelik tutumlarının genel olarak erkek öğrencilere göre daha kararlı olduğu görülmektedir. Grafik 2B: Erkek öğrencilerin emoticonları kullanma ile ilgili tutumları Grafik 2B: Erkek öğrencilerin emoticonları kullanma ile ilgili tutumları Kastamonu Eğitim Dergisi Cilt: 26 Sayı: 4 1088 Grafik 2B’de erkek öğrencilerin kız öğrencilerden daha fazla oranda olumsuz tutuma sahip olması Wolf’un (2000) bulgusuyla farklı niteliktedir. İki grafik karşılaştırıldığında erkek katılımcıların kız katılımcılardan genel olarak daha az oranda “çok katılıyorum” ve “katılıyorum” seçeneklerini kullandığı görülüyor. Bu bulgudan hareketle kız katılımcıların emoticonları kullanmaya yönelik olumlu tutumlarının daha yüksek olduğu tespiti bir kez daha belirginleşmiştir. Her iki grafikte de hem kız hem de erkek katılımcılar; birisiyle yazışırken ,  gibi anlamlı suratları kullanmanın onlara kolaylık sağladığını belirtmişlerdir (madde 1). Fakat grafiğe dikkatli bir şekilde bakıldığında kız öğrencilerin bu düşünceye daha güçlü bir şekilde katıldıkları görülüyor. Birisiyle e-mail veya mesaj yoluyla yazışırken anlamlı suratla- rın çok sık kullanılıp kullanılmadığı ile ilgili tutumların incelendiği madde 8’de kız öğrencilerin fazla oranda olumlu tu- tuma sahip olduğu, erkek öğrencilerin ise bu düşünceye az katıldıkları gözlemleniyor. Madde 11’de iletişimde kullanılan emoticonların amaçlarına uygun olup olmadığı yönünde katılımcıların tutumları değerlendirildiğinde kız öğrencilerden çoğunun bunları amaçlarına uygun buldukları görülüyor. Bu güne kadar kullanılmayan anlamlı suratları bulup bunu insanlarla paylaşma düşüncesine (madde 17) kız öğrenciler genelde olumlu yönde daha fazla ilgi göstermiştir. Yaşam alanlarında emoticonların kullanılması (madde 23) ile ilgili tutumlara bakıldığında ise kız katılımcıların çoğu, yaşadığı alanda anlamlı suratların olmasını olumlu karşılarken; erkek katılımcıların ise bu düşünceye çok katılmadığı ve olum- suz yaklaştığı görülüyor. Bu bulgudan hareketle sıkça yaşanılan ortamda emoticonların kullanılıp kullanılmamasında cinsiyetin önemli bir faktör olduğu söylenebilir. 4. Tartışma ve Sonuç Çünkü emoticonların farklı kullanım yollarını sunan araştırmalarla bilinmeyen birçok konu aydınlatılırsa emoticonlar, eğitim sürecinde etkili daha şekilde kullanılabilir. Yapılacak bu araştırmalarla emoticonlar ilerde severek yapılan bir meslek veya ilginç bir çalışma alanı olarak hem öğrencilerin hem de eğitim uzmanlarının ilgisini çekebilir. Grafik 2A ve 2B’de emoticonların kullanılmasında cinsiyetin önemli bir rol oynadığı görülmüştür. Bu durum, önceki Kastamonu Eğitim Dergisi Cilt: 26 Sayı: 4 1089 araştırma sonuçlarını desteklemektedir (Hudson, Nicolas, Howser, Lipsett, Robinson, Pope, Hobby ve Friedman, 2015: 88). Bu çalışmada kız öğrencilerin emoticonları erkek öğrencilerden daha fazla yararlı buldukları belirlenmiştir. Aynı zamanda kız katılımcıların duygu ve düşüncelerini emoticonlarla daha kolay ifade ettiklerini düşündükleri görül- mektedir. Çalışmada dikkati çeken bir diğer nokta ise kız öğrencilerin emoticonlara yönelik tutumlarında erkeklerden daha fazla kararlı olmasıdır. Çünkü kız öğrenciler, genellikle “çok katılıyorum”, “katılıyorum” ve “hiç katılmıyo- rum” gibi seçenekleri tercih etmişlerdir. Dolayısıyla kız öğrencilerin emoticonları kullanmayı yararlı veya yararsız buldukları ile ilgili tutumları daha nettir. Bu durum, eğitim-öğretim sürecinde zorluk yaşayan kız öğrencilerin lehine değerlendirilebilir. Örneğin, bireysel öğrenmenin ön planda olduğu öğretim etkinliklerinde öğrenme zorluğu yaşayan kız öğrenciler için emoticonlar eğlenceli ve kolay bir öğrenme aracı olarak kullanılabilir. Emoticonların eğitimde kullanılması sürecinde dikkat edilmesi gereken önemli hususlar vardır. Bunlardan ilki, emo- ticonların gereğinden fazla ve bilinçsizce kullanılması problemidir. Emoticonların çok sık kullanılması özellikle anlatma becerilerinde (konuşma ve yazma) olumsuz etkilere neden olabilir. Çünkü öğrencilerin duygu ve düşüncelerini sıklıkla konuşma veya yazma yerine emoticonlarla ifade etmesi onların kelime dağarcığını olumsuz etkileyebilir. Burada dikkat edilmesi gereken temel özellik emoticonların hangi amaçla, kimler tarafından ve ne kadar kullanılması gerektiğinin iyi saptanmasıdır. Emoticonların öğrencilerin anlama ve anlatma becerilerindeki kullanım amacı ve sınırlarının iyi tespit edilmesi gerekir. Aksi takdirde bu yoğun kullanım öğrencilerin anlama ve anlatma becerileri üzerinde olumsuz sonuçlar doğurabilir. Örneğin öğretmen, utangaç bir öğrencinin derse katılımını sağlamak ve bunu pekiştirmek için emoticon- lardan yararlanabilir. Ama bu öğrenciden kendini sıklıkla emoticonlarla ifade etmesini beklemek başta kelime dağarcığı olmak üzere birçok yönden öğrencinin dil ve sosyal gelişimini olumsuz etkileyebilir. Aynı zamanda bu yoğun kullanım, zamanla öğrencinin ilgisini çekmeyeceği gibi öğrenme ihtiyacını da karşılayamayabilir. Sonuç olarak öğrencilerin emo- ticonları kullanmayı sevmelerine rağmen eğitimin her aşamasında bunların plansız ve orantısız şekilde kullanmasının engellenmesi gerekir. Emoticonlar, diğer araştırma alanlarında da etkili bir ölçme aracı olarak kullanılabilir. Teknoloji çağı ile yaygınlaşan ve toplumdaki çoğu kişi tarafından tercih edilen emoticonların kullanım amacı ve sıklığı birçok araştırmacıya sosyal bilimlerde yardımcı olabilir. 4. Tartışma ve Sonuç Örneğin, bir toplumun gelişmişlik ve refah düzeyi ile o toplumun mutlu veya mutsuz olma durumu arasındaki ilişkiyi belirlemek için emoticonlara başvurulabilir. Çünkü toplumdaki bireylerin iletişim sürecinde kullandığı emoticonların türü toplumun mutlu veya mutsuz olma durumunun göstergesi olabilir. 5. Kaynakça Büyüköztürk, Ş. (2008). Bilimsel araştırma yöntemleri. Ankara: Pegem Akademi. Çokluk, Ö., Şekercioğlu, G. ve Büyüköztürk, Ş. (2012). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LİSREL uygulamaları. Ankara: Pegem Akademi. De Vellis, R. F. (2014). Ölçek geliştirme kuram ve uygulamalar (Çev. Edt. Tarık Totan). Ankara: Nobel Yayıncılık. Goleman, D. (2016). Duygusal zekâ EQ neden IQ’dan daha önemlidir? (Çev. Banu Seçkin Yüksel) İstanbul: Varlık rçayır, S. (2009). “İnternet çağının hiyeroglifleri” ya da evrenselleşen sanal bedenler: MSN ifadeleri. Millî Folklor, 8 l orsen A (2012) Patterns of emoticon sage in ESL st dents’ disc ssion for m riting CALICO J l 29 (4) 6 Gürçayır, S. (2009). “İnternet çağının hiyeroglifleri” ya da evrenselleşen sanal bedenler: MSN ifadeleri. Millî Folklor, 83, 111-15. Halvorsen, A. (2012). Patterns of emoticon usage in ESL students’ discussion forum writing. CALICO Journal, 29 (4), 694-717. Halvorsen, A. (2012). Patterns of emoticon usage in ESL students’ discussion forum writing. CALICO Journal, 29 (4), 694-717. Huang, A. H., Yen D. C. & Zhang, X. (2008). Exploring the potential effects of emoticons. Information & Manage n D. C. & Zhang, X. (2008). Exploring the potential effects of emoticons. Information & Management, 45, 466-473 Hudson, M. B., B. A, S Nicolas, S. C., Howser, M. E., Lipsett, K. E., Robinson, W., Pope, L. J., Hobby, A. F. & Friedman, D. R. (2015). Examining how gender and emoticons influence facebook jealousy. Cyberpsychology, Behavior And Social Networking, 18. Ito, E. & Fujimoto, T. (2013). A proposal of intuitive and immediate emoticons system to do non-verbal communication with smartphones, 2013 4th International Conference on Intelligent Systems, Modelling and Simulation, 335-339. Karasar, N. (2013). Bilimsel araştırma yöntemleri. Ankara: Noben Yayıncılık. Karasar, N. (2013). Bilimsel araştırma yöntemleri. Ankara: Noben Yayıncılık.f dın, A. (2002). Non-concordance in amblyopia treatment: the effective use of ‘smileys’. Strabismus, 10, 23– Oto, S. Pelit, P. & Aydın, A. (2002). Non-concordance in amblyopia treatment: the effective use of ‘smileys Privitera, J. G., Phillips, T. E., Zuraikat, F. M. & Paque, R. (2015). Research report: Emolabeling increases healthy food choices among grade school children in a structured grocery aisle setting, Appetite, 92,  173-177. f Siegel, R. M., Anneken, A., Duffy, C., Simmons, K., Hudgens, M., Lockhart, M. K. & Shelly, J. (2015). Emoticon use increases plain milk and vegetable purchase in a school cafeteria without adversely affecting total milk purchase. Clinical Therapeutics, 37, 1938-1943. Skovholt, K. & Kankaanranta, A. (2014). Çokluk, Ö., Şekercioğlu, G. ve Büyüköztürk, Ş. (2012). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LİSREL uygulamaları. Ankara: Pegem Akademi. 5. Kaynakça The communicative functions of emoticons in workplace e-ma puter-Mediated Communication, 19, 780-797. nranta, A. (2014). The communicative functions of emoticons in workplace e-mails: :-). Journal of Com- mmunication, 19, 780-797. Visser N., Alant, E. & Harty, M. (2008). Which graphic symbols do 4-year-old children choose to represent each of the four basic emotions? Augmentative and Alternative Communication, 24 (4), 302-312. f Wolf, A. (2000). Emotional expression online: gender differences in emoticon use. Cyberpsychology & Behavior, 3 (59), 827-33. Kastamonu Eğitim Dergisi Cilt: 26 Sayı: 4 Kastamonu Eğitim Dergisi Cilt: 26 Sayı: 4
https://openalex.org/W4289713925
http://old.scielo.br/pdf/bioet/v30n2/en_1983-8042-bioet-30-02-0337.pdf
English
null
Discussões sobre bioética, direito penal e pacientes testemunhas de Jeová
Revista Bioética
2,022
cc-by
6,416
Revista Bioética Print version ISSN 1983-8042 | On-line version ISSN 1983-8034 Revista Bioética Print version ISSN 1983-8042 | On-line version ISSN 1983-8034 Rev. Bioét. vol.30 no.2 Brasília Apr./Jun. 2022 Rev. Bioét. vol.30 no.2 Brasília Apr./Jun. 2022 Discussions on bioethics, criminal law, and Jehovah’s witness patients Nathalia da Fonseca Campos 1, Leonardo Bocchi Costa 2 Nathalia da Fonseca Campos 1, Leonardo Bocchi Costa 2 1. Pontifícia Universidade Católica do Paraná, Londrina/PR, Brasil. 2. Universidade Estadual do Norte do Paraná, Jacarezinho/PR, Brasil. Abstract This study aims to reflect on the bioethical and juridical aspects tied to the doctor-Jehovah’s Witness patient relationship. To that end, the work will focus, initially, on the doctor-patient relationship faced with the therapeutic obstacles of this group of patients, studying the relationship from the historical standpoint and elucidating the topics about the patients of this religion. Then, we will focus on the bioethical principles involved in the care for Jehovah’s Witness patients, discussing each principle and its incorporation to the care for this group. Finally, we will focus on the juridical approach in the light of the patient’s fundamental rights, characterizing the constitutional and criminal norms that apply to the care of health professionals to patients of this religion. Keywords: Personal autonomy. Bioethics. Paternalism. Physician-patient relations. Religion. Discussões sobre bioética, direito penal e pacientes testemunhas de Jeováilii i , p p Este estudo tem como finalidade refletir sobre os aspectos bioéticos e jurídicos implicados na rela- ção médico-paciente testemunha de Jeová. Para isso, o trabalho abordará, inicialmente, a relação médico-paciente diante dos impasses terapêuticos desse grupo de pacientes, estudando essa relação do ponto de vista histórico e elucidando os pontos acerca dos pacientes adeptos à religião. Em seguida, abordar-se-ão os princípios bioéticos envolvidos no cuidado do paciente testemunha de Jeová, discutindo cada princípio e sua incorporação ao atendimento desse grupo. Por fim, será discutida a abordagem jurídica à luz dos direitos fundamentais do paciente, caracterizando as normas constitucio- nais e penais que se aplicam ao cuidado dos profissionais de saúde a pacientes adeptos a essa religião. Palavras-chave: Autonomia pessoal. Bioética. Paternalismo. Relação médico-paciente. Religião. Debates sobre bioética, derecho penal y pacientes testigos de Jehováiili ii Este estudio tiene como objetivo reflexionar sobre los aspectos bioéticos y legales involucrados en la relación médico-paciente de los testigos de Jehová. Para ello, se abordará inicialmente la relación médico-paciente ante los impasses terapéuticos de este grupo de pacientes desde la perspectiva his- tórica teniendo en cuenta a los pacientes practicantes de esta religión. Luego, se plantearán los prin- cipios bioéticos involucrados en el cuidado del paciente testigo de Jehová, discutiendo cada principio y su incorporación en la asistencia a este grupo. Por último, se discutirá el enfoque jurídico a la luz de los derechos fundamentales del paciente, caracterizando las normas constitucionales y penales que se aplican a la asistencia de los profesionales de la salud a los pacientes practicantes de esta religión. Palabras clave: Autonomía Personal. Bioética. Paternalismo. Relaciones médico-paciente. Religión. Palabras clave: Autonomía Personal. Bioética. Paternalismo. Relaciones médico-paciente. Religión The authors declare no conflict of interest. The authors declare no conflict of interest. http://dx.doi.org/10.1590/1983-80422022302529EN Rev. bioét. (Impr.). 2022; 30 (2): 337-45 337 Discussions on bioethics, criminal law, and Jehovah’s witness patients Known for preaching testimonies from house to house, Jehovah’s witnesses (JW) correspond to a religious group that began in 1869, being initially a group of biblical studies, which later evolved into an extensive religious community. Its members must fulfill requirements as a form of commitment and fidelity to the kingdom of God, the best known being: avoid any type of civil interest, such as taking part in political parties and military service; and not undergo blood transfusion 1. With all the peculiarities, JW are part of the users of health services, and therefore it is necessary to establish essential and unique care for these patients, and the health service must be prepared to welcome and care for them, respecting their autonomy.i provision by its holder. Thus, if a patient expressly disposes of his or her right to life for the sake of his or her right to religious freedom, the physician or health professional who acts in collusion with such a will (by both commission acts and omission acts) would not be exempt from legal sanctions, especially criminal ones, since the consent of the offended person (the patient) is irrelevant when it comes to unalienable rights, such as the right to life. Therefore, from a legal point of view, the doctor has the duty to respect the autonomy and religious freedom of the patient, while having the duty to take care of the patient’s life, under penalty of criminal liability. Undoubtedly, this is a complex and peculiar situation, which inspires further discussions to clarify the limits of the doctor’s or health professional’s work when caring for a Jehovah’s witness patient. Within the scope of medical practice, JW are considered a group that requires singular attention. This religious community has as an important foundation the position against treatments that involve blood transfusion, based on biblical writings present in the books of Genesis, Leviticus, and Acts, according to which receiving blood results in eternal damnation, as highlighted by Chehaibar 1. For them, transfusion transforms them into polluted beings, allowing the community to implement punishments that may involve suspension of religious privileges, public censure, and disassociation, in which friends and family must avoid them 1. http://dx.doi.org/10.1590/1983-80422022302529EN Given the personal and professional impact of the JW patient’s therapy, this study seeks to correlate the bioethical and legal aspects with the relationship between physician and Jehovah’s witness patient, bringing, to that end, a discussion about the bioethical principles and the physician- patient relationship before therapeutic impasses, in addition to a legal approach in the light of the fundamental rights of the patient, with emphasis on the constitutional and criminal norms that apply to the therapeutic or surgical intervention of doctors and health professionals on patients adhering to this religious community. In this scenario, bioethics serves as the basis for supporting the physician-patient relationship before this difficult situation. It brings with it principles defined as bioethical trinity, formed by autonomy, beneficence, and justice 2, in addition to proposals to be followed in this bond, always valuing a democratic and deliberative relationship, counting on the participation not only of the professional, but of all those involved in this bond, to choose the best intervention alternative. Since this is a qualitative and descriptive study, the deductive approach method was used to seek to prove its hypothesis. To that end, we carried out a review of the narrative literature via a bibliographic search in databases and a targeted search, mainly related to the legal doctrinal content and the Brazilian legal system. Research Research In addition to this, in the legal perspective, these patients have fundamental rights, which must be considered and observed by the doctor, since the The Federal Constitution of 1988 guarantees to all individuals the right to religious freedom, also bringing in the caput of its 5th article a general clause of freedom, which covers the private autonomy of individuals and, therefore, aspects inherent to the dignity of the human person 3. Relationship between physician and Jehovah’s witness patient Medicine and the physician-patient relationship have experienced periods of different characteristics regarding the interaction between the professional and patient poles. Initially qualified as paternalistic, the physician-patient relationship was based on the asymmetry between professional and patient, On the other hand, one must consider that the right to life is an unalienable fundamental right and therefore cannot be the object of Rev. bioét. (Impr.). 2022; 30 (2): 337-45 http://dx.doi.org/10.1590/1983-80422022302529EN 338 Discussions on bioethics, criminal law, and Jehovah’s witness patients based on the technical knowledge with which the doctor was endowed. It was understood that patients, being lay people, were not able to understand their health problems and, therefore, were not prepared to decide the best therapeutic option for themselves, assigning the technical autonomy to the doctor 4,5. This paternalistic conception has gained foundation in numerous moments of history, among them, the conception of the Hippocratic Oath, which did not bring the sharing of the decision with the patient in their recommendations, in addition to the medieval periods, in which the medical figure began to be associated with a priestly ethics, whose authority was of divine origin 4. after clarifying them about the procedure to be performed, except in case of imminent risk of death (art. 22), as well as failing to ensure the patient the exercise of the right to freely decide on their person or well-being, as well as to exercise their authority to limit it (art. 24) 7. Thus, CEM establishes the duty of the physician to clarify the procedures and respect the patient’s decision regarding the available options.ii Therefore, in the relationship with a JW patient, the professional must have as a basis a deliberative position, offering the best options to the patient and accepting what is declared as their will, using the FIC as a tool. Faced with a patient with a clear capacity for understanding and decision-making and who does not present an imminent risk of death, the doctor should never violate their religious principles and, knowing that the philosophy of JW goes against blood transfusion therapies, the medical team should respect the autonomy and religious freedom of the patient, as well as their right to a dignified life, using alternative therapies to meet their needs. On the other hand, in cases of imminent risk of death, there is the exception brought by art. Bioethical principles Bioethical principles It was only in the 20th century that the tendency to establish a horizontal physician- patient relationship emerged, in an attempt to abandon the asymmetries between the poles that promoted the verticalization of the relationship. At this stage, we began to value the joint decision involving all parties present in this bond, with the health professional and their team having the responsibility of clarifying all the therapeutic components to be performed, and the patient having the choice to confront the options and declare their wishes. Therefore, consent is no longer informed and starts to be called free and informed consent, counting on the activity of the two poles of the relationship 6. Relationship between physician and Jehovah’s witness patient 22 of CEM 7, and the doctor can value the preservation of life and apply transfusion therapy without the patient’s consent. From 1945 onward and the publication of Universal Declaration of Human Rights, it was possible to observe a change in the panorama of the physician-patient relationship, with the inclusion of the rights and freedoms of choice of the patient, promoting an inversion of happened previously 6. That is, the doctor attributed to patients the choice about their treatment, even if they did not present themselves in adequate conditions for such a decision. This phase of focus on the patient also included the informed consent form, an instrument that is associated with respect to the patient’s autonomy, but also with the rhetoric of freedom of choice and consumption 4,6. Care for the Jehovah’s witness patient In view of the technological advances involving the biological sciences, bioethics has come to ensure the responsible integration between life and biotechnology, considering the moral, social, and scientific dilemmas that arise in the midst of these associations. Bioethics is presented in the form of three principles, also called the bioethical trinity: autonomy, beneficence, and justice 1,2. These are not regulatory, but serve as guidance for the reflection of professionals in their technical and scientific performance 2. The principle of autonomy corresponds to respect and the right to self-government 2,5, that is, the right of patients to decide on their care, treatment, and everything that concerns their body 2. The health professional and their team have the duty to respect the will of the patient or their legal representative, and must also respect their moral values and beliefs 8. Currently, the establishment of a deliberative and democratic position in medical practice is based, among several documents, on the Code of Medical Ethics (CEM), when it states that it is forbidden for the doctor (...) to fail to obtain consent from the patient or their legal representative Rev. bioét. (Impr.). 2022; 30 (2): 337-45 http://dx.doi.org/10.1590/1983-80422022302529EN 339 Discussions on bioethics, criminal law, and Jehovah’s witness patients equality, and balance of human relations, aiming at the equality of right to health services 2, by offering to each patient what presents itself as morally right, adequate, and ethically due 1. Justice can be seen from different perspectives, and they can be utilitarian, liberal, egalitarian, or communitarian, allowing medical conducts and procedures not to be exempt from questions about the application of justice 1. However, the reception and the construction of a good physician-patient relationship, based on bioethical principles and always valuing the practice of patient autonomy, will allow justice to be achieved, since professionals will guarantee singular care according to the singularities of each patient, whether they are JW or not. That is, faced with the reality of the treatment of a JW patient, it is up to the health professional to provide an integral and adequate reception of the patient, identifying their wishes, values, and particularities, so that the best therapeutic conduct is offered, consistent with the patient’s wishes. Blood transfusion in Jehovah’s witness patients Blood transfusion in Jehovah’s witness patients Blood transfusion in Jehovah’s witness patients After a bioethical approach to the situations in which blood transfusion is necessary in JW patients, one should then proceed to a legal analysis of such a situation, to investigate the hypotheses in which, in addition to acting in violation of bioethical principles, the doctor or health professional also violates Brazilian legal norms. To that end, this study will address the context of blood transfusion in JW patients in light of the fundamental rights presented in the Federal Constitution 3, without loss to the assessment of possible criminal liability to the doctor who forcibly submits the patient to blood transfusion, so as to deny them the autonomy inherent in the physician-patient relationship today. The principle of beneficence has as its main focus to maximize the good of the other 2. This principle guided the medical professional activity for years, founding Hippocratic ethics, being connected to another principle, that of non-maleficence, and both proved to be inseparable, since they constantly seek to obtain maximum benefits and minimum harms. Thus, according to these principles, health professionals should always evaluate the risks and benefits of their practices, exposing them to users of health services, so that they make the best choice considering the risk-benefit ratio. Beneficence and non-maleficence should always be integrated with other bioethical principles, aiming at the non-use of beneficence in a paternalistic way, as occurred in past periods. That is, it is up to the doctor to technically evaluate the disease and analyze the best steps to be taken to solve the problem, based on beneficence and non-maleficence. From this, the patient and the family should be made aware of all the content that involves the options of choice, so that, among the best possibilities, the patient chooses the one that best matches their values. First of all, it should be borne in mind that the conduct of the JW patient, who refuses medical treatment for religious reasons, has constitutional protection. This is because the Federal Constitution of 1988 enforces, in its article 5, V, the fundamental right to freedom of belief, according to which freedom of conscience and belief is inviolable, the free exercise of religious worship is guaranteed, and the protection of places of worship and their liturgies is ensured in the form of law 3. Care for the Jehovah’s witness patient It is worth mentioning that, in this context, autonomy is present from the moment the professional fully and adequately explains to the patient and their families all the procedures to be performed, respecting the educational level of the patient and informing them with appropriate language. This is because, to make an adequate decision, the patient must fully understand the techniques, risks, complications, and alternatives, and it is up to the professional to enable them to deliberate and make their choices independently. It is in this context that the FIC stands out, which should always be used for the benefit of the patient and the professional, ensuring the autonomy of the physician-patient relationship 5,9. Blood transfusion in Jehovah’s witness patients The third principle, that of justice, can be defined by the phrase “we must treat equally the equal and unequally the unequal” 1, that is, the principle of justice is aimed at equity. It is based on freedom, Therefore, the Constitution explicitly recognizes religious freedom, protecting the right to adhere or not to any transcendental faith and positively Rev. bioét. (Impr.). 2022; 30 (2): 337-45 340 http://dx.doi.org/10.1590/1983-80422022302529EN Discussions on bioethics, criminal law, and Jehovah’s witness patients welcoming the plurality of religious expressions in its constitutional system 10. It should be noted that the refusal of blood transfusion by JW patients is understood as part of their dogmas and doctrines, thus belonging to the exercise of their religious faith. It should be pointed out, therefore, that the right to health concerns not only the physical well- being of the individual, but also their mental and emotional balance. That is, the patient should not be understood by the doctor as a simply physical being, but rather as a complex existence, which includes physical, emotional, social, and spiritual aspects. If, on the one hand, the right to health of the individual is shown to be at risk by the fact that they deprive themselves of adequate treatment due to their religious convictions, there would be a violation of this fundamental right if the doctor unjustifiably imposed medical treatment on the individual, violating, in such a way, their mental well-being by subjecting them to treatment that affronts the teachings of their religion. In addition, the patient who refuses blood transfusion has at their side the principle of private autonomy, directly related to the bioethical principle of autonomy and considered the ethical element of the dignity of the human person. Such a principle is considered the foundation of the free will of individuals, which allows them to seek, in their own way, the ideal of living well and having a good life 11. Because it is considered one of the elements of the principle of the dignity of the human person, private autonomy is present in the Federal Constitution of 1988, being established, in its article 1, III, as one of the fundamental principles of the Democratic State of Brazilian Law 3. Blood transfusion in Jehovah’s witness patients In this sense, private autonomy expresses individual self- determination and results from the recognition of human beings as moral agents, capable of deciding what is good or bad for themselves, and with the right to follow their decision, as long as it does not violate the rights of others 12. It should be borne in mind, given the above, that the fundamental right to health does not only give rise to the interpretation that there is an imposition on state entities in the sense of observing the right to health of individuals, whether in the defensive or service aspect. This is because the constitutional provision that concerns the right to health imposes on individuals themselves, in their horizontal relationships, the duty to respect the right to health of their equivalents, in order to guarantee the observance of the so-called horizontal effectiveness of fundamental rights 15. Finally, private autonomy is related to the personal responsibility that each person has over their life, which includes making and executing final decisions that involve what type of life would be good to live 13. It is understood that, in addition to not being able to violate the rights of others, private autonomy finds limits in unalienable rights, such as life. There is no question of private autonomy when a person asks the doctor for a lethal injection to end their own life. The inalienability of the right must therefore be considered a limit to this principle. Concerning the right to life, the caput of article 5 of the Federal Constitution of 1988 3 advocates that the right to life will be considered inviolable, and that this will be guaranteed to Brazilians and foreigners residing in the country. It can be stated that the right to life consists in the right to be alive, to fight for living, to remain alive. Without loss, it is the right not to have the vital process interrupted, but by spontaneous and inevitable death 16. In Brazil, the right to life is an unalienable fundamental right, that is, if a JW patient authorizes the doctor to take their life so that they do not have to undergo a blood transfusion, for example, even then this would be an illicit fact, since the consent of the victim cannot be valid in this case, because it is a right that cannot be provided by its holder. Blood transfusion in Jehovah’s witness patients However, it should be understood that the principle of proportionality, developed by German jurisprudence and externalized in a rationally defined structure, with independent subelements, namely, analysis of adequacy, necessity, and proportionality in the strict sense 17, should only be applied when the restriction to a fundamental right is conveyed in the form of a rule present in an infra-constitutional normative text 18, so that the constitutionality of the infra- constitutional restrictive norm of fundamental rights is analyzed by analysis of its proportionality. The penal legislator, however, excludes, in paragraph 3, I, of the article 19 analyzed, the typicality of the conduct of the intervening doctor or surgeon, without the consent of the patient or their legal representative, if the intervention is justified by imminent danger to life. Because it is provided for in the very device that provides for typified conduct, this is a legitimate legal cause for exclusion of typicality. Despite this, there are cases in which there is no constitutional or infra-constitutional rule that disciplines the collision between fundamental rights. That is, it may be that a given collision situation has not yet been the subject of consideration by the legislator. In these cases, the application of the principle of proportionality is not appropriate, and one must adopt the technique of weighing between the potential principles applicable in the solution of the specific case 18. Nevertheless, the exclusion addressed can be clearly justified by one of the four exclusionaries of wrongfulness: the state of necessity. Article 24 of the Brazilian Penal Code provides: one is considered to be in a state of necessity the one who practices the fact to save from actual danger, which they did not provoke by their will, nor could they otherwise avoid, their own or someone else’s right, whose sacrifice, in the circumstances, it was unreasonable to demand 19. In this sense, the state of necessity is characterized by the collision of legal goods of different values, with one of them having to be sacrificed for the sake of the preservation of the one who is reputed to be most valuable. Blood transfusion in Jehovah’s witness patients On the other hand, the conduct of rejecting blood transfusion can endanger two fundamental rights of extreme importance in the Democratic State of Brazilian law: the right to health and the right to life. The right to health urges the State to fulfill the demands that can provide citizens with a life without any compromise that affects their physical or mental balance. Thus, it can be said that its extent of incidence is very wide, since it encompasses all measures that protect the integrity of the human person 14. In this context, there is a clear situation of collision of fundamental rights, since, if a Jehovah’s witness individual decides to exercise their private http://dx.doi.org/10.1590/1983-80422022302529EN Rev. bioét. (Impr.). 2022; 30 (2): 337-45 341 Discussions on bioethics, criminal law, and Jehovah’s witness patients the health professional, even if such an attitude contradicts the prescription given by the physician based on the diagnosis. The patient’s will may be waived only in case of imminent risk of death, when the fundamental right to life shall prevail over the patient’s religious freedom. autonomy, preventing the health professional from submitting them to a blood transfusion, to guarantee the exercise of their religious freedom, their right to health and even their right to life may be impaired. Such a conflict situation must be solved by adopting the criterion of proportionality or by weighing the values involved.i Despite not having legal scope, the provisions contained in the CEM 7 are indirectly present in other legal acts. Art. 22 of CEM finds correspondence in art. 146 of the Criminal Code 19, which typifies unlawful constraint, that is, compelling someone, by violence or grave threat, or after having reduced, by any other means, their capacity to resist, not to do what the law allows, or to do what it does not command 19. It is very common to mention the principle of proportionality as a criterion intrinsic to the weighting of fundamental rights or even as a synonym for it. Blood transfusion in Jehovah’s witness patients (…) With this configuration, the delimitation of the state of necessity and the required safeguard conduct is usually done by the criterion of weighting of goods 20.ii The Federal Council of Medicine (CFM), a regulatory agency for the practice of Medicine in Brazil, ends up indirectly disciplining the attitude to be taken by the physician in the occasion of collision of rights, even if such provisions do not have legal scope, since it entails only physicians, and its infringement would generate only administrative responsibility to the offender. In this sense, as previously seen, the art. 22 of CEM 7, prohibits the doctor from not obtaining consent from the patient or their legal representative after clarifying to them the procedure to be performed, except in case of imminent risk of death. Research Such a situation fits perfectly with the conduct of the physician who intervenes on the patient without their consent in case of imminent risk of death, since they practiced the fact to save from actual danger (death), which they did not cause by their will (the disease arises from natural causes, and not from the doctor’s action) nor could they otherwise avoid, a right of others whose sacrifice was not Therefore, the expected conduct of a physician is that the will of the patient, in a horizontal physician-patient relationship, is respected by Rev. bioét. (Impr.). 2022; 30 (2): 337-45 http://dx.doi.org/10.1590/1983-80422022302529EN 342 Discussions on bioethics, criminal law, and Jehovah’s witness patients reasonable to demand (that is, the patient’s life). Note, however, the passage in which the legislator provides that the agent could not otherwise avoid the present danger. That is, if there is a way to avoid the death of a patient who authorized it, the physician must try to execute it, and not choose a non-consensual intervention, under penalty of removing the incidence from the state of necessity and, thus, from the exclusion of typicality of art. 146, § 3, I, of the Criminal Code 19. including pharmaceutical one, is included in the scope of the Brazilian Unified Health System (SUS). In addition, art. 19-M of the same legal act specifies comprehensive therapeutic care in dispensing of medicines and products of interest to health and the offer of therapeutic procedures, at home, outpatient, and inpatient regimes 24. Blood transfusion in Jehovah’s witness patients That is, the SUS law itself provides for the offer of comprehensive therapeutic care by doctors to their patients.ii Therefore, we presented the requirements so that there is no criminal liability of the doctor who intervenes in a Jehovah’s witness patient in order to forcibly submit them to blood transfusion. In short, one must seek to apply practical agreement between conflicting fundamental rights to harmonize the interests at stake. Thus, blood transfusion in absentia of the patient will only be possible in exceptional situations in which, cumulatively, there is a risk of death, blood transfusion is the only possible treatment, and, finally, when there are sufficient medical reasons to justify transfusion 21. Interventions with therapeutic purpose are those that pursue the conservation or restoration of health, the prevention of greater damage, or, in some cases, the simple attenuation or disappearance of pain 25. In this sense, interventions that end up generating some bodily injury to the patient also have a therapeutic end, when they pursue any of these objectives, even if they fail in their purpose. In all therapeutic interventions that do not involve imminent risk of death, the doctor is obliged to ask for the patient’s authorization, under penalty of bearing administrative liability. Nevertheless, it is worth discussing the criminal liability of the doctor in cases where, without the patient’s authorization, the health professional intervenes for therapeutic purposes and ends up causing bodily injury (which can happen in the case of blood transfusion). The doctor may commit, in this case, a crime against personal freedom, more specifically, a crime of illegal constraint, according to art. 146 of the Criminal Code 19. Let us now turn to the analysis of possible criminal liability to the doctor who intervenes in absentia of the patient to subject them to forced blood transfusion, especially in cases that involve any bodily injury resulting from such a therapeutic method. The Brazilian Penal Code 19 typifies, in its art. 129, bodily injury as a crime, which, at first, could generate criminal liability to the doctor who left bodily injuries in the patient undergoing blood transfusion. However, the doctrine 22 has defended the incidence of a theory capable of excluding the typicality of the conducts of health professionals who intervene in their patients for therapeutic purposes. It is the theory of conglobating typicality. Final considerations flagrant noncompliance with the CEM. In addition, a medical action that unduly violates the patient’s will decisively hurts the fundamental right to health, especially in its social and spiritual aspects. Finally, by preventing a patient who is not at risk of death from having control over their own body, one of the fundamental elements of the dignity of the human person is disrespected: the principle of private autonomy. Recognizing Jehovah’s witness patients as endowed with their particularities through the therapeutic approach, especially before techniques involving blood transfusion, the need for the team to adapt the care to continue offering the best options to the users of health services is evident. The contrary expression coming from the patient is justified by their right to freedom of religion, as well as by the bioethical principle of autonomy, and, therefore, the doctor must respect and always act aiming at the bioethical principles and the patient’s rights. Thus, it is up to the professional to act based on bioethical principles, always with a view to maintaining the patient’s rights. A horizontal relationship must be built between both poles, in which the professional recognizes the patient as an entity beyond the disease and, given their particularities, offers convenient therapeutic options for the case. With this, the professional can be in accordance with the ethical and legal ideals established for the profession and patients can receive an adequate medical approach, considering them a biopsychosocial and spiritual being. Such a will could only be disregarded in case of imminent risk of death, under the terms that art. 22 of CEM 7 and art. 146, § 3, I, of the Criminal Code 19 establish. However, in other circumstances, the disobedience of the health team to the patient’s request would constitute a crime of illegal constraint, provided for in the Criminal Code, in addition to being a conduct subject to administrative liability for Blood transfusion in Jehovah’s witness patients It should be pointed out, however, that, due to the fact that the Brazilian legal system encourages therapeutic medical intervention, no type of bodily injury resulting from such practice, regardless of the patient’s consent, is punishable, as it lacks typicality due to the application of the conglobating typicality theory. Therefore, in cases that do not involve imminent risk of death, medical intervention on the patient should always be consensual, otherwise the health professional will be subjected to administrative accountability. In addition, criminal liability may be assigned if it configures some type of offense against personal freedom, but never criminal typicality of injuries, because the therapeutic purpose excludes these interventions from the scope of prohibition of the type of injuries 25. According to this theory, the judgment of typicality requires, in addition to legal typicality, a conglobating typicality, that is, consistent in the investigation of the prohibitive scope of the norm, which cannot be considered in isolation, but along with the legal order 23. In this sense, it is verified that the Brazilian legal system, systematically analyzed, not only does not prohibit, but also encourages medical intervention in its patients for therapeutic purposes. Law 8,080/1990 24 (SUS Law) provides, in its art. 6, I, d, that a comprehensive therapeutic care, Rev. bioét. (Impr.). 2022; 30 (2): 337-45 http://dx.doi.org/10.1590/1983-80422022302529EN 343 Discussions on bioethics, criminal law, and Jehovah’s witness patients References 1. Chehaibar GZ. Bioética e crença religiosa: estudo da relação médico-paciente Testemunha de Jeová com potencial risco de transfusão de sangue [tese] [Internet]. São Paulo: Universidade de São Paulo; 2010 [acesso 5 jan 2022]. Disponível: https://bit.ly/3P7Swcb 2. Campos A, Oliveira DR. A relação entre o princípio da autonomia e o princípio da beneficência (e não maleficência) na bioética médica. Revista Brasileira de Estudos Políticos [Internet]. 2017 [acesso 5 jan 2022];(115):13-45. DOI: 10.9732/P.0034-7191.2017V115P13 2. Campos A, Oliveira DR. A relação entre o princípio da autonomia e o princípio da beneficência (e não maleficência) na bioética médica. Revista Brasileira de Estudos Políticos [Internet]. 2017 [acesso 5 jan 2022];(115):13-45. DOI: 10.9732/P.0034-7191.2017V115P13ii 3. Brasil. Constituição da República Federativa do Brasil de 1988 [Internet]. Brasília: Presidência da República; 1988 [acesso 5 jan 2020]. Disponível: https://bit.ly/3P525Z8 3. Brasil. Constituição da República Federativa do Brasil de 1988 [Internet]. Brasília: Presidência da República; 1988 [acesso 5 jan 2020]. Disponível: https://bit.ly/3P525Z8 4. Wanssa MCD. Autonomia versus beneficência. Rev. bioét (Impr.) [Internet]. 2011 [acesso 5 jan 2022]; 19(1):105-17. Disponível: https://bit.ly/391tZVE 4. Wanssa MCD. Autonomia versus beneficência. Rev. bioét (Impr.) [Internet]. 2011 [acesso 5 jan 2022]; 19(1):105-17. Disponível: https://bit.ly/391tZVE 5. Kovács MJ. Bioética nas questões da vida e da morte. Psicol USP [Internet]. 2003 [acesso 5 jan 2022]; 14(2):115-67. DOI: 10.1590/S0103-65642003000200008 5. Kovács MJ. Bioética nas questões da vida e da morte. Psicol USP [Internet]. 2003 [acesso 5 jan 2022]; 14(2):115-67. DOI: 10.1590/S0103-65642003000200008 Research 6. Siqueira JE, Zoboli E, Sanches M, Pessini L. Bioética clínica: memórias do XI Congresso Brasileiro de Bioética, III Congresso Brasileiro de Bioética Clínica e III Conferência Internacional sobre o Ensino da Ética [Internet]. Brasília: CFM; 2016 [acesso 5 jan 2022]. Disponível: https://bit.ly/3ymNDpp 6. Siqueira JE, Zoboli E, Sanches M, Pessini L. Bioética clínica: memórias do XI Congresso Brasileiro de Bioética, III Congresso Brasileiro de Bioética Clínica e III Conferência Internacional sobre o Ensino da Ética [Internet]. Brasília: CFM; 2016 [acesso 5 jan 2022]. Disponível: https://bit.ly/3ymNDpp 7. Conselho Federal de Medicina. Código de Ética Médica [Internet]. Brasília: CFM; 2018 [acesso 5 jan 2022]. Disponível: https://bit.ly/3kOv1qD 7. Conselho Federal de Medicina. Código de Ética Médica [Internet]. Brasília: CFM; 2018 [acesso 5 jan 2022]. Disponível: https://bit.ly/3kOv1qD 8. Leite Segundo AV, Barros KMA, Axiotes ECG, Zimmerman RD. Aspectos éticos e legais na abordagem de pacientes Testemunhas de Jeová. Rev Ciênc Méd [Internet]. 2007 [acesso 5 jan 2022];16(4-6):257-65. Disponível: https://bit.ly/394tSbS 8. Leite Segundo AV, Barros KMA, Axiotes ECG, Zimmerman RD. References Zaffaroni ER, Pierangeli JH. Op. cit. p. 480. Nathalia da Fonseca Campos – Undergraduate student – nah-fonseca@hotmail.com 0000-0002-6251-0626 Leonardo Bocchi Costa – Master’s student – leonardo.bocchi@hotmail.com 0000-0002-2425-7105 Correspondence Nathalia da Fonseca Campos – Av. Comendador José Giorgi, 883 CEP 19780-000. Quatá/SP, Brasil. Participation of the authors Nathalia da Fonseca Campos was responsible for the bibliographic review, writing of the manuscript, supervision, and critical review of the text. Leonardo Bocchi Costa was responsible for the Bibliographic Review and the writing of the manuscript. Received: 10.2.2020 Revised: 4.27.2022 Approved: 4.28.2022 345 Rev. bioét. (Impr.). 2022; 30 (2): 337-45 References Aspectos éticos e legais na abordagem de pacientes Testemunhas de Jeová. Rev Ciênc Méd [Internet]. 2007 [acesso 5 jan 2022];16(4-6):257-65. Disponível: https://bit.ly/394tSbS 9. França ISX, Baptista RS, Brito VRS. Dilemas éticos na hemotransfusão em Testemunhas de Jeová: uma análise jurídico-bioética. Acta Paul Enferm [Internet]. 2008 [acesso 5 jan 2022];21(3):498-503. Disponível: https://bit.ly/3sk2ai7 9. França ISX, Baptista RS, Brito VRS. Dilemas éticos na hemotransfusão em Testemunhas de Jeová: uma análise jurídico-bioética. Acta Paul Enferm [Internet]. 2008 [acesso 5 jan 2022];21(3):498-503. Disponível: https://bit.ly/3sk2ai7 344 Rev. bioét. (Impr.). 2022; 30 (2): 337-45 http://dx.doi.org/10.1590/1983-80422022302529EN 344 Discussions on bioethics, criminal law, and Jehovah’s witness patients 10. Branco PGG. Direitos fundamentais em espécie. In: Mendes GF, Coelho IM, Branco PGG. Curso de Direito Constitucional. 10ª ed. São Paulo: Saraiva; 2015. p. 393-401.i 11. Barroso LR. A dignidade da pessoa humana no Direito Constitucional contemporâneo: a construção de um conceito jurídico à luz da jurisprudência mundial. Belo Horizonte: Fórum; 2014. 12. Sarmento D. Dignidade da pessoa humana: conteúdo, trajetórias e metodologia. Belo Horizonte: Fórum; 2016. p. 140. 13. Dworkin R. Is democracy possible here? Princeton: Princeton University Press; 2006. 14. Agra WM. Curso de direito constitucional. 9ª ed. Belo Horizonte: Fórum; 2018. 15. Rothenburg WC. Direitos fundamentais. São Paulo: Método; 2014. 16. Silva JA. Curso de direito constitucional positivo. 39ª ed. São Paulo: Malheiros; 2016. 17. Silva VA. O proporcional e o razoável. Revista dos Tribunais [Internet]. 2002 [acesso 5 jan 2022]; 798(2002):23-50. Disponível: https://bit.ly/3kNZYuX 18. Silva VA. Direitos fundamentais: conteúdo essencial, restrições e eficácia. 2ª ed. São Paulo: Malh 19. Brasil. Decreto-Lei nº 2.848, de 7 de dezembro de 1940. Código Penal. Diário Oficial da União [Internet]. Brasília, p. 23911, 31 dez 1940 [acesso 5 jan 2022]. Seção 1. Disponível: https://bit.ly/3FpmvYx 20. Bitencourt CR. Tratado de direito penal. 22ª ed. São Paulo: Saraiva; 2016. p. 410. 21. Marmelstein G. Curso de direitos fundamentais. 5ª ed. São Paulo: Atlas; 2014. 22. Zaffaroni ER, Pierangeli JH. Manual de Direito Penal Brasileiro. 8ª ed. São Paulo: Revista dos Tribunais; 2009. 23. Queiroz P. Direito Penal: parte geral. 4ª ed. Rio de Janeiro: Lumen Juris; 2008. 24. Brasil. Lei nº 8.080, de 19 de setembro de 1990. Dispõe sobre as condições para a promoção, proteção e recuperação da saúde, a organização e o funcionamento dos serviços correspondentes e dá outras providências. Diário Oficial da União [Internet]. Brasília, p. 18055, 20 set 1990 [acesso 5 jan 2022]. Seção 1. Disponível: https://bit.ly/3w9tHny 25. Discussions on bioethics, criminal law, and Jehovah’s witness patients http://dx.doi.org/10.1590/1983-80422022302529EN 345
https://openalex.org/W3100946307
https://www.biorxiv.org/content/biorxiv/early/2019/04/29/360180.full.pdf
English
null
Nuclear and mitochondrial genomic resources for the meltwater stonefly, <i>Lednia tumana</i> Ricker, 1952 (Plecoptera: Nemouridae)
bioRxiv (Cold Spring Harbor Laboratory)
2,018
cc-by
7,220
. CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint Nuclear and mitochondrial genomic resources for the meltwater stonefly, Lednia tumana 1 Ricker, 1952 (Plecoptera: Nemouridae) 2 3 Scott Hotalinga,b*, Joanna L. Kelleya, and David W. Weisrockb 4 5 a School of Biological Sciences, Washington State University, Pullman, WA, USA; b Department 6 of Biology, University of Kentucky, Lexington, KY, USA 7 8 * Scott Hotaling, School of Biological Sciences, Washington State University, Pullman, WA, 9 99164, USA; Email: scott.hotaling@wsu.edu; Phone: (828) 507-9950; ORCID: 0000-0002- 10 5965-0986 11 Abstract: 12 Abstract: 12 With more than 3,700 described species, stoneflies (Order Plecoptera) are an impor 13 component of global aquatic biodiversity. The meltwater stonefly Lednia tumana ( 14 Family Nemouridae) is endemic to alpine streams of Glacier National Park and has 15 petitioned for listing under the U.S. Endangered Species Act (ESA) due to climate 16 induced loss of alpine glaciers and snowfields. Here, we present de novo assemblie 17 nuclear (~520 million base pairs [bp]) and mitochondrial (15,014-bp) genomes for 18 The L. tumana nuclear genome is the most complete stonefly genome reported to d 19 ~71% of genes present in complete form and more than 4,600 contigs longer than 1 20 (kb). The L. tumana mitochondrial genome is the second for the family Nemourida 21 from North America. Together, both genomes represent important foundational res 22 the stage for future efforts to understand the evolution of L. tumana, stoneflies, and 23 insects worldwide. 24 25 Keywords: Plecoptera; Nemouridae; Lednia; genomics; nuclear genome; USA 26 27 Introduction: 28 Stoneflies are a diverse, globally distributed group of hemimetabolous insec 29 diverged from their closest relatives (e.g., Orthoptera, Dermaptera, Zoraptera) at le 30 million years ago in the Carboniferous Period (Béthoux, Cui, Kondratieff, Stark, an 31 With more than 3,700 described species, stoneflies account for a substantial portion 32 freshwater biodiversity (DeWalt, Kondratieff, and Sandberg 2015). The meltwater 33 Lednia tumana (Ricker, 1952; Plecoptera: Nemouridae), resides in alpine streams o 34 National Park (GNP), USA, where it is iconic of habitat loss due to climate change 35 (Muhlfeld et al. 2011; Giersch, Hotaling, Kovach, Jones and Muhlfeld 2017). Ledn 36 one of four extant species in the genus Lednia which all exhibit alpine, cold-water 37 in western North America (Baumann and Kondratieff 2010; Baumann and Call 201 38 majority of L. tumana’s habitat is supported by seasonal melting of permanent ice a 39 habitat type that is under considerable threat of near-term loss as the global cryosph 40 (Hotaling, Finn, Giersch, Weisrock, and Jacobsen 2017; Hotaling et al. 2019). The 41 evolutionary history of L. tumana is closely tied to glacier dynamics with present-d 42 With more than 3,700 described species, stoneflies (Order Plecoptera) are an important 13 component of global aquatic biodiversity. The meltwater stonefly Lednia tumana (Ricker, 1952; 14 Family Nemouridae) is endemic to alpine streams of Glacier National Park and has been 15 petitioned for listing under the U.S. Nuclear and mitochondrial genomic resources for the meltwater stonefly, Lednia tumana 1 Ricker, 1952 (Plecoptera: Nemouridae) 2 a School of Biological Sciences, Washington State University, Pullman, WA, USA; b Department 6 of Biology, University of Kentucky, Lexington, KY, USA 7 1 1 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint Abstract: 12 CC-BY 4.0 International license a y p ) , g p y p p p p y clusters arising in parallel with ice sheet recession at the end of the Pleistocene (~20,000 years 43 ago, Hotaling et al. 2018). Genetic evidence has also highlighted a possible loss of mitochondrial 44 genetic diversity for the species on even more recent, decadal timescales (Jordan et al. 2016). 45 With such a narrow habitat niche in a small, mountainous region of the northern Rocky 46 Mountains, L. tumana has been recommended for listing under the U.S. Endangered Species Act 47 (US Fish & Wildlife Service 2016). 48 In this study, we present an assembly of the nuclear genome for L. tumana, the most 49 complete nuclear genome for the order Plecoptera reported to date. This resource also represents 50 one of only three high-coverage (> 50x) genomes for any EPT taxon (Ephemeroptera, Ephemera 51 danica, Polechau et al. 2014; Plecoptera, this study; Trichoptera, Stenopsyche tienmushanensis, 52 Luo, Tang, Frandsen, Stewart, and Zhou 2018), a globally important group of aquatic organisms 53 commonly used for biological monitoring (e.g., Tronstad, Hotaling, and Bish 2016). We also 54 present a nearly complete mitochondrial genome assembly (mitogenome) for L. tumana, the 55 fourth for the stonefly family Nemouridae after two previous studies (Chen and Du 2017; Cao, 56 Wang, Huang, and Li 2019). 57 58 Materials and Methods: 59 Genomic DNA was extracted using a Qiagen DNeasy Blood & Tissue Kit from a single 60 L. tumana nymph collected in 2013 from Lunch Creek in GNP. Prior to extraction, both the head 61 and as much of the digestive tract as possible were removed A whole genome shotgun 62 Mountains, L. tumana has been recommended for listing under the U.S. Endangered Species Act 47 (US Fish & Wildlife Service 2016). 48 In this study, we present an assembly of the nuclear genome for L. tumana, the most 49 complete nuclear genome for the order Plecoptera reported to date. This resource also represents 50 one of only three high-coverage (> 50x) genomes for any EPT taxon (Ephemeroptera, Ephemera 51 danica, Polechau et al. 2014; Plecoptera, this study; Trichoptera, Stenopsyche tienmushanensis, 52 Luo, Tang, Frandsen, Stewart, and Zhou 2018), a globally important group of aquatic organisms 53 commonly used for biological monitoring (e.g., Tronstad, Hotaling, and Bish 2016). Abstract: 12 Endangered Species Act (ESA) due to climate change- 16 induced loss of alpine glaciers and snowfields. Here, we present de novo assemblies of the 17 nuclear (~520 million base pairs [bp]) and mitochondrial (15,014-bp) genomes for L. tumana. 18 The L. tumana nuclear genome is the most complete stonefly genome reported to date, with 19 ~71% of genes present in complete form and more than 4,600 contigs longer than 10-kilobases 20 (kb). The L. tumana mitochondrial genome is the second for the family Nemouridae and the first 21 from North America. Together, both genomes represent important foundational resources, setting 22 the stage for future efforts to understand the evolution of L. tumana, stoneflies, and aquatic 23 insects worldwide. 24 Introduction: 28 Stoneflies are a diverse, globally distributed group of hemimetabolous insects that 29 diverged from their closest relatives (e.g., Orthoptera, Dermaptera, Zoraptera) at least 300 30 million years ago in the Carboniferous Period (Béthoux, Cui, Kondratieff, Stark, and Ren 2011). 31 With more than 3,700 described species, stoneflies account for a substantial portion of 32 freshwater biodiversity (DeWalt, Kondratieff, and Sandberg 2015). The meltwater stonefly, 33 Lednia tumana (Ricker, 1952; Plecoptera: Nemouridae), resides in alpine streams of Glacier 34 National Park (GNP), USA, where it is iconic of habitat loss due to climate change in the region 35 (Muhlfeld et al. 2011; Giersch, Hotaling, Kovach, Jones and Muhlfeld 2017). Lednia tumana is 36 one of four extant species in the genus Lednia which all exhibit alpine, cold-water distributions 37 in western North America (Baumann and Kondratieff 2010; Baumann and Call 2012). The 38 majority of L. tumana’s habitat is supported by seasonal melting of permanent ice and snow, a 39 habitat type that is under considerable threat of near-term loss as the global cryosphere recedes 40 (Hotaling, Finn, Giersch, Weisrock, and Jacobsen 2017; Hotaling et al. 2019). The recent 41 evolutionary history of L. tumana is closely tied to glacier dynamics with present-day genetic 42 2 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint clusters arising in parallel with ice sheet recession at the end of the Pleistocene (~20,000 years 43 ago, Hotaling et al. 2018). Abstract: 12 Genetic evidence has also highlighted a possible loss of mitochondrial 44 genetic diversity for the species on even more recent, decadal timescales (Jordan et al. 2016). 45 With such a narrow habitat niche in a small, mountainous region of the northern Rocky 46 Mountains, L. tumana has been recommended for listing under the U.S. Endangered Species Act 47 (US Fish & Wildlife Service 2016). 48 In this study, we present an assembly of the nuclear genome for L. tumana, the most 49 complete nuclear genome for the order Plecoptera reported to date. This resource also represents 50 one of only three high-coverage (> 50x) genomes for any EPT taxon (Ephemeroptera, Ephemera 51 danica, Polechau et al. 2014; Plecoptera, this study; Trichoptera, Stenopsyche tienmushanensis, 52 Luo, Tang, Frandsen, Stewart, and Zhou 2018), a globally important group of aquatic organisms 53 commonly used for biological monitoring (e.g., Tronstad, Hotaling, and Bish 2016). We also 54 present a nearly complete mitochondrial genome assembly (mitogenome) for L. tumana, the 55 fourth for the stonefly family Nemouridae after two previous studies (Chen and Du 2017; Cao, 56 Wang, Huang, and Li 2019). 57 58 Materials and Methods: 59 Genomic DNA was extracted using a Qiagen DNeasy Blood & Tissue Kit from a single 60 L. tumana nymph collected in 2013 from Lunch Creek in GNP. Prior to extraction, both the head 61 and as much of the digestive tract as possible were removed. A whole-genome shotgun 62 sequencing library targeting a 250-bp fragment size was constructed and sequenced by the 63 Florida State University Center for Genomics. The library was sequenced twice on 50% of an 64 Illumina HiSeq2500 flow cell each time with paired-end, 150-bp chemistry, resulting in 65 242,208,840 total reads. The size of the L. tumana nuclear genome was estimated using a kmer- 66 based approach in sga preQC (Simpson 2014). Read quality was assessed with fastQC (Andrews 67 2010) and low-quality reads were either trimmed or removed entirely using TrimGalore (Krueger 68 2015) with the flags: --stringency 3 --quality 20 --length 40. We assembled the nuclear genome 69 using SPAdes v3.11.1 with default settings (Bankevich et al. 2012) and generated summary 70 statistics with the Assemblathon2 perl script (assemblathon_stats.pl, Bradnam et al. 2013). The 71 completeness of our nuclear assembly was assessed by calculating the number of conserved 72 single copy orthologous genes [Benchmarking Universal Single-Copy Orthologs (BUSCOs)] in 73 . Abstract: 12 We also 54 present a nearly complete mitochondrial genome assembly (mitogenome) for L. tumana, the 55 fourth for the stonefly family Nemouridae after two previous studies (Chen and Du 2017; Cao, 56 Wang, Huang, and Li 2019). 57 58 Materials and Methods: 59 tumana mitogenome with NOVOPlasty v2.6.7 (Dierckxsens, 82 Mardulyn, and Smits 2016) using an 872-bp segment of the L. tumana cytb gene (GenBank 83 KX212756.1) as the “seed” sequence. After assembly, the mitogenome was annotated through a 84 combination of the MITOS web server with default settings (Bernt et al. 2013) and comparison 85 to the Nemoura nanikensis mitogenome (Plecoptera: Nemouridae; Chen and Du 2017). 86 Materials and Methods: 59 Genomic DNA was extracted using a Qiagen DNeasy Blood & Tissue Kit from a single 60 L. tumana nymph collected in 2013 from Lunch Creek in GNP. Prior to extraction, both the head 61 and as much of the digestive tract as possible were removed. A whole-genome shotgun 62 sequencing library targeting a 250-bp fragment size was constructed and sequenced by the 63 Florida State University Center for Genomics. The library was sequenced twice on 50% of an 64 Illumina HiSeq2500 flow cell each time with paired-end, 150-bp chemistry, resulting in 65 242,208,840 total reads. The size of the L. tumana nuclear genome was estimated using a kmer- 66 based approach in sga preQC (Simpson 2014). Read quality was assessed with fastQC (Andrews 67 2010) and low-quality reads were either trimmed or removed entirely using TrimGalore (Krueger 68 2015) with the flags: --stringency 3 --quality 20 --length 40. We assembled the nuclear genome 69 using SPAdes v3.11.1 with default settings (Bankevich et al. 2012) and generated summary 70 statistics with the Assemblathon2 perl script (assemblathon_stats.pl, Bradnam et al. 2013). The 71 completeness of our nuclear assembly was assessed by calculating the number of conserved 72 single copy orthologous genes [Benchmarking Universal Single-Copy Orthologs (BUSCOs)] in 73 3 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint the assembly using BUSCO v3 and the 1,658 “insecta_ob9” set of reference genes (Simão, 74 Waterhouse, Ioannidis, Kriventseva, and Zdobnov 2015). To compare the completeness of the L. 75 tumana genome in the context of other stoneflies, we downloaded the two other publicly 76 available stonefly genomes for Isoperla grammatica (Poda, 1761; Perlodidae) and Amphinemura 77 sulcicollis (Stephens, 1836; Nemouridae) which are deposited under GenBank BioProject 78 PRJNA315680 (Macdonald, Cunha, and Bruford 2016; Macdonald, Ormerod, and Bruford 79 2017). We performed the same BUSCO and Assemblathon2 analyses on the I. Materials and Methods: 59 grammatica and 80 A. sulcicollis genomes as we did for L. tumana above. 81 We assembled the L. tumana mitogenome with NOVOPlasty v2.6.7 (Dierckxsens, 82 Mardulyn, and Smits 2016) using an 872-bp segment of the L. tumana cytb gene (GenBank 83 KX212756.1) as the “seed” sequence. After assembly, the mitogenome was annotated through a 84 combination of the MITOS web server with default settings (Bernt et al. 2013) and comparison 85 to the Nemoura nanikensis mitogenome (Plecoptera: Nemouridae; Chen and Du 2017). 86 However, in this initial assembly, the 16S gene was fragmented and the 12S gene was missing 87 entirely. To mitigate this, we extracted sequences for both genes from the N. nanikensis 88 mitogenome (Plecoptera: Nemouridae; Chen and Du 2017) and mapped our raw reads to these 89 reference sequences for each gene with BWA-MEM v0.7.12-r1039 (Li 2013) using the default 90 settings. Next, we used bcftools v1.9 (Li, Orti, Zhang, and Lu 2009) to collect summary 91 information on the read mapping and genotype likelihoods (‘mpileup’ with default settings), 92 called consensus nucleotides (‘call’ with -m flag), and output the consensus sequence 93 (‘consensus’ with default settings). Finally, we used samtools v1.7 (Li et al. 2009) to calculate 94 coverage depth per nucleotide for each sequence and masked consensus bases with no coverage 95 (i.e., bases with no information from the L. tumana read mapping). We manually integrated our 96 16S and 12S sequences into the L. tumana mitogenome through comparison with the N. 97 nanikensis mitogenome (Chen and Du 2017) and re-annotated the assembly with the MITOS 98 web server (Bernt et al. 2013) as described above. 99 100 Results and Discussion: 101 the assembly using BUSCO v3 and the 1,658 “insecta_ob9” set of reference genes (Simão, 74 Waterhouse, Ioannidis, Kriventseva, and Zdobnov 2015). To compare the completeness of the L. 75 tumana genome in the context of other stoneflies, we downloaded the two other publicly 76 available stonefly genomes for Isoperla grammatica (Poda, 1761; Perlodidae) and Amphinemura 77 sulcicollis (Stephens, 1836; Nemouridae) which are deposited under GenBank BioProject 78 PRJNA315680 (Macdonald, Cunha, and Bruford 2016; Macdonald, Ormerod, and Bruford 79 2017). We performed the same BUSCO and Assemblathon2 analyses on the I. grammatica and 80 A. sulcicollis genomes as we did for L. tumana above. 81 We assembled the L. Results and Discussion: 101 The size of the L. tumana nuclear genome was estimated to be 536.7-megabases (Mb) 102 from raw sequence data. Our final L. tumana genome assembly was 520.2-Mb with 50% of the 103 assembly in contigs ≥ 4.69-kilobases (kb; Figure 1a, Table 1). The assembled genome size is in 104 4 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint line with the only other publicly available stonefly genomes, I. grammatica (509.5 Mb) and A. 105 sulcicollis (271.9 Mb). The L. tumana genome assembly also includes ~3,800 more contigs > 10 106 kb than the A. sulcicollis genome and ~4,600 more than the I. grammatica assembly (Figure 1a, 107 Table 1). All associated data for the resources detailed in this study, including both raw reads and 108 assemblies, are available as part of GenBank BioProject PRJNA472568 (mitogenome: 109 MH374046, nuclear genome: SAMN09295077, raw reads: SRP148706). 110 The meltwater stonefly’s nuclear genome is similarly A/T-rich (58.4%) to the other 111 stoneflies (58–60%; Table 1), ants (55–67%; Gadau et al. 2012), Drosophila melanogaster 112 (58%), Anopheles gambiae (56%), and the honeybee, Apis mellifera (67%, The Honeybee 113 Genome Sequencing Consortium 2006). However, the L. tumana genome is far more complete in 114 terms of genic regions than both existing stonefly assemblies with 92.8% of BUSCO reference 115 genes either complete (70.6%) or fragmented (22.2%) versus 80.8% for A. sulcicollis (50.5% 116 complete, 31.3% fragmented) and just 50.1% for I. grammatica (13.3% complete, 36.8% 117 fragmented; Figure 1b, Table 1). 118 The L. tumana mitogenome is nearly complete, covering 15,014-bp, including all 13 119 protein-coding genes, 21 tRNA genes, both rRNA genes, and is only missing the control region 120 (Figure 2). The organization of the L. tumana mitogenome is similar to that of N. nankinensis, 121 the only other mitogenome available for the family Nemouridae. In N. Results and Discussion: 101 nankinensis, the control 122 region is ~1-kb which indicates that the complete L. tumana mitogenome is likely around 16-kb. 123 This predicted size would fall in line with mitogenome sizes reported for other stoneflies (Chen 124 and Du 2017). Our inability to resolve the control region is also unsurprising. In N. nankinensis, 125 the control region contains a large ~1-kb repeat region which is inherently difficult to resolve 126 without targeted long-range PCR re-sequencing or longer read high-throughput sequencing. 127 128 Conclusion: 129 The increasing availability of genome assemblies for a wide array of organisms is rapidly 130 expanding the scope and comparative power of modern genome biology (Hotaling and Kelley 131 2019). With more than 4,600 contigs longer than 10-kb and ~70% of genes assembled in their 132 complete form, the L. tumana nuclear genome provides new opportunity for exploring genome 133 evolution within Plecoptera, a highly diverse, globally distributed insect order, or at higher levels 134 of taxonomic organization (e.g., across all insects). Specifically, the L. tumana genome could be 135 5 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint mined for genes for phylogenomic studies (e.g., Li et al. 2007; Borowiec, Lee, Chiu, and 136 Plachetzki 2015) or more targeted, comparative assessments of specific genes or gene families 137 across many taxa to clarify evolutionary shifts and/or copy number variation (e.g., Baalsrud et al. 138 2017). 139 mined for genes for phylogenomic studies (e.g., Li et al. 2007; Borowiec, Lee, Chiu, and 136 Plachetzki 2015) or more targeted, comparative assessments of specific genes or gene families 137 across many taxa to clarify evolutionary shifts and/or copy number variation (e.g., Baalsrud et al. 138 2017). 139 Moreover, single-copy orthologous genes compared among species can provide a means 140 for quantifying differences in evolutionary rates across diverse taxa (e.g., Honeybee Genome 141 Sequencing Consortium 2006) and/or to identify rapidly evolving genes that underlie 142 evolutionary transitions of interest. In the case of stoneflies and aquatic biodiversity in general, 143 little is known of the evolutionary changes underlying the shift to an aquatic larval stage that is 144 common among many orders (e.g., Plecoptera, Ephemeroptera, Trichoptera). With the addition 145 of the L. tumana nuclear genome reported here to the recently published caddisfly (S. 146 tienmushanensis, Order Trichoptera, Luo et al. 2018) and mayfly (E. Conclusion: 129 danica, Order 147 Ephemeroptera, Polechau et al. 2014) genomes, the stage is now set for broad, genome-scale 148 investigations of how this major life history transition occurred across three globally distributed 149 insect orders. 150 Future efforts to refine both assemblies, including the incorporation of longer reads (e.g., 151 generated using Pacific Biosciences sequencing technology, Utturkar et al. 2014) will yield 152 greater insight into the genome biology of L. tumana, stoneflies, and aquatic insects broadly. 153 Still, the resources provided here, and particularly the most complete stonefly nuclear genome 154 published thus far, represent an important step towards empowering modern stonefly research, a 155 globally relevant group of aquatic insects that has been largely overlooked in the genomic age. 156 157 Acknowledgements: 158 We thank Alan Lemmon and Emily Lemmon for advice and assistance with sequencing. This 159 research was supported by the University of Kentucky (UK) and National Science Foundation 160 (DEB-0949532). Computational resources were provided by the UK Center for Computational 161 Sciences and the Lipscomb High Performance Computing Cluster, as well as the Washington 162 State University Center for Institutional Research Computing. 163 164 The authors declare no financial interest or benefit stemming from this research. 166 6 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint References: 167 Andrews, S. (2010), 'FastQC: a quality control tool for high throughput sequence data', 168 https://www.bioinformatics.babraham.ac.uk/projects/download.html#fastqc 169 Baalsrud, H. T., Tørresen, O. K., Solbakken, M. H., Salzburger, W., Hanel, R., Jakobsen, K. S., 170 and Jentoft, S. (2017), ‘De novo gene evolution of antifreeze glycoproteins in codfishes 171 revealed by whole genome sequence data’, Molecular Biology and Evolution, 35, 593–606. 172 Bankevich, A., Nurk, S., Antipov, D., Gurevich, A.A., Dvorkin, M., Kulikov, A.S., Lesin, V.M., 173 Nikolenko, S.I., Pham, S., and Prjibelski, A.D. (2012), 'SPAdes: a new genome assembly 174 algorithm and its applications to single-cell sequencing', Journal of Computational Biology, 175 19, 455–477. 176 Baumann, R.W., and Kondratieff, B.C. (2010), 'The stonefly genus Lednia in North America 177 (Plecoptera: Nemouridae)', Illiesia, 6, 315–327. 178 References: 167 Andrews, S. (2010), 'FastQC: a quality control tool for high throughput sequence data', 168 https://www.bioinformatics.babraham.ac.uk/projects/download.html#fastqc 169 Baalsrud, H. T., Tørresen, O. K., Solbakken, M. H., Salzburger, W., Hanel, R., Jakobsen, K. S., 170 and Jentoft, S. (2017), ‘De novo gene evolution of antifreeze glycoproteins in codfishes 171 revealed by whole genome sequence data’, Molecular Biology and Evolution, 35, 593–606 172 Bankevich, A., Nurk, S., Antipov, D., Gurevich, A.A., Dvorkin, M., Kulikov, A.S., Lesin, V.M., 173 Nikolenko, S.I., Pham, S., and Prjibelski, A.D. Acknowledgements: 158 (2012), 'SPAdes: a new genome assembly 174 algorithm and its applications to single-cell sequencing', Journal of Computational Biology 175 19, 455–477. 176 Baumann, R.W., and Kondratieff, B.C. (2010), 'The stonefly genus Lednia in North America 177 (Plecoptera: Nemouridae)', Illiesia, 6, 315–327. 178 Baumman, R.W., and Call, R.G. (2012), ‘Lednia tetonica, a new species of stonefly from 179 Wyoming (Plecoptera: Nemouridae)’, Illesia, 8, 104–110. 180 Bernt, M., Donath, A., Jühling, F., Externbrink, F., Florentz, C., Fritzsch, G., Pütz, J., 181 Middendorf, M., and Stadler, P.F. (2013), 'MITOS: improved de novo metazoan 182 mitochondrial genome annotation', Molecular Phylogenetics and Evolution, 69, 313–319. 183 Béthoux, O., Cui, Y., Kondratieff, B., Stark, B., and Ren, D. (2011), ‘At last, a Pennsylvanian 184 Andrews, S. (2010), 'FastQC: a quality control tool for high throughput sequence data', 168 Andrews, S. (2010), 'FastQC: a quality control tool for high throughput sequence data', 168 https://www.bioinformatics.babraham.ac.uk/projects/download.html#fastqc CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint Cao, J. J., Wang, Y., Huang, Y. R., and Li, W. H. (2019), ‘Mitochondrial genomes of the 192 stoneflies Mesonemoura metafiligera and Mesonemoura tritaenia (Plecoptera, 193 Nemouridae), with a phylogenetic analysis of Nemouroidea’, ZooKeys, 835, 43. 194 Chen, Z.-T., and Du, Y.-Z. (2017), 'First mitochondrial genome from Nemouridae (Plecoptera) 195 reveals novel features of the elongated control region and phylogenetic implications', 196 International Journal of Molecular Sciences, 18, 996. 197 DeWaltR.E., Kondratieff B.C., and Sandberg J.B. 2015, ‘Order Plecoptera’, Thorp J., Rogers 198 D.C. (eds), Ecology and General Biology: Freshwater Invertebrates. – Academic Press, 199 Cambridge. 200 Dierckxsens, N., Mardulyn, P., and Smits, G. (2016), 'NOVOPlasty: de novo assembly of 201 organelle genomes from whole genome data', Nucleic Acids Research, 45, e18. 202 Gadau, J., Helmkampf, M., Nygaard, S., Roux, J., Simola, D.F., Smith, C.R., Suen, G., Wurm, 203 Y., and Smith, C.D. (2012), ‘The genomic impact of 100 million years of social evolution 204 Gadau, J., Helmkampf, M., Nygaard, S., Roux, J., Simola, D.F., Smith, C.R., Suen, G., Wurm, 203 Y., and Smith, C.D. (2012), ‘The genomic impact of 100 million years of social evolution 204 in seven ant species’, Trends in Genetics, 28, 14–21. 205 Giersch, J.J., Hotaling, S., Kovach, R.P., Jones, L.A., and Muhlfeld, C.C. (2017), 'Climate- 206 induced glacier and snow loss imperils alpine stream insects', Global Change Biology, 23, 207 2577–2589. 208 Honeybee Genome Sequencing Consortium. (2006), 'Insights into social insects from the 209 genome of the honeybee Apis mellifera', Nature, 443, 931. 210 Honeybee Genome Sequencing Consortium. (2006), 'Insights into social insects from the 209 genome of the honeybee Apis mellifera', Nature, 443, 931. 210 Hotaling, S., Finn, D.S., Giersch, J.J., Weisrock, D.W., and Jacobsen, D. (2017), 'Climate change 211 and alpine stream biology: progress, challenges, and opportunities for the future', 212 Biological Reviews, 92, 2024–2045. 213 Hotaling, S., Giersch, J.J., Finn, D.S., Tronstad, L.M., Jordan, S., Serpa, L.E., Call, R.G., 214 Muhlfeld, C.C., and Weisrock, D.W. (2019), ‘Congruent population genetic structure but 215 differing depths of divergence for three alpine stoneflies with similar ecology and 216 geographic distributions’, Freshwater Biology, 64, 335–347. https://www.bioinformatics.babraham.ac.uk/projects/download.html#fastqc Baalsrud, H. T., Tørresen, O. K., Solbakken, M. H., Salzburger, W., Hanel, R., Jakobsen, K. S., 170 and Jentoft, S. (2017), ‘De novo gene evolution of antifreeze glycoproteins in codfishes 171 revealed by whole genome sequence data’, Molecular Biology and Evolution, 35, 593–606. 172 Bankevich, A., Nurk, S., Antipov, D., Gurevich, A.A., Dvorkin, M., Kulikov, A.S., Lesin, V.M., 173 Nikolenko, S.I., Pham, S., and Prjibelski, A.D. (2012), 'SPAdes: a new genome assembly 174 algorithm and its applications to single-cell sequencing', Journal of Computational Biology, 175 19, 455–477. 176 Baumann, R.W., and Kondratieff, B.C. (2010), 'The stonefly genus Lednia in North America 177 (Plecoptera: Nemouridae)', Illiesia, 6, 315–327. 178 Baumman, R.W., and Call, R.G. (2012), ‘Lednia tetonica, a new species of stonefly from 179 Wyoming (Plecoptera: Nemouridae)’, Illesia, 8, 104–110. 180 Bernt, M., Donath, A., Jühling, F., Externbrink, F., Florentz, C., Fritzsch, G., Pütz, J., 181 Middendorf, M., and Stadler, P.F. (2013), 'MITOS: improved de novo metazoan 182 mitochondrial genome annotation', Molecular Phylogenetics and Evolution, 69, 313–319. 183 Bernt, M., Donath, A., Jühling, F., Externbrink, F., Florentz, C., Fritzsch, G., Pütz, J., 181 Middendorf, M., and Stadler, P.F. (2013), 'MITOS: improved de novo metazoan 182 mitochondrial genome annotation', Molecular Phylogenetics and Evolution, 69, 313–319. 183 Béthoux, O., Cui, Y., Kondratieff, B., Stark, B., and Ren, D. (2011), ‘At last, a Pennsylvanian 184 stem-stonefly (Plecoptera) discovered’, BMC Evolutionary Biology, 11, 248. 185 Borowiec, M. L., Lee, E. K., Chiu, J. C., and Plachetzki, D. C. (2015), ‘Extracting phylogenetic 186 signal and accounting for bias in whole-genome data sets supports the Ctenophora as sister 187 to remaining Metazoa’, BMC Genomics, 16, 987. 188 Bradnam, K.R., Fass, J.N., Alexandrov, A., Baranay, P., Bechner, M., Birol, I., Boisvert, S., 189 Bradnam, K.R., Fass, J.N., Alexandrov, A., Baranay, P., Bechner, M., Birol, I., Boisvert, S., 189 Chapman, J.A., Chapuis, G., and Chikhi, R. (2013), 'Assemblathon 2: evaluating de novo 190 methods of genome assembly in three vertebrate species', GigaScience, 2, 10. 191 7 7 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint . https://www.bioinformatics.babraham.ac.uk/projects/download.html#fastqc 217 Hotaling, S., Finn, D.S., Giersch, J.J., Weisrock, D.W., and Jacobsen, D. (2017), 'Climate change 211 and alpine stream biology: progress, challenges, and opportunities for the future', 212 Biological Reviews, 92, 2024–2045. 213 Hotaling, S., Giersch, J.J., Finn, D.S., Tronstad, L.M., Jordan, S., Serpa, L.E., Call, R.G., 214 Muhlfeld, C.C., and Weisrock, D.W. (2019), ‘Congruent population genetic structure but 215 differing depths of divergence for three alpine stoneflies with similar ecology and 216 geographic distributions’, Freshwater Biology, 64, 335–347. 217 8 8 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint Hotaling, S., and Kelley, J.L. (2019), ‘The rising tide of high-quality genomic resources’, 218 Molecular Ecology Resources, 19, 567–569. 219 Hotaling, S., Muhlfeld, C.C., Giersch, J.J., Ali, O.A., Jordan, S., Miller, M.R., Luikart, G., and 220 Weisrock, D.W. (2018), 'Demographic modelling reveals a history of divergence with gen 221 flow for a glacially tied stonefly in a changing post-Pleistocene landscape', Journal of 222 Biogeography, 45, 304–317. 223 Jordan, S., Giersch, J.J., Muhlfeld, C.C., Hotaling, S., Fanning, L., Tappenbeck, T.H., and 224 Luikart, G. (2016), 'Loss of genetic diversity and increased subdivision in an endemic 225 alpine stonefly threatened by climate change', PLoS One, 11, e0157386. 226 Krueger, F. (2015), 'Trim Galore!: A wrapper tool around Cutadapt and FastQC to consistently 227 apply quality and adapter trimming to FastQ files'. 228 https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/ 229 Li, C., Ortí, G., Zhang, G., and Lu, G. (2007), ‘A practical approach to phylogenomics: the 230 phylogeny of ray-finned fish (Actinopterygii) as a case study’, BMC Evolutionary 231 Biology, 7, 44. 232 Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., 233 and Durbin. R. (2009) ‘The sequence alignment/map format and SAMtools’, 234 Bioinformatics, 25, 2078–2079. 235 Li, H. (2013), ‘Aligning sequence reads, clone sequences and assembly contigs with BWA- 236 MEM’, arXiv, 1303, 3997. https://www.bioinformatics.babraham.ac.uk/projects/download.html#fastqc 237 Luo, S., Tang, M., Frandsen, P. B., Stewart, R. J., and Zhou, X. (2018), ‘The genome of an 238 underwater architect, the caddisfly Stenopsyche tienmushanensis Hwang (Insecta: 239 Trichoptera)’, GigaScience, Doi: 10.1093/gigascience/giy143. 240 M d ld H C C h L d B f d M W (2016) ‘D l t f i f 241 Hotaling, S., and Kelley, J.L. (2019), ‘The rising tide of high-quality genomic resources’, 218 Molecular Ecology Resources, 19, 567–569. 219 Hotaling, S., and Kelley, J.L. (2019), ‘The rising tide of high-quality genomic resources’, 218 Molecular Ecology Resources, 19, 567–569. 219 Hotaling, S., Muhlfeld, C.C., Giersch, J.J., Ali, O.A., Jordan, S., Miller, M.R., Luikart, G., and 220 Weisrock, D.W. (2018), 'Demographic modelling reveals a history of divergence with gene 221 flow for a glacially tied stonefly in a changing post-Pleistocene landscape', Journal of 222 Biogeography, 45, 304–317. 223 Jordan, S., Giersch, J.J., Muhlfeld, C.C., Hotaling, S., Fanning, L., Tappenbeck, T.H., and 224 Luikart, G. (2016), 'Loss of genetic diversity and increased subdivision in an endemic 225 alpine stonefly threatened by climate change', PLoS One, 11, e0157386. 226 Krueger, F. (2015), 'Trim Galore!: A wrapper tool around Cutadapt and FastQC to consistently 227 apply quality and adapter trimming to FastQ files'. 228 https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/ 229 Li, C., Ortí, G., Zhang, G., and Lu, G. (2007), ‘A practical approach to phylogenomics: the 230 phylogeny of ray-finned fish (Actinopterygii) as a case study’, BMC Evolutionary 231 Biology, 7, 44. 232 Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., 233 and Durbin. R. (2009) ‘The sequence alignment/map format and SAMtools’, 234 Bioinformatics, 25, 2078–2079. 235 Li, H. (2013), ‘Aligning sequence reads, clone sequences and assembly contigs with BWA- 236 MEM’, arXiv, 1303, 3997. 237 Luo, S., Tang, M., Frandsen, P. B., Stewart, R. J., and Zhou, X. (2018), ‘The genome of an 238 underwater architect, the caddisfly Stenopsyche tienmushanensis Hwang (Insecta: 239 Trichoptera)’, GigaScience, Doi: 10.1093/gigascience/giy143. 240 Macdonald, H.C., Cunha, L., and Bruford, M.W. (2016), ‘Development of genomic resources for 241 four potential environmental bioindicator species: Isoperla grammatica, Amphinemura 242 sulcicollis, Oniscus asellus and Baetis rhodani’, bioRxiv, 046227. 243 9 9 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. https://www.bioinformatics.babraham.ac.uk/projects/download.html#fastqc It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint Macdonald, H.C., Ormerod, S.J., and Bruford, M.W. (2017), ‘Enhancing capacity for freshwater 244 conservation at the genetic level: a demonstration using three stream 245 macroinvertebrates’, Aquatic Conservation: Marine and Freshwater Ecosystems, 27, 452– 246 461. 247 Muhlfeld, C.C., Giersch, J.J., Hauer F.R., Pederson, GT., Luikart, G., Peterson, D.P., Downs, 248 C.C., and Fagre, D.P. (2011), ‘Climate change links fate of glaciers and an endemic alpine 249 invertebrate’, Climatic Change, 106, 337–345. 250 Poelchau, M., Childers, C., Moore, G., Tsavatapalli, V., Evans, J., Lee, C. Y., and Hackett, K. 251 (2014) ‘Th i5k W k @ NAL bli i d t i li ti d 252 Poelchau, M., Childers, C., Moore, G., Tsavatapalli, V., Evans, J., Lee, C. Y., and Hackett, K. 251 (2014), ‘The i5k Workspace@ NAL—enabling genomic data access, visualization and 252 curation of arthropod genomes’, Nucleic Acids Research, 43, D714–D719. 253 Ricker, W. E. (1952), ‘Systematic studies in Plecoptera’, Indiana University, Bloomington. 254 Simão, F.A., Waterhouse, R.M., Ioannidis, P., Kriventseva, E.V., and Zdobnov, E.M. (2015), 255 'BUSCO: assessing genome assembly and annotation completeness with single-copy 256 orthologs', Bioinformatics, 31, 3210–3212. 257 Simpson, J.T. (2014), 'Exploring genome characteristics and sequence quality without a 258 reference', Bioinformatics, 30, 1228–1235. 259 Tronstad, L.M., Hotaling, S., and Bish, J.C. (2016), 'Longitudinal changes in stream invertebrate 260 assemblages of Grand Teton National Park, Wyoming', Insect Conservation and Diversity, 261 9, 320–331. 262 US Fish & Wildlife Service. (2016), 'Endangered and threatened wildlife and plants; 12-month 263 finding on a petition to list the western glacier stonefly as an endangered or threatened 264 species; proposed threatened species status for Meltwater Lednian Stonefly and Western 265 Glacier Stonefly', Federal Register, 81, 68379–68397. 266 Utturkar, S.M., Klingeman, D.M., Land, M.L., Schadt, C.W., Doktycz, M.J., Pelletier, D.A., and 267 Brown, S.D. (2014), 'Evaluation and validation of de novo and hybrid assembly techniques 268 to derive high-quality genome sequences', Bioinformatics, 30, 2709–2716. 269 10 . https://www.bioinformatics.babraham.ac.uk/projects/download.html#fastqc CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint Tables: 270 Table 1. Assembly statistics for the nuclear genome of Lednia tumana (Ricker, 1952; Plecoptera: 271 Nemouridae) and two other stonefly species, Amphinemura sulcicollis (Stephens, 1836) and 272 Isoperla grammatica (Poda, 1761; Macdonald et al. 2016; Macdonald et al. 2017). BUSCOs: 273 Single-copy, orthologous genes known to be highly conserved among insects. A total of 1,658 274 BUSCOs were searched. 275 L. tumana A. sulcicollis I. grammatica Estimated genome size 536,700,000 n/a n/a Assembly size 520,200,814 271,924,966 509,522,935 Coverage ~60x ~1.4x ~0.7x Contigs > 1-kb 74,445 51,555 53,204 Contigs > 10-kb 4,608 849 4 Contig N50 4.69-kb 0.85-kb 0.46-kb %A/T 58.4 58.2 59.9 %G/C 41.5 42.8 40.1 %N 0.1 0 0 Complete BUSCOs 1,172 (70.6%) 837 (50.5%) 221 (13.3%) Fragmented BUSCOs 368 (22.2%) 519 (31.3%) 610 (36.8%) Missing BUSCOs 118 (7.2%) 302 (18.2%) 827 (49.9%) 276 Tables: 270 Table 1. Assembly statistics for the nuclear genome of Lednia tumana (Ricker, 1952; Plecoptera: 271 Nemouridae) and two other stonefly species, Amphinemura sulcicollis (Stephens, 1836) and 272 Isoperla grammatica (Poda, 1761; Macdonald et al. 2016; Macdonald et al. 2017). BUSCOs: 273 Single-copy, orthologous genes known to be highly conserved among insects. A total of 1,658 274 BUSCOs were searched. 275 L. tumana A. sulcicollis I. grammatica Estimated genome size 536,700,000 n/a n/a Assembly size 520,200,814 271,924,966 509,522,935 Coverage ~60x ~1.4x ~0.7x Contigs > 1-kb 74,445 51,555 53,204 Contigs > 10-kb 4,608 849 4 Contig N50 4.69-kb 0.85-kb 0.46-kb %A/T 58.4 58.2 59.9 %G/C 41.5 42.8 40.1 %N 0.1 0 0 Complete BUSCOs 1,172 (70.6%) 837 (50.5%) 221 (13.3%) Fragmented BUSCOs 368 (22.2%) 519 (31.3%) 610 (36.8%) Missing BUSCOs 118 (7.2%) 302 (18.2%) 827 (49.9%) 276 276 11 11 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint 277 Figures: 278 Figure 1. Comparisons of the gene content and contiguity of the Lednia tumana (Ricker, 1952; 279 Plecoptera: Nemouridae) nuclear genome to the two other previously published stonefly 280 genomes for Amphinemura sulcicollis (Stephens, 1836) and Isoperla grammatica (Poda, 1761; 281 Macdonald et al. 2016; Macdonald et al. 2017). (a) The number of contigs > 1-kb and > 10-kb 282 across the three stonefly genomes. For I. grammatica, the assembly contains just four contigs 283 greater than 10-kb. (b) Presence of highly conserved, single-copy orthologous genes (BUSCOs) 284 across the three stonefly genomes. 285 Figure 1. Comparisons of the gene content and contiguity of the Lednia tumana (Ricker, 1952; 279 Plecoptera: Nemouridae) nuclear genome to the two other previously published stonefly 280 genomes for Amphinemura sulcicollis (Stephens, 1836) and Isoperla grammatica (Poda, 1761; 281 Macdonald et al. 2016; Macdonald et al. 2017). (a) The number of contigs > 1-kb and > 10-kb 282 across the three stonefly genomes. For I. grammatica, the assembly contains just four contigs 283 greater than 10-kb. (b) Presence of highly conserved, single-copy orthologous genes (BUSCOs) 284 across the three stonefly genomes. 285 Figure 1. Tables: 270 Comparisons of the gene content and contiguity of the Lednia tumana (Ricker, 1952; 279 Plecoptera: Nemouridae) nuclear genome to the two other previously published stonefly 280 genomes for Amphinemura sulcicollis (Stephens, 1836) and Isoperla grammatica (Poda, 1761; 281 Macdonald et al. 2016; Macdonald et al. 2017). (a) The number of contigs > 1-kb and > 10-kb 282 across the three stonefly genomes. For I. grammatica, the assembly contains just four contigs 283 greater than 10-kb. (b) Presence of highly conserved, single-copy orthologous genes (BUSCOs) 284 across the three stonefly genomes. 285 omparisons of the gene content and contiguity of the Lednia tumana (Ricker, 1952 12 . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 29, 2019. ; https://doi.org/10.1101/360180 doi: bioRxiv preprint 286 Figure 2. (a) The mitogenome of Lednia tumana (Ricker, 1952; Plecoptera: Nemouridae). (b) 287 Locations of tRNAs. (c) Locations of protein coding (PCGs) and rRNA genes. 288 Figure 2. (a) The mitogenome of Lednia tumana (Ricker, 1952; Plecoptera: Nemouridae). (b) 287 Locations of tRNAs. (c) Locations of protein coding (PCGs) and rRNA genes. 288 Figure 2. (a) The mitogenome of Lednia tumana (Ricker, 1952; Plecoptera: Nemouridae). (b) 287 Locations of tRNAs. (c) Locations of protein coding (PCGs) and rRNA genes. 288 13
https://openalex.org/W4232218243
http://www.ajnr.org/content/ajnr/41/2/E8.full.pdf
English
null
<i>Reply:</i>
American journal of neuroradiology
2,020
cc-by
441
http://dx.doi.org/10.3174/ajnr.A6400 Letters Feb 2020 www.ajnr.org of October 23, 2024. This information is current as Reply: Inglesby, J.J. Bloomberg, M.S. George and T.R. Brown D.R. Roberts, D. Asemani, P.J. Nietert, M.A. Eckert, D.C. http://www.ajnr.org/content/41/2/E8 https://doi.org/10.3174/ajnr.A6400 doi: 2020, 41 (2) E8 AJNR Am J Neuroradiol of October 23, 2024. This information is current as REPLY: have on brain health. This work will be important in guiding the development of effective countermeasures protecting brain func- tion in support of future human spaceflight. W e i W e thank Drs Bevelacqua, Welsh, and Mortazavi for their interest in our article, “Prolonged Microgravity Affects Human Brain Structure and Function.” We disagree, however, that we have ignored the multiple unique features of the space- flight environment to which astronauts are exposed and that “this omission has possibly affected the validity of the findings.” D.R. Roberts D. Asemani Department of Radiology and Radiological Science P.J. Nietert Department of Public Health M.A. Eckert Department of Otolaryngology - Head and Neck Surgery D.C. Inglesby Department of Radiology and Radiological Science Medical University of South Carolina Charleston, South Carolina J.J. Bloomberg Neurosciences Laboratory NASA Johnson Space Center Houston, Texas M.S. George Department of Psychiatry and Behavioral Sciences Medical University of South Carolina Charleston, South Carolina Ralph H. Johnson VA Medical Center Charleston, South Carolina T.R. Brown Department of Radiology and Radiological Science Medical University of South Carolina Charleston, South Carolina D.R. Roberts D. Asemani Department of Radiology and Radiological Science P.J. Nietert Department of Public Health M.A. Eckert Department of Otolaryngology - Head and Neck Surgery D.C. Inglesby Department of Radiology and Radiological Science Medical University of South Carolina Charleston, South Carolina J.J. Bloomberg Neurosciences Laboratory NASA Johnson Space Center Houston, Texas M.S. George Department of Psychiatry and Behavioral Sciences Medical University of South Carolina Charleston, South Carolina Ralph H. Johnson VA Medical Center Charleston, South Carolina T.R. Brown Department of Radiology and Radiological Science Medical University of South Carolina Charleston, South Carolina As we stated in the article, many factors affect individual astro- naut performance. These factors include psychological stress, gravitational changes, and radiation exposure as highlighted in the letter of Drs Bevelacqua, Welsh, and Mortazavi. Other unique characteristics of the spaceflight environment include elevated car- bon dioxide levels, cephalad fluid shifts, and unique microbial hab- itats among others. Any of these factors may act individually or in synergy to result in the changes in brain structure and cognitive function that we have documented in astronauts after spaceflight. Our study highlights the need for further investigations of human brain adaptation to spaceflight to disentangle the relative contribution that each factor, including radiation exposure, may Letters Feb 2020 www.ajnr.org E8 E8
https://openalex.org/W3034519409
https://uvadoc.uva.es/bitstream/10324/58993/1/The-Role-of-Selenium-Mineral%20.pdf
English
null
The Role of Selenium Mineral Trace Element in Exercise: Antioxidant Defense System, Muscle Performance, Hormone Response, and Athletic Performance. A Systematic Review
Nutrients
2,020
cc-by
9,462
Diego Fernández-Lázaro 1,*,† , Cesar I. Fernandez-Lazaro 1,2,† , Juan Mielgo-Ayuso 3 , Lourdes Jiménez Navascués 4, Alfredo Córdova Martínez 3 and Jesús Seco-Calvo 5 Diego Fernández-Lázaro 1,*,† , Cesar I. Fernandez-Lazaro 1,2,† , Juan Mielgo-Ayuso 3 Lourdes Jiménez Navascués 4, Alfredo Córdova Martínez 3 and Jesús Seco-Calvo 5 1 Department of Cellular Biology, Histology and Pharmacology, Faculty of Health Sciences, University o Valladolid, Campus of Soria, 42003 Soria, Spain; fernandezlazaro@usal.es 2 Department of Preventive Medicine and Public Health, School of Medicine, University of Navarra, IdiSNA, 31008 Pamplona, Spain 2 Department of Preventive Medicine and Public Health, School of Medicine, University of Navarra, IdiSNA, 31008 Pamplona, Spain 3 Department of Biochemistry, Molecular Biology and Physiology, Faculty of Health Sciences, University of Valladolid, Campus of Soria, 42003 Soria, Spain; juanfrancisco.mielgo@uva.es (J.M.-A.); a.cordova@bio.uva.es (A.C.M.) 4 Department of Nursing, Faculty of Health Sciences, University of Valladolid, Campus of Soria, 42003 S Spain; lourdes.jimenez@uva.es p j 5 Institute of Biomedicine (IBIOMED), Physiotherapy Department, University of Leon, Visiting Researcher of Basque Country University, Campus de Vegazana, 24071 Leon, Spain; dr.seco.jesus@gmail.com Institute of Biomedicine (IBIOMED), Physiotherapy Department, University of Leon, Visiting Researcher o B C U i i C d V 24071 L S i d j @ il 5 Institute of Biomedicine (IBIOMED), Physiotherapy Department, University of Leon, Visiting Researche Basque Country University, Campus de Vegazana, 24071 Leon, Spain; dr.seco.jesus@gmail.com * Correspondence: diego.fernandez.lazaro@uva.es; Tel.: +34-975-129-185 * Correspondence: diego.fernandez.lazaro@uva.es; Tel.: +34-975-129-185 † Equal contributions * Correspondence: diego.fernandez.lazaro@uva.es; Tel.: +34-975-129-185 † Equal contributions. † Equal contributions. www.mdpi.com/journal/nutrients Nutrients 2020, 12, 1790; doi:10.3390/nu12061790 nutrients nutrients 1. Introduction Selenium (Se) is an essential trace element in mammals with antioxidant and immune functions that can be found in seafood, pea lentils, beans, whole grains, organ meats, dairy products, and vegetables [1,2]. Se mineral is a vital element of selenoproteins that are involved in redox catalytic activity, structural, and transport functions. The effects of Se are related to antioxidant defense, synthesis of thyroid hormones, testosterone metabolism, DNA structure, modulation of vitamin E (alpha-tocopherol), anti-carcinogen processes, and muscle performance [2,3]. The primary biological role of Se lies in two fundamental properties: (i) the protective antioxidant function of oxidative damage; and (ii) immunomodulation. These Se properties may potentially be applicable to improve athletic performance and training recovery among physically active individuals [4,5]. During physical exercise, oxygen consumption increases between 10 and 15 times above the resting values and may trigger an elevated production of reactive oxygen species (ROS) [6]. Under physiological conditions, antioxidant systems (enzymatic and non-enzymatic systems) neutralizes the harmful effects of ROS [7]. The selenoprotein family is encoded by 25 genes [8], and two of these genes encode the enzyme glutathione peroxidase (GPx) and the enzyme glutathione reductase (GR). These enzymes comprise the glutathione redox cycle, probably an essential physiological antioxidants system [9]. Glutathione serves as a substrate for GPx to prevent the degradation of cell structures, reducing the action of free radicals and lipid peroxides. GR allows to maintain concentrations of glutathione in the cell, not only to be used by the GPx in the elimination of peroxides but also to detoxify ROS. Glutathione modulates the process of recovery of vitamin C (ascorbic acid) and vitamin E after neutralizing free radicals generated by physical exercise [10]. The GPx/GR antioxidant system is related to different antioxidant systems such as the superoxide dismutase/catalase (SOD/CAT). Both systems, the GPx/GR and the SOD/CAT, do not act simultaneously [11]. The SOD eliminates the superoxide radical before it reacts with susceptible biological molecules or causes other toxic agents [12]. In circumstances of elevated consumption of oxygen, such as intense exercise, ROS may exceed the body’s antioxidant capacity to neutralize them [7]. Probably, the risk of cellular injury caused by free radicals may be attenuated by the action of skeletal muscle antioxidant enzymes (GPx, GR, SOD, and CAT). Free radicals can cause lesions in the cell membranes of the skeletal muscle [13]. Received: 17 April 2020; Accepted: 9 June 2020; Published: 16 June 2020 Abstract: Exercise overproduces oxygen reactive species (ROS) and eventually exceeds the body’s antioxidant capacity to neutralize them. The ROS produce damaging effects on the cell membrane and contribute to skeletal muscle damage. Selenium (Se), a natural mineral trace element, is an essential component of selenoproteins that plays an important role in antioxidant defense. The activity of the enzyme glutathione peroxidase (GPx), a highly-efficient antioxidant enzyme, is closely dependent on the presence of Se. These properties of Se may be potentially applicable to improve athletic performance and training recovery. We systematically searched for published studies to evaluate the effectiveness of Se supplementation on antioxidant defense system, muscle performance, hormone response, and athletic performance among physically active individuals. We used the Preferred Reporting Elements for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and searched in SCOPUS, Web of Science (WOS), and PubMed databases to identify published studies until March 2020. The systematic review incorporated original studies with randomized controlled crossover or parallel design in which intake of Se administered once a day was compared with the same placebo conditions. No exclusions were applied for the type of physical exercise performed, the sex, nor the age of the participants. Among 150 articles identified in the search, 6 met the criteria and were included in the systematic review. The methodological quality of the studies was evaluated using the McMaster Critical Review Form. Oral Se supplementation with 180 µg/day or 240 µg/day (selenomethionine) and 200 µg/day (Sodium Selenite), significantly decreased lipid hydroperoxide levels and increased GPx in plasma, erythrocyte, and muscle. No significant effects were observed on athletic performance, testosterone hormone levels, creatine kinase activity, and exercise training-induced adaptations on oxidative enzyme activities or on muscle fiber type myosin heavy chain expression. In addition, Se supplementation showed to have a dampening effect on the mitochondria changes in chronic and acute exercise. In summary, the use of Se supplementation has no benefits on aerobic or anaerobic athletic performance but it may prevent Se deficiencies among athletes with high-intensity and high-volume training. Optimal Se plasma levels may be Nutrients 2020, 12, 1790; doi:10.3390/nu12061790 2 of 16 Nutrients 2020, 12, 1790 important to minimize chronic exercise-induced oxidative effects and modulate the exercise effect on mitochondrial changes. important to minimize chronic exercise-induced oxidative effects and modulate the exercise effect on mitochondrial changes. Keywords: mineral trace element; selenium; exercise; antioxidants; muscle; hormone response; athletic performance 1. Introduction Some muscle proteins such as creatine kinase (CK), lactate dehydrogenase (LDH), and myoglobin (Mb) have been observed to increase their concentration in the blood after episodes of intense or continuous exercise. In addition, intense exercise may modify the hormonal response, mainly the testosterone/cortisol ratio that regulates the anabolic/catabolic processes involved in protein replenishment [14]. The disruption of normal levels CK, LDH, MB, and testosterone/cortisol ratio are indicative of muscle damage, and may decrease sports performance, and increase the training recovery time, and consequently, may affect the health of athletes [15]. A prevention strategy to avoid the consequence of oxidative stress (OS) and reduce muscle damage may be the oral intake of antioxidant supplementation [7]. The activity of the enzyme glutathione peroxidase (GPx), a highly-efficient antioxidant enzyme, is strictly dependent on the presence of its co-factor Se [16]. Increases in blood levels of Se have been reported through exogenous Se intake, mostly in its organic form of selenomethionine [17] and inorganic salts of sodium selenite (Na2SeO3) [18,19]. Elevated blood concentrations of Se may stimulate the activity of the GSH-Px enzyme in the muscle [11]. The GSH-Px enzyme may protect polyunsaturated fatty acids, proteins, 3 of 16 Nutrients 2020, 12, 1790 and cell membranes from the effects of peroxides and lipid hydroperoxide (LH), and consequently may lead to prevent exercise-induced muscle damage. Moreover, the GSH-Px participates in the regulation of the inflammatory response [20]. Somestudies[21–24]haveexaminedtheimpactofantioxidantsupplementationonathletes, including minerals’ trace elements with antioxidant properties such as Se [4]. Nevertheless, the properties of Se are not limited to antioxidant activity. Se may play a transcendental biological role as anti-carcinogenic agent and may be related to the reproductive function of humans and the endocrine system. Likewise, Se constitutes a necessary micronutrient for the immune system with a recognized protective role against viral infection. Moreover, elevated serum Se and selenoenzymes (GPx and Se protein) levels have been observed in the early stages of a severe disease characterized by inflammatory response and oxidative stress [25]. However, more studies are needed to confirm the potential properties of Se. Furthermore, Se has not been extensively studied in situations involving physical exercise [26]. There is limited information about the effect of Se supplementation and exercise, particularly on its impact on antioxidant systems, muscle damage, hormonal response, and athletic performance. 1. Introduction Therefore, the purpose of this study was to critically evaluate the effectiveness of Se supplementation on physiological antioxidant defense system, muscle damage markers, testosterone hormone, and athletic performance in physically active population. In addition, the study aims to determine the effective dose, timing, and duration of treatment for optimal application. 2.1. Search Strategy We aimed to systematically review published articles that examined the effects of Se supplementation on exercise performance, physiological indicators of exercise, and antioxidant markers. We followed the Preferred Reporting Elements for Systematic Reviews and Meta-Analysis (PRISMA) guidelines [27], and we structured the PICOS question model for the definition of inclusion criteria as follows: P (population) “healthy exercise practitioners”; I (intervention) “supplementation with selenium”; C (comparison) “same conditions with placebo or control group”; O (outcomes) “antioxidant effect, skeletal muscle status, hormonal response, and athletic performance”, S (study design) “double- or single-blind design and randomized parallel or crossed”. g g g p The systematic review was conducted in Scopus, PubMed, and Web of Science (WOS) databases without language or time restriction. These databases were chosen because they provide high-quality scientific information. The search terms used as search strategy were a combination of Medical Subject Headings (MeSH) and keywords related to Se, skeletal muscle, exercise, antioxidants, and physiology. The search terms included the following: (“athletes” OR “sports people” OR “sports” OR “elite athletes”) AND (“selenium”-Title/Abstract-OR “selenium intake”) AND (“athletic performance” -Title/Abstract-OR “athletic performance/physiology” OR “exercise”) AND (“skeletal muscle -Title/Abstract-OR “muscle skeletal/physiology”). We used the “snowball method” to screen for additional studies. All titles and abstracts were analyzed meticulously to find any duplicate and were later screened. The full texts of the selected articles were read to verify the inclusion and exclusion criteria were met. This process was conducted by two investigators (D.F.-L. and C.I.F.-L.) that discussed discrepancies. 2.2. Selection of Articles: Inclusion and Exclusion Criteria The inclusion criteria in this systematic review included: (i) human experimental studies involving the supplementation intake of a dose of Se or a product containing Se, before and/or during exercise; (ii) with a control group (lack of Se supplementation intake) in the same experimental conditions (with or without placebo intake); (iii): randomized, parallel or crossover design and double or single-blind studies; (iv) with specific information about the supplemental intake and period of intervention; (v) with information about the type of pharmaceutical form used for the supplementation (pills, 4 of 16 d to Nutrients 2020, 12, 1790 l t ti ( ill tablets, gel caps, liquids); (vi) with at least one reported outcomes related to skeletal muscle status, antioxidant effect, or hormonal response. keletal muscle status, antioxidant effect, or hormonal response. Exclusion criteria included the following: (i) animal studies; (ii) uncontrolled trials; (iii) studies with unknown Se intake dose; (iv) studies conducted among subjects with comorbidities or injuries Exclusion criteria included the following: (i) animal studies; (ii) uncontrolled trials; (iii) studies with unknown Se intake dose; (iv) studies conducted among subjects with comorbidities or injuries that prevented the execution of exercise protocols; (v) studies that include Se preparations plus other active ingredients; (vi) editorials, reviews, letters, meeting abstracts, and comments. No inclusion criteria regarding the level of fitness, sex, or age were included. ( ) g j j hat prevented the execution of exercise protocols; (v) studies that include Se preparations plus other ctive ingredients; (vi) editorials, reviews, letters, meeting abstracts, and comments. No inclusion riteria regarding the level of fitness, sex, or age were included. We used the McMaster’s Critical Review Form [28] to assess the quality of each of the selected rticles. We used this Form to find potential limitations in the methodology of the studies. We used the McMaster’s Critical Review Form [28] to assess the quality of each of the selected cles. We used this Form to find potential limitations in the methodology of the studies. s. We used this Form to find potential limitations in the methodology of the studies. 2.2. Selection of Articles: Inclusion and Exclusion Criteria he following information was extracted from each study included in the systematic review: of the first author, year of publication, study design, sample size and characteristics of the The following information was extracted from each study included in the systematic review: name of the first author, year of publication, study design, sample size and characteristics of the included participants such as age, sex, weight, body mass index (BMI), or body fat, dose of supplementation, intervention group, control group, intervention duration, outcomes, and results. Two investigators (D.F.-L. and C.I.F.-L.) conducted the data extraction process using a spreadsheet (Microsoft Inc, Seattle, WA, USA). , y p , y g , p ncluded participants such as age, sex, weight, body mass index (BMI), or body fat, dose of upplementation, intervention group, control group, intervention duration, outcomes, and results. wo investigators (D.F.-L. and C.I.F.-L.) conducted the data extraction process using a spreadsheet Microsoft Inc, Seattle, WA, USA). . Results 3.2. Characteristics of the Studies Among the selected articles, 1 study included active subjects [18], 4 studies regularly trained athletes [13,26,29,30], and 1 study had a population who lacked regular training before the study [19]. Furthermore, in 4 studies, supplementation was organic Se in the form of selenomethionine [13,26,29,30], while in 2 studies, supplementation was in form of salts of sodium selenite [18,19]. Regarding the daily dose of Se, 3 studies used 180 µg [13,26,29], 2 studies used 200 µg [18,19], and 1 study used 240 µg [30]. All studies used a single dose given once a day [13,18,19,26,29,30]. The treatment duration of the studies ranged from 4 to 14 weeks, with 1 study of 4-week duration [18], 1 study of 14 week-duration [19], and 4 studies of 10-duration [13,26,29,30] (Table 1). Table 1. Characteristics of participants and interventions in the studies included in the review. Level of Participants Active 1 Study [18] Regularly trained athletes 4 Studies [13,26,29,30] No Regular Training before the Study 1 Study [19] Age Range (years) 20–35 years 5 Studies [13,19,26,29,30] Not Specified 1 Study [18] Se Plasma Level (µg/l) Assayed 4 Studies [13,19,26,30] Not Assayed 2 Studies [18,29] Type of Administration of Selenium Organic selenium in form of selenomethionine 4 Studies [13,26,29,30] Salts of sodium selenite (Na2Se03) 2 Studies [18,19] Dosage Used 180 µg single dose 3 Studies [13,26,29] 200 µg single dose 2 Studies [18,19] 240 µg single dose 1 Study [30] Moment of Supplementation Daily 6 Studies [13,18,19,26,29,30] Duration of Treatment 4 weeks 1 Study [18] 10 weeks 4 Studies [13,26,29,30] 14 weeks 1 Study [19] Table 1. Characteristics of participants and interventions in the studies included in the review. 3.3. Assessment of the Methodological Quality The results of the assessment of the methodical quality according to the McMaster Quantitative Review Form [28] were as follows: 1 study was evaluated as having “good” quality [13], 4 studies as “very good” [19,26,29,30], and 1 study as “excellent “quality [18]. All studies met the minimum quality score (Table 2). 3.1. Literature Search The results of the l The results of the literature search are shown in Figure 1. In total, 150 articles were identified in Scopus, Medline, and WOS until March 2020. After exclusions of duplicates (n = 39), 111 records were screened. In the first instance, records were screened by title and abstract content and, 91 articles were excluded. The 20 remaining abstracts were full-text reviewed, and the articles that did not meet the inclusion criteria were excluded. The reasons for the exclusion of studies included: animal studies (n = 1), studies among subjects with comorbidities or unable to follow an exercise protocol (n = 12), and studies with no relevant outcomes for the purpose of the study (n = 1). copus, Medline, and WOS until March 2020. After exclusions of duplicates ( n = 39 ), 111 records were screened. In the first instance, records were screened by title and abstract content and, 91 articles were excluded. The 20 remaining abstracts were full-text reviewed, and the articles that did not meet he inclusion criteria were excluded. The reasons for the exclusion of studies included: animal studies n = 1 ), studies among subjects with comorbidities or unable to follow an exercise protocol ( n = 12), nd studies with no relevant outcomes for the purpose of the study ( n = 1 ). Figure 1. Flow-chart of the literature search and study selection. Figure 1. Flow-chart of the literature search and study selection. gure 1. Flow-chart of the literature search and study selection. Figure 1. Flow-chart of the literature search and study selection. 5 of 16 Nutrients 2020, 12, 1790 3.4. Findings of Included Studies A summary of the population, intervention, comparison, outcome measures, and main conclusions is provided in Table 3A–C. 6 of 16 Nutrients 2020, 12, 1790 Table 2. Methodological quality of the studies included in the systematic review. References Margaritis et al. 1997 [13] Zamora et al. 1995 [29] Savory et al. 2012 [19] Tessier et al. 1994 [26] Neek et al. 2011 [18] Tessier et al. 1995 [30] TI ITEMS 1 1 1 1 1 1 1 6 2 1 1 1 1 1 1 6 3 1 1 1 1 1 1 6 4 1 1 1 1 1 1 6 5 1 1 1 1 1 1 6 6 0 0 1 0 0 0 2 7 1 1 1 1 1 1 6 8 1 1 1 1 1 1 6 9 0 1 1 1 1 1 5 10 0 0 0 0 0 0 1 11 1 1 1 1 1 1 6 12 1 1 1 1 1 1 6 13 1 1 1 1 1 1 6 14 0 0 0 0 0 0 0 15 1 1 1 1 1 1 6 16 1 1 1 1 1 1 6 TS 12 13 14 13 15 13 % 75 81.3 87.5 81.3 93.8 81.3 MQ G VG VG VG E VG (TS) Total items fulfilled by study. (1) Criterion met; (0) Criterion not met. (TI): Total items fulfilled by items. Methodological Quality (MQ): poor (P) ≤8 points; acceptable (A) 9–10 points; good (G) 11–12 points; very good (VG) 13–14 points; excellent (E) ≥15 points. Table 2. Methodological quality of the studies included in the systematic review. 7 of 16 Nutrients 2020, 12, 1790 Table 3. Characteistics of the studies included in the systematic review. (A) Authors & Year Study Design Population Intervention Analyzed Results Main Conclusions Savory et al., 2012 [19] Placebo-controlled, double-blind, crossover 20 healthy subjects 9♂& 1♀ NW: 4 ♂& 6 ♀ 27.9 ± 2.2 y BMI 22.8 ± 0.4 kg/m2 OW: 5 ♂& 5 ♀ 31.4 ± 1.9 y BMI 28.0 ± 0.8 kg/m2 Supplementation: 200 µg Se (sodium selenite) once per day * 3 weeks’ placebo (not containing glucose) during another 3-week period. Washout period 2 moth. 3.4. Findings of Included Studies Order treatment: NW: Se/Placebo OW: Placebo/Se 14-week total period PhA: test 30 min treadmill session at 70% VO2peak [Se] Post Se treatment period ↑*[Se] NW & OW compared to week 0 Post Se treatment period ↑* [Se] NW & OW compared to placebo treatment TAS, GSH, SOD Placebo period & Se treatment period - rest vs. post PhA: OW & NW ↔TAS; GSH; SOD - OW vs. NW ↔TAS; GSH; SOD LH Placebo period - rest vs. post PhA: OW ↑*LH NW ↑LH - OW vs. NW ↑*LH Se treatment period - rest vs. post PhA: OW †LH NW †LH - OW vs. NW †LH Placebo vs. Se treatment post PhA: OW ↓*LH; NW↔LH Tessier et al., 1994 [26] Placebo-controlled, double-blind, randomized 24 ♂healthy students 22.9 ± 2.1 y; 8.0 ± 8.7 Kg; 178.0 ± 6.6 cm; Body fat 11.2 ± 4.4 % PbG n = 12 ♂ 22.5 ± 2.0 y; 67.3 ±7.0 Kg; 177.4 ± 7.0 cm; Body fat 10.4 ± 3.9 % SeG n = 12 ♂ 23.2 ± 2.3 y; 68.7 ± 10.4 Kg; 178.7 ± 6.3 cm; Body fat 12.3 ± 4.8 % Supplementation: 180 µg Se (Seleniomethionine) once per day * 10-week period PhA: 10-week endurance training program 4-week nontraining Pre-PhA vs. Post-PhA SeG vs. PbG [Se] ↑*[Se] SeG ↓[Se] PbG # [Se] GTtotal ↓* SeGr ↓* PbGr † GTtotal GSSG ↓GSSG SeGr ↓GSSG PbGr † GSSG GPx plasma ↑* SeG ↑PbG # GPx EGPx ↑* SeG ↑PbG # EGPx EGR ↑* SeG ↑*PbG † EGR Vitamin E ↓SeG ↑PbG † Vitamin E VO2max ↑* SeG ↑*PbG † VO2max SeG: ↑VO2max positive correlated ↑GPX (r:0.66 p < 0.05 n = 12) Table 3. Characteistics of the studies included in the systematic review. Savory et al., 2012 [19] Placebo-controlled, double-blind, crossover Tessier et al., 1994 [26] Placebo-controlled, double-blind, randomized 24 ♂healthy students 22.9 ± 2.1 y; 8.0 ± 8.7 Kg; 178.0 ± 6.6 cm; Body fat 11.2 ± 4.4 % PbG n = 12 ♂ 22.5 ± 2.0 y; 67.3 ±7.0 Kg; 177.4 ± 7.0 cm; Body fat 10.4 ± 3.9 % SeG n = 12 ♂ 23.2 ± 2.3 y; 68.7 ± 10.4 Kg; 178.7 ± 6.3 cm; Body fat 12.3 ± 4.8 % Supplementation: 180 µg Se (Seleniomethionine) once per day * 10-week period PhA: 10-week endurance training program 4-week nontraining Pre-PhA vs. Post-PhA SeG vs. 3.4. Findings of Included Studies PbG [Se] ↑*[Se] SeG ↓[Se] PbG # [Se] GTtotal ↓* SeGr ↓* PbGr † GTtotal GSSG ↓GSSG SeGr ↓GSSG PbGr † GSSG GPx plasma ↑* SeG ↑PbG # GPx EGPx ↑* SeG ↑PbG # EGPx EGR ↑* SeG ↑*PbG † EGR Vitamin E ↓SeG ↑PbG † Vitamin E VO2max ↑* SeG ↑*PbG † VO2max SeG: ↑VO2max positive correlated ↑GPX (r:0.66 p < 0.05 n = 12) Tessier et al., 1994 [26] Placebo-controlled, double-blind, randomized 8 of 16 Nutrients 2020, 12, 1790 Table 3. Cont. (B) Author/s—Year Study Design Population Intervention Analyzed Results Results and Main Conclusions Neek et al., 2011 [18] Placebo-controlled, double-blind, randomized 16 ♂road cyclists Pb n = 8 ♂cyclists 66.1 ± 4.2 Kg; 176.8 ± 8.0 cm; BMI 21.1 ± 4.4 Kg/m2 SeG n = 8 ♂cyclists 61.6 ± 4.7 Kg; 177.7 ± 4.2 cm; BMI 20.5 ± 1.2 Kg/m2 Supplementation: 200 µg de Selenium (sodium selenite) once per day * 4-week period PhA: cycling exhaustive exercise 4-week Pre-PhA vs. Post-PhA SeG vs. PbG Tt ↑* SeG ↑* PbG ↔Tt Tf ↑* SeG ↑* PbG ↔Tf [La] ↑* SeG ↑* PbG ↔[La] Margaritis et al., 1997 [13] Placebo-controlled, double-blind, randomized 24 ♂healthy subjects 22.9 ± 2.2 y; 68.0 ± 8.7 Kg; 178.1 ± 6.6 cm; Body fat 11.2 ± 4.9 % PbG n = 12 ♂ 22.5 ± 2.0 y; 67.3 ± 7.0 Kg; 177.4 ± 7.0 cm; Body fat 10.1 ± 4.0% SeG n = 12 ♂ 23.3 ± 2.4 y; 68.8 ± 10.4 kg; 178.8 ± 6.4 cm; Body fat 12.6 ± 4.9 % Supplementation: 180 µg Se (Seleniomethionine) once per day * 10-week period PhA: 10-wk endurance training program, 3 sessions per week Pre-PhA vs. Post-PhA SeG vs. PbG [Se] ↑*[Se] SeG ↓[Se] PbG # SeG vs. PbG GPx plasma ↑*SeG ↑PbG # SeG vs. PbG GPx muscle ↓SeG ↓PbG † SeG vs. PbG Vitamin E ↓SeG ↑PbG † SeG vs. PbG CK ↓SeG ↓PbG † SeG vs. PbG Cyt Ox ↑SeG ↑PbG # SeG vs. PbG SDH ↑SeG ↑PbG † SeG vs. PbG MHC I ↑SeG ↑PbG # SeG vs. PbG MHC II ↓SeG ↓PbG † SeG vs. PbG MHC I-MHC II co-expressed ↑SeG ↑PbG # SeG vs. PbG VO2max ↑*SeG ↑*PbG # SeG vs. PbG VO2total ↑*SeG ↑*PbG # SeG vs. PbG Table 3. Cont. (B) Results and Main Conclusions 9 of 16 Nutrients 2020, 12, 1790 Table 3. Cont. 3.4. Findings of Included Studies (C) Author/s—Year Study Design Population Intervention Analyzed Results Main Conclusions Zamora et al., 1995 [29] Placebo-controlled, double-blind, randomized 24 ♂healthy students; 22.9 ± 2.1 y; 68.0 ± 8.7 Kg; 178.1 ± 6.6 cm; Body fat 11.2 ± 4.4 % PbG n = 12 ♂ 22.5 ± 2.0 y; 67.3 ± 7.0 Kg; 177.4 ± 7.0 cm; Body fat 10.1 ± 3.9 % SeG n = 12 ♂ 23.28 ± 2.36 y; 68.78 ± 10.44 Kg; 178.7 ± 6.3 cm; Body fat 12.3 ± 4.8 % Supplementation: 180 µg Se (Seleniomethionine) once per day * 10-week period PhA: 10-week endurance training programme (3 sessions per week) after a 4-week period of restricted At rest Post-PhA Pre-PhA vs. Post-PhA SeG vs. PbG Pre-PhA vs. Post-PhA SeG vs. PbG Muscle mitochondria morphometric parameters QA Aa â ↑*SelG ↔PbG ↑*SelGr ↔PbG ↔SelGr ↔PbG #SelGr vs PbG #SelGr vs PbG #SelGr vs PbG ↑*SelG ↔PbG ↑*SelG ↔PbG ↔SelGr ↔PbG #SelGr vs PbG ↔SelGr vs PbG #SelGr vs PbG VO2max ↔SelGr ↔PbG † SelGr vs PbG ↔SelGr ↔PbG † SelGr vs PbG Body fat % ↔SelGr ↔PbG † SelGr vs PbG ↔SelGr ↔PbG † SelGr vs PbG BMI Kg*m2 ↔SelGr ↔PbG † SelGr vs PbG ↔SelGr ↔PbG † SelGr vs PbG Tessier et al., 1995 [30] Placebo-controlled, double-blind, randomized 24 ♂healthy; 22.9 ± 2.1 y Supplementation: 240 µg organic selenium (70% selenomethionine) Selenion® once per day *10-week period PhA: 4-week deconditioning period with no training, followed by running endurance training lasting 10 week (3 sessions/week). Pre-PhA vs. Post-PhA SeG vs. 3.4. Findings of Included Studies PbG [Se] ↑*SelG ↓PbG † SelGr vs PbG Vitamin E ↓SelG ↑PbG † SelGr vs PbG GPx muscle PhA cronic ↓SelG ↓PbG † SelGr vs PbG PhA acute ↑*SelG ↓*PbG # SelGr vs PbG ♂: Men; ♀: Women; NW: Normal weight; OW: Over weight; y: Years; Kg: Kilograms; m: Meters; cm: Centimeters; BMI: Body mass index; PhA: Physical activity; Se: Selenium; [Se]: Plasma Selenium levels; ↑*: Statistically significant increase; ↑: Non-statistical increase; ↓*: Statistically significant decrease; ↓: Non-statistical decrease; †: Change without statistical significance; #: Change statistical significance; ↔: Without changes; LH: Lipid hydroperoxidase; GSH: Reduced glutathione; SOD: Superoxide dismutase; TAS: Total antioxidant status; PbG: Placebo group; SeG: Selenium group; GTtotal: Glutathione total; GSSG: Glutathione oxidized; GPx: Glutathione peroxidase; EGPx: Erythrocyte glutathione peroxidase; EGR: Erythrocyte glutathione reductase; VO2max: Maximum oxygen consumption; Tt: Total testosterone; Tf: Testosterone free; [La]: Plasma lactate; CK: Creatine kinase; Cyt Ox: Cytochrome C oxidase; SDH: Succinate dehydrogenase; MCH: Myosin heavy chains; QA: Density of the mitochondria profile; Aa: surface of all the mitochondria profile area; â: mean surface of individual mitochondria profile area. ♂: Men; ♀: Women; NW: Normal weight; OW: Over weight; y: Years; Kg: Kilograms; m: Meters; cm: Centimeters; BMI: Body mass index; PhA: Physical activity; Se: Selenium; [Se]: Plasma Selenium levels; ↑*: Statistically significant increase; ↑: Non-statistical increase; ↓*: Statistically significant decrease; ↓: Non-statistical decrease; †: Change without statistical significance; #: Change statistical significance; ↔: Without changes; LH: Lipid hydroperoxidase; GSH: Reduced glutathione; SOD: Superoxide dismutase; TAS: Total antioxidant status; PbG: Placebo group; SeG: Selenium group; GTtotal: Glutathione total; GSSG: Glutathione oxidized; GPx: Glutathione peroxidase; EGPx: Erythrocyte glutathione peroxidase; EGR: Erythrocyte glutathione reductase; VO2max: Maximum oxygen consumption; Tt: Total testosterone; Tf: Testosterone free; [La]: Plasma lactate; CK: Creatine kinase; Cyt Ox: Cytochrome C oxidase; SDH: Succinate dehydrogenase; MCH: Myosin heavy chains; QA: Density of the mitochondria profile; Aa: surface of all the mitochondria profile area; â: mean surface of individual mitochondria profile area. 4.1. Selenium Supplementation The Se dietary reference intakes (DRI) for north American adult population have been set by the Institute of Medicine at 55 µg (0.7 µmol)/day, while tolerable upper intake levels (UILs) have been set at 400 µg (5.1 µmol)/day. Se levels higher than the UILs (400 µg/day) causes selenosis disease, which manifests itself as an increased breakability of hair and nails [31]. The dose of Se supplementation administered in the selected studies was 180 or 240 µg/day (selenomethionine) [13,26,29,30] and 200 µg/day (sodium selenite) [18,19], which it is very likely that the total Se intake (dietary + supplementation) of the study population did not exceed tolerable upper intake levels. Moreover, some authors have reported that daily Se intakes of 750 to 850 µg did not produce any adverse effects in adults [32]. No side effects of Se supplementation were reported in any of the studies included in this systematic review. Therefore, it seems that daily doses of Se supplementation of 180 µg/day or 240 µg/day of Se supplementation are apparently safe, as reported previously [33]. For Se supplementation, two pharmaceutical forms of Se preparations were used, organic compounds in the form of selenomethionine [13,26,29,30] and inorganic Se salts in the form of sodium selenite [18,19]. Se supplements in the form of organic compounds (selenomethionine) are generally less likely to be toxic and more bioavailable than inorganic salts [33]. However, both organic [13,26,30] and inorganic [19] Se preparations, significantly increased Se plasm levels when compared with the placebo group. Moreover, both organic and inorganic Se supplementation was effective in maintaining optimal physiological levels [13,19,26,30]. This result may be explained because of the high bioavailability of organic and inorganic Se supplements. The bio bioavailability is substantially higher the bioavailability of other antioxidant supplements such as curcumin, which is administered together with piperine as a bioavailability enhancer [7]. The Se supplementation intake of 180 or 240 µg/day (selenomethionine) and 200 µg/day (sodium selenite) may safely be used as an “enhancer” of the antioxidant defense systems. Although the safety of Se supplementation of the aforementioned dosages has been demonstrated, different characteristics such as the pharmaceutical form of Se, duration of treatment, and exercise modality should be taken into account to adjust the dosage of Se supplementation. 3.4. Findings of Included Studies ♂: Men; ♀: Women; NW: Normal weight; OW: Over weight; y: Years; Kg: Kilograms; m: Meters; cm: Centimeters; BMI: Body mass index; PhA: Physical activity; Se: Selenium; [Se]: Plasma Selenium levels; ↑*: Statistically significant increase; ↑: Non-statistical increase; ↓*: Statistically significant decrease; ↓: Non-statistical decrease; †: Change without statistical significance; #: Change statistical significance; ↔: Without changes; LH: Lipid hydroperoxidase; GSH: Reduced glutathione; SOD: Superoxide dismutase; TAS: Total antioxidant status; PbG: Placebo group; SeG: Selenium group; GTtotal: Glutathione total; GSSG: Glutathione oxidized; GPx: Glutathione peroxidase; EGPx: Erythrocyte glutathione peroxidase; EGR: Erythrocyte glutathione reductase; VO2max: Maximum oxygen consumption; Tt: Total testosterone; Tf: Testosterone free; [La]: Plasma lactate; CK: Creatine kinase; Cyt Ox: Cytochrome C oxidase; SDH: Succinate dehydrogenase; MCH: Myosin heavy chains; QA: Density of the mitochondria profile; Aa: surface of all the mitochondria profile area; â: mean surface of individual mitochondria profile area. Nutrients 2020, 12, 1790 10 of 16 10 of 16 4. Discussion The purpose of this study was to determine the impact of Se supplementation on physiological antioxidant defense systems, muscle damage markers, testosterone hormone, and athletic performance in physically active population. The results suggested that Se oral supplementation of 180 µg/day or 240 µg/day (selenomethionine) and 200 µg/day (sodium selenite) decreased LH levels and significantly increased GPx in plasma, erythrocyte, and muscle, but did not suggest to have an effect on cytochrome C oxidase (Cyt Ox), erythrocyte-reduced glutathione (GSH), SOD, glutathione total (GTtotal), glutathione oxidized (GSSG), erythrocyte glutathione reductase (EGR), vitamin E levels, and succinate dehydrogenase (SDH). In addition, the results did not evidence any improvement in sports performance, testosterone hormone levels, CK activity, oxidative enzyme activities, and the expression of muscle fiber type myosin heavy chain (MHC). Se supplementation was observed to have a dampening effect on the mitochondria changes, including the density of the mitochondria profile, the surface of all the mitochondria profile areas, and the mean surface of individual mitochondria profile areas. 4.2. Antioxidant Defense System Prior research has been demonstrated that exercise upregulates erythrocyte GPx activity [34] and may be enhanced with Se supplementation, as it was previously demonstrated by Tessier et al. [26]. The combination of exercise and Se supplementation may suggest a reinforcement of the antioxidant potential. In muscle, GPx activity was observed to increase with exercise [21]. Se supplementation increased blood Se concentrations [30] and this increase may enhance the muscle GPx enzyme activity as it has been previously described in animal models [37] and in acute exercise in humans [30]. However, moderate- or low-endurance exercise did not change muscle GPx enzyme activity between the Se group and placebo group [13,30] and muscle GPx enzyme was not correlated with Se plasma levels [12]. It may be possible that the training intensity, volume, and the frequency of exercise [13,30] were sufficient to induce an upregulation muscle GPx activity to control the OS, but in acute exercise [30] Se supplementation is necessary for antioxidant GPx defense. This may suggest that exercise and Se are linked to erythrocyte GPx [26] or muscle GPx [30] activity, resulting in effects on the development of antioxidant potential, which could result in better protection of membranes at this level (muscle and/or erythrocyte). The intensification in muscle-cell membrane defense may lead lower exercise-induced muscle damage in athletes. Also, OS repercussions on the phospholipid bilayer repair and the integral proteins were associated to erythrocyte cytoskeleton, including Band 3 protein, and they participated in erythrocytes deformability and tissue oxygenation [38]. Therefore, the aforementioned antioxidant effect was a factor that improved the transport and use of oxygen at a muscular level, ehich is particularly important because endurance and aerobic capacity is key for atheltes. Athletes generally have a very demanding training. Intense anv vigorous training may improve sport performance in competitions [4,6]. The generation of radicals and other ROS during exercise in muscle, and the antioxidant defense provided by Se, may establish an interrelationship, in which they may play a key role of Se mineral trace element in exercise performance [35]. Theincrease in GPx in plasma [13,26], erythrocyte [26] or muscle [30] activity may be sensitive to the Se supplementation in the form of selenomethionine with doses between 180–240 µg/day. In this systematic review, we observed the absence of effect of Se supplementation in other molecules related to the enzymatic defense system. 4.2. Antioxidant Defense System The excessive production of ROS exceeds the capacity of neutralization and elimination of the physiological system by altering the homeostatic balance and establishing a state of OS. High concentrations of ROS determine structural modifications in the lipid bilayer of the cellular membranes, nucleic acids, and proteins. In addition, high concentrations of ROS may alter the intracellular signaling pathways by modifying the responses and functions of the cells [34]. The incorporation of Se supplementation may be a practical approach to enhance the antioxidant 11 of 16 Nutrients 2020, 12, 1790 activity of diets because Se is a more powerful antioxidant than vitamin E, vitamin C, vitamin A, or and B-carotene. The Se is an important element of the amino acids selenocysteine and selenomethionine, which have antioxidant activity that support the antioxidant enzymatic defence systems [34,35]. activity of diets because Se is a more powerful antioxidant than vitamin E, vitamin C, vitamin A, or and B-carotene. The Se is an important element of the amino acids selenocysteine and selenomethionine, y pp y y Previous studies have evaluated lipid peroxidation by determining LH concentrations in serum [19]. These authors reported that Se supplementation in overweight adults was effective in increasing plasma Se levels near to recommended levels, and decreased the LH responses at rest and after high-intensity exercise. However, in normal-weight individuals, Se supplementation was not effective to reduce LH concentrations. These results may explained because optimal Se levels maximize the expression of GPx activity, but the overweight group had low Se levels before supplementation, and this is the most likely cause of a compromised GPx antioxidant system. The reduction of LH after Se supplementation may be explained by the activation of the GPx system [19]. Although GPx was not measured, it was likely that GPx antioxidant system activity increased because GPx is part of an antioxidant system to protect from the harmful consequences of LH [36] as it has been described by Burk et al. [20]. y y y from the harmful consequences of LH [36] as it has been described by Burk et al. [20]. p q y Se supplementation increased the activity of plasma GPx in some studies [13,26], which suggests that the relationship between GPx and Se may play an important role in the antioxidant GPx defense that detoxifies excess of ROS. 4.3. Muscle Performance CK activity assessed in blood samples is often used to monitor the levels of muscle damage in exercise [7]. One study [13] reported that CK activities did not significantly differ between pre- and post-training. The absence of change in CK after 200 µg Se (sodium selenite) supplementation may suggest a lack of an antioxidant function that is not able to neutralize ROS produced during the electron transport chain oxidative phosphorylation necessary for energy requirements in physical exercise [7]. The response of human skeletal muscle to endurance training may result of a transformation from histological type II fibers to type I fibers and may induce a decrease in the respiratory mitochondrial activity caused by the production of oxygen-free radicals [39]. In non-trained subjects after 10 weeks of endurance training and a 180 µg of Se (seleniomethionine) supplementation, no effects were observed on exercise training-induced adaptations on oxidative enzyme activities or on expressed muscle myosin heavy chain (MHC) fiber type. Therefore, it may be probably that Se supplementation may have no effect on exercise-induced muscle adaptations. Some studies [21,39] have reported that exercise depressing mitochondrial respiratory capacity may occur due to the interruption of mitochondrial structure. These mithochondrial degradations are compensated by the development of antioxidant defense systems in the cytosol and the membranes such as GPx that is an essential component of the antioxidative capacity of muscle fibers. Zamora et al. [29] reported that 180 µg of Se (seleniomethionine) supplementation may indicate the cushioning effect of the Se on the mitochondria alteration (density of the mitochondria profile; surface of all the mitochondria profile areas). The observation of the muscle biopsies using the electron microscope confirmed these changes in the muscle mitochondria. In addition, quantitative determination of the totality of mitochondria in the muscle fibers was performed [29]. Although the mechanism by which mitochondrial turnover occurs is unknown, it may be related to the enhanced activity of the Se-dependent enzyme GPx. Some authors have reported that the activity of the muscle GPx enzyme increased during prolonged exercise after training with Se supplementation [26,30]. The GPx enzyme may seem to be a powerful component of the muscle antioxidant defense system. A potential mechanism for the suggested dampening effect of Se may rely in the mitochondria biogenesis, which may be a consequence of the increased activity of GPx, avoiding OS-induced cellular degeneration, which occurrs during continuous and strenuous mesocycles of training. 4.2. Antioxidant Defense System This may be partially explained because the adaptive effects of exercise were adequate to induce these enzymes. For the technique of application to quantify total antioxidant status (TAS), Savory et al. [19] proposed a presumed “index of antioxidants”, or diminishing potentiality of biofluids. No differences in TAS were detected between groups, of the study at rest or post-exercise pre- and post-Se supplementation [19]. Although other studies included in this review did not evaluate TAS, we hypothesized that Se did not have had any influence in TAS. The potential explanation for this may rely in the effect of the Se supplementation was only on GPx activity, and overall the antioxidant activity could be the result of all the enzymes involved and not just the individual action of one enzyme. This may suggest that the protection of the cell has to be Nutrients 2020, 12, 1790 12 of 16 12 of 16 guaranteed by a synergistic action of all the antioxidant enzymes and not just only one. In addition, vitamin E plays an antioxidant role in the organism the differences were not detected between control and Se group [13,26,30]. It may result difficult to specify that Se supplementation antioxidant effect because the wide variation in OS reduction following Se supplementation which flow from divergences in study methodology. In addition, the concentration of seleoenzymes dependents on the amount of Se administered, which is prevalent due to the influence of seleno-protein expression. One more important factor is the inter-individual response of selenoenzymes to Se supplementation, which may indicate that the amount of Se should be tailored to each subject, even within the same population group [9,33,36]. 4.5. Athletic Performance Regarding the Se supplementation and athletic performance, Neek et al. [18] found no differences between the control and intervention group among professional cyclists [18]. These findings are reported by other studies that demonstrated that intakes of 180 µg of Se (seleniomethionine) during 10 weeks of endurance training, in healthy students, had no effects on aerobic performance (VO2max) [13,26,29]. Some authors [13] have described correlations between the proportion of type I MHC and VO2max increments which may suggest a relationship between endurance performance capacity and muscle fiber type. Probably, the magnitude of adaptive responses may depend on the quantity of muscle contractile activity during exercise rather than the levels of Se. Other authors [26] have found significant increases in erythrocyte GPx when supplementing with Se and this may be explained the correlation between erythrocyte GPx/VO2max [26]. These results may suggest that the participation of physiological antioxidant potential in the mechanism of development of aerobic performance had no direct effect on VO2max, which only increased after exercise and has been reported previously [29]. Plasma lactate concentration increased with higher levels of exercise and may be useful for monitoring anaerobic training [41]. Se supplementation may boost the antioxidant system when exercising [9]. In animal models, the increase in free radical production and blood lactate concentrations due to acute swimming exercise may be compensate with Se supplementation [36]. However, in a study that included 16 professional cyclists, oral supplemented with 200 µg/day (sodium selenite) had no effects on plasma lactate in pre- and post- exercise [18]. For this reason, the Se supplementation may have no effect on anaerobic glucose metabolism. 4.4. Hormone Response The function of the hypothalamus-pituitary-adrenal axis increases the levels of plasma adrenocorticotropic hormone [7]. In general, continuous and intensive exercise has been reported to induce a dysfunction of the hypothalamic-pituitary-testicular axis, particularly testicular impairment. This dysfunction may cause a suppression of the testosterone (T) secretion during latter stages of exercise. The levels of T hormone is indicative of the degree of anabolism/catabolism of the body and can be used as a biomarker to monitor and optimize athletes’ training loads [40]. T metabolism and testicular morphology may explain the existence of other selenoproteins in the male gonads [3]. Neek et al. [18] observed that 200 µg/day (Sodium Selenite) of Se supplementation during 4 weeks had no effect on levels of total and free T at resting. These researchers additionally observed that 13 of 16 Nutrients 2020, 12, 1790 there were no significant differences in T between intervention and placebo group in pre- and post-exercise. Therefore, Se supplementation did not seem to stimulate the activity of protection against GPx peroxidation (Se-dependent) that is required for the metabolic pathway of T biosynthesis in Leydig cells. T synthesis levels may change depending on the activity of this enzyme. Additionally, only one study [18] assessed the effects of Se supplementation on testosterone hormone response, therefore further studies are needed. 4.7. Limitations and Strengths We acknowledge the following limitations. First, the systematic review included a small number of articles that were conducted quite a time before. In addition, all the studies had a small sample size (mostly men), and only 2 studies reported Se plasma concentrations. Second, the intervention characteristics of the studies such intensity and duration of exercise, timing and dose of Se supplementation, and the number of participants, among many others, were quite different. Consequently, it results difficult to draw strong conclusions on whether Se supplementation is recommended as a sport supplement. On the other hand, this systematic evidences the need of further studies to re-evaluate the effects of long periods of Se supplementation on antioxidant defense system, muscle performance, and hormonal response to determine potential improvements in sports performance. Despite these limitations, the strengths of this systematic review rely in the use of the PRISMA guidelines [27] the McMaster Quantitative Review Form [28]. 5. Conclusions In summary, we found no evidence of beneficial effects of the use of Se supplementation on aerobic or anaerobic athletic performance. However, Se supplementation may contribute to maintain optimal levels in athletes who have significant losses from high-intensity and high-volume exercise and, consequently, reduce chronic exercise-induced oxidative stress. Optimal levels of Se modulate exercise-effect on mitochondrial changes (structure, respiratory) probably because the high efficiency of the Se-dependent enzyme GPx that increased during prolonged exercise. Therefore, Se supplementation may be used as enhancer of antioxidant potential activity in physically active individuals. Author Contributions: D.F.-L. and C.I.F.-L.: conceived and designed the investigation, analyzed and interpreted the data, drafted the paper, and approved the final version submitted for publication. J.S.-C. and J.M.-A.: analyzed and interpreted the data, critically reviewed the paper and approved the final version submitted for publication. L.J.N. and A.C.M.: critically reviewed the paper and approved the final version submitted for publication. All authors have read and agreed to the published version of the manuscript. Funding: The authors declare no funding sources. Funding: The authors declare no funding sources. Acknowledgments: The authors are grateful to the Department of Cellular Biology, Histology and Pharmacology, Faculty of Medicine (Valladolid) and Faculty of Health Sciences (Soria), University of Valladolid for its collaboration in infrastructures, bibliographic bases and computer support. Conflicts of Interest: The authors declare no conflict of interest. Conflicts of Interest: The authors declare no conflict of interest. 4.6. Practical Applications In general, the selected studies suggest that the use of Se as a supplement may decrease the lipid peroxidation generated by an intense and continuous physical activity. However, there was no evidence of improvement on athlete performance. Although Se supplementation did not demonstrate beneficial effects on athletic performance, Se supplementation may be required to maintain optimal levels of Se, and prevent negative health outcomes of the athletes [42]. In athletes, several etiological factors such as gastrointestinal loss, increased loss of Se through sweating and urine, intestinal malabsorption, and malnutrition may explain the storage depletion of Se, which may lead to deficiencies in Se [18,34]. Health problems related to Se deficiency have been described in athletes with vigorous and strenuous training [4]. Therefore, Se supplementation may be a simple approach to reduce chronic oxidative stress among individuals with Se deficiency [19]. Furthermore, the Se supplementation may be beneficial for athletes because it may reinforce the antioxidant potential activity by increasing the level of GPx in erythrocytes [26] or muscles [13,30], and increase plasma Se concentration [13,26,30]. Moreover, Se supplementation may prevent some diseases such as Keshan disease (KD), an endemic cardiomyopathy that is exclusively manifested in China among populations with Se deficiency [43]. Moreover, Se supplementation in athletes who usually perform high-intensity exercise training may prevent low levels of immune system, and consequently, decrease the risk of infection [44]. Therefore, Se might be hypothesized as a strategy to prevent emerging viral diseases, such as COVID-19. The immunomodulatory properties of Se, together with the ability to limit the mutation and progression of the virus, may suggest that optimal levels of Se in the blood may have positive effects against COVID-19 [45]. Nutrients 2020, 12, 1790 14 of 16 14 of 16 On the other hand, we believe that more studies performed among athletes are needed. Athletes may be very susceptible to Se defficiens because their vigorous and intense practices. Special caution should be noted when recommending Se supplementation. Elevated levels of Se may cause toxicityand induce excessive mitochondrial oxidative stress, leading to organelle damage and dysfunction [2]. In this review none of the selected studies [13,18,19,26,29,30] reported any side effects of Se supplementation among the participants. References 1. Vatansever, R.; Ozyigit, I.I.; Filiz, E. Essential and beneficial trace elements in plants, and their transport in roots: A review. Appl. Biochem. Biotechnol. 2017, 181, 464–482. [CrossRef] 2. Mehdi, Y.; Hornick, J.-L.; Istasse, L.; Dufrasne, I. Selenium in the environment, metabolism and involvement in body functions. Molecules 2013, 18, 3292–3311. [CrossRef] 3. Behne, D.; Weiler, H.; Kyriakopoulos, A. Effects of selenium deficiency on testicular morphology and function in rats. J. Reprod. Fertil. 1996, 106, 291–297. [CrossRef] p 4. Heffernan, S.M.; Horner, K.; De Vito, G.; Conway, G.E. The role of mineral and trace element supplementation in exercise and athletic performance: A systematic review. Nutrients 2019, 11, 696. [CrossRef] 15 of 16 Nutrients 2020, 12, 1790 5. Speich, M.; Pineau, A.; Ballereau, F. Minerals, trace elements and related biological variables in athletes and during physical activity. Clin. Chim. Acta 2001, 312, 1–11. [CrossRef] 6. Seo, D.-Y.; Heo, J.-W.; Ko, J.R.; Kwak, H.-B. Exercise and neuroinflammation in health and disease. Int. Neurourol. J. 2019, 23, S82. [CrossRef] 7. Fernández-Lázaro, D.; Mielgo-Ayuso, J.; Seco Calvo, J.; Córdova Martínez, A.; Caballero García, A.; Fernandez-Lazaro, C.I. Modulation of Exercise-Induced Muscle Damage, Inflammation, and Oxidative Markers by Curcumin Supplementation in a Physically Active Population: A Systematic Review. Nutrients 2020, 12, 501. [CrossRef] 8. Zoidis, E.; Seremelis, I.; Kontopoulos, N.; Danezis, G.P. Selenium-Dependent Antioxidant Enzymes: Actions and Properties of Selenoproteins. Antioxidants 2018, 7, 66. [CrossRef] 9. Ranchordas, M.K.; Rogerson, D.; Soltani, H.; Costello, J.T. Antioxidants for preventing and reducing muscle soreness after exercise. Cochrane Database Syst. Rev. 2017. [CrossRef] 10. Cisnero Prego, E.; Pupo Balboa, J.; Céspedes Miranda, E. Enzimas que participan como barreras fisiológicas para eliminar los radicales libres: III. Glutatión peroxidasa. Rev. Cuba. Investig. Biomed. 1997, 1, 10–15. 11. Cisneros Prego, E. La glutatión reductasa y su importancia biomédica. Rev. Cuba. Investig. Biome 14, 10–12. 12. García Triana, B.; García Morales, O.; Clapes Hernández, S.; Rodes Fernández, L.; García Piñeiro, J.C. Enzimas que participan como barreras fisiológicas para eliminar los radicales libres: I. Superóxido dismutasas. Rev. Cuba. Investig. Biomed. 1995, 14, 15–21. 13. Margaritis, I.; Tessier, F.; Prou, E.; Marconnet, P.; Marini, J. Effects of endurance training on skeletal muscle oxidative capacities with and without selenium supplementation. J. Trace Elem. Med. Biol. 1997, 11, 37–43. [CrossRef] 14. Córdova, A.; Mielgo-Ayuso, J.; Fernandez-Lazaro, C.I.; Caballero-García, A.; Roche, E.; Fernández-Lázaro, D. 26. Tessier, F.; Margaritis, I.; Richard, M.-J.; Moynot, C.; Marconnet, P. Selenium and training effects on the glutathione system and aerobic performance. Med. Sci. Sports Exerc. 1995, 27, 390–396. [CrossRef] References Law, M.; Stewart, D.; Letts, L.; Pollock, N.; Bosch, J.; Westmorland, M. Guidelines for Critical Review Form—Quantitative Studies 1998; McMaster University: Hamilton, ON, Canada, 2008. 29. Zamora, A.; Tessier, F.; Marconnet, P.; Margaritis, I.; Marini, J.-F. Mitochondria changes in human muscle after prolonged exercise, endurance training and selenium supplementation. Eur. J. Appl. Physiol. Occup. Physiol. 1995, 71, 505–511. [CrossRef] 30. Tessier, F.; Hida, H.; Favier, A.; Marconnet, P. Muscle GSH-Px activity after prolonged exercise, training, and selenium supplementation. Biol. Trace Elem. Res. 1995, 47, 279–285. [CrossRef] 31. Hays, S.M.; Macey, K.; Nong, A.; Aylward, L.L. Biomonitoring Equivalents for selenium. Regul. Toxicol. Pharmacol. 2014, 70, 333–339. [CrossRef] 32. Yang, G.; Yin, S.; Zhou, R.; Gu, L.; Yan, B.; Liu, Y. Studies of safe maximal daily dietary Se-intake in a seleniferous area in China. Part II: Relation between Se-intake and the manifestation of clinical signs and certain biochemical alterations in blood and urine. J. Trace Elem. Electrolytes Health Dis. 1989, 3, 123–130. [PubMed] 33. Schrauzer, G.N. Nutritional selenium supplements: Product types, quality, and safety. J. Am. Co 2001, 20, 1–4. [CrossRef] [PubMed] 34. Brenneisen, P.; Steinbrenner, H.; Sies, H. Selenium, oxidative stress, and health aspects. Mol. Aspects Med. 2005, 26, 256–267. [CrossRef] 35. Klotz, L.-O.; Kröncke, K.-D.; Buchczyk, D.P.; Sies, H. Role of copper, zinc, selenium and tellurium in the cellular defense against oxidative and nitrosative stress. J. Nutr. 2003, 133, 1448S–1451S. [CrossRef] [PubMed] 36. Akil, M.; Gurbuz, U.; Bicer, M.; Sivrikaya, A.; Mogulkoc, R.; Baltaci, A.K. Effect of selenium supplementation on lipid peroxidation, antioxidant enzymes, and lactate levels in rats immediately after acute swimming exercise. Biol. Trace Elem. Res. 2011, 142, 651–659. [CrossRef] [PubMed] 37. Brady, P.S.; Brady, L.J.; Ullrey, D.E. Selenium, vitamin E and the response to swimming stress in the rat. J. Nutr. 1979, 109, 1103–1109. [CrossRef] 8. Morabito, R.; Remigante, A.; Marino, A. Melatonin Protects Band 3 Protein in Human Erythrocytes aga H2O2-Induced Oxidative Stress. Molecules 2019, 24, 2741. [CrossRef] 39. Egan, B.; Zierath, J.R. Exercise metabolism and the molecular regulation of skeletal muscle adaptation. Cell Metab. 2013, 17, 162–184. [CrossRef] 40. Fernández-Landa, J.; Fernández-Lázaro, D.; Calleja-González, J.; Caballero-García, A.; Córdova, A.; León-Guereño, P.; Mielgo-Ayuso, J. Long-Term Effect of Combination of Creatine Monohydrate Plus β-Hydroxy β-Methylbutyrate (HMB) on Exercise-Induced Muscle Damage and Anabolic/Catabolic Hormones in Elite Male Endurance Athletes. Biomolecules 2020, 10, 140. [CrossRef] 41. Mujika, I. References Effect of iron supplementation on the modulation of iron metabolism, muscle damage biomarkers and cortisol in professional cyclists. Nutrients 2019, 11, 500. [CrossRef] 15. Alfredo, C.; Diego, F.; Juan, M.; Calvo, S.; Jesús, C.G.A. Effect of magnesium supplementation on muscular damage markers in basketball players during a full season. J. Magnes. Res. 2017, 30, 61–70. 6. Rotruck, J.T.; Pope, A.L.; Ganther, H.E.; Swanson, A.; Hafeman, D.G.; Hoekstra, W. Selenium: Biochem role as a component of glutathione peroxidase. Science 1973, 179, 588–590. [CrossRef] p g p 17. Neve, J. Human selenium supplementation as assessed by changes in blood selenium concentration and glutathione peroxidase activity. J. Trace Elem. Med. Biol. 1995, 9, 65–73. [CrossRef] 18. Neek, L.S.; Gaeini, A.A.; Choobineh, S. Effect of zinc and selenium supplementation on serum testosterone and plasma lactate in cyclist after an exhaustive exercise bout. Biol. Trace Elem. Res. 2011, 144, 454–462. [CrossRef] 19. Savory, L.A.; Kerr, C.J.; Whiting, P.; Finer, N.; McEneny, J.; Ashton, T. Selenium supplementation and exercise: Effect on oxidant stress in overweight adults. Obesity 2012, 20, 794–801. [CrossRef] 20. Burk, R.F. Protection against free radical injury by selenoenzymes. Pharmacol. Ther. 1990, 45, 383–385. [CrossRef] 21. Bloomer, R.J.; Falvo, M.J.; Schilling, B.K.; Smith, W.A. Prior exercise and antioxidant supplementation: Effect on oxidative stress and muscle injury. J. Int. Soc. Sports Nutr. 2007, 4, 9. [CrossRef] [PubMed] 22. Gomez-Cabrera, M.C.; Salvador-Pascual, A.; Cabo, H.; Ferrando, B.; Viña, J. Redox modulation of mitochondriogenesis in exercise. Does antioxidant supplementation blunt the benefits of exercise training? Free Radic. Biol. Med. 2015, 86, 37–46. [CrossRef] 23. Kanter, M.M. Free radicals, exercise, and antioxidant supplementation. Int. J. Sport Nutr. Exerc. Metab. 1994, 4, 205–220. [CrossRef] 24. Urso, M.L.; Clarkson, P.M. Oxidative stress, exercise, and antioxidant supplementation. Toxicology 2003, 189, 41–54. [CrossRef] 25. Manzanares Castro, W. Selenium in critical patients with systemic inflammatory response. Nutr. Hosp. 2007, 22, 295–306. 26. Tessier, F.; Margaritis, I.; Richard, M.-J.; Moynot, C.; Marconnet, P. Selenium and training effects on the glutathione system and aerobic performance. Med. Sci. Sports Exerc. 1995, 27, 390–396. [CrossRef] 16 of 16 Nutrients 2020, 12, 1790 16 of 16 27. Liberati, A.; Altman, D.G.; Tetzlaff, J.; Mulrow, C.; Gøtzsche, P.C.; Ioannidis, J.P.; Clarke, M.; Devereaux, P.J.; Kleijnen, J.; Moher, D. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. PLoS Med. 2009, 151, W-65–W-94. References Quantification of training and competition loads in endurance sports: Methods and applications. Int. J. Sports Physiol. Perform. 2017, 12, S29–S217. [CrossRef] 42. Pingitore, A.; Lima, G.P.P.; Mastorci, F.; Quinones, A.; Iervasi, G.; Vassalle, C. Exercise and oxidative stress: Potential effects of antioxidant dietary strategies in sports. Nutrition 2015, 31, 916–922. [CrossRef] [PubMed] 42. Pingitore, A.; Lima, G.P.P.; Mastorci, F.; Quinones, A.; Iervasi, G.; Vassalle, C. Exercise and oxidative stress: Potential effects of antioxidant dietary strategies in sports. Nutrition 2015, 31, 916–922. [CrossRef] [PubMed] 43. Zhou, H.; Wang, T.; Li, Q.; Li, D. Prevention of Keshan disease by selenium supplementation: A systematic review and meta-analysis. Biol. Trace Elem. Res. 2018, 186, 98–105. [CrossRef] [PubMed] 43. Zhou, H.; Wang, T.; Li, Q.; Li, D. Prevention of Keshan disease by selenium supplementation: A systematic review and meta-analysis. Biol. Trace Elem. Res. 2018, 186, 98–105. [CrossRef] [PubMed] 44. Simpson, R.J.; Kunz, H.; Agha, N.; Graff, R. Exercise and the Regulation of Immune Functions. Prog. Mol. Biol. Transl. Sci. 2015, 135, 355–380. [PubMed] 45. Kieliszek, M.; Lipinski, B. Selenium supplementation in the prevention of coronavirus infections (COVID-19). Med. Hypotheses 2020, 143, 109878. [CrossRef] © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
https://openalex.org/W2037350170
https://europepmc.org/articles/pmc2515304?pdf=render
English
null
Mourning and melancholia revisited: correspondences between principles of Freudian metapsychology and empirical findings in neuropsychiatry
Annals of general psychiatry
2,008
cc-by
22,407
Published: 24 July 2008 Annals of General Psychiatry 2008, 7:9 doi:10.1186/1744-859X-7-9 This article is available from: http://www.annals-general-psychiatry.com/content/7/1/9 © 2008 Carhart Harris et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. BioMed Central BioMed Central Abstract Freud began his career as a neurologist studying the anatomy and physiology of the nervous system, but it was his later work in psychology that would secure his place in history. This paper draws attention to consistencies between physiological processes identified by modern clinical research and psychological processes described by Freud, with a special emphasis on his famous paper on depression entitled 'Mourning and melancholia'. Inspired by neuroimaging findings in depression and deep brain stimulation for treatment resistant depression, some preliminary physiological correlates are proposed for a number of key psychoanalytic processes. Specifically, activation of the subgenual cingulate is discussed in relation to repression and the default mode network is discussed in relation to the ego. If these correlates are found to be reliable, this may have implications for the manner in which psychoanalysis is viewed by the wider psychological and psychiatric communities. Annals of General Psychiatry Open Access Review Email: Robin L Carhart-Harris* - R.carhart-harris@bris.ac.uk; Helen S Mayberg - hmayber@emory.edu; Andrea L Malizia - Andrea.L.Malizia@bristol.ac.uk; David Nutt - david.j.nutt@bris.ac.uk * Corresponding author Received: 2 February 2008 Accepted: 24 July 2008 Page 1 of 23 (page number not for citation purposes) Background The physiological events do not cease as soon as the psychical ones begin; on the contrary, the physiological chain contin- ues. What happens in simply that, after a certain point in time, each (or some) of its links has a psychical phe- nomena corresponding to it. Accordingly, the psychi- cal is a process parallel to the physiological – "a dependent concomitant"' [9]. This paper will begin with an overview of some key con- cepts of Freudian metapsychology (libido, cathexis, object cathexis, the ego, the super ego, the id, the unconscious, the primary and secondary psychical process and repres- sion) and an attempt will be made to hypothesise their physiological correlates. This will be followed by a sum- mary of 'Mourning and melancholia' and an extensive look at relevant findings in neuropsychiatry. Of special interest are neuroimaging findings in depression and induced depressed mood, deep brain stimulation (DBS) of the subgenual cingulate (Brodmann area 25/Cg25) for the treatment of intractable depression, electrical stimula- tion of medial temporal regions, and regional atrophy and glial loss in the brains of patients suffering from major depression. Integrating psychoanalysis with modern neuroscience is a difficult and controversial endeavour. It should be made clear from the outset what we believe it is possible for this approach to achieve. Psychoanalysis can be viewed on two levels: a hermeneutic, interpretative or meaning based level; and a metapsychological, mental process based level. The hermeneutic level is inherently subjective. The ques- tion has often been raised whether it is possible to identify spatiotemporal coordinates of subjective meaning. This view was shared by Paul McLean in his seminal book 'The triune brain in evolution' [10]: Before beginning, it is important to make a few brief com- ments on the principle of psycho-physical parallelism. Drawing connections between psychological and biologi- cal phenomena was an approach that Freud was both crit- ical of: 'Since the subjective brain is solely reliant on the deri- vation of immaterial information, it can never estab- lish an immutable yardstick of its own...Information is information, not matter or energy' [10]. It would be incorrect to align this position with dualism. Psychophysical parallelism is a materialist approach that acknowledges that meaning arises through time between networks of communicative systems. Background It must be stated that the evidence cited in this paper cannot logically vali- date psychoanalysis on the hermeneutic level and neither does it provide evidence for the efficacy of psychoanalysis as a treatment modality (see [11] for a review). What we believe it can do, however, is bring together converging lines of enquiry in support of the Freudian topography of the mind. The findings cited below describe changes in physiological processes paralleling changes in psycholog- ical processes; however, the objective measures do not shed any light on the specific content or meaning held within these processes. Aside from interpretation, much of Freud's work was spent theorising about dynamic psy- chical processes; energies flowing into and out of mental provinces, energy invested, dammed up and discharged throughout the mind. It is this metapsychological level of psychoanalysis that we believe is most accessible to inte- gration with modern neuroscience. 'I shall carefully avoid the temptation to determine psychical locality in any anatomical fashion' [5]. 'Every attempt to discover a localisation of mental processes...has miscarried completely. The same fate would await any theory that attempted to recognise the anatomical position of the system [consciousness] – as being in the cortex, and to localise the uncon- scious processes in the subcortical parts of the brain. There is a hiatus here which at present cannot be filled, nor is it one of the tasks of psychology to fill it. Our psychical topography has for the present nothing to do with anatomy' [6]. And receptive to: 'All our provisional ideas in psychology will presuma- bly some day be based on an organic substructure' [7]. The ambiguity in Freud's position can be explained by his criticism of the modular or 'segregationist' [8] approach and preference for a more dynamic model [9]. Essentially, Freud was opposed to 'flag polling' the anatomical causes of psychological phenomena but not the drawing of par- allels between psychological and physiological processes: Background ory to the illness of depression. It is the task of this paper to parallel the psychological processes described by Freud with the physiological processes identified by modern clinical research in order to furnish a more comprehensive understanding of the whole phenomenon. g 'When some new idea comes up in science, which is hailed at first as a discovery and is also as a rule dis- puted as such, objective research soon afterwards reveals that after all it was in fact no novelty' [1]. The intention of this paper is to draw attention to consist- encies between Freudian metapsychology and recent find- ings in neuropsychiatry, especially those relating to depression. A case will be made that findings in neuroim- aging and neurophysiology can provide a fresh context for some of the most fundamental theories of psychoanalysis. In his famous paper 'Mourning and melancholia', Freud carried out an elegant application of psychoanalytic the- Under the tutelage of Meynert, Freud began his career as neurologist studying the anatomy and physiology of the medulla. Inspired by a Helmholtzian tradition (1821– 1894) and a 'psycho-physical parallelism' made fashiona- ble by the likes of Hering (1838–1918), Sherrington (1857–1952) and Hughlings-Jackson (1835–1911), Freud began to consider more seriously how a science of movements of energy in the brain might account for psy- Page 1 of 23 (page number not for citation purposes) Page 1 of 23 (page number not for citation purposes) Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 chological phenomena [2]. It has been argued that Freud never truly abandoned his physiological roots [3,4] and that his early flirtations with psycho-physical parallelism continued to haunt 'the whole series of [his] theoretical works to the very end' [4]. 'It is probable that the chain of physiological events in the nervous system does not stand in a causal connec- tion with the psychical events. The physiological events do not cease as soon as the psychical ones begin; on the contrary, the physiological chain contin- ues. What happens in simply that, after a certain point in time, each (or some) of its links has a psychical phe- nomena corresponding to it. Accordingly, the psychi- cal is a process parallel to the physiological – "a dependent concomitant"' [9]. 'It is probable that the chain of physiological events in the nervous system does not stand in a causal connec- tion with the psychical events. p Libido 'Libido means in psycho-analysis in the first instance the force (thought of as quantitatively variable and Page 2 of 23 (page number not for citation purposes) Page 2 of 23 (page number not for citation purposes) http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 Annals of General Psychiatry 2008, 7:9 measurable) of the sexual drives directed towards an object – "sexual" in the extended sense required by analytic theory' [12]. object cathexis which manifests in depression as anhedo- nia (see Hypofrontality below). As will be discussed in the next section, activation of the DLPFC is accompanied by a deactivation in a network of regions known as the default- mode network (DMN) [19]. The DMN is highly active during resting cognition. The regions engaged during active cognition are referred to here as the object-oriented network (ON). We propose that activation in the ON and deactivation in the DMN correlates with the process of object cathexis. From its earliest recorded use [13] the term 'libido' was used to connote the principal energy of the nervous sys- tem. Freud differentiated 'libido' from a more general 'psychical energy': 'We have defined the concept of libido as a quantita- tively variable force which could serve as a measure of processes and transformations occurring in the field of sexual excitation. We distinguish this libido in respect of its special origin from the energy which must be supposed to underlie the mental processes in general' [14]. 4. A reservoir of libido: 'Thus we form the idea of there being an original libid- inal cathexis of the ego, from which some is later given off to objects' [7]. 3. A nucleus of somatic cohesion: 'The ego is first and foremost a bodily ego' [1]. 'The ego is first and foremost a bodily ego' [1]. 'The ego is first and foremost a bodily ego' [1]. Cathexis h G 'It is certain that much of the ego is itself unconscious and notably what we may call its nucleus; only a small part of it is covered by the term "preconscious"' [20]. The German original 'Besetzung' literally translates as 'occupation', 'filling' or 'investment'. The neologism 'cathexis' was one that Freud was not especially fond of [16]. Freud first used the term on an explicitly physiolog- ical level, referring to neurons 'cathected with a certain quantity [of energy]' [2], systems 'loaded with a sum of excitation' [17] and 'provided with a quota of affect' [18]. Succinctly, the term 'cathexis' means 'libidinal invest- ment'. It is a vitally important concept for the integration of Freudian metapsychology with principles of modern neuroscience. In this paper, we discuss changes in haemo- dynamic response and other neurophysiological meas- ures in relation to the withdrawal and investment of libido. 3. A nucleus of somatic cohesion: 3. A nucleus of somatic cohesion: 1. A referent to the conscious sense of self: ' [I]n each individual there is a coherent organisation of mental processes; and this we call his ego. It is to this ego that consciousness is attached' [1]. 2. An unconscious force maintaining self-cohesion: Object cathexis The concept of "the object" is used in a broad sense in psy- choanalysis to refer to literal, abstract and symbolic objects. People, tasks, work and ideas can all serve as objects. The process of object cathexis can be compared with the process of goal-directed cognition, since both require libidinal investment. Based on neuroimaging data in depression (see Neuropsychiatric findings in depres- sion correlated with principles of Freudian metapsychol- ogy below), we propose that activation of the dorsolateral prefrontal cortex (DLPFC) correlates with object cathexis, and reduced DLPFC activation correlates with reduced 5. The primary agent of repression: The ego h The German original 'das Ich' literally translates as 'the I'. It is somewhat regrettable that Freud's terms have not been translated more literally since the originals have an appeal that is lost in translation. Freud used the concept of the ego in a number of different ways; a useful way of gaining a sense of the different applications therefore, is to cite some examples of its use: Freud's extended use of the term 'sexual' brought him into conflict with Jung, who argued that the principal energy of the nervous system was not inherently sexual [15]. Argua- bly, the two perspectives are not irreconcilable. We may view Freud's 'libido' in connection with the motivational drive system (see The id below) and the withdrawal and investment of cerebral energy (see The ego below). Jung's 'psychical energy' can be viewed less specifically as cere- bral energy in general. Freud's extended use of the term 'sexual' brought him into conflict with Jung, who argued that the principal energy of the nervous system was not inherently sexual [15]. Argua- bly, the two perspectives are not irreconcilable. We may view Freud's 'libido' in connection with the motivational drive system (see The id below) and the withdrawal and investment of cerebral energy (see The ego below). Jung's 'psychical energy' can be viewed less specifically as cere- bral energy in general. 1. A referent to the conscious sense of self: 5. The primary agent of repression: A recent analysis in a large sample of healthy volunteers has shown that connectivity within the DMN undergoes a marked increase with maturation from childhood to adulthood [31]. Activity in the mPFC node of the DMN has been closely associated with self-reflection (e.g. [22,24,27,32]) and recent evidence suggests that the mPFC exerts the principal causality within the network [33]. The PCC and IPL have been associated with propri- oception [34,35] and the PCC and medial temporal regions have been associated with the retrieval of autobi- ographical memories [36-39]. The DMN shows a high level of functional connectivity at rest [28,33]. Activity in this network consistently decreases during engagement in goal-directed cognition [28,33,40] and connectivity within the network tends to decrease during states of reduced consciousness [41,42]. Expressed in Freudian terms, goal-directed cognition requires a displacement of libido (energy) from the ego's reservoir (the DMN) and its investment in objects (activation of the DLPFC). There is evidence that this function is impaired in a number of psychiatric disorders, including depression [43-48]. In addition to the mPFC and PCC nodes of the DMN and their relation to the ego, we speculate on the basis of neu- roimaging data and findings from deep brain stimulation (see Neuropsychiatric findings in depression correlated with principles of Freudian metapsychology below), that ventromedial PFC (vmPFC) exerts a strong repressive hold over emotional and motivational ('visceromotor') centres [50]. This repressive force is the most primitive function of the ego. As will be elaborated later, the posterior vmPFC plays a major role in the pathophysiology of depression. For example, inhibition of the region ventral to the genu of the copus callosum, the subgenual cingu- late or Cg25 has been found to alleviate depressive symp- tomology in patients suffering from treatment resistant depression (TRD) [51]. The subgenual cingulate and regions proximal to it appear to exert a modulatory influ- ence over key 'visceromotor' centres such as the amygdala, the ventral tegmental area (VTA) and the nucleus accumbens (NAc) [50,52]. Certain limbic centres (e.g., the amygdala) have been shown to be pathologically active in depression (see [50] for a review). 5. The primary agent of repression: ' [T]he ego is the power that sets repression in motion' [12]. Given the many different functions to the ego, it would be counterintuitive to suggest that it is 'housed' in a single given region of the brain. Based on a large number of neu- roimaging studies, we propose that a highly connected network of regions, principally incorporating the medial Page 3 of 23 (page number not for citation purposes) Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 'The ego is a great reservoir from which the libido that is destined for objects flows out and into which it flows back from those objects' [49]. 'The ego is a great reservoir from which the libido that is destined for objects flows out and into which it flows back from those objects' [49]. prefrontal cortex (mPFC), posterior cingulate cortex (PCC), inferior parietal lobule (IPL) and medial temporal regions [19,21-31] meets many of the criteria of the Freudian ego. This conglomeration of activity has been named the 'default mode network' [19] (Figure 1). A recent analysis in a large sample of healthy volunteers has shown that connectivity within the DMN undergoes a marked increase with maturation from childhood to adulthood [31]. Activity in the mPFC node of the DMN has been closely associated with self-reflection (e.g. [22,24,27,32]) and recent evidence suggests that the mPFC exerts the principal causality within the network [33]. The PCC and IPL have been associated with propri- oception [34,35] and the PCC and medial temporal regions have been associated with the retrieval of autobi- ographical memories [36-39]. The DMN shows a high level of functional connectivity at rest [28,33]. Activity in this network consistently decreases during engagement in goal-directed cognition [28,33,40] and connectivity within the network tends to decrease during states of reduced consciousness [41,42]. Expressed in Freudian terms, goal-directed cognition requires a displacement of libido (energy) from the ego's reservoir (the DMN) and its investment in objects (activation of the DLPFC). There is evidence that this function is impaired in a number of psychiatric disorders, including depression [43-48]. prefrontal cortex (mPFC), posterior cingulate cortex (PCC), inferior parietal lobule (IPL) and medial temporal regions [19,21-31] meets many of the criteria of the Freudian ego. This conglomeration of activity has been named the 'default mode network' [19] (Figure 1). Page 4 of 23 (page number not for citation purposes) The ego ideal/super ego The concept of the 'ego ideal' was introduced by Freud in his paper 'On narcissism' [7], forming the basis of what Regions positively correlated with the default mode network (orange), most notably the medial prefrontal cortex (mPFC), pos- terior cingulate cortex (PCC), inferior parietal lobule and medial temporal regions Figure 1 Regions positively correlated with the default mode network (orange), most notably the medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), inferior parietal lobule and medial temporal regions. Activity in these regions has been shown to decrease during the performance of goal-directed cognition. The areas shown in blue are negatively correlated with the default mode network (DMN) and may be described as an object-oriented network (ON). The ON is consistently activated during goal-directed cognitions but is relatively inactive at rest. It is argued in the present work that the DMN is functionally consistent with the Freudian ego. Image reproduced with permission from http://www.blackwell- synergy.com[289]. Regions positively correlated with the default mode network (orange), most notably the medial prefrontal cortex (mPFC), pos terior cingulate cortex (PCC), inferior parietal lobule and medial temporal regions Figure 1 Regions positively correlated with the default mode network (orange), most notably the medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), inferior parietal lobule and medial temporal regions. Activity in these regions has been shown to decrease during the performance of goal-directed cognition. The areas shown in blue are negatively correlated with the default mode network (DMN) and may be described as an object-oriented network (ON). The ON is consistently activated during goal-directed cognitions but is relatively inactive at rest. It is argued in the present work that the DMN is functionally consistent with the Freudian ego. Image reproduced with permission from http://www.blackwell- synergy.com[289]. Page 4 of 23 (page number not for citation purposes) Page 4 of 23 (page number not for citation purposes) http://www.annals-general-psychiatry.com/content/7/1/9 Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 ego above) may parallel the experience of pursuing an ideal and judging how successfully it is met. would later become 'the super ego' [1] (German original = 'Das über-Ich'; 'the over-I'). The ego ideal/super ego plays a fundamental role in the aetiology of depression: would later become 'the super ego' [1] (German original = 'Das über-Ich'; 'the over-I'). Freud described this more fully in the following passage: Freud described this more fully in the following passage: 'The ego ideal is...the target of the self-love which was enjoyed in childhood by the actual ego. The subject's narcissism makes its appearance displaced on to this new ideal ego, which like the infantile ego finds itself possessed of every perfection that is of value. As always where the libido is concerned, man has here shown himself incapable of giving up a satisfaction he had once enjoyed. He is not willing to forgo the narcissistic perfection of his childhood; and when as he grows up, he is disturbed by the admonitions of others and by the awakening of his own critical judgement, so that he can no longer retain that perfection, he seeks to recover it in the new form of an ideal. What he projects before him as his ideal is the substitute for the lost nar- cissism of his childhood in which he was his own ideal' [7]. The super ego's control over the ego gives it a unique power to influence the motility and expression of the drives. Impassioned behaviours deemed dangerous to the ego in the context of its environment may be denied expression by activating Cg25 and the DMN. Integrating this hypothesis into a model of depression, we can postu- late that activating Cg25 and the DMN controls the full expression of affective, mnemonic and motivational behaviours promulgated by visceromotor centres. Thus, engaging Cg25 contains limbic activity within paralimbic- thalamic circuits maintained by the Cg25 in reaction to sustained limbic arousal (for relevant models, see [46,50,55-58]). It is difficult to postulate a neurodynamic correlate of such a high-level concept as the ego ideal or super ego. The fol- lowing model should therefore be considered speculative and preliminary. The super ego might be thought of as an umbrella term for high-level cognitions that work to appraise the ego's ability to meet an imagined ideal. This ideal-ego or 'ego ideal' is acquired through an internalisa- tion of value judgements of others (e.g., one's early care givers) under social and environmental demands (see Mourning and melancholia below). Through the super ego, the ego receives feedback on how closely it corre- sponds with an imagined ideal. Freud described this more fully in the following passage: If the super ego judges the ego as falling short of this ideal, or if the super ego judges the ego's or the id's drives as unhealthy or dangerous in the context of its social environment, then the ego may repel these drives, withholding them from consciousness. The implications of the super ego's instruction to repress will be discussed in the next section in relation to depres- sion. The ego ideal/super ego The ego ideal/super ego plays a fundamental role in the aetiology of depression: In relation to the unconscious, punishing aspect of the super-ego it might be useful to consider the role of the anterior cingulate (ACC). Activation of the ACC has been associated with error detection and guilt [8,53,54]. It may be significant that a recent analysis of functional connec- tivity in the human cingulate revealed strong connectivity between the ACC and the DLPFC [54]. Conversely, Cg25 was found to be strongly connected with regions of the DMN such as the OFC. It is possible that feedback between the DLPFC and the mPFC is mirrored at a lower level by feedback between the ACC, OFC and Cg25. Feed- back between the ON and DMN likely takes place via cor- tico-striato-pallido-thalamo-cortical circuitry. 'Repression, we have said, proceeds from the ego, we might say with greater precision that it proceeds from the self-respect of the ego' [7]. The id h The German original 'das es' literally translates as 'the it'. As with the German word for the ego (das Ich), the origi- nal word for the id has an appeal that is lost in translation. The id was one of Freud's later concepts, being introduced in his paper 'The ego and the id' [1]. Some have argued that the id is synonymous with the unconscious, and it is true that two are closely related: 'The id and the unconscious are as intimately linked as the ego and the preconscious' [59]. 'The truth is that it is not only the psychically repressed that remains alien to our consciousness, but also some of the impulses which dominate our ego' [6]. Although the id and the unconscious are related, they also retain some important differences, both psychologically and physiologically. Essentially, the id refers to the uncon- scious as a system in a topographical sense [60]. Freud described the id as an archaic psychical system governed by primitive drives. It is highly unlikely that the ego ideal/super ego is housed in any specific region of the brain but we may speculate about dynamic physiological processes paralleling psy- chological ones. Thus, paralleling the super ego's value judgements of the ego may be feedback between the DLPFC of the ON and the mPFC of the DMN. Informa- tion communicated between these two systems (see The It is highly unlikely that the ego ideal/super ego is housed in any specific region of the brain but we may speculate about dynamic physiological processes paralleling psy- chological ones. Thus, paralleling the super ego's value judgements of the ego may be feedback between the DLPFC of the ON and the mPFC of the DMN. Informa- tion communicated between these two systems (see The Page 5 of 23 (page number not for citation purposes) Page 5 of 23 (page number not for citation purposes) http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 'We now distinguish in our mental life (which we regard as an apparatus compounded of several agen- cies, districts or provinces) one region which we call the ego proper and another which we name the id. The id is the older of the two; the ego has developed out of it, like a cortical layer, through the influence of the external world. The id h It is in the id that all our primary drives are at work, all the processes in the id take place unconsciously' [61]. induced states will provide converging evidences for the existence of a characteristic psychical system. It is hoped that identifying the neurophysiological activity parallel- ing the subjective phenomena in these states will provide the necessary scientific breakthrough to finally do away with the persuasive impression that the unconscious does not exist. Identifying the correlates of 'primary process' (see The pri- mary and secondary psychical process below) activities taking place during wakefulness is extremely difficult given the relatively rigid, impervious nature of normal waking consciousness. The altered states of consciousness mentioned above are comparatively much more yielding. For example, during transient episodes of 'dreamlike' cog- nition, the normal processes of repression may be dis- turbed, allowing unconscious material to flow into consciousness with greater freedom. In a recent review of human intracranial electroencephalography recordings of rapid eye movement (REM) sleep, acute psychotic states, temporal lobe auras and psychedelic drug states, Carhart- Harris identified bursts of rhythmic theta and slow-wave activity in the medial temporal regions in all these states and hypothesised that these discharges of limbic theta are the signature activity of the unconscious mind, described by Freud as 'the primary psychical process' [71]. The function of the id corresponds closely with that of the mesocorticolimbic dopamine system [62]. The NAc and VTA are especially sensitive to rewarding stimuli [63]. Neuroimaging studies in humans have shown that rewarding stimuli activate dopaminergic cells in the VTA [64-66] eliciting an increase of dopamine release in the NAc [67]. Jaak Panksepp has described the mesocorticol- imbic dopamine system as the appetitive, motivational or 'seeking' system [68]. High voltage electrical stimulation of the NAc in both animals and humans has been found to elicit pleasurable and sexual responses [68,69] and ejaculation in human males has been found to correlate with activation of the VTA [64]. The unconscious James Strachey explained in a footnote to Freud's paper 'The unconscious' [6] that the German word for 'uncon- scious' ('das unbewusste') typically translates as 'not con- sciously known' and does not have the unhelpful connotation of the English equivalent meaning 'knocked out' or 'comatose'. This information is useful for an under- standing of this difficult concept. Along with repression, the theory of a conscious/unconscious dynamic is one of the most important in psychoanalysis. The term uncon- scious is used in both a topographical ('the system uncon- scious') and descriptive sense (e.g., 'rendered unconscious') [60]. When we speak of 'the unconscious', it is usually the topographical meaning that is being employed. In this paper, we refer to 'the unconscious' as an archaic psychical system with its own characteristic phenomenology and physiology. The primary and secondary psychical process ' [T]he essence of repression lies simply in turning something away, and keeping it at a distance, from the conscious' [6]. ' [R]epression is brought to bear invariably on ideas which evoke a distressing affect (unpleasure) in the ego' [2]. 'The repressions behave like dams against the pressure of water' [73]. 'The mechanisms of repression...[involve] a withdrawal of the cathexis of energy (or of libido)' [6]. of the primary psychical process of the unconscious mind [71]. Repression Freud described repression in the following ways: 'The theory of repression is the corner-stone on which the whole structure of psycho-analysis rests' [7]. ' [T]he essence of repression lies simply in turning something away, and keeping it at a distance, from the conscious' [6]. ' [R]epression is brought to bear invariably on ideas which evoke a distressing affect (unpleasure) in the ego' [2]. 'The repressions behave like dams against the pressure of water' [73]. 'The mechanisms of repression...[involve] a withdrawal of the cathexis of energy (or of libido)' [6]. that the repressive function is modulated by information transmitted through feedback between the ON and the DMN (see The ego idea/super ego above). 'For the ego, the formation of an ideal would be the conditioning factor for repression' [7]. Mourning and melancholia In 'Mourning and melancholia' [74], Freud compared the experience of mourning with the pathological state of depression: ' [T]he essence of repression lies simply in turning something away, and keeping it at a distance, from the conscious' [6]. 'It is well worth notice that, although mourning involves grave departures from the normal attitude to life, it never occurs to us to regard it as a pathological condition and refer to it medical treatment. We rely on it being overcome after a certain lapse of time, and we look upon any interference with it as useless or even harmful. The distinguishing mental features of melan- cholia, are a profoundly painful sense of dejection, a cessation of interest in the outside world, loss of capacity to love, inhibition of all activity...a lowering of the self-regarding feelings to a degree that finds utterance in self-reproaches and self-revilings, and cul- minates in a delusional expectation of punishment' [74]. ' [R]epression is brought to bear invariably on ideas which evoke a distressing affect (unpleasure) in the ego' [2]. ' [R]epression is brought to bear invariably on ideas which evoke a distressing affect (unpleasure) in the ego' [2]. 'The repressions behave like dams against the pressure of water' [73]. 'The repressions behave like dams against the pressure of water' [73]. 'The mechanisms of repression...[involve] a withdrawal of the cathexis of energy (or of libido)' [6]. 'The mechanisms of repression...[involve] a withdrawal of the cathexis of energy (or of libido)' [6]. Based on the evidence reviewed below, we propose that the Cg25, the orbitofrontal cortex (OFC) and vmPFC exert a strong repressive hold over visceromotor centres, serving to restrain untempered drive and flurries of unconscious material from discharging into the cortices and being con- sciously registered (Figure 2). It is likely however that there are different gradations of repression and that the repressive function takes place more through a set of proc- esses than the action of a specific nucleus. We maintain that Cg25 exerts the principal suppressive effect on vis- ceromotor centres but it is likely that the vmPFC and OFC facilitate this action (see The function of the vmPFC and OFC in relation to repression below). We also speculate Freud described how both mourning and depression involve a forced withdrawal of object cathexis. Since this withdrawal is involuntary, it is experienced as a painful process against which the ego protests. The primary and secondary psychical process The primary and secondary psychical process 'We have found that processes in the unconscious or in the id obey different laws from those in the precon- scious ego. We name these laws in their totality the pri- mary process, in contrast to the secondary process which governs the course of events in the precon- scious, in the ego' [59]. Dating back to his early work on dissociative states [72], Freud described two distinct laws or principles governing the distribution of psychical energy in the mind: (1) the secondary psychical process of normal waking consciousness which exerts a tonic inhibitory hold over the primary psy- chical process in accordance with the demands of social context; (2) The archaic and ontogenetically and phyloge- netically regressive primary psychical process. The primary psychical process describes the relatively motile, free- flowing activity of the unconscious mind. The primary psychical process becomes observable when the forces of repression are circumvented by the forces of the uncon- scious. Such episodes are characterised by a fluidity of association – perceptually and cognitively, and a flooding of affect. James Uleman comments in the introduction to the book 'The new unconscious' [70] that 'the psychoanalytic unconscious is widely acknowledged to be a failure as a scientific theory because evidence of its major compo- nents cannot be observed, measured precisely, or manip- ulated easily'. In order to address this not unreasonable charge, it is important for those who have 'turned their ear' to the unconscious to devise a method of demonstrat- ing its phenomenology to those who have not. A case will be made in this paper that the study of consistent phe- nomenologies in a number of different altered states of consciousness such as dreaming, acute psychotic states, the aura of temporal lobe epilepsy and psychedelic drug This paper takes the position that discharges of rhythmic theta and slow-wave activity from the medial temporal lobes to the association cortices are the signature activity Page 6 of 23 (page number not for citation purposes) Page 6 of 23 (page number not for citation purposes) Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 of the primary psychical process of the unconscious mind [71]. Repression Freud described repression in the following ways: 'The theory of repression is the corner-stone on which the whole structure of psycho-analysis rests' [7]. Page 7 of 23 (page number not for citation purposes) 'Thus the shadow of the object fell upon the ego' [74]. 'Thus the shadow of the object fell upon the ego' [74]. In depression, this is experienced as an increase in intro- spection and a reciprocal decrease in interest in the out- side world. The ego, having taken itself as its own object, begins a process of self-evaluation. The self-questioning becomes fiercely critical as ambivalent feelings felt towards the lost object and self-rapprochement for failing to live up to ideals are targeted at the ego. In depression, this is experienced as an increase in intro- spection and a reciprocal decrease in interest in the out- side world. The ego, having taken itself as its own object, begins a process of self-evaluation. The self-questioning becomes fiercely critical as ambivalent feelings felt towards the lost object and self-rapprochement for failing to live up to ideals are targeted at the ego. 'Ambivalence gives a pathological cast to mourning and forces it to express itself in the form of self- reproaches to the effect that the mourner himself is to blame for the loss of the loved object, i.e., that he has willed it... If the love for the object – a love which can- not be given up though the object itself is given up – takes refuge in narcissistic identification, then the hate comes into operation on this substitutive object, abus- ing it, debasing it, making it suffer and deriving sadis- tic satisfaction from its suffering... It is sadism alone that solves the riddle of the tendency to suicide, which makes the melancholic so interesting – and so danger- ous. So immense is the ego's self-love, which we have come to recognise as the primal state from which instinctual life proceeds, and so vast is the amount of narcissistic libido that we see liberated in the threat to life, that we cannot conceive how the ego can consent to its own destruction. We have known, it is true, that no neurotic harbours thoughts of suicide which he has not turned back upon himself from murderous impulses against others' [74]. 'The object cathexis...was brought to an end. But the free libido was not displaced onto another object; it was withdrawn into the ego. There, however, it was not employed in an unspecified way, but served to establish an identification of the ego with the aban- doned object. Mourning and melancholia The ego denies the loss and strives to place within its grasp a substitute object – whether real or imaginary, in fantasy or hallucination. In cases of successful recovery, the energetic ties which once bound the subject to the object begin to be severed Freud described how both mourning and depression involve a forced withdrawal of object cathexis. Since this withdrawal is involuntary, it is experienced as a painful process against which the ego protests. The ego denies the loss and strives to place within its grasp a substitute object – whether real or imaginary, in fantasy or hallucination. In cases of successful recovery, the energetic ties which once bound the subject to the object begin to be severed Functional connectivity of the subgenua Figure 2 Functional connectivity of the subgenual cingulate (Cg25) Figure 2 Functional connectivity of the subgenual cingulate (Cg25). Yellow/red indicates regions positively correlated with the seed region (i9) and blue indicates regions negatively correlated with the seed region. The seed region, i9, fell within the area of Cg25. This region's network of connectivity incorporated several areas associated with the default mode network (DMN). Although it is not clear in these images, activity in Cg25 was also strongly correlated with activity in the ventral striatum and medial temporal regions. Image reproduced with permission [54]. Functional Figure 2 y g g ( g ) g Functional connectivity of the subgenual cingulate (Cg25). Yellow/red indicates regions positively correlated with the seed region (i9) and blue indicates regions negatively correlated with the seed region. The seed region, i9, fell within the area of Cg25. This region's network of connectivity incorporated several areas associated with the default mode network (DMN). Although it is not clear in these images, activity in Cg25 was also strongly correlated with activity in the ventral striatum and medial temporal regions. Image reproduced with permission [54]. Page 7 of 23 (page number not for citation purposes) Page 7 of 23 (page number not for citation purposes) http://www.annals-general-psychiatry.com/content/7/1/9 Annals of General Psychiatry 2008, 7:9 and the libidinal energies that flowed out of the ego and into the object are displaced into alternative objects. and the libidinal energies that flowed out of the ego and into the object are displaced into alternative objects. melancholia, but only in the sense he knows whom he has lost but not what he has lost in him. Mourning and melancholia This would suggest that melancholia is in some way related to an object-loss which is withdrawn from consciousness, in contradistinction to mourning, in which there is noth- ing about the loss that is unconscious' [74]. In depression, the attempted recovery begins in a similar manner to mourning, with a protest from the ego and search for a substitute object. However, failing to find a suitable replacement in the outside world and refusing to concede that the object is lost, the ego draws within itself its own cathexes. The energies, which were before sent out freely from the ego, now return from the object to con- dense and concentrate upon it. If we are to be consistent with Freud's economic theory of libido [2], the intensity of the mental anguish experienced in depression is proportionate to the intensity of the emo- tion held back from consciousness, and the severity of aggression directed towards the self is proportionate to the severity of aggression that, were it not for repression, would be propelled towards the object: Page 8 of 23 (page number not for citation purposes) Neuropsychiatric findings in depression correlated with principles of Freudian metapsychology Hypofrontality One of the most consistent findings in the neuroimaging of depression is decreased cerebral blood flow (CBF) and glucose metabolism in the PFC, particularly the DLPFC [77-85] (figure 3). The PFC is a large and functionally het- erogeneous structure. Studies of frontal activity in depres- sion have highlighted these differences, with the DLPFC, associated with cognitive and executive functions show- ing decreased activity in depressed states, and the ventral PFC, associated with emotional processing, showing increased activity during episodes of emotional rumina- tion (see [86] or [50]). 'The broad general outcome of the sexual phase dom- inated by the Oedipus complex may, therefore, be taken to be the forming of a precipitate in the ego, con- sisting of these two identifications in some way united with each other. This modification of the ego retains its special position; it confronts the other contents of the ego as an ego ideal or super ego' [1]. Several studies have found negative correlations between depression severity and frontal metabolism [78,81,87- 93]. The induction of depressed symptomology in healthy volunteers and remitted depressed patients has been found to correlate reliably with decreases in frontal activ- ity [56,94,95]. Frontal blood flow and metabolism tends to normalise after spontaneous or treatment-induced remission [51,78,79,96-105]. These studies highlight the reliability of frontal hypometabolism, particularly in the DLPFC, in neuroimaging studies of depression. 'The super ego retains the character of the father, the more powerful the Oedipus complex was and the more rapidly it succumbed to repression (under the influence of authority, religious teaching, schooling and reading), the stricter will be the domination of the super ego over the ego later on – in the form of con- science or perhaps of an unconscious sense of guilt' [1]. ' [I]n the undertaking of repression, the ego is at bot- tom following the commands of its super ego – com- mands which, in their turn, originate from influences in the external world that have found representation in the super ego. The fact remains that the ego has taken sides with those powers, that in it their demands have more strength than the instinctual demands of the id, and that the ego is the power that sets the repression in motion against the portion of the id con- cerned' [1]. ryone and commiserates with his own relatives for being connected with someone so unworthy' [74]. introjection and which contains the lost object. But the piece that behaves so cruelly is not unknown to us either. It comprises the conscience, a critical agency within the ego, which even in normal times takes up a critical attitude towards the ego, though never so relentlessly and so unjustifiably' [76]. The super ego is of central importance in psychoanalytic theory, but it is a much more difficult concept to identify physiologically than e.g., libido or cathexis. Freud argued that the super ego results from a process that took place in infancy (the Oedipus complex) as a recapitulation of a process that occurred in the development of the species [75]. Through this process, the infant was coerced via parental and communal authority to renounce its libidi- nal demands. Although the infant's free reign was put to an end, he/she internalised the demands for concession and turned them into an image of an ideal: 'Thus the shadow of the object fell upon the ego' [74]. This, indeed, might be so even if the patient is aware of the loss that has given rise to his Page 8 of 23 (page number not for citation purposes) http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 Annals of General Psychiatry 2008, 7:9 ryone and commiserates with his own relatives for being connected with someone so unworthy' [74]. 'Thus the shadow of the object fell upon the ego' [74]. Thus, the shadow of the object fell upon the ego, and the latter could henceforth be judged by a special agency, as though it were an object, the for- saken object. In this way an object-loss was trans- formed into an ego-loss and the conflict between the ego and the loved person into a cleavage between the critical activity of the ego and the ego as altered by identification' [74]. Object loss in mourning relates to a literal death; the psy- chological significance of which is well appreciated by the mourner and those around him/her. Accordingly, expres- sions of sadness in mourning are viewed as appropriate, healthy and cathartic. In depression however, the negative affect that accompanies the condition is often viewed as disproportionate to the individual's circumstances – both by the individual him/herself and by others. In contrast to mourning, Freud argued that the intense, ostensibly dis- proportionate level of negative affect experienced in depression is symptomatic of unpleasant and problematic emotions (e.g., love and resentment) that are denied a fully conscious actualisation: In addition to the anger and resentment that is turned towards the ego, the ego is admonished for failing to live up to expectations. 'Mourning and melancholia' was writ- ten shortly after Freud introduced the idea of 'the ego ideal' [17] that would later become 'the super ego' [1]. As discussed in section 1.5, the super ego is a critical agency that judges the ego in relation to its own ideal. 'The melancholic displays something else besides which is lacking in mourning – an extraordinary dim- inution in his self-regard, an impoverishment of his ego on a grand scale. In mourning it is the world that has become poor and empty; in melancholia it is the ego itself. The patient represents his ego to us as worth- less, incapable of any achievement and morally despi- cable; he reproaches himself, vilifies himself and expects to be punished. He abases himself before eve- ' [In depression], one cannot see clearly what it is that has been lost, and it is all the more reasonable to sup- pose that the patient cannot consciously perceive what he has lost either. Page 9 of 23 (page number not for citation purposes) Neuropsychiatric findings in depression correlated with principles of Freudian metapsychology Hypofrontality Based on the neuroimaging data we speculate that hypoactivity in the DLPFC is a correlate of withdrawn object cathexis experienced subjectively as impoverished motivation and diminished interest in the matters outside of the self. A recent functional magnetic resonance imag- ing (fMRI) study reported a positive correlation between subjective measures of anhedonia and activity in the vmPFC and OFC (Brodmann areas (BA)10, 11, and 32) [106]. Importantly, an additional relationship was found between anhedonia scores and diminished activation of the amygdala and the ventral striatum. As will be explained in the following section, in depression, Cg25 can be envisaged as functioning in a manner analogous to a dam, preventing ascending energies from being invested in the PFC. To summarise the key processes involved in depression as outlined by Freud: the illness is triggered by the loss of an object imbued with a particularly intense level of libidinal cathexis, there is a forced withdrawal of cathexis, a regres- sion of libido into the ego, a critical judgement of the ego based on its failure to live up to ideals, and a simultaneous attacking of the ego by repressed emotions felt towards the lost object. ' [T]he ego controls the approaches to motility – that is, to the discharge of excitations into the external world...' [107]. ' [Melancholias] show us the ego divided, fallen apart into two pieces, one which rages against the second. This second piece is the one which has been altered by Page 9 of 23 (page number not for citation purposes) Page 9 of 23 (page number not for citation purposes) Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 Single photon emission computed tomography (SPECT) images from a depressed patient showing characteristic hypofrontality relative to a healthy control subject [82] Figure 3 Single photon emission computed tomography (SPECT) images from a depressed patient showing character- istic hypofrontality relative to a healthy control subject[82]. Single photon emission computed tomography (SPECT) images from a depressed patient showing characteristic hypofrontality relative to a healthy control subject [82] Figure 3 Single photon emission computed tomography (SPECT) images from a depressed patient showing character- istic hypofrontality relative to a healthy control subject[82]. Neuropsychiatric findings in depression correlated with principles of Freudian metapsychology Hypofrontality Single photon emission computed tomography (SPECT) images from a depressed patient showing characteristic hypofrontality relative to a healthy control subject [82] Figure 3 Single photon emission computed tomography (SPECT) images from a depressed patient showing character- istic hypofrontality relative to a healthy control subject[82]. http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 Annals of General Psychiatry 2008, 7:9 related with Cg25 hypermetabolism [115] and increased functional connectivity [46]. Spontaneous and treatment- induced remission of symptoms is associated with signif- icantly decreased Cg25 metabolism [51,100,105,110,113,116-119]. Interestingly, sudden and dramatic deactivations of Cg25 and functionally related regions of the vmPFC and OFC have recently been recorded after intravenous infusion of the dissociative hallucinogen ketamine in healthy human volunteers [121]. These deactivations correlated strongly with dissociative phenomena. Significant activations were seen in the parahippocampal gyrus, temporal cortex and PCC. Importantly, the regions deactivated by ketamine (OFC and vmPFC) are those postulated in this paper to be involved in the process of repression, and the regions acti- vated by ketamine (specifically the medial temporal struc- tures), are those we hypothesise to be involved in the primary psychical process of the unconscious mind. As with the classic psychedelic drugs (e.g., LSD and psilocy- bin), the effects of ketamine have been described as dis- turbing the mechanisms of repression and facilitating the release of primary process thought [122]. Single doses of ketamine have been found to elicit a short-term antide- pressant effect in depressed patients [123-126] and the drug has also been used as an adjunct to psychotherapy with reported efficacy in the treatment of alcoholism [122]. related with Cg25 hypermetabolism [115] and increased functional connectivity [46]. Spontaneous and treatment- induced remission of symptoms is associated with signif- icantly decreased Cg25 metabolism [51,100,105,110,113,116-119]. The subgenual cingulate has been the target of ablative surgeries in the past [120] and, more recently, DBS [51], where high frequency stimulation is used to inhibit activ- ity in target nuclei. The preliminary results of chronic bilateral high frequency stimulation of Cg25 in six patients suffering from severe treatment-resistant depres- sion were reported by Mayberg and colleagues [51]. Sig- nificant improvements (a 50% or greater reduction in Hamilton depression rating scale (HDRS-17) score) were seen in five of the six patients at 2-month follow-up with sustained improvements achieved in four patients at 6 months. Positron emission tomography (PET) scans of patients at 3 and 6 months post stimulation revealed decreased blood flow in Cg25 and increased blood flow in the DLPFC. Significant improvements were seen in sleep, energy, interest and psychomotor speed. The function of the vmPFC and OFC in relation to repression p The data cited in the previous section supports the hypothesis that Cg25 plays a key role in repression. How- ever, it is likely that Cg25 does not act alone in this regard. For example, activity in the ventral anterior PFC correlates positively with depression severity and activity in this region decreases after effective treatment [50]. The OFC (BA11 and BA47) is activated when subjects try to decrease arousal to erotic films [127] and there is impov- erished activation of BA10 and 11 in paedophile sex offenders viewing paedophilic material [128]. In healthy controls viewing the same images, the lateral OFC (BA47) was activated. The lateral OFC has also been found to be activated during contemplation of moral transgressions [129] and script-induced guilt [130]. At the 2007 international Neuropsychoanalysis congress in Vienna, some first-person accounts relating to acute stim- ulation were reported: 'It isn't like something has been added – no, some- thing has been taken away'. 'It is as if I have just suddenly shifted from a state of all consuming internal focus to realising that there are number of things around to do'. 'When you're depressed the focus is inwards. So if someone tells you, well you aren't the only one who feels like that, you don't care. With the stimulator, I don't feel that inward look; it has lifted so I am not so focused on myself...'. Using autobiographical scripts designed to evoke strong emotion, healthy control subjects showed increased blood flow in the vmPFC during script-induced anger compared to patients with anger attacks who showed an impoverished vmPFC response [131]. Impoverished vmPFC activation in anger patients suggests that recruit- ment of this region is necessary for suppression of aggres- sive affect. Significantly lower resting metabolism has been recorded in the OFC of patients with a history of reactive aggression [132,133] and patients with OFC and mPFC lesions who show an increased risk of reactive aggression [134-136]. Healthy participants who imagined responding in an unrestrained aggressive manner to an assault showed hypoactivity in the OFC but increased activity in the same region when imagining restraint 'It is as though I have been locked in a room with 10 screaming children; constant noise, no rest, no escape. http://www.annals-general-psychiatry.com/content/7/1/9 Patients and their families reported 'renewed interest and pleasure in social and family activities, decreased apathy and anhedo- nia, as well as improved ability to plan, initiate, and com- plete tasks that were reported as impossible prior to surgery'. Page 11 of 23 (page number not for citation purposes) Hyperactivity and electrical stimulation of Cg25 eral neuroimaging studies have correlated hyperactivity in this region with depressed mood states and induced sad- ness in healthy volunteers and depressed patients [46,56,95,107-114] (figure 4). Depression severity is cor- Certainly one of the most exciting findings in neuropsy- chiatry in recent years has been the identification of Cg25 as a key region in the pathophysiology of depression. Sev- Positron emission tomography (PET) images of cerebral blood flow changes during transient induced sadness in healthy con- trols (left); pre deep brain stimulation (DBS) in depressed patients (centre); and 3-month post DBS in treatment responsive patients (right) Figure 4 Positron emission tomography (PET) images of cerebral blood flow changes during transient induced sadness in healthy controls (left); pre deep brain stimulation (DBS) in depressed patients (centre); and 3-month post DBS in treatment responsive patients (right). Hyperactivity in Cg25 and hypoactivity in the dorsolateral prefrontal cor- tex (DLPFC) is evident during low mood and depression. This situation is reversed during remission of symptoms. ACC, ante- rior cingulate cortex; ins = insular; PF, prefrontal cortex [51,95]. g p y ( ) g g g y ( ); p p ( ) p p ( ); p p p ( g ) g Positron emission tomography (PET) images of cerebral blood flow changes during transient induced sadness in healthy controls (left); pre deep brain stimulation (DBS) in depressed patients (centre); and 3-month post DBS in treatment responsive patients (right). Hyperactivity in Cg25 and hypoactivity in the dorsolateral prefrontal cor- tex (DLPFC) is evident during low mood and depression. This situation is reversed during remission of symptoms. ACC, ante- rior cingulate cortex; ins = insular; PF, prefrontal cortex [51,95]. Page 10 of 23 (page number not for citation purposes) The function of the vmPFC and OFC in relation to repression Whatever just happened, the children have just left the building' The 'something...taken away' described in these accounts is consistent with the idea of a release from repression (deactivation of Cg25) and a return to object cathexis (DLPFC activation). The final account is especially inter- esting given that the patient was a father of 5. Page 11 of 23 (page number not for citation purposes) Page 11 of 23 (page number not for citation purposes) Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 to elicit a range of primitive emotional responses includ- ing: fear, anxiety, anger, aggression, sexual behaviours, déjà vu and autobiographical recollections [141,174- 185]: [137]. In cases of post traumatic stress disorder, a condi- tion characterised by unsuccessful repression of traumatic memories, patients exposed to a script-driven reminder of a personally traumatic experience showed impoverished activity in the rostral anterior cingulate compared with controls [138]. A related study showed a strong negative correlation between emotional scores and vmPFC activa- tion in PTSD patients exposed to script-driven reminders of their traumatic experience [139] implying that impov- erished vmPFC activation facilitates the return of the affect attached to the original trauma. 'I just get the electrical feeling, and it goes all the way through me...it makes me do things I don't want to do – I get mad' [10]. 'I had a flash of familiar memory, but I don't know what it was... I had a little memory – a scene in a play. They were talking and I could see it... Just seeing it in my memory...a very familiar memory of a girl talking to me...that feeling of familiarity – a familiar memory' [177]. As will be discussed in the next section, activation of the amygdala is associated with the expression of primitive emotions such as anger and fear as well as complex auto- biographical recollections [140,141]. It is interesting therefore that the study by Dougherty and colleagues cited above discovered an inverse relationship between blood flow in the vmPFC and amygdala in healthy control sub- jects during script-driven anger but a positive relationship between amygdala and vmPFC activity in patients with anger attacks [131]. These findings imply that patients with anger attacks suffer from ineffective suppression of amygdala activation [131]. The function of the vmPFC and OFC in relation to repression A number of studies have demonstrated that activation of the amygdala with con- comitant emotional arousal is very quickly followed by activation of the OFC [142-145] and – in healthy individ- uals – suppression of the amygdala response [146-148]. This suppressive function of the vmPFC/OFC is supported by a large body of preclinical data [147-160]. It is likely that this function is impaired in depression, with the sup- pressive/repressive action of the vmPFC/OFC being dom- inated by persistent flurries of limbic arousal [161]. A thorough phenomenological review of these experi- ences is necessary for an appreciation of the functional sig- nificance of the medial temporal lobes in relation to the primary psychical process of the unconscious mind. Such experiences have been interpreted by several clinicians and researchers as examples of primary process activity taking over from the secondary psychical process of nor- mal waking consciousness [72,174,177,179,180,186- 193]: 'Reflected in the seizure-related behaviour may be emotional trauma of early life, negative feelings towards specific individuals because of past incidents or situations' [192]. 'Repression fails, the usual defence systems crumble, disturbing unconscious material erupts, anxiety mounts, and the personality structure becomes inef- fective' [189]. Amygdala hyperactivity and electrical stimulation of medial temporal lobes 'It is in my view wrong to call the feeling of having experienced something before an illusion. It is rather that at such moments something is touched on which we have already experienced once before' [5]. Hyperactivity in the amygdala has been reported in a large number of imaging studies of depression [47,87,97,111,162-169]. Increased activity in the amy- gdala has been recorded in studies of induced sadness in healthy volunteers [169-171]. Amygdala activity has been found to correlate positively with depression severity [87,162,166], to show a sustained response to negative emotional stimuli in depressed patients compared to healthy controls [161] and to decrease in sensitivity to emotional stimuli after successful antidepressant treat- ment [172,173]. A review of depth electroencephalography recordings from the medial temporal regions suggests that stimula- tion-induced dreamlike experiences share a common phe- nomenology and neurophysiology (bursts of rhythmic theta and slow-wave activity) with other dreamlike states [71]. It is hoped that converging evidences correlating neurophysiological activity with qualitatively analysed phenomenological experiences will facilitate a wider understanding of the phenomenology and psychophysi- ology of the unconscious mind. The amygdala has long been recognised to play an impor- tant role in emotion. Bilateral resection of the amygdala has been found to result in dramatic behavioural changes (Klüver and Bucy syndrome) including emotional blunt- ing, indifference to loved ones, hyperorality and hypersex- uality [140]. Electrical stimulations of the human amygdala and medial temporal regions have been found Cg25 connectivity Anatomical studies in primates have revealed dense con- nections between Cg25 and the hypothalamus [194,195] Page 12 of 23 (page number not for citation purposes) Page 12 of 23 (page number not for citation purposes) Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 course and be overlooked. As a rule defence retains the upper hand in it; in any case alterations of the ego, comparable to scars, are left behind' [61]. course and be overlooked. As a rule defence retains the upper hand in it; in any case alterations of the ego, comparable to scars, are left behind' [61]. mPFC [196], parahippocampal cortex [197], amygdala, ventral striatum, septal nuclei, dorsomedial caudate nucleus and mediodorsal nucleus of the thalamus; with moderate connections to the periaqueductal grey and dor- sal raphe nucleus [195,196]. Human tractography and functional connectivity analyses support these findings, showing prominent connections between Cg25 and the NAc, amygdala, hypothalamus, OFC and vmPFC [54,198,199]. The connections of Cg25 to a number of important visceromotor centres offering profuse projec- tions to the PFC has led to suggestions that Cg25 plays an important modulatory role in cortical functioning [195]. A recent cytological analysis of the human cingulate cor- tex has revealed an especially dense concentration of inhibitory receptors in Cg25 [200]. These findings are consistent with the hypothesis that Cg25 exerts a control- ling influence over visceromotor regions. Postmortem and MRI studies have found glial loss and volume reductions in the PFC in major depressive disor- der (MDD) and bipolar disorder (BPD) [209-214] as well as extensive losses in Cg25 and proximal paralimbic regions [163,201,215-221]. Unilateral and bilateral volu- metric reductions in the medial temporal regions – prima- rily in the hippocampus, have also been reported in depressed patients [112,201,222-232], as have reductions in the ventral striatum [233,234]. It is not difficult to surmise that the metabolic work of repression has structural ramifications. This paper hypothesises that the volumetric reductions found in postmortem and neuroimaging studies of depression are related to the effects of repression. It is significant that the most severe reductions have been found in Cg25 (48% reductions in 163) the area hypothesised to exert the pri- mary repressive force. One possible mechanism for the volumetric reductions is glucocorticiod-mediated neuro- toxicity [235]. Dysregulation of the stress related hypoth- alamic-pituitary-adrenal (HPA) axis is consistently associated with depression [236]. Dysregulation of the HPA may be related to hyperactivity in the amygdala [237]. Discussion The main inspiration behind the primary hypothesis of this paper i.e., that Cg25 is centrally involved in repres- sion, was Mayberg's paper on DBS for the treatment of severe depression [51]. The findings of this study have a special significance for Freudian metapsychology. It has been inferred in this paper that the sudden lifting of neg- ative affect upon stimulation of Cg25 is consistent with the idea of a release of libido for object cathexis after it has been pathologically 'dammed up' behind a central repressing force. However, the therapeutic response to stimulation raises some difficult questions for both psy- choanalysis and psychiatry. One important question con- Cg25 connectivity Electrical stimulation of the amygdala increases cortisol release in humans [238]. HPA hyperactivity increases the likelihood of excitotoxic processes, downreg- ulating glial, and increasing the concentrations of neuro- toxic glucocorticiods and excitiotoxic glutamate [239]. The OFC and the vmPFC are dense in glucocorticiod receptors and glutamate cells, with glutamatergic afferents ascending from the amygdala and hippocampus [240]. Connectivity between Cg25 and the amygdala has been found to be especially strong during the viewing of fearful and threatening faces [201]. The magnitude of disconnec- tivity between these structures predicted anxiety scores in a number of individuals [201]. Resting state connectivity between Cg25 and a range of structures including the medial temporal lobes has been found to predict treat- ment response in depressed patients [58] and a strong cor- relation was discovered between subjective measures of neuroticism and Cg25 and amygdala activation during the viewing of emotionally provocative images [202]. In addition to medial temporal structures, other impor- tant visceromotor centres connected with Cg25 include the NAc [198,203,204] and the VTA [196,205]. Cg25 shows an especially high level of functional connectivity with the NAc at rest [23,54,204]. The NAc and VTA are key nuclei in the mesocorticolimbic dopamine systems, being central to the mechanisms of motivation and reward [10,68]. The VTA has also been found to be strongly acti- vated during ejaculation in male humans [64] cocaine induced euphoria [65] and the heroin rush [66]. Electrical stimulation of the NAc and the septum has been found to elicit feelings of sexual pleasure and orgasm in humans [69,206,207]. Patients given a self-stimulator connected to the septal region stimulated themselves repeatedly for hours and protested bitterly when attempts were made to take the device from them [206]. These findings support the association of the mesolimbic dopamine system with the Freudian 'id' [1]. Chronic stimulation of the NAc has recently been carried out in three TRD patients [208]. Early results suggest that this intervention may be particu- larly effective in relieving symptoms of anhedonia. It is hypothesised that the volumetric reductions discov- ered in depressed patients, as well as patients suffering from other major psychiatric conditions such as schizo- phrenia [194,208,210,212,215,216,219,241-248] may be related to the effects of psychological conflict. Page 13 of 23 (page number not for citation purposes) memory traces and exogenous stressors facilitating a recall of lost objects, regretted behaviours and eluded ideals? memory traces and exogenous stressors facilitating a recall of lost objects, regretted behaviours and eluded ideals? cerns the economy of psychical energy in relation to depression and mania. Freud discussed the issue of mania towards the end of 'Mourning and melancholia': One possible reason why the effect of Cg25 stimulation appears to have a sustained beneficial effect [253] rather than an iatrogenic one [254] may be that inhibiting activ- ity in Cg25 facilitates the disintegration of a wider net- work. For example, it is possible that activation of Cg25 supports activation of the DMN and deactivation of Cg25 supports deactivation of the DMN and activation of the ON. This model would account for the diminished self focus (ego cathexis) and rejuvenated task focus (object cathexis) seen upon Cg25 stimulation. It may be possible to test this formulation through neuroimaging studies of patients undergoing Cg25 stimulation. If the ego is dependent on repression, we would expect to see decreased activity in the DMN, decreased activity in Cg25 and increased activity in the ON after stimulation. Prelim- inary evidence lends support to this model [51]. Evidence supporting the interdependency of the ego and repression would of course have important implications for the his- tory of the evolution of human consciousness. 'The impression which several psycho-analytic investi- gators have already put into words is that the content of mania is no different from that of melancholia, that both disorders are wrestling with the same "complex", but that probably in melancholia the ego has suc- cumbed to the complex whereas in mania it has mas- tered it or pushed it aside. Our second pointer is afforded by the observation that all states such as joy, exultation or triumph, which give us the normal model for mania, depend on the same economic con- ditions. What has happened here is that, as a result of some influence, a large expenditure of psychical energy, long maintained or habitually occurring, has at last become unnecessary, so that it is available for numerous applications and possibilities of discharge' [74]. Neuroimaging studies of manic patients have shown that in direct contrast to depression, resting state activity is decreased in the OFC [249,250] and increased in dorsal frontal areas during manic episodes [250,251]. It is signif- icant that the early responses to Cg25 stimulation do not appear to switch patients from pathological depression to overt mania. memory traces and exogenous stressors facilitating a recall of lost objects, regretted behaviours and eluded ideals? According to Freud's model, manic episodes depend on a quantity of dammed-up libido being sud- denly made available for object cathexis. In order to test the validity of the Freudian model, it is important that there be thorough psychophenomenolog- ical and neurophysiological analyses of Cg25 and NAc stimulations. Ideally, subjective and objective measures should be taken simultaneously, in real time. If, as this paper predicts, Cg25 is centrally involved in repression, then in addition to dramatic improvements in energy/ libido we would also expect to see some adverse responses to stimulation, such as disinhibited behaviour, patholog- ical drive, perseverance, hostility, aggression, sexual pro- miscuity and a reduced capacity to consider others. Such behaviours are commonly associated with ventromedial prefrontal lesions [255-259]. We would also predict that patients undergoing Cg25 stimulation would be more susceptible to temporal lobe phenomena (such as déjà vu) as a result of diminished inhibitory control over exci- tatory medial temporal structures. If electrophysiological recordings are carried out, we would hypothesise that electrodes placed within the proximity of septal, supramammillary or hippocampal theta structures would display characteristic bursts of high voltage rhythmic theta during moments of strong emotion ([69], see [71] for a review). We would also predict that intracranial EEG recordings in bipolar patients would reveal significant changes in activity paralleling shifts in mood i.e., Cg25 hyperactivity/NAc hypoactivity during depression and Cg25 hypoactivity/NAc hyperactivity during mania. 'An important element in the theory of repression is the view that repression is not an event that occurs once but that it requires a permanent expenditure [of energy]. If this expenditure were to cease, the repressed impulse, which is being fed all the time from its sources, would on the next occasion flow along the channels from which it had been forced away, and the repression would either fail in its purpose or would have to be repeated an indefinite number of times. Thus it is because drives are continuous in their nature that the ego has to make its defensive action secure by a permanent expenditure [of energy]' [252]. In the long term it is feasible that abeyance of repression leads to a therapeutic shift in the energetic equilibrium of the mind; but even if this is true, we still need to consider why upon release from repression, we do not see a patho- logical release of primitive drive and repressed memory. Volumetric reductions 'The neurosis may last a considerable time and cause marked disturbances, but it may also run a latent Page 13 of 23 (page number not for citation purposes) Page 13 of 23 (page number not for citation purposes) Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 Due to the rigour of repression, depression is not the easiest phenomenon to gain a per- spective on the workings of the unconscious. The psycho- ses provide a better vantage: It has been said before that it matters little which psycho- logical discipline we choose to derive our operational terms; the approach is secondary to the phenomena: 'Listen my friend, the golden tree of life is green, all theory is grey' [260]. 'Listen my friend, the golden tree of life is green, all theory is grey' [260]. 'Listen my friend, the golden tree of life is green, all theory is grey' [260]. Psychological models do serve a purpose however, but to provide comprehensive explanations of mental states and behaviours, effective models must evolve naturally from their phenomena. In a recent letter published in a reputa- ble journal and co-signed by a number of leading researchers [261] a proposal was put-forward as part of a 'decade of the mind' initiative to work towards a transdis- ciplinary explanation of mental phenomena. The main psychological discipline championed by the authors was cognitive psychology. While the essential idea is a com- mendable one, we must ask ourselves seriously whether the information processing paradigm is really the best model for carrying out this initiative. The psychological limitations of the behavioural model have been recog- nised for several decades but the cognitive approach, which views the human mind as an information processor is currently the favoured model of clinicians and research- ers. If the computer analogy is an accurate representation of the human psyche, then we can feel comfortable going into the final years of the 'decade of the mind' that real progress will be made. If however, the model is at all incomplete, we may need to consult alternative para- digms to assist our empiricism. The information process- ing model has traditionally been put to good use guiding 'Things that in the neuroses have to be laboriously fetched up from the depths are found in the psychoses on the surface, visible to every eye' [265]. ' [M]aterial which is ordinarily unconscious can trans- form itself into preconscious material and then become conscious – a thing that happens to a large extent in psychotic states. From this we infer that the maintenance of certain internal resistances is a sine qua non of normality' [59]. http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 Annals of General Psychiatry 2008, 7:9 hypotheses that do not correspond well with the findings of modern clinical research. However, it must be empha- sised that what we have brought together in this paper are principal concepts of Freudian metapsychology together with principal findings of neuropsychiatry. It is all the more significant therefore that the meeting has been com- plementary. and informing empirical research. However, several researchers are now recognising that the computational model has limitations, especially when it is applied to human emotion [62,68,262,263]. What we hope psycho- analysis can bring to the table therefore, is a psychological model that has its roots set firmly in human experience. We hope psychoanalysis can work alongside cognitive psychology to provide a more comprehensive under- standing of human experience. In order to develop a discussion of the comparative merits of psychological paradigms, it is worth reminding our- selves of the two main aims of this paper: (1) to propose a series of hypotheses correlating neurophysiological processes with some fundamental processes of psychoa- nalysis, and (2) to highlight correspondences between Freud's writings in 'Mourning and melancholia' and cur- rent findings in depression. How successful these tasks have been will largely depend on two factors: (1) whether evidences from other fields converge with the evidences reviewed here, and (2) whether the psychoanalytic per- spective is given credence. There is already ample evidence to support the role of Cg25, the vmPFC and OFC in sup- pressing primitive affect, but the psychoanalytic signifi- cance of this function has yet to be fully appreciated. ' [T]he mind would often slip through the fingers of psychology, if psychology refused to keep a hold on the mind's unconscious states' [264]. 'Psychoanalysis still represents the most coherent and intellectually satisfying view of the mind that we have' [263]. The primary requirement for a scientific psychoanalysis is (and always has been) to confirm beyond reasonable doubt that the unconscious mind exists and that it is not only important but essential for an understanding of the human mind and behaviour. If, as this paper maintains, the unconscious does exist, then regardless of the words chosen to define it, the establishment of its phenomenol- ogy as subject matter worthy of scientific investigation is important. Deciding how best to test and confirm the hypothesis that the unconscious mind exists will present us simultaneously with a direction towards studying its form and physiology. memory traces and exogenous stressors facilitating a recall of lost objects, regretted behaviours and eluded ideals? Are we to assume that electrical stimulation of Cg25 removes both the physiological and psychological causes of depression? Even if depression is primarily an energetic phenomenon and the physiological causes are the psycho- logical causes (and vice versa), wouldn't there still remain It is acknowledged that very little in the way of counter evidence has been cited in this paper challenging the validity of the Freudian model. It is likely that several examples could be found in Freud's evolving work of Page 14 of 23 (page number not for citation purposes) Page 14 of 23 (page number not for citation purposes) Conclusion The goal of this paper has been to investigate consistencies between Freudian metapsychology and empirical findings in neuropsychiatry. A summary of several key psychoana- lytic concepts was given together with some early hypoth- eses about their physiological coordinates. This was done to facilitate an understanding of Freudian terminology and allow for the application of these ideas to areas of clinical interest. Modern clinical research and older empirical work such as intracranial stimulations was dis- cussed in relation to Freudian metapsychology in order to highlight correspondences between physiology, phenom- enology and theory. If a new level of scientific verification is achieved for subjective phenomena of relevance to psy- choanalysis, this will have implications not just for the way in which psychoanalysis is viewed by the wider phil- osophical, psychological and psychiatric communities, but also for those interested in incorporating psychoana- lytic ideas into their own clinical practice. 'Thus, the psychological hypotheses to which we are led by an analysis of the process of dreaming must be left, as it were, in suspense, until they can be related to the findings of other enquiries which seek to approach the kernel of the same problem from another angle' [5]. Future work may provide the necessary evidence. Alterna- tive means of studying the unconscious – perhaps by way of a pharmacological agent such as a psychedelic drug [193,266] may open up fresh angles of enquiry. Freud famously described the interpretation of dreams as 'the royal road to a knowledge of the unconscious activities of the mind' [5]. However, dreaming occurs in sleep, making real-time recitation of subjective phenomena impossible. If we could stimulate the primary psychical process in waking we would have a more effective method for stud- ying the unconscious: ' [I]t should not be forgotten that in fact [the distinc- tion between the unconscious and conscious dimen- sions of the mind] is not a theory at all but a first stock- taking of the facts of our observations, that it keeps as close to them as possible' [59]. 'Freud once said of dreams that they were the via regia or royal way to study the unconscious; to an even greater degree this seems to be true for the LSD experi- ence' [265]. http://www.annals-general-psychiatry.com/content/7/1/9 In depression we only assume the existence of the uncon- scious through a process of deduction based on ostensibly irrational behaviours (e.g., self-harm, violent self-criticism etc). As Freud made clear, there are much better ways of studying the unconscious and the free-flowing psychical energies that are its signature. Freud first stumbled across a realisation of the unconscious through his work on dis- sociative states [72]: Page 15 of 23 (page number not for citation purposes) http://www.annals-general-psychiatry.com/content/7/1/9 Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 sciousness. There is a wealth of evidence to suggest that this can be reliably achieved through the use of a psyche- delic drug such as LSD [193,266-285]: ' [O]ne received the clearest impression – especially from the behaviour of subjects after hypnosis – of the existence of mental processes that one could only describe as "unconscious". The "unconscious" has it is true, long been under discussion among philosophers as a theoretical concept; but now for the first time, in the phenomena of hypnotism, it became something actual, tangible and subject to experiment' [1]. 'One must...put it simply, it does seem that all LSD does is open the doors to the unconscious' [279]. Using neuroimaging techniques we would predict that the ego dissolving, primary process releasing properties of a psychedelic compound would correspond with a shift in effective connectivity in the DMN, with the medial tem- poral regions (as opposed to the vmPFC) exerting princi- pal causality [33,121,286,287]. Testing this hypothesis will be difficult, but such challenging procedures are nec- essary if the primary psychical process is to be considered a matter worthy of investigation. Once we are better able to study the phenomenology of the unconscious, the application of our new knowledge to the study and treat- ment of the whole of the mind will follow more easily. 'To most people educated in philosophy the idea of anything psychical which is not also conscious is so inconceivable that it seems to them absurd and refut- able simply by logic. I believe this is only because they have never studied the relevant phenomena of hypno- sis and dreams, which – quite apart from pathological manifestations – necessitate this view. Their psychol- ogy of consciousness is incapable of solving the prob- lems of dreams and hypnosis' [1]. http://www.annals-general-psychiatry.com/content/7/1/9 For Freud, dreams were a way of studying the unconscious – unfettered by waking consciousness but the phenome- nology of dreaming has largely failed to convince sceptics of the existence of the unconscious. Freud acknowledged that converging lines of enquiry would be required to con- solidate the insights gained through the study of dreams: Page 16 of 23 (page number not for citation purposes) References Raichle ME, Snyder AZ: A default mode of brain function: a brief history of an evolving idea. Neuroimage 2007, 37:1083-1090. 4 G O S g 16. Strachey J: Freud S (1893–1899). The emergence of Freud's fundamental hypotheses 3rd edition. Edited by: Strachey J. London: Vintage; 1924. 41. Greicius MD, Kiviniemi V, Tervonen O, Vainionpää V, Alahuhta S, Reiss AL, Menon V: Persistent default-mode network connec- tivity during light sedation. Hum Brain Map 2008, 29:839-847. yp y y J g 17. Freud S: The psychoneuroses of defence 3rd edition. London: Vintage; 1894. y g g p 42. Rombouts SA, Barkhof F, Goekoop R, Stam CJ, Scheltens P: Altered resting state networks in mild cognitive impairment and mild Alzheimer's disease: an fMRI study. Hum Brain Map 2005, 26:231-239. 18. Freud S: Some points for an organic study of hysterical and motor paralyses 1st edition. London: Vintage; 1893. g 19. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shul- g 19. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shul- man GL: A default mode of brain function. Proc Natl Acad Sci USA 2001, 98:676-682. y J man GL: A default mode of brain function. Proc Natl Acad Sci USA 2001, 98:676-682. 43. Kennedy DP, Redcay E, Courchesne E: Failing to deactivate: rest- ing functional abnormalities in autism. Proc Natl Acad Sci USA 2006, 103:8275-8280. , 20. Frued : Beyond the pleasure principle 18th edition. London: Vintage; 1920. 44. Garrity AG, Pearlson GD, McKiernan K, Lloyd D, Kiehl KA, Calhoun VD: Aberrant "default mode" functional connectivity in schizophrenia. Am J Psychiatry 2007, 164:450-457. 21. Gusnard DA, Raichle ME: Searching for a baseline: functional imaging and the human brain. Nat Rev Neurosci 2001, 2:685-694. 22. Gusnard DA, Akbudak E, Shulman GL, Raichle ME: Medial prefron- tal cortex and self-referential mental activity: relation to a default mode of brain function. Proc Natl Acad Sci USA 2001, 98:4259-4264. p J y y 45. Zhou Y, Liang M, Tian L, Wang K, Hao Y, Liu H, Liu Z, Jiang T: Func- tional disintegration in paranoid schizophrenia using resting- state fMRI. Schizophr Res 2007, 97:194-205. p 46. Greicius MD, Flores BH, Menon V, Glover GH, Solvason HB, Kenna H, Reiss AL, Schatzberg AF: Resting-state functional connectiv- ity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry 2007, 62:429-437. 23. Competing interests 28. Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME: The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci USA 2005, 102:9673-9678. p g The authors declare that they have no competing interests. References Freud S: The ego and the id 19th edition. London: Vintage; 1 p p 34. Saxe R, Xiao DK, Kovacs G, Perrett DI, Kanwisher N: A region of right posterior superior temporal sulcus responds to observed intentional actions. Neuropsychologia 2004, 42:1435-1446. 2. Freud S: Project for a scientific psychology 1st edition. London: Vintage; 1895. 2. Freud S: Project for a scientific psychology 1st edition. London: Vintage; 1895. 3. Pribram K, Gill M: Freud's project re-assessed Tiptree, UK: Anchor Press; 1976. 35. Stark M, Coslett H, Saffran E: Impairment of an egocentric map of locations: Implications for perception and action. Cogn Neuropsychol 1996, 13:481-523. 4. Strachey J: Freud S (1886–1899). Project for a scientific psychology 1st edition. Edited by: Strachey J. London: Vintage; 1954. y y J g 5. Freud S: The interpretation of dreams London: Penguin; 1900. p y 36. Maddock RJ, Garrett AS, Buonocore MH: Remembering familiar people: the posterior cingulate cortex and autobiographical memory retrieval. Neurosci 2001, 104:667-676. 6. Freud S: The unconscious 14th edition. London: Vintage; 1915. Freud S: On narcissism 14th edition. London: Vintage; 1914. 8. Fletcher P, McKenna PJ, Friston KJ, Frith CD, Dolan RJ: Abnormal cingulate modulation of fronto-temporal connectivity in schizophrenia. Neuroimage 1999, 9:337-342. y 37. Maguire EA, Mummery CJ: Differential modulation of a common memory retrieval network revealed by positron emission tomography. Hippocampus 1999, 9:54-61. p g 9. Freud S: On aphasia 14th edition. London: Vintage; 1891. g p y pp p 38. Vincent JL, Snyder AZ, Fox MD, Shannon BJ, Andrews JR, Raichle ME, Buckner RL: Coherent spontaneous activity identifies a hip- pocampal-parietal memory network. J Neurophysiol 2006, 96:3517-3531. 10. MacLean PD: The triune brain in evolution New York: Plenum Press; 1990. 11. Fonagy P: Psychoanalysis today. World Psychiatry 2003, 2:73-80. gy y y y y y 12. Freud S: Neurosis and psychosis 19th edition. London: Vintage; 1924. 12. Freud S: Neurosis and psychosis 19th edition. London: 39. Gilboa A, Winocur G, Grady CL, Hevenor SJ, Moscovitch M: Remembering our past: functional neuroanatomy of recol- lection of recent and very remote personal events. Cereb Cor- tex 2004, 14:1214-1225. p y 13. Freud S: Draft F 1st edition. London: Vintage; 1894. 14. Freud S: Three essays on the theory of sexuality 7th edition. London: Vin- tage; 1905. g 15. Jung CG: On psychic energy. In On the nature of the psyche New York: Routledge; 1928. 40. Authors' contributions 29. Fransson P: Spontaneous low-frequency BOLD signal fluctua- tions: an fMRI investigation of the resting-state default mode of brain function hypothesis. Hum Brain Map 2005, 26:15-29. The present paper was inspired by the work of HSM as pre- sented at the 2007 International Neuropsychoanalysis congress in Vienna. The paper was written by RLC–H with intellectual support and guidance from HSM, ALM and DJN. All authors read and approved the final manuscript. yp p 30. Greicius MD, Supekar K, Menon V, Dougherty RF: Resting-state functional connectivity reflects structural connectivity in the default mode network. Cereb Cortex 2008. 31. Fair DA, Cohen AL, Dosenbach NU, Church JA, Miezin FM, Barch DM, Raichle ME, Petersen SE, Schlaggar BL: The maturing archi- tecture of the brain's default network. Proc Natl Acad Sci USA 2008, 105:4028-4032. http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 Annals of General Psychiatry 2008, 7:9 25. 25. Vogeley K, May M, Ritzl A, Falkai P, Zilles K, Fink GR: Neural corre- lates of first-person perspective as one constituent of human self-consciousness. J Cogn Neurosci 2004, 16:817-827. plete and always ready to correct or modify its theo- ries. There is no incongruity (anymore than in the case of physics or chemistry) if its most general concepts lack clarity and if its postulates are provisional; it leaves their more precise definition to the results of future work' [288]. J g 26. Kelley WM, Macrae CN, Wyland CL, Caglar S, Inati S, Heatherton TF: J g 26. Kelley WM, Macrae CN, Wyland CL, Caglar S, Inati S, Heatherton TF: Finding the self? An event-related fMRI study. J Cogn Neurosci 2002, 14:785-794. 26. Kelley WM, Macrae CN, Wyland CL, Caglar S, Inati S, Finding the self? An event-related fMRI study. J Cogn Neurosci 2002, 14:785-794. 27. Fossati P, Hevenor SJ, Graham SJ, Grady C, Keightley ML, Craik F, Mayberg H: In search of the emotional self: an fMRI study using positive and negative emotional words. Am J Psychiatry 2003, 160:1938-1945. Acknowledgements 32. Buckner RL, Carroll DC: Self-projection and the brain. Trends Cogn Sci 2006, 11:49-57. RCH is grateful to Drs S J Wilson and S J C Davies of the University of Bris- l P h h l U f d dd l ll l RCH is grateful to Drs S J Wilson and S J C Davies of the University of Bris- tol Psychopharmacology Unit for providing additional intellectual support. 33. Uddin LQ, Clare Kelly AM, Biswal BB, Xavier Castellanos F, Milham MP: Functional connectivity of default mode network compo- nents: correlation, anticorrelation, and causality. Hum Brain Map 2008 in press. Conclusion 'Psycho-analysis an Empirical Science – Psychoanalysis is not, like philosophies, a system starting out from a few sharply defined basic concepts, seeking to grasp the whole universe with the help of these and, once it is completed, having no room for fresh discoveries or better understanding. On the contrary, it keeps close to the facts in its field of study, seeks to solve the immediate problems of observation, gropes its way forward by the help of experience, is always incom- It is anticipated that progress towards a wider appreciation of the psychoanalytic model will first require confirma- tion of the existence of the unconscious mind. We pro- pose that the most effective way of achieving this is to stimulate the primary psychical process in waking con- Page 16 of 23 (page number not for citation purposes) Page 16 of 23 (page number not for citation purposes) http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 72. Breuer J, Freud S: Studies on hysteria. Standard edition of the complete works of Sigmund Freud Volume 2. London: Vintage :1893-1895. ing circuit in depression: a functional magnetic resonance study. Biol Psychiatry 2005, 57:1079-1088. ing circuit in depression: a functional magnetic resonance study. Biol Psychiatry 2005, 57:1079-1088. 48. g g 73. Freud S: Analysis terminable and interminable 23rd edition. London: Vin- tage; 1937. y y y 48. Pomarol-Clotet E, Salvador R, Sarró S, Gomar J, Vila F, Martínez A, Guerrero A, Ortiz-Gil J, Sans-Sansa B, Capdevila A, Cebamanos JM, McKenna PJ: Failure to deactivate in the prefrontal cortex in schizophrenia: dysfunction of the default mode network? Psy- chol Med 2008, 29:1-9. 74. Freud S: Mourning and melancholia 14th edition. London: Vintage; 1917. 75. Freud S: Totem and taboo 13th edition. London: Vintage; 1913. 49. Freud S: A difficulty in the path of psycho-analysis 17th edition. London: Vintage; 1917. 76. Freud S: Group psychology and the analysis of the ego 18th edition. Lon- don: Vintage; 1921. g 50. Drevets WC: Orbitofrontal cortex function and structure in depression. Ann NY Acad Sci 2007, 1121:499-527. 77. Bremner JD, Innis RB, Salomon RM, Staib LH, Ng CK, Miller HL, Bro- nen RA, Krystal JH, Duncan J, Rich D, Price LH, Malison R, Dey H, Soufer R, Charney DS: Positron emission tomography meas- urement of cerebral metabolic correlates of tryptophan depletion-induced depressive relapse. Arch Gen Psychiatry 1997, 54(4):364-374. p 51. Mayberg HS, Lozano AM, Voon V, McNeely HE, Seminowicz D, Ham- ani C, Schwalb JM, Kennedy SH: Deep brain stimulation for treat- ment-resistant depression. Neuron 2005, 45:651-660. 52. Dougherty DD, Shin LM, Rauch SL: Orbitofrontal cortex activa- tion during functional neuroimaging studies of emotion induction in humans. In The orbitofrontal cortex Edited by: Zald DH, Rauch SL. Oxford, UK: Oxford University Press; 2006. ( ) 78. Baxter LR Jr, Schwartz JM, Phelps ME, Mazziotta JC, Guze BH, Selin CE, Gerner RH, Sumida RM: Reduction of prefrontal cortex glu- cose metabolism common to three types of depression. Arch Gen Psychiatry 1989, 46:243-250. 53. Meyer-Lindenberg AS, Olsen RK, Kohn PD, Brown T, Egan MF, Wein- berger DR, Berman KF: Regionally specific disturbance of dor- solateral prefrontal-hippocampal functional connectivity in schizophrenia. Arch Gen Psychiatry 2005, 62:379-386. y y 79. Bench CJ, Friston KJ, Brown RG, Scott LC, Frackowiak RS, Dolan RJ: The anatomy of melancholia – focal abnormalities of cere- bral blood flow in major depression. http://www.annals-general-psychiatry.com/content/7/1/9 Psychol Med 1992, 22:607-615. p y y 54. Margulies DS, Kelly AM, Uddin LQ, Biswal BB, Castellanos FX, Milham MP: Mapping the functional connectivity of anterior cingulate cortex. Neuroimage 2007, 37:579-588. 80. Biver F, Goldman S, Delvenne V, Luxen A, De Maertelaer V, Hubain P, Mendlewicz J, Lotstra F: Frontal and parietal metabolic dis- turbances in unipolar depression. Biol Psychiatry 1994, 36:381-388. 55. Mayberg HS, Brannan SK, Mahurin RK, Jerabek PA, Brickman JS, Tekell JL, Silva JA, McGinnis S, Glass TG, Martin CC, Fox PT: Cingu- late function in depression: a potential predictor of treat- ment response. Neuroreport 1997, 8:1057-1061. 81. Cohen RM, Gross M, Nordahl TE, Semple WE, Oren DA, Rosenthal N: Preliminary data on the metabolic brain pattern of patients with winter seasonal affective disorder. Arch Gen Psy- chiatry 1992, 49:545-552. 56. Mayberg HS, Liotti M, Brannan SK, McGinnis S, Mahurin RK, Jerabek PA, Silva JA, Tekell JL, Martin CC, Lancaster JL, Fox PT: Reciprocal limbic-cortical function and negative mood: converging PET findings in depression and normal sadness. Am J Psychiatry 1999, 156:675-682. y 82. Mayberg HS, Lewis PJ, Regenold W, Wagner HN Jr: Paralimbic hypoperfusion in unipolar depression. J Nucl Med 1994, 35(6):929-934. 57. Mayberg HS: Modulating dysfunctional limbic-cortical circuits in depression: towards development of brain-based algo- rithms for diagnosis and optimised treatment. Br Med Bull 2003, 65:193-207. ( ) 83. Ebert D, Feistel H, Barocka A: Effects of sleep deprivation on the limbic system and the frontal lobes in affective disorders: a study with Tc-99m-HMPAO SPECT. Psychiatry Res 1991, 40:247-251. 84. Ring HA, Bench CJ, Trimble MR, Brooks DJ, Frackowiak RS, Dolan RJ: Depression in Parkinson's disease. A positron emissionstudy. Br J Psychiatry 1994, 165:333-339. 58. Seminowicz DA, Mayberg HS, McIntosh AR, Goldapple K, Kennedy S, Segal Z, Rafi-Tari S: Limbic-frontal circuitry in major depres- sion: a path modeling metanalysis. Neuroimage 2004, 22:409-18. J y y 85. Drevets WC, Ongür D, Price JL: Reduced glucose metabolism in the subgenual prefrontal cortex in unipolar depression. Mol Psychiatry 1998, 3:190-191. p g y g 59. Freud S: An outline of psychoanalysis 23rd edition. London: Vintage; 1940. 60. Freud S: New introductory lectures of psychoanalysis 22nd edition. Lon- don: Vintage; 1933. y y 86. Dougherty DD, Rauch SL: Brain correlates of antidepressant treatment outcome from neuroimaging studies in depres- sion. Psychiatr Clin North Am 2007, 30:91-103. g 61. Freud S: Moses and monotheism 23rd edition. London: Vintage; 1939. 62. http://www.annals-general-psychiatry.com/content/7/1/9 Solms M, Turnbull O: The brain and the inner world London: Karnac; 2002. y 87. Drevets WC, Videen TO, Price JL, Preskorn SH, Carmichael ST, Rai- chle ME: A functional anatomical study of unipolar depres- sion. J Neurosci 1992, 12:3628-3641. 63. Pagnoni G, Zink CF, Montague PR, Berns GS: Activity in human ventral striatum locked to errors of reward prediction. Nat Neurosci 2002, 5:97-98. J 88. Yazici KM, Kapucu O, Erbas B, Varoglu E, Gülec C, Bekdik CF: Assessment of changes in regional cerebral blood flow in patients with major depression using the 99mTc-HMPAO single photon emission tomography method. Eur J Nucl Med 1992, 19(12):1038-1043. 64. Holstege G, Georgiadis JR, Paans AM, Meiners LC, Graaf FH van der, 64. Holstege G, Georgiadis JR, Paans AM, Meiners LC, Graaf FH van der, Reinders AA: Brain activation during human male ejaculation. J Neurosci 2003, 23:9185-9193. Reinders AA: Brain activation during human male ejaculation. J Neurosci 2003, 23:9185-9193. 65. Breiter HC, Gollub RL, Weisskoff RM, Kennedy DN, Makris N, Berke JD, Goodman JM, Kantor HL, Gastfriend DR, Riorden JP, Mathew RT, Rosen BR, Hyman SE: Acute effects of cocaine on human brain activity and emotion. Neuron 1997, 19:591-611. ( ) 89. Andreason PJ, Altemus M, Zametkin AJ, King AC, Lucinio J, Cohen RM: Regional cerebral glucose metabolism in bulimia ner- vosa. Am J Psychiatry 1992, 149:1506-1513. y 66. Sell LA, Morris J, Bearn J, Frackowiak RS, Friston KJ, Dolan RJ: Acti- vation of reward circuitry in human opiate addicts. Eur J Neu- rosci 1999, 11:1042-1048. J y y 90. Hirono N, Mori E, Ishii K, Ikejiri Y, Imamura T, Shimomura T, Hashi- moto M, Yamashita H, Sasaki M: Frontal lobe hypometabolism and depression in Alzheimer's disease. Neurology 1998, 50:380-383. 67. Pappata S, Dehaene S, Poline JB, Gregoire MC, Jobert A, Delforge J, Frouin V, Bottlaender M, Dolle F, Di Giamberardino L, Syrota A: In vivo detection of striatal dopamine release during reward: a PET study with [(11)C]raclopride and a single dynamic scan approach. Neuroimage 2002, 16:1015-1027. 91. Mayberg HS, Starkstein SE, Sadzot B, Preziosi T, Andrezejewski PL, Dannals RF, Wagner HN Jr, Robinson RG: Selective hypometab- olism in the inferior frontal lobe in depressed patients with Parkinson's disease. Ann Neurol 1990, 28:57-64. 92. Volkow ND, Hitzemann R, Wang GJ, Fowler JS, Wolf AP, Dewey SL, Handlesman L: Long-term frontal brain metabolic changes in cocaine abusers. Synapse 1992, 11:184-190. 68. References Greicius MD, Krasnow B, Reiss AL, Menon V: Functional connec- tivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci USA 2003, 100:253-258. yp 24. Johnson SC, Baxter LC, Wilder LS, Pipe JG, Heiserman JE, Prigatano GP: Neural correlates of self-reflection. Brain 2002, 125:1808-1814. 47. Anand A, Li Y, Wang Y, Wu J, Gao S, Bukhari L, Mathews VP, Kalnin A, Lowe MJ: Activity and connectivity of brain mood regulat- 47. Anand A, Li Y, Wang Y, Wu J, Gao S, Bukhari L, Mathews VP, Kalnin A, Lowe MJ: Activity and connectivity of brain mood regulat- Page 17 of 23 (page number not for citation purposes) Page 17 of 23 (page number not for citation purposes) Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 p J p y y ( ) 104. Ogura A, Morinobu S, Kawakatsu S, Totsuka S, Komatani A: Changes in regional brain activity in major depression after successful treatment with antidepressant drugs. Acta Psychiatr Scand 1998, 98:54-59. 125. Zarate CA Jr, Singh JB, Carlson PJ, Brutsche NE, Ameli R, Lucken- baugh DA, Charney DS, Manji HK: A randomized trial of an N- methyl-D-aspartate antagonist in treatment-resistant major depression. Arch Gen Psychiatry 2006, 63:856-864. 105. Kennedy SH, Evans KR, Krüger S, Mayberg HS, Meyer JH, McCann S, Arifuzzman AI, Houle S, Vaccarino FJ: Changes in regional brain glucose metabolism measured with positron emission tom- ography after paroxetine treatment of major depression. Am J Psychiatry 2001, 158:899-905. p y y 126. Liebrenz M, Borgeat A, Leisinger R, Stohler R: Intravenous keta- mine therapy in a patient with a treatment-resistant major depression. Swiss Med Week 2007, 137:234-236. J y y 106. Keedwell PA, Andrew C, Williams SC, Brammer MJ, Phillips ML: The neural correlates of anhedonia in major depressive disorder. Biol Psychiatry 2005, 58:843-853. p 127. Beauregard M, Lévesque J, Bourgouin P: Neural correlates of con- scious self-regulation of emotion. J Neurosci 2001, 21:RC165. 28 S ff G f S g J 128. Schiffer B, Paul T, Gizewski E, Forsting M, Leygraf N, Schedlowski M, Kruger TH: Functional brain correlates of heterosexual pae- dophilia. Neuroimage 2008, 41:80-91. 128. Schiffer B, Paul T, Gizewski E, Forsting M, Leygraf N, Schedlowski M, K TH F i l b i l f h l y y 107. Baker SC, Frith CD, Dolan RJ: The interaction between mood and cognitive function studied with PET. Psychol Med 1997, 3:565-578. Kruger TH: Functional brain correlates of heterosexual pae- dophilia. Neuroimage 2008, 41:80-91. p g 129. Finger EC, Marsh AA, Kamel N, Mitchell DG, Blair JR: Caught in the act: the impact of audience on the neural response to mor- ally and socially inappropriate behavior. Neuroimage 2006, 33:414-421. 108. George MS, Ketter TA, Parekh PI, Horwitz B, Herscovitch P, Post RM: Brain activity during transient sadness and happiness in healthy women. Am J Psychiatry 1995, 152:341-351. 130. Shin LM, Dougherty DD, Orr SP, Pitman RK, Lasko M, Macklin ML, Alpert NM, Fischman AJ, Rauch SL: Activation of anterior paral- imbic structures during guilt-related script-driven imagery. Biol Psychiatry 2000, 48:43-50. y J y y 109. http://www.annals-general-psychiatry.com/content/7/1/9 Panksepp J: Affective neuroscience New York: Oxford University Press; 1998. 69. Heath RG: The role of pleasure in behavior New York: Hoeber; 1964. y p 93. Bonne O, Krausz Y, Shapira B, Bocher M, Karger H, Gorfine M, Chisin R, Lerer B: Increased cerebral blood flow in depressed patients responding to electroconvulsive therapy. J Nucl Med 1996, 37(7):1075-1080. 70. Hassin RR, Uleman JS, Bargh JA: The new unconscious Oxford, UK: Oxford University Press; 2005. Oxford University Press; 2005. 71. Carhart-Harris R: Waves of the unconscious: The neurophysi- ology of dreamlike states and its implications for the psy- chodynamic model of the mind. Neuropsychoanalysis 2007, 9:183-211. ( ) 94. Bremner JD, Vythilingam M, Ng CK, Vermetten E, Nazeer A, Oren DA, Berman RM, Charney DS: Regional brain metabolic corre- lates of alpha-methylparatyrosine-induced depressive symp- Page 18 of 23 (page number not for citation purposes) Page 18 of 23 (page number not for citation purposes) Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 toms: implications for the neural circuitry of depression. JAMA 2003, 289:3125-34. toms: implications for the neural circuitry of depression. JAMA 2003, 289:3125-34. olism across waking and non-rapid eye movement sleep in depression. Arch Gen Psychiatry 2005, 62:387-396. 115. J 95. Liotti M, Mayberg HS, McGinnis S, Brannan SL, Jerabek P: Unmask- ing disease-specific cerebral blood flow abnormalities: mood challenge in patients with remitted unipolar depression. Am J Psychiatry 2002, 159:1830-1840. 115. Osuch EA, Ketter TA, Kimbrell TA, George MS, Benson BE, Willis MW, Herscovitch P, Post RM: Regional cerebral metabolism associated with anxiety symptoms in affective disorder patients. Biol Psychiatry 2000, 48:1020-1023. J y y 96. Drevets WC: Functional neuroimaging studies of depression: the anatomy of melancholia. Ann Rev Med 1998, 49:341-361. p y y 116. Liotti M, Martin CC, Gao JH, Roby JW, Mayberg HS, Zamarripa F, Jer- abek PA, Fox PT: Xenon effects on regional cerebral blood flow assessed by 15O-H2O positron emission tomography: impli- cations for hyperpolarized xenon MRI. J Mag Res Imag 1997, 7:761-764. 97. Drevets WC, Raichle ME: Neuroanatomical circuits in depres- sion: implications for treatment mechanisms. Psychopharmacol Bull 1992, 28:261-274. 117. Wu J, Buchsbaum MS, Gillin JC, Tang C, Cadwell S, Wiegand M, Najafi A, Klein E, Hazen K, Bunney WE Jr, Fallon JH, Keator D: Prediction of antidepressant effects of sleep deprivation by metabolic rates in the ventral anterior cingulate and medial prefrontal cortex. Am J Psychiatry 1999, 156:1149-1158. 98. http://www.annals-general-psychiatry.com/content/7/1/9 Goodwin GM, Austin MP, Dougall N, Ross M, Murray C, O'Carroll RE, Moffoot A, Prentice N, Ebmeier KP: State changes in brain activity shown by the uptake of 99mTc-exametazime with single photon emission tomography in major depression before and after treatment. J Affect Disord 1993, 29:243-253. J y y 118. Mayberg HS, Brannan SK, Tekell JL, Silva JA, Mahurin RK, McGinnis S, Jerabek PA: Regional metabolic effects of fluoxetine in major depression: serial changes and relationship to clinical response. Biol Psychiatry 2000, 48:830-843. J 99. Martinot JL, Hardy P, Feline A, Huret JD, Mazoyer B, Attar-Levy D, Pappata S, Syrota A: Left prefrontal glucose hypometabolism in the depressed state: a confirmation. Am J Psychiatry 1990, 147:1313-1317. 100. Nobler MS, Sackeim HA, Prohovnik I, Moeller JR, Mukherjee S, Schnur DB, Prudic J, Devanand DP: Regional cerebral blood flow in mood disorders, III. Treatment and clinical response. Arch Gen Psychiatry 1994, 51:884-897. p y y 119. Mayberg HS, Silva JA, Brannan SK, Tekell JL, Mahurin RK, McGinnis S, Jerabek PA: The functional neuroanatomy of the placebo effect. Am J Psychiatry 2002, 159:728-737. J y y 120. Cosgrove GR, Rauch SL: Psychosurgery. Neurosurg Clin N Am 1995, 6(1):167-176. 101. Rubin P, Hemmingsen R, Holm S, Møller-Madsen S, Hertel C, Povlsen UJ, Karle A: Relationship between brain structure and func- tion in disorders of the schizophrenic spectrum: single posi- tron emission computerized tomography, computerized tomography and psychopathology of first episodes. Acta Psy- chiatr Scand 1994, 90:281-289. 121. Deakin JF, Lees J, McKie S, Hallak JE, Williams SR, Dursun SM: Gluta- mate and the neural basis of the subjective effects of keta- mine: a pharmaco-magnetic resonance imaging study. Arch Gen Psychiatry 2008, 65:154-164. 122. Krupitsky EM, Grinenko AY: Ketamine psychedelic therapy (KPT): a review of the results of ten years of research. J Psy- choactive Drugs 1997, 29:165-183. 102. Trivedi MH, Morris DW, Grannemann BD, Mahadi S: Symptom clusters as predictors of late response to antidepressant treatment. J Clin Psychiatry 1994, 66(8):1064-1070. 123. Berman RM, Cappiello A, Anand A, Oren DA, Heninger GR, Charney DS, Krystal JH: Antidepressant effects of ketamine in depressed patients. Biol Psychiatry 2000, 47:351-354. J y y ( ) 103. Mayberg HS: Limbic-cortical dysregulation: a proposed model of depression. J Neuropsychiatry Clin Neurosci 1997, 9(3):471-481. p p y y 124. Ostroff R, Gonzales M, Sanacora G: Antidepressant effect of ket- amine during ECT. Am J Psychiatry 2005, 162:1385-1386. http://www.annals-general-psychiatry.com/content/7/1/9 167. Nofzinger EA, Nichols TE, Meltzer CC, Price J, Steppe DA, Miewald JM, Kupfer DJ, Moore RY: Changes in forebrain function from waking to REM sleep in depression: preliminary analyses of [18F]FDG PET studies. Psychiatry Res 1999, 91:59-78. 143. Krolak-Salmon P, Hénaff MA, Vighetto A, Bertrand O, Mauguière F: Early amygdala reaction to fear spreading in occipital, tem- poral, and frontal cortex: a depth electrode ERP study in humans. Neuron 2004, 42:665-676. 168. Ketter TA, Kimbrell TA, George MS, Dunn RT, Speer AM, Benson BE, Willis MW, Danielson A, Frye MA, Herscovitch P, Post RM: Effects of mood and subtype on cerebral glucose metabolism in treatment-resistant bipolar disorder. Biol Psychiatry 2001, 49:97-109. 144. Streit M, Ioannides AA, Liu L, Wölwer W, Dammers J, Gross J, Gaebel W, Müller-Gärtner HW: Neurophysiological correlates of the recognition of facial expressions of emotion as revealed by magnetoencephalography. Brain Res Cogn Brain Res 1999, 7:481-491. 169. Ketter TA, Wang PW: Predictors of treatment response in bipolar disorders: evidence from clinical and brain imaging studies. J Clin Psychiatry 2002, 63(Suppl 3):21-25. 145. Streit M, Ioannides A, Sinnemann T, Wölwer W, Dammers J, Zilles K, Gaebel W: Disturbed facial affect recognition in patients with schizophrenia associated with hypoactivity in distributed brain regions: a magnetoencephalographic study. Am J Psychi- atry 2001, 158:1429-1436. 170. Schneider F, Gur RE, Mozley LH, Smith RJ, Mozley PD, Censits DM, Alavi A, Gur RC: Mood effects on limbic blood flow correlate with emotional self-rating: a PET study with oxygen-15 labeled water. Psychiatry Res 1995, 61:265-283. y 146. Garcia R, Vouimba RM, Baudry M, Thompson RF: The amygdala modulates prefrontal cortex activity relative to conditioned fear. Nature 1999, 402:294-296. 171. Schneider F, Grodd W, Weiss U, Klose U, Mayer KR, Nägele T, Gur RC: Functional MRI reveals left amygdala activation during emotion. Psychiatry Res 1997, 76:75-82. 147. Hariri AR, Bookheimer SY, Mazziotta JC: Modulating emotional responses: effects of a neocortical network on the limbic sys- tem. Neuroreport 2000, 11:43-48. y y 172. Sheline YI, Barch DM, Donnelly JM, Ollinger JM, Snyder AZ, Mintun MA: Increased amygdala response to masked emotional faces in depressed subjects resolves with antidepressant treatment: an fMRI study. Biol Psychiatry 2001, 50:651-658. p 148. Milad MR, Quirk GJ: Neurons in medial prefrontal cortex signal memory for fear extinction. Nature 2002, 420:70-74. 173. http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 damage in human prefrontal cortex. Nat Neurosci 1999, 2:1032-1037. damage in human prefrontal cortex. Nat Neurosci 1999, 2:1032-1037. 160. Paré D, Quirk GJ, Ledoux JE: New vistas on amygdala networks in conditioned fear. J Neurophysiol 2004, 92:1-9. J p y 161. Siegle GJ, Steinhauer SR, Thase ME, Stenger VA, Carter CS: Can't shake that feeling: event-related fMRI assessment of sus- tained amygdala activity in response to emotional informa- tion in depressed individuals. Biol Psychiatry 2002, 51:693-707. 136. Eslinger PJ, Grattan LM: Altered serial position learning after frontal lobe lesion. Neuropsychologia 1994, 32:729-739. frontal lobe lesion. Neuropsychologia 1994, 32:729-7 137. Pietrini P, Guazzelli M, Basso G, Jaffe K, Graffman J: Neural corre- lates of imaginal aggressive behaviour assessed by positron emission tomography in healthy subjects. Am J Psychiatry 2000, 157:1772-1781. p y y 162. Drevets WC, Burton H, Videen TO, Snyder AZ, Simpson JR Jr, Rai- chle ME: Blood flow changes in human somatosensory cortex during anticipated stimulation. Nature 1995, 373:249-252. 138. Britton JC, Phan KL, Taylor SF, Fig LM, Liberzon I: Corticolimbic blood flow in posttraumatic stress disorder during script- driven imagery. Biol Psychiatry 2005, 57:832-840. g p 163. Drevets WC, Price JL, Simpson JR Jr, Todd RD, Reich T, Vannier M, Raichle ME: Subgenual prefrontal cortex abnormalities in mood disorders. Nature 1997, 386:824-827. 139. Frewen P, Lane RD, Neufeld RW, Densmore M, Stevens T, Lanius R: Neural correlates of levels of emotional awareness during trauma script-imagery in posttraumatic stress disorder. Psy- chosom Med 2007, 70:27-31. 164. Wu JC, Gillin JC, Buchsbaum MS, Hershey T, Johnson JC, Bunney WE Jr: Effect of sleep deprivation on brain metabolism of depressed patients. Am J Psychiatry 1992, 149:538-543. p p J y y 165. Mentis MJ, Pietrini P, Polles A: Cerebral glucose metabolism in late onset depression without cognitive impairment. Neurosci 1995, 21:1736. 140. Terzian H, Ore GD: Syndrome of Kluver and Bucy. Repro- duced in man by bilateral removal of the temporal lobes. Neurology 1955, 5:373-380. 166. Abercrombie HC, Larson CL, Ward TL: Metabolic rate in the amygdala predicts negative affect and depression severity in depressed patients: an FDG-PET study. Neuroimage 1996, 3:S217. 141. Gloor P: Experiential phenomena of temporal lobe epilepsy. Brain 1990, 113:1673-1694. 142. Kawasaki H, Kaufman O, Damasio H, Damasio AR, Granner M, Bakken H, Hori T, Howard MA 3rd, Adolphs R: Single-neuron responses to emotional visual stimuli recorded in human ventral prefrontal cortex. Nat Neurosci 2001, 4:15-16. http://www.annals-general-psychiatry.com/content/7/1/9 Fu CH, Williams SC, Cleare AJ, Brammer MJ, Walsh ND, Kim J, Andrew CM, Pich EM, Williams PM, Reed LJ, Mitterschiffthaler MT, Suckling J, Bullmore ET: Attenuation of the neural response to sad faces in major depression by antidepressant treatment: a prospective, event-related functional magnetic resonance imaging study. Arch Gen Psychiatry 2004, 61:877-889. y 149. Morgan MA, Romanski LM, LeDoux JE: Extinction of emotional learning: contribution of medial prefrontal cortex. Neurosci Lett 1993, 163:109-113. 150. Morgan MA, LeDoux JE: Differential contribution of dorsal and ventral medial prefrontal cortex to the acquisition and extinction of conditioned fear in rats. Behav Neurosci 1995, 109:681-688. g g y y y 174. Delgado JR, Hamlin H, Higgins JW, Mahl GF: Behavioral changes during intracerebral electrical stimulation. AMA Arch Neurol Psychiatry 1956, 76:399-419. 151. LeDoux JE: The emotional brain New York: Simon & Schuster; 1996. 175. Bickford RG, Mulder DW, Dodge HW Jr, Svien HJ, Rome HP: Changes in memory function produced by electrical stimula- tion of the temporal lobe in man. Res Pub Assoc Res Nerv Mental Dis 1958, 36:227-40. 152. LeDoux JE: Emotion circuits in the brain. Ann Rev Neurosci 2000, 23:155-184. 153. Quirk GJ, Russo GK, Barron JL, Lebron K: The role of ventrome- dial prefrontal cortex in the recovery of extinguished fear. J Neurosci 2000, 20:6225-6231. 176. Baldwin M: Electrical stimulation of the mesial temporal region. In Electrical studies on the unanesthetized brain Edited by: Ramey ER, Doherty DS. New York: Hoeber; 1960:159-176. 154. LeDoux JE, Gorman JM: A call to action: overcoming anxiety through active coping. Am J Psychiatry 2001, 158:1953-1955. y y 177. Penfield W, Perrot P: The brain's record of auditory and visual experience. Brain 1963, 86:595-696. 155. Garcia R: Postextinction of conditioned fear: between two CS-related memories. Learn Mem 2002, 9:361-363. 178. Horowitz MJ, Adams JE, Rutkin BB: Visual imagery on brain stim- ulation. Arch Gen Psychiatry 1968, 19:469-486. 156. Grace AA, Rosenkranz JA: Regulation of conditioned responses of basolateral amygdala neurons. Physiol Behav 2002, 77:489-493. 179. Ferguson SM, Rayport M, Gardner R, Kass W, Weiner H, Reiser MF: Similarities in mental content of psychotic states, spontane- ous seizures, dreams, and responses to electrical brain stim- ulation in patients with temporal lobe epilepsy. Psychosom Med 1969, 31:479-498. 157. Herry C, Garcia R: Prefrontal cortex long-term potentiation, but not long-term depression, is associated with the mainte- nance of extinction of learned fear in mice. J Neurosci 2002, 22:577-583. Page 20 of 23 (page number not for citation purposes) http://www.annals-general-psychiatry.com/content/7/1/9 Bench CJ, Friston KJ, Brown RG, Frackowiak RS, Dolan RJ: Regional cerebral blood flow in depression measured by positron emission tomography: the relationship with clinical dimen- sions. Psychol Med 1993, 23(3):579-590. 110. Pardo JV, Sheikh SA, Schwindt GC, Lee JT, Kuskowski MA, Surerus C, Lewis SM, Abuzzahab FS, Adson DE, Rittberg BR: Chronic vagus nerve stimulation for treatment-resistant depression decreases resting ventromedial prefrontal glucose metabo- lism. Neuroimage 2008. 131. Dougherty DD, Rauch SL, Deckersbach T, Marci C, Loh R, Shin LM, Alpert NM, Fischman AJ, Fava M: Ventromedial prefrontal cor- tex and amygdala dysfunction during an anger induction pos- itron emission tomography study in patients with major depressive disorder with anger attacks. Arch Gen Psychiatry 2004, 61:795-804. g 111. Drevets WC, Price JL, Bardgett ME, Reich T, Todd RD, Raichle ME: Glucose metabolism in the amygdala in depression: relation- ship to diagnostic subtype and plasma cortisol levels. Pharma- col Biochem Behav 2002, 71:431-447. 132. Raine A, Meloy JR, Bihrle S, Stoddard J, LaCasse L, Buchsbaum MS: Reduced prefrontal and increased subcortical brain function- ing assessed using positron emission tomography in preda- tory and affective murderers. Behav Sci Law 1998, 16:319-332. 112. Videbech P, Ravnkilde B: Hippocampal volume and depression: a meta-analysis of MRI studies. Am J Psychiatry 2004, 161:1957-1966. 133. Goyer PF, Andreason PJ, Semple WE, Clayton AH, King AC, Comp- ton-Toth BA, Schulz SC, Cohen RM: Positron-emission tomogra- phy and personality disorders. Neuropsychopharmacology 1994, 10:21-28. 113. Dougherty DD, Weiss AP, Cosgrove GR, Alpert NM, Cassem EH, Nierenberg AA, Price BH, Mayberg HS, Fischman AJ, Rauch SL: Cer- ebral metabolic correlates as potential predictors of response to anterior cingulotomy for treatment of major depression. J Neurosurg 2003, 99:1010-1017. 134. Grafman J, Schwab K, Warden D, Pridgen A, Brown HR, Salazar AM: Frontal lobe injuries, violence, and aggression: a report of the Vietnam Head Injury Study. Neurology 1996, 46:1231-1238. j gy 135. Anderson SW, Bechara A, Damasio H, Tranel D, Damasio AR: Impairment of social and moral behavior related to early 114. Nofzinger EA, Buysse DJ, Germain A, Price JC, Meltzer CC, Miewald JM, Kupfer DJ: Alterations in regional cerebral glucose metab- Page 19 of 23 (page number not for citation purposes) Page 19 of 23 (page number not for citation purposes) Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 Benes FM, McSparren J, Bird ED, San Giovanni JP, Vincent SL: Defi- cits in small interneurons in prefrontal and cingulate cortices of schizophrenic and schizoaffective patients. Arch Gen Psychi- atry 1991, 48:996-1001. 197. Kondo H, Saleem KS, Price JL: Differential connections of the perirhinal and parahippocampal cortex with the orbital and medial prefrontal networks in macaque monkeys. J Comp Neurol 2005, 493:479-509. y 217. Ongür D, Drevets WC, Price JL: Glial reduction in the subgenual prefrontal cortex in mood disorders. Proc Natl Acad Sci USA 1998, 95:13290-13295. 218. Orlovskaya DD, Vostrikov VM, Rachmanova VI, Uranova NA: Decreased numerical density of oligodendroglial density cells in the prefrontal cortex area 9 in schizophrenia and mood disorders: a study of brain collection from the Stanley Foundation Neuropathology Consortium. Schizophr Res 2000, 41:105-106. 198. Johansen-Berg H, Gutman DA, Behrens TE, Matthews PM, Rush- worth MF, Katz E, Lozano AM, Mayberg HS: Anatomical connec- tivity of the subgenual cingulate region targeted with deep brain stimulation for treatment-resistant depression. Cereb Cortex 2008, 18:1374-1383. 199. Lehéricy S, Ducros M, Moortele PF Van de, Francois C, Thivard L, Poupon C, Swindale N, Ugurbil K, Kim DS: Diffusion tensor fiber tracking shows distinct corticostriatal circuits in humans. Ann Neurol 2004, 55:522-9. 219. Cotter D, Mackay D, Landau S, Kerwin R, Everall I: Reduced glial cell density and neuronal size in the anterior cingulate cor- tex in major depressive disorder. Arch Gen Psychiatry 2001, 58:545-553. 200. Palomero-Gallagher N, Mohlberg H, Zilles K, Vogt B: Cytology and receptor architecture of human anterior cingulate cortex. J Comp Neurol 2008, 508:906-926. 220. Hirayasu Y, Shenton ME, Salisbury DF, Kwon JS, Wible CG, Fischer IA, Yurgelun-Todd D, Zarate C, Kikinis R, Jolesz FA, McCarley RW: Subgenual cingulate cortex volume in first-episode psycho- sis. Am J Psychiatry 1999, 156:1091-1093. 201. Pezawas L, Meyer-Lindenberg A, Drabant EM, Verchinski BA, Munoz KE, Kolachana BS, Egan MF, Mattay VS, Hariri AR, Weinberger DR: 5- HTTLPR polymorphism impacts human cingulate-amygdala interactions: a genetic susceptibility mechanism for depres- sion. Nat Neurosci 2005, 8:828-834. 221. Botteron KN, Raichle ME, Drevets WC, Heath AC, Todd RD: Volu- metric reduction in left subgenual prefrontal cortex in early onset depression. Biol Psychiatry 2002, 51:342-344. 202. Haas BW, Omura K, Constable RT, Canli T: Emotional conflict and neuroticism: personality-dependent activation in the amygdala and subgenual anterior cingulate. Behav Neurosci 2007, 121:249-256. 222. http://www.annals-general-psychiatry.com/content/7/1/9 p 187. Ostow M: Psychodynamic disturbances in patients with tem- poral lobe disorder. J Mt Sinai Hosp N Y 1954, 20:293. 188. Kubie LS: Some implications for psychoanalysis of modern concepts of the organization of the brain. Psychoanal Q 1953, 22:21-68. 210. Johnston-Wilson NL, Sims CD, Hofmann JP, Anderson L, Shore AD, Torrey EF, Yolken RH: Disease-specific alterations in frontal cortex brain proteins in schizophrenia, bipolar disorder, and major depressive disorder. The Stanley Neuropathology Consortium. Mol Psychiatry 2000, 5:142-149. 189. Rodin EA, Mulder DW, Faucett RL, Bickford RG: Psychologic fac- tors in convulsive disorders of focal origin. AMA Arch Neurol Psy- chiatry 1955, 74:440. y y 211. Rajkowska G: Postmortem studies in mood disorders indicate altered numbers of neurons and glial cells. Biol Psychiatry 2000, 48:766-777. y 190. Epstein AW, Ervin F: Psychodynamic significance of seizure content in psychomotor epilepsy. Psychosom Med 1956, 18:43-55. 212. Rajkowska G, Miguel-Hidalgo JJ, Wei J, Dilley G, Pittman SD, Meltzer HY, Overholser JC, Roth BL, Stockmeier CA: Morphometric evi- dence for neuronal and glial prefrontal cell pathology in major depression. Biol Psychiatry 1999, 45:1085-1098. 191. Mahl GF, Rothenberg A, Delgado JMR, Hamlin H: Psychological responses in the human to intracerebral electrical stimula- tion. Psychosom Med 1964, 26:337-368. y 192. Ferguson SM, Rayport M: Id, ego, and temporal lobe revisited. Int Rev Neurobiol 2006, 76:21-31. j p y y 213. Bremner JD, Vythilingam M, Vermetten E, Nazeer A, Adil J, Khan S, Staib LH, Charney DS: Reduced volume of orbitofrontal cortex in major depression. Biol Psychiatry 2002, 51:273-279. 193. Cohen S: The Beyond Within. The LSD Story New York: Atheneum; 1964. j p y y 214. Cotter D, Mackay D, Chana G, Beasley C, Landau S, Everall IP: Reduced neuronal size and glial cell density in area 9 of the dorsolateral prefrontal cortex in subjects with major depres- sive disorder. Cereb Cortex 2002, 12:386-394. 194. Ongür D, An X, Price JL: Prefrontal cortical projections to the hypothalamus in macaque monkeys. J Comp Neurol 1998, 401:480-505. 215. Benes FM, Davidson J, Bird ED: Quantitative cytoarchitectural studies of the cerebral cortex of schizophrenics. Arch Gen Psy- chiatry 1986, 43:31-35. 195. Freedman LJ, Insel TR, Smith Y: Subcortical projections of area 25 (subgenual cortex) of the macaque monkey. J Comp Neurol 2000, 421:172-188. 196. Ongür D, An X, Price JL: Prefrontal cortical projections to the hypothalamus in macaque monkeys. J Comp Neurol 2000, 401:480-505. 216. http://www.annals-general-psychiatry.com/content/7/1/9 158. Harrison BJ, Pujol J, Ortiz H, Fornito A, Pantelis C, Yücel M: Modu- lation of brain resting-state networks by sad mood induction. PLoS ONE 2008, 3:e1794. 180. Halgren E, Walter RD, Cherlow DG, Crandall PH: Mental phenom- ena evoked by electrical stimulation of the human hippoc- ampus formation and amygdala. Brain 1978, 101:83-117. 159. Myers KM, Davis M: Behavioral and neural analysis of extinc- tion. Neuron 2002, 36:567-584. p g 181. Wieser HG, ILAE Commission on Neurosurgery of Epilepsy: ILAE Commission Report. Mesial temporal lobe epilepsy with hip- pocampal sclerosis. Epilepsia 2004, 45:695-714. Page 20 of 23 (page number not for citation purposes) Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 182. Bartolomei F, Barbeau E, Gavaret M, Guye M, McGonigal A, Regis J, Chauvel P: Cortical stimulation study of the role of rhinal cor- tex in deja vu and reminiscence of memories. Neurology 2004, 63:858-864. connectivity of human striatum: a resting state fMRI study. Cereb Cortex 2008. connectivity of human striatum: a resting state fMRI study. Cereb Cortex 2008. 205. Leichnetz GR, Astruc J: The efferent projections of the medial prefrontal cortex in the squirrel monkey (Saimiri sciureus). Brain Res 1976, 109:455-472. 183. Bancaud J, Brunet-Bourgin F, Chauvel P, Halgren E: Anatomical ori- gin of déjà vu and vivid 'memories' in human temporal lobe epilepsy. Brain 1994, 117:71-90. 206. Heath RG: Electrical stimulation of the brain in man. Am J Psy- chiatry 1963, 120:571-577. y 207. Heath RG: Pleasure and brain activity in man. Deep and sur- face electroencephalograms during orgasm. J Nerv Mental Dis 1972, 154:3-18. p p y 184. Barbeau E: Recollection of vivid memories after perirhinal region stimulations: synchronization in the theta range of spatially distributed brain areas. Neuropsychologia 2005, 43:1329-1337. 208. Schlaepfer TE, Cohen MX, Frick C, Kosel M, Brodesser D, Axmacher N, Joe AY, Kreft M, Lenartz D, Sturm V: Deep brain stimulation to reward circuitry alleviates anhedonia in refractory major depression. Neuropsychopharmacology 2008, 33:368-377. 185. Vignal JP, Maillard L, McGonigal A, Chauvel P: The dreamy state: hallucinations of autobiographic memory evoked by tempo- ral lobe stimulations and seizures. Brain 2007, 130:88-99. 186. Ostow M: Psychodynamic disturbances in patients with tem- poral lobe disorders. Trans Am Neurol Assoc 1952, 56:79-83. p p y p gy 209. Uranova NA, Zimina IS, Vikhreva OV, Denisov DV, Orlovskaya DD: Morphometric study of ultrastructural alterations of myeli- nated fibres in post-mortem schizophrenia brains. Schizophr Res 1999, 36:85. Page 21 of 23 (page number not for citation purposes) 204. Di Martino A, Scheres A, Margulies DS, Kelly AM, Uddin LQ, Shehzad Z, Biswal B, Walters JR, Castellanos FX, Milham MP: Functional http://www.annals-general-psychiatry.com/content/7/1/9 225. Bell-McGinty S, Butters MA, Meltzer CC, Greer PJ, Reynolds CF 3rd, Becker JT: Brain morphometric abnormalities in geriatric depression: long-term neurobiological effects of illness dura- tion. Am J Psychiatry 2002, 8:1424-1427. 247. Honer WG, Falkai P, Chen C, Arango V, Mann JJ, Dwork AJ: Synap- tic and plasticity-associated proteins in anterior frontal cor- tex in severe mental illness. Neurosci 1999, 91:1247-1255. 248. Owen F, Crow TJ, Frith CD, Johnson JA, Johnstone EC, Lofthouse R, Owens DG, Poulter M: Selective decreases in MAO-B activity in post-mortem brains from schizophrenic patients with type II syndrome. Br J Psychiatry 1987, 151:514-519. 226. Steffens DC, Byrum CE, McQuoid DR, Greenberg DL, Payne ME, Blitchington TF, MacFall JR, Krishnan KR: Hippocampal volume in geriatric depression. Biol Psychiatry 2003, 48:301-309. 249. Rubin E, Sackeim HA, Prohovnik I, Moeller JR, Schnur DB, Mukherjee S: Regional cerebral blood flow in mood disorders: IV. Com- parison of mania and depression. Psychiatry Res 1995, 61:1-10. 227. Mervaala E, Föhr J, Könönen M, Valkonen-Korhonen M, Vainio P, Par- tanen K, Partanen J, Tiihonen J, Viinamäki H, Karjalainen AK, Lehto- nen J: Quantitative MRI of the hippocampus and amygdala in severe depression. Psychol Med 2000, 30:117-125. 250. Blumberg HP, Stern E, Martinez D, Ricketts S, de Asis J, White T, Epstein J, McBride PA, Eidelberg D, Kocsis JH, Silbersweig DA: Increased anterior cingulate and caudate activity in bipolar mania. Biol Psychiatry 2000, 48:1045-1052. p y 228. Bremner JD, Narayan M, Anderson ER, Staib LH, Miller HL, Charney DS: Hippocampal volume reduction in major depression. Am J Psychiatry 2000, 157(1):115-118. y y 251. Goodwin GM, Cavanagh JT, Glabus MF, Kehoe RF, O'Carroll RE, Ebmeier KP: Uptake of 99mTc-exametazime shown by single photon emission computed tomography before and after lithium withdrawal in bipolar patients: associations with mania. Br J Psychiatry 1997, 170:426-430. 229. Shah PJ, Ebmeier KP, Glabus MF, Goodwin GM: Cortical grey mat- ter reductions associated with treatment-resistant chronic unipolar depression. Controlled magnetic resonance imag- ing study. Br J Psychiatry 1998, 172:527-532. 230. Pearlson GD, Barta PE, Powers RE, Menon RR, Richards SS, Aylward EH, Federman EB, Chase GA, Petty RG, Tien AY: Medial and supe- rior temporal gyral volumes and cerebral asymmetry in schizophrenia versus bipolar disorder. Biol Psychiatry 1997, 41:1-14. 252. Freud S: Inhibitions, symptoms and anxiety 20th edition. London: Vin- tage; 1926. 253. http://www.annals-general-psychiatry.com/content/7/1/9 Neimat JS, Hamani C, Giacobbe P, Merskey H, Kennedy SH, Mayberg HS, Lozano AM: Neural stimulation successfully treats depres- sion in patients with prior ablative cingulotomy. Am J Psychiatry 2008, 165:687-693. 231. Bowley MP, Drevets WC, Ongür D, Price JL: Low glial numbers in the amygdala in major depressive disorder. Biol Psychiatry 2002, 52:404-412. 254. McNeely HE, Mayberg HS, Lozano AM, Kennedy SH: Neuropsycho- logical impact of Cg25 deep brain stimulation for treatment- resistant depression: preliminary results over 12 months. J Nerv Mental Dis 2008, 196:405-410. 232. Frodl T, Meisenzahl EM, Zetzsche T, Born C, Groll C, Jäger M, Leins- inger G, Bottlender R, Hahn K, Möller HJ: Hippocampal changes in patients with a first episode of major depression. Am J Psy- chiatry 2002, 159:1112-1118. 255. Eslinger PJ, Damasio AR: Severe disturbance of higher cognition after bilateral frontal lobe ablation: patient EVR. Neurology 1985, 35:1731-1741. y 233. Baumann B, Danos P, Krell D, Diekmann S, Leschinger A, Stauch R, Wurthmann C, Bernstein HG, Bogerts B: Reduced volume of lim- bic system-affiliated basal ganglia in mood disorders: prelim- inary data from a postmortem study. J Neuropsychiatry Clin Neurosci 1999, 11:71-78. 256. Cummings JL: Clinical neuropsychiatry New York: Grune and Stratton; 1985. 257. Beer JS, Heerey EA, Keltner D, Scabini D, Knight RT: The regula- tory function of self-conscious emotion: insights from patients with orbitofrontal damage. J Personal Soc Psychol 2003, 85:594-604. 234. Krishnan KR, McDonald WM, Escalona PR, Doraiswamy PM, Na C, Husain MM, Figiel GS, Boyko OB, Ellinwood EH, Nemeroff CB: Mag- netic resonance imaging of the caudate nuclei in depression. Preliminary observations. Arch Gen Psychiatry 1992, 49(7):553-7. 258. Moretti L, Dragone D, di Pellegrino G: Reward and social valua- tion deficits following ventromedial prefrontal damage. J Cogn Neurosci 2008. y y y ( ) 235. Sapolsky RM: Glucocorticoids and hippocampal atrophy in neuropsychiatric disorders. Arch Gen Psychiatry 2000, 57:925-935. p y y y 236. Nemeroff CB: The corticotropin-releasing factor (CRF) hypothesis of depression: new findings and new directions. Mol Psychiatry 1996, 1:336-342. 259. Seeley WW, Menon V, Schatzberg AF, Keller J, Glover GH, Kenna H, Reiss AL, Greicius MD: Dissociable intrinsic connectivity net- works for salience processing and executive control. J Neuro- sci 2007, 27:2349-2356. y y 237. Drevets WC: Neuroimaging abnormalities in the amygdala in mood disorders. Ann NY Acad Sci 2003, 985:420-444. 260. Goethe JWV: Faust. http://www.annals-general-psychiatry.com/content/7/1/9 The first part of the tragedy Hertfordshire, UK: Wordsworth Editions Ltd; 1808. 238. Rubin RT, Mandell AJ, Crandall PH: Corticosteroid responses to limbic stimulation in man: localization of stimulus sites. Sci- ence 1966, 153:767-768. 261. Albus JS, Bekey GA, Holland JH, Kanwisher NG, Krichmar JL, Mishkin M, Modha DS, Raichle ME, Shepherd GM, Tononi GA: Proposal for a Decade of the Mind initiative. Science 2007, 317:1321. 239. Sheline YI: Neuroimaging studies of mood disorder effects on the brain. Biol Psychiatry 2003, 54:338-352. 262. Sacks O: A leg to stand on London: Duckworth; 1984. 240. Finch DM: Hippocampal, subicular, and entorhinal afferents and synaptic integration in rodent cingulate cortex. In Neuro- biology of cingulate cortex and the limbic thalamus: a comprehensive hand- book Edited by: Vogt BA, Gabriel M. Boston: Birkhauser; 1993. 263. Kandel ER: Biology and the future of psychoanalysis: a new intellectual framework for psychiatry revisited. Am J Psychiatry 1999, 156:505-524. 264. Hering E: Uber das Gedachtnis al seine allgemaine Function der organi- sirten Materie Vienna: Imperial Academy of Sciences; 1870. y g 241. Falkai P, Bogerts B: Cell loss in the hippocampus of schizo- phrenics. Eur Arch Psychiatry Neurol Sci 1986, 236:154-161. 242 i i i i p y 265. Freud S: An autobiographical study 20th edition. London: Vintage; 1925. 265. Freud S: An autobiographical study 20th edition. London 266 Ab HA Th d l f p y y 242. Falkai P, Bogerts B, Rozumek M: Limbic pathology in schizophre- nia: the entorhinal region – a morphometric study. Biol Psychi- atry 1988, 24:515-521. 266. Abramson HA: The second international conference on the use of LSD in psychotherapy New York: The Bobbs-Merrill Company; 1967. p y py p y 267. Martin AJ: The treatment of twelve male homosexuals with LSD. Acta Psychother 1962, 10:394-402. y 243. Bogerts B, Häntsch J, Herzer M: A morphometric study of the dopamine-containing cell groups in the mesencephalon of normals, Parkinson patients, and schizophrenics. Biol Psychia- try 1983, 18:951-969. y 268. Grof S: Realms of the human unconscious. Observations from LSD research London: Souvenir Press; 1975. 269. Sandison RA: Psychological aspects of the LSD treatment of the neuroses. J Ment Sci 1954, 100:508-515. y 244. Radewicz K, Garey LJ, Gentleman SM, Reynolds R: Increase in HLA-DR immunoreactive microglia in frontal and temporal cortex of chronic schizophrenics. J Neuropathol Exp Neurol 2000, 59:137-150. J 270. http://www.annals-general-psychiatry.com/content/7/1/9 MacQueen GM, Campbell S, McEwen BS, Macdonald K, Amano S, Joffe RT, Nahmias C, Young LT: Course of illness, hippocampal function, and hippocampal volume in major depression. Proc Natl Acad Sci USA 2003, 100:1387-13892. 203. Mogenson GJ, Swanson LW, Wu M: Neural projections from nucleus accumbens to globus pallidus, substantia innomi- nata, and lateral preoptic-lateral hypothalamic area: an ana- tomical and electrophysiological investigation in the rat. J Neurosci 1983, 3:189-202. 223. Sheline YI, Wang PW, Gado MH, Csernansky JG, Vannier MW: Hip- pocampal atrophy in recurrent major depression. Proc Natl Acad Sci USA 1996, 93:3908-3913. 224. Sheline YI, Sanghavi M, Mintun MA, Gado MH: Depression dura- tion but not age predicts hippocampal volume loss in medi- cally healthy women with recurrent major depression. J Neurosci 1999, 19:5034-5043. 204. Di Martino A, Scheres A, Margulies DS, Kelly AM, Uddin LQ, Shehzad Z, Biswal B, Walters JR, Castellanos FX, Milham MP: Functional Page 21 of 23 (page number not for citation purposes) Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 Sandison RA: The contribution of LSD therapy to analytic the- ory and practice. Bull Br Psychol Soc 1957, 33:24. 271. Sandison RA: Certainty and uncertainty in the LSD treatment of psychoneurosis. In Hallucinogenic drugs and their psychotherapeu- tic use Edited by: Crocket R, Sandison RA, Walk A. London: Lewis HK; 1963. 245. Orlovskaya DD, Vikhreva OV, Zimina IS, Denisov DV, Uranova NA: Ultrastructural dystrophic changes of oligodendroglial cells in autopsied prefrontal cortex and striatum in schizophre- nia: a morphometric study. Schizophr Res 1999, 36:82-83. 272. Lewis DJ, Sloane RB: Therapy with lysergic acid diethylamide. J Clin Exp Psychopathol 1958, 19:19-31. p p 246. Webster MJ, Johnston-Wilson N, Nagata K, Yolken RH: Alterations in the expression of phosphorylated glial fibrillary acidic pro- teins in the frontal cortex of individuals with schizophrenia, bipolar disorder, and depression. Schizophr Res 2000, 41:106. p y p 273. Cutner M: Analytic work with LSD 25. Psychiatr Q 1959, 33:715-757. Page 22 of 23 (page number not for citation purposes) Page 22 of 23 (page number not for citation purposes) Annals of General Psychiatry 2008, 7:9 http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 http://www.annals-general-psychiatry.com/content/7/1/9 274. Rolo A, Krinsky LW, Goldfarb L: LSD as an adjunct to psycho- therapy with alcoholics. J Psychol 1960, 50:85-104. 275. Ling TM: The use of LSD and ritalin in the treatment of neu- rosis. In The second international conference on the use of LSD in psy- chotherapy Edited by: Abramson HA. New York: The Bobbs-Merrill Company; 1967. p y 276. Spencer AM: Permissive group therapy with lysergic acid diethylamide. Br J Psychiatry 1963, 109:37-45. 277. Spencer AM: Modifications in the technique of LSD therapy. Comp Psychiatry 1964, 5:232-252. 278. Abramson HA: Lysergic acid diethylamide (LSD-25): XIX. As an adjunction to brief psychotherapy with special reference to ego enhancement. J Psychology 1956, 41:199-229. g J y gy 279. Abramson HA: The use of LSD in psychotherapy New York: The Josiah Macy Jr Foundation; 1959. 280. Leuner H: Present state of psycholytic therapy and its possi- bilities. In The second international conference on the use of LSD in psy- chotherapy Edited by: Abramson HA. New York: The Bobbs-Merrill Company; 1967. 281. Osmond H: A comment on some uses of psychotomimetics in psychiatry. In The second international conference on the use of LSD in psychotherapy Edited by: Abramson HA. New York: The Bobbs-Mer- rill Company; 1967. p y 282. Busch AK, Johnson WC: LSD-25 as an aid to psychotherapy. http://www.annals-general-psychiatry.com/content/7/1/9 Dis- ease Nerv Sys 1950, 11:241. y 283. Grof S: The use of LSD-25 in personality diagnostics and ther- apy of psychogenic disorders. In The second international confer- ence on the use of LSD in psychotherapy Edited by: Abramson HA. New York: The Bobbs-Merrill Company; 1967. p y 284. Grof S: LSD psychotherapy Florida: MAPS; 1980. 285. Eisner BG: Communication to first international congress of CNIP, Rome. In The use of LSD in psychotherapy New York: The Josiah Macy Jr Foundation; 1959. 286. Vollenweider FX, Leenders KL, Scharfetter C, Maguire P, Stadelmann O, Angst J: Positron emission tomography and fluorodeoxy- glucose studies of metabolic hyperfrontality and psychopa- thology in the psilocybin model of psychosis. Neuropsychopharmacology 1997, 16:357-372. p y p gy 287. Hermle L, Fünfgeld M, Oepen G, Botsch H, Borchardt D, Gouzoulis E, Fehrenbach RA, Spitzer M: Mescaline-induced psychopatho- logical, neuropsychological, and neurometabolic effects in normal subjects: experimental psychosis as a tool for psychi- atric research. Biol Psychiatry 1992, 32:976-991. y y 288. Freud S: Two encyclopaedia articles 18th edition. London: Vintage; 1923. 289. Buckner RL, Andrews-Hanna JR, Schacter DL: The brain's default network: anatomy, function, and relevance to disease. Ann NY Acad Sci 2008, 1124:1-38. Publish with BioMed Central and every scientist can read your work free of charge "BioMed Central will be the most significant development for disseminating the results of biomedical research in our lifetime." Sir Paul Nurse, Cancer Research UK Your research papers will be: available free of charge to the entire biomedical community peer reviewed and published immediately upon acceptance cited in PubMed and archived on PubMed Central yours — you keep the copyright Submit your manuscript here: http://www.biomedcentral.com/info/publishing_adv.asp BioMedcentral Page 23 of 23 (page number not for citation purposes) Publish with BioMed Central and every scientist can read your work free of charge "BioMed Central will be the most significant development for disseminating the results of biomedical research in our lifetime." Sir Paul Nurse, Cancer Research UK Your research papers will be: available free of charge to the entire biomedical community peer reviewed and published immediately upon acceptance cited in PubMed and archived on PubMed Central yours — you keep the copyright Submit your manuscript here: http://www.biomedcentral.com/info/publishing_adv.asp BioMedcentral Publish with BioMed Central and every scientist can read your work free of charge Page 23 of 23 (page number not for citation purposes)
https://openalex.org/W2111212003
https://academicjournals.org/journal/AJMR/article-full-text-pdf/830F14122830.pdf
English
null
Investigation on clinical healthy swine carrier status of Streptococcus suis in Hebei Province of China
African journal of microbiology research
2,012
cc-by
3,401
Full Length Research Paper 1Key Laboratory of Preventive Veterinary Medicine in Hebei Province, Hebei Normal University of Science and Technology, Qinhuangdao, 066004 China. 2 Technology, Qinhuangdao, 066004 China. 2The Second Hospital of Qinhuangdao, Changli, 066600, China. gy, g , 2The Second Hospital of Qinhuangdao, Changli, 066600, China. Accepted 25 July, 2012 A total of 600 samples of nose swabs collected from Hebei Province, China, were examined by polymerase chain reaction (PCR) for the presence of Streptococcus suis in healthy swine and the serotype were identified. Results showed that 148 strains (24.67%) of 600 tested were positive with S. suis, including 27 strains (18.24%) were identified to be type 7, 24 strains (16.22%) were type 2 and 20 strains (13.51%) were type 9. But serotypes of other 75 strains (50.68%) were undetermined. To our knowledge, this is the first epidemiological investigation of S. suis in healthy swine from Hebei Province of China. Key words: Streptococcus suis, polymerase chain reaction (PCR), serotype, epidemiological. Key words: Streptococcus suis, polymerase chain reaction (PCR), serotype, epidemio Strains and antisera S. suis standard strain SS2 was provided by Professor Lu Chengping, Nanjing Agricultural University, China. Standard strains SS1, SS7, SS9 was donated by researcher Cai Xuehui, Harbin Veterinary Research Institute China. Standard antiserum of S. suis type 1, type 2, type 7, type 9, 1/2 and 14 types were taken from college of Veterinary Medicine, Nanjing Agricultural University. *Corresponding author. E-mail: mzj6699@126.com. Tel: +86- 0335-2039084. Fax: +86-0335-2039084. INTRODUCTION Streptococcus suis is an important pathogenic bacteria hazard in modern swine industry. It can be divided into 35 serotypes (type 1 to 34 and 1/2) according to the differences in antigenic properties of polysaccharide capsular. S. suis serotype 2 is considered to be the most widely popular and highest pathogenicity isolated in both swine and humans, which is also an important zoonotic pathogen. It reported that slaughterhouse employees can be infected with S. suis and to be considered as an occupational disease (He et al., 2000; Hu et al., 2000). In recent years, S. suis outbreaks in many countries from Europe, Americas and Asian. It can not only cause huge losses to the world's swine industry, but also endangers with public health and safety (Staats et al., 1997; Touil et al., 1998; Torremorell et al., 1998). S. suis serotype 2 (SS2) was discovered firstly in Guangdong Province, China, in 1990. There were two large outbreaks of SS2, people had been found infected with SS2 died in Jiang su, Si chuan Province, in 1998 (Shen et al., 2000; Liu et al., 2005). In addition to SS2, SS1, SS7, SS9, etc are also important serotypes in pigs. In order to investigate the presence of S. suis in normal swine herds in Hebei Province, 600 nasal swabs were collected from Shijiazhuang, Xingtai, Zhangjiakou, Cangzhou, Tangshan, Qinhuangdao and other areas of Hebei Province in May 2009 to October 2009, and then detected by polymerase chain reaction (PCR). This study can provide information for epidemiological investigation of S. suis, and has great significance for further monitoring and effective prevention to S. suis. African Journal of Microbiology Research Vol. 6(30) pp. 5900-5904, 9 August, 2012 Available online at http://www.academicjournals.org/AJMR DOI: 10.5897/AJMR12.186 ISSN 1996-0808 ©2012 Academic Journals African Journal of Microbiology Research Vol. 6(30) pp. 5900-5904, 9 August, 2012 Available online at http://www.academicjournals.org/AJMR DOI: 10.5897/AJMR12.186 ISSN 1996-0808 ©2012 Academic Journals Full Length Research Paper Investigation on clinical healthy swine carrier status of Streptococcus suis in Hebei Province of China Ping Rui1, Zeng-Jun Ma1*, Qiu-Yue Wang1, Xiang-zhai Zhang1, Jin-Xia Wang2, Yan-Ying Zhang1 and Hai Fang1 Full Length Research Paper Isolation and identification of S. suis 600 nasal swabs were collected from healthy pigs (different growth stage) on farms of Hebei Province in China, such as Shijiazhuang, Xingtai, Zhangjiakou, Cangzhou, Tangshan and Qinhuangdao. Samples were collected and processed to refrigerated storage. The strain was identified as S. suis in morphology. S. suis is Gram- positive cocci in pairs or short chains of broth cultures by microscopy. Bacterial liquid rules on blood agar plates, at 37°C for 18 ~ 24 h, 3~6 colonies each plate with α hemolytic, smooth, moist, white translucent, diameter 1 ~2 mm were picked selectively, and inoculated into 2 ml 5% bovine serum of THB, suspected of S. suis were stored at 4°C. Finally, PCR methods established above were used to identified the isolated bacteria. Serum agglutination test Each drop of diagnose serum antibodies known and bacilli were mixed in the slide, a few minutes after, it was identified as positive when there was emergence of visible agglutination. Also set up normal saline as control. PCR identification as S. suis serotype 2 were to have further identification with 1/2 Standard antiserum, PCR identification as S. suis serotype 1, and S. suis serotype 14 and 1/2 standard anti-serum were used for further identification, respectively. Bacteria culture and identification 100 μl samples of nasal swab were inoculated into 2 ml of Streptococcus liquid selection medium (containing 15 μg/ml polymyxin B, 30 μg/ml nalidixic acid and 0.2 g/ml crystal purple) for 18 to 24 h at 37°C, S. suis was observed in Gram's method by a microscope. Primers Five pairs of primers were designed according to the reference (Okwumabua et al., 2003; Smith et al., 1999; Wang et al., 2009) respectively and synthesized in Sangon Biotech (Shanghai) Co., LTD. The details of the primers were listed in Table 1. Medium and reagents The PCR products were detected by electrophoresis in 1.2% agarose gel. Preparation of the templates 1000 μl Gram-positive Streptococcus culture liquid were centrifuged at 10000r / min for 1 min, supernatant was discarded, resuspended with 200 μl ddH2O and then boiled for 10 min, after cooling, centrifuged at 7000r / min for 5 min, supernatant were stored at - 20°C. DNA was extracted using Bacteria genomic DNA extraction kit. Medium and reagents Medium was purchased from Qingdao Haibo biotech companies. Brain heart infusion broth was purchased from Oxoid company, Rui et al. 5901 5901 Rui et al. Table 1. Primers of S. suis. Target genes Primers’sequences(5′ to 3′) Annealing temperature (°C) Length (bp) References gdh-1 gdh-2 GCAGCGTATTCTGTCAAACG CCATGGACAGATAAAGATGG 55 689 Okwumabua et al. (2003) cps1I-1 cps1I-2 GGCGGTCTAGCAGATGCTCG GCGAACTGTTAGCAATGAC 55 441 Smith et al. (1999) Cps2J-1 Cps2J-2 ATGTTTGGAATACGCAGAGCAAAGAT CAACAAGGGCTATTAAAGATACCGC 55 351 Wang et al. (2009) cps7H-1 cps7H-2 AGCTCTAACACGAAATAAGGC GTCAAACACCCTGGATAGCCG 55 251 Wang et al. (2009) cps9H-1 cps9H-2 GGCTACATATAATGGAAGCCC CCGAAGTATCTGGGCTACTG 55 388 Smith et al. (1999) ExTaq polymerase (5U/L), dNTPs (2.5 mmol/L each), 10 × PCR buffer (containing MgCL2), DNA Marker DL2000 were purchased from TaKaRa Company, bacterial genomic DNA extraction kit purchased from Tiangen Biotech(Beijing) CO.,LTD. Samples were also identified by PCR based on the S. suis serotype 1,2,7,9. The final PCR volume was 25 μl, the reaction components are as follows: 10×PCR bufferr (Mg2+ Plus) 2.5 μl, dNTPs Mixture (2.5 mM) 2.0 μl, upstream and downstream primer 1.0 μl, Ex Taq DNA polymerase 0.2 μl (5 U), DNA template 2.5 μl, added ddH2O to 25 μl. PCRs consisted of 30 cycles of denaturation for 5 min at 95°C, then 95°C denaturation 15S (gdh and cps1I) or 94°C for 30 s (Cps2J, Cps7H, Cps9H), annealing at 55°C for 45 s, and extension for 30 s at 72°C. A final extension was performed for 10 min at 72°C. PCR reaction condition of the rest genes are the same as except for annealing temperature. Simultaneously, negative control was designed. The PCR products were detected by electrophoresis in 1.2% agarose gel. Samples were also identified by PCR based on the S. suis serotype 1,2,7,9. The final PCR volume was 25 μl, the reaction components are as follows: 10×PCR bufferr (Mg2+ Plus) 2.5 μl, dNTPs Mixture (2.5 mM) 2.0 μl, upstream and downstream primer 1.0 μl, Ex Taq DNA polymerase 0.2 μl (5 U), DNA template 2.5 μl, added ddH2O to 25 μl. PCRs consisted of 30 cycles of denaturation for 5 min at 95°C, then 95°C denaturation 15S (gdh and cps1I) or 94°C for 30 s (Cps2J, Cps7H, Cps9H), annealing at 55°C for 45 s, and extension for 30 s at 72°C. A final extension was performed for 10 min at 72°C. PCR reaction condition of the rest genes are the same as except for annealing temperature. Simultaneously, negative control was designed. Fig 3 Figure 3. PCR result of cps1I gene from S.suis M: DS2000 Maker; 1-2, cps1I positive strain; 3, positive control. esult of cps1I gene M k 1 2 1I Figure 2. PCR result of cps2J gene from S. suis M: DS2000 Maker; 1-6, cps2J positive strain; 7, negative control. Fig 3: M: DS 3, Pos from S M: DS 1 2 3 M M 1 2 3 4 5 6 7 M 1 2 3 4 5 6 7 Figure 1. PCR result of gdh gene from S. suis. M: DS2000 Maker; 1-7, gdh positive strain; 8, negative control. Fig 1: PCR result of gdh gene from S.su M: DS2000 Maker;1-7, gdh positive strai ti t l M 1 2 3 4 5 6 7 8 S.suis train; 8, Fig M: 7, n Figure 3. PCR result of cps1I gene from S.suis M: DS2000 Maker; 1-2, cps1I positive strain; 3, positive control. esult of cps1I gene f Maker;1 2 1I R result of cps2J gene 00 Maker;1-6, cps2J p e control. Figure 1. PCR result of gdh gene from S. suis. M: DS2000 Maker; 1-7, gdh positive strain; 8, negative control. Fig 1: PCR result of gdh gene from S.s M: DS2000 Maker;1-7, gdh positive stra i l M 7, cps9H genes of some strains respectively are shown as Figures 1, 2, 3 and 4. bp DNA ladder;1, cps7H posit H positive strain PCR identification of S. suis PCR analysis showed that 148 samples in 600 nasal Firstly, GDH sequence of S. suis was applied to identify the strain. 5902 Afr. J. Microbiol. Res. Table 2. Results of S. suis positive rates. negative Table 2. Results of S. suis positive rates. Regions Samples number SS positive number Positive rate (%) Qinhuangdao 100 30 30 Tangsan 100 32 32 Xingtai 100 25 25 Shijiazhuang 100 34 34 Zhangjiakou 100 11 11 Cangzhou 100 17 17 Total 600 148 24.67 negative control. M 1 2 3 4 5 6 7 1 2 3 M ontrol. M 1 2 3 4 Figure 4. PCR result of cps7H and cps9H gene from S. suis M: 100 bp DNA ladder;1, cps7H positive strain; 3-4, cps9H positive strain. Maker;1-7, gdh po result of cps7H and c Figure 2. PCR result of cps2J gene from S. suis M: DS2000 Maker; 1-6, cps2J positive strain; 7, negative control. swabs were positive for S. suis, the positive rate was 24.67%, results were shown in Table 2. Zhangjiakou, Cangzhou positive rates were 11 and 17%, significantly lower than other regions, the difference was significant (p<0.01), Qinhuangdao, Tangshan, Shijiazhuang positive samples were high, were 30, 32 and 34%, significantly higher than other regions, which showed that the S. suis infection had some regional differences (Table 2). The electrophoresis graphs of gdh, cps2J, cps1I, cps7H and rom S.suis positive strain; Fig 4: S.suis M: 100 4 cps9 Figure 4. PCR result of cps7H and cps9H gene from S. suis M: 100 bp DNA ladder;1, cps7H positive strain; 3-4, cps9H positive strain. result of cps7H and c cps9H genes of some strains respectively are shown as Figures 1, 2, 3 and 4. bp DNA ladder;1, cps7H posit H positive strain Rui et al. 5903 5903 Rui et al. Table 3. Major pathogenic S. suis serotype carrying cases in different regions. Region Total sample number S.suis positive number SS1 n (%) SS2 n (%) SS7 n (%) SS9 n (%) others n (%) Qinhuangdao 100 1(1.0) 6(6) 4(4) 1 (1) 18(18) Tangshan 100 0 5(5) 5(5) 10(10) 12(12) Xingtai 100 0 4(4) 1(1) 6(6) 14(14) Shijiazhuang 100 0 4(4) 12(12) 4(4) 14(14) Zhangjiakou 100 0 1(1) 2(2) 0 8(8) Cangzhou 100 1(1) 4(4) 3(3) 0 9(9) Total 600 2(0.33) 24(4) 27(4.5) 20(3.3) 75(12.5)) Table 4. Different S. suis serotypes mixed infection. Total sample number SS positive sample number SS positive sample number SS2+SS7 n (%) SS2+SS9 n (%) SS7+SS9 n (%) SS2+SS7+SS9 n (%) SS1+ SS2 n (%) 600 148 6(1) 4(0.67) 10(1.67) 3(0.5) 1(0.17) Table 4. Different S. suis serotypes mixed infection. Major pathogenic S. suis serotype carrying cases in different regions S. suis strains were obtained, isolated rate was 11.55%. SS2 and SS7 were the most, each 11 stains was (2.08%). SS9 were 8 (1.52%), SS1 was not isolated. No- finalized SS were 31 stains (5.87%). Serum agglutination test Results for 30 isolates with a slide serum agglutination test showed that 11 S. suis serotype 2 bacilli only had antiserum agglutination with S. suis type 2, not with S. suis 1/2 type, so it was judged as S. suis type 2. S. suis serotype 7 (11) and type 9 (8) bacilli had specific agglutination with S. suis serotype 7, type 9 antiserum respectively. All results were consistent with the PCR analysis results. DISCUSSION The S. suis detection rate is different in the normal swine herds in different regions of China. Yang et al. (2009) reported 14 strains of S. suis in 248 pig tonsils were detected collected from 20 different regions of China, S. suis isolated from the tonsils were obtained from southern region of China, which may be related to S. suis outbreak and its hot and humid climate in south. Lu et al. (2008) isolated a highly pathogenic S. suis type 2 containing eight major virulence factor from 40 tonsil collected from a slaughterhouse, Jiangsu Province. Luo et al. (2009) investigated the carrying S. suis of healthy pigs from nasal swabs, throat swabs and tonsil in Ziyang, S. suis type 2 was only detected, S. suis carrier rate was 14.93%, concentrated in July, has a more obvious S. suis serotype mixed infections in different parts Statistics of nasal swab test results showed that the same one sample could be infected with two or more different serotypes of Streptococcus suis. But the samples were limited,the proportion in the sample was less than 5%. The samples of infected with both SS7 and SS9 sample were the most, up to 1.67% of the total sample, both SS2 and SS7 were the second, accounting for 1%, both SS2 and SS9 infection accounted for 0.67%. There were also infected with SS2, SS7 and SS9 or more serotypes, but the proportion was very small, only 0.5%. (Table 4). ontrol. M 1 2 3 4 PCR test results showed that each serotype carrying case as follows: SS7 were the highest (4.5%), followed by SS2 up to 4%; SS9 of 3.3%; SS1 was the least, only 0.33%. The positive rate of SS7 in Shijiazhuang or Qinhuangdao was significantly (p<0.01) higher than other areas; SS1 positive rate was lower, in addition to one was detected in Qinhuangdao, Cangzhou, other regions were not detected positive. The positive rate of SS9 in Qinhuangdao was significantly higher than other regions (p <0.01) (Table 3). REFERENCES He JH, Xu JX, Hou JB, Qian JF, Wang JC, Liu DX, Zhu CG, Xing JC, Zhang ZJ, Lu JG, Gao SW (2000). One cases pigs of outbreak and epidemiology of Acute septicemia caused by streptococcus suis Ⅱ. Chin. J. Zoonoses 16(l):109. ( ) Hu XS, Zhu FC, Wang H, Chen SY, Wang GH, Sun JZ, Hua CT, Yang HF (2000). Studies on human streptococcal infectious syndrome Hu XS, Zhu FC, Wang H, Chen SY, Wang GH, Sun JZ, Hua CT, Yang HF (2000). Studies on human streptococcal infectious syndrome caused by infected pigs. Chin. J. Prev. Med. 34(3):150-152. Liu HL, Zhao YG , Wang JW, Zhao YL, Li L, Zheng DX, Sun CY, Wang S, Liu PL, Song CP , Fan WX, Chen YP , Wang ZL (2005). Isolation and identification of pathogen related to recent outbreak of pig- human infection in Sichuan province. Chin. J. Microbiol. Immunol. 25(12):1006-1010. ( ) Lu LX, He KW, Ni YX, Zhang XH, Yu ZY, Zhou JM (2008). Isolation and identification of virulent Streptococcus suis type 2 fromtonsillar specimens of slaughtered healthy pigs. Chin. J. Zoonoses 24(4):379- 383. p g Study found that SS7 had the highest detection rate, 4.5%, followed by SS2, SS9, and the detection rates were 4 and 3.3% respectively, these results suggested SS2, SS7 and SS9 were the most important popular serotypes in the Hebei region of China, and SS2 was zoonotic disease. More attention should be paid to this disease. SS7 was the highest detection strain. The authors found the pig cases infected with SS7 in Hebei, therefore, it needs to conduct deeper research on SS7 and strengthen prevention and control. SS1 carrier rate was relatively low (0.33%). There were multiple S. suis serotypes in the same nasal swabs by PCR, but it was small rate related to the carrier rate of each serotypes, its epidemiological significance remains to be studied. The study also found that, samples collected from Zhangjiakou, Cangzhou was significantly lower than other places of the province, can be inferred there are some regional differences in SS infection or the incidence of different farms will be different. Luo LZ, Wang X, Cui ZG, Li YC, Guo ZQ, Jin D, Zheng H, He SS, Liu XC, Jia Y, Liao AB, Jing HQ (2009). Isolation of Streptococcus suis type 2 from healthy pigs in Ziyang district of Sichuan province and analysis of their molecular characteristics. Chin. J. REFERENCES Zoonoses 25(9):842-845. ( ) Okwumabua O, O’Connor M, Shull E (2003). A polymerase ehain reaction (PCR) assay specific for Streptococcus suis based on the gene encoding the glutamate delydrogenase [J]. FEMS Microbiol. Lett. 218:79-84. Shen J, Sun JZ, You YM, Bo YJ, Wang CL, Zang L, Chen SY (2000). Analysis of prevention and control effect on Human Streptococcal Infectious Syndrome Caused by Infected Pigs in Rugao city. J. Math. Med. 13(3):257-258. Smith HE, Veenbergen V, van der Velde J, Damman M, Wisslink HJ, Smits MA (1999). The cps genes of Streptococcus suis serotypes 1, 2, and 9: development of rapid serotype-specific PCR assays [J]. J. Clin. Microbiol. 37:3146-3152. Staats JJ, Feder I, Okwumabua O, Chengappa MM (1997). Streptococcus suis past and present. Vet. Res. Commun. 21(6):381- 407. Torremorell M, Calsamiglia M, Pijoan C (1998). Colonization of sucking pigs by Streptococcus suis with particular reference to pathogenic sereotype 2 strains. Can. J. Vet. Res. 62(l):21-26. yp ( ) Touil F, Higgins R, Nadeau M (1988). Isolation of Streptococcus suis from diseased pigs in Canada. Vet. Microbiol. 17(2):171-177. PCR is the most commonly method for the detection of S. suis. But PCR cannot distinguish between S. suis type 1 and type 14, S. suis 1/2 and type 1, type 2. To make test results more accurate, standard antiserum of S. suis type 2, type 7, type 9, 14 and 1/2 prepared by our laboratory were used to have a re-examination for this epidemiological survey. S. suis type 1 and 1/2 were not isolated in this study, it may be relative to the two serotypes little in Hebei Province. Wang SJ, Lei LC, Xu M, Sun CJ, Li CJ, Cai XH, Liu YG, Zhang Q, Liu DQ, Shi WD (2009). Isolation, identifiation and epidemiological analysis of swine Streptococcus in the northeast region of China. Chin. J. Vet. Sci. 29(7):877-881. Yang Z, Wang KC, Fan WX, Jiang P (2009). Epidemiological investigation on the carrier status of Streptococcus suis in healthy pigs. Chin. J. Zoonoses 25(10):977-979. Bacterial isolatation and PCR results Gram-positive cocci in pairs or short chains of 528 broth cultures by microscopic examination were isolated, 61 Afr. J. Microbiol. Res. Afr. J. Microbiol. Res. 5904 REFERENCES seasonal characteristics. However, there were no related reports about carrying S. suis cases in clinical healthy pig herds in Hebei Province. In this study, 600 healthy pigs nasal swabs were first detected by PCR and isolate collected from 6 different regions of Hebei Province, 148 samples were found to be SS-positive (24.67%), mainly prevalent serotypes of S. suis type 1 , type 2, type 7, type 9, total 73, other types were 75, was lower than S. suis detected in Heilongjiang (29%), Jilin (27%), Liaoning (34%) Province, report by Shu-Jie Wang et al. (2009). It confirmed that S. suis is also widespread in Hebei Health pig herds, and the coexistence of multiple serotypes, indicating that pigs carrying S. suis serotype is complex and diverse in normal pigs farms. ACKNOWLEDGEMENT This study was financially supported by grant from Natural funded project of Hebei (No.C2009000877), Education Department of Hebei Province (No. 2008448).
https://openalex.org/W4387905658
https://www.nature.com/articles/s41396-023-01546-2.pdf
English
null
Genomic and transcriptomic insights into complex virus–prokaryote interactions in marine biofilms
˜The œISME journal
2,023
cc-by
11,476
ARTICLE OPEN Genomic and transcriptomic insights into complex virus–prokaryote interactions in marine biofilms Kun Zhou 1,2,3, Tin Yan Wong 4, Lexin Long1, Karthik Anantharaman 3, Weipeng Zhang 1, Wai Chuen Wong 1, Rui Zhang5✉and Pei-Yuan Qian 1,2✉ Kun Zhou 1,2,3, Tin Yan Wong 4, Lexin Long1, Karthik Anantharaman 3, Weipeng Zhang 1, Rui Zhang5✉and Pei-Yuan Qian 1,2✉ © The Author(s) 2023 Marine biofilms are complex communities of microorganisms that play a crucial ecological role in oceans. Although prokaryotes are the dominant members of these biofilms, little is known about their interactions with viruses. By analysing publicly available and newly sequenced metagenomic data, we identified 2446 virus–prokaryote connections in 84 marine biofilms. Most of these connections were between the bacteriophages in the Uroviricota phylum and the bacteria of Proteobacteria, Cyanobacteria and Bacteroidota. The network of virus–host pairs is complex; a single virus can infect multiple prokaryotic populations or a single prokaryote is susceptible to several viral populations. Analysis of genomes of paired prokaryotes and viruses revealed the presence of 425 putative auxiliary metabolic genes (AMGs), 239 viral genes related to restriction–modification (RM) systems and 38,538 prokaryotic anti-viral defence-related genes involved in 15 defence systems. Transcriptomic evidence from newly established biofilms revealed the expression of viral genes, including AMGs and RM, and prokaryotic defence systems, indicating the active interplay between viruses and prokaryotes. A comparison between biofilms and seawater showed that biofilm prokaryotes have more abundant defence genes than seawater prokaryotes, and the defence gene composition differs between biofilms and the surrounding seawater. Overall, our study unveiled active viruses in natural biofilms and their complex interplay with prokaryotes, which may result in the blooming of defence strategists in biofilms. The detachment of bloomed defence strategists may reduce the infectivity of viruses in seawater and result in the emergence of a novel role of marine biofilms. The ISME Journal (2023) 17:2303–2312; https://doi.org/10.1038/s41396-023-01546-2 The ISME Journal (2023) 17:2303–2312; https://doi.org/10.1038/s41396-023-01546-2 Received: 15 June 2023 Revised: 12 October 2023 Accepted: 16 October 2023 1Department of Ocean Science, The Hong Kong University of Science and Technology, Hong Kong, China. 2Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China. 3Department of Bacteriology, University of Wisconsin–Madison, Madison, WI, USA. 4Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong, China. 5Institute for Advanced Study, Shenzhen University, Shenzhen 518060, China. ✉email: ruizhang@szu.edu.cn; boqianpy@ust.hk www.nature.com/ismej Received: 15 June 2023 Revised: 12 October 2023 Accepted: 16 October 2023 Published online: 24 October 2023 1Department of Ocean Science, The Hong Kong University of Science and Technology, Hong Kong, China. 2Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China. 3Department of Bacteriology, University of Wisconsin–Madison, Madison, WI, USA. 4Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong, China. 5Institute for Advanced Study, Shenzhen University, Shenzhen 518060, China. ✉email: ruizhang@szu.edu.cn; boqianpy@ust.hk Received: 15 June 2023 Revised: 12 October 2023 Accepted: 16 October 2023 Published online: 24 October 2023 MATERIALS AND METHODS DNA and RNA extraction and sequencing of biofilms established in Hong Kong waters Total RNA was divided into three repeats, and they were separately sequenced using the NovaSeq platform (Illumina) by Novogene Company (Beijing, China) with a 150 bp short-insert library to generate 10 Gb paired-end reads for each repeat sample. In this work, we studied publicly available metagenomic data generated from biofilms and surrounding seawater samples from the South China Sea, East China Sea, Red Sea and South Atlantic [11] and three additional metagenomes of biofilms developed in Hong Kong waters. To demonstrate viral and prokaryotic gene expression, we produced the three metatran- scriptomes of biofilms established in Hong Kong waters. Using a large set of omics data, we aimed to predict virus–prokaryote pairs, identify genes related to auxiliary metabolism and counter-defence in viral genomes and determine defence systems in the prokaryotic genomes of biofilms and surrounding seawater. We hypothesise that viruses are active in natural marine biofilms, and the infections they cause lead to the proliferation of prokaryotic defence strategists, which may enhance anti-viral resistance in seawater when they return to a free-living style through detachment. Metagenome assembly and identification of viral sequences The sequenced reads of three HK-2022 biofilms and the raw Illumina reads of publicly available biofilms and seawater samples (Fig. 1a and Table S1) Fig. 1 Virus–host pairs and their distribution in marine biofilms. a Global location of marine biofilms in the study. The quantities of datasets are indicated by numbers enclosed in brackets. The ocean map underwent modification using ArcGIS online maps (available at https://www.arcgis.com/). b Virus–prokaryote connections at the phylum rank. The number of pairs was indicated after each phylum. c Distribution of virus–prokaryote pairs in biofilms in the oceans. ECS: East China Sea (30° 42′ 00.0′′ N 122° 49′ 12.0′′ E). HKW: Hong Kong waters (22° 20′ 24.0′′ N 114° 16′ 12.0′′ E). RS: Red Sea (22° 12′ 00.0′′ N 39° 01′ 48.0′′ E). CSCS: Central South China Sea (14° 00′ 00.0′′ N 116° 00′ 00.0′′ E). SY: Sanya (18° 13′ 48.0′′ N 109° 29′ 24.0′′ E). SA: South Atlantic (31° 25′ 12.0′′ N 81° 18′ 00.0′′ W). ZH: Zhuhai (21° 42′ 00.0′′ N 114° 21′ 00.0′′ E). d Shared phage–bacteria pairs in different biofilms from Hong Kong waters (e.g. Biofilm1 shared Uroviricota–Proteo- bacteria pairs with Biofilm2) and the Red Sea (e.g. Biofilm9 shared Uroviricota–Cyanobacteria pairs with Biofilm10). Biofilm1: HK-2022-1. Biofilm2: HK-2022-2. Biofilm3: SRR6854594.1. Biofilm4: SRR6854592.1. Biofilm5: SRR6854597.1 Biofilm6: SRR6854601.1. Biofilm7: SRR6854599.1. Biofilm8: SRR6854598.1. MATERIALS AND METHODS DNA and RNA extraction and sequencing of biofilms established in Hong Kong waters employed by bacteria to counter viral attacks through signalling systems (e.g. quorum sensing) or anti-viral defence systems (e.g. CRISPR–Cas system [CRISPR stands for clustered regularly interspaced short palindromic repeat]) [7]. However, viruses trapped in a biofilm matrix can remain active and infect colonising cells, as demonstrated in T7 phages [17]. One of the ways for viruses to penetrate the EPS matrix and access host cells is to encode depolymerases that degrade polymeric substances [18]. In addition, viruses can use biofilm channels for diffusion to target bacterial hosts [19]. The interplay between bacteria and phages under laboratory conditions indicates complex virus–prokaryote interactions in natural environments and triggers our interest to investigate natural marine biofilms. I hi k di d bli l il bl i d g g Biofilms were developed with polystyrene Petri dishes at Hong Kong waters (22° 20′ 24.0′′ N, 114° 16′ 12.0′′ E, depth of 1–2 m) for gene expression analyses. After a 25-day development period, biofilms were collected in April 2022 and named HK-2022 biofilms. Three biofilm samples on the surfaces were collected immediately with sterile cell scrapers and stored separately in DNA buffer (500 mmol/L NaCl, 50 mmol/L Tris–HCl, 40 mmol/L EDTA and 50 mmol/L glucose referring to [11]) for DNA extraction. The three biofilms were merged into one and immediately transferred to RNAprotect Bacteria Reagent (QIAGEN, Hilden, Germany) for RNA storage. To extract the total DNA of microbiomes including viruses, we used polyethylene glycol (PEG) to concentrate viral particles. In brief, the pH of the virus-containing supernatant (biofilms in DNA buffer) was adjusted to pH 7.5. PEG (MW 6000) was added to a final concentration of 10% (w/v) and incubated at 4 °C for 8 h, followed by centrifugation at 10,000 × g for 1 h. Finally, the total DNA of metagenomes was extracted using DNeasy PowerBiofilm kit (QIAGEN, Hilden, Germany) according to the manufacturer’s protocol. Libraries with an insert size of approximately 350 bp were constructed and sequenced on the HiSeq X Ten platform (Illumina) with a read length of 150 bp (Novogene, Beijing, China). For RNA extraction, the total RNA of merged biofilms was extracted using the Rneasy PowerBiofilm kit (Qiagen, Hilden, Germany) according to the manufacturer’s protocol. INTRODUCTION 97%) globally [11]. Over 25,000 species are likely to be present in marine biofilms according to an empirical study which demon- strated that 16 S rRNA gene sequence similarity between most strains exceeds 97% [12]. A large number of prokaryotic species constitute more than 30 phyla, such as Proteobacteria, Acidobac- teria, Actinobacteria and Crenarchaeota, and Proteobacteria is the predominant group [6, 11]. Marine biofilms have a distinct microbial community composition, as evidenced by a metage- nomic survey that unveiled 7300 OTUs unique to marine biofilms [11]. Despite these findings, prokaryotic interactions with viruses in marine biofilms have not been explored. Microbial biofilms are surface-attached mixed communities of microorganisms, including eukaryotes (e.g. diatoms and fungi), prokaryotes (bacteria and archaea) and acellular viruses, which are enclosed in a matrix of extracellular polymeric substances (EPSs) [1, 2]. The microbial biofilms are widely distributed on marine substrate surfaces, which include seawater surfaces, coastal rocks, zooplankton, phytoplankton, sea floors, animal bodies and artificial surfaces [2]. They play prominent ecological roles in oceans; specifically, they facilitate the degradation of organic pollutants, contribute to photosynthesis, participate in biogeo- chemical cycling and influence the productivity of coastal ecosystems [3, 4]. Viruses are the most abundant biological entities on Earth [13]. They are a major cause of microbial mortality and help shape the community composition of planktonic prokaryotes [14]. However, viral predation is limited in biofilms, as living in biofilms offers more benefits to microorganisms than seawater, particularly under adverse conditions [15]. In laboratory experi- ments, biofilm structure and composition were found to inhibit viral predation [7]. For instance, the EPS matrix of a biofilm structure can entrap viruses and inhibit their diffusion, thereby limiting access to prokaryotic cells, such as the cultured bacterium Pantoea stewartia [16]. Other mechanisms can be In oceans, prokaryotes dominate marine biofilms [5–7], and the dominant prokaryotes have been thoroughly investigated. Nearly 90 years ago, ZoBell and Anderson showed that biofilm bacteria on bottle glass surfaces outnumbered bacteria in seawater [8]. On abiotic or biotic surfaces, such as marine-grade plywood substrates or macroalgae, prokaryotic density can reach 108 cells per square centimetre [9, 10]. More than 25,000 operational taxonomic units (OTUs) of the 16 S rRNA genes of marine biofilm prokaryotes have been clustered (threshold of sequence identity: K. Zhou et al. 2304 MATERIALS AND METHODS DNA and RNA extraction and sequencing of biofilms established in Hong Kong waters MATERIALS AND METHODS DNA and RNA extraction and sequencing of biofilms established in Hong Kong waters Given that eukaryotic scaffolds might be misidentified as viral sequences by DeepVirFinder or Seeker, eukaryotic sequences were recognised by CAT v4.6 (--fraction 1 at phylum rank) against the NCBI-nr database [27]. When a viral sequence candidate belonged to the identified eukaryotes, this sequence candidate was removed. The remaining scaffolds, classified as low-quality, medium-quality, high-quality or complete sequences by CheckV v0.7.0 (end_to_end) [28], were identified as viral sequences. from a previous study [11] were retrieved from the NCBI database (BioProject accession: PRJNA438384). Raw reads were trimmed by Trimmo- matic v0.36 [20] with custom parameters (ILLUMINACLIP: TruSeq3- PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:40) to remove adaptors and low-quality reads. The quality-controlled reads were assembled using SPAdes v3.11.1 (--meta) [21]. Viral sequence candidates (scaffolds ≥5 kb) were identified from assembled metagenomic sequences by multiple identifiers, including VirSorter v1.0.5 (searching against the RefSeqABVir database; hallmark gene number ≥1) [22], VirSorter2 v2.2.3 (score≥0.9 and/or hallmark gene number ≥1) [23], VIBRANT v1.2.0 (categorised as lytic or lysogenic phages) [24], Seeker (score≥0.7) [25] and DeepVirFinder (score≥0.9, p < 0.05) [26], which rely on protein similarity and/ or machine-learning models. Given that eukaryotic scaffolds might be misidentified as viral sequences by DeepVirFinder or Seeker, eukaryotic sequences were recognised by CAT v4.6 (--fraction 1 at phylum rank) against the NCBI-nr database [27]. When a viral sequence candidate belonged to the identified eukaryotes, this sequence candidate was removed. The remaining scaffolds, classified as low-quality, medium-quality, high-quality or complete sequences by CheckV v0.7.0 (end_to_end) [28], were identified as viral sequences. CheckV and were associated with Dividoviricota, Duplornaviricota, Hofnei- viricota, Phixviricota, Preplasmiviricota and Uroviricota, which infect prokaryotes according to the Virus–Host DB (https://www.genome.jp/ virushostdb/) [35]. Whether the candidates are viruses infecting prokar- yotes was determined by virus–host prediction. Putative virus–host connections between the virus candidates and prokaryotic bins extracted with metaWRAP from biofilm microbiomes were identified according to any of the following criteria: (1) sequences from a viral fragment/bin/ complete genome and scaffolds from a prokaryotic bin had ≥70% BLASTn identity (E-value ≤10−3) and ≥2.5 kb alignment length [36, 37]. (2) The CRISPR spacers >6 bp predicted with MetaCRT [38, 39] from a prokaryotic genome bin identically matched the genome sequences of a viral fragment/bin/complete genome [37, 40] with fuzznuc [41]. (3) The tRNA genes from a viral fragment/bin/complete genome were identical to the tRNA from a prokaryotic bin (using BLASTn) [40, 42]. Identification of shared virus–prokaryote pairs between biofilms Identification of proviral sequences and closed viral genomes Some putative viral scaffolds might be derived from proviruses that are components of host chromosomes. The proviral scaffolds were predicted based on the following criteria: (1) scaffolds were classified as sequences containing proviruses by CheckV v0.7.0 (end_to_end) [28]; and (2) scaffolds were from the prokaryotic bins that were extracted using metaWRAP v1.2 (-l 1000 bp -metabat2 -maxbin2 -concoct; bin_refinement; completeness ≥50, contamination ≤10) [29]. Referring to a prior study [28], CheckV was used to predict closed viral genomes that should meet all the following criteria: (1) scaffolds were in the type of DTR; (2) scaffolds were not obtained from proviruses identified above; (3) scaffolds did not contain low-complexity repeats; (4) repeats were without Ns that represented gaps; (5) repeat number should be lower than six in one scaffold; and (6) the repeat region must be less than 20% of the scaffold in length. Viral and prokaryotic genomes were assigned to ‘populations’ based on average nucleotide identity (ANI). FastANI v.1.33 was employed to calculate ANI for viruses with custom parameters (--fragLen 500 -minFraction 0.8) and for prokaryotic hosts with a custom setting (-minFraction 0.5) [44]. If the paired viruses and prokaryotes in different biofilms belonged to the same populations (ANI ≥95%), then the virus–prokaryote pairs were shared between the compared biofilms. MATERIALS AND METHODS DNA and RNA extraction and sequencing of biofilms established in Hong Kong waters (4) Sequences from a viral fragment/bin/complete genome and scaffold(s) from a prokaryotic bin shared exact matches (k-mer length = 25) after alignment-free PHIST v1.0.0 with default parameters was used [43]. Calculation of average read coverage and virus-to- prokaryote ratios y Paired viral and prokaryotic genome sequences, along with metagenomic reads, were input into Bowtie2 version 2.3.4 [45] and SAMtools version 1.6 [46] to calculate the average sequencing depth with default parameters. Viral bins and closed genomes that can represent viral populations and their prokaryotic host genomes were selected to estimate virus-to- prokaryote ratios. A prokaryotic host paired with multiple viruses indicated the accumulation of the read coverage of all the viruses. Identification of auxiliary metabolic genes Identification of auxiliary metabolic genes Prodigal [31] with customised settings (-c, -m) was used to analyse genomes of viruses paired with prokaryotes to predict ORFs. Subsequently, the ORFs were searched against the Kyoto Encyclopedia of Genes and Genomes (KEGG) database [48] using KofamScan version 1.2.0 (E-value < 10−5, score>predefined thresholds by KofamScan) [49]. The ORFs were imported into HMMScan (E-value < 10−3 and bit score>30) [50] for further annotation based on the PFAM database [34]. ORFs with KEGG and PFAM annotation were then searched against a viral AMG database derived from previous studies [37, 51–58] including experimentally verified AMGs [51, 53–55, 57], and a set of PFAM and KEGG accessions of the AMGs was retrieved. ORFs with the retrieved PFAM and KEGG accessions were retained and incorporated into the set of AMGs. After identification based on customised scripts, VIBRANT v1.2.0 was used to automatically predict other possible AMGs, which were classified into the category of KEGG metabolic pathways. Lastly, gene position in viral scaffolds (in the classifications of genome fragments and bins) and functional annotation of all the putative AMGs were manually checked. MATERIALS AND METHODS DNA and RNA extraction and sequencing of biofilms established in Hong Kong waters Biofilm9: SRR6869052.1. Biofilm10: SRR6869055.1. Biofilm11: SRR6869053.1. Biofilm12: SRR6869051.1. e Complex virus–prokaryote pairs in marine biofilms. A subnetwork highlighted within a black box was magnified on the left side to provide detailed information. Fig. 1 Virus–host pairs and their distribution in marine biofilms. a Global location of marine biofilms in the study. The quantities of datasets are indicated by numbers enclosed in brackets. The ocean map underwent modification using ArcGIS online maps (available at https://www.arcgis.com/). b Virus–prokaryote connections at the phylum rank. The number of pairs was indicated after each phylum. c Distribution of virus–prokaryote pairs in biofilms in the oceans. ECS: East China Sea (30° 42′ 00.0′′ N 122° 49′ 12.0′′ E). HKW: Hong Kong waters (22° 20′ 24.0′′ N 114° 16′ 12.0′′ E). RS: Red Sea (22° 12′ 00.0′′ N 39° 01′ 48.0′′ E). CSCS: Central South China Sea (14° 00′ 00.0′′ N 116° 00′ 00.0′′ E). SY: Sanya (18° 13′ 48.0′′ N 109° 29′ 24.0′′ E). SA: South Atlantic (31° 25′ 12.0′′ N 81° 18′ 00.0′′ W). ZH: Zhuhai (21° 42′ 00.0′′ N 114° 21′ 00.0′′ E). d Shared phage–bacteria pairs in different biofilms from Hong Kong waters (e.g. Biofilm1 shared Uroviricota–Proteo- bacteria pairs with Biofilm2) and the Red Sea (e.g. Biofilm9 shared Uroviricota–Cyanobacteria pairs with Biofilm10). Biofilm1: HK-2022-1. Biofilm2: HK-2022-2. Biofilm3: SRR6854594.1. Biofilm4: SRR6854592.1. Biofilm5: SRR6854597.1 Biofilm6: SRR6854601.1. Biofilm7: SRR6854599.1. Biofilm8: SRR6854598.1. Biofilm9: SRR6869052.1. Biofilm10: SRR6869055.1. Biofilm11: SRR6869053.1. Biofilm12: SRR6869051.1. e Complex virus–prokaryote pairs in marine biofilms. A subnetwork highlighted within a black box was magnified on the left side to provide detailed information. The ISME Journal (2023) 17:2303 – 2312 K. Zhou et al. 2305 from a previous study [11] were retrieved from the NCBI database (BioProject accession: PRJNA438384). Raw reads were trimmed by Trimmo- matic v0.36 [20] with custom parameters (ILLUMINACLIP: TruSeq3- PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:40) to remove adaptors and low-quality reads. The quality-controlled reads were assembled using SPAdes v3.11.1 (--meta) [21]. Viral sequence candidates (scaffolds ≥5 kb) were identified from assembled metagenomic sequences by multiple identifiers, including VirSorter v1.0.5 (searching against the RefSeqABVir database; hallmark gene number ≥1) [22], VirSorter2 v2.2.3 (score≥0.9 and/or hallmark gene number ≥1) [23], VIBRANT v1.2.0 (categorised as lytic or lysogenic phages) [24], Seeker (score≥0.7) [25] and DeepVirFinder (score≥0.9, p < 0.05) [26], which rely on protein similarity and/ or machine-learning models. Binning of viral genome fragments In the binning of scaffolds, proviral and closed sequences identified above were removed. The remaining scaffolds were individually clustered in each sample with vRhyme v1.0.0 (default parameters) on the basis of read coverage and sequence composition [30]. Viral bins were further filtered to remove the bins of mixed populations (one bin consisting of different populations). Genome bins were firstly imported into Prodigal v2.6.3 (-m -p meta) [31] for gene prediction. In the following, the predicted genes were aligned to the viral RefSeq database from NCBI (https:// www.ncbi.nlm.nih.gov) and individually classified using a Last Common Ancestor algorithm [32] embedded in the Contig Annotation Tool (CAT) v4.6 [27]. A majority rule (--fraction 0.5), where >50% of the sum of bit- scores of all genes supports the classification, was employed to assign taxonomy at the phylum level to each sequence. Given that CAT has not been tested on viral genomes, it was tested using viral genomes derived from GenBank (https://www.ncbi.nlm.nih.gov/) before employment. The results showed that CAT could generate classification that was largely consistent with the International Committee on Taxonomy of Viruses at the phylum level (3804 out of 3805 GenBank genomes consistent; Table S2). In addition, CAT was tested using GenBank viral genomes in Duplornaviricota, Dividoviricota, Hofneiviricota, Phixviricota, Preplasmiviricota and Uroviricota, which were the outputs of annotation on vRhyme bins from CAT. Similarly, testing results on the six phyla showed high congruence (> 96%) with NCBI taxonomy (Table S3). Additionally, HMMScan in HMMER v3.3 tool suite [33] with parameters (--notextw -E 1e-5; bit score ≥30) was used to search terminase large subunit (TerL) genes against Pfam v35.0 [34]. Finally, when a bin contained sequences from more than one phylum or the bin displayed multiple TerL genes, the bin was removed because it may belong to different populations. The removed scaffolds were added to the pool of genomic fragments. Gene calling and taxonomic annotation of prokaryotic hosts In the gene prediction of prokaryotes, the open reading frames (ORFs) of genomes of bacteria and archaea were predicted by performing Prodigal [31] with customised settings (-c, -m). For the taxonomic annotation of bacterial and archaeal bins, the predicted genes were fed into GTDB-Tk v0.3.1 [47], using the ‘classify_wf’ parameter, to identify single-copy marker genes that were then analysed for prokaryotic classification with GTDB taxonomy [47]. Identification of defence and counter-defence genes p y The identified viral genome fragments, genome bins and complete genomes were classified at the phylum level using the Last Common Ancestor algorithm and the majority rule. Viral RefSeq viruses were searched as mentioned above. Sequences or bins were selected as prokaryotic virus candidates when they contained viral genes identified by g Prokaryotic defence system-related gene candidates were identified by searching against Prokaryotic Antiviral Defence System (PADS) [59] using the DIAMOND BLASTp command (more sensitive mode, identity ≥30%, E- value < 10−10) [60]. To verify the presence of conserved domains of the The ISME Journal (2023) 17:2303 – 2312 K. Zhou et al. 2306 phyla were identified: two archaeal phyla (Asgardarchaeota and Thermoproteota) and 15 bacterial phyla (Acidobacteriota, Actino- bacteriota, Bacteroidota, Bdellovibrionota, Campylobacterota, Chlor- oflexota, Cyanobacteria, Deinococcota, Firmicutes, Myxococcota, Patescibacteria, Planctomycetota, Proteobacteria, Spirochaetota and Verrucomicrobiota). For the prokaryotic viruses in connections, the phyla Hofneiviricota, Preplasmiviricota and Uroviricota were assigned to viruses. Most of the identified connections were between bacteriophages in the phylum of Uroviricota and the bacteria of Proteobacteria, Cyanobacteria and Bacteroidota. phyla were identified: two archaeal phyla (Asgardarchaeota and Thermoproteota) and 15 bacterial phyla (Acidobacteriota, Actino- bacteriota, Bacteroidota, Bdellovibrionota, Campylobacterota, Chlor- oflexota, Cyanobacteria, Deinococcota, Firmicutes, Myxococcota, Patescibacteria, Planctomycetota, Proteobacteria, Spirochaetota and Verrucomicrobiota). For the prokaryotic viruses in connections, the phyla Hofneiviricota, Preplasmiviricota and Uroviricota were assigned to viruses. Most of the identified connections were between bacteriophages in the phylum of Uroviricota and the bacteria of Proteobacteria, Cyanobacteria and Bacteroidota. antiphage defence gene, we annotated the identified gene candidates using HMMScan in HMMER 3.3 tool suite [33] against PFAM 32.0 [34] (E- value < 10−3, bit score≥30). The PFAM accessions of the conserved domains of antiphage defence genes [61] were used to check their presence in the annotated gene candidates. Gene sequences containing the conserved domains were retained and incorporated into the set of defence-related genes of prokaryotes. Similar processes used to predict prokaryotic defence genes were performed to identify counter-defence genes in viruses. Viral genomes were imported into DIAMOND BLASTp and HMMScan in HMMER to search against PADS and PFAM, respectively. Viral genes containing the conserved domains of RM system-related genes were considered counter-defence genes. We detected the gene components of a system in a contig sequence or a bacterial bin as previously described to predict the completeness of defence systems [62–66]. The system was considered complete when it included all the genes required. Abundance of anti-viral defence genes in prokaryotes of biofilms and seawater We used available metagenome samples from Hong Kong waters (biofilm established on polystyrene panels: n = 55, seawater: n = 11) and the Red Sea (biofilm established on zinc panels: n = 12, seawater: n = 12) to compare the abundance of defence-related genes between prokaryotes in biofilms and their ambient seawater. Metagenomic sequences classified as prokaryotes by CAT and sequences of metagenome-assembled bins were selected for the following analyses. Referring to the above-mentioned section Identification of defence and counter-defence genes, anti-viral defence genes were identified. According to the pipeline proposed by Jin Choi (https://github.com/edamame-course/Metagenome/blob/master/ 2016-07-15-counting-abundance-with-mapped-reads.md), metagenomic reads were mapped to the identified defence genes with Bowtie2 version 2.3.4 [45], and aligned reads were counted using SAMtools version 1.6 [46]. RPKM was calculated for each sample to estimate gene abundance. The relative abundance of defence-related genes was calculated by dividing the RPKM of one gene by the sum of RPKM for each location and sample type. DESeq2 1.38.3 package [69] was employed to calculate the differential abundance of defence-related genes between paired sample types from each location. Then, the significantly differentially abundant genes (adjusted p < 0.05) were recognised with a meta-analysis random effects model embedded in R package metafor 3.8-1 [70], to which the log2-fold change value and its associated standard error were input. y The clustering of paired viral and prokaryotic genomes generated 433 groups, of which 184 were composed of more than one viral or prokaryotic genome (Fig. 1e). The virus–host pair network reflected a complex relationship between viruses and prokaryotes in marine biofilms. Such a relationship indicated that a single virus could infect multiple prokaryotic populations or a single prokaryote is susceptible to several viral populations. For instance, Vibrio SRR6869398.1_bin.13 was paired with 14 viral bins, such as SRR6869398.1_vRhyme_bin_100 in the phylum of Uroviricota, and Uroviricota SRR6869398.1_vRhyme_bin_67 was related to Halomonas SRR6869398.1_bin.24 and Vibrio SRR6869398.1_bin.19 (Fig. 1e). The infection of a single prokaryote by several viral populations might lead to high virus-to-prokaryote ratios. According to the analysis of average metagenomic read coverage, many phage–bacterium pairs had high phage-to- bacterium ratios (Supplementary Table S8). A total of 52 bacterial bins had ratios of over 10, which were distributed in biofilms sampled from the South China Sea, East China Sea, Red Sea and South Atlantic. Notably, the ratios of phage to bacterium in the biofilms derived from the South Atlantic reached up to 645. Transcriptome assembly and gene expression quantification for the microbiomes of HK-2022 biofilms Sequenced raw RNA reads of the metatranscriptome of three biofilm repeats were trimmed by Trimmomatic (version 0.36) with custom parameters (ILLUMINACLIP: TruSeq3-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:40) to remove Illumina adapters and low- quality bases of RNA reads. The trimmed reads were processed with Trinity v2.8.5 with default parameters [67] to de novo assemble metatranscrip- tomes. Reconstructed transcripts were mapped to the predicted genes of metagenomes of viruses/prokaryotes of the HK-2022 biofilms using BLASTn (E-value < 10−3, identity ≥95%, coverage = 100%). Simultaneously, Salmon with default parameters and an input of RNA-sequencing reads [68] was used in the quantification in transcripts per million (TPM) to assess expression levels of viral/prokaryotic genes. In this study, we defined the expression of a viral/prokaryotic gene as having the support of at least one transcript from one repeat sample or read mapping to all repeat samples. Virus–prokaryote pairs and distribution Virus prokaryote pairs and distribution The identification of viral sequences from metagenomes resulted in the generation of three genome datasets. These datasets comprised closed genomes, which were regarded as potential complete genomes; genome bins, encompassing groups of fragmented genomes; and genome fragments, representing unbinned viral scaffolds. The three genome datasets were utilised for pairing with prokaryotic genome bins. A total of 2446 connections (Fig. 1b) were identified between prokaryotes (902 genome bins) and viruses (102 closed genomes, 884 viral bins and 1155 viral genome fragments) from 84 marine biofilms (Supple- mentary Tables S4–S6). For the prokaryotes with connections, 17 Identification of defence and counter-defence genes , y The viruses and prokaryotes constituted 21 phylum–phylum pairs and were widely distributed in oceans (Fig. 1c). The Uroviricota–Proteobacteria and Uroviricota–Bacteroidota pairs were found in most of the biofilms of the South China Sea, East China Sea, Red Sea and South Atlantic, indicating a wide distribution in oceans. By contrast, the Uroviricota–Thermoproteota pair was specific to biofilms of Hong Kong waters. In addition to the pairing between Uroviricota and Thermoproteota, many other virus–prokaryote pairs, such as Hofneiviricota and Cyanobacteria, were exclusively found in a specific location with a small number of biofilms, suggesting that the distribution of viruses and their prokaryotic hosts displayed an endemic feature in marine biofilms. Moreover, the analysis of the average nucleotide identity (ANI; ≥95%) of closed/binned viral genomes and prokaryotic genome bins showed the absence of shared virus–host pairs in different environments. By contrast, in a specific environment, such as the Red Sea or Hong Kong waters, viral and host populations were shared among biofilms (Fig. 1d and Supplementary Table S7). In the biofilms from the Red Sea, two populations of Uroviricota–- Proteobacteria and Uroviricota–Cyanobacteria pairs were shared among different biofilms. In Hong Kong waters, nine shared pairs (Uroviricota–Proteobacteria and Uroviricota–Verrucomicrobiota) were identified. The viral and host populations of Uroviricota and Proteobacteria, respectively, were present in biofilm3 (SRR6854594.1_vRhyme_bin_3 and SRR6854594.1_bin.2) and bio- film4 (SRR6854592.1_vRhyme_bin_4 and SRR6854592.1_bin.2). Abundance of anti-viral defence genes in prokaryotes of biofilms and seawater The bacteria with such high ratios were affiliated with Proteobacteria, Firmicutes and Planctomycetota, and their paired phages were affiliated with Uroviricota. Diverse auxiliary metabolic genes in viral genomes paired with prokaryotes Analysis of viral genomes paired with prokaryotic genomes predicted 425 auxiliary metabolic genes (AMGs; Supplementary Table S9). These putative metabolic genes were related to 57 pathways, of which 37 contained more than one metabolic gene (Fig. 2a). Most of the identified AMGs were classified into the pathways of purine metabolism (72 genes), pyrimidine The ISME Journal (2023) 17:2303 – 2312 K. Zhou et al. Fig. 2 Auxiliary metabolic genes of viruses paired with prokaryotes from 84 marine biofilms. a Count of AMGs in each pathway. Here, only pathways containing gene count>1 are shown. b Schematic of representative AMG-involved pathways with relatively abundant genes. Pathways were highlighted in violet. AMGs were highlighted in dark red. K. Zhou et al. 2 2307 Fig. 2 Auxiliary metabolic genes of viruses paired with prokaryotes from 84 marine biofilms. a Count of AMGs in each pathway. Here, only pathways containing gene count>1 are shown. b Schematic of representative AMG-involved pathways with relatively abundant genes. Pathways were highlighted in violet. AMGs were highlighted in dark red. development of RM systems to withstand host defence by employing anti-restriction strategies [77]. metabolism (61 genes), folate biosynthesis (58 genes), amino sugar and nucleotide sugar metabolism (56 genes), O-antigen nucleotide sugar biosynthesis (53 genes), and nicotinate and nicotinamide metabolism (45 genes). A total of 61 and 7 genes were the homologues of the genes nrdA and psbA, respectively, which are two experimentally verified genes that play a crucial role in viral replication [51, 53–55, 57]. The gene nrdA [57] encodes the ribonucleoside–diphosphate reductase alpha chain that converts guanosine diphosphate into deoxyguanosine dipho- sphate (Fig. 2b), whereas the gene psbA codes for the photosystem II P680 reaction centre D1 protein [51, 53–55], which is involved in photosynthesis. Genes homologous to nrdA occurred in almost all the biofilm locations of the Red Sea, South China Sea, East China Sea and South Atlantic. The temporal and spatial distributions of nrdA reflected the stable presence of nucleotide metabolism-related AMGs in marine biofilms (Figs. S3 and S4). On the basis of taxonomic annotation, nrdA and psbA were mainly from the Uroviricota viruses, which infect Actinobac- teriota, Bacillota, Bacteroidota, Cyanobacteria, Planctomycetota, Proteobacteria and Verrucomicrobiota. Proteobacteria and Cyano- bacteria accounted for a large proportion. We detected 239 viral genes related to RM systems encom- passing types I, II and III (details in Supplementary Table S10). Diverse auxiliary metabolic genes in viral genomes paired with prokaryotes Biofilm viruses encoding RM systems were distributed widely from the East China Sea to the South China Sea and Red Sea. Specifically, they were identified in biofilms that grew on the beaches and rocks of Hong Kong; zinc panels at the Red Sea; and polystyrene dishes in the East China Sea, South China Sea and South Atlantic. For example, three genes that are near an integrase gene and encode N-6 DNA methylase, type I RM DNA specificity domain and type III restriction enzyme in the viral bin SRR6869023.1_vRhyme_bin_27 were present in the rock biofilm at Hong Kong waters (Fig. 3a). Type II RM systems including genes encoding type II restriction endonuclease were detected in SRR6869046.1_vRhyme_bin_18 from the Red Sea biofilms. y A total of 38,538 anti-viral defence-related genes were detected in 902 genome bins of biofilm prokaryotes paired with viruses (Table S11). These genes were involved in 15 defence systems encompassing Zorya, Hachiman, defence island system associated with RM (DISARM), TA, Gabija, RM, Septu, Lamassu, Brex, CRISPR–Cas, Thoeris, Druantia, Wadjet, abortive infection (ABI) and Shedu (Fig. 3b). Amongst these systems, the Zorya, Hachiman, DISARM, TA, Gabija and RM displayed a large number of genes, comprising the main gene components. In terms of completeness of systems, Zorya, Hachiman, Lamassu, Gabija, Wadjet, Shedu, Septu, TA, RM and CRISPR–Cas systems showed a full set of required defence genes (Fig. 3c; details in Supplementary Results). Counter-defence and anti-viral genes in paired viral and prokaryotic genomes p y g In the arms race between viruses and microbes, bacteria can evolve innate and adaptive immunity, including systems for restriction–modification (RM) [71], defence island system asso- ciated with restriction–modification (DISARM) [72], bacteriophage exclusion (BREX) [73] and CRISPR–Cas [74], to target invading DNA for defence. They can develop toxin–antitoxin (TA) [75] and abortive infection (ABI) [76] to abort viral replication and initiate programmed death. Systems with unknown mechanisms, such as the Zorya, Hachiman, Gabija, Septu, Thoeris, Lamassu, Druantia, Wadjet, Kiwa and Shedu, have evolved in some bacteria [61]. Conversely, viruses have the capability to undergo mutations as a means of evading these defences, thereby enhancing their fitness. One well-established counter-defence mechanism involves the Defence gene composition differs in biofilms and surrounding seawater Here, we regarded all the prokaryotic defence genes as anti-viral defensomes. To investigate the differences between biofilm and seawater defensome profiles, we identified the defence genes in prokaryotic communities from Hong Kong waters and the Red Sea with sufficient samples. We then compared the abundance, measured as reads per kilobase of gene per million mapped The ISME Journal (2023) 17:2303 – 2312 K. Zhou et al. 2308 Fig. 3 Defence system-related genes in paired viral and prokaryotic genomes from 84 marine biofilms. a Schematic of gene composition of a representative RM system in a temperate viral genome bin. SRR6869023.1_vRhyme_bin_27 represents a virus in the phylum of Uroviricota from the biofilm established on rocks situated in Hong Kong waters. b Count of genes in each system. The horizontal axis represents the value of Log10 [Gene Count]. c Anti-viral defence systems in marine biofilm prokaryotes with a complete set of required system components. Bacteria of biofilms developed on Petri dishes at Hong Kong waters: Cyanobacteria (SRR6854573.1_bin.1, SRR6854590.1_bin.4 and SRR6854711.1_bin.3), Verrucomicrobiota (SRR6854573.1_bin.4) and Proteobacteria (SRR6854588.1_bin.3, SRR6854588.1_bin.6, SRR6854591.1_bin.2, SRR6854716.1_bin.13 and SRR6854716.1_bin.15). SRR6869023.1_bin.26 represents a bacterium in the order of Cyanobacteria established on rocks at Hong Kong waters. SRR6869054.1_bin.19 is in the order of Proteobacteria from the biofilm developed on zinc panels at the Red Sea. SRR6869393.1_bin.16 represents a bacterium of Proteobacteria from the biofilm developed on Petri dishes at the East China Sea. Green represents genes encoding non-defence or unknown functions. 8 Fig. 3 Defence system-related genes in paired viral and prokaryotic genomes from 84 marine biofilms. a Schematic of gene composition of a representative RM system in a temperate viral genome bin. SRR6869023.1_vRhyme_bin_27 represents a virus in the phylum of Uroviricota from the biofilm established on rocks situated in Hong Kong waters. b Count of genes in each system. The horizontal axis represents the value of Log10 [Gene Count]. c Anti-viral defence systems in marine biofilm prokaryotes with a complete set of required system components. Bacteria of biofilms developed on Petri dishes at Hong Kong waters: Cyanobacteria (SRR6854573.1_bin.1, SRR6854590.1_bin.4 and SRR6854711.1_bin.3), Verrucomicrobiota (SRR6854573.1_bin.4) and Proteobacteria (SRR6854588.1_bin.3, SRR6854588.1_bin.6, SRR6854591.1_bin.2, SRR6854716.1_bin.13 and SRR6854716.1_bin.15). SRR6869023.1_bin.26 represents a bacterium in the order of Cyanobacteria established on rocks at Hong Kong waters. SRR6869054.1_bin.19 is in the order of Proteobacteria from the biofilm developed on zinc panels at the Red Sea. SRR6869393.1_bin.16 represents a bacterium of Proteobacteria from the biofilm developed on Petri dishes at the East China Sea. Defence gene composition differs in biofilms and surrounding seawater Green represents genes encoding non-defence or unknown functions. reads (RPKM), between biofilm and seawater samples. In total, 16,563 and 18,996 genes were separately identified in biofilm and seawater samples of Hong Kong waters, and 24,043 and 21,498 genes were identified in the biofilm and seawater samples of the Red Sea, respectively (Tables S12–15). The total abundance of defence-related genes in biofilms developed on polystyrene Petri dishes at Hong Kong waters was higher than that in other samples, including the seawater samples from Hong Kong waters and the biofilms developed on zinc panels and seawater of the Red Sea (Fig. 4a). Biofilms developed on zinc panels at the Red Sea and seawater of Hong Kong waters had a slightly higher abundance than seawater samples from the Red Sea (Fig. 4a). Although the biofilms of Hong Kong waters had a higher abundance of defence genes than the biofilms of the Red Sea, they had similar system compositions (Fig. 4b and Table S16). Additionally, the seawater of Hong Kong and the Red Sea had similar defence system compositions. Biofilm samples from both Hong Kong waters and the Red Sea contained a higher relative abundance of defence-related genes coding for the systems of ABI, CRISPR–Cas, Kiwa, RM, Shedu, TA, Thoeris and Wadjet than seawater samples (Fig. 4b). By contrast, defence-related genes coding for the systems of DISARM, Druantia, Hachiman, Lamassu and Zorya were higher in abundance in seawater prokaryotes than in biofilm samples. 0.48, respectively) compared with those of the biofilm samples (Fig. 4c). Biofilm samples were enriched with 38 genes coding for six systems (CRISPR–Cas, TA, RM, Wadjet, Thoeris and BREX; Fig. 4c). The highest log fold changes were observed in genes encoding the RAMP superfamily, Cmr2, GSU0054 family and Cmr3 of CRISPR–Cas from biofilms ( −1.15, −1.11, −0.97 and −0.94, respectively) compared with seawater samples. By contrast, genes for type II TA systems encompassing bacterial antitoxin VapB, the PIN domain and antitoxin MazE had the lowest log fold changes (−0.196, −0.195 and −0.192, respectively). reads (RPKM), between biofilm and seawater samples. In total, 16,563 and 18,996 genes were separately identified in biofilm and seawater samples of Hong Kong waters, and 24,043 and 21,498 genes were identified in the biofilm and seawater samples of the Red Sea, respectively (Tables S12–15). Defence gene composition differs in biofilms and surrounding seawater The total abundance of defence-related genes in biofilms developed on polystyrene Petri dishes at Hong Kong waters was higher than that in other samples, including the seawater samples from Hong Kong waters and the biofilms developed on zinc panels and seawater of the Red Sea (Fig. 4a). Biofilms developed on zinc panels at the Red Sea and seawater of Hong Kong waters had a slightly higher abundance than seawater samples from the Red Sea (Fig. 4a). Although the biofilms of Hong Kong waters had a higher abundance of defence genes than the biofilms of the Red Sea, they had similar system compositions (Fig. 4b and Table S16). Additionally, the seawater of Hong Kong and the Red Sea had similar defence system compositions. Biofilm samples from both Hong Kong waters and the Red Sea contained a higher relative abundance of defence-related genes coding for the systems of ABI, CRISPR–Cas, Kiwa, RM, Shedu, TA, Thoeris and Wadjet than seawater samples (Fig. 4b). By contrast, defence-related genes coding for the systems of DISARM, Druantia, Hachiman, Lamassu and Zorya were higher in abundance in seawater prokaryotes than in biofilm samples. Expression of anti-viral defence genes, hallmark genes, auxiliary metabolic genes and counter-defence genes in the microbiomes of HK-2022 biofilms Expression of anti-viral defence genes, hallmark genes, auxiliary metabolic genes and counter-defence genes in the microbiomes of HK-2022 biofilms microbiomes of HK 2022 biofilms For the prokaryotes paired with identified viruses in biofilm microbial communities, sequenced read and reconstructed transcript mapping showed that genes related to all the detected anti-viral systems of Zorya, Hachiman, DISARM, TA, Gabija, RM, Septu, Lamassu, Brex, CRISPR–Cas, Thoeris, Druantia, Wadjet and Shedu were transcribed by Actinobacteriota, Bacteroidota, Plancto- mycetota and Proteobacteria (Table S17). Some defence systems had a high level of gene expression, such as the type II-C CRISPR–Cas in Alteromonadaceae biofilm1_bin.9 targeting phages in Uroviricota (Table S17). The TPM values of genes for Cas2, Cas1 and HNH endonuclease in type II-C CRISPR–Cas were high compared with those of other defence genes. In particular, the TPM of the Cas1 gene for spacer insertion could reach up to 604. Transcriptomic analysis also showed that the genes of viruses paired with prokaryotic hosts were expressed (Supplementary Tables S18–20 and Supplementary Results). Transcriptomic read and transcript mapping supported the expression levels of 35 AMGs, which were involved in 13 pathways: folate biosynthesis; sulphur metabolism; purine and pyrimidine metabolism; pentose For the prokaryotes paired with identified viruses in biofilm microbial communities, sequenced read and reconstructed transcript mapping showed that genes related to all the detected anti-viral systems of Zorya, Hachiman, DISARM, TA, Gabija, RM, Septu, Lamassu, Brex, CRISPR–Cas, Thoeris, Druantia, Wadjet and Shedu were transcribed by Actinobacteriota, Bacteroidota, Plancto- mycetota and Proteobacteria (Table S17). Some defence systems had a high level of gene expression, such as the type II-C CRISPR–Cas in Alteromonadaceae biofilm1_bin.9 targeting phages in Uroviricota (Table S17). The TPM values of genes for Cas2, Cas1 and HNH endonuclease in type II-C CRISPR–Cas were high compared with those of other defence genes. In particular, the TPM of the Cas1 gene for spacer insertion could reach up to 604. l l h d h h f The comparison amongst the abundance levels of the defence- related genes showed that seawater samples were enriched with 33 genes coding for 13 defence systems (Fig. 4c). Defence genes encoding LmuB of Lamassu, ATPase family associated with various cellular activities (AAA) of DISARM and GajB of GABIJA in seawater prokaryotes had the highest log fold changes (2.79, 2.67 and 2.63, respectively), whereas genes for BrxA of BREX, N-6 DNA methylase of RM and nucleotidyltransferase substrate binding protein-like antitoxin of TA had the lowest log fold changes (0.44, 0.47 and The ISME Journal (2023) 17:2303 – 2312 K. Zhou et al. 2309 Fig. Expression of anti-viral defence genes, hallmark genes, auxiliary metabolic genes and counter-defence genes in the microbiomes of HK-2022 biofilms b Relative abundance of reads labelled by defence systems across all samples from Hong Kong waters (biofilm established on polystyrene panels: n = 55, seawater: n = 11) and the Red Sea (biofilm established on zinc panels: n = 12, seawater: n = 12). c Estimated average log2 fold change of defence-related genes between paired biofilm and seawater samples from Hong Kong waters and the Red Sea via random effects meta-analysis (p < 0.05). Error bars represent 95% confidence intervals. Defence genes (adjusted p < 0.05 from differential abundance analysis) selected for the meta-analysis between paired samples of biofilms and seawater from Hong Kong waters (biofilm established on polystyrene panels: n = 55, seawater: n = 11) and the Red Sea (biofilm established on zinc panels: n = 12, seawater: n = 12). worldwide. These viruses infect a significant proportion of prokaryotes within marine biofilms, as indicated by the relative abundance analysis of metagenomic reads, which revealed virus- prokaryote pairings in the majority of prokaryotic genome bins across the various marine biofilms (detailed results in Figure S1). Our results unveiled 2446 virus–prokaryote pairs in marine biofilms developed at eight locations from the South China Sea, East China Sea, Red Sea and South Atlantic. The connected viruses and their hosts included three phyla of viruses and 17 phyla of bacteria and archaea. The highly diverse and widespread connections suggested interactions between viruses and prokar- yotes in marine biofilms. Additionally, we detected the expression of genes in viral sequences from HK-2022 biofilms, including the viral sequence biofilm1_NODE_68 with a high virus–host ratio (about 10:1) that has expressed genes encoding phage tail tube proteins (Table S20). This evidence demonstrates that viruses are active to infect hosts in natural marine biofilms. phosphate pathway; glycosaminoglycan degradation; methane metabolism; photosynthesis; porphyrin and chlorophyll metabo- lism; glutathione metabolism; cysteine and methionine metabo- lism; glycine, serine and threonine metabolism; and one-carbon metabolism (Table S19). Amongst these AMGs, the gene nrdA associated with purine and pyrimidine metabolisms accounted for a large proportion (15 genes). An assessment of expression level showed that the viral nrdA was highly expressed in biofilms. The TPM of nrdA in the unbinned scaffold NODE_184 of biofilm1 ranged from 8.5 to 16.3, whereas the TPM of all the other expressed AMGs in biofilm1 was below 8.5 (Table S19). Expression of anti-viral defence genes, hallmark genes, auxiliary metabolic genes and counter-defence genes in the microbiomes of HK-2022 biofilms 4 Comparison of defence-related gene abundance between biofilms and surrounding seawater from Hong Kong waters and Red Sea. a Absolute abundance in log10 of reads per kilobase of read per million (RPKM) of defence-related genes for paired samples of biofilms and seawater from Hong Kong waters (biofilm established on polystyrene panels: n = 55, seawater: n = 11) and the Red Sea (biofilm established on zinc panels: n = 12, seawater: n = 12). The horizontal line that splits the box is the median, the upper and lower sides of the box are upper and lower quartiles, whiskers are 1.5 times the interquartile ranges and data points beyond whiskers are considered potential outliers. b Relative abundance of reads labelled by defence systems across all samples from Hong Kong waters (biofilm established on polystyrene panels: n = 55, seawater: n = 11) and the Red Sea (biofilm established on zinc panels: n = 12, seawater: n = 12). c Estimated average log2 fold change of defence-related genes between paired biofilm and seawater samples from Hong Kong waters and the Red Sea via random effects meta-analysis (p < 0.05). Error bars represent 95% confidence intervals. Defence genes (adjusted p < 0.05 from differential abundance analysis) selected for the meta-analysis between paired samples of biofilms and seawater from Hong Kong waters (biofilm established on polystyrene panels: n = 55, seawater: n = 11) and the Red Sea (biofilm established on zinc panels: n = 12, seawater: n = 12). 2 Fig. 4 Comparison of defence-related gene abundance between biofilms and surrounding seawater from Hong Kong waters and Red Sea. a Absolute abundance in log10 of reads per kilobase of read per million (RPKM) of defence-related genes for paired samples of biofilms and seawater from Hong Kong waters (biofilm established on polystyrene panels: n = 55, seawater: n = 11) and the Red Sea (biofilm established on zinc panels: n = 12, seawater: n = 12). The horizontal line that splits the box is the median, the upper and lower sides of the box are upper and lower quartiles, whiskers are 1.5 times the interquartile ranges and data points beyond whiskers are considered potential outliers. Expression of anti-viral defence genes, hallmark genes, auxiliary metabolic genes and counter-defence genes in the microbiomes of HK-2022 biofilms As for viral genes related to counter-defence, though few genes had read support, the type III restriction enzyme genes were active in three samples, indicating the expression of the counter-defence systems of the viruses. REFERENCES Observations on the multiplication of bacteria in dif- ferent volumes of stored sea water and the influence of oxygen tension and solid surfaces. Biol Bull. 1936;71:324–42. 9. Agostini VO, Rodrigues LT, Macedo AJ, Muxagata E. Comparison of techniques for counting prokaryotes in marine planktonic and biofilm samples. Sci Mar. 2021;85:211–20. 10. Wahl M, Shahnaz L, Dobretsov S, Saha M, Symanowski F, David K, et al. Ecology of antifouling resistance in the bladder wrack Fucus vesiculosus: pat- terns of microfouling and antimicrobial protection. Mar Ecol Prog Ser. 2010;411:33–48. 11. Zhang W, Ding W, Li YX, Tam C, Bougouffa S, Wang R, et al. Marine biofilms constitute a bank of hidden microbial diversity and functional potential. Nat Commun. 2019;10:517. 12. Konstantinidis KT, Tiedje JM. Genomic insights that advance the species defini- tion for prokaryotes. Proc Natl Acad Sci USA. 2005;102:2567–72. 13. Suttle CA. Viruses in the sea. Nature. 2005;437:356–61. 14. Weinbauer MG. Ecology of prokaryotic viruses. FEMS Microbiol Rev. 2004;28:127–81. Compared with defence systems in seawater microbiomes, biofilm prokaryotes displayed higher abundance and difference in composition, consistent with the observation that biofilm bacteria and archaea are unique communities [11]. Abundant defence mechanisms can confer resistance to viral infection on prokar- yotes, as evidenced by a study revealing that enriched defence systems reduce the infectivity of the phage strains of Pseudomo- nas aeruginosa [88]. Given the high level of resistance, we hypothesised that marine biofilms are habitats for the blooming of anti-viral defence strategists. Seawater is conducive to the rapid growth of competition strategists but it restricts the development of defence strategists. A switch from free-living to being sessile will make defence strategists dominant in microbial communities. This switch will also benefit the stability of microbial communities in seawater under viral predation when prokaryotes go back to a free-living style via detachment. The abundance and composition of defence genes are linked to substrate surfaces. Cell culture Petri dishes made of polystyrene support the colonisation of defence- preferring microorganisms, whereas zinc panels inhibit the blooming of defence systems in biofilm communities. Zinc can cause biofilm biomass reduction in marine habitats [89] and is unfavourable to the biofilm development of certain species, such as Actinobacillus pleuropneumoniae [90]. Phage biocontrol has been applied to treat environmentally detrimental biofilms in the food industry [91] and has been tested in water systems [92, 93]. REFERENCES 1. Flemming HC, Wingender J. The biofilm matrix. Nat Rev Microbiol. 2010;8:623–33. 1. Flemming HC, Wingender J. The biofilm matrix. Nat Rev Microbiol. 2010;8:623–33. 2. Qian PY, Cheng A, Wang R, Zhang R. Marine biofilms: diversity, interactions and biofouling. Nat Rev Microbiol. 2022;20:671–84. 2. Qian PY, Cheng A, Wang R, Zhang R. Marine biofilms: diversity, interactions and biofouling. Nat Rev Microbiol. 2022;20:671–84. 3. Davey ME, O’toole GA. Microbial biofilms: from ecology to molecular genetics. Microbiol Mol Biol Rev. 2000;64:21. 3. Davey ME, O’toole GA. Microbial biofilms: from ecology to molecular genetics. Microbiol Mol Biol Rev. 2000;64:21. 4. Egan S, Thomas T, Kjelleberg S. Unlocking the diversity and biotechnological potential of marine surface associated microbial communities. Curr Opin Micro- biol. 2008;11:219–25. However, prokaryotes can employ multiple defence lines for fighting viruses [85]. Our study on archaeal and bacterial genomes showed that hundreds of thousands of genes are related to 17 defence systems in marine biofilms. The expression of these systems in microbial communities in HK-2022 biofilms indicates that multiple systems exert a synergistic effect that efficiently removes invading viruses [86]. For instance, when the phages biofilm1_vRhyme_bin_46 and biofilm1_vRhyme_bin_52 inject their genetic materials into the bacterial cells of biofilm1_bin.9 in the family of Alteromonadaceae, the activity of the CRISPR–Cas system encoding Cas1, Cas2 and Cas9 (Table S17) for cleaving invading DNA and incorporating viral sequences as spacers for memory was observed. Additionally, TA systems, including the type II TA encoding the ParE toxins and ParD antitoxins [87] in biofilm1_bin.9, can employ toxins to inhibit cell proliferation and inhibit viral replication. Other systems (e.g. HACHIMAN, Thoeris and Shedu) with unknown mechanisms might play a comple- mentary role for Alteromonadaceae biofilm1_bin.9 in the presence of invading phages. Along with known mechanisms, such as quorum sensing under phage predation, abundant defence systems contribute to prokaryotic genotypic evolution and facilitate coexistence with viruses in marine biofilms. 5. Salta M, Wharton JA, Blache Y, Stokes KR, Briand JF. Marine biofilms on artificial surfaces: structure and dynamics. Environ Microbiol. 2013;15:2879–93. 6. Antunes J, Leao P, Vasconcelos V. Marine biofilms: diversity of communities and of chemical cues. Environ Microbiol Rep. 2019;11:287–305. 6. Antunes J, Leao P, Vasconcelos V. Marine biofilms: diversity o of chemical cues. Environ Microbiol Rep. 2019;11:287–305. 7. Pires DP, Melo LDR, Azeredo J. Understanding the complex phage-host interac- tions in biofilm communities. Annu Rev Virol. 2021;8:73–94. 8. Zobell CE, Anderson DQ. DISCUSSION C l i Viruses can employ diverse mechanisms to aid in their infections. One such mechanism involves exploiting host meta- bolisms for replication. Notably, genes related to nucleotide mechanism, such as nrdA, are frequently observed and highly expressed in biofilms. This result suggests that viruses in marine biofilms have evolved efficient strategies to produce purine and pyrimidine for DNA replication. Moreover, energy metabolism plays a pivotal role in viral replication. During infection, viruses harness the energy generated by the host’s metabolism [82]. For instance, in the case of phage T4, viral infection consumes nearly double the host’s normal energy supply, with a burst size of 1000 [83]. In our study, we detected gene homologues of psbA in marine biofilm viruses. Viruses carrying psbA genes may prevent photo-inhibition in infected cells, ensuring the continuity of photosynthesis and supplying the necessary energy for viral replication [55]. Beyond psbA and nrdA, we identified hundreds of Coastal marine environments are characterised by their unforgiv- ing conditions, which include temperature fluctuations, pH variations, wave action, evaporation and salinity changes [78]. These challenging environmental factors compel prokaryotes to adopt a sessile lifestyle by attaching to natural and man-made surfaces. Remarkably, this strategy has been adopted by cellular organisms for billions of years, as evidenced by fossil records [79, 80]. Marine biofilms, formed as a result of this attachment strategy, serve as protective shields for individual cells against various types of environmental stressors, including the threat of predation by other organisms [81]. This protective environment fosters the development of a diverse microbial community and enables these microorganisms to thrive within marine biofilms. g Where there is life, viruses are present [13]. Our study has provided evidence for the presence of viruses in marine biofilms The ISME Journal (2023) 17:2303 – 2312 K. Zhou et al. 2310 specific materials may enrich defence strategists and counter the effect of phage biocontrol. Finally, enriched defence systems can provide a catalogue of defence-related genes in marine environ- ments, and further exploration would expand the defence systems database and contribute to immune research. additional auxiliary metabolic genes. These metabolic genes are associated with over 60 pathways, encompassing amino acid metabolism, nucleotide metabolism, energy metabolism and fatty acid biosynthesis. Thus, a complex interplay exists between viruses and host metabolisms, potentially facilitating viral replication and representing evolutionarily conserved and essential mechanisms for nutrient digestion and energy generation by the host [82]. DATA AVAILABILITY g gy g y In addition to employing AMGs, viruses can develop counter- defence systems to enhance their ability to infect host organisms. During infection, viruses likely encounter restriction enzymes derived from the hosts’ RM defence systems, which are detected in 90% of bacterial and archaeal genomes [84]. In phages, foreign DNA-targeting RM systems have evolved as counter-defence systems to resist host defence through anti-restriction strategies [77]. Over 200 viral genes related to the RM systems of types I, II and III are present in marine biofilms and endow biofilm viruses with the capability to modify viral DNA. Thus, the recognition of host restriction enzymes can be prevented and viral genome cleavage can be avoided. The data of HK-2022 biofilms that support the findings of this study are deposited into the NCBI database under the BioProject ID PRJNA983852. REFERENCES A widespread bacter- iophage abortive infection system functions through a Type IV toxin-antitoxin mechanism. Nucl Acids Res. 2014;42:4590–605. 35. Mihara T, Nishimura Y, Shimizu Y, Nishiyama H, Yoshikawa G, Uehara H, et al. Linking virus genomes with host taxonomy. Viruses. 2016;8:66. 36. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403–10. 66. Zhou K, Xu Y, Zhang R, Qian PY. Arms race in a cell: genomic, transcriptomic, and proteomic insights into intracellular phage-bacteria interplay in deep-sea snail holobionts. Microbiome. 2021;9:1–13. 37. Roux S, Brum JR, Dutilh BE, Sunagawa S, Duhaime MB, Loy A, et al. Ecogenomics and potential biogeochemical impacts of globally abundant ocean viruses. Nat- ure. 2016;537:689–93. 67. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Full- length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 2011;29:644–52. 38. Bland C, Ramsey TL, Sabree F, Lowe M, Brown K, Kyrpides NC, et al. CRISPR recognition tool (CRT): a tool for automatic detection of clustered regularly interspaced palindromic repeats. BMC Bioinf. 2007;8:209. 68. Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods. 2017;14:417–9. 39. Rho M, Wu YW, Tang H, Doak TG, Ye Y. Diverse CRISPRs evolving in human microbiomes. PLoS Genet. 2012;8:e1002441. 40. Nishimura Y, Watai H, Honda T, Mihara T, Omae K, Roux S, et al. Environmental viral genomes shed new light on virus-host interactions in the ocean. mSphere. 2017;2:e00359–00316. 69. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:1–21. 70. Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Stat Softw. 2010;36:1–48. 41. Rice P, Longden I, Bleasby A. EMBOSS: the european molecular biology open software suite. Trends Genet. 2000;16:276–7. 71. Ershova AS, Rusinov IS, Spirin SA, Karyagina AS, Alexeevski AV. Role of restriction- modification systems in prokaryotic evolution and ecology. Biochem (Mosc). 2015;80:1373–86. 42. Paez-Espino D, Eloe-Fadrosh EA, Pavlopoulos GA, Thomas AD, Huntemann M, Mikhailova N, et al. Uncovering Earth’s virome. Nature. 2016;536:425. 43. Zielezinski A, Deorowicz S, Gudys A. PHIST: fast and accurate prediction of pro- karyotic hosts from metagenomic viral sequences. Bioinformatics. 2021;38:1447–9. 72. Ofir G, Melamed S, Sberro H, Mukamel Z, Silverman S, Yaakov G, et al. DISARM is a widespread bacterial defence system with broad anti-phage activities. REFERENCES Thompson LR, Zeng Q, Kelly L, Huang KH, Singer AU, Stubbe J, et al. Phage auxiliary metabolic genes and the redirection of cyanobacterial host carbon metabolism. Proc Natl Acad Sci USA. 2011;108:E757–E764. 28. Nayfach S, Camargo AP, Schulz F, Eloe-Fadrosh E, Roux S, Kyrpides NC. CheckV assesses the quality and completeness of metagenome-assembled viral gen- omes. Nat Biotechnol. 2020;39:578–85. 58. Zeng QL, Chisholm SW. Marine viruses exploit their host’s two-component reg- ulatory system in response to resource limitation. Curr Biol. 2012;22:124–8. 29. Uritskiy GV, DiRuggiero J, Taylor J. MetaWRAP-a flexible pipeline for genome- resolved metagenomic data analysis. Microbiome. 2018;6:1–13. 59. Zhang YD, Zhang ZW, Zhang H, Zhao YB, Zhang ZC, Xiao JF. PADS Arsenal: a database of prokaryotic defense systems related genes. Nucl Acids Res. 2020;48:D590–D598. 30. Kieft K, Adams A, Salamzade R, Kalan L, Anantharaman K. vRhyme enables bin- ning of viral genomes from metagenomes. Nucl Acids Res. 2022;50:e83. 60. Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIA- MOND. Nat Methods. 2015;12:59–60. 31. Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: pro- karyotic gene recognition and translation initiation site identification. BMC Bioinf. 2010;11:1–11. 61. Doron S, Melamed S, Ofir G, Leavitt A, Lopatina A, Keren M et al. Systematic discovery of antiphage defense systems in the microbial pangenome. Science. 2018;359:eaar4120. 32. Huson DH, Beier S, Flade I, Gorska A, El-Hadidi M, Mitra S, et al. MEGAN com- munity edition-interactive exploration and analysis of large-scale microbiome sequencing data. PLoS Comput Biol. 2016;12:e1004957. 62. Bernheim A, Sorek R. The pan-immune system of bacteria: antiviral defence as a community resource. Nat Rev Microbiol. 2019;18:113–9. 33. Mistry J, Finn RD, Eddy SR, Bateman A, Punta M. Challenges in homology search: HMMER3 and convergent evolution of coiled-coil regions. Nucl Acids Res. 2013;41:e121. 63. Shmakov S, Smargon A, Scott D, Cox D, Pyzocha N, Yan W, et al. Diversity and evolution of class 2 CRISPR-Cas systems. Nat Rev Microbiol. 2017;15:169–82. 64. Kamruzzaman M, Iredell J. A ParDE-family toxin antitoxin system in major resis- tance plasmids of Enterobacteriaceae confers antibiotic and heat tolerance. Sci Rep. 2019;9:1–12. 34. El-Gebali S, Mistry J, Bateman A, Eddy SR, Luciani A, Potter SC, et al. The Pfam protein families database in 2019. Nucl Acids Res. 2019;47:D427–D432. 65. Dy RL, Przybilski R, Semeijn K, Salmond GPC, Fineran PC. REFERENCES Nat Microbiol. 2018;3:90–8. 44. Jain C, Rodriguez RL, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun. 2018;9:5114. 73. Goldfarb T, Sberro H, Weinstock E, Cohen O, Doron S, Charpak-Amikam Y, et al. BREX is a novel phage resistance system widespread in microbial genomes. EMBO J. 2015;34:169–83. 45. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357–9. 74. Makarova KS, Wolf YI, Alkhnbashi OS, Costa F, Shah SA, Saunders SJ, et al. An updated evolutionary classification of CRISPR-Cas systems. Nat Rev Microbiol. 2015;13:722–36. 46. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25:2078–9. lignment/map format and SAMtools. Bioinformatics. 2009;25:2078– 75. Yamaguchi Y, Park JH, Inouye M. Toxin-antitoxin systems in bacteria and archaea. Annu Rev Genet. 2011;45:61–79. 47. Parks DH, Chuvochina M, Waite DW, Rinke C, Skarshewski A, Chaumeil PA, et al. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat Biotechnol. 2018;36:996–1004. 76. Chopin MC, Chopin A, Bidnenko E. Phage abortive infection in lactococci: varia- tions on a theme. Curr Opin Microbiol. 2005;8:473–9. 48. Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucl Acids Res. 2000;28:27–30. 77. Samson JE, Magadan AH, Sabri M, Moineau S. Revenge of the phages: defeating bacterial defences. Nat Rev Microbiol. 2013;11:675–87. 49. Aramaki T, Blanc-Mathieu R, Endo H, Ohkubo K, Kanehisa M, Goto S, et al. KofamKOALA: KEGG Ortholog assignment based on profile HMM and adaptive score threshold. Bioinformatics. 2020;36:2251–2. 78. Dash HR, Mangwani N, Chakraborty J, Kumari S, Das S. Marine bacteria: potential candidates for enhanced bioremediation. Appl Microbiol Biotechnol. 2013;97:561–71. 50. Eddy SR. Accelerated profile HMM searches. PLoS Comput Biol. 2011;7:e1002195. 79. Rasmussen B. Filamentous microfossils in a 3,235-million-year-old volcanogenic massive sulphide deposit. Nature. 2000;405:676–9. 51. Clokie MRJ, Shan JY, Bailey S, Jia Y, Krisch HM, West S, et al. Transcription of a ‘photosynthetic’ T4-type phage during infection of a marine cyanobacterium. Environ Microbiol. 2006;8:827–35. 80. Westall F, de Wit MJ, Dann J, van der Gaast S, de Ronde CEJ, Gerneke D. Early Archean fossil bacteria and biofilms in hydrothermally-influenced sediments from the Barberton greenstone belt, South Africa. Precambrian Res. 2001;106:93–116. 52. Hurwitz BL, Brum JR, Sullivan MB. Depth-stratified functional and taxonomic niche specialization in the ‘core’ and ‘flexible’ Pacific Ocean Virome. ISME J. 2015;9:472–84. 81. REFERENCES Phages facilitate the control of biofilms, but surface substrates to which biofilms attach should not be overlooked. Biofilms on 15. de Carvalho CCCR. Marine biofilms: A successful microbial strategy with eco- nomic implications. Front Mar Sci. 2018;5:126. 16. Dunsing V, Irmscher T, Barbirz S, Chiantia S. Purely polysaccharide-based biofilm matrix provides size-selective diffusion barriers for nanoparticles and bacter- iophages. Biomacromolecules. 2019;20:3842–54. 17. Bond MC, Vidakovic L, Singh PK, Drescher K, Nadell CD. Matrix-trapped viruses can prevent invasion of bacterial biofilms by colonizing cells. Elife. 2021;10:e65355. 18. Knecht LE, Veljkovic M, Fieseler L. Diversity and function of phage encoded depolymerases. Front Microbiol. 2020;10:2949. 19. Lacqua A, Wanner O, Colangelo T, Martinotti MG, Landini P. Emergence of biofilm-forming subpopulations upon exposure of Escherichia coli to environ- mental bacteriophages. Appl Environ Microbiol. 2006;72:956–9. 20. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20. 21. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19:455–77. 22. Roux S, Enault F, Hurwitz BL, Sullivan MB. VirSorter: mining viral signal from microbial genomic data. PeerJ. 2015;3:e985. 23. Guo J, Bolduc B, Zayed AA, Varsani A, Dominguez-Huerta G, Delmont TO, et al. VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses. Microbiome. 2021;9:37. VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses. Microbiome. 2021;9:37. 24. Kieft K, Zhou Z, Anantharaman K. VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences. Microbiome. 2020;8:1–23. 25. Auslander N, Gussow AB, Benler S, Wolf YI, Koonin EV. Seeker: alignment-free identification of bacteriophage genomes by deep learning. Nucl Acids Res. 2020;48:e121. The ISME Journal (2023) 17:2303 – 2312 The ISME Journal (2023) 17:2303 – 2312 K. Zhou et al. 2311 56. Sullivan MB, Coleman ML, Weigele P, Rohwer F, Chisholm SW. Three Pro- chlorococcus cyanophage genomes: signature features and ecological inter- pretations. PLoS Biol. 2005;3:790–806. 26. Ren J, Song K, Deng C, Ahlgren NA, Fuhrman JA, Li Y, et al. Identifying viruses from metagenomic data using deep learning. Quant Biol. 2020;8:64–77. 27. von Meijenfeldt FAB, Arkhipova K, Cambuy DD, Coutinho FH, Dutilh BE. Robust taxonomic classification of uncharted microbial sequences and bins with CAT and BAT. Genome Biol. 2019;20:217. 57. ADDITIONAL INFORMATION Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41396-023-01546-2. 89. Mayer-Pinto M, Coleman RA, Underwood AJ, Tolhurst TJ. Effects of zinc on microalgal biofilms in intertidal and subtidal habitats. Biofouling. 2011;27:721–7. 90. Wu C, Labrie J, Tremblay YDN, Haine D, Mourez M, Jacques M. Zinc as an agent for the prevention of biofilm formation by pathogenic bacteria. J Appl Microbiol. 2013;115:30–40. Correspondence and requests for materials should be addressed to Rui Zhang or Pei-Yuan Qian. 91. Gutierrez D, Rodriguez-Rubio L, Martinez B, Rodriguez A, Garcia P. Bacteriophages as weapons against bacterial biofilms in the food industry. Front Microbiol. 2016;7:825. Reprints and permission information is available at http://www.nature.com/ reprints Reprints and permission information is available at http://www.nature.com/ reprints 92. Yu PF, Mathieu J, Lu GW, Gabiatti N, Alvarez PJ. Control of antibiotic-resistant bacteria in activated sludge using polyvalent phages in conjunction with a production host. Environ Sci Technol Lett. 2017;4:137–42. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 93. Bin Naser I, Hoque MM, Abdullah A, Bari SMN, Ghosh AN, Faruque SM. Envir- onmental bacteriophages active on biofilms and planktonic forms of toxigenic Vibrio cholerae: potential relevance in cholera epidemiology. PLoS One. 2017;12:e0180838. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creativecommons.org/licenses/by/4.0/. COMPETING INTERESTS 87. Makarova KS, Wolf YI, Snir S, Koonin EV. Defense islands in bacterial and archaeal genomes and prediction of novel defense systems. J Bacteriol. 2011;193:6039–56. The authors declare no competing interests. 88. Costa AR, Berg DFVd, Esser JQ, Muralidharan A, Bossche HVd, Bonilla BE et al. Accumulation of defense systems drives panphage resistance in Pseudomonas aeruginosa. bioRxiv. (2022). https://doi.org/10.1101/2022.08.12.503731. AUTHOR CONTRIBUTIONS 84. Roberts RJ, Vincze T, Posfai J, Macelis D. REBASE-a database for DNA restriction and modification: enzymes, genes and genomes. Nucl Acids Res. 2010;38:D234–D236. PYQ and RZ conceived the project. KZ, TYW, LL and WCW carried out experiments. KZ performed data analyses and drafted the manuscript. PYQ, RZ, KA and WZ contributed to manuscript editing. All authors read and approved the final manuscript. 85. Dupuis ME, Villion M, Magadan AH, Moineau S. CRISPR-Cas and restriction- modification systems are compatible and increase phage resistance. Nat Com- mun. 2013;4:1–7. 86. Rostøl JT, Marraffini L. (Ph) ighting phages: how bacteria resist their parasites. Cell Host Microbe. 2019;25:184–94. REFERENCES Matz C, Webb JS, Schupp PJ, Phang SY, Penesyan A, Egan S, et al. Marine biofilm bacteria evade eukaryotic predation by targeted chemical defense. PLoS One. 2008;3:e2744. 53. Lindell D, Jaffe JD, Johnson ZI, Church GM, Chisholm SW. Photosynthesis genes in marine viruses yield proteins during host infection. Nature. 2005;438:86–89. 54. Lindell D, Sullivan MB, Johnson ZI, Tolonen AC, Rohwer F, Chisholm SW. Transfer 54. Lindell D, Sullivan MB, Johnson ZI, Tolonen AC, Rohwer F, Chisholm SW. Transfer of photosynthesis genes to and from Prochlorococcus viruses. Proc Natl Acad Sci USA. 2004;101:11013–8. 82. Girdhar K, Powis A, Raisingani A, Chrudinova M, Huang RX, Tran T, et al. Viruses and metabolism: the effects of viral infections and viral insulins on host meta- bolism. Annu Rev Virol. 2021;8:373–91. of photosynthesis genes to and from Prochlorococcus viruses. Proc Natl Acad Sci USA. 2004;101:11013–8. 55. Mann NH, Cook A, Millard A, Bailey S, Clokie M. Marine ecosystems: bacterial photosynthesis genes in a virus. Nature. 2003;424:741. 83. Mahmoudabadi G, Milo R, Phillips R. Energetic cost of building a virus. Proc Natl Acad Sci USA. 2017;114:E4324–E4333. The ISME Journal (2023) 17:2303 – 2312 K. Zhou et al. 2312 © The Author(s) 2023 ACKNOWLEDGEMENTS We thank Ruojun Wang (The Hong Kong University of Science and Technology) and Lanlan Cai (The Hong Kong University of Science and Technology) for their assistance in this project. This work was supported by the principal investigator projects of the Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou; 2021HJ01), the Major Basic and Applied Research Projects of Guangdong Province (2019B030302004-04), the Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou; SMSEGL20SC01), the National Natural Science Foundation of China (42188102 and 91951209), the Innovation Team Project of Universities in Guangdong Province (2023KCXTD028) and the Hong Kong Special Administrative Region government (16101822, C2013-22GF and T11-104/22R). © The Author(s) 2023 The ISME Journal (2023) 17:2303 – 2312
https://openalex.org/W3189072118
https://upcommons.upc.edu/bitstream/2117/359852/1/antioxidants-10-01270.pdf
English
null
Targeting Pro-Oxidant Iron with Deferoxamine as a Treatment for Ischemic Stroke: Safety and Optimal Dose Selection in a Randomized Clinical Trial
Antioxidants
2,021
cc-by
13,319
  p g p 3 Department of Clinical Pharmacology, Hospital Germans Trias i Pujol, 08916 Badalona, Barcelona, Spain; joan.costa.pages@gmail.com   Citation: Millán, M.; DeGregorio-Rocasolano, N.; Pérez de la Ossa, N.; Reverté, S.; Costa, J.; Giner, P.; Silva, Y.; Sobrino, T.; Rodríguez-Yáñez, M.; Nombela, F.; et al. Targeting Pro-Oxidant Iron with Deferoxamine as a Treatment for Ischemic Stroke: Safety and Optimal Dose Selection in a Randomized Clinical Trial. Antioxidants 2021, 10, 1270. https://doi.org/10.3390/ antiox10081270 Academic Editors: Alessandra Napolitano and Rosa M. Lamuela-Raventos Received: 14 June 2021 Accepted: 5 August 2021 Published: 10 August 2021 j p g g 4 Department of Pharmacy, Hospital Germans Trias i Pujol, 08916 Badalona, Barcelona, Spain; pginerb@gmail.com 5 Department of Neurology, Hospital Dr. Josep Trueta, 17007 Girona, Spain; ysilva.girona.ics@gencat.cat (Y.S.) jserena.girona.ics@gencat.cat (J.S.) 6 Clinical Neurosciences Research Laboratory, Health Research Institute of Santiago de Compostela, Hospital Clínico Universitario, Universidade de Santiago de Compostela, 15706 Santiago de Compostela, Spain; tomas.sobrino.moreiras@sergas.es (T.S.); Francisco.Campos.Perez@sergas.es (F.C.) 7 Department of Neurology, Hospital Clínico Universitario, 15706 Santiago de Compostela, Spain; manuel.rodriguez.yanez@sergas.es g y g 8 Department of Neurology, Hospital La Princesa, 28006 Madrid, Spain; fnombela hlpr@salud madrid org (F N ); joseaurelio vivancos@salud ma 8 Department of Neurology, Hospital La Princesa, 28006 Madrid, Spain; 8 Department of Neurology, Hospital La Princesa, 28006 Madrid, Spain; fnombela.hlpr@salud.madrid.org (F.N.); joseaurelio.vivancos@salud.madrid.org (J.V.) 9 p gy p p fnombela.hlpr@salud.madrid.org (F.N.); joseaurelio.vivancos@salud.madrid.org (J.V.) 9 9 Department of Cellular Biology, Physiology and Immunology, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain p 10 Department of Statistics and Operations Research, Universitat Politècnica de Catalunya (UPC), 10 Department of Statistics and Operations Research, Universitat Politècnica de Catalunya (UPC), 08028 Barcelona, Spain; jordicortes40@gmail.com p j g * Correspondence: mmillan.germanstrias@gencat.cat (M.M.); tgasull@igtp.cat or teresagasull@yahoo.com (T.G.) Abstract: A role of iron as a target to prevent stroke-induced neurodegeneration has been recently revisited due to new evidence showing that ferroptosis inhibitors are protective in experimental ischemic stroke and might be therapeutic in other neurodegenerative brain pathologies. Ferroptosis is a new form of programmed cell death attributed to an overwhelming lipidic peroxidation due to excessive free iron and reactive oxygen species (ROS). This study aims to evaluate the safety and tolerability and to explore the therapeutic efficacy of the iron chelator and antioxidant deferoxamine mesylate (DFO) in ischemic stroke patients. antioxidants antioxidants antioxidants Targeting Pro-Oxidant Iron with Deferoxamine as a Treatment for Ischemic Stroke: Safety and Optimal Dose Selection in a Randomized Clinical Trial Mònica Millán 1,*, Núria DeGregorio-Rocasolano 1,2 , Natàlia Pérez de la Ossa 1, Sílvia Reverté 1 , Joan Costa 3, Pilar Giner 4, Yolanda Silva 5, Tomás Sobrino 6 , Manuel Rodríguez-Yáñez 7, Florentino Nombela 8, Francisco Campos 6 , Joaquín Serena 5, José Vivancos 8, Octavi Martí-Sistac 2,9, Jordi Cortés 10 , Antoni Dávalos 1 and Teresa Gasull 1,2,* 1 Department of Neurosciences, Hospital Germans Trias i Pujol, 08916 Badalona, Barcelona, Spain; ndgregorio@igtp.cat (N.D.-R.); nperez.germanstrias@gencat.cat (N.P.d.l.O.); silvia.reverte@urv.cat (S.R.); adavalos.germanstrias@gencat.cat (A.D.) 2 Cellular and Molecular Neurobiology Research Group, Department of Neurosciences, Germans Trias i Pujol Research Institute (IGTP), 08916 Badalona, Barcelona, Spain; omarti@igtp.cat or octavi.marti@uab.cat   Administration of placebo or a single DFO bolus followed by a 72 h continuous infusion of three escalating doses was initiated during the tPA infusion, and the impact on blood transferrin iron was determined. Primary endpoint was safety and tolerability, and secondary endpoint was good clinical outcome (clinicalTrials.gov NCT00777140). DFO was found safe as adverse effects were not different between placebo and DFO arms. DFO (40–60 mg/Kg/day) reduced the iron saturation of blood transferrin. A trend to efficacy was observed in patients with moderate-severe ischemic stroke (NIHSS > 7) treated with DFO 40–60 mg/Kg/day. A good outcome was observed at day 90 in 31% of placebo vs. 50–58% of the 40–60 mg/Kg/day DFO-treated patients. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Keywords: iron; deferoxamine; antioxidant; ferroptosis; neuroprotection; outcome https://www.mdpi.com/journal/antioxidants Antioxidants 2021, 10, 1270. https://doi.org/10.3390/antiox10081270 2 of 15 Antioxidants 2021, 10, 1270 1. Introduction A growing body of novel evidence points to a newly described type of programmed cell death having a pivotal role in neurodegeneration. This cell death is known as ferropto- sis, which is iron- and lipid peroxidation-dependent, and associated with reduced cellular antioxidant activity. In support of this concept, ferroptosis has been recently reported to drive the acute neurodegeneration observed in ischemic and hemorrhagic stroke [1–6]; in traumatic brain injury [7]; or in long-term neurodegeneration observed in pathologies such as Alzheimer’s disease, Parkinson’s disease, or Huntington’s disease [8]. Preclinical investigations indicate that iron, either resident in brain cells, released from hemolyzed red blood cells that reach the brain parenchyma during hemorrhage, imported from blood to brain as free-labile iron or by iron-carrying molecules, or acting at the cerebral vasculature, is a potent pro-oxidant that contributes to the neurodegeneration and brain damage observed in acute ischemic stroke (AIS) and in intracerebral hemorrhage (ICH) [4,6,8–12]. Iron exacerbates excitotoxicity and induces neurodegeneration through the production of highly reactive and cytotoxic hydroxyl radicals which foster oxidative DNA damage and lipid peroxidation [12–14]. In the clinical arena, iron overload conditions at admission, measured as high ferritin levels in blood, have been consistently associ- ated with poor functional outcome in patients with either intracranial hemorrhage [15,16] or ischemic stroke [17,18]. Moreover, increased systemic iron stores are associated with severe edema and with symptomatic hemorrhagic transformation in ischemic stroke pa- tients treated with thrombolytic reperfusion therapy with intravenous recombinant tissue plasminogen activator (tPA) [18]. Importantly, the biological iron chelator and powerful antioxidant deferoxamine mesylate (DFO), that has long been used in clinic as a first line treatment to remove excess iron in iron-overload diseases such as thalassemia [19], has demonstrated its effectiveness as a neuroprotective agent in experimental stroke models of AIS and ICH [4,20–23] and prevents the excess of mitochondrial free radicals induced in transient ischemic stroke models [24]. Given the pivotal role of iron in reactive oxygen species production, ferroptosis, and ischemia/reperfusion damage, and since iron chelation with DFO is neuroprotective in experimental stroke models and well-tolerated in ICH patients [25], the TANDEM 1 study aimed to evaluate safety and tolerability, and to explore potential efficacy of intravenous DFO administered to ischemic stroke patients. 2. Materials and Methods Study design and participants: TANDEM-1 (Thrombolysis And Deferoxamine in Middle Cerebral Artery Occlusion study) was a multicenter, randomized, double-blind, placebo-controlled, dose-finding phase II clinical trial approved by the Spanish Drug Agency (eudraCT 2007-0006731-31) and local Ethics Committee, and registered in clinicalTrials.gov as NCT00777140. Consecutive patients with acute ischemic stroke af- fecting the middle cerebral artery (MCA) territory, with baseline National Institute of Health Stroke Scale (NIHSS) ≥4, treated with IV tPA within 3 h of symptoms onset, and with written informed consent were enrolled at four Spanish centers: Hospital Germans Trias i Pujol, Hospital de La Princesa, Hospital Dr. Josep Trueta, and Hospital Clínico de Santiago de Compostela. CONSORT work flow diagram and inclusion and exclusion criteria are depicted in Figure 1. Hypertension, diabetes or dyslipidemia conditions were diagnosed as explained in the legend in Table 1. Alcohol consumption, current smoking habit, or iron supplementation were assessed at inclusion. Vital signs, laboratory param- eters and other parameters of interest for the stroke evolution such as pre-stroke Rankin Scale, NIHSS neurological scale at baseline, previous stroke, inflammatory conditions, or time to recanalization treatment (tPA or endovascular) were recorded. Study interventions and procedures: Previous reports on pharmacokinetics in healthy humans administered at the maximum recommended DFO dose (10 mg/Kg as a bolus) demonstrate an extremely short half-life of DFO [26]. To quickly reach sustained meaning- 3 of 15 3 of 15 Antioxidants 2021, 10, 1270 ful concentrations in blood, we administered DFO as a bolus followed by a continuous three-day IV infusion of three DFO doses up to a maximum of 60 mg/Kg/day. 4 of 16 Figure 1. Inclusion and exclusion criteria and CONSORT flow diagram of the three-dose tier sub- studies (DTS). In each DTS early termination cases due to mortality, discontinuation due to serious adverse events (SAE) possibly related to treatment, and patients excluded are indicated. Figure 1. Inclusion and exclusion criteria and CONSORT flow diagram of the three-dose tier sub-studies (DTS). In each DTS early termination cases due to mortality, discontinuation due to serious adverse events (SAE) possibly related to treatment, and patients excluded are indicated. Figure 1. Inclusion and exclusion criteria and CONSORT flow diagram of the three-dose tier sub- studies (DTS). In each DTS early termination cases due to mortality, discontinuation due to serious adverse events (SAE) possibly related to treatment, and patients excluded are indicated. Figure 1. 2. Materials and Methods and pharmacometabolism of DFO reported in the literature further recommend not to use the higher doses allowed. the higher doses allowed. Table 1. Description of the demographic and baseline clinical characteristics in the placebo and DFO group in each DTS. 2. Materials and Methods KERRYPNX DTS 1 DTS 2 DTS 3 Placebo (n = 5) DFO 20 (n = 15) Placebo (n = 5) DFO 40 (n = 16) Placebo (n = 5) DFO 60 (n = 16) Age 64.4 ± 8 67.8 ± 13 67.6 ± 8 64.1 ± 10 60.0 ± 16 70.0 ± 11 Sex, % male 40 60 80 75 100 81 Medical history, % patients Hypertension 80 53 80 50 80 63 Diabetes 60 20 20 19 40 19 Current smoking habit 20 20 20 13 20 6 Dislipemia 40 40 40 31 40 44 Alcohol consumption 20 0 60 19 20 31 Atrial fibrillation 20 40 20 13 20 13 Prior stroke 0 7 0 13 0 19 Vital signs and laboratory parameters Systolic BP, mmHg 166 ± 41 148 ±21 143 ± 10 140 ± 16 147 ± 16 150 ± 21 Diastolic BP, mmHg 79 ± 9 78 ± 18 80 ± 15 77 ± 11 85 ± 24 80 ± 14 Body temperature, ◦C 35.8 ± 0.5 36.0 ± 0.3 35.5 ± 0.3 36.0 ± 0.4 35.9 ± 0.6 35.9 ± 0.5 Heart rate, bpm 62 ± 12 82 ± 22 81 ± 19 71 ± 19 94 ± 9.4 70 ± 10 Serum glucose, mg/dL 142 ± 19 107 ± 33 155 ± 71 160 ± 94 212 ± 197 147 ± 72 Platelet count (×1000) 226 ± 61 218 ± 61 277 ± 54 237 ± 75 285 ± 102 234 ± 63 aPTT, s 28 ± 5 26 ± 3 26 ± 6 25 ± 4 28 ± 5 27 ± 3 Hematocrit, % 40.4 ± 3.8 41.4 ± 3.1 45.8 ±3.4 41.0 ± 3.6 45.1 ± 1.1 41.8 ± 4.6 Hemoglobin, g/dL 13.5 ± 1.5 14.0 ± 1.1 15.3 ± 1.0 13.8 ± 1.3 15.3 ± 0.4 14.2 ± 1.5 Creatinin, mg/dL 0.9 ± 0.1 0.9 ± 0.1 0.9 ± 0.5 0.9 ± 0.2 1.1 ± 0.3 0.9 ± 0.2 NIHSS at baseline 14 11 16 17 21.5 12 [12, 15] [9, 18.5] [13, 21] [8, 21] [17.5, 25] [7.5, 16.5] Stroke subtype, % patients Atherothrombotic 40 7 0 13 40 0 Cardioembolic 20 60 20 44 60 50 Undetermined 40 33 80 31 0 50 Other 0 0 0 6 0 0 ASPECTS score on baseline CT scan 10 10 10 10 9.5 10 [9, 10] [10, 10] [10, 10] [9, 10] [7.5, 10] [9, 10] Time from onset to tPA, min 110 136 100 140 132 140 [90, 110] [102, 168] [90, 130] [95, 155] [88, 174] [115, 157] Time from onset to trial treatment, min 140 163 125 170 163 155 [135, 143] [150, 213] [125, 150] [140, 190] [128, 192] [141, 195] Rescue endovascular treatment, % patients 0 7 20 19 80 31 Values are presented as mean ± SD, % percentage, or median [quartiles]. 2. Materials and Methods DTS: dose tier sub-study; DFO: deferoxamine (in mg/Kg/day for 3 days); NIHSS: National Institutes of Health Stroke Scale; BP: blood pressure; tPA: tissue plasminogen activator; aPTT: activated partial thromboplastin time. Hypertension is diagnosed if, when it is measured on two different days, the systolic blood pressure on both days is ≥140 mmHg and/or the diastolic blood pressure on both days is ≥90 mmHg. Diabetes, a condition where the body can′t control the amount of glucose in blood, is diagnosed when fasting plasma glycemia is ≥126 mg/dL. Alcohol consumption is here considered as an actual average daily alcohol consumption of less than 40 g/day. Dyslipidemia is diagnosed as an elevation of plasma cholesterol, triglycerides, or both, or a low HDL cholesterol level. ption of the demographic and baseline clinical characteristics in the placebo and DFO group in each DTS. Values are presented as mean ± SD, % percentage, or median [quartiles]. DTS: dose tier sub-study; DFO: deferoxamine (in mg/Kg/day for 3 days); NIHSS: National Institutes of Health Stroke Scale; BP: blood pressure; tPA: tissue plasminogen activator; aPTT: activated partial thromboplastin time. Hypertension is diagnosed if, when it is measured on two different days, the systolic blood pressure on both days is ≥140 mmHg and/or the diastolic blood pressure on both days is ≥90 mmHg. Diabetes, a condition where the body can′t control the amount of glucose in blood, is diagnosed when fasting plasma glycemia is ≥126 mg/dL. Alcohol consumption is here considered as an actual average daily alcohol consumption of less than 40 g/day. Dyslipidemia is diagnosed as an elevation of plasma cholesterol, triglycerides, or both, or a low HDL cholesterol level. Values are presented as mean ± SD, % percentage, or median [quartiles]. DTS: dose tier sub-study; DFO: deferoxamine (in mg/Kg/day for 3 days); NIHSS: National Institutes of Health Stroke Scale; BP: blood pressure; tPA: tissue plasminogen activator; aPTT: activated partial thromboplastin time. Hypertension is diagnosed if, when it is measured on two different days, the systolic blood pressure on both days is ≥140 mmHg and/or the diastolic blood pressure on both days is ≥90 mmHg. Diabetes, a condition where the body can′t control the amount of glucose in blood, is diagnosed when fasting plasma glycemia is ≥126 mg/dL. Alcohol consumption is here considered as an actual average daily alcohol consumption of less than 40 g/day. 2. Materials and Methods Inclusion and exclusion criteria and CONSORT flow diagram of the three-dose tier sub-studies (DTS). In each DTS early termination cases due to mortality, discontinuation due to serious adverse events (SAE) possibly related to treatment, and patients excluded are indicated. y interventions and procedures: Previous reports on pharmacokinetics in healthy dministered at the maximum recommended DFO dose (10 mg/Kg as a bolus) ate an extremely short half-life of DFO [26]. To quickly reach sustained mean- centrations in blood, we administered DFO as a bolus followed by a continuous IV infusion of three DFO doses up to a maximum of 60 mg/Kg/day. basis for analyzing the safety of up to 60 mg/Kg/day DFO in the preferred intra- dministration route in terms of pharmacometabolism and pharmacokinetics llows. Firstly, to never reach the maximal recommended dose in infusion of 15 ur (Available online: https://www.medicines.org.uk/emc/product/5/smpc (ac- 12 June 2021)). The continuous infusion of 60 mg/Kg/day results in the admin- f 2.5 mg/Kg of DFO each hour of infusion. As 10 mg/Kg DFO was administered immediately preceding the infusion, during the first hour of treatment patients mg in the bolus + 2.5 mg in infusion = 12.5 mg/Kg DFO, this being close to, but The basis for analyzing the safety of up to 60 mg/Kg/day DFO in the preferred intravenous administration route in terms of pharmacometabolism and pharmacokinetics were as follows. Firstly, to never reach the maximal recommended dose in infusion of 15 mg/Kg/hour (Available online: https://www.medicines.org.uk/emc/product/5/smpc (accessed on 12 June 2021)). The continuous infusion of 60 mg/Kg/day results in the administration of 2.5 mg/Kg of DFO each hour of infusion. As 10 mg/Kg DFO was administered as a bolus immediately preceding the infusion, during the first hour of treatment patients receive 10 mg in the bolus + 2.5 mg in infusion = 12.5 mg/Kg DFO, this being close to, but below, the maximum recommended dose. Secondly, according to the recommendations, DFO dosage should be reduced as soon as possible and should not exceed 80 mg/Kg/day. The dose of 60 mg/Kg/day used added to the 10 mg/Kg DFO bolus results in 70 mg/Kg/day during the first 24 h, close to, but again below, the maximum dose allowed. In addition, the large individual differences in pharmacokinetics Antioxidants 2021, 10, 1270 4 of 15 and pharmacometabolism of DFO reported in the literature further recommend not to use the higher doses allowed. 2. Materials and Methods Safety stopping rules were prespecified as either the presence of 15% of patients (n = 3) with symptomatic intracranial hemorrhage (sICH) or 25% mortality (n = 5) or the presence of unexpected serious adverse events (SAE) in the DFO arm in one DTS. After each DTS an independent data safety monitoring board (DSMB) reviewed all SAE. The next DTS only started after a positive DSMB evaluation, otherwise termination of the study was mandatory. y Patients were continuously monitored in the stroke units of participating centers. Neurological examination was assessed using the NIHSS by certified neurologists at admission and during hospitalization at 24, 48, and 72 h, and also at 7 and 90 days. Stroke worsening was considered at least a four-point increase in the widely used and reported scale NIHSS score. Follow-up CT scans were performed at 24–36 h after tPA administration to assess intracranial hemorrhage (ICH) and hypodensity volume. Functional outcome was evaluated using the modified Rankin Scale (mRS) at 7 days and 90 days. g ( ) y y Serum was obtained before, and at several time points after DFO administration and was stored at −80 ◦C. Samples were taken longitudinally from each patient before (baseline), right after the bolus administration, and at different times after the infusion treatment with placebo or DFO, including sampling at 24 and 72 h after the baseline pre- sampling at exactly the same time of day to avoid circadian interferences in the variables under study. At completion of the study, we determined serum levels of DFO (time course along 72 h; n = 5–7 patients in each DTS), % of iron saturation of blood transferrin (TSAT) (in patients with serum available pre-, 24 and 72 h post treatment) and ferritin (at admission and at 24 and 72 h) respectively, using an HPLC-based modification of a previously described protocol [27], a method that allows a direct and accurate measure of TSAT in serum samples [12], or an immunodiagnosis ELECSYS 2010 System. To determine TSAT, 0.26 µL of human serum were loaded in Precast 6% TBE urea gels (U-PAGE) (Life Technologies). Human ATf (hATf) and human holotrasferrin (hHTf) from Sigma-Aldrich were used as electrophoretic standards in U-PAGE, ATf, monoferric and diferric hHTf molecules show different electrophoretic mobility in those gels, allowing to detect the amount of each form. 2. Materials and Methods Dyslipidemia is diagnosed as an elevation of plasma cholesterol, triglycerides, or both, or a low HDL cholesterol level. The clinical trial was performed as three sequential dose tier sub-studies (DTS), DTS1 to DTS3, from lowest to highest DFO dose. Patients received IV tPA and were randomized using a computer-generated number sheet in a 3:1 ratio to receive either IV DFO or IV placebo treatment starting within the one-hour tPA infusion with no stratification tech- niques since primary outcome was safety. Some patients received rescue endovascular 5 of 15 Antioxidants 2021, 10, 1270 treatment according to the local protocols. Dose tier protocol was: for DTS1, 0.9% saline so- lution as placebo (n = 5) or a 10 mg/Kg DFO bolus + continuous infusion of 20 mg/Kg/day DFO (n = 15); for DTS2, saline as placebo (n = 5) or a 10 mg/Kg DFO bolus + continuous infusion of 40 mg/Kg/day DFO (n = 16), and for DTS 3, saline as placebo (n = 5) or a 10 mg/Kg DFO bolus + continuous infusion of 60 mg/Kg/day DFO (n = 16). At the end of the study, 15 placebo patients had been included. The maximum dose per hour never reached the maximal recommended dose in infusion of 15 mg/Kg/hour (Available online: https://www.medicines.org.uk/emc/product/5/smpc (accessed on 12 June 2021)). Trial drug was prepared according to Good Manufacturing and Clinical Practices and masking process and drug randomization was held centralized in the Pharmacy Service of one of the participating sites. Drug trial preparation was done by local non-blinded nurses who signed a confidentiality agreement. Containers and venous and urinary catheters were opaque to prevent viewing of the particular color of the drug and urine in order to maintain the blinding plan. p g p p ( J )) drug was prepared according to Good Manufacturing and Clinical Practices and masking process and drug randomization was held centralized in the Pharmacy Service of one of the participating sites. Drug trial preparation was done by local non-blinded nurses who signed a confidentiality agreement. Containers and venous and urinary catheters were opaque to prevent viewing of the particular color of the drug and urine in order to maintain the blinding plan. 2. Materials and Methods Gels were electroblotted onto PVDF-LF membranes (Millipore) which were incubated overnight at 4 ◦C with the specific anti-transferrin primary antibody and thereafter with the NIR-conjugated secondary antibody. Bands were measured using an Odyssey imaging system and its dedicated software. The anti-transferrin antibody used equally recognizes ATf and iron-containing Tf forms in WB. In contrast with the usual indirect methods, we calculate TSAT (%) directly by combining electrophoretic U-PAGE (that separates Tf into ATf (devoid of iron), two monoferric Tf, and the diferric Tf bands) with immunodetecttion and individual band quantification. We calculated % TSAT in serum samples of stroke patients using our U-PAGE/WB results, according to the following formula: TSAT (%) = (0.5 *mFe·Tf + diFe·Tf)*100/(ATf + mFe·Tf + diFe·Tf. Outcomes: Primary end points were any SAE that occurred within 90 days, the presence of sICH in the 24–36 h CT scan according to the ECASS II criteria [28] (neurological Antioxidants 2021, 10, 1270 6 of 15 worsening of NIHSS ≥4 in any bleeding), early neurological worsening (worsening of NIHSS ≥4 within 24 h after stroke onset), and mortality at 90 days. worsening of NIHSS ≥4 in any bleeding), early neurological worsening (worsening of NIHSS ≥4 within 24 h after stroke onset), and mortality at 90 days. Secondary end points were good clinical outcomes defined as a dichotomized score (mRS ≤2) at 7 and 90 days, the percent reduction of NIHSS at 90 days, pharmacokinetics of IV DFO and the effect of DFO on iron saturation of blood transferrin. Statistical analysis: The stopping safety rules were calculated according to the higher confidence interval of the accepted risk of sICH and mortality in the SITS-MOST study [29] assuming that all drug-related SAE will occur in the DFO arm. All patients enrolled in the trial, including those who had treatment discontinuation at any time point, were included in the safety analysis. Proportions between two groups were compared by using the X2 test or Fisher’s exact test, as appropriate. Data are expressed as the mean and SD or the median and quartiles. For vital signs, slope (resulting from a linear regression) and maximum increase were used, whereas for most routine laboratory parameters, the change from baseline was used. Groups were compared using the Student’s t-test, the Mann–Whitney U test, or independent or repeated measures ANOVA as appropriate. 2. Materials and Methods Statistical analyses were performed using SPSS (version 24) or GraphPad Prism (version 8.3); statistical significance was considered at p ≤0.05. 3.1. Subject Clinical Characteristics A total of 62 subjects were enrolled, 45 men and 17 women. The percentage of males is high in all the groups and similar among them: 73%, 60%, 75%, and 81% males were present respectively in the placebo pool and in the treatment groups of DTS1, DTS2, and DTS3. Mean ± SD age of the sample was 66 ± 11 years, median (quartiles) of NIHSS score was 14 [9, 20] and time from stroke onset to IV thrombolysis was 130 [100, 160] minutes and to investigational trial initiation 157 [140, 190] minutes. g All patients were treated with the full dose of IV tPA and received at least one dose of the investigational product according to the estimated weight; 58 (93%) subjects completed the 72 h drug infusion. Forty-seven patients received DFO and 15 placebo. All patients completed the follow up. The treatment was kept blind for all patients during the 90 days of the study, except for one patient displaying an allergic reaction. Table 1 summarizes the demographic and baseline clinical characteristics in both groups of treatment in each DTS, which were similar across treatment subgroups, except in the DTS3 subgroups that showed higher NIHSS (21.5 versus 12) in the placebo sub- group. By pooling all the placebo groups, the basal NIHSS differences among treatment groups disappear. 3.2. Safety Data Intracranial hemorrhage, neurological worsening and mortality are events that as- sociate to the normal evolution of the stroke pathology. No significant differences were found between placebo and DFO groups in any DTS in the total number of reported adverse events (AE) or SAE in the clinical trial (Table 2), indicating no safety concerns of the treatment with DFO. Each DTS terminated without crossing the safety stopping rules. SAE was reported in 4 patients in the placebo arm pooled from the 3 DTS (26% of placebo pool-treated patients) and in 5 (33.4%), 4 (25%), and 4 (25%) of DFO patients in DTS1, DTS2, and DTS3, respectively. Five events were deemed possibly or definitely drug-related by the local investigator, consisting in a sICH, an asymptomatic bradycardia, a symptomatic hypotension, a patient who suffered an early neurological worsening, and an anaphylaxis considered to be an allergic reaction to DFO during the bolus; in the last four events the drug was discontinued. Only 2 of 62 patients, both treated with the lower dose (IV 20 mg/Kg/day DFO), presented sICH during the study. Nine (14.5%) patients died during the 90-day follow-up post-stroke (causes of mortality are shown in Table S1). No differences were found in the early neurological worsening, early and late mortality Antioxidants 2021, 10, 1270 7 of 15 (Table 2), or hypodensity volume during the 36 h (Figure S1) post stroke-onset between placebo pool and DFO groups. Table 2. Safety and outcome results in the placebo and DFO group in each DTS. 3.3. Hemodynamic Vital Signs and Routine Clinical Laboratory Results Continuous monitoring of vital signs and also time-course measures of several lab- oratory parameters were collected during the 72 h drug infusion. DFO administration at the doses of 20 mg/Kg/day and 40 mg/Kg/day did not modify systolic and diastolic blood pressure (Figure S2), although there was a patient in the 40 mg/Kg/day DFO arm who suffered a symptomatic hypotension requiring medical treatment with complete recovery 10 min later without sequelae. The 60 mg/Kg/day DFO infusion was associ- ated with mild systolic blood pressure-lowering effects that were not clinically significant (Figure S2). A trend to increased heart rate which is not clinically relevant was observed in the 60 mg/Kg/day DFO, with a maximum increase of 13 bpm (95% CI, 4.1 to 22.6). Administration of DFO at any dose did not change body temperature or serum glucose levels (Figure S2). No clinically significant safety concerns or differences across treatment groups were observed for clinical biochemistry or hematological parameters. 3.2. Safety Data DTS 1 DTS 2 DTS 3 Placebo (n = 5) DFO 20 (n = 15) p Placebo (n = 5) DFO 40 (n = 16) p Placebo (n = 5) DFO 60 (n = 16) p Patients with AE, % 100 73.3 0.197 100 75 0.214 100 87.5 0.406 AE n = 13 2.6 ± 1.1 n = 28 1.9 ± 1.8 0.349 n = 12 2.4 ± 1.1 n = 36 2.1 ± 1.8 0.603 n = 18 3.5 ± 3.1 n = 44 2.7 ± 1.8 0.603 Patients with SAE, % 40 33.4 0.787 0 25 0.214 40 25 0.517 SAE n = 2 0.4 ± 0.5 n = 6 0.4 ± 0.6 0.933 n = 0 n = 6 0.4 ± 0.8 0.445 n = 4 0.5 ± 1 n = 6 0.4 ± 0.8 0.548 ENW, % 20 20 1 0 6 0.567 0 6 0.567 sICH, % 0 13.3 0.389 0 0 - 0 0 - Mortality 7 days, % 20 6.7 0.389 0 6.3 0.567 20 12.5 0.676 Mortality 90 days, % 20 13.3 0.718 0 18.8 0.296 20 12.5 0.676 Most stroke patients show adverse events (AE), and a significant number of patients show serious adverse events (SAE) associated to the normal evolution of the stroke pathology. These include symptomatic intracranial hemorrhage (sICH), early neurological worsening (ENW) and mortality. Values are presented as percentage %, n and mean ± SD. DTS: dose tier sub-study. DFO: deferoxamine (in mg/Kg/day for three days). The AE and SAE recorded within each DTS allowed to proceed with the next DTS, since each DTS terminated without crossing the safety stopping rules. (Table 2), or hypodensity volume during the 36 h (Figure S1) post stroke-onset between placebo pool and DFO groups. (Table 2), or hypodensity volume during the 36 h (Figure S1) post stroke-onset between placebo pool and DFO groups. Table 2. Safety and outcome results in the placebo and DFO group in each DTS. Most stroke patients show adverse events (AE), and a significant number of patients show serious adverse events (SAE) associated to the normal evolution of the stroke pathology. These include symptomatic intracranial hemorrhage (sICH), early neurological worsening (ENW) and mortality. Values are presented as percentage %, n and mean ± SD. DTS: dose tier sub-study. DFO: deferoxamine (in mg/Kg/day for three days). 3.2. Safety Data The AE and SAE recorded within each DTS allowed to proceed with the next DTS, since each DTS terminated without crossing the safety stopping rules. 3.4. Ferritin, DFO Pharmacokinetics, and Effects on TSAT Arrows indicate the different electrophoretic pattern of ATf, the two monoferric forms of transferrin (mFe-Tf), and the diferric transferrin (diFe-Tf) form in serum samples of stroke patients. Placebo and DFO depict bands of transferrin of two representative patients (one of the placebo group and one of the DFO 60 group) before the onset of treatment (0), and 24 and 72 h after administration. In each lane, optical density of the bands allow calculation of the % TSAT for a given patient at a given time point using the formula: TSAT (%) = (0.5 *mFe·Tf + diFe·Tf)*100/(ATf + mFe·Tf + diFe·Tf). (C–F) % TSAT before the onset of treatment (0 h), and 24 and 72 h after administration of placebo (C), 20 mg/Kg/day DFO (D), 40 mg/Kg/day DFO (E), or 60 mg/Kg/day DFO (F). Values are presented as mean ± SD. * p ≤0.05, ** p ≤0.005 (repeated measures one-way ANOVA plus the post-hoc Benjamini–Krieger–Yekutieli test). 0.0 0.5 1.0 2 4 6 24 48 72 0 20 40 60 80 100 time (h) DFO (µM) DFO 20 DFO 40 DFO 60 A B 0 24 h 72 h 0 10 20 30 40 50 60 70 % TSAT DFO 20 D time (h) 0 24 h 72 h 0 10 20 30 40 50 60 70 % TSAT placebo 0 24 h 72 h 0 10 20 30 40 50 60 70 % TSAT DFO 20 C D time (h) 0 24 h 72 h 0 10 20 30 40 50 60 70 % TSAT placebo C D C DFO 20 0 24 h 72 h 0 10 20 30 40 50 60 70 % TSAT ** p = 0.101 DFO 60 F p 0 24 h 72 h 0 10 20 30 40 50 60 70 % TSAT * DFO 40 DFO 20 0 24 h 72 h 0 10 20 30 40 50 60 70 % TSAT ** p = 0.101 DFO 60 E F 0 24 h 72 h 0 10 20 30 40 50 60 70 % TSAT * DFO 40 E Figure 2. Deferoxamine (DFO) reduces TSAT time- and dose-dependently. 3.4. Ferritin, DFO Pharmacokinetics, and Effects on TSAT (A) Time-course of se- rum DFO levels along the infusion in AIS patients treated with a 10 mg/Kg bolus of DFO IV followed by a 72 h continuous IV infusion of DFO in escalating dose tiers of 20, 40, or 60 mg/Kg/day (blood DFO levels at time = 0 of infusion in this graph are the result of the initial previous 10 mg/Kg bolus of DFO IV). Mean ± SD are shown; no significant effects were found (repeated measures ANOVA). (B) U-PAGE/WB depicting the bands of the iron-devoid form of human transferrin standard (Std) (apotransferrin, ATf) and human diferric transferrin (diFe-Tf) standard (holotransferrin, HTf). The iron load of transferrin determines the electrophoretic mobility of the different Tf forms in these urea gels. Arrows indicate the different electrophoretic pattern of ATf, the two monoferric forms of transferrin (mFe-Tf), and the diferric transferrin (diFe-Tf) form in serum samples of stroke patients. Placebo and DFO depict bands of transferrin of two representative patients (one of the placebo group and one of the DFO 60 group) before the onset of treatment (0), and 24 and 72 h after admin- istration. In each lane, optical density of the bands allow calculation of the % TSAT for a given pa- tient at a given time point using the formula: TSAT (%) = (0.5 *mFe·Tf + diFe·Tf)*100/(ATf + mFe·Tf + diFe·Tf). (C–F) % TSAT before the onset of treatment (0 h), and 24 and 72 h after administration of placebo (C), 20 mg/Kg/day DFO (D), 40 mg/Kg/day DFO (E), or 60 mg/Kg/day DFO (F). Values are presented as mean ± SD. * p ≤ 0.05, ** p ≤ 0.005 (repeated measures one-way ANOVA plus the post- hoc Benjamini–Krieger–Yekutieli test). Figure 2. Deferoxamine (DFO) reduces TSAT time- and dose-dependently. (A) Time-course of serum DFO levels along the infusion in AIS patients treated with a 10 mg/Kg bolus of DFO IV followed by a 72 h continuous IV infusion of DFO in escalating dose tiers of 20, 40, or 60 mg/Kg/day (blood DFO levels at time = 0 of infusion in this graph are the result of the initial previous 10 mg/Kg bolus of DFO IV). Mean ± SD are shown; no significant effects were found (repeated measures ANOVA). (B) U-PAGE/WB depicting the bands of the iron-devoid form of human transferrin standard (Std) (apotransferrin, ATf) and human diferric transferrin (diFe-Tf) standard (holotransferrin, HTf). 3.4. Ferritin, DFO Pharmacokinetics, and Effects on TSAT Large individual differences in blood DFO levels were observed among patients within a given dose tier group. DFO levels in serum were found higher in most subjects within the first 30 min following the initial 10 mg/Kg DFO bolus administration (average values were 21 µM ± 31). No differences were observed in blood DFO levels when comparing patients in the DFO arms DTS1 (n = 7), DTS2 (n = 5) and DTS3 (n = 5) (Figure 2A). Baseline serum TSAT in ischemic stroke patients was 31.2 ± 11.0, this being consistent with the TSAT levels and variability reported for healthy non-hemochromatosis individ- uals [30]. TSAT levels remained steady along the 3 days following ischemia onset in the placebo group as stated using a direct method using longitudinal measures performed in each individual pre- and post- treatment (Figure 2C). Repeated measures analysis show that DFO 20 mg/Kg/day did not change TSAT (Figure 2D). DFO 40 and 60 mg/Kg/day reduced by 30% and 40%, respectively, the TSAT when measured 72 h post-treatment onset (Figure 2E,F). At the 60 mg/Kg/day dose, DFO showed a trend to reduce TSAT (p = 0.101) after only 24 h of treatment. Ferritin levels in serum showed a 32% increase 72 h post-stroke onset as compared with baseline (p = 0.0046), in agreement with a previous study [18], and DFO treatment did not alter ferritin levels. 8 of 15 9 of 16 Antioxidants 2021, 10, 1270 Antioxidants 2021, 10, x FOR Figure 2. Deferoxamine (DFO) reduces TSAT time- and dose-dependently. (A) Time-course of se- rum DFO levels along the infusion in AIS patients treated with a 10 mg/Kg bolus of DFO IV followed by a 72 h continuous IV infusion of DFO in escalating dose tiers of 20, 40, or 60 mg/Kg/day (blood DFO levels at time = 0 of infusion in this graph are the result of the initial previous 10 mg/Kg bolus of DFO IV). Mean ± SD are shown; no significant effects were found (repeated measures ANOVA). (B) U-PAGE/WB depicting the bands of the iron-devoid form of human transferrin standard (Std) (apotransferrin, ATf) and human diferric transferrin (diFe-Tf) standard (holotransferrin, HTf). The iron load of transferrin determines the electrophoretic mobility of the different Tf forms in these urea gels. 3.4. Ferritin, DFO Pharmacokinetics, and Effects on TSAT Arrows indicate the different electrophoretic pattern of ATf, the two monoferric forms of transferrin (mFe-Tf), and the diferric transferrin (diFe-Tf) form in serum samples of stroke patients. Placebo and DFO depict bands of transferrin of two representative patients (one of the placebo group and one of the DFO 60 group) before the onset of treatment (0), and 24 and 72 h after admin- istration. In each lane, optical density of the bands allow calculation of the % TSAT for a given pa- tient at a given time point using the formula: TSAT (%) = (0.5 *mFe·Tf + diFe·Tf)*100/(ATf + mFe·Tf + diFe·Tf). (C–F) % TSAT before the onset of treatment (0 h), and 24 and 72 h after administration of placebo (C), 20 mg/Kg/day DFO (D), 40 mg/Kg/day DFO (E), or 60 mg/Kg/day DFO (F). Values are presented as mean ± SD. * p ≤ 0.05, ** p ≤ 0.005 (repeated measures one-way ANOVA plus the post- hoc Benjamini–Krieger–Yekutieli test). 0.0 0.5 1.0 2 4 6 24 48 72 0 20 40 60 80 100 time (h) DFO (µM) DFO 20 DFO 40 DFO 60 0 24 h 72 h 0 10 20 30 40 50 60 70 % TSAT placebo 0 24 h 72 h 0 10 20 30 40 50 60 70 % TSAT * DFO 40 0 24 h 72 h 0 10 20 30 40 50 60 70 % TSAT DFO 20 0 24 h 72 h 0 10 20 30 40 50 60 70 % TSAT ** p = 0.101 DFO 60 A C D E F B Figure 2. Deferoxamine (DFO) reduces TSAT time- and dose-dependently. (A) Time-course of serum DFO levels along the infusion in AIS patients treated with a 10 mg/Kg bolus of DFO IV followed by a 72 h continuous IV infusion of DFO in escalating dose tiers of 20, 40, or 60 mg/Kg/day (blood DFO levels at time = 0 of infusion in this graph are the result of the initial previous 10 mg/Kg bolus of DFO IV). Mean ± SD are shown; no significant effects were found (repeated measures ANOVA). (B) U-PAGE/WB depicting the bands of the iron-devoid form of human transferrin standard (Std) (apotransferrin, ATf) and human diferric transferrin (diFe-Tf) standard (holotransferrin, HTf). The iron load of transferrin determines the electrophoretic mobility of the different Tf forms in these urea gels. 3.4. Ferritin, DFO Pharmacokinetics, and Effects on TSAT The iron load of transferrin determines the electrophoretic mobility of the different Tf forms in these urea gels. Arrows indicate the different electrophoretic pattern of ATf, the two monoferric forms of transferrin (mFe-Tf), and the diferric transferrin (diFe-Tf) form in serum samples of stroke patients. Placebo and DFO depict bands of transferrin of two representative patients (one of the placebo group and one of the DFO 60 group) before the onset of treatment (0), and 24 and 72 h after administration. In each lane, optical density of the bands allow calculation of the % TSAT for a given patient at a given time point using the formula: TSAT (%) = (0.5 *mFe·Tf + diFe·Tf)*100/(ATf + mFe·Tf + diFe·Tf). (C–F) % TSAT before the onset of treatment (0 h), and 24 and 72 h after administration of placebo (C), 20 mg/Kg/day DFO (D), 40 mg/Kg/day DFO (E), or 60 mg/Kg/day DFO (F). Values are presented as mean ± SD. * p ≤0.05, ** p ≤0.005 (repeated measures one-way ANOVA plus the post-hoc Benjamini–Krieger–Yekutieli test). 3.5. Clinical Outcome No differences were observed in baseline parameters between five of the experimental groups of the study. The lack of patient stratification in the randomization process resulted in a difference in the baseline NIHSS of placebo/DFO arms within the DTS3 (Table 1), this distorting the correct assessment of the effect of treatment within the DTS3 sub-study but not affecting the study when placebo patients were considered as a pool. A post-hoc Antioxidants 2021, 10, 1270 9 of 15 exploratory analysis was performed to evaluate the trend to outcome improvement of DFO in those patients with moderate-severe ischemic stroke (NIHSS > 7) (n = 47) of the whole cohort. Placebo patients in each of the three sub-studies were compiled within a single placebo group, which we term “placebo pool”; NIHSS at admission was not different between placebo and DFO groups in this patient population (Figure 3A). Interestingly, in this patient subpopulation, a trend of reduction of neurological impairment as expressed in percentage of the initial score: (NIHSS baseline-NIHSS 90 days) * 100/NIHSS baseline) was observed in the patient groups administered with the higher DFO doses (DFO 40 and DFO 60, Figure 3B). In addition, a higher proportion of patients having a good outcome (mRS ≤2) was observed in the higher DFO dose groups when assessed early (at day 7) or at 90 days after the stroke event (Figure 3C). At day 7, 40% of patients treated with DFO ≥40 mg/Kg/day showed a good outcome vs. 23% of patients in the placebo arm. Similarly, at 90 days 50–60% of patients treated with DFO ≥40 mg/Kg/day showed a good outcome vs. only 30% in the placebo arm. REVIEW 10 of 16 Figure 3. Exploratory analysis to examine whether the TSAT-modifier deferoxamine (DFO) doses favors a good outcome. (A) Median and quartiles of baseline NIHSS in a subpopulation of the TAN- DEM-1 study with NIHSS at admission > 7. Baseline NIHSS were found balanced between the four treatment groups when considering this patient subpopulation (NIHSS > 7) (p = 0.24, one-way ANOVA). (B) In this subpopulation (NIHSS > 7) we calculated the percentage of neurological im- provement with the formula: % reduction of NIHSS at 90 days = ((NIHSS at admission-NIHSS at a given time)*100/NIHSS at admission). As DFO 40 and DFO 60, but not DFO 20, reduce TSAT, these two groups were pooled and compared to the placebo group. 3.5. Clinical Outcome We observed that half of the patients in the 40 + 60 DFO group showed a 100% reduction of their initial neurological impairment, in con- trast to those in the placebo group (p = 0.0546, Mann–Whitney U test). (C) Graph depicting the pro- portion of AIS patients showing good functional outcome (in black) in the placebo and DFO groups. DFO dose tiers of 40 and 60 mg/Kg/day have higher proportion of AIS classified as good outcome patients (mRS ≤ 2) at 7 and 90 days. Values are presented as median and quartiles and compared with one-way ANOVA (A) or Mann–Whitney U test (B). 4 Discussion Figure 3. Exploratory analysis to examine whether the TSAT-modifier deferoxamine (DFO) doses favors a good outcome. (A) Median and quartiles of baseline NIHSS in a subpopulation of the TANDEM-1 study with NIHSS at admission > 7. Baseline NIHSS were found balanced between the four treatment groups when considering this patient subpopulation (NIHSS > 7) (p = 0.24, one- way ANOVA). (B) In this subpopulation (NIHSS > 7) we calculated the percentage of neurological improvement with the formula: % reduction of NIHSS at 90 days = ((NIHSS at admission-NIHSS at a given time)*100/NIHSS at admission). As DFO 40 and DFO 60, but not DFO 20, reduce TSAT, these two groups were pooled and compared to the placebo group. We observed that half of the patients in the 40 + 60 DFO group showed a 100% reduction of their initial neurological impairment, in contrast to those in the placebo group (p = 0.0546, Mann–Whitney U test). (C) Graph depicting the proportion of AIS patients showing good functional outcome (in black) in the placebo and DFO groups. DFO dose tiers of 40 and 60 mg/Kg/day have higher proportion of AIS classified as good outcome patients (mRS ≤2) at 7 and 90 days. Values are presented as median and quartiles and compared with one-way ANOVA (A) or Mann–Whitney U test (B). Figure 3 Exploratory analysis to examine whether the TSAT-modifier deferoxamine (DFO) doses Figure 3. Exploratory analysis to examine whether the TSAT-modifier deferoxamine (DFO) doses Figure 3 Exploratory analysis to examine whether the TSAT-modifier Figure 3. Exploratory analysis to examine whether the TSAT-modifier Figure 3. Exploratory analysis to examine whether the TSAT-modifier deferoxamine (DFO) doses favors a good outcome. 3.5. Clinical Outcome (A) Median and quartiles of baseline NIHSS in a subpopulation of the TAN- DEM-1 study with NIHSS at admission > 7. Baseline NIHSS were found balanced between the four treatment groups when considering this patient subpopulation (NIHSS > 7) (p = 0.24, one-way ANOVA). (B) In this subpopulation (NIHSS > 7) we calculated the percentage of neurological im- provement with the formula: % reduction of NIHSS at 90 days = ((NIHSS at admission-NIHSS at a given time)*100/NIHSS at admission). As DFO 40 and DFO 60, but not DFO 20, reduce TSAT, these two groups were pooled and compared to the placebo group. We observed that half of the patients in the 40 + 60 DFO group showed a 100% reduction of their initial neurological impairment, in con- trast to those in the placebo group (p = 0.0546, Mann–Whitney U test). (C) Graph depicting the pro- portion of AIS patients showing good functional outcome (in black) in the placebo and DFO groups. DFO dose tiers of 40 and 60 mg/Kg/day have higher proportion of AIS classified as good outcome patients (mRS ≤ 2) at 7 and 90 days. Values are presented as median and quartiles and compared with one-way ANOVA (A) or Mann–Whitney U test (B). 4 Di i Figure 3. Exploratory analysis to examine whether the TSAT-modifier deferoxamine (DFO) doses favors a good outcome. (A) Median and quartiles of baseline NIHSS in a subpopulation of the TANDEM-1 study with NIHSS at admission > 7. Baseline NIHSS were found balanced between the four treatment groups when considering this patient subpopulation (NIHSS > 7) (p = 0.24, one- way ANOVA). (B) In this subpopulation (NIHSS > 7) we calculated the percentage of neurological improvement with the formula: % reduction of NIHSS at 90 days = ((NIHSS at admission-NIHSS at a given time)*100/NIHSS at admission). As DFO 40 and DFO 60, but not DFO 20, reduce TSAT, these two groups were pooled and compared to the placebo group. We observed that half of the patients in the 40 + 60 DFO group showed a 100% reduction of their initial neurological impairment, in contrast to those in the placebo group (p = 0.0546, Mann–Whitney U test). (C) Graph depicting the proportion of AIS patients showing good functional outcome (in black) in the placebo and DFO groups. 3.5. Clinical Outcome DFO dose tiers of 40 and 60 mg/Kg/day have higher proportion of AIS classified as good outcome patients (mRS ≤2) at 7 and 90 days. Values are presented as median and quartiles and compared with one-way ANOVA (A) or Mann–Whitney U test (B). Figure 3. Exploratory analysis to examine whether the TSAT-modifier deferoxamine (DFO) doses favors a good outcome. (A) Median and quartiles of baseline NIHSS in a subpopulation of the TAN- DEM-1 study with NIHSS at admission > 7. Baseline NIHSS were found balanced between the four treatment groups when considering this patient subpopulation (NIHSS > 7) (p = 0.24, one-way ANOVA). (B) In this subpopulation (NIHSS > 7) we calculated the percentage of neurological im- provement with the formula: % reduction of NIHSS at 90 days = ((NIHSS at admission-NIHSS at a given time)*100/NIHSS at admission). As DFO 40 and DFO 60, but not DFO 20, reduce TSAT, these two groups were pooled and compared to the placebo group. We observed that half of the patients in the 40 + 60 DFO group showed a 100% reduction of their initial neurological impairment, in con- trast to those in the placebo group (p = 0.0546, Mann–Whitney U test). (C) Graph depicting the pro- portion of AIS patients showing good functional outcome (in black) in the placebo and DFO groups. DFO dose tiers of 40 and 60 mg/Kg/day have higher proportion of AIS classified as good outcome patients (mRS ≤ 2) at 7 and 90 days. Values are presented as median and quartiles and compared with one-way ANOVA (A) or Mann–Whitney U test (B). 4 Di i Figure 3. Exploratory analysis to examine whether the TSAT-modifier deferoxamine (DFO) doses favors a good outcome. (A) Median and quartiles of baseline NIHSS in a subpopulation of the TANDEM-1 study with NIHSS at admission > 7. Baseline NIHSS were found balanced between the four treatment groups when considering this patient subpopulation (NIHSS > 7) (p = 0.24, one- way ANOVA). (B) In this subpopulation (NIHSS > 7) we calculated the percentage of neurological improvement with the formula: % reduction of NIHSS at 90 days = ((NIHSS at admission-NIHSS at a given time)*100/NIHSS at admission). As DFO 40 and DFO 60, but not DFO 20, reduce TSAT, these two groups were pooled and compared to the placebo group. 4. Discussion This is the first report testing DFO, that targets pro-oxidant iron, in patients with ischemic stroke. DFO as a 10 mg/Kg IV bolus during the tPA infusion followed by a three- day IV continuous infusion of up to 60 mg/Kg/day is safe and well-tolerated, reduces TSAT, and shows a promising trend to better outcome. p g We did not find thrombolysis complications due to DFO or any other DFO-induced change in the number and type of adverse events (see Table 2). This safety DFO data in ischemic stroke patients set the groundwork for a larger clinical trial given the recently reported role of iron-induced ferroptosis as a main contributor of brain damage in exper- imental stroke models [1,4–6,31–33] and of previous reports in which DFO treatment is associated with lower infarct volume, less mitochondrial free radicals [24], less hemor- rhagic transformation, and improved neurological status in experimental ischemic stroke models [4,20,21,24,34–37]. Of note, either treatment with DFO or prevention of cellular iron uptake have been reported to protect neuronal phenotype cells from excitotoxic cell death through a reduction of oxidative stress [12,38,39]. In iron intoxication/overload, DFO administration for several days as a subcutaneous or intravenous slow infusion is indicated [40]. Although DFO administered systemically does not penetrate very well into the brain through an intact blood–brain barrier (BBB), DFO has been found in the experimentally-induced ischemic brain within the first hour post-stroke [34]. Thus, DFO would preferentially reach the ischemic brain areas, with a leaky BBB, while precluding iron chelation by DFO affecting the activity of cellular metalloenzymes in the healthy brain areas. Our study provides information about the pharmacokinetics of DFO in ischemic stroke patients, these data being of interest given that in all the species tested so far DFO demonstrate an extremely short half-life in serum/plasma. In healthy humans, IV or i.m. bolus injection of 10 mg/Kg is safe and serum concentrations of DFO range from 5 to 120 µM within minutes after the bolus injection but levels drop quickly [26,41]. To overcome DFO clearance from blood and to secure sustained therapeutic effects during the critical three days post-stroke-onset, the present study used a single 10 mg/Kg bolus of DFO IV, to reach high blood concentrations within minutes, followed by a 72 h continuous IV infusion of 20, 40, or 60 mg/Kg/day DFO. 3.5. Clinical Outcome We observed that half of the patients in the 40 + 60 DFO group showed a 100% reduction of their initial neurological impairment, in contrast to those in the placebo group (p = 0.0546, Mann–Whitney U test). (C) Graph depicting the proportion of AIS patients showing good functional outcome (in black) in the placebo and DFO groups. DFO dose tiers of 40 and 60 mg/Kg/day have higher proportion of AIS classified as good outcome patients (mRS ≤2) at 7 and 90 days. Values are presented as median and quartiles and compared with one-way ANOVA (A) or Mann–Whitney U test (B). 10 of 15 10 of 15 Antioxidants 2021, 10, 1270 4. Discussion Given that TSAT < 16% is usually considered inadequate for erythropoiesis [49], this provides a rationale for the harmful side effects observed associated to the five-day treatment with 62 mg DFO/Kg/day that was initially proposed in the high dose HI- DEF trial protocol [50]. After a three-day high dose DFO treatment, other interventions known to have a mild effect on TSAT, such as a daily intake of the functional compound polyphenol [51], might be worth being evaluated for their possible contribution to TSAT long-term effects and long-term recovery from stroke. Our findings explain both the safety issues of the HI-DEF trial protocol just mentioned and the lack of effect observed when using an alternative intermediate DFO dose (32 mg/Kg/day) and a shorter three-day infusion in the i-DEF [43] and the Chinese Clinical Trial Registry ChiCTR-TRC-14004979 studies [52]. A strength of our study is that we developed and used a direct measurement of TSAT as a reliable surrogate marker of iron status. The effect of each DFO dose was determined longitudinally in each individual patient, from pre-DFO to the end of treatment, each patient being its own control. Using this strategy, we observed that only 40 and 60 mg/Kg DFO reduced TSAT, and we next studied the effect of these TSAT-modifying doses on outcome. The present study focused on safety and it is not powered to statistically assess efficacy or to equally distribute covariates at baseline along experimental groups, this being a limitation of the study. However, an exploratory analysis of efficacy was performed introducing as a selection criteria that of patients with baseline NIHSS > 7, the less severe strokes not being included in this post-hoc analysis and, in addition, we used the percentage reduction of neurological deterioration as an index that considers the specific neurological score of each patient at admission. In this subpopulation in which baseline scores are similar, DFO induced a larger percent reduction of neurological impairment at 90 days (Figure 3B), and the proportion of good outcome patients (mRS ≤2) increased with the dose of DFO at 7 and at 90 days. The mRS, that has been used to assess neurological status mostly at 90 days to evaluate long-term outcomes, has been reported in recent papers to be informative in the evaluation of short-term outcomes as well [53,54]. 4. Discussion In this regard, previous reports have showed that DFO IV infusion rapidly clears around one third of the non-transferrin- bound iron in the blood [46,47] and reduces intracellular labile iron stores in breast cancer cells [48]. The reduction of TSAT by DFO might well be meaningful to the final outcome in the patients according to the fact that: (1) reduction of TSAT by IV administration of iron-free Tf (apotransferrin) at reperfusion has demonstrated neuroprotective and found associated to better outcome in experimental ischemic stroke models [12]; and (2) blood TSAT at reperfusion positively correlated with infarct volume and neurological impairment in experimental stroke; in rats, a 25% reduction in transferrin saturation decreases ischemic brain damage accordingly [12]. In addition, in the placebo group of the present TANDEM-1 study, the endogenous TSAT level seems to impact the outcome of stroke patients, as indicated by preliminary evidence obtained in the present study (Figure S3). (Available online: https://www.medicines.org.uk/emc/product/5/smpc (accessed on 12 June 2021)) [45], TSAT can be modulated by the iron available in blood to bind circulating Tf and/or the iron availability in the Tf-synthesizing cells. In this regard, previous reports have showed that DFO IV infusion rapidly clears around one third of the non-transferrin- bound iron in the blood [46,47] and reduces intracellular labile iron stores in breast cancer cells [48]. The reduction of TSAT by DFO might well be meaningful to the final outcome in the patients according to the fact that: (1) reduction of TSAT by IV administration of iron-free Tf (apotransferrin) at reperfusion has demonstrated neuroprotective and found associated to better outcome in experimental ischemic stroke models [12]; and (2) blood TSAT at reperfusion positively correlated with infarct volume and neurological impairment in experimental stroke; in rats, a 25% reduction in transferrin saturation decreases ischemic brain damage accordingly [12]. In addition, in the placebo group of the present TANDEM-1 study, the endogenous TSAT level seems to impact the outcome of stroke patients, as indicated by preliminary evidence obtained in the present study (Figure S3). y p y p y g Results in Figure 2F show that a bolus + three-day 60 mg/Kg/day DFO treatment reduces TSAT to half the baseline levels, and the time-effect suggests that administration of 60 mg/Kg/day exceeding three consecutive days would result in too low TSAT (below 16%). 4. Discussion The higher serum DFO levels were observed within the first 30 min of treatment onset as a result of the initial DFO bolus administration (Figure 2A); thereafter, blood DFO levels dropped despite the three-day continuous infusion protocol. We did not find significant differences in DFO pharmacokinetics among different dose tiers along the 72 h follow-up (Figure 2A); this lack of differences could be anticipated in view of: (1) the limited stability and high individual variability of DFO pharmacokinetics reported in a previous clinical study [42], and (2) the rapid clearance of DFO from systemic circulation at clinically relevant doses (half-life of 5–17 min [26,42]). Of note, previous clinical studies using DFO as a continuous infusion in ICH stroke patients did not report pharmacokinetic data [25,43], and a recent study in rats concluded that the biodistribution and clearance from blood was too rapid to generate meaningful blood DFO pharmacokinetics [44]. A dose-dependent effect of the bolus + three-day sustained DFO infusion was ob- served on the reduction of an important systemic iron parameter, the % saturation of blood transferrin (Tf) with iron (TSAT), which gives the relative amount of iron-free and iron-loaded Tf in blood. Transferrin is the physiological carrier and provider of iron to neurons. We have previously reported the importance of blood Tf load with iron in ischemia events, as iron-loaded transferrin promotes ROS production at reperfusion in stroke models whereas iron-free transferrin prevents the production of 4-hydroxynonenal during ischemia/excitotoxicity in vitro [12]. Blood TSAT remained steady along 72 h in the stroke patients in the placebo group. DFO 40 and 60 mg/Kg/day significantly reduced TSAT by 30% and 40%, respectively, when measured at 72 h (Figure 2E,F) indicating an effective reduction of systemic iron, and the higher 60 mg/Kg/day DFO dose showed a trend to reduce TSAT after only 24 h of treatment (p = 0.107, repeated measures analysis). Although DFO is unable to directly remove iron from transferrin at physiological pH 11 of 15 Antioxidants 2021, 10, 1270 11 of 15 (Available online: https://www.medicines.org.uk/emc/product/5/smpc (accessed on 12 June 2021)) [45], TSAT can be modulated by the iron available in blood to bind circulating Tf and/or the iron availability in the Tf-synthesizing cells. 4. Discussion Although this is a post hoc analysis based on a relatively small number of patients, our observations support that DFO, at doses capable of reducing systemic iron and TSAT, seem to be a promising therapy increasing the proportion of patients showing better functional outcome. The effects of DFO preventing neurological impairment induced by AIS does not seem to be due to a possible impact on circulating immune cells since no effect of DFO was observed in blood leucocyte counts in our study (Figure S4), but rather associated with its iron-chelation and antioxidant properties. 12 of 15 12 of 15 Antioxidants 2021, 10, 1270 5. Conclusions Acknowledgments: The authors acknowledge Karla Odendaal for her help in improving the stan- dard of English in the manuscript. Acknowledgments: The authors acknowledge Karla Odendaal for her help in improving the stan- dard of English in the manuscript. Conflicts of Interest: The authors declare that there is no conflict of interest regarding the publication of this paper. 5. Conclusions This study demonstrates that DFO in a bolus followed by doses of 40 to 60 mg/Kg/day is safe and well-tolerated in AIS patients, reduces systemic iron over 1–3 days and might provide long term (three months) benefit to AIS patients. Our findings have important implications to select the appropriate DFO dosage for future trials and provide medical plausibility and the rationale to further explore DFO effect in a larger cohort of patients or to test other therapeutic interventions addressed to quickly reduce TSAT in stroke. Supplementary Materials: The following are available online at https://www.mdpi.com/article/ 10.3390/antiox10081270/s1, Figure S1: Effect of DFO on CT hypodensity; Figure S2: Effect of deferoxamine (DFO) on cardiovascular parameters, body temperature, and blood glucose; Figure S3: Relationship between % TSAT of each patient in the placebo arm at admission and % reduction of neurological impairment; Figure S4: Effect of 72 h treatment with DFO on blood leucocytes; Table S1: Reported serious adverse events in the placebo and DFO group in each DTS. Author Contributions: Conceptualization, M.M., A.D., and T.G.; Patient inclusion and clinical data collection, M.M., N.P.d.l.O., Y.S., F.N., P.G., M.R.-Y., J.C. (Joan Costa), J.S., J.V., and A.D.; Investigation and laboratory work, N.D.-R., F.C., T.S., and O.M.-S.; Data curation and statistics J.C. (Jordi Cortés); Writing—original draft preparation and writing-review and editing, M.M., A.D., and T.G.; Project administration, S.R.; Funding acquisition, A.D. All authors have read and agreed to the published version of the manuscript. Funding: This academic research was supported by grants from the Fondo de Investigaciones Sanitarias-Instituto de Salud Carlos III (2007-006731-31) to M.M., INVICTUS PLUS RD16/0019/0020 to A.D. that was susceptible to be co-financed by FEDER funds, and a grant from Agència de Gestió d’Ajuts Universitaris i de Recerca 2017 SGR 1520 to A.D. and 2019PROD00120 to T.G. Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Spanish Drug Agency (eudraCT 2007-0006731-31) and the Institutional Ethics Committee of the Hospital Germans Trias i Pujol. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: Data is contained within the article and supplementary material. Data Availability Statement: Data is contained within the article and supplementary material. Acknowledgments: The authors acknowledge Karla Odendaal for her help in improving the stan- dard of English in the manuscript. Abbreviations AE adverse events AIS acute ischemic stroke aPTT activated partial thromboplastin time ASPECTS Alberta Stroke Program Early CT Score ATf apotransferrin BBB blood–brain barrier CT computed tomography DFO deferoxamine diFe-Tf diferric transferrin DSMB data safety monitoring board DTS dose tier sub-study ENW early neurological worsening HTf holotransferrin ICH intracerebral hemorrhage i.m. intramuscular IV intravenous AE adverse events AIS acute ischemic stroke aPTT activated partial thromboplastin tim ASPECTS Alberta Stroke Program Early CT Sc ATf apotransferrin BBB blood–brain barrier CT computed tomography DFO deferoxamine diFe-Tf diferric transferrin DSMB data safety monitoring board DTS dose tier sub-study ENW early neurological worsening HTf holotransferrin ICH intracerebral hemorrhage i.m. intramuscular IV intravenous Antioxidants 2021, 10, 1270 13 of 15 13 of 15 MCA middle cerebral artery mFe-Tf monoferric transferrin mRS modified Rankin Scale NIHSS National Institute of Health Stroke Scale ROS reactive oxygen species SAE serious adverse events sICH symptomatic intracranial hemorrhage; study TANDEM Thrombolysis And Deferoxamine in Middle Cerebral Artery Occlusion Tf transferrin tPA tissue plasminogen activator TSAT % of iron saturation of blood transferrin U-PAGE/WB urea-polyacrylamide gel electrophoresis/Western Blot References Extract of Naotaifang, a compound Chinese herbal medicine, protects neuron ferroptosis induced by acute cerebral ischemia in rats. J. Integr. Med. 2020, 18, 344–350. [CrossRef] 7. Geng, Z.; Guo, Z.; Guo, R.; Ye, R.; Zhu, W.; Yan, B. Ferroptosis and traumatic brain injury. Brain Res. Bull. 2021, 172, 212–219. [CrossRef] [PubMed] 6. Lan, B.; Ge, J.; Cheng, S.; Zheng, X.; Liao, J.; He, C.; Rao, Z.-Q.; Wang, G.-Z. Extract of Naotaifang, a compound Chinese herbal medicine, protects neuron ferroptosis induced by acute cerebral ischemia in rats. J. Integr. Med. 2020, 18, 344–350. [CrossRef] 7 G Z G Z G R Y R Zh W Y B F t i d t ti b i i j B i R B ll 2021 172 212 219 6. Lan, B.; Ge, J.; Cheng, S.; Zheng, X.; Liao, J.; He, C.; Rao, Z.-Q.; Wang, G.-Z. Extract of Naotaifang, a compound Chinese herbal medicine, protects neuron ferroptosis induced by acute cerebral ischemia in rats. J. Integr. Med. 2020, 18, 344–350. [CrossRef] 7. Geng, Z.; Guo, Z.; Guo, R.; Ye, R.; Zhu, W.; Yan, B. Ferroptosis and traumatic brain injury. Brain Res. Bull. 2021, 172, 212–219. [CrossRef] [PubMed] [ ] [ ] 8. Tan, Q.; Fang, Y.; Gu, Q. Mechanisms of Modulation of Ferroptosis and Its, Role in Central, Nervous System, Diseases. Front. Pharmacol. 2021, 12, 657033. [CrossRef] [PubMed] 9. Mehta, S.H.; Webb, R.C.; Ergul, A.; Tawfik, A.; Dorrance, A.M. Neuroprotection by tempol in a model of iron-induced oxidative stress in acute ischemic stroke. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2004, 286, R283–R288. [CrossRef] [PubMed] 10. Wu, J.; Hua, Y.; Keep, R.F.; Nakamura, T.; Hoff, J.T.; Xi, G. Iron and iron-handling proteins in the brain after intracerebral hemorrhage. Stroke 2003, 34, 2964–2969. [CrossRef] [PubMed] 11. García-Yébenes, I.; García-Culebras, A.; Peña-Martínez, C.; Fernández-López, D.; Díaz-Guzmán, J.; Negredo, P.; Avendaño, C.; Castellanos, M.; Gasull, T.; Dávalos, A.; et al. Iron overload exacerbates the risk of hemorrhagic transformation after tPA (tissue-type plasminogen activator) administration in thromboembolic stroke mice. Stroke 2018, 49, 2163–2172. [CrossRef] [PubMed] 12. DeGregorio-Rocasolano, N.; Martí-Sistac, O.; Ponce, J.; Castelló-Ruiz, M.; Millán, M.; Guirao, V.; García-Yébenes, I.; Salom, J.B.; Ramos-Cabrer, P.; Alborch, E.; et al. Iron-loaded transferrin (Tf) is detrimental whereas iron-free Tf confers protection against brain ischemia by modifying blood Tf saturation and subsequent neuronal damage. Redox Biol. 2018, 15, 143–158. [CrossRef] [PubMed] 13. References 1. Yang, W.; Liu, X.; Song, C.; Ji, S.; Yang, J.; Liu, Y.; You, J.; Zhang, J.; Huang, S.; Cheng, W.; et al. Structure-activity relationship studies of phenothiazine derivatives as a new class of ferroptosis inhibitors together with the therapeutic effect in an ischemic stroke model. Eur. J. Med. Chem. 2021, 209, 112842. [CrossRef] 1. Yang, W.; Liu, X.; Song, C.; Ji, S.; Yang, J.; Liu, Y.; You, J.; Zhang, J.; Huang, S.; Cheng, W.; et al. Structure-activity relationship studies of phenothiazine derivatives as a new class of ferroptosis inhibitors together with the therapeutic effect in an ischemic stroke model. Eur. J. Med. Chem. 2021, 209, 112842. [CrossRef] 2. Magtanong, L.; Dixon, S.J. Ferroptosis and brain injury. Dev. Neurosci. 2018, 40, 382–395. [CrossRef 2. Magtanong, L.; Dixon, S.J. Ferroptosis and brain injury. Dev. Ne g g p j y 3. DeGregorio-Rocasolano, N.; Martí-Sistac, O.; Gasull, T. Deciphering the iron side of stroke: Neurodegeneration at the crossroads between iron dyshomeostasis, excitotoxicity, and ferroptosis. Front. Neurosci. 2019, 13, 85. [CrossRef] g g p j y 3. DeGregorio-Rocasolano, N.; Martí-Sistac, O.; Gasull, T. Deciphering the iron side of stroke: Neurodegeneration at the crossroads between iron dyshomeostasis, excitotoxicity, and ferroptosis. Front. Neurosci. 2019, 13, 85. [CrossRef] y y p 4. Abdul, Y.; Li, W.; Ward, R.; Abdelsaid, M.; Hafez, S.; Dong, G.; Jamil, S.; Wolf, V.; Johnson, M.H.; Fagan, S.C.; et al. Deferoxamine treatment prevents post-stroke vasoregression and neurovascular unit remodeling leading to improved functional outcomes in type 2 male diabetic rats: Role of endothelial ferroptosis. Transl. Stroke Res. 2020, 12, 615–630. [CrossRef] y y p 4. Abdul, Y.; Li, W.; Ward, R.; Abdelsaid, M.; Hafez, S.; Dong, G.; Jamil, S.; Wolf, V.; Johnson, M.H.; Fagan, S.C.; et al. Deferoxamine treatment prevents post-stroke vasoregression and neurovascular unit remodeling leading to improved functional outcomes in type 2 male diabetic rats: Role of endothelial ferroptosis. Transl. Stroke Res. 2020, 12, 615–630. [CrossRef] yp p [ ] 5. Lu, J.; Xu, F.; Lu, H. LncRNA PVT1 regulates ferroptosis through miR-214-mediated TFR1 and p53. Life Sci. 2020, 260, 118305. [CrossRef] yp p 5. Lu, J.; Xu, F.; Lu, H. LncRNA PVT1 regulates ferroptosis through miR-214-mediated TFR1 and p53. Life Sci. 2020, 260, 118305. [CrossRef] 6. Lan, B.; Ge, J.; Cheng, S.; Zheng, X.; Liao, J.; He, C.; Rao, Z.-Q.; Wang, G.-Z. 19. Ghosh, K.; Ghosh, K. Iron chelators or therapeutic modulators of iron overload: Are we anywhere nea Res. 2018, 148, 369–372. [CrossRef] References Cui, H.J.; He, H.Y.; Yang, A.L.; Zhou, H.J.; Wang, C.; Luo, J.K.; Lin, Y.; Tang, T. Efficacy of deferoxamine in animal models of intracerebral hemorrhage: A systematic review and stratified meta-analysis PLoS ONE 2015 10 e0127256 [CrossRef] yp g y 22. Cui, H.J.; He, H.Y.; Yang, A.L.; Zhou, H.J.; Wang, C.; Luo, J.K.; Lin, Y.; Tang, T. Efficacy of deferoxam intracerebral hemorrhage: A systematic review and stratified meta-analysis. PLoS ONE 2015, 10, e0127 g y y 23. Guo, X.; Qi, X.; Li, H.; Duan, Z.; Wei, Y.; Zhang, F.; Tian, M.; Ma, L.; You, C. Deferoxamine alleviates iron overload and brain injury in a rat model of brainstem hemorrhage. World Neurosurg. 2019, 128, e895–e904. [CrossRef] [PubMed] 24. Im, D.S.; Jeon, J.W.; Lee, J.S.; Won, S.J.; Cho, S.I.; Lee, Y.B.; Gwag, B.J. Role of the NMDA receptor and iron on free radical production and brain damage following transient middle cerebral artery occlusion. Brain Res. 2012, 1455, 114–123. [CrossRef] 25. Selim, M.; Yeatts, S.; Goldstein, J.N.; Gomes, J.; Greenberg, S.; Morgenstern, L.B.; Schlaug, G.; Torbey, M.; Waldman, B.; Xi, G.; et al. 24. Im, D.S.; Jeon, J.W.; Lee, J.S.; Won, S.J.; Cho, S.I.; Lee, Y.B.; Gwag, B.J. Role of the NMDA receptor and iron on free radical production and brain damage following transient middle cerebral artery occlusion. Brain Res. 2012, 1455, 114–123. [CrossRef] 25. Selim, M.; Yeatts, S.; Goldstein, J.N.; Gomes, J.; Greenberg, S.; Morgenstern, L.B.; Schlaug, G.; Torbey, M.; Waldman, B.; Xi, G.; et al. Safety and tolerability of deferoxamine mesylate in patients with acute intracerebral hemorrhage. Stroke 2011, 42, 3067–3074. [CrossRef] 26. Summers, M.R.; Jacobs, A.; Tudway, D.; Perera, P.; Ricketss, C. Studies in desferrioxamine and ferrioxamine metabolism in normal and iron-loaded subjects. Br. J. Haematol. 1979, 42, 547–555. [CrossRef] [PubMed] 27. Menéndez-Fraga, P.; Blanco-González, E.; Sanz-Medel, A.; Cannata-Andía, J.B. Micellar versus reversed phase liquid chromatog- raphy for the determination of desferrioxamine and its chelates with aluminium and iron in uremic serum. Talanta 1997, 45, 25–33. [CrossRef] 28. Larrue, V.; von Kummer, R.; Müller, A.; Bluhmki, E. Risk factors for severe hemorrhagic transformation in ischemic stroke patients treated with recombinant tissue plasminogen activator. Stroke 2001, 32, 438–441. [CrossRef] 29. Wahlgren, N.; Ahmed, N.; Dávalos, A.; Ford, G.A.; Grond, M.; Hacke, W.; Hennerici, M.G.; Kaste, M.; Kuelkens, S.; Larrue, V.; et al. References Thrombolysis with alteplase for acute ischaemic stroke in the Safe Implementation of Thrombolysis in Stroke-Monitoring Study (SITS-MOST): An observational study. Lancet 2007, 369, 275–282. [CrossRef] y 30. Adams, P.C.; Reboussin, D.M.; Barton, J.C.; McLaren, C.E.; Eckfeldt, J.H.; McLaren, G.D.; Dawkins, F.W.; Acton, R.T.; Harris, E.L.; Gordeuk, V.R.; et al. Hemochromatosis and iron-overload screening in a racially diverse population. N. Engl. J. Med. 2005, 352, 1769–1778. [CrossRef] 31. Karuppagounder, S.S.; Alin, L.; Chen, Y.; Brand, D.; Bourassa, M.W.; Dietrich, K.; Wilkinson, C.M.; Nadeau, C.A.; Kumar, A.; Perry, S.; et al. N-acetylcysteine targets 5 lipoxygenase-derived, toxic lipids and can synergize with PGE 2 to inhibit ferroptosis and improve outcomes following hemorrhagic stroke in mice. Ann. Neurol. 2018, 84, 854–872. [CrossRef] [PubMed] 32. Chen, B.; Chen, Z.; Liu, M.; Gao, X.; Cheng, Y.; Wei, Y.; Wu, Z.B.; Cui, D.; Shang, H. Inhibition of neuronal ferroptosis in the acute phase of intracerebral hemorrhage shows long-term cerebroprotective effects. Brain Res. Bull. 2019, 153, 122–132. [CrossRef] 33. Tuo, Q.; Lei, P.; Jackman, K.-A.; Li, X.; Xiong, H.; Li, X.; Liuyang, Z.-Y.; Roisman, L.; Zhang, S.-T.; A iron export prevents ferroptotic damage after ischemic stroke. Mol. Psychiatry 2017, 22, 1520–1530. p p p g y y 34. Palmer, C.; Roberts, R.; Bero, C. Deferoxamine posttreatment reduces ischemic brain injury in neonatal rats. Stroke 1994, 25, 1039–1045. [CrossRef] [PubMed] 35. Freret, T.; Valable, S.; Chazalviel, L.; Saulnier, R.; Mackenzie, E.T.; Petit, E.; Bernaudin, M.; Boulouard, M.; Schumann-Bard, P. Delayed administration of deferoxamine reduces brain damage and promotes functional recovery after transient focal cerebral ischemia in the rat. Eur. J. Neurosci. 2006, 23, 1757–1765. [CrossRef] 36. Li, Y.X.; Ding, S.J.; Xiao, L.; Guo, W.; Zhan, Q. Desferoxamine preconditioning protects against cerebral ischemia in rats by inducing expressions of hypoxia inducible factor 1α and erythropoietin. Neurosci. Bull. 2008, 24, 89–95. [CrossRef] h h l k d l d h d f 37. Zhao, Y.; Rempe, D.A. Prophylactic neuroprotection against stroke: Low-dose, prolonged treatment with deferoxamine or deferasirox establishes prolonged neuroprotection independent of HIF-1 function. J. Cereb. Blood Flow Metab. 2011, 31, 1412–1423. [CrossRef] 38. Sakamoto, K.; Suzuki, T.; Takahashi, K.; Koguchi, T.; Hirayama, T.; Mori, A.; Nakahara, T.; Nagasawa, H.; Ishii, K. Iron-chelating agents attenuate NMDA-Induced neuronal injury via reduction of oxidative stress in the rat retina. Exp. Eye Res. 2018, 171, 30–36. [CrossRef] [PubMed] 39. Tian, Y.; He, Y.; Song, W.; Zhang, E.; Xia, X. 20. Hanson, L.R.; Roeytenberg, A.; Martinez, P.M.; Coppes, V.G.; Sweet, D.C.; Rao, R.J.; Marti, D.L.; Hoekman, J.D.; Matthews, R.B.; Frey, W.H.; et al. Intranasal deferoxamine provides increased brain exposure and significant protection in rat ischemic stroke. J. Pharmacol. Exp. Ther. 2009, 330, 679–686. [CrossRef] References Castellanos, M.; Puig, N.; Carbonell, T.; Castillo, J.; Martinez, J.M.; Rama, R.; Davalos, A. Iron intake increases infarct volume after permanent middle cerebral artery occlusion in rats. Brain Res. 2002, 952, 1–6. [CrossRef] p y 14. Nakamura, T.; Keep, R.F.; Hua, Y.; Schallert, T.; Hoff, J.T.; Xi, G. Deferoxamine-induced attenuation of brain edema and neurological deficits in a rat model of intracerebral hemorrhage. J. Neurosurg. 2004, 100, 672–678. [CrossRef] 15. Mehdiratta, M.; Kumar, S.; Hackney, D.; Schlaug, G.; Selim, M. Association between serum ferritin level and perihematoma edema volume in patients with spontaneous intracerebral hemorrhage. Stroke 2008, 39, 1165–1170. [CrossRef] 16. De la Ossa, N.P.; Sobrino, T.; Silva, Y.; Blanco, M.; Millan, M.; Gomis, M.; Agulla, J.; Araya, P.; Reverté-Vil Iron-related brain damage in patients with intracerebral hemorrhage. Stroke 2010, 41, 810–813. [CrossR 16. De la Ossa, N.P.; Sobrino, T.; Silva, Y.; Blanco, M.; Millan, M.; Gomis, M.; Agulla, J.; Araya, P.; Reverté-Villarroya, S.; Serena, J.; et al. Iron-related brain damage in patients with intracerebral hemorrhage. Stroke 2010, 41, 810–813. [CrossRef] 17 Dá l A C till J M t J F d R l J M A A C b l P R R B d i t d l 17. Dávalos, A.; Castillo, J.; Marrugat, J.; Fernandez-Real, J.M.; Armengou, A.; Cacabelos, P.; Rama, R. Bo neurologic deterioration in acute cerebral infarction. Neurology 2000, 54, 1568–1574. [CrossRef] 18. Millan, M.; Sobrino, T.; Castellanos, M.; Nombela, F.; Arenillas, J.F.; Riva, E.; Cristobo, I.; García, M.M.; Vivancos, J.; Serena, J.; et al. Increased body iron stores are associated with poor outcome after thrombolytic treatment in acute stroke. Stroke 2007, 38, 90–95. [CrossRef] [ ] 19. Ghosh, K.; Ghosh, K. Iron chelators or therapeutic modulators of iron overload: Are we anywhere near ideal one? Indian J. Med. Res. 2018, 148, 369–372. [CrossRef] 14 of 15 14 of 15 Antioxidants 2021, 10, 1270 20. Hanson, L.R.; Roeytenberg, A.; Martinez, P.M.; Coppes, V.G.; Sweet, D.C.; Rao, R.J.; Marti, D.L.; Hoekman, J.D.; Matthews, R.B.; Frey, W.H.; et al. Intranasal deferoxamine provides increased brain exposure and significant protection in rat ischemic stroke. J. Pharmacol. Exp. Ther. 2009, 330, 679–686. [CrossRef] p 21. Xing, Y.; Hua, Y.; Keep, R.; Xi, G. Effects of deferoxamine on brain injury after transient focal ce hyperglycemia. Brain Res. 2009, 1291, 113–121. [CrossRef] [PubMed] hyperglycemia. Brain Res. 2009, 1291, 113–121. [CrossRef] [PubMed] 22. References Neuroprotective effect of deferoxamine on N-methyl-d-aspartate-induced excitotoxicity in RGC-5 cells. Acta Biochim. Biophys. Sin. 2017, 49, 827–834. [CrossRef] 40. Aaseth, J.; Skaug, M.A.; Cao, Y.; Andersen, O. Chelation in metal intoxication-Principles and parad 2015, 31, 260–266. [CrossRef] , M.A.; Cao, Y.; Andersen, O. Chelation in metal intoxication-Principles and paradigms. J. Trace Elem. Med. 6. [CrossRef] 41. Allain, P.; Mauras, Y.; Chaleil, D.; Simon, P.; Ang, K.; Cam, G.; Le Mignon, L.; Simon, M. Pharmacokinetics and renal elimination of desferrioxamine and ferrioxamine in healthy subjects and patients with haemochromatosis. Br. J. Clin. Pharmacol. 1987, 24, 207–212. [CrossRef] 42. Lee, P.; Mohammed, N.; Marshall, L.; Abeysinghe, R.D.; Hider, R.C.; Porter, J.B.; Singh, S. Intravenous in of desferrioxamine in thalassaemic patients. Drug Metab. Dispos. 1993, 21, 640–644. 43. Selim, M.; Foster, L.D.; Moy, C.S.; Xi, G.; Hill, M.D.; Morgenstern, L.B.; Greenberg, S.M.; James, M.L.; Singh, V.; Clark, W.M.; et al. Deferoxamine mesylate in patients with intracerebral haemorrhage (i-DEF): A multicentre, randomised, placebo-controlled, double-blind phase 2 trial. Lancet Neurol. 2019, 18, 428–438. [CrossRef] 15 of 15 15 of 15 Antioxidants 2021, 10, 1270 44. Wang, Y.; Liu, Z.; Lin, T.M.; Chanana, S.; Xiong, M.P. Nanogel-DFO conjugates as a model to investigate pharmacokinetics, biodistribution, and iron chelation in vivo. Int. J. Pharm. 2018, 538, 79–86. [CrossRef] [PubMed] J [ ] [ ] 45. Abergel, R.J.; Raymond, K.N. Terephthalamide-containing ligands: Fast removal of iron from transferrin. J Biol. Inorg. Chem. 2008, 13, 229–240. [CrossRef] [PubMed] 46. Porter, J.B.; Abeysinghe, R.D.; Marshall, L.; Hider, R.C.; Singh, S. Kinetics of removal and reappearance of non-transferrin-bound plasma iron with deferoxamine therapy. Blood 1996, 88, 705–713. [CrossRef] p py 47. Porter, J.B.; Rafique, R.; Srichairatanakool, S.; Davis, B.A.; Shah, F.T.; Hair, T.; Evans, P. Recent insights into interactions of deferoxamine with cellular and plasma iron pools: Implications for clinical use. Ann. N. Y. Acad. Sci. 2005, 1054, 155–168. [CrossRef] 48. Bajbouj, K.; Shafarin, J.; Hamad, M. High-dose deferoxamine treatment disrupts intracellular iron homeostasis reduces growth and induces apoptosis in metastatic and nonmetastatic breast cancer cell lines. Technol. Cancer Res. Treat. 2018, 17, 1533033818764470. [CrossRef] 49. Worwood, M.; May, A.M.; Bain, B.J. Iron deficiency anaemia and iron overload. In Dacie and Lewis Practical Haematology, 20th ed.; Elsevier: Amsterdam, The Netherlands, 2017; pp. 165–186. 50. Yeatts, S.D.; Palesch, Y.Y.; Moy, C.S.; Selim, M. High dose deferoxamine in intracerebral hemorrhage (Hi-Def) trial: Rationale, design, and methods. Neurocrit. Care 2013, 19, 257–266. References [CrossRef] [PubMed] 51. Xu, T.; Zhang, X.; Liu, Y.; Wang, H.; Luo, J.; Luo, Y.; An, P. Effects of dietary polyphenol supplementation on iron status and erythropoiesis: A systematic review and meta-analysis of randomized controlled trials. Am. J. Clin. Nutr. 2021, 114, 780–793. [CrossRef] [PubMed] 52. Yu, Y.; Zhao, W.; Zhu, C.; Kong, Z.; Xu, Y.; Liu, G.; Gao, X. The clinical effect of deferoxamine mesylate on edema after intracerebral hemorrhage. PLoS ONE 2015, 10, e0122371. [CrossRef] [PubMed] 53. Byrappa, V.; Lamperti, M.; Ruzhyla, A.; Killian, A.; John, S.; St Lee, T. Acute ischemic stroke & emergency mechanical thrombec- tomy: The effect of type of anesthesia on early outcome. Clin. Neurol. Neurosurg. 2021, 202, 106494. [CrossRef] [PubMed] 54. Gulati, A.; Agrawal, N.; Vibha, D.; Misra, U.K.; Paul, B.; Jain, D.; Pandian, J.; Borgohain, R. Safety and Efficacy of Sovateltide (IRL-1620) in a Multicenter Randomized Controlled Clinical Trial in Patients with Acute Cerebral Ischemic Stroke. CNS Drugs 2021 35 85 104 [C R f] [P bM d] 53. Byrappa, V.; Lamperti, M.; Ruzhyla, A.; Killian, A.; John, S.; St Lee, T. Acute ischemic stroke & emergency mechanical thrombec- tomy: The effect of type of anesthesia on early outcome. Clin. Neurol. Neurosurg. 2021, 202, 106494. [CrossRef] [PubMed] 54. Gulati, A.; Agrawal, N.; Vibha, D.; Misra, U.K.; Paul, B.; Jain, D.; Pandian, J.; Borgohain, R. Safety and Efficacy of Sovateltide (IRL-1620) in a Multicenter Randomized Controlled Clinical Trial in Patients with Acute Cerebral Ischemic Stroke. CNS Drugs 2021, 35, 85–104. [CrossRef] [PubMed]
https://openalex.org/W4301319716
https://jurnal.unimed.ac.id/2012/index.php/aromatika/article/download/37448/19057
Indonesian
null
Bioethanol Levels from Corn Cob Waste: Effect of Fermentation Time and Saccharomyces cerevisiae Yeast Amount (Zea mays)
Indonesian Journal of Chemical Science and Technology
2,022
cc-by
1,790
Bioethanol Levels from Corn Cob Waste: Effect of Fermentation Time and Saccharomyces cerevisiae Yeast Amount (Zea mays) Veronika Meiyuina Simatupang *, Ramlan Silaban Dapertemen Kimia, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Medan *Email : vmeiyulina@gmail.com Keywords: Immobilisasi sel, Corn cobs (Zea mays), Bioethanol anaerob4. Fermentasi dilakukan dengan tujuan perombakan glukosa menjadi alkohol dengan bantuan khamir 5. ABSTRACT This study aims to determine the highest levels of bioethanol produced through the fermentation process, by looking at the effect of variations in the amount of Saccharomyces cerevisiae, immobilization, and fermentation time, as well as the effect of the amount of Saccharomyces cerevisiae and fermentation time on the ethanol content produced. The highest ethanol content was 39.5 percent in the bioethanol test, with the amount of Saccharomyces cerevisiae 8 grams and fermentation time of 9 days. The treatment given to the number of immobilized Saccharomyces cerevisiae cells and the length of time of fermentation had a major effect on the ethanol content produced, as shown by Anova. Keywords: Immobilisasi sel, Corn cobs (Zea mays), Bioethanol Article Indonesian Journal of Chemical Science and Technology State University of Medan e-ISSN : 2622-4968, p-ISSN : 2622-1349 IJCST-UNIMED, Vol. 05, No. 2, Page ; 63 – 66 Received : June 9th, 2022 Accepted : July 13th, 2022 Web Publised ; July 30th, 2022 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- Article Indonesian Journal of Chemical Science and Technology State University of Medan e-ISSN : 2622-4968, p-ISSN : 2622-1349 IJCST-UNIMED, Vol. 05, No. 2, Page ; 63 – 66 Received : June 9th, 2022 Accepted : July 13th, 2022 Web Publised ; July 30th, 2022 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- Article Received : June 9th, 2022 Received : June 9th, 2022 Received : June 9th, 2022 Accepted : July 13th, 2022 IJCST.2022 I. Pendahuluan Penggunaan bahan bakar fosil memiliki kontribusi dalam pencemaran terhadap lingkungan. Penggunaan bahan bakar fosil dapat menyebabkan emisi karbon dioksida, pemanasan global, gas rumah kaca, dan dapat membentuk lapisan diatmosfer yang memyebabkan peningkatan panas diatmosfer. Selain karena penggunaan bahan bakar fosil yang menyebabkan pencemaran terhadap lingkungan, sumber bahan bakar fosil juga memiliki ketersediaan yang sedikit dialam1. Etanol adalah bagian paling sederhana dalam alkohol, dimana alkohol adalah istilah yang umum untuk senyawa organik yang memiliki gugus hidroksil (–OH) yang terikat pada atom karbon, yang ia sendiri terikat pada atom hidrogen dan/atau atom karbon6. Penggunaan bioetanol sebagai bahan bakar, memberikan beberapa keunggulan jika dibandingkan dengan penggunaan bahan bakar fosil. Pertama, nilai bilangan oktan bioetanol lebih tinggi (106-110) dengan nilai bilangan oktan (91- 96). Kedua, pemanfaatan bioetanol dapat meningkatkan efisiensi pembakaran dan menguragi penurunan emisi polutan7. Menipisnya ketersedian bahan bakar fosil dialam memerlukan adanya pembaharuan energi2, energi alternatif yang tersedia saat ini adalah dengan penggunaan bioetanol sebagai bahan bakar yang berasal dari tumbuhan yang mengandung komponen gula dan pati dengan menggunakan proses fermentasi3. Fermentasi bioetanol dilakukan dengan bantuan khamir Saccharomyces cerevisiae dimana proses fermentasi dilakukan dalam kondisi Tongkol jagung memiliki sifat kimia dan fisik yang menjadikannya ideal untuk produksi energi alternatif (bioetanol). Mereka mengandung 6,7- 13,9 % senyawa kompleks lignin, 39,8 % 63 IJCST.2022 © 2022 State University of Medan IJCST.2022 esian Journal of Chemical Science and Technology (IJCST-UNIMED) (2022) Volume 05, No 2, pp 63-66 hemiselulosa, dan 32,3-45,6 % selulosa8. Selulosa merupakan komponen struktural yang tergolong sebagai karbohidrat dan utama terkandung dalam biomassa sebesar 40 – 50% dari berat9. diatur pH nya menjadi 4,5-5 dengan penambahan NaOH/HCl. Tahap keempat Saccharomyces cerevisiae di immobilisasikan menggunakan Na-Alginate 4% dan CaCl 7% dengan variasi banyak ragi sebesar (2 gram, 5 gram, 8 gram). Sehingga menghasilkan sel Saccharomyces cerevisiae terimmobil dalam bentuk beads. Penggunaan Saccharomyces cerevisiae dalam pembuatan bioetanol dikarenakan kemampuan Saccharomyces cerevisiae untuk menghasilkan etanol dalam jumlah besar, dan nilai toleransi yg cukup tinggi terhadap kadar etanol yang tinggi10. Dalam perkembangannya dalam pembuatan bioetanol mengarah pada cara yang lebih modern, dengan menggunakan teknik immobilisasi sel, yang berpotensi dalam meningkatkan kadar bioetanol yang didapatkan11. Tahap kelima adalah tahap fermentasi, dimana sel Saccharomyces cerevisiae yang telah terimobilisasi dengan variasi ragi (2 gram, 5 gram, 8 gram) dimasukkan kedalam filtrat hasil hidrolisis yang telah diatur pH nya. Proses fermentasi dilakukan dengan variasi lama waktu fermentasi (2 hari, 5 hari, 9 hari, 14 hari) dengan kondisi anaerob, suhu ruang. I. Pendahuluan Berdasarkan latar belakang diatas, peneliti ingin meneliti mengenai pengaruh dari waktu fermentasi dan banyak ragi Saccharomyces cerevisiae terhadap kadar bioetanol dari limbah tongkol jagung (Zea mays). Untuk tahap pemisahan, hasil fermentasi tersebut di destilasi dengan alat destilasi sederhana pada suhu 78oC. Selanjutnya hasil destilasi diukur kadar etanol nya menggunakan Spektrofotometer UV-Vis pada panjang gelombang 580nm. Dengangan penambahan reagen jones pada larutan sampel tersebut. 2.1. Bahan kimia, peralatan dan instrumentasi Pada penelitian ini bahan kimia yang digunakan ialah, tongkol jagung, natrium hidroksida (NaOH) (Merck), HCl 0,5 M(Merck), ragi Saccharomyces cerevisiae, Aquadest, Na- Alginat (Merck), CaCl2 (Merck). Adapun alat yang digunakan pada penelitian ini terdiri dari: beaker glass, wadah fermentasi, hot plate, termometer, labu ukur, corong kaca, alat destilasi, Spektrofotometer UV-Vis. Untuk analisa data digunakan metode Rancangan Acak Lengkap (RAL) dua Faktorial, dengan uji anova dimana berfungsi untuk melihat pengaruh dari waktu fermentasi dan banyaknya ragi Saccharomyces cerevisiae terhadap kadar bioetanol yang dihasilkan. II. Metodologi Penelitian 2.1. Bahan kimia, peralatan dan instrumentasi III. Hasil dan Diskusi 2.2. Prosedur penelitian 2.2. Prosedur penelitian 3.1. Analisis hasil uji kadar bioetanol Proses produksi etanol dilakukan dengan kondisi fermenatasi pada suhu kamar dimana hasil fermentasi tersebut dipisahkan dengan cara destilasi12. Hasil destilasi sampel diuji kadar etanolnya menggunakan spektrofotometer UV-Vis pada panjang gelombang 580nm dengan metode kurva kalibrasi. Kurva kalibrasi digunakan untuk menentukan konsentrasi analit dalam sampel. Konsentrasi analit dapat ditentukan dari persamaan garis regresi linear yang diperoleh13. Dimana kadar bioetanol tersebut didapatkan dengan menentukan persamaan regresi linear larutan etanol standar dan blanko terlebih dahulu. Dimana persamaan regresi linear larutan standar dan etanol yaitu y= 0,018x + 0,137 dengan nilai R= 0,964. Tahap pertama Tongkol jagung dibersihkan di bawah air mengalir, lalu dikeringkan dibawah sinar matahari, tongkol jagung yang telah kering dihaluskan menggunakan blender hingga berukuran 40 mesh. Tahap kedua tongkol jagung yang telah halus di delignifikasi menggunakan NaOH 0,1 M dengan perbandingan sampel dan NaOH (1:10 )w/v dengan suhu delignifikasi 110oC selama 2 jam. Hasil delignifikasi dipisahkan dengan filtratnya dengan cara disaring, selanjutnya endapan dicuci dengan aquadest hingga pH endapan netral. serbuk yang telah dinetralkan dikeringkan menggunakan oven. Pada tahap ketiga serbuk yang telah kering dihidrolisis menggunakan HCl 0,5 M dengan perbandingan (1:10 )w/v pada suhu 110oC selama 2 jam. Selanjutnya serbuk dan filtrat dipisahkan dengan cara disaring, filtrat yang telah dipisahkan 64 IJCST.2022 © 2022 State University of Medan IJCST.2022 esian Journal of Chemical Science and Technology (IJCST-UNIMED) (2022) Volume 05, No 2, pp 63-66 dikarenakan semakin lama waktu fermentasi maka semakin banyak glukosa yang tereduksi menjadi alkohol terutama etanol tetapi terdapat batas maksimum aktivitas mikroba, namun pada fermentasi dengan waktu 14 hari terdapat penurunan kadar etanol dikarenakan pada fermentasi selama 14 hari sel khamir telah berada pada fase kematian. Gambar 1. Grafik Larutan Standar Etanol. Menurut Kurniawan, dkk (2014) Semakin banyak jumlah ragi roti yang ditambahkan, maka semakin banyak khamir, kapang, dan bakteri yang dihasilkan, sehingga produksi enzim amylase, zimase, dan invertase yang dihasilkan semakin meningkat. Produksi enzim yang tinggi menyebabkan proses sakarafikasi pati menjadi glukosa dan konversi glukosa menjadi alkohol semakin cepat. Dapat diketahui pada penelitian ini semakin banyak ragi yang digunakan, semakin tinggi kadar etanol yang dihasilkan. Gambar 1. Grafik Larutan Standar Etanol. Nilai kadar etanol didapatkan dengan memasukkan nilai ansorbansi yang didapatkan dari sampel ke persamaan regresi linear larutan standar etanol. Maka didapatkan nilai kadar etanol sampel yang dapat dilihyat pada tabel dibawah ini: Gambar 2. IV. Kesimpulan Adapun kesimpulan dari penelitian penentuan kadar etanol dari limbah tongkol jagung dengan melihat pengaruh dari variasi waktu fermentasi dan banyaknya Saccharomyces cerevisiae dengan metode fermentasi pada sel yang terimmobilisasi didapatkan kadar bioetanol tertinggi yaitu sebesar 39,5%. Berdasarkan uji anova dapat diketahui bahwa perlakuan variasi jumlah Saccharomyces cerevisiae dan lama waktu fermentasi berpengaruh secara nyata terhadap kadar bioetanol. 2.2. Prosedur penelitian Grafik Hubungan waktu fermentasi dan banyaknya sel Saccharomyces cerevisiae terimmobilisasi terhadap kadar etanol dari tongkol jagung. Tabel 1. Kadar etanol pada Sampel. Perlakuan Kadar Bioetanol Waktu Jumlah U-1 U-2 U-3 2 Hari 2 gram 5,61 5,28 5,78 5 gram 10,56 9,22 12,17 8 gram 13,39 13,28 13,78 5 Hari 2 gram 7,83 7,11 8,44 5 gram 11,61 10,5 12,61 8 gram 20,33 20,11 22,39 9 Hari 2 gram 13,22 12,39 14,5 5 gram 25 23,06 25,39 8 gram 38,44 38,39 39,5 14 Hari 2 gram 3 2 4,17 5 gram 4,56 3,11 4,67 8 gram 4,61 2,94 5,17 Gambar 2. Grafik Hubungan waktu fermentasi dan banyaknya sel Saccharomyces cerevisiae terimmobilisasi terhadap kadar etanol dari tongkol jagung. Dalam penelitian ini dilakukan dengan adanya dua variasi yaitu variasi jumlah Saccharomyces cerevisiae dan juga variasi waktu fermentasi bioetanol, berdasarkan nilai absorbansi yang didapatkan pada setiap sampel dapat diketahui bahwasannya kadar bioetanol terbesar adalah pada perlakuan jumlah Saccharomyces cerevisiae sebanyak 8 gram dan waktu fermentasi selama 9 hari. Hal ini menunjukkan bahwasanya kedua variasi tersebut mempunyai pengaruh terhadap kadar bioetanol yang didapatkan. Berdasarkan uji anova (analisis of varians) dapat diketahui bahwa perlakuan lebih kecil dari pada alfa (α=0,05) dimana menunjukkan hasil yang signifikan. Dapat diketahui bahwa perlakuan variasi jumlah Saccharomyces cerevisiae dan lama waktu fermentasi berpengaruh secara nyata terhadap kadar bioetanol, berdasarkan hal ini maka H0 ditolak dan H1 diterima. Semakin lama waktu fermentasi, maka kadar alkohol yang dihasilkan semakin tinggi. Hal ini 65 © 2022 State University of Medan IJCST.2022 IJCST.2022 Tabel 2. Uji ANOVA sampel bioetanol hasil Tabel 2. Uji ANOVA sampel bioetanol hasil fermentasi. 12. O. Tiska, Sofiyantia. (2019, Januari.) IJCST- UNIMED. 2(1), pp. 75-79. ANOVA Kadar_Bioetanol Sum of Squares f Mean Square F Sig. Between Groups 3612,224 1 328,384 333,433 ,000 Within Groups 23,637 4 ,985 Total 3635,860 5 13. E. Manik, Magdalena, Herlinawati. (2021, Januari.) IJCST-UNIMED. 4(1), pp. 11-14. ANOVA © 2022 State University of Medan 12. O. Tiska, Sofiyantia. (2019, Januari.) IJCST- UNIMED. 2(1), pp. 75-79. 13. E. Manik, Magdalena, Herlinawati. (2021, Januari.) IJCST-UNIMED. 4(1), pp. 11-14. Referensi 1. Erna, H,P. Abram. (2016, August.) J.Akad Kim. 5(3), pp. 121-126. 2. D. Dayatmo, H. H. S (2015, Oktober.) KONVERSI. 4(2), pp. 43-52. 3. Irhamni, Diana, Saudah, D. Mulyati, M. A. Suzzani, Erlinasari, (2017, November.) SEMDI-UNAYA. pp. 281-288. 4. F. Z. Khaira, E. Yenie, S.R. Muria, (2015, Oktober.) JOM FTEKNIK. 2(2), pp. 2-8. 5. Nurhasana, O, Zona. (2018, Juli.) IJCST- UNIMED. 1(1), pp. 17-22. 6. S. Erika. (2022, Feb.) IJCST-UNIMED. 5(1), pp. 1-3. 7. D.P. Amanda, Marlinda, Ramli, K. Andri. (2021, September.) Jurnal Teknik Kimia Vokasional. 1(2), pp. 45-50. 8. Fardiana, N. Ningsih, K. Mustapa. (2018, February.) J. Akademika Kim. 7(1), pp. 19- 22. 9. S. Gracella, M. Zainuddin. (2022, Feb.) IJCST-UNIMED. 5(1), pp. 28-30. 10. A. Sri. (2019, Juli.) Jurnal Teknik Patra Akademika. 10(1), pp. 13-20. 11. F. Ahmad, A. Puji, P. Tri. (2013, Januari.) Jurnal Teknik Kimia. 1(19), pp. 60-69. 66 IJCST.2022
https://openalex.org/W2128432722
https://breast-cancer-research.biomedcentral.com/counter/pdf/10.1186/bcr1203
English
null
Early detection of breast cancer based on gene-expression patterns in peripheral blood cells
Breast cancer research
2,005
cc-by
7,906
Received: 11 Apr 2005 Accepted: 28 Apr 2005 Published: 14 Jun 2005 Breast Cancer Research 2005, 7:R634-R644 (DOI 10.1186/bcr1203) This article is online at: http://breast-cancer-research.com/content/7/5/R634 , ( ) This article is online at: http://breast-cancer-research.com/content/7/5/R634 , ( ) This article is online at: http://breast-cancer-research.com/content/7/5/R634 p © 2005 Sharma et al.; licensee BioMed Central Ltd. ; This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/ 2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Introduction Existing methods to detect breast cancer in asymptomatic patients have limitations, and there is a need to develop more accurate and convenient methods. In this study, we investigated whether early detection of breast cancer is possible by analyzing gene-expression patterns in peripheral blood cells. Results We identified a set of 37 genes that correctly predicted the diagnostic class in at least 82% of the samples. The majority of these genes had a decreased expression in samples from breast cancer patients, and predominantly encoded proteins implicated in ribosome production and translation control. In contrast, the expression of some defense-related genes was increased in samples from breast cancer patients. Methods Using macroarrays and nearest-shrunken-centroid method, we analyzed the expression pattern of 1,368 genes in peripheral blood cells of 24 women with breast cancer and 32 women with no signs of this disease. The results were validated using a standard leave-one-out cross-validation approach. Conclusion The results show that a blood-based gene- expression test can be developed to detect breast cancer early in asymptomatic patients. Additional studies with a large sample size, from women both with and without the disease, are warranted to confirm or refute this finding. ANOVA = analysis of variance; EDTA = ethylenediaminetetraacetic acid; eEF = eukaryotic elongation factor; RACK1 = receptor for activated C kinase 1; SSC = standard saline citrate (1 × SSC, 0.15 M NaCl, 0.015 M sodium citrate, pH 7.0). Available online http://breast-cancer-research.com/content/7/5/R634 Available online http://breast-cancer-research.com/content/7/5/R634 Open Access Vol 7 No 5Research article Early detection of breast cancer based on gene-expression patterns in peripheral blood cells Praveen Sharma1, Narinder S Sahni1, Robert Tibshirani2, Per Skaane3, Petter Urdal4, Hege Berghagen1, Marianne Jensen1, Lena Kristiansen1, Cecilie Moen1, Pradeep Sharma1, Alia Zaka1, Jarle Arnes5, Torill Sauer6, Lars A Akslen5, Ellen Schlichting7, Anne-Lise Børresen-Dale8 and Anders Lönneborg1 Praveen Sharma1, Narinder S Sahni1, Robert Tibshirani2, Per Skaane3, Petter Urdal4, Hege Berghagen1, Marianne Jensen1, Lena Kristiansen1, Cecilie Moen1, Pradeep Sharma1, Alia Zaka1, Jarle Arnes5, Torill Sauer6, Lars A Akslen5, Ellen Schlichting7, Anne-Lise Børresen-Dale8 and Anders Lönneborg1 Corresponding author: Praveen Sharma, praveen.sharma@diagenic.com Received: 11 Apr 2005 Accepted: 28 Apr 2005 Published: 14 Jun 2005 Received: 11 Apr 2005 Accepted: 28 Apr 2005 Published: 14 Jun 2005 Preparation of cDNA arrays One thousand four hundred thirty-five cDNA clones were ran- domly picked from a plasmid library constructed from whole blood of 550 healthy individuals (Clontech, Palo Alto, CA, USA). Based on the sequence analysis of more than 500 cDNAs, redundancy among the randomly picked clones was estimated to be about 20%. For amplification of inserts, bac- terial clones were grown in microtiter plates containing 150 µl Luria Broth media with 50 µg/ml carbenicillin, and incubated overnight with agitation at 37°C. To lyse the cells, 5 µl of each culture was diluted with 50 µl dH2O and incubated for 12 min at 95°C. Of this mixture, 2 µl were subjected to a PCR reaction using 40 µmol of 5' – and 3' – sequencing primers in the pres- ence of 1.5 mM MgCl2. PCR reactions were performed with the following cycling protocol: 4 min at 95°C, followed by 25 cycles of 1 min at 94°C, 1 min at 60°C, and 3 min at 72°C either in a RoboCycler Temperature Cycler (Stratagene, La Jolla, CA, USA) or DNA Engine Dyad Peltier Thermal Cycler (MJ Research Inc, Waltham, MA, USA). The amplified prod- ucts were denatured with NaOH (0.2 M, final concentration) for 30 min and spotted onto Hybond-N+ membranes (Amer- sham Pharmacia Biotech, Little Chalfont, UK), using a Micro- Grid II workstation in accordance with the manufacturer's instructions (BioRobotics Ltd, Cambridge, UK). The immobi- lized cDNAs were fixed using a UV cross-linker (Hoefer Scien- tific Instruments, San Francisco, CA, USA). It has recently been suggested that circulating leukocytes can be viewed as scouts, continuously maintaining a vigilant and comprehensive surveillance of the body for signs of infection or other threats, including cancer [9]. In line with this view, we show that peripheral blood can be used to develop a gene- expression-based test for early detection of breast cancer. The rationale for using blood cells as monitors for a malignant dis- ease elsewhere in the body is based on the hypothesis that a malignant growth will cause characteristic changes in the bio- chemical environment of blood. These changes will affect the expression pattern of certain genes in blood cells. In this pilot study, we have analyzed gene-expression patterns in peripheral blood cells of women diagnosed with breast can- cer and women with no signs of this disease. We have identi- fied a panel of genes with distinct expression patterns in cancer versus noncancer samples. Breast Cancer Research Vol 7 No 5 Sharma et al. stored at -80°C, while PAX tubes were left overnight at room temperature and then stored at -80°C until use. A vast amount of literature is already available describing the potential use of large-scale gene expression analysis in dis- ease diagnosis, including breast cancer [2-8]. However, most published work with implications in cancer diagnosis has involved clinical samples comprising either diseased tissues or cells. Obtaining such samples for clinical purposes requires a prior knowledge of both their presence and their location in the body. A gene-expression-based test to detect cancers that does not rely upon the availability of tissues or cells from the diseased area has not yet been described. Introduction interpret. For example, in a study of over 11,000 women with no clinical symptoms of breast cancer, the sensitivity of mam- mography was only 48% for the subset of women with extremely dense breasts, compared with 78% sensitivity for the entire sample of women in the study [1]. In addition, when an abnormality has been detected, further tests involving inva- sive steps must complement mammography to establish whether the detected abnormality is a cancer. Early detection of breast cancer can improve the chances of successful treatment and recovery. To date, mammographic screening is the most reliable method to detect breast cancer in asymptomatic patients. Although highly effective, it has sig- nificant limitations, so that the development of more accurate, convenient, and objective detection methods is needed. In the absence of microcalcification, mammography often fails to detect tumors that are less than 5 mm in size, and also mam- mograms of women with dense breast tissue are difficult to R634 Breast Cancer Research Vol 7 No 5 Sharma et al. Preparation of cDNA arrays The results indicate that breast cancer causes characteristic changes in the biochemi- cal environment of blood already during early stages of dis- ease development. Blood cells sense and respond to the change by decreasing the expression of genes involved in pro- tein synthesis and increasing the expression of defense- related genes. We show that the expression pattern of the identified genes can be used to discriminate and predict the class of breast cancer and non-breast-cancer samples with high accuracy. Our findings should pave way for the develop- ment of a blood-based gene-expression test for early detec- tion of breast cancer. The printed arrays also contained controls for assessing back- ground level, consistency, and sensitivity of the assay. These were spotted at multiple positions in addition to the 1,435 cDNAs, and included controls such as PCR mix (without any insert); controls of the SpotReport™ 10-array validation sys- tem (Stratagene), and cDNAs corresponding to constitutively expressed genes such as β-actin, γ-actin, glyceraldehyde-3- phosphate dehydrogenase, human ornithine decarboxylase and cyclophilin. Available online http://breast-cancer-research.com/content/7/5/R634 As a result, for each value of the threshold, the esti- mate of cross-validation error obtained is approximately unbi- ased for the true test-error rate. The leave-one-out cross-validation approach was used in this work. The data were divided into M nonoverlapping subsets (M = number of unique blood samples present). The model was then trained M-1 times on these subsets combined, each time leaving out one of the subsets (unique blood sample) from the training data, but using only the omitted subset to compute the prediction error. The errors obtained on all parts were added together and used to compute the overall misclas- sification error. It is well known that leave-one-out cross-valida- tion provides an approximately unbiased and reliable estimate of the misclassification rate that would be obtained from an independent sample of patients [11,12]. In the terminology of Ambroise and McLachlan [12], we used external cross-valida- tion (as they recommend). The membranes were equilibrated in 4 × standard saline cit- rate (SSC) (1 × SSC, 0.15 M NaCl, 0.015 M sodium citrate, pH 7.0) for 2 hours at 30°C and prehybridized overnight at 65°C in 10 ml prehybridization solution (4 × SSC, 0.1 M NaH2PO4, 1 mM EDTA, 8% dextran sulfate, 10 × Denhardt's solution, 1% SDS). Freshly prepared probes were added to 5 ml of the same prehybridization solution, and hybridization con- tinued overnight at 65°C. The membranes were washed at 65°C with increasing stringency (2 × 30 min each in 2 × SSC, 0.1% SDS; 1 × SSC, 0.1% SDS; 0.1 × SSC, 0.1% SDS). The raw and the batch-adjusted data for 1,368 genes in an Excel file is provided in Supplementary Table 1 (Additional file 2) and Supplementary Table 2 (Additional file 3). Results W l The hybridized membranes were exposed to Phosphoscreens (super resolution) and an image file generated using Phos- phoImager (Cyclone, Packard, Meriden, CT, USA). The identi- fication and quantification of the hybridization signals, as well as subtraction of local background values, were performed using Phoretix™ software (Nonlinear Dynamics, Newcastle upon Tyne, UK). For background subtraction, the median of the line of pixels around each spot outline was subtracted from the intensity of the signals assessed in each spot. We analyzed gene-expression patterns in 60 blood samples obtained from 56 different women (Table 1). The experiments were performed in 16 batches. To investigate the reproducibil- ity of results, 13 samples from women with breast cancer and 23 samples from women with no breast cancer were analyzed in different batches using aliquots from the same mRNA pool, giving a total of 102 experimental samples. The generated expression data was preprocessed and then analyzed by the nearest-shrunken-centroid method [10]. A standard leave-one-out cross-validation approach was used to determine the optimal amount of shrinkage threshold. Since we had 60 unique blood samples and for some of them exper- iments were replicated more than once, for cross-validation Available online http://breast-cancer-research.com/content/7/5/R634 Available online http://breast-cancer-research.com/content/7/5/R634 RNA were determined by measuring the absorbance at 260 nm and 280 nm. From the total RNA, mRNA was isolated using Dynabeads in accordance with the supplier's instruc- tions (Dynal AS, Oslo, Norway). 67 cDNAs in total were removed from all membranes, and the expression data for only 1,368 genes were further analyzed. The data were normalized by dividing the value of each spot by the mean of signals in each array followed by a cube-root transformation. Supplementary Fig. 1 (left panel) (Additional file 1) shows a clear batch effect in the cube-root-normalized data (similar effects were also visible in the raw data). A simple one-way analysis of variance (ANOVA) was performed to adjust for the batch effects. Supplementary Fig. 1 (right panel) (Additional file 1) shows that the systematic batch effects were removed by the ANOVA adjustment. The batch-adjusted data were then analyzed using the nearest-shrunken-centroid method [10]. Labeling and hybridization experiments were performed in 16 batches. The number of samples assayed in each batch varied from six to nine. To minimize the noise due to batch-to-batch variation in printing, only the arrays manufactured during the same print run were used in each batch. When samples were assayed more than once (replicates), aliquots from the same mRNA pool were used for probe synthesis. For probe synthe- sis, aliquots of mRNA corresponding to 4 to 5 µg of total RNA were mixed together with oligodT25NV (0.5 µg/µl) and mRNA spikes of the SpotReport™ 10-array validation system (10 pg; Spike 2, 1 pg), heated to 70°C, and then chilled on ice. The probes were synthesized by reverse transcription in 35 µl reaction mix in the presence of 50 µCi [α33P]dATP, 3.5 µM dATP, 0.6 mM each of dCTP, dTTP, dGTP, 200 units of SuperScript II reverse transcriptase (Invitrogen, Life Technolo- gies, Carlsbad, CA, USA), and 0.1 M DTT labeling for 1.5 hours at 42°C. After synthesis, the enzyme was deactivated for 10 min at 70°C and mRNA removed by incubating the reaction mix for 20 min at 37°C in 4 units of Ribo H (Promega, Madison, WI, USA). Unincorporated nucleotides were removed using ProbeQuant G 50 columns (Amersham Biosciences, Piscata- way, NJ, USA). In this method, standard 'external' cross-validation is used to determine the optimal shrinkage threshold. This optimal threshold is then used with the full training set to construct the centroid. Materials and methods Blood samples RNA extraction, probe synthesis, and hybridization Blood collected in EDTA tubes was thawed at 37°C and trans- ferred to PAX tubes, and total RNA was purified in accordance with the supplier's instructions (PreAnalytiX). From blood col- lected directly in PAX tubes, total RNA was extracted in the tubes as above without any transfer to new tubes. Contaminat- ing DNA was removed from the isolated RNA by DNAase I treatment using a DNA-free kit (Ambion Inc, Austin, TX, USA). RNA quality was determined visually by inspecting the integrity of 28S and 18S ribosomal bands after agarose-gel electro- phoresis. Only samples from which good-quality RNA was extracted were used in this study. In our experience, blood col- lected in EDTA tubes often resulted in poor-quality RNA, whereas blood collected in PAX tubes almost always yielded good-quality RNA. The concentration and purity of extracted Blood samples were collected from donors with their informed consent under an approval from Regional Ethical Committee of Norway (331-99-99138). All donors were treated anony- mously during analysis. Blood was drawn from women with a suspect initial mammogram, prior to any knowledge of whether the abnormality observed during first screening was benign or malignant. In all cases, the blood samples were drawn between 8 a.m. and 4 p.m. From each woman, 10 ml blood was drawn by skilled personnel either in vacutainer tubes con- taining ethylenediaminetetraacetic acid (EDTA) as anticoagu- lant (Becton Dickinson, Baltimore, MD, USA) or directly in PAXgene™ tubes (PreAnalytiX, Hombrechtikon, Switzerland). Blood collected in EDTA-containing tubes was immediately R635 Figure 1 Figure 1 Misclassification rate as a function of threshold value and the number of genes involved Misclassification rate as a function of threshold value and the number of genes involved. The error was calculated using the majority rule. A nondeci- sion was counted as an error. The upper graph shows that the minimum overall misclassification error was observed at a threshold value of 2.28. The lower graph shows the profile for misclassification error for breast-cancer (C) and non-breast-cancer (N) samples as a function of threshold value and the number of genes involved. Misclassification rate as a function of threshold value and the number of genes involved Misclassification rate as a function of threshold value and the number of genes involved. The error was calculated using the majority rule. A nondeci- sion was counted as an error. The upper graph shows that the minimum overall misclassification error was observed at a threshold value of 2.28. The lower graph shows the profile for misclassification error for breast-cancer (C) and non-breast-cancer (N) samples as a function of threshold value and the number of genes involved. the data were divided into 60 nonoverlapping subsets, where each subset represented a unique blood sample and included all the replicates present in the data set. A sample was judged as correctly classified only when a majority of members in the corresponding cross-validation segment were correctly classi- fied. The minimum overall misclassification error was observed at a threshold value of 2.28, yielding a subset of 37 genes (Fig. 1). At this threshold, 10 of the 57 samples were misclassified and 3 samples were judged nondecisions, because there was no majority for either the breast-cancer or non-breast-cancer class (Table 2). A detailed prediction result is presented in Table 1. group was obtained from a woman who had invasive lobular carcinoma in one breast and a tubular adenocarcinoma in the other. Unlike ductal carcinoma, which originates from cells lin- ing ducts, lobular carcinoma originates from cells lining lob- ules. Both samples were incorrectly predicted. It is possible that cancer of other than ductal origin affects the expression pattern of the selected 37 genes in blood cells differently than ductal carcinomas. Data analysis From the background-subtracted data for 1,435 genes, 1.25% of the lowest and 1.25% of the highest signals were trimmed from each membrane. Since the cDNAs with signals falling within this range varied between membranes, values of R636 Breast Cancer Research Vol 7 No 5 Sharma et al. Figure 1 Seventeen of 19 samples obtained from women with a sus- pect first mammogram were correctly predicted (Table 1, sub- group A2), indicating the expression profile of the selected 37 genes to be highly efficient in discriminating between cancer- ous and noncancerous breast abnormalities. In two samples, we were not able to make any diagnostic decision. The prediction was highly accurate for samples from women with early stages of breast cancer, stage 0 and stage I. Among the 14 samples representing early stages, there was one non- decision and 11 of 13 samples were correctly predicted. Five of seven stage II and one of two stage III samples were cor- rectly predicted. Among the 17 samples from women with no reported breast abnormality, 13 were correctly predicted (Table 1, subgroup A3). These included samples from breast-feeding women as well as those drawn at different times in the menstrual cycle from one woman. However, the three samples from pregnant women and a sample from a woman with acute bacterial infec- tion at the time of blood collection were all incorrectly pre- dicted. The woman with acute bacterial infection was, in addition, chronically infected with Epstein–Barr virus. It is known that both pregnancy and chronic infection may elicit Most of the cancer samples (22 of 24) analyzed in this study were obtained from women who had cancer of ductal origin. One woman, the origin of whose cancer was not known, had a previous history of breast cancer and at the time of blood col- lection the cancer had spread to supraclavicular and infracla- vicular nodes. Figure 1 Another sample that did not belong to the ductal R637 R637 Available online http://breast-cancer-research.com/content/7/5/R634 Table 1 Gene-expression patterns in 60 blood samples obtained from 56 different women Subgroup A1: Women with breast cancer Sample ID Age (y) Stage Histology Grade Size (mm) Nodes Comments/ other disease if present Times assayed Prediction (37 genes) 3 54 I IDC 1 11 0 # 2 + 5 67 0 DCIS 2 20 0 # 3 + 7 51 II IDC 3 20 1/7 # 2 + 8 84 II IDC 1 22 2/2 # 2 + 15 66 I IDC 2 15 0 Rheumatic disease 3 + 16 68 I IDC 1 7 0 # 1 + 17 66 II IDC 1 26 0 Epilepsy 1 - 27 48 I IDC 2 4 0 # 2 ND 31 47 I IDC 2 15 0 # 2 - 35 44 II IDC 2 25 0 # 1 + 36 50 I Multifocal IDC 1 5 × 14 0 # 1 - 38 n.a. 0 DCIS 2 9 0 # 1 + 39 65 I IDC 1 15 0 # 1 + 40 n.a. I IDC 2 14 0 Psoriasis 1 + 42 71 I IDC 1 8 0 # 1 + 44 55 III IDC 1 35 0 # 1 + 45 63 II IDC 3 23 0 # 1 - 48 65 IV - - - Metastases in supra- and infra- clavicular nodes Breast cancer, 1982 1 - 49 65 I IDC 1 11 0 Type 2 diabetes 3 + 50 69 III ILC 2 50 2/19 # 2 - 51 50 II IDC 2 24 0 # 2 + 53 60 II IDC 2 23 0 # 2 + 59 63 I IDC 1 10 0 # 2 + 60 52 I IDC 1 3 0 # 2 + Subgroup A2: Women with abnormal first mammography Sample ID Age (y) Breast abnormality Comments / other disease if present Times assayed Prediction (37 genes) 1 44 Benign density # 2 + 2 53 Benign microcalcifications Encapsulated cyst in left knee 2 + 4 45 Benign density # 2 + 11 46 Benign density Ulcerative colitis since 1983 2 + 12 44 Benign density # 2 + 13 50 Benign density Type 1 diabetes 2 + 14 47 Benign microcalcifications # 2 + 19 46 Benign density, cyst Crohn's disease 2 + 20 n.a. Figure 1 Benign density Rheumatic disease 1 + 28 44 Benign microcalcifications # 2 + 29 63 Benign density, cyst Fibromyalgia 2 ND 30 46 Benign density # 2 + Gene-expression patterns in 60 blood samples obtained from 56 different women Breast Cancer Research Vol 7 No 5 Sharma et al. Breast Cancer Research Vol 7 No 5 Sharma et al. Table 1 (Continued) Gene-expression patterns in 60 blood samples obtained from 56 different women 32 59 Benign tumor, fibroadenoma # 2 + 34 45 Benign density Type 2 diabetes 2 + 41 50 Fibrosis, benign Size histology 60 mm 1 + 43 51 Radial scar Size histology 10 mm 1 + 52 47 Benign density # 2 ND 54 52 Benign microcalcifications Cancer, large intestine, 1992 1 + 58 46 Benign density # 2 + Subgroup A3: Women with no reported breast abnormality Sample ID Age (y) Comments Times assayed Prediction (37 genes) 6 42 # 3 + 9 30 Breast feeding 2 + 10 34 Breast feeding 3 + 21 26 # 1 + 22 - # 1 + 18* 18 Week 1 2 + 23* Week 2 1 + 24* Week 3 1 + 26* Week 4 2 + 25* Week 5 1 + 33 34 Pregnant, 8 months 3 - 37 51 Acute bacterial infection in addition to chronic Epstein–Barr virus infection 1 - 46 27 Pregnant, 6 months 1 - 47 29 Pregnant, 9 months 1 - 55 43 # 1 + 56 43 # 2 + 57 22 # 2 + Sample detail. Stage 0, in situ carcinoma; Stage I, invasive carcinoma with tumor size <20 mm; Stage II, invasive carcinoma with tumor size >20-50 mm; Stage III, invasive carcinoma with tumor size >50 mm. Stage IV, cancer spread to distant parts. *, Blood samples taken on five consecutive weeks from the same woman; -, incorrectly predicted; #, no relevant information available; +, correctly predicted; DCIS, ductal carcinoma in situ; IDC, invasive ductal carcinoma; ILC, invasive lobular carcinoma; n.a., not available; ND, nondecision. Gene-expression patterns in 60 blood samples obtained from 56 different women Sample detail. Stage 0, in situ carcinoma; Stage I, invasive carcinoma with tumor size <20 mm; Stage II, invasive carcinoma with tumor size >20-50 mm; Stage III, invasive carcinoma with tumor size >50 mm. Stage IV, cancer spread to distant parts. Figure 2 Relative expression of 13 predictive genes with the highest scores in breast-cancer and non-breast-cancer samples Relative expression of 13 predictive genes with the highest scores in breast-cancer and non-breast-cancer samples. Red circles represent samples from women with breast cancer and green circles represent samples from women with no signs of breast cancer. The number on the upper axis rep- resents the position ID of predictive genes in the array (Table 3). Relative expression of 13 predictive genes with the highest scores in breast-cancer and non-breast-cancer samples Relative expression of 13 predictive genes with the highest scores in breast-cancer and non-breast-cancer samples. Red circles represent samples from women with breast cancer and green circles represent samples from women with no signs of breast cancer. The number on the upper axis rep- resents the position ID of predictive genes in the array (Table 3). Sequence analysis revealed that 8 of 35 predictive genes con- tained redundant information. Since the arrayed cDNAs were derived from randomly picked clones from a library con- structed from whole blood from 550 healthy individuals, we had expected a redundancy of about 20% among the selected genes. Of the 35 genes, 18 (51%) encoded ribosomal pro- teins. In comparison, the frequency of cDNAs representing ribosomal proteins was estimated to be only about 8% among the arrayed cDNAs. All genes encoding ribosomal proteins had reduced expression in samples from breast cancer patients, indicating a decrease in ribosome production in the blood cells of these patients. Also, genes encoding a transla- tion elongation factor, eEF1 and RACK1 (receptor for Sequence analysis revealed that 8 of 35 predictive genes con- tained redundant information. Since the arrayed cDNAs were derived from randomly picked clones from a library con- structed from whole blood from 550 healthy individuals, we had expected a redundancy of about 20% among the selected genes. Of the 35 genes, 18 (51%) encoded ribosomal pro- teins. In comparison, the frequency of cDNAs representing ribosomal proteins was estimated to be only about 8% among the arrayed cDNAs. All genes encoding ribosomal proteins had reduced expression in samples from breast cancer patients, indicating a decrease in ribosome production in the blood cells of these patients. Table 2 Table 2 aWhen there was no majority for either the breast-cancer or non-breast-cancer class, the prediction was regarded as a nondecision. bTotal error rate = 0.18; 3 nondecisions. C, breast-cancer samples; N, non-breast-cancer samples. aWhen there was no majority for either the breast-cancer or non-breast-cancer class, the prediction was regarded as a nondecision. bTotal error rate = 0.18; 3 nondecisions. C, breast-cancer samples; N, non-breast-cancer samples. Figure 1 *, Blood samples taken on five consecutive weeks from the same woman; -, incorrectly predicted; #, no relevant information available; +, correctly predicted; DCIS, ductal carcinoma in situ; IDC, invasive ductal carcinoma; ILC, invasive lobular carcinoma; n.a., not available; ND, nondecision. responses that can mimic breast cancer. During late preg- nancy, similar to breast cancer, cells of mammary epithelial buds divide to form ducts infiltrating breast stroma and build a local blood supply. Also, both breast cancer and chronic infec- tions are known to induce inflammatory responses in the body. responses that can mimic breast cancer. During late preg- nancy, similar to breast cancer, cells of mammary epithelial buds divide to form ducts infiltrating breast stroma and build a local blood supply. Also, both breast cancer and chronic infec- tions are known to induce inflammatory responses in the body. sented an average class probability for each sample, and we predicted each sample to the class with the highest average probability. The main purpose of adopting this approach was to be able to make a unanimous decision with respect to class membership. The minimum error rate using the average-class approach was obtained at a threshold value of 2.42 and involved a subset of only 25 genes, giving a further reduction of 12 genes (Supplementary Fig. 2) (Additional file 4). Also, 10 (7 breast cancer and 3 non-breast-cancer samples) of the 60 samples were misclassified, which is a slightly better result than that obtained with 37 genes, where there were 3 nonde- cisions (Supplementary Fig. 3) (Additional file 5). We also calculated the misclassification error, taking an aver- age of the class probability for each sample in all 60 cross-val- idation segments as compared with our previous approach in which a sample was judged as correctly classified only when a majority of members in the corresponding cross-validation segment were correctly classified. Thus, each segment repre- R639 R639 Available online http://breast-cancer-research.com/content/7/5/R634 Available online http://breast-cancer-research.com/content/7/5/R634 Table 2 Confusion matrix of prediction results using 37 genesa True/Predicted C N Error rateb C 17 6 0.26 N 4 30 0.12 aWhen there was no majority for either the breast-cancer or non-breast-cancer class, the prediction was regarded as a nondecision. bTotal error rate = 0.18; 3 nondecisions. C, breast-cancer samples; N, non-breast-cancer samples. Figure 1 Table 2 Confusion matrix of prediction results using 37 genesa True/Predicted C N Error rateb C 17 6 0.26 N 4 30 0.12 aWhen there was no majority for either the breast-cancer or non-breast-cancer class, the prediction was regarded as a nondecision. bTotal error rate = 0.18; 3 nondecisions. C, breast-cancer samples; N, non-breast-cancer samples. Figure 2 Also, genes encoding a transla- tion elongation factor, eEF1 and RACK1 (receptor for Table 3 shows the shrunken t-statistic scores of the selected 37 predictive genes for comparing breast-cancer class to non- breast-cancer class, the genes in the public databases to which they show sequence similarity, and their putative biolog- ical function. The relative expression of 12 predictive genes with highest scores is presented in Fig. 2. The majority of the predictive genes (29 of 37) had a decreased expression (pos- itive score) in the samples from breast cancer patients. The identity of predictive genes was determined by partially sequencing the corresponding spotted cDNA clones and searching for gene similarities in public databases. R640 Breast Cancer Research Vol 7 No 5 Sharma et al. Breast Cancer Research Vol 7 No 5 Sharma et al. Table 3 Table 3 Table 3 Details of the identified 37 predictive genes Accession no. Table 3 Gene similarity Putative cellular function Position ID Scorea BC000514 Ribosomal protein L13a Ribosome production 19AM 0.8377 BC007512 Ribosomal protein L18a Ribosome production 31AJ 0.7321 BC019093 Guanine nucleotide binding protein, beta polypeptide 2-like; RACKs (receptors for activated C kinase) Protein translation 12AM 0.6972 BC009696 Interferon induced transmembrane protein 2 Cell – environment interaction, Immune response 12Q -0.6962 BC047681 S100 calcium binding protein A9 (Calgranulin B) Defence; inhibition of casein kinase II 31J -0.6444 BC066901 H3 histone, family 3B (H3.3B) Chromatin remodelling 5AK -0.6394 BC034149 Ribosomal protein S3 Ribosome production 23V 0.639 AK026634 Highly similar to HUMTI227HC, mRNA for TI-227H - 21AH 0.627 BC047681 S100 calcium binding protein A9 (Calgranulin B) Defence; inhibition of casein kinase II 24AQ -0.627 BC001126 Ribosomal protein S14 Ribosome production 28T 0.6231 NM_000980 Ribosomal protein L18a Ribosome production 31AF 0.6215 AY495316 Cytochrome c oxidase subunit, COX 1 Mitochondrial electron transport chain 15AK 0.6112 NM_001016 Ribosomal protein S12 Ribosome production 22S 0.6102 - - - 20AG 0.5839 BC016378 Ribosomal protein S11 Ribosome production 8S 0.5827 AY495316 Cytochrome c oxidase subunit, COX 1 Mitochondrial electron transport chain 27AG 0.5729 AF077043 Ribosomal protein L36 Ribosome production 3AR 0.5699 AF346981 Mitochondrial 16S rRNA Ribosome production 25P 0.5507 BC013857 H3 histone, family 3A Chromatin remodelling 3T -0.5496 M22146 Ribosomal protein S4 Ribosome production 31U 0.5176 BC016857 Ferritin, heavy polypeptide 1 Iron storage; defence against ROS 6N -0.5134 BC053370 Ribosomal protein SA Ribosome production 2G 0.5113 BC010165 Ribosomal protein S2 Ribosome production 2V 0.5071 BC009689 Cyclin D-type binding protein E2F-mediated transcription 21O 0.4978 BC018641 Eukaryotic translation elongation factor 1α (eEF1A) Protein translation 4AA 0.4974 D87735 Ribosomal protein L14 Ribosome production 19H 0.486 - - - 6AQ 0.4837 BC016857 Ferritin, heavy polypeptide 1 Iron storage; defence against ROS 3AB -0.481 BC012146 Ribosomal protein L3 Ribosome production 32AM 0.4776 Details of the identified 37 predictive genes R641 Available online http://breast-cancer-research.com/content/7/5/R634 Available online http://breast-cancer-research.com/content/7/5/R634 BC001126 Ribosomal protein S14 Ribosome production 25R 0.4759 BC006784 Ribosomal protein S14 Ribosome production 24AJ 0.4695 J03223 Human secretory granule proteoglycan peptide core Defence (may neutralize hydrolytic enzymes) 11H -0.4681 AY147037 Myeloid/lymphoid or mixed-lineage leukemia 5 cDNA Chromatin remodeling and cellular growth suppression 30AP 0.4669 CD246392, EST Agencourt_14095501 NIH_MGC_172 cDNA - 8AK 0.4666 AY339570 Cytochrome c oxidase subunit, COX 1 Mitochondrial electron transport chain 2E 0.4662 U43701 Human ribosomal protein L23a Ribosome production 8G 0.4629 AY495252 Mitochondrial 16S rRNA Ribosome production 8AF 0.4625 The position of genes in the array is shown as well as their scores, the accession number of sequences in public databases that match them, and their known or putative cellular function. Table 3 aThe score is a shrunken t-statistic for comparing breast-cancer class to non-breast-cancer class. A positive score means that expression was greater in the noncancer sample than the cancer sample; a negative score means that expression was greater in the cancer sample than the noncancer sample. -, no information available; ROS, reactive oxygen species. Table 3 (Continued) Details of the identified 37 predictive genes Table 3 (Continued) Table 3 (Continued) Details of the identified 37 predictive genes The position of genes in the array is shown as well as their scores, the accession number of sequences in public databases that match them, and their known or putative cellular function. aThe score is a shrunken t-statistic for comparing breast-cancer class to non-breast-cancer class. A positive score means that expression was greater in the noncancer sample than the cancer sample; a negative score means that expression was greater in the cancer sample than the noncancer sample. -, no information available; ROS, reactive oxygen species. results clearly show that by analyzing the expression pattern of selected genes in blood cells, a diagnostic test for breast can- cer detection can be efficiently developed. results clearly show that by analyzing the expression pattern of selected genes in blood cells, a diagnostic test for breast can- cer detection can be efficiently developed. activated C kinase), were expressed at a lower level in sam- ples from cancer patients, indicating reduced protein transla- tion activity in these samples. RACK1 plays a key role in the joining of 60S and 40S subunits into a functionally active 80S ribosome complex [13]. In the present study, we examined gene-expression patterns in peripheral blood cells as a whole, rather than specific cellular subsets. It has recently been shown that individual variations in gene-expression pattern in peripheral blood could be traced to altered relative proportions of the specific blood cell sub- sets [9]. If there were systematic differences in the relative pro- portions of peripheral blood cell types in women with breast cancer and those without this disease, such differences might explain the observed gene-expression patterns. Interestingly, Whitney and colleagues [9] found that transcripts involved in protein synthesis were over-represented in lymphocytes and monocytes as compared with granulocytes. Table 3 The reduced expression of transcripts involved in protein synthesis and the increased expression of transcripts involved in defense responses in breast cancer patients may reflect a systematic shift in favor of granulocytes as compared with lymphoid cells in the peripheral blood of breast cancer patients. However, to our knowledge, no such systematic shift during breast cancer development has been reported, and the subject requires fur- ther investigation. Alternatively, changes in the expression pat- tern of genes involved in protein synthesis, chromatin remodelling, and defense-related genes in the blood samples of breast cancer patients may indicate systematic activation of certain blood cell subsets such as neutrophils in these patients. Among the eight predictive genes with increased expression in samples from breast cancer patients, two encoded histone replacement protein H3.3, which is thought to be involved in chromatin remodelling [14], and six encoded proteins that may play a role in defense-related functions. Four genes with increased expression encoded ferritin and calgranulin B. Ferri- tin is involved in intracellular storage and sequestration of iron. Increased expression of ferritin has been shown to reduce the accumulation of reactive oxygen species in response to oxi- dant challenge in HeLa cells [15]. Calgranulin B is expressed by blood cells both during infection and during inflammation and may play a role in host defense [16]. Interferon-induced transmembrane protein 2 has been implicated in the immune response, while human granule proteoglycan peptide core is assumed to form stable complexes with proteases and other granule-localized proteins to prevent their intragranular autoly- sis and facilitate their concerted action extracellularly [17]. Interestingly, most predictive genes identified in this study belonged to the family of genes that exhibited altered expres- sion in neutrophils after stimulation by nonvirulent and virulent bacterial stimuli [18,19]. Conclusion Th l The results presented show that breast cancer even during early stages of disease development affects the expression pattern of certain genes in peripheral blood cells. By identify- ing these genes and analyzing their expression pattern, it is possible to develop a blood-based gene-expression test for early detection of breast cancer. Additional studies with a large sample size, both from women with and without the dis- ease, are warranted to confirm or refute this finding. The efficient prediction of samples derived from patients whose cancer had not yet spread to lymph nodes shows that a blood-based gene-expression test can be developed for breast cancer detection in asymptomatic patients. As com- pared with existing methods, an accurate method for breast cancer detection based on peripheral blood as a clinical sam- ple will be highly desirable because of the easy accessibility and the less invasive procedure for obtaining samples. The test could be integrated as an adjunct to already established methods and be used to improve their efficacy. For example, a blood-based gene-expression test could assist mammography in discriminating between benign and malignant breast abnor- malities. It could become a part of routine screening programs, especially when the patient has an increased risk for breast cancer. Competing interests PvS, NSS, HB, MJ, LK, CM, PdS, AZ, and AL are employees of DiaGenic. None of the other authors have any competing interests. Authors' contributions PvS and AL conceived the experiments. PvS, AL, and NSS designed the experiments. HB, MJ, CM, AZ, LK, PdS, PvS, and AL performed the experiments. PSk, PU, ES, TS, JA, and LAA provided the samples and their clinical details. RT and NSS performed the statistical analysis. PvS wrote the paper. RT, ALBD, AL, NSS, and PSk provided helpful comments during preparation of the manuscript. All authors read and approved the final manuscript. It is important that any test intended for use in breast cancer diagnosis has a low rate of both false positives and false neg- atives. Based on the expression pattern of identified 37 genes, the prediction achieved corresponded to a false positive rate of 0.12 and false negative rate of 0.26. Since, the main goal of this work was to see whether the information about breast can- cer is present in peripheral blood samples in the form of changed gene-expression patterns, we analyzed only a limited number of gene candidates in this study. The genes analyzed corresponded to clones that were randomly picked from a plasmid library constructed from whole blood of 550 individu- als. The motivation for this approach for selecting gene candi- dates was based on the assumption that if the expression pattern of certain genes in blood cells is affected during early stages of breast cancer, the genes affected would most likely include ones involved in cell maintenance and general metab- olism. Since such genes are expressed at high level in a cell, they would be frequently represented in a cDNA library and selected preferentially when randomly picked. It is our view that expression techniques such as microarrays, where the expression of thousands of genes can be monitored simulta- neously, can further be used to screen for better predictive genes and develop more accurate diagnostic models. Additional File 2 Supplementary Table 1, an Excel file showing the raw data for 1,368 genes. C, breast-cancer class; N, non- breast-cancer class. See http://www.biomedcentral.com/content/ supplementary/bcr1203-S2.xls Breast Cancer Research Vol 7 No 5 Sharma et al. changes in the biochemical environment of blood and affect the gene-expression patterns in blood cells. Specific gene- expression-based models can then be developed and used for diagnostic purposes. that malignant lesions, though confined within the breast duct, may induce similar changes in the expression pattern of these genes to the changes seen during the more advanced stages of breast cancer (stages I to III). However, incorrect prediction of a sample obtained from a woman with invasive lobular car- cinoma and tubular adenocarcinoma and from a woman where the cancer had spread to supraclavicular and infraclavicular nodes indicates that malignancy in itself is not a prerequisite condition for the observed changes in the expression pattern of the identified predictive genes. The following Additional files are available online: The following Additional files are available online: The following Additional files are available online: Additional File 1 Supplementary Figure 1, a pdf showing batch adjustment. (Left) Normalized data before batch adjustment; (right) normalized data after batch adjustment by ANOVA. See http://www.biomedcentral.com/content/ supplementary/bcr1203-S1.pdf Discussion This is a first report demonstrating that breast cancer affects gene-expression patterns in peripheral blood cells during early stages of disease development. The results presented repre- sent an initial phase in the development of a blood-based gene-expression test for breast cancer detection. A larger number of samples, from both women with and women without the disease, should be further analyzed before the clin- ical efficacy of our finding can be evaluated. However, the Our ability to correctly assign the class of samples from women with Crohn's disease, rheumatic disease, or diabetes as non-breast-cancer suggests that breast cancer affects the expression pattern of identified predictive genes differently from some of the diseases associated with anemia and chronic inflammation. The correct prediction of two samples from a woman with ductal carcinoma in situ further suggested R642 Breast Cancer Research Vol 7 No 5 Sharma et al. Additional files The following Additional files are available online: Additional File 1 Supplementary Figure 1, a pdf showing batch adjustment. (Left) Normalized data before batch adjustment; (right) normalized data after batch adjustment by ANOVA. See http://www.biomedcentral.com/content/ supplementary/bcr1203-S1.pdf Additional File 2 Supplementary Table 1, an Excel file showing the raw data for 1,368 genes. C, breast-cancer class; N, non- breast-cancer class. See http://www.biomedcentral.com/content/ supplementary/bcr1203-S2.xls Additional File 3 Supplementary Table 2, an Excel file showing the batch- corrected data for 1,368 genes. C, breast-cancer class; N, non-breast-cancer class. See http://www.biomedcentral.com/content/ supplementary/bcr1203-S3.xls Additional File 5 Supplementary Figure 3, a pdf showing estimated cross- validated probabilities of 60 different blood samples. Red circles represent breast-cancer class (C) and green circles represent non-breast-cancer class (N). Each sample has two probabilities, one for the breast-cancer class and the other for the non-breast-cancer class. The sample is classified in the class whose probability is >0.5. 15. Orino K, Lehman L, Tsuji Y, Ayaki H, Torti SV, Torti FM: Ferritin and the response to oxidative stress. Biochem J 2001, 357:241-247. 16. Nisapakultorn K, Ross KF, Herzberg MC: Calprotectin expres- sion inhibits bacterial binding to mucosal epithelial cells. Infect Immun 2001, 69:3692-3696. 17. Nicodemus CF, Avraham S, Austen KF, Purdy S, Jablonski J, Ste- vens RL: Characterization of the human gene that encodes the peptide core of secretory granule proteoglycans in promyelo- cytic leukemia HL-60 cells and analysis of translated product. J Biol Chem 1990, 265:5889-5896. See http://www.biomedcentral.com/content/ supplementary/bcr1203-S5.pdf See http://www.biomedcentral.com/content/ supplementary/bcr1203-S5.pdf See http://www.biomedcentral.com/content/ supplementary/bcr1203-S5.pdf , 18. Zhang X, Kluger Y, Nakayama Y, Poddar R, Whitney C, DeTora A, Weismann SM, Newburger PE: Gene expression in mature neu- trophils: early responses to inflammatory stimuli. J Leukoc Biol 2004, 75:358-372. 19. Subrahmanyam YV, Yamga S, Prashar Y, Lee HH, Hoe NT, Kluger Y, Gerstein M, Goguen JD, Newburger PE, Weismann SM: RNA expression patterns change dramatically in human neu- trophils exposed to bacteria. Blood 2001, 97:2457-2468. Additional File 4 Supplementary Figure 2, pdf showing misclassification rate as a function of threshold value and the number of genes involved when the error is calculated by taking an average of the class probability for each sample in all 60 cross-validation segments. The upper graph shows that the minimum overall misclassification error is observed at a threshold value of 2.42. The lower graph shows the profile for the misclassification error for breast-cancer (C) and non-breast-cancer (N) samples as a function of threshold value and the number of genes involved. See http://www.biomedcentral.com/content/ supplementary/bcr1203-S4.pdf p , 9. Whitney AR, Diehn M, Popper SJ, Alizadeh AA, Boldrick JC, Rel- man DA, Brown PO: Individuality and variation in gene expres- sion patterns in human blood. Proc Natl Acad Sci USA 2003, 100:1896-1901. 10. Tibshirani R, Hastie T, Narasimhan B, Chu G: Diagnosis of multi- ple cancer types by shrunken centroids of gene expression. Proc Natl Acad Sci USA 2002, 99:6567-6572. 11. Hastie T, Tibshirani R, Friedman J: The Elements of Statistical Learning New York: Springer; 2001. g p g 12. Ambroise C, McLachlan GJ: Selection bias in gene extraction on the basis of microarray gene-expression data. Proc Natl Acad Sci USA 2002, 99:6562-6566. 13. Ceci M, Gaviraghi C, Gorrini C, Sala LA, Offenhauser N, Marchisio PC, Biffo S: Release of elF6 (p27-BBP) from the 60S subunit allows 80S ribosome assembly. Nature 2003, 426:579-584. y , 14. Ahmad K, Henikoff S: Histone H3 variants specify modes of chromatin assembly. Proc Natl Acad Sci USA 2002, 99:16477-16484. Acknowledgements The experimental work was supported by DiaGenic ASA. ALBD was supported by a grant under the Functional Genomics (FUGE) pro- gramme (159188/S10) from the Research Council of Norway. Additional File 3 Additional File 3 Supplementary Table 2, an Excel file showing the batch- corrected data for 1,368 genes. C, breast-cancer class; N, non-breast-cancer class. See http://www.biomedcentral.com/content/ supplementary/bcr1203-S3.xls We envisage blood-based gene-expression tests to have the potential of becoming a versatile and powerful tool for detec- tion of disease, including other forms of cancers. As with breast cancer, other diseases may also cause characteristic R643 Available online http://breast-cancer-research.com/content/7/5/R634 8. West M, Blanchette C, Dressman H, Huang E, Ishida S, Spang R, Zuzan H, Olson JA Jr, Marks JR, Nevins JR: Predicting the clinical status of human breast cancer by using gene expression profiles. Proc Natl Acad Sci USA 2001, 98:11462-11467. References 1. Kolb TM, Lichy J, Newhouse JH: Comparison of the performance of screening mammography, physical examination, and breast US and evaluation of factors that influence them: an analysis of 27,825 patient evaluations. Radiology 2002, 225:165-175. gy 2. Bertucci F, Nasser V, Granjeaud S, Eisinger F, Adelaide J, Tagett R, Loriod B, Giaconia A, Benziane A, Devilard E, et al.: Gene expression profiles of poor-prognosis primary breast cancer correlate with survival. Hum Mol Genet 2002, 11:863-872. 3. Ellis M, Davis N, Coop A, Liu M, Schumaker L, Lee RY, Srikan- chana R, Russell CG, Singh B, Miller WR, et al.: Development and validation of a method for using breast core needle biop- sies for gene expression microarray analyses. Clin Cancer Res 2002, 8:1155-1166. , 4. Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, et al.: Molecular por- traits of human breast tumours. Nature 2000, 406:747-752. 5. Sørlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, et al.: Gene expres- sion patterns of breast carcinomas distinguish tumor sub- classes with clinical implications. Proc Natl Acad Sci USA 2001, 98:10869-10874. , 6. Sørlie T, Tibshirani R, Parker J, Hastie T, Marron JS, Nobel A, Deng S, Johnsen H, Pesich R, Geisler S, et al.: Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 2003, 100:8418-8423. 7. van 't Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT, et al.: Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002, 415:530-536. R644
https://openalex.org/W2799902756
https://birmingham.elsevierpure.com/files/54052434/Mueller_et_al_Human_DHEA_sulfation_Journal_Biological_Chemistry.pdf
English
null
Human DHEA sulfation requires direct interaction between PAPS synthase 2 and DHEA sulfotransferase SULT2A1
Journal of biological chemistry/˜The œJournal of biological chemistry
2,018
cc-by
13,532
Human DHEA sulfation requires direct interaction between PAPS synthase 2 and DHEA sulfotransferase SULT2A1 Document Version Publisher's PDF, also known as Version of record Citation for published version (Harvard): Mueller, JW, Idkowiak, J, Gesteira, TF, Vallet, C, Hardman, R, van den Boom, J, Dhir, V, Knauer, SK, Rosta, E & Arlt, W 2018, 'Human DHEA sulfation requires direct interaction between PAPS synthase 2 and DHEA sulfotransferase SULT2A1', Journal of Biological Chemistry, vol. 293, no. 25, pp. 9724-9735. https://doi.org/10.1074/jbc.RA118.002248 Citation for published version (Harvard): Mueller, JW, Idkowiak, J, Gesteira, TF, Vallet, C, Hardman, R, van den Boom, J, Dhir, V, Knauer, SK, Rosta, E & Arlt, W 2018, 'Human DHEA sulfation requires direct interaction between PAPS synthase 2 and DHEA sulfotransferase SULT2A1', Journal of Biological Chemistry, vol. 293, no. 25, pp. 9724-9735. https://doi.org/10.1074/jbc.RA118.002248 General rights U l li General rights Unless a licence is specified above, all rights (including copyright and moral rights) in this document are retained by the authors and/or the copyright holders. The express permission of the copyright holder must be obtained for any use of this material other than for purposes permitted by law. y y y p •Users may download and/or print one copy of the publication from the University of Birmingham research portal for the purpose of private study or non-commercial research. mercial research. racts from the document in line with the concept of ‘fair dealing’ under the Copyright, Designs and Patents Act 1988 (?) rther distribute the material nor use it for the purposes of commercial gain. y •User may use extracts from the document in line with the concept of ‘fair dealing’ under the Copyright, Designs and P •Users may not further distribute the material nor use it for the purposes of commercial gain. Where a licence is displayed above, please note the terms and conditions of the licence govern your use of this document. here a licence is displayed above, please note the terms and conditions of the licence govern your use of this document When citing, please reference the published version. 2 The abbreviations used are: PAPS, 3-phosphoadenosine-5-phosphosul- fate; APS, adenosine 5-phosphosulfate; DHEA, dehydroepiandrosterone; DHEAS, dehydroepiandrosterone-3-sulfate; EGFP, enhanced green fluo- rescent protein; MD, molecular dynamics; MM-PBSA, molecular mechan- ics-Poisson-Boltzmann surface area; PAP, adenosine 3-phospho-5-phos- phate; PAPSS, PAPS synthase; PLA, proximity ligation assay; r.m.s., root mean square; SULT2A1, (DHEA) sulfotransferase 2A1; PDB, Protein Data Bank; ANOVA, analysis of variance. Human DHEA sulfation requires direct interaction between PAPS synthase 2 and DHEA sulfotransferase SULT2A1 Received for publication,February 2, 2018, and in revised form, April 28, 2018 Published, Papers in Press, May 9, 2018, DOI 10.1074/jbc.RA118.002248 X Jonathan W. Mueller‡§1, Jan Idkowiak‡§, Tarsis F. Gesteira¶, Cecilia Vallet, Rebecca Hardman‡, Johannes van den Boom**, Vivek Dhir‡, Shirley K. Knauer, Edina Rosta¶, and X Wiebke Arlt‡§ From the ‡Institute of Metabolism and Systems Research (IMSR), University of Birmingham, Birmingham B15 2TT, United Kingdom, the §Centre for Endocrinology, Diabetes and Metabolism (CEDAM), Birmingham Health Partners, Birmingham B15 2TH, United Kingdom, the ¶Department of Chemistry, King’s College London, London SE1 1DB, United Kingdom, and the Departments of Molecular Biology II, Centre for Medical Biotechnology (ZMB) and **Molecular Biology I, Centre for Medical Biotechnology (ZMB), University of Duisburg-Essen, 45141 Essen, Germany Edited by Joseph M. Jez at The University of Birmingham on September 5, 201 http://www.jbc.org/ Downloaded from at The University of Birming http://www.jbc.org/ Downloaded from The high-energy sulfate donor 3-phosphoadenosine-5- phosphosulfate (PAPS), generated by human PAPS synthase isoforms PAPSS1 and PAPSS2, is required for all human sulfa- tion pathways. Sulfotransferase SULT2A1 uses PAPS for sulfation of the androgen precursor dehydroepiandrosterone (DHEA), thereby reducing downstream activation of DHEA to active androgens. Human PAPSS2 mutations manifest with undetectable DHEA sulfate, androgen excess, and metabolic disease, suggesting that ubiquitous PAPSS1 cannot compensate for deficient PAPSS2 in supporting DHEA sulfation. In knock- down studies in human adrenocortical NCI-H295R1 cells, we found that PAPSS2, but not PAPSS1, is required for efficient DHEA sulfation. Specific APS kinase activity, the rate-limiting step in PAPS biosynthesis, did not differ between PAPSS1 and PAPSS2. Co-expression of cytoplasmic SULT2A1 with a cyto- plasmic PAPSS2 variant supported DHEA sulfation more efficiently than co-expression with nuclear PAPSS2 or nuclear/ cytosolic PAPSS1. Proximity ligation assays revealed protein– protein interactions between SULT2A1 and PAPSS2 and, to a lesser extent, PAPSS1. Molecular docking studies showed a putative binding site for SULT2A1 within the PAPSS2 APS kinase domain. Energy-dependent scoring of docking solutions identified the interaction as specific for the PAPSS2 and SULT2A1 isoforms. These findings elucidate the mechanistic basis for the selective requirement for PAPSS2 in human DHEA sulfation. and removal (1, 2). Many sulfotransferases ensure substrate specificity of sulfation; the 62 human sulfotransferase genes only have 46 direct counterparts in the mouse genome (2, 3). In contrast, 3-phosphoadenosine-5-phosphosulfate (PAPS)2 synthases, the enzymes responsible for sulfate activation, are rep- resented by only two genes in humans, PAPSS1 and PAPSS2 (4). ARTICLE ARTICLE Author’s Choice Author’s Choice Human DHEA sulfation requires direct interaction between PAPS synthase 2 and DHEA sulfotransferase SULT2A1 Received for publication,February 2, 2018, and in revised form, April 28, 2018 Published, Papers in Press, May 9, 2018, DOI 10.1074/jbc.RA118.002248 X Jonathan W. Mueller‡§1, Jan Idkowiak‡§, Tarsis F. Gesteira¶, Cecilia Vallet, Rebecca Hardman‡, Johannes van den Boom**, Vivek Dhir‡, Shirley K. Knauer, Edina Rosta¶, and X Wiebke Arlt‡§ From the ‡Institute of Metabolism and Systems Research (IMSR), University of Birmingham, Birmingham B15 2TT, United Kingdom, the §Centre for Endocrinology, Diabetes and Metabolism (CEDAM), Birmingham Health Partners, Birmingham B15 2TH, United Kingdom, the ¶Department of Chemistry, King’s College London, London SE1 1DB, United Kingdom, and the Departments of Molecular Biology II, Centre for Medical Biotechnology (ZMB) and **Molecular Biology I, Centre for Medical Biotechnology (ZMB), University of Duisburg-Essen, 45141 Essen, Germany This article contains Figs. S1 and S2 and Tables S1–S4. they have no conflicts of interest with the contents of this article. Author’sChoice—FinalversionopenaccessunderthetermsoftheCreative Commons CC-BY license. Human DHEA sulfation requires direct interaction between PAPS synthase 2 and DHEA sulfotransferase SULT2A1 This gene pair is evolutionary conserved in all vertebrate genomes investigated so far; RNA splice forms and additional teleost-spe- cific gene duplications of PAPSS2 are the only exceptions (4). The primary role of PAPS synthases is to provide the many and diverse sulfotransferases with the high-energy sulfate donor PAPS. PAPS availability is generally the limiting factor in this system (5), due to the high energetic cost of PAPS biosyn- thesis. First, nucleophilic sulfate needs to attack the -phos- phorus of ATP, catalyzed by ATP sulfurylase, resulting in the formation of APS (adenosine 5-phosphosulfate) and the release of pyrophosphate (6). This reaction lies heavily on the educt side, with an equilibrium constant for APS formation of 108 (7); a fact exploited in pyrosequencing (8). To pull the reaction toward product formation, pyrophosphatases swiftly cleave the pyrophosphate and APS kinase phosphorylates APS at its ribose 3 position, resulting in the formation of PAPS (6). Once PAPS is used in sulfation reactions, the remaining bis- phosphorylated nucleotide PAP (3-phosphoadenosine-5- phosphate) needs to be cleaved by dedicated PAP phosphatases (9, 10). In animal genomes, ATP sulfurylase and APS kinase are fused to the above mentioned bifunctional PAPS synthases (4, 11). The phosphorylation of APS by APS kinase is regarded the rate-limiting step of overall PAPS biosynthesis (6, 12). Sulfation pathways are a vital part of human physiology, encompassing the central triad of sulfate activation, transfer, PAPS synthases 1 and 2 are very similar enzyme isoforms with 78% amino acid identity (4), but with an unknown degree of functional overlap. The clinical phenotype of human loss-of- function mutations in the gene encoding PAPSS2 have sug- gested differential roles for PAPSS1 and PAPSS2 in human sul- g 1 To whom correspondence should be addressed: Institute of Metabolism and Systems Research (IMSR), College of Medical and Dental Sciences, Uni- versity of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom. Tel.: 44-0-1214158819; E-mail: j.w.mueller@bham.ac.uk. g 1 To whom correspondence should be addressed: Institute of Metabolism and Systems Research (IMSR), College of Medical and Dental Sciences, Uni- versity of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom. Tel.: 44-0-1214158819; E-mail: j.w.mueller@bham.ac.uk. This work was supported by the European Commission Marie Curie Fellow- ship SUPA-HD 625451 (to J. W. M.), Wellcome Trust Project Grant 092283 (to W. A.), ISSF award (to J. W. M.), Medical Research Council UK Research Training Fellowship G1001964 (to J. I.), the Biotechnology and Biological Sciences Research Council UK Grant BB/N007700/1 (to E. R.), and a Society for Endocrinology Early Career Grant (to J. W. M.). The authors declare that they have no conflicts of interest with the contents of this article. Author’sChoice—FinalversionopenaccessunderthetermsoftheCreative Commons CC-BY license. Take down policy hil h i i Take down policy While the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive. Take down policy While the University of Birmingham exercises care and attention in making items available there are rare occasions wh uploaded in error or has been deemed to be commercially or otherwise sensitive. If you believe that this is the case for this document, please contact UBIRA@lists.bham.ac.uk providing details and we will remove access to the work immediately and investigate. this is the case for this document, please contact UBIRA@lists.bham.ac.uk providing details and we will remove access ely and investigate. If you believe that this is the case for this document, please contact UBIRA@lists.bham.ac.uk providing details and we the work immediately and investigate. Download date: 24. Oct. 2024 cro This work was supported by the European Commission Marie Curie Fellow- ship SUPA-HD 625451 (to J. W. M.), Wellcome Trust Project Grant 092283 (to W. A.), ISSF award (to J. W. M.), Medical Research Council UK Research Training Fellowship G1001964 (to J. I.), the Biotechnology and Biological Sciences Research Council UK Grant BB/N007700/1 (to E. R.), and a Society for Endocrinology Early Career Grant (to J. W. M.). The authors declare that they have no conflicts of interest with the contents of this article. Author’sChoice—FinalversionopenaccessunderthetermsoftheCreative Commons CC-BY license. This article contains Figs. S1 and S2 and Tables S1–S4. 1 To whom correspondence should be addressed: Institute of Metabolism and Systems Research (IMSR), College of Medical and Dental Sciences, Uni- versity of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom. Tel.: 44-0-1214158819; E-mail: j.w.mueller@bham.ac.uk. 1 To whom correspondence should be addressed: Institute of Metabolism and Systems Research (IMSR), College of Medical and Dental Sciences, Uni- versity of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom. Tel.: 44-0-1214158819; E-mail: j.w.mueller@bham.ac.uk. 9724 J. Biol. Chem. (2018) 293(25) 9724–9735 9724 9724 © 2018 Mueller et al. Published by The American Society for Biochemistry and Molecular Biology, Inc. © 2018 Mueller et al. Published by The American Society for Biochemistry and Molecular Biology, Inc. © 2018 Mueller et al. Published by The American Society for Biochemistry and Molecular Biology, Inc. DHEA sulfation and PAPSS2–SULT2A1 interaction at The University of Birmingham on September 5, 2018 http://www.jbc.org/ Downloaded from fation pathways (2, 13, 14). Inactivating PAPSS2 mutations have been reported to present with skeletal malformations, specifi- cally variable phenotypes of spondyloepimetaphyseal dysplasia (14, 15), and with biochemical and clinical evidence of andro- gen excess (13, 14). Sulfation of the androgen precursor dehy- droepiandrosterone (DHEA) reduces the availability of nonsul- fated DHEA for downstream conversion to androgens. Hence, impaired DHEA sulfation results in a higher rate of androgen activation and clinically in androgen excess phenotypes such as polycystic ovary syndrome (13, 14, 16). Crucially, the pheno- type of human PAPSS2 deficiency proves that with regard to DHEA sulfation and bone and chondrocyte development, human PAPSS1, the gene encoding the only other PAPS syn- thase, appears not to be able to compensate for the loss of PAPSS2 gene function. at The University of Birmingham on September 5, 2018 http://www.jbc.org/ Downloaded from There has been considerable debate about the cause of the divergent functions of the two PAPS synthase isoforms. Differ- ences in subcellular localization have been suggested as an underlying mechanism, with PAPSS1 reported as nuclear pro- tein and PAPSS2 as primarily located in the cytoplasm (17). However, this was recognized as oversimplification as both enzymes actively shuttle between nucleus and cytoplasm, guided by conserved nuclear localization and nuclear export signals (18). Another aspect was an apparent difference in spe- cific enzymatic activity. When assayed as pseudo one-step enzymes, PAPSS2 was reported to display a much higher kcat/Km value than PAPSS1 (19). When assaying only the rate- limiting step of overall PAPS biosynthesis, the APS kinase-cat- alyzed reaction, this difference was no longer observed (20). Differences in tissue-specific distribution of the two PAPS syn- thases have also been reported (13, 19, 21). Nevertheless, none of those studies could sufficiently explain why the PAPSS1 gene cannot compensate for the loss of PAPSS2 due to inactivating PAPSS2 mutations. 9724 J. Biol. Chem. (2018) 293(25) 9724–9735 y g p p j g at The Univer http://www.jbc.org/ nloaded from Here we report experimental evidence for nonoverlapping functionality of PAPSS1 and PAPSS2 with regard to DHEA sul- fation by SULT2A1 (Fig. 1A). Proximity ligation assays (PLAs) detect a novel protein–protein interaction between SULT2A1 and PAPSS2 and molecular docking suggests SULT2A1 con- tacts the APS kinase domain of PAPSS2. This newly described protein–protein interaction, specific to the PAPSS2 and SULT2A1 isoforms, may guide the directionality of sulfation pathways in tissues with equal expression of PAPS synthases and high expression levels of various sulfotransferases. Figure 1. Knockdown of components of the DHEA sulfation pathway. A, schematic representation of the DHEA sulfation pathway. Activated sulfate in the form of PAPS is produced by either PAPSS1 or PAPSS2 and then used by the sulfotransferase SULT2A1 to convert DHEA to DHEAS. B and C, siRNA-mediated knockdown of SULT2A1, PAPSS1, or PAPSS2 in adrenocorti- cal NCI-H295R1 cells was verified by real-time PCR and Western blotting. A scrambled oligonucleotide served as control (ctrl). Real-time PCR data nor- malized to 18S rRNA, fold-change relative to that control. Densitometric quantification of Western blots revealed knockdown efficiencies of up to 90% on the protein level. Double bands were interpreted as degradation products and jointly analyzed. D, DHEA sulfation was assayed for all knockdowns men- tioned above, revealing functional differences between PAPSS1 and PAPSS2 for DHEA sulfation by sulfotransferase SULT2A1. Three biological replicates and their average are shown; each dot consists of at least three technical replicates. Normally distributed data were analyzed by one-way ANOVA (p value  0.001) and post-hoc Bonferroni tests (*, p  0.05; **, p  0.01) relative to the control. PAPSS2 is functionally required for DHEA sulfation in a human adrenocortical cell line The adrenal cortex is a major site of DHEA sulfation. We used human adrenocortical NCI-H295R1 cells, which we found to express high levels of SULT2A1 mRNA (CT value 13.4  1.3 relative to 18S rRNA,  S.D., see also Table S1) and almost identical mRNA levels of PAPSS1 and PAPSS2 (CT values 16.1  0.8 and 15.8  0.9, respectively). We separately targeted SULT2A1 and both PAPS synthase isoforms by siRNA- mediated knockdown, achieving knockdown efficiencies of up to 90% at mRNA (Fig. 1B) and protein levels (Fig. 1C). We Enzymatic properties are very similar for both PAPS synthases To determine whether different enzyme activities may explain the above described differences in functionality, we determined specific APS kinase activities of recombinant PAPSS1 and PAPSS2 proteins in a coupled spectrophotometric assay. APS kinase activity is known to be the rate-limiting step of overall PAPS biosynthesis (12). Using two different enzyme batches, performing multiple repeat measurements (Fig. 2A), specific APS kinase activities appeared nondistinguishable, 34.9  17.0 nmol min1 mg1 for PAPSS1 and 31.6  10.6 nmol min1 mg1 for PAPSS2 (Table 1), in line with previous findings (20). Cytosmic PAPSS2 supports SULT2A1 activity To determine whether different cellular localization of PAPS synthases might contribute to their functional differences, we examined subcellular localization variants of PAPS synthases 1 and 2 with preferential nuclear or cytoplasmic localization (18) for their ability to support DHEA sulfation by SULT2A1 (Fig. 3A). A nonsteroidogenic HEK293 cellular background with no notable expression of these sulfation enzymes was used to co- express PAPS synthase protein variants with cytoplasmic SULT2A1; activity of this sulfation pathway was then tested in DHEA sulfation assays (Fig. 3B). Cytoplasmic PAPSS1 expres- sion only supported DHEA sulfation to 61% of WT protein activity (conversion rates in (nmol DHEA/h) are given in Table S2). Both nuclear PAPS synthases showed less DHEA sulfation than the respective WT protein (72 and 82% of WT for PAPSS1 and PAPSS2, respectively). Only cytoplasmic PAPSS2 was as effective in supporting DHEA sulfation as WT PAPSS2 (Fig. 3B). This effect of subcellular location on the ability of PAPSS2 to support DHEA sulfation by SULT2A1 led us to hypothesize that these sulfation pathway proteins might physically interact. then carried out functional assays and found that siRNA- mediated knockdown of SULT2A1 and PAPSS2 reduced DHEA sulfation rates to 19 and 30%, respectively, whereas depletion of PAPSS1 showed no discernable effect on DHEA sulfation (Fig. 1D). This suggests nonoverlapping functionality of the two human PAPS synthase proteins with regard to DHEA sulfation. Table 1 15 individual velocity measurements from two different batches are shown. Please refer to Table 1 for the averaged specific activity. B, APS binding studies where fluorescently labeled APS (1 M mant- APS) was titrated with increasing concentrations of PAPS synthase protein. Data were fitted assuming one binding site. C, back-titration of 1 M mant- APS and 50 M PAPSS protein with increasing concentrations of APS. As mant-APScanbedisplacedbyAPS,thefluorescentmantmoietydidnotinter- fere with binding to the protein. Table 1 Assuming a single nucleotide binding site. ** EC50 was measured in the presence of 50 M PAPSS protein and 1 M mant-APS. derivative (mant-APS) to recombinant PAPS synthase proteins (Fig. 2B). Theoretically, APS could bind to all six nucleotide- binding sites of dimeric PAPS synthase proteins (6); but fitting to the Hill equation resulted in very weak cooperativity with Hill coefficients close to 1 (1.09  0.02 and 1.22  0.05 for PAPSS1 and PAPSS2, respectively). Hence, data were fitted assuming one binding site, resulting in apparent KD values of 13.2  0.3 and 23.0  1.6 M for PAPSS1 and PAPSS2, respec- tively. Titrations of preformed PAPS synthase–mant-APS complexes with APS confirmed that both nucleotides actually bound to the same site(s) within the enzyme (Fig. 2C). We also attempted to determine ATP sulfurylase activity; however, this was hindered by considerable batch-to-batch variability in PAPSS2 (data not shown). Without any significant differences in the APS kinase activity of PAPSS1 and PAPSS2 and very similar affinities for the modulating APS nucleotide, we con- clude that differences in enzymatic activity cannot explain the above described functional differences. derivative (mant-APS) to recombinant PAPS synthase proteins (Fig. 2B). Theoretically, APS could bind to all six nucleotide- binding sites of dimeric PAPS synthase proteins (6); but fitting to the Hill equation resulted in very weak cooperativity with Hill coefficients close to 1 (1.09  0.02 and 1.22  0.05 for PAPSS1 and PAPSS2, respectively). Hence, data were fitted assuming one binding site, resulting in apparent KD values of 13.2  0.3 and 23.0  1.6 M for PAPSS1 and PAPSS2, respec- tively. Titrations of preformed PAPS synthase–mant-APS complexes with APS confirmed that both nucleotides actually bound to the same site(s) within the enzyme (Fig. 2C). We also attempted to determine ATP sulfurylase activity; however, this was hindered by considerable batch-to-batch variability in PAPSS2 (data not shown). Without any significant differences in the APS kinase activity of PAPSS1 and PAPSS2 and very similar affinities for the modulating APS nucleotide, we con- clude that differences in enzymatic activity cannot explain the above described functional differences. at The University of Birmingham on September 5 http://www.jbc.org/ Downloaded from Figure 2. APS kinase activity and APS binding properties of human PAPS synthases. A, APS kinase activity was measured in a coupled enzymatic assay where ADP production is linked to NADH consumption via pyruvate kinase and lactate dehydrogenase. J. Biol. Chem. (2018) 293(25) 9724–9735 9725 DHEA sulfation and PAPSS2–SULT2A1 interaction Figure 2. APS kinase activity and APS binding properties of human PAPS synthases. A, APS kinase activity was measured in a coupled enzymatic assay where ADP production is linked to NADH consumption via pyruvate kinase and lactate dehydrogenase. 15 individual velocity measurements from two different batches are shown. Please refer to Table 1 for the averaged specific activity. B, APS binding studies where fluorescently labeled APS (1 M mant- APS) was titrated with increasing concentrations of PAPS synthase protein. Data were fitted assuming one binding site. C, back-titration of 1 M mant- APS and 50 M PAPSS protein with increasing concentrations of APS. As mant-APScanbedisplacedbyAPS,thefluorescentmantmoietydidnotinter- fere with binding to the protein. D su at o a d SS SU te act o derivative (mant-APS) to recombinant PAPS synthase proteins (Fig. 2B). Theoretically, APS could bind to all six nucleotide- binding sites of dimeric PAPS synthase proteins (6); but fitting to the Hill equation resulted in very weak cooperativity with Hill coefficients close to 1 (1.09  0.02 and 1.22  0.05 for PAPSS1 and PAPSS2, respectively). Hence, data were fitted assuming one binding site, resulting in apparent KD values of 13.2  0.3 and 23.0  1.6 M for PAPSS1 and PAPSS2, respec- tively. Titrations of preformed PAPS synthase–mant-APS complexes with APS confirmed that both nucleotides actually bound to the same site(s) within the enzyme (Fig. 2C). We also attempted to determine ATP sulfurylase activity; however, this was hindered by considerable batch-to-batch variability in PAPSS2 (data not shown). Without any significant differences in the APS kinase activity of PAPSS1 and PAPSS2 and very similar affinities for the modulating APS nucleotide, we con- clude that differences in enzymatic activity cannot explain the above described functional differences. Cytosmic PAPSS2 supports SULT2A1 activity To determine whether different cellular localization of PAPS synthases might contribute to their functional differences, we examined subcellular localization variants of PAPS synthases 1 Figure 2. APS kinase activity and APS binding properties of human PAPS synthases. A, APS kinase activity was measured in a coupled enzymatic assay where ADP production is linked to NADH consumption via pyruvate kinase and lactate dehydrogenase. 15 individual velocity measurements from two different batches are shown. Please refer to Table 1 for the averaged specific activity. B, APS binding studies where fluorescently labeled APS (1 M mant- APS) was titrated with increasing concentrations of PAPS synthase protein. Data were fitted assuming one binding site. C, back-titration of 1 M mant- APS and 50 M PAPSS protein with increasing concentrations of APS. As mant-APScanbedisplacedbyAPS,thefluorescentmantmoietydidnotinter- fere with binding to the protein. Table 1 Enzymatic characterization of human PAPS synthase isoforms * Assuming a single nucleotide binding site. ** EC50 was measured in the presence of 50 M PAPSS protein and 1 M mant-APS. at The University of Birmingha http://www.jbc.org/ Downloaded from Table 1 Enzymatic characterization of human PAPS synthase isoforms * Assuming a single nucleotide binding site. ** EC50 was measured in the presence of 50 M PAPSS protein and 1 M mant-APS. Table 1 Enzymatic characterization of human PAPS synthase isoforms * Assuming a single nucleotide binding site. ** EC50 was measured in the presence of 50 M PAPSS protein and 1 M mant-APS. SULT2A1 docks uniformly to the APS kinase domain of PAPSS2 To examine the newly detected PAPSS–SULT2A1 complex on a molecular level, we used different available crystal struc- tures of human SULT2A1 and structural information about PAPS synthases for protein–protein docking using ClusPro (24). This procedure revealed a novel protein–interaction interface at the APS kinase domain of PAPSS2, where SULT2A1 binds (Fig. 5A). Considering the almost perfect C2 symmetry of the APS kinase domain, we regarded two binding sites as equivalent. Docking SULT2A1 to PAPSS1 resulted in more diffuse complexes, as SULT2A1 populated additional binding sites at the ATP sulfurylase of PAPSS1 (Fig. 5B). Statis- tical analysis of the ensembles of docked complexes confirm this observation (Fig. 5C). For PAPSS2, all amino acids found most often at the interface with SULT2A1 cluster within the APS kinase domain, whereas interacting amino acids of The novel protein interaction may be specific for PAPS synthase 2 and the sulfotransferase SULT2A1 from hominids Best scoring complexes were then subjected to local docking and re-scoring using RosettaDock (25, 26). The resulting com- plexes are described by their structural similarity to an average complex (interface r.m.s. deviation) and a docking score repre- senting an energy term (Fig. 6A). Docking of PAPSS2 and SULT2A1 resulted in a cloud of docking experiments with a clearly visible funnel toward low r.m.s. deviations and low Rosetta energies (Fig. 6A). The corresponding PAPSS1/ SULT2A1 docking neither showed such a trend nor was it char- acterized by similarly favorable Rosetta scores (Fig. 6A). J. Biol. Chem. (2018) 293(25) 9724–9735 9727 Proximity ligation assays detect a protein–protein interaction of PAPSS2 and SULT2A1 Negative controls were generated using only one primary antibody at a time. 600 magnification for A and B. C, box-and-whis- ker analysis of the PLA foci number per cell from at least 400 cells pooled from three independent experiments. Data were found to be not normally distrib- uted; hence, one-way ANOVA (p value  0.001) and post hoc Bonferroni tests (***, p  0.001) were performed after data were square root transformed. PAPSS2–SULT2A1 interaction is of transient character, we employed PLA technology, which is well-suited to capture tran- sient interactions (22). DNA-linked secondary antibodies and a linker oligo enable rolling circle amplification and signal gener- ation (“foci”) only if the primary antibodies against SULT2A1 and PAPSS1/PAPSS2 have bound less than 40 nm apart. One “focus” is assumed to correspond to one ligation event and the average number of “foci per cell” is interpreted as binding strength (23). PLA technology combined with automated cell, nucleus, and foci recognition (Fig. 4A) allows for the analysis of large numbers of cells per staining, more than 400 cells per condition in our analysis. Foci per cell were clearly elevated in the staining for PAPSS2 and SULT2A1, indicative of a physical interaction between these proteins (Fig. 4B). Furthermore, foci per cell were significantly higher for PAPSS2–SULT2A1 than for a corresponding staining of SULT2A1 and PAPSS1 (Fig. 4C). PAPSS2–SULT2A1 interaction is of transient character, we employed PLA technology, which is well-suited to capture tran- sient interactions (22). DNA-linked secondary antibodies and a linker oligo enable rolling circle amplification and signal gener- ation (“foci”) only if the primary antibodies against SULT2A1 and PAPSS1/PAPSS2 have bound less than 40 nm apart. One “focus” is assumed to correspond to one ligation event and the average number of “foci per cell” is interpreted as binding strength (23). PLA technology combined with automated cell, nucleus, and foci recognition (Fig. 4A) allows for the analysis of large numbers of cells per staining, more than 400 cells per condition in our analysis. Foci per cell were clearly elevated in the staining for PAPSS2 and SULT2A1, indicative of a physical interaction between these proteins (Fig. 4B). Furthermore, foci per cell were significantly higher for PAPSS2–SULT2A1 than for a corresponding staining of SULT2A1 and PAPSS1 (Fig. 4C). ersity of Birmingham on September 5, 2018 PAPSS1 seem to be scattered over the entire protein (Fig. 5C). Proximity ligation assays detect a protein–protein interaction of PAPSS2 and SULT2A1 Looking from the SULT2A1 side, the mode of binding to PAPSS1 and PAPSS2 appears to be very similar, involving the substrate-binding loops. One notable difference is that amino acids from the cap, the major substrate-binding loop, are involved in binding to PAPSS1, whereas these amino acids do not play a role in binding to PAPSS2 (Fig. 5D). Proximity ligation assays detect a protein–protein interaction of PAPSS2 and SULT2A1 To test for a physical interaction between PAPSS2 and SULT2A1, we employed PLA technology after demonstrating that this putative interaction was not amenable to detection by GFP-trap pulldown (Fig. S1A). Hypothesizing that the putative The nucleotide APS has been reported to be a highly effective modulator of PAPS synthase proteins (4, 6). Hence, we deter- mined binding affinity (KD) of a fluorescently labeled APS 9726 J. Biol. Chem. (2018) 293(25) 9724–9735 9726 Figure3.CytoplasmicPAPSS2bestsupportscytoplasmicSULT2A1activ- ity. A, HEK293 cells were transfected with cytoplasmic sulfotransferase SULT2A1 as well as cytoplasmic (PAPSS1 K9A,K10A and PAPSS2 K6A,K8A) or nuclear protein variants of PAPS synthases (PAPSS1 R111A,R112A and PAPSS2 R101A,R102A) as EGFP fusion proteins. The different variants for PAPSS1 are shown exemplarily; their localization was as described before (18). 600 magnification. B, DHEA sulfation was assayed for these different PAPS synthase variants. Each point represents the average from triplicate measurements. Normally distributed data were analyzed by one-way ANOVA (p value  0.001) and post-hoc Bonferroni tests (*, p  0.05; **, p  0.01) relative to the control. DHEA sulfation and PAPSS2–SULT2A1 interaction Figure 4. A physical interaction of PAPSS2 and SULT2A1 detected by proximityligationassays.A,representativeimagesoftheproximityligation assay between PAPSS2 and SULT2A1 as well as subsequent analysis with Cell- Profiler. Endogenous PAPS synthases and SULT2A1 were detected by mouse monoclonal antibodies for PAPSS1 or PAPSS2 and a rabbit SULT2A1 poly- clonal antibody in a HepG2 cell line. PLA analysis, including automated cell and nucleus recognition and foci counting was carried out using CellProfiler software. Cell nuclei were stained with Hoechst 33342 (blue); CellMask stain- ing is shown in magenta. PLA foci are shown in white in the single channel picture. In the output image of CellProfiler analysis edges of nuclei are repre- sentedincyan,cellboardersinred,andPLAfociinyellow.B,CellProfilerresults for all other combinations. Negative controls were generated using only one primary antibody at a time. 600 magnification for A and B. C, box-and-whis- ker analysis of the PLA foci number per cell from at least 400 cells pooled from three independent experiments. Data were found to be not normally distrib- uted; hence, one-way ANOVA (p value  0.001) and post hoc Bonferroni tests (***, p  0.001) were performed after data were square root transformed. at The University of Birmingham on September 5, 2018 http://www.jbc.org/ Downloaded from Figure3.CytoplasmicPAPSS2bestsupportscytoplasmicSULT2A1activ- Figure3.CytoplasmicPAPSS2bestsupportscytoplasmicSULT2A1activ- ity. Proximity ligation assays detect a protein–protein interaction of PAPSS2 and SULT2A1 A, HEK293 cells were transfected with cytoplasmic sulfotransferase SULT2A1 as well as cytoplasmic (PAPSS1 K9A,K10A and PAPSS2 K6A,K8A) or nuclear protein variants of PAPS synthases (PAPSS1 R111A,R112A and PAPSS2 R101A,R102A) as EGFP fusion proteins. The different variants for PAPSS1 are shown exemplarily; their localization was as described before (18). 600 magnification. B, DHEA sulfation was assayed for these different PAPS synthase variants. Each point represents the average from triplicate measurements. Normally distributed data were analyzed by one-way ANOVA (p value  0.001) and post-hoc Bonferroni tests (*, p  0.05; **, p  0.01) relative to the control. Figure 4. A physical interaction of PAPSS2 and SULT2A1 detected by proximityligationassays.A,representativeimagesoftheproximityligation assay between PAPSS2 and SULT2A1 as well as subsequent analysis with Cell- Profiler. Endogenous PAPS synthases and SULT2A1 were detected by mouse monoclonal antibodies for PAPSS1 or PAPSS2 and a rabbit SULT2A1 poly- clonal antibody in a HepG2 cell line. PLA analysis, including automated cell and nucleus recognition and foci counting was carried out using CellProfiler software. Cell nuclei were stained with Hoechst 33342 (blue); CellMask stain- ing is shown in magenta. PLA foci are shown in white in the single channel picture. In the output image of CellProfiler analysis edges of nuclei are repre- sentedincyan,cellboardersinred,andPLAfociinyellow.B,CellProfilerresults for all other combinations. Negative controls were generated using only one primary antibody at a time. 600 magnification for A and B. C, box-and-whis- ker analysis of the PLA foci number per cell from at least 400 cells pooled from three independent experiments. Data were found to be not normally distrib- uted; hence, one-way ANOVA (p value  0.001) and post hoc Bonferroni tests (***, p  0.001) were performed after data were square root transformed. Figure 4. A physical interaction of PAPSS2 and SULT2A1 detected by proximityligationassays.A,representativeimagesoftheproximityligation assay between PAPSS2 and SULT2A1 as well as subsequent analysis with Cell- Profiler. Endogenous PAPS synthases and SULT2A1 were detected by mouse monoclonal antibodies for PAPSS1 or PAPSS2 and a rabbit SULT2A1 poly- clonal antibody in a HepG2 cell line. PLA analysis, including automated cell and nucleus recognition and foci counting was carried out using CellProfiler software. Cell nuclei were stained with Hoechst 33342 (blue); CellMask stain- ing is shown in magenta. PLA foci are shown in white in the single channel picture. In the output image of CellProfiler analysis edges of nuclei are repre- sentedincyan,cellboardersinred,andPLAfociinyellow.B,CellProfilerresults for all other combinations. The PAPSS2–SULT2A1 interaction may be isoform-specific. A, SULT2B1 was selected as homologous sulfotransferase to analyze specificity of the novel PAPSS2–sulfotransferase interaction. PAPS synthase–sulfurylase docking was refined using RosettaDock. At least 10,000 docking experiments are shown where the docking score was correlated with the interface r.m.s. deviation value compared with the average complex. B, best solutions from Rosetta were subjected to MD simulations (3  20 ns, see Fig. S2 for averaged Figure 5. SULT2A1 docks to the APS kinase domain of PAPSS2. ClusPro computational docking of three different SULT2A1 crystal structures (PDB codes 1EFH, 3F3Y, and 4IFB) to structural models of PAPSS1 and PAPSS2. A, PAPSS2–SULT2A1-docked complexes are shown. PAPSS2 APS kinase is labeled; ATP sulfurylase is labeled and boxed. The two PAPSS2 dimeric sub- units are gray and red. Two SULT2A1 molecules are depicted in yellow, ball representation; contacting PAPSS2 at its APS kinase domain, sites 1 and 1. B, corresponding representation of PAPSS1–SULT2A1 docking experiments. In addition to sites 1 and 1, SULT2A1 contacts PAPSS1 also at the ATP sulfury- lase domain. Color coding as in A, except the two PAPSS1 dimeric subunits, which are gray and black. C and D, statistical analysis of all ClusPro docking experiments, looking from the PAPS synthase side (C) and from the SULT2A1 side (D). Frequency of individual residues within 3 Å of the other protein was analyzed for PDB 1EFH, 3F3Y, and 4IFB structures separately (30 dockings each) and then averaged. Note the higher number of frequent protein con- tacts within the APS kinase domain of PAPSS2, compared with the one from PAPSS1. SULT2A1 contacted PAPS synthases mainly via its isoform-specific substrate binding loops; one of these is regarded as “cap.” at The University of Birmingham on September 5, 2018 http://www.jbc.org/ Downloaded from Figure 5. SULT2A1 docks to the APS kinase domain of PAPSS2. ClusPro computational docking of three different SULT2A1 crystal structures (PDB codes 1EFH, 3F3Y, and 4IFB) to structural models of PAPSS1 and PAPSS2. A, PAPSS2–SULT2A1-docked complexes are shown. PAPSS2 APS kinase is labeled; ATP sulfurylase is labeled and boxed. The two PAPSS2 dimeric sub- units are gray and red. Two SULT2A1 molecules are depicted in yellow, ball representation; contacting PAPSS2 at its APS kinase domain, sites 1 and 1. B, corresponding representation of PAPSS1–SULT2A1 docking experiments. In addition to sites 1 and 1, SULT2A1 contacts PAPSS1 also at the ATP sulfury- lase domain. To explore isoform specificity also for the sulfotransferase, an equilibrium state within the simulation time window (Fig. S2), indicating that energy calculations were appropriate. Free energy MM-PBSA calculations for all four complexes are shown in Fig. 6B, van der Waals energies, polar solvation, and SASA energy terms are roughly the same for all four combina- Figure 5. SULT2A1 docks to the APS kinase domain of PAPSS2. ClusPro computational docking of three different SULT2A1 crystal structures (PDB codes 1EFH, 3F3Y, and 4IFB) to structural models of PAPSS1 and PAPSS2. A, PAPSS2–SULT2A1-docked complexes are shown. PAPSS2 APS kinase is labeled; ATP sulfurylase is labeled and boxed. The two PAPSS2 dimeric sub- units are gray and red. Two SULT2A1 molecules are depicted in yellow, ball representation; contacting PAPSS2 at its APS kinase domain, sites 1 and 1. B, corresponding representation of PAPSS1–SULT2A1 docking experiments. In addition to sites 1 and 1, SULT2A1 contacts PAPSS1 also at the ATP sulfury- lase domain. Color coding as in A, except the two PAPSS1 dimeric subunits, which are gray and black. C and D, statistical analysis of all ClusPro docking experiments, looking from the PAPS synthase side (C) and from the SULT2A1 side (D). Frequency of individual residues within 3 Å of the other protein was analyzed for PDB 1EFH, 3F3Y, and 4IFB structures separately (30 dockings each) and then averaged. Note the higher number of frequent protein con- tacts within the APS kinase domain of PAPSS2, compared with the one from PAPSS1. SULT2A1 contacted PAPS synthases mainly via its isoform-specific substrate binding loops; one of these is regarded as “cap.” Figure 6. The PAPSS2–SULT2A1 interaction may be isoform-specific. A, SULT2B1 was selected as homologous sulfotransferase to analyze specificity of the novel PAPSS2–sulfotransferase interaction. PAPS synthase–sulfurylase docking was refined using RosettaDock. At least 10,000 docking experiments are shown where the docking score was correlated with the interface r.m.s. deviation value compared with the average complex. B, best solutions from Rosetta were subjected to MD simulations (3  20 ns, see Fig. S2 for averaged traces); MM-PBSA energies were derived therefrom, expressed as average  S.D. from three independent calculations. DHEA sulfation and PAPSS2–SULT2A1 interaction at The University of Birmingham on September 5, 2018 http://www.jbc.org/ Downloaded from DHEA sulfation and PAPSS2–SULT2A1 interaction DHEA sulfation and PAPSS2–SULT2A1 interaction DHEA sulfation and PAPSS2–SULT2A1 interaction sulfation and PAPSS2–SULT2A1 inter DHEA sulfation and PAPSS2–SULT2A1 interaction Figure 6. (2018) 293(25) 9724–9735 DHEA sulfation and PAPSS2–SULT2A1 interaction DHEA sulfation and PAPSS2–SULT2A1 interaction DHEA sulfation and PAPSS2–SULT2 DHEA sulfation and PAPSS2–SULT2 at The University of Birmingham on September 5, 2018 http://www.jbc.org/ Downloaded from at The University of Birmingham on September 5 http://www.jbc.org/ Downloaded from Figure 7. A PAPSS2–SULT2A1 protein interaction facilitates DHEA sulfation. A and B, molecular representation of a PAPSS2–SULT2A1 complex averaged over15nsofMDtime.ThedimericPAPSS2subunitproximaltoSULT2A1isdepictedingraycolorandwithmolecularsurfacerepresentation;thedistantPAPSS2 subunit in red color and ribbon representation. SULT2A1 is drawn in yellow. Please note the composite nature of the PAPSS2-binding site. Amino acids on the interface are shown in stick representation of the side chains and labeled accordingly. C, all SULT2A1 amino acids on the interface with PAPSS2 were highlighted in an alignment of diverse mammalian SULT2A1 protein sequences. The only two interface amino acids that were specific to great apes are Thr85 and Tyr238 (depicted in blue in B). D, the PAPSS2–SULT2A1 interface was analyzed using Rosetta-based alanine scanning (27). Furthermore, the two great ape-specific amino acids were mutated to their nonhominoid counterparts. T85K resulted in a dramatic loss of stability of the complex. E, the hominid-specific PAPSS2–SULT2A1 complex coincides with a higher DHEAS/DHEA ratio in gorilla, chimpanzee, and human. DHEAS/DHEA ratios are derived from Refs. 28 and 29. Figure 7. A PAPSS2–SULT2A1 protein interaction facilitates DHEA sulfation. A and B, molecular representation of a PAPSS2–SULT2A1 complex averaged over15nsofMDtime.ThedimericPAPSS2subunitproximaltoSULT2A1isdepictedingraycolorandwithmolecularsurfacerepresentation;thedistantPAPSS2 subunit in red color and ribbon representation. SULT2A1 is drawn in yellow. Please note the composite nature of the PAPSS2-binding site. Amino acids on the interface are shown in stick representation of the side chains and labeled accordingly. C, all SULT2A1 amino acids on the interface with PAPSS2 were highlighted in an alignment of diverse mammalian SULT2A1 protein sequences. The only two interface amino acids that were specific to great apes are Thr85 and Tyr238 (depicted in blue in B). D, the PAPSS2–SULT2A1 interface was analyzed using Rosetta-based alanine scanning (27). Furthermore, the two great ape-specific amino acids were mutated to their nonhominoid counterparts. T85K resulted in a dramatic loss of stability of the complex. E, the hominid-specific PAPSS2–SULT2A1 complex coincides with a higher DHEAS/DHEA ratio in gorilla, chimpanzee, and human. DHEAS/DHEA ratios are derived from Refs. 28 and 29. mainly driven by electrostatic and entropic binding energy terms. tion might be, we looked at all interface amino acids of SULT2A1 within an alignment of various mammalian SULT2A1 species (Fig. 7C). There we found only two interface amino acids to be specific to great apes, Thr85 and Tyr238. These amino acids were then mutated and the effects of these muta- tions were assessed by Rosetta-based alanine scanning (27). An averaged the PAPSS2–SULT2A1 complex is shown in Fig. 7A. An important feature is the composite nature of the PAPSS2-binding site, both subunits contribute to the interac- tion interface (Fig. 7B). To determine how general this interac- Color coding as in A, except the two PAPSS1 dimeric subunits, which are gray and black. C and D, statistical analysis of all ClusPro docking experiments, looking from the PAPS synthase side (C) and from the SULT2A1 side (D). Frequency of individual residues within 3 Å of the other protein was analyzed for PDB 1EFH, 3F3Y, and 4IFB structures separately (30 dockings each) and then averaged. Note the higher number of frequent protein con- tacts within the APS kinase domain of PAPSS2, compared with the one from PAPSS1. SULT2A1 contacted PAPS synthases mainly via its isoform-specific substrate binding loops; one of these is regarded as “cap.” Figure 6. The PAPSS2–SULT2A1 interaction may be isoform-specific. A, SULT2B1 was selected as homologous sulfotransferase to analyze specificity of the novel PAPSS2–sulfotransferase interaction. PAPS synthase–sulfurylase docking was refined using RosettaDock. At least 10,000 docking experiments are shown where the docking score was correlated with the interface r.m.s. deviation value compared with the average complex. B, best solutions from Rosetta were subjected to MD simulations (3  20 ns, see Fig. S2 for averaged traces); MM-PBSA energies were derived therefrom, expressed as average  S.D. from three independent calculations. an equilibrium state within the simulation time window (Fig. S2), indicating that energy calculations were appropriate. Free energy MM-PBSA calculations for all four complexes are shown in Fig. 6B, van der Waals energies, polar solvation, and SASA energy terms are roughly the same for all four combina- tions. However, an electrostatics term of 1040 kJ/mol for PAPSS2–SULT2A1 shows that electrostatics favor this interac- tion; this energy term is about twice as high as those for PAPSS1–SULT2A1 and PAPSS2–SULT2B1; PAPSS1–SULT2B1 is characterized by an even smaller electrostatics term (Fig. 6B). Binding energies strongly favor PAPSS2 interactions over PAPSS1 interactions, with both sulfotransferases (Fig. 6B). Taken together, the interaction of PAPSS2 and SULT2A1 is To explore isoform specificity also for the sulfotransferase, we repeated the entire docking procedure with the sulfotrans- ferase SULT2B1 most closely related to SULT2A1 (51% amino acid identity). Although PAPSS1 docking gave similar ensem- bles both for SULT2A1 and SULT2B1, the PAPSS2–SULT2B1 pairing only gave nonpreferable scores (Fig. 6A). Best-scoring complexes from each of these combinations were subjected to molecular dynamics simulations. R.m.s. deviation trajectories showed that all these complexes are stable and converge toward 9728 J. Biol. Chem. Discussion at The University of Birmingham on September 5, 2018 http://www.jbc.org/ Downloaded from Our knockdown studies of sulfation pathway enzymes in human adrenal NCI-H295R1 cells, an established model of the adrenal zona reticularis, the main site of DHEA sulfation by SULT2A1, provide experimental evidence for a functional dif- ference of PAPS synthases in the DHEA sulfation pathway. PAPSS2 seems to be better able to support the sulfotransferase SULT2A1 than its enzyme ortholog PAPSS1. Deviations in cat- alytic properties or subcellular localization are not sufficient to explain the leading role of PAPSS2 in this sulfation pathway. By employing PLAs, we could detect a transient protein–protein interaction between PAPS synthases and SULT2A1. The aver- age number of foci per cell was significantly higher for PAPSS2 than for PAPSS1, indicative of a stronger interaction. Further- more, molecular docking suggested a specific interaction of SULT2A1 with the APS kinase domain of PAPSS2, whereas analogous docking studies with PAPSS1 suggested a more dif- fuse interaction pattern. This transient protein–protein inter- action provides the mechanistic basis for the observed func- tional differences between PAPSS1 and PAPSS2 with regard to sulfation of DHEA by SULT2A1, a critical step in controlling biosynthesis of active androgens in humans. at The University of Birmingham on September 5 http://www.jbc.org/ Downloaded from A striking feature of the PAPSS2 interface with SULT2A1 is its composite nature (Fig. 7, A and B). Within the PAPSS2 dimer, the N terminus of the distant subunit swaps over to form the SULT2A1-binding site together with residues from the proximal subunit, initially seen crystallographically for PAPSS1 (38). Then it was observed in protein dissociation/association studies using fluorescently labeled PAPS synthases, PAPSS2 adopts this conformation about 2.5-fold quicker than PAPSS1 (20). An N terminally-truncated PAPSS1 protein, however, does not show any different catalytic properties compared with WT (38); parts of the protein responsible for quinary protein interactions are obviously dispensable for the primary catalytic function, as previously described for other quinary interactions (34). This N-terminal peptide shows large displacement values within the r.m.s. fluctuations calculations over the MD simula- tion time (Table S3), indicating that its flexibility may play a role for the PAPSS–SULT2A1 interaction; these r.m.s. fluctuation values are also higher in PAPSS2 than in PAPSS1. The protein–protein interaction described here is a novel regulatory mechanism to confer directionality to sulfation pathways (Fig. 7). DHEA sulfation and PAPSS2–SULT2A1 interaction transient and isoform-specific interaction highly relevant for a functioning sulfation pathway. Although the Y238F mutation only moderately compromised the stability of the PAPSS2–SULT2A1 complex, the T85K mutant destabilized the complex by more than 22 kJ/mol (Fig. 7D). Furthermore, the double mutation also induced secondary destabilizing effects at Asn17 (12 kJ/mol) as well as Arg166 and Ile172 (5 kJ/mol each). We concluded that the PAPSS2– SULT2A1 interaction was facilitated by amino acid exchanges that only occurred in hominids. It thus correlates with the higher DHEAS/DHEA ratios found in gorilla, chimpanzee, and human (28), but not in other nonhominid primates or other mammals (29, 30). In the crowded and complex environment of the living cell, proteins tend to form higher-order, transient protein–protein interactions (34), mostly remaining unnoticed or at least very hard to study (35). These have been termed “quinary interac- tions” (34), originally linked to an apparent conservation of iso- electric points among homologous proteins (36). The two human PAPS synthases PAPSS1 and PAPSS2 show very differ- ent isoelectric points, 6.40 and 8.18, respectively (Table S4). Taking the pI of SULT2A1 (pI  5.69) into account, a more acidic (lower) value than most of the other cytoplasmic SULTs (Table S4), a transient interaction between PAPSS2 and SULT2A1, driven mainly by electrostatic interactions, is in good agreement with what our MM-PBSA free energy calcula- tions show (Fig. 6B). Counterintuitively, the PAPSS2 residues at the SULT2A1 interface are mainly conserved in PAPSS1 (Table S3). This suggests that the difference between PAPS synthase isoforms may be caused by residues outside the protein inter- face, possibly in the second or even third shell of the protein (37). 9729 J. Biol. Chem. (2018) 293(25) 9724–9735 9729 DHEA sulfation and PAPSS2–SULT2A1 interaction DHEA sulfation and PAPSS2–SULT2A1 interaction more of it would be needed for intracellular stabilization of PAPSS2; making stabilization of PAPSS2 by a quinary interac- tion a likely alternative. SULT1A3/4 genes have only been found in higher primates (New World monkeys, Old World monkeys, great apes, and humans) so far (32, 51), suggesting a strong evolutionary drive to develop this particular capacity specifically in higher primates. Similar to this finding, the current study about hominoid-specific facilitated DHEA sulfation may be rele- vant for the validity of animal models of steroid sulfation with significant implications for drug development relying on the predictive quality of animal models. Soluble sulfotransferases are believed to form dimers via an unusually small binding interface spanning only 10 residues, known as the KTVE motif (39), whereas dimer formation of Golgi-localized sulfotransferases is mainly guided by their stem regions (40, 41). Notably, dimer formation was reported to be beneficial for sulfotransferase protein stability (42). This pre- sumably “sticky” motif did not interfere with our docking experiments; it was never found to be enriched at the PAPSS2– SULT2A1 protein interface. In fact, the KTVE motif merges into the PAPS-binding loop on the other side of the sulfotrans- ferase molecule (43). Comparing trajectories of MD simula- tions has been used in the past to approximate protein stability (44, 45). The SULT2A1 MD trajectory for the PAPSS2– SULT2A1 simulation certainly differs from the corresponding PAPSS1 complex; suggesting the SULT2A1 molecule reaching a stable state sooner (1 ns) in the presence of PAPSS2 than PAPSS1 (Fig. S2). Furthermore, the average r.m.s. deviation of SULT2A1 stays at around 3 Å in the presence of PAPSS2, but further increases with PAPSS1. The presence of PAPSS2 seem- ingly stabilizes the SULT2A1 protein. Sulfotransferases feature three major substrate-binding “loops” based on early structural characterization and sequence alignments (46, 47). For SULT2A1, these would include Asp62–Arg74, Ser80–Gly83, and Glu207–Ser251; however, most of these residues are within well- defined secondary structure elements. In the three SULT2A1 crystal structures that we used for the present study (PDB codes 1EFH, 3F3Y, and 4IFB), a better description of the substrate- binding site are the loops Pro14–Ser20, Glu79–Ile82, and Asn136–Lys144 as well as the extended Tyr231–Gln244 loop that covers the binding pocket (43). These substrate-binding loops harbor all PAPSS2-contacting amino acids, except Glu73 and Glu89. Discussion This might be of most relevance in tissues where both PAPS synthases are present at roughly similar levels and where SULT2A1 is co-expressed with other cytoplasmic sulfotransferases. The first condition is met in the adrenocorti- cal NCI-H295R1 cell line of which we started, assuming our real-time CT values roughly correlate with protein levels, we had nearly identical PAPSS1 and PAPSS2 mRNA levels and about 5-fold higher levels for SULT2A1 mRNA (Table S1). Condition 2 is basically fulfilled in any of the tissues where SULT2A1 is expressed: it is found strongly enriched in adrenal cortex, duodenum, liver, and small intestine (31, 32). In all these tissues, transcript abundance of SULT2A1 is higher than that of PAPS synthases (31) and another sulfotransferase, SULT1A1, is considerably co-expressed (31). In fact, cytoplasmic sulfotrans- ferases are generally highly abundant, up to about 1% of total soluble protein (“cytosolic fraction”) of intestine tissue was reported to consist of the SULT enzymes SULT1A1/1A3, -1B1, -2A1, and -1E1 (32); corresponding to 20–30 M sulfotrans- ferase proteins. This means that there are many more PAPS- utilizing enzymes than PAPS synthases and sulfotransferases may even outnumber the PAPS cofactor itself (33), making a g Analyzing RMSF data allows assessing the effect of the novel PAPSS2–SULT2A1 protein interaction on the PAPS synthase. Within dimeric PAPSS2, nearly all 61 residues at the SULT2A1 interface show lower r.m.s. fluctuation values in the proximity to the sulfotransferase, compared with the corresponding amino acid in the distant PAPS synthase subunit (Table S3), which can be interpreted as stabilizing the otherwise fragile protein (4). In the past, PAPS synthases have been purported to have vastly differing specific activities (19), which actually was only a 5-fold difference in kcat/Km values when treating bi-func- tional PAPS synthases as Michaelis-Menten enzymes. For APS kinase, which catalyzes the rate-limiting step in overall PAPS biosynthesis, we did not observe this difference previously (20) nor in the present study (Fig. 2A). Using fluorescently labeled APS, we determined binding affinity of this nucleotide to PAPS synthases that theoretically have six APS-binding sites per pro- tein dimer. This apparent KD of APS is somewhat larger for PAPSS2 (meaning APS binds less tightly) than for PAPSS1. APS was described as a modulator of PAPS synthase function (6) and 9730 730 J. Biol. Chem. (2018) 293(25) 9724–9735 Materials and methods Cell culture Adrenal NCI-H295R1 cells (kindly provided by Enzo Lalli, Nice, France) were grown in Dulbecco’s modified Eagle’s medi- um/F-12 (Gibco, Thermo Fisher, Waltham, MA) supple- mented with 2.5% Nu-Serum, 1% ITS premix, and 1% peni- cillin/streptomycin at 37 °C and 5% CO2. HEK293 cells were propagated in minimal essential medium (Sigma) with 10% FCS (PAA, GE Healthcare) and 1% penicillin/streptomycin (PAA, GE Healthcare). HepG2 cells were maintained in RPMI (Invit- rogen, Karlsruhe, Germany) with 10% FBS (Gibco, Thermo Fisher) and 1% antibiotic-antimycotic (Gibco, Thermo Fisher) in a humidified 5% CO2 atmosphere at 37 °C as recommended by the American Type Culture Collection (ATCC). All cells were verified to be mycoplasma-negative by PCR in regular intervals. Recent amino acid exchanges within the substrate-binding loops of SULT2A1 may make the PAPSS2–SULT2A1 interac- tion specific to hominid primates only (Fig. 7) and this coin- cides with significantly higher DHEAS/DHEA rates in the cir- culation in anthropoid primates (28), contrasted to other primates and other mammals (29, 30). Adaptive changes in anthropoid proteomes have also been described for other genes (49). One of these is another sulfotransferase, SULT1A3, with a glutamic acid Glu146 within the substrate- binding site making it a preferential catecholamine-sulfating enzyme (50). SULT1A3 (and a duplicated gene named SULT1A4 encoding the same protein) is the only sulfotrans- ferase to have an acidic amino acid in this position. Knockdown by siRNA in adrenal NCI-H295R1 cells Adrenal NCI-H295R1 cells were transfected with the follow- ing siRNA oligonucleotides (target (mRNA position) RNA sequence (sense strand 5 to 3)): PAPSS1 (309) CCU GGU UUG UCA UGG UAU U; (419) GCA UCG CAG AAG UUG CUA A; (1380) GCA GGA UAC CCA UAA GCA A; PAPSS2, (612) CCA GCU UUA UUU CUC CAU U; (899) GCA GAA CAU UGU ACC CUA U; (1180) CCG UCU CUG CAG AGG AUA A; SULT2A1 (169) GCA UAG CUU UCC CUA CUA U; (622) GGU CAU GGU UUG ACC ACA U; (763) CCG AAG AAC UGA ACU UAA U; control, GCC ACG UAA GAU GAG UCA A; using the Viromer Blue transfection reagent (Lipoca- DHEA sulfation and PAPSS2–SULT2A1 interaction Glu89 is located on the other end of a short helix con- taining the Glu79–Ile82 motif; Glu73 is part of a helical loop spanning Ile71–Arg74 and just 5 Å apart from the substrate lith- ocholic acid in the PDB 3F3Y structure. Being located in sub- strate-binding loops, all these residues are at least 15 Å apart from the 5-phosphorous atom of the 3-phosphoadenosine- 5-phosphate (PAP) cofactor. Thus, it seems unlikely that the PAPSS2–SULT2A1 interaction facilitates cofactor transfer. Instead, allosteric activation as recently described for SULT1A1 (48) and/or protein stabilization may be the mecha- nisms responsible for increased support of DHEA sulfation. In conclusion, we have elucidated the mechanistic basis for the selective requirement for PAPSS2 in providing the sulfation cofactor PAPS to the DHEA sulfotransferase SULT2A1. This preference is explained by an isoform-specific, transient pro- tein interaction of PAPSS2 and SULT2A1. SULT2A1 mainly interacts with PAPSS2 via residues within its nonconserved substrate-binding loops. Our analyses with PAPSS2 and the closely related SULT2B1 sulfotransferase confirm that this interaction is specific to SULT2A1. Isoform specificity on the side of PAPS synthases arises from nonconserved sec- ond- and third-shell residues causing differences in protein flexibility and electrostatics. The PAPSS2–SULT2A1 inter- action stabilizes the interaction partners and may even allos- terically activate them. The current findings show a novel regulatory mechanism within sulfation pathways and deepen our understanding of PAPS synthase biochemistry; they may help to better understand clinically observed PAPSS2 muta- tions and even open new avenues to develop novel therapeu- tic targets. at The University of Birmingham on September 5 http://www.jbc.org/ Downloaded from at The University of Birmingham on September 5, 2018 http://www.jbc.org/ nloaded from e University of Birmingham on September 5, 2018 DHEA sulfation and PAPSS2–SULT2A1 interaction DHEA sulfation and PAPSS2–SULT2A1 interaction binding studies; for back-titration with label-free APS, 50 M protein was added. lyx, Halle/Saale, Germany) according to the manufacturer’s instructions. Knockdown efficiency was checked by quantita- tive PCR using the following exon-spanning gene expression assays, all TaqMan probes were labeled with 6-carboxyfluores- cein (FAM) (Life Technologies, Thermo Fisher): Hs00234219_ m1 (SULT2A1); Hs00968937_m1 (PAPSS1); and Hs00989921_ m1 (PAPSS2). Expression levels were normalized to 18S rRNA (HS99999901_s1). Protein expression was probed by West- ern blotting using the polyclonal rabbit antibody ab38416 (Abcam, Cambridge, UK) or the monoclonal mouse antibody SAB1100881 (Sigma) for SULT2A1, the mAb ab56398 (Abcam, Cambridge, UK) against PAPSS1 and the mAb ab56393 (Abcam) for PAPSS2. Equal loading was confirmed with horse- radish peroxidase-linked mAb ab20272 (Abcam) against -ac- tin. ECL (Millipore, Watford, UK) or anti-mouse ReadyTector solution (CandorBioscience, Wangen im Allga¨u, Germany) were used for detection. Overexpression of PAPS synthase variants in HEK293 cells PAPS synthase protein variants with preferred nuclear or cytoplasmic localization have been described previously (18). Mutating K9A,K10A in PAPSS1 or K6A,K8A in PAPSS2 dis- rupts a conserved nuclear localization signal and results in pref- erential cytoplasmic localization. Changing R111A,R112A in PAPSS1 or R101A,R102A in PAPSS2, on the other hand, inac- tivates a motif with nuclear export signal activity, resulting in pronounced nuclear accumulation (18). Coding sequences for all these protein variants without stop codons were NheI/ BamHI inserted in the eukaryotic expression vector pEGFP-N1 with a C-terminal EGFP fusion. HEK293 cells were transiently co-transfected with these plasmids and a SULT2A1 expression vector (14) using XtremeGene HP (Sigma) according to the manufacturer’s protocol. Proximity ligation assays Interactions of sulfation pathway proteins were tested for by PLA technology. Human HepG2 cells were grown, fixed, blocked, and permeabilized as described above. Cells were then incubated overnight at 4 °C with primary antibodies specific for PAPSS1 or PAPSS2 (both from Abcam) and SULT2A1 (Sigma) diluted 1:200 in PBS containing 1% BSA (Carl Roth, Karlsruhe, Germany) and 0.3% Triton X-100. PLA was conducted using the Duolink In Situ PLA probes and detection reagents (Sigma), following the instructions of the manufacturer. DNA was stained with Hoechst 33342 (AppliChem, Darmstadt, Ger- many) in PBS for 15 min at room temperature; entire cells were stained with HCS CellMask Deep Red Stain (Life Technologies, Thermo Fisher) in PBS for 15 min at room temperature. Images were taken with a Leica SP8 confocal microscope equipped with a HCX PL Apo CS 63.0  1.20 water UV objective, a sen- sitive hybrid detector and Diode 405, Argon and DPSS561 lasers, and further analyzed with CellProfiler (52, 53). We noticed that the overall intensity of the PLA signal inversely correlated with cell density: when grown more densely, lower PLA signal intensities were observed. However, cell density did not affect foci number. J. Biol. Chem. (2018) 293(25) 9724–9735 9731 Immunofluorescence For immunofluorescence staining, human HepG2 cells were seeded in 35-mm glass bottom dishes (MatTek, Ashland, MA). Cells were fixed with 4% Histofix (Carl Roth, Karlsruhe, Ger- many) for 20 min at room temperature, followed by blocking and permeabilization with PBS containing 5% normal serum (Dako, Glostrup, Denmark) and 0.3% Triton X-100 (Appli- Chem, Darmstadt, Germany). Immunostaining was performed overnight at 4 °C with primary antibodies specific for PAPSS1 or PAPSS2 (both Abcam, Cambridge, UK) and SULT2A1 (Sigma) diluted 1:200 in PBS containing 1% BSA (Carl Roth, Karlsruhe, Germany) and 0.3% Triton X-100. Following several washing steps, secondary antibodies labeled with Alexa Fluor 488 and Alexa Fluor 568 (Life Technologies, Thermo Fisher) were incubated for 1 h at room temperature. DNA was stained with Hoechst 33342 (AppliChem, Darmstadt, Germany) in PBS for 15 min at room temperature. Images (Fig. S1B) were taken with a Leica SP8 confocal microscope equipped with a HCX PL Apo CS 63.0  1.20 water UV objective, a sensitive hybrid detector and Diode 405, Argon and DPSS561 lasers (Leica, Wetzlar, Germany). at The University of Birmingham on September 5, 201 http://www.jbc.org/ Downloaded from Enzymatic assays The functionality of the DHEA sulfation pathway was assessed by DHEA sulfation assays. NCI-H295R1 cells were incubated with 250 nM DHEA and 0.2 Ci of [3H]DHEA for 2 h at 37 °C; all assays were performed in triplicate. Steroids were extracted as previously described (13, 14), analyzed on a Lab- logicAR2000 bioscanner, and identified by referring to simul- taneously run labeled steroid standards. Sulfation activity after transfection of scrambled control oligonucleotides was set to 100% activity. APS kinase activity was measured according to the STRENDA convention as previously described (4, 20). Briefly, ADP produced in the APS kinase-catalyzed reaction was used by pyruvate kinase to convert phosphoenolpyruvate to pyruvate. This is then converted by lactate dehydrogenase to lactate. The concurrent conversion of NADH to NAD is fol- lowed spectrophotometrically at 340 nm. APS kinase assays were carried out at 20 mM Tris-HCl, pH 7.3, 100 mM KCl, 5 mM DTT, 2.5 mM ATP, 15 M APS, 10 mM MgCl2, 17.5/25 units of LDH/protein kinase mix, 2 units of nuclease P1, 0.8 mM phos- phoenolpyruvate, 0.3 mM NADH, 30 g/ml of PAPS. For APS ligand binding studies, mant-APS was obtained from Jena Bio- science (Jena, Germany) where an N-methylanthraniloyl fluo- rophore was esterified to the (2,3)-hydroxyl of the ribose moi- ety. Mant-APS was at a concentration of 1 M for protein Structural analysis and molecular docking H., J. v. d. B., V. D., S. K. K., E. R., and W. A. writ- ing-review and editing; T. F. G. software; C. V., J. v. d. B., V. D., S. K. K., and E. R. validation. Acknowledgments—We thank Enzo Lalli (CNRS, Valbonne, France) for kindly providing adrenal NCI-H295R1 cells. We acknowledge the help of Joanne C. McNelis and Ian T. Rose with early stages of the work. Barbara Torlinska is acknowledged for statistical advice. We thank Alessandro Prete and David Jeevan for critical reading of the final manuscript (all University of Birmingham, UK). S. K. K. and C. V. acknowledge the use of the imaging equipment and the support in microscope usage and image analysis by the Imaging Centre Cam- pus Essen (ICCE), Centre for Medical Biotechnology (ZMB), Univer- sity of Duisburg-Essen, Germany. at The University of Birmingham on September 5, 20 http://www.jbc.org/ Downloaded from at The University of Birmingham on September 5, 2018 http://www.jbc.org/ Downloaded from at The University of Birmingham http://www.jbc.org/ Downloaded from For each PAPS synthase/sulfotransferase system, MD simu- lations were run as the following. The protein complex was inserted in a dodecahedric box of TIP3P water molecules ensuring a minimum distance to the box edges of 10 Å. The proper amount of Na and Cl ions was added to reach an ionic concentration of 150 mM and ensure final neutral systems. A steepest-descent minimization was applied to relax the solvent molecules around the solute. The equilibration was performed in two steps: the system was at first thermalized up to 300 K coupling the protein and the solvent to a V-rescale thermostat (t  0.1 ps) in the canonical ensemble (NVT). Then, we switched to the NPT statistical ensemble, performing 100 ps of MD at 300 K, coupling the system with a Parrinello-Rahman barostat (p  2 ps). After this initial phase, the system was submitted for production MD simulations. Production runs were carried out in the NPT (p  1 bar, T  300 K) statistical ensemble. All bonds were constrained with LINCS (55), allow- ing to use a time step set of 2 fs. Periodic boundary conditions were applied to the systems in all directions. The PME method was used to evaluate long-range electrostatic interactions (PME order  4, Fourier spacing  0.12), and a cutoff of 10 Å was used to account for the van der Waals interactions. Structural analysis and molecular docking Full all-atom models of PAPSS1 and PAPSS2 were built with the MMMserver (54) using the crystal structures of both the isolated kinase domain and an APS complex of full-length PAPSS1 (PDB 2OFX and 1XNJ, respectively). Homology build- ing also for PAPSS1 ensured that we used comparable struc- tures of PAPSS1 and PAPSS2 coherently throughout this study. To elucidate the binding sites and investigate the mode of bind- ing, these optimized models of both PAPSS1 and PAPSS2 were docked to three different SULT2A1 structures (PDB codes 9732 732 J. Biol. Chem. (2018) 293(25) 9724–9735 DHEA sulfation and PAPSS2–SULT2A1 interaction 3F3Y, 4IFB, and 1EFH) and to SULT2B1 (PDB code 1Q1Q) by the rigid-body protein–protein docking software ClusPro. PAPS synthase and sulfotransferase structures were submitted as receptor and ligand, respectively, to the ClusPro protein– protein docking server using default settings (24). The top 1000 lowest energy-docking poses of aforementioned complexes are grouped into 30 clusters and the lowest energy poses of each cluster form the final 30 docking poses. Docking results were scored using the standard ClusPro “balanced docking score,” where all electrostatic, hydrophobic, and van der Waals Elec coefficients are taken into account. All 30 ClusPro poses where further filtered by populating the top amino acid contacts within all complex structures. To analyze the involvement of each amino acid in the protein–protein interaction interfaces, we calculated the prevalence of interface interactions for the receptor PAPSS residues with contacts made to the ligand SULTs in all dockings. Author contributions—J. W. M. and W. A. conceptualization; J. W. M., S. K. K., and W. A. resources; J. W. M., J. I., T. F. G., C. V., R. H., and J. v. d. B. data curation; J. W. M., J. I., T. F. G., C. V., R. H., J. v. d. B., V. D., S. K. K., E. R., and W. A. formal analysis; J. W. M., V. D., S. K. K., E. R., and W. A. supervision; J. W. M. and W. A. fund- ing acquisition; J. W. M., J. I., R. H., and J. v. d. B. investigation; J. W. M., T. F. G., C. V., and S. K. K. visualization; J. W. M., J. I., C. V., J. v. d. B., S. K. K., and E. R. methodology; J. W. M. writing-original draft; J. W. M. and W. A. project administration; J. W. M., J. I., T. F. G., C. V., R. References 1. Strott, C. A. (2002) Sulfonation and molecular action. Endocr. Rev. 23, 703–732 CrossRef Medline 2. Mueller, J. W., Gilligan, L. C., Idkowiak, J., Arlt, W., and Foster, P. A. (2015) The regulation of steroid action by sulfation and desulfation. Endocr. Rev. 36, 526–563 CrossRef Medline 3. Herrero, J., Muffato, M., Beal, K., Fitzgerald, S., Gordon, L., Pignatelli, M., Vilella, A. J., Searle, S. M., Amode, R., Brent, S., Spooner, W., Kulesha, E., Yates, A., and Flicek, P. (2016) Ensembl comparative genomics resources. Database (Oxford) 2016, pii:baw053 Medline 4. van den Boom, J., Heider, D., Martin, S. R., Pastore, A., and Mueller, J. W. (2012) 3-Phosphoadenosine 5-phosphosulfate (PAPS) synthases, natu- rally fragile enzymes specifically stabilized by nucleotide binding. J. Biol. Chem. 287, 17645–17655 CrossRef Medline 4. van den Boom, J., Heider, D., Martin, S. R., Pastore, A., and Mueller, J. W. (2012) 3-Phosphoadenosine 5-phosphosulfate (PAPS) synthases, natu- rally fragile enzymes specifically stabilized by nucleotide binding. J. Biol. Chem. 287, 17645–17655 CrossRef Medline 5. Kauffman, F. C. (2004) Sulfonation in pharmacology and toxicology. Drug Metab. Rev. 36, 823–843 CrossRef Medline 6. Mueller, J. W., and Shafqat, N. (2013) Adenosine-5-phosphosulfate: a multifaceted modulator of bifunctional 3-phosphoadenosine-5-phos- phosulfate synthases and related enzymes. FEBS J. 280, 3050–3057 CrossRef Medline 6. Mueller, J. W., and Shafqat, N. (2013) Adenosine-5-phosphosulfate: a multifaceted modulator of bifunctional 3-phosphoadenosine-5-phos- phosulfate synthases and related enzymes. FEBS J. 280, 3050–3057 CrossRef Medline 7. Lipmann, F. (1958) Biological sulfate activation and transfer. Science 128, 575–580 CrossRef Medline 7. Lipmann, F. (1958) Biological sulfate activation and transfer. Science 128, 575–580 CrossRef Medline 8. Ahmadian, A., Ehn, M., and Hober, S. (2006) Pyrosequencing: history, biochemistry and future. Clin. Chim. Acta 363, 83–94 CrossRef Medline 8. Ahmadian, A., Ehn, M., and Hober, S. (2006) Pyrosequencing: history, biochemistry and future. Clin. Chim. Acta 363, 83–94 CrossRef Medline 9. Chan, K. X., Mabbitt, P. D., Phua, S. Y., Mueller, J. W., Nisar, N., Gigolas- hvili, T., Stroeher, E., Grassl, J., Arlt, W., Estavillo, G. M., Jackson, C. J., and Pogson, B. J. (2016) Sensing and signaling of oxidative stress in chloro- plasts by inactivation of the SAL1 phosphoadenosine phosphatase. Proc. Natl. Acad. Sci. U.S.A. 113, E4567–E4576 CrossRef Medline Structural analysis and molecular docking Coordinates of the systems were collected every 2 ps. All MD simulations were carried out with GROMACS-5 using the Gromos 53A6 force field on GPU/CPU machines. The length of the MD simula- tions was 20 ns, and standard MD were used for MM-PBSA and for all analysis. Binding free energy were calculated using the GROMACS tool g_mmpbsa (56). Data analysis Enzyme kinetics and titration data were analyzed and visual- ized using GraphPad Prism. Densitometric analysis of bands on Western blots was carried out with GelAnalyzer. Visualization of protein structures and structural models was done in PyMol, VMD, and YASARA. Normality of any data were checked for by visual inspection of histogram plots as well as with Ryan-Joiner and D’Agostino-Person tests. Pairwise and multiple compari- sons of normally distributed data were done with two-tailed unpaired t tests and one-way ANOVA as well as post hoc Bon- ferroni tests, respectively. All statistical analyses were carried out with the Analysis ToolPak-VBA (Microsoft) or Minitab 17. 10. Hudson, B. H., and York, J. D. (2012) Roles for nucleotide phosphatases in sulfate assimilation and skeletal disease. Adv. Biol. Regul. 52, 229–238 CrossRef Medline 11. Patron, N. J., Durnford, D. G., and Kopriva, S. (2008) Sulfate assimilation in eukaryotes: fusions, relocations and lateral transfers. BMC Evol. Biol. 8, 39 CrossRef Medline 12. Lansdon, E. B., Fisher, A. J., and Segel, I. H. (2004) Human 3-phosphoad- enosine 5-phosphosulfate synthetase (isoform 1, brain): kinetic proper- ties of the adenosine triphosphate sulfurylase and adenosine 5-phospho- sulfate kinase domains. Biochemistry 43, 4356–4365 CrossRef Medline 12. Lansdon, E. B., Fisher, A. J., and Segel, I. H. (2004) Human 3-phosphoad- enosine 5-phosphosulfate synthetase (isoform 1, brain): kinetic proper- ties of the adenosine triphosphate sulfurylase and adenosine 5-phospho- sulfate kinase domains. Biochemistry 43, 4356–4365 CrossRef Medline DHEA sulfation and PAPSS2–SULT2A1 interaction 367, 488–500 CrossRef Medlin 22. Weibrecht, I., Leuchowius, K. J., Clausson, C. M., Conze, T., Jarvius, M., Howell, W. M., Kamali-Moghaddam, M., and So¨derberg, O. (2010) Prox- imity ligation assays: a recent addition to the proteomics toolbox. Expert Rev. Proteomics 7, 401–409 CrossRef Medline 39. Weitzner, B., Meehan, T., Xu, Q., and Dunbrack, R. L., Jr. (2009) An unusually small dimer interface is observed in all available crystal structures of cytosolic sulfotransferases. Proteins 75, 289–295 CrossRef Medline am on Septem 40. Goettsch, S., Badea, R. A., Mueller, J. W., Wotzlaw, C., Schoelermann, B., Schulz, L., Rabiller, M., Bayer, P., and Hartmann-Fatu, C. (2006) Human TPST1 transmembrane domain triggers enzyme dimerisation and locali- sation to the Golgi compartment. J. Mol. Biol. 361, 436–449 CrossRef Medline mber 5, 2018 23. Sundqvist, A., Zieba, A., Vasilaki, E., Herrera Hidalgo, C., So¨derberg, O., Koinuma, D., Miyazono, K., Heldin, C. H., Landegren, U., Ten Dijke, P., and van Dam, H. (2013) Specific interactions between Smad proteins and AP-1 components determine TGF-induced breast cancer cell invasion. Oncogene 32, 3606–3615 CrossRef Medline 41. Nagai, N., Habuchi, H., Esko, J. D., and Kimata, K. (2004) Stem domains of heparan sulfate 6-O-sulfotransferase are required for Golgi localization, oligomer formation and enzyme activity. J. Cell Sci. 117, 3331–3341 CrossRef Medline 24. Kozakov, D., Hall, D. R., Xia, B., Porter, K. A., Padhorny, D., Yueh, C., Beglov, D., and Vajda, S. (2017) The ClusPro web server for protein-pro- tein docking. Nat. Protoc. 12, 255–278 CrossRef Medline 25. Gray, J. J., Moughon, S., Wang, C., Schueler-Furman, O., Kuhlman, B., Rohl, C. A., and Baker, D. (2003) Protein-protein docking with simultane- ous optimization of rigid-body displacement and side-chain conforma- tions. J. Mol. Biol. 331, 281–299 CrossRef Medline 42. Lu, L. Y., Chiang, H. P., Chen, W. T., and Yang, Y. S. (2009) Dimerization is responsible for the structural stability of human sulfotransferase 1A1. Drug Metab. Dispos. 37, 1083–1088 CrossRef Medline g 43. Pedersen, L. C., Petrotchenko, E. V., and Negishi, M. (2000) Crystal struc- ture of SULT2A3, human hydroxysteroid sulfotransferase. FEBS Lett. 475, 61–64 CrossRef Medline 26. Sircar, A., Chaudhury, S., Kilambi, K. P., Berrondo, M., and Gray, J. J. (2010) A generalized approach to sampling backbone conformations with RosettaDock for CAPRI rounds 13–19. Proteins 78, 3115–3123 CrossRef Medline 44. Knapp, B., Frantal, S., Cibena, M., Schreiner, W., and Bauer, P. DHEA sulfation and PAPSS2–SULT2A1 interaction 29. Feher, T., Bodrogi, L., Feher, K. G., Poteczin, E., and Kolcsey, I. S. (1977) Free and solvolysable dehydroepiandrosterone and androste- rone in blood of mammals under physiological conditions and follow- ing administration of dehydroepiandrosterone. Acta Endocrinol. (Co- penh) 85, 126–133 Medline 13. Noordam, C., Dhir, V., McNelis, J. C., Schlereth, F., Hanley, N. A., Krone, N., Smeitink, J. A., Smeets, R., Sweep, F. C., Claahsen-van der Grinten, H. L., and Arlt, W. (2009) Inactivating PAPSS2 mutations in a patient with premature pubarche. N. Engl. J. Med. 360, 2310–2318 CrossRef Medline 14. Oostdijk, W., Idkowiak, J., Mueller, J. W., House, P. J., Taylor, A. E., O’Reilly, M. W., Hughes, B. A., de Vries, M. C., Kant, S. G., Santen, G. W., Verkerk, A. J., Uitterlinden, A. G., Wit, J. M., Losekoot, M., and Arlt, W. (2015) PAPSS2 deficiency causes androgen excess via impaired DHEA sulfation: in vitro and in vivo studies in a family harboring two novel PAPSS2 mutations. J. Clin. Endocrinol. Metab. 100, E672–E680 CrossRef Medline 30. Schuler, G., Sa´nchez-Guijo, A., Hartmann, M. F., and Wudy, S. A. (2018) Simultaneous profiles of sulfonated androgens, sulfonated estrogens and sulfonatedprogestogensinpostpubertalboars(susscrofadomestica)mea- sured by LC-MS/MS. J. Steroid Biochem. Mol. Biol. 179, 55–63 Medline 31. Fagerberg, L., Hallstro¨m, B. M., Oksvold, P., Kampf, C., Djureinovic, D., Odeberg, J., Habuka, M., Tahmasebpoor, S., Danielsson, A., Edlund, K., Asplund, A., Sjo¨stedt, E., Lundberg, E., Szigyarto, C. A., Skogs, M., et al. (2014) Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics. Mol. Cell Proteomics 13, 397–406 CrossRef Medline 15. Faiyaz ul Haque, M., King, L. M., Krakow, D., Cantor, R. M., Rusiniak, M. E., Swank, R. T., Superti-Furga, A., Haque, S., Abbas, H., Ahmad, W., Ahmad, M., and Cohn, D. H. (1998) Mutations in orthologous genes in human spondyloepimetaphyseal dysplasia and the brachymorphic mouse. Nat. Genet. 20, 157–162 CrossRef Medline 32. Riches, Z., Stanley, E. L., Bloomer, J. C., and Coughtrie, M. W. (2009) Quantitative evaluation of the expression and activity of five major sulfo- transferases (SULTs) in human tissues: the SULT “pie.” Drug Metab. Dis- pos. 37, 2255–2261 CrossRef Medline 16. Ka¨lsch, J., Bechmann, L. P., Heider, D., Best, J., Manka, P., Ka¨lsch, H., Sowa, J. P., Moebus, S., Slomiany, U., Jo¨ckel, K. H., Erbel, R., Gerken, G., and Canbay, A. (2015) Normal liver enzymes are correlated with severity of metabolic syndrome in a large population based cohort. Sci. Rep. 9733 J. Biol. Chem. (2018) 293(25) 9724–9735 DHEA sulfation and PAPSS2–SULT2A1 interaction 5, 13058 CrossRef Medline at The University of Birmingham on September 5, 2018 http://www.jbc.org/ Downloaded from pos. 37, 2255–2261 CrossRef Medline 33. Wang, T., Cook, I., and Leyh, T. S. (2014) 3-Phosphoadenosine 5-phos- phosulfate allosterically regulates sulfotransferase turnover. Biochemistry 53, 6893–6900 CrossRef Medline 17. Besset, S., Vincourt, J. B., Amalric, F., and Girard, J. P. (2000) Nuclear localization of PAPS synthetase 1: a sulfate activation pathway in the nu- cleus of eukaryotic cells. FASEB J. 14, 345–354 CrossRef Medline 34. Cohen, R. D., and Pielak, G. J. (2017) A cell is more than the sum of its (dilute) parts: a brief history of quinary structure. Protein Sci. 26, 403–413 CrossRef Medline 18. Schro¨der, E., Gebel, L., Eremeev, A. A., Morgner, J., Grum, D., Knauer, S. K., Bayer, P., and Mueller, J. W. (2012) Human PAPS synthase isoforms are dynamically regulated enzymes with access to nucleus and cytoplasm. PLoS ONE 7, e29559 CrossRef Medline 35. Matena, A., Sinnen, C., van den Boom, J., Wilms, C., Dybowski, J. N., Maltaner, R., Mueller, J. W., Link, N. M., Hoffmann, D., and Bayer, P. (2013) Transient domain interactions enhance the affinity of the mitotic regulator Pin1 toward phosphorylated peptide ligands. Structure 21, 1769–1777 CrossRef Medline 19. Fuda, H., Shimizu, C., Lee, Y. C., Akita, H., and Strott, C. A. (2002) Characterization and expression of human bifunctional 3-phospho- adenosine 5-phosphosulphate synthase isoforms. Biochem. J. 365, 497–504 CrossRef Medline 36. McConkey, E. H. (1982) Molecular evolution, intracellular organization, and the quinary structure of proteins. Proc. Natl. Acad. Sci. U.S.A. 79, 3236–3240 CrossRef Medline 20. Grum, D., van den Boom, J., Neumann, D., Matena, A., Link, N. M., and Mueller, J. W. (2010) A heterodimer of human 3-phospho-adenosine-5- phosphosulphate (PAPS) synthases is a new sulphate activating complex. Biochem. Biophys. Res. Commun. 395, 420–425 CrossRef Medline 37. Yang, G., Hong, N., Baier, F., Jackson, C. J., and Tokuriki, N. (2016) Con- formational tinkering drives evolution of a promiscuous activity through indirect mutational effects. Biochemistry 55, 4583–4593 CrossRef Medline 21. Stelzer, C., Brimmer, A., Hermanns, P., Zabel, B., and Dietz, U. H. (2007) Expression profile of Papss2 (3-phosphoadenosine 5-phosphosulfate synthase 2) during cartilage formation and skeletal development in the mouse embryo. Dev. Dyn. 236, 1313–1318 CrossRef Medline 38. Sekulic, N., Dietrich, K., Paarmann, I., Ort, S., Konrad, M., and Lavie, (2007) Elucidation of the active conformation of the APS-kinase doma of human PAPS synthetase 1. J. Mol. Biol. DHEA sulfation and PAPSS2–SULT2A1 interaction 46. Allali-Hassani, A., Pan, P. W., Dombrovski, L., Najmanovich, R., Tempel, W., Dong, A., Loppnau, P., Martin, F., Thonton, J., Edwards, A. M., Boch- karev, A., Plotnikov, A. N., Vedadi, M., and Arrowsmith, C. H. (2007) Structural and chemical profiling of the human cytosolic sulfotrans- ferases. PLos Biol. 5, e97 CrossRef Medline ferase substrate specificity. J. Biol. Chem. 274, 37862–37868 CrossRef Medline ferase substrate specificity. J. Biol. Chem. 274, 37862–37868 CrossRef Medline 51. Coughtrie, M. W. (2016) Function and organization of the human cyto- solic sulfotransferase (SULT) family. Chem. Biol. Interact. 259, 2–7 CrossRef Medline ferases. PLos Biol. 5, e97 CrossRef Medline 52. Carpenter, A. E., Jones, T. R., Lamprecht, M. R., Clarke, C., Kang, I. H., Friman, O., Guertin, D. A., Chang, J. H., Lindquist, R. A., Moffat, J., Golland, P., and Sabatini, D. M. (2006) CellProfiler: image analysis soft- ware for identifying and quantifying cell phenotypes. Genome Biol. 7, R100 CrossRef Medline 47. Hirschmann, F., Krause, F., Baruch, P., Chizhov, I., Mueller, J. W., Man- stein, D. J., Papenbrock, J., and Fedorov, R. (2017) Structural and biochem- ical studies of sulphotransferase 18 from Arabidopsis thaliana explain its substrate specificity and reaction mechanism. Sci. Rep. 7, 4160 CrossRef Medline 53. Kamentsky, L., Jones, T. R., Fraser, A., Bray, M. A., Logan, D. J., Madden, K. L., Ljosa, V., Rueden, C., Eliceiri, K. W., and Carpenter, A. E. (2011) Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software. Bioinformatics 27, 1179–1180 CrossRef Medline 48. Wang, T., Cook, I., and Leyh, T. S. (2016) Isozyme specific allosteric reg- ulation of human sulfotransferase 1A1. Biochemistry 55, 4036–4046 CrossRef Medline 49. Kessler, D., Papatheodorou, P., Stratmann, T., Dian, E. A., Hartmann- Fatu, C., Rassow, J., Bayer, P., and Mueller, J. W. (2007) The DNA binding parvulin Par17 is targeted to the mitochondrial matrix by a recently evolved prepeptide uniquely present in Hominidae. BMC Biol. 5, 37 CrossRef Medline 54. Rai, B. K., Madrid-Aliste, C. J., Fajardo, J. E., and Fiser, A. (2006) MMM: a sequence-to-structure alignment protocol. Bioinformatics 22, 2691–2692 CrossRef Medline at The University of Birmingham on September 5, 201 http://www.jbc.org/ Downloaded from at The University of Birmingham on September 5, 2018 http://www.jbc.org/ Downloaded from 55. Hess, B., Bekker, H., Berendsen, H. J., and Fraaije, J. G. (1997) LINCS: A linear constraint solver for molecular simulations. J. Comput. Chem. 18, 1463–1472 CrossRef 50. DHEA sulfation and PAPSS2–SULT2A1 interaction (2011) Is an intuitive convergence definition of molecular dynamics simulations solely based on the root mean square deviation possible? J. Comput. Biol. 18, 997–1005 CrossRef Medline 27. Barlow, K. A., O´ Conchu´r, S., Thompson, S., Suresh, P., Lucas, J. E., Hei- nonen, M., and Kortemme, T. (2018) Flex ddG: Rosetta ensemble-based estimation of changes in protein-protein binding affinity upon mutation. J. Phys. Chem. B CrossRef Medline 45. Gesteira, T. F., Pol-Fachin, L., Coulson-Thomas, V. J., Lima, M. A., Verli, H., and Nader, H. B. (2013) Insights into the N-sulfation mechanism: molecular dynamics simulations of the N-sulfotransferase domain of NDST1 and mutants. PLoS ONE 8, e70880 CrossRef Medline 28. Bernstein, R. M., Sterner, K. N., and Wildman, D. E. (2012) Adrenal an- drogen production in catarrhine primates and the evolution of adre- narche. Am. J. Phys. Anthropol. 147, 389–400 CrossRef Medline 9734 9734 J. Biol. Chem. (2018) 293(25) 9724–9735 J. Biol. Chem. (2018) 293(25) 9724–9735 9735 Wiebke Arlt Hardman, Johannes van den Boom, Vivek Dhir, Shirley K. Knauer, Edina Rosta and Jonathan W. Mueller, Jan Idkowiak, Tarsis F. Gesteira, Cecilia Vallet, Rebecca DHEA sulfotransferase SULT2A1 Human DHEA sulfation requires direct interaction between PAPS synthase 2 and doi: 10.1074/jbc.RA118.002248 originally published online May 9, 2018 2018, 293:9724-9735. J. Biol. Chem. Wiebke Arlt Hardman, Johannes van den Boom, Vivek Dhir, Shirley K. Knauer, Edina Rosta and Jonathan W. Mueller, Jan Idkowiak, Tarsis F. Gesteira, Cecilia Vallet, Rebecca DHEA sulfotransferase SULT2A1 Human DHEA sulfation requires direct interaction between PAPS synthase 2 and doi: 10.1074/jbc.RA118.002248 originally published online May 9, 2018 2018, 293:9724-9735. J. Biol. Chem. doi: 10.1074/jbc.RA118.002248 originally published online May 9, 2018 2018, 293:9724-9735. J. Biol. Chem. lerts: When this article is cited • When a correction for this article is posted • 10.1074/jbc.RA118.002248 Access the most updated version of this article at doi: at The University of Birmingham on Septem http://www.jbc.org/ Downloaded from at The University of Birmingham on September 5, 2018 http://www.jbc.org/ Downloaded from at The University of Birmingham on September 5 http://www.jbc.org/ Downloaded from DHEA sulfation and PAPSS2–SULT2A1 interaction Dajani, R., Cleasby, A., Neu, M., Wonacott, A. J., Jhoti, H., Hood, A. M., Modi, S., Hersey, A., Taskinen, J., Cooke, R. M., Manchee, G. R., and Coughtrie, M. W. (1999) X-ray crystal structure of human dopamine sul- fotransferase, SULT1A3: molecular modeling and quantitative structure- activity relationship analysis demonstrate a molecular basis for sulfotrans- 56. Kumari, R., Kumar, R., Open Source Drug Discovery Consortium, and Lynn, A. (2014) g_mmpbsa: a GROMACS tool for high-throughput MM- PBSA calculations. J. Chem. Inf. Model 54, 1951–1962 CrossRef Medline J. Biol. Chem. (2018) 293(25) 9724–9735 9735 Alerts: Alerts: When this article is cited • When a correction for this article is posted • to choose from all of JBC's e-mail alerts Click here to choose from all of JBC's e-mail alerts Click here http://www.jbc.org/content/293/25/9724.full.html#ref-list-1 This article cites 56 references, 11 of which can be accessed free at
https://openalex.org/W3014058128
https://www.frontiersin.org/articles/10.3389/fpsyg.2020.00520/pdf
English
null
The Challenge of Greening Religious Schools by Improving the Environmental Competencies of Teachers
Frontiers in psychology
2,020
cc-by
10,053
The Challenge of Greening Religious Schools by Improving the Environmental Competencies of Teachers 1 Department of Business Organization and Sociology, School of Business and Tourism, Cáceres, Spain, 2 Department of Business Organization and Sociology, School of Economics and Business Administration, University of Extremadura, Badajoz, Spain, 3 Department of Finance and Accounting, School of Business, Finance and Tourism, Cáceres, Spain Even though sacred scriptures emphasize the key role that Creation and respect for living creatures play in all religions, the so-called religious schools seem to show little interest in putting this sacred mandate into effect. To shed light on this subject, this work investigates the role of teachers in the process, focusing on their environmental competencies. Our hypotheses are tested through a structural equation model on a sample of 214 biology and religion teachers from 118 Catholic schools in Spain who voluntary participated in a survey. The research findings confirm that it is crucial that environmental competencies are developed in teachers to enable the greening of schools. Theoretical and practical implications for defining the job training of teachers in religious schools are drawn from the study. Edited by: Edited by: Radha R. Sharma, Management Development Institute, India Reviewed by: Antonio Baena Extremera, University of Granada, Spain Carmen De-Pablos-Heredero, Rey Juan Carlos University, Spain Keywords: competences, environmental threat, greening, schools, religious schools INTRODUCTION *Correspondence: Rafael Robina-Ramírez rrobina@unex.es Recently, the World Economic Forum’s Global Risks Report 2018 has warned about some of the biggest environmental threats in the near future, namely extreme weather events and natural disasters, water crises, biodiversity loss, and air and soil pollution (Hossain and Purohit, 2018). These challenging threats have previously been defined as ‘wicked problems’ (Rittel and Webber, 1973) because of the difficulties in finding optimal solutions to them (Shindler and Cramer, 1999). Specialty section: This article was submitted to Organizational Psychology, a section of the journal Frontiers in Psychology g p In the last three decades, a vast amount of literature has been published with the aim of tackling these environmental threats (Van Eijndhoven et al., 2001; Farrell and Jäger, 2006). Despite the outstanding efforts made by environmental organizations to preserve nature, it is broadly agreed that natural resources are still not used and replaced appropriately (Melkert and Vos, 2008; World Health Organization [WHO], 2013) because social, economic and environmental resources are not developed in harmony (Kates et al., 2005). Economic development and environmental needs and resources should therefore be reconciled (Kuhlman and Farrington, 2010). Received: 06 September 2019 Accepted: 04 March 2020 Published: 24 March 2020 ORIGINAL RESEARCH published: 24 March 2020 doi: 10.3389/fpsyg.2020.00520 Keywords: competences, environmental threat, greening, schools, religious schools Citation: Robina-Ramírez R, Sánchez-Hernández MI, Jiménez-Naranjo HV and Díaz-Caro C (2020) The Challenge of Greening Religious Schools by Improving the Environmental Competencies of Teachers. Front. Psychol. 11:520. doi: 10.3389/fpsyg.2020.00520 g Sustainable development has been defined and identified as the preservation of natural resources (the environmental perspective) but also as cooperation between communities (the socio-economic perspective) (Rauch, 2002). As the Brundtland Commission described, sustainable development can be developed by meeting the needs of the current times and by respecting future generations (WCED, 1987). The sustainable methodology that links economic development and the environment needs to be taught at an early stage in life. As the UNECE (2005) has March 2020 | Volume 11 | Article 520 1 Frontiers in Psychology | www.frontiersin.org Religious Schools and Environmental Education Robina-Ramírez et al. stated, ‘it is important to ensure that all pupils and students acquire appropriate knowledge of sustainable development and are aware of the impact of decisions that do not support sustainable development’ (p. 6). by reflecting on how moral issues have a positive influence on behavior (Schreiner, 2000). The process of understanding moral issues in religious schools not only provides students with feelings of affiliation and of belonging to a religion, but also produces a moral atmosphere (Francis, 1986; Flynn, 1995), which gives students a sense of direction beyond materialistic approaches to life (Ysseldyk et al., 2010). In this process of education in sustainability, schools have become the appropriate educational institutions to train new generations to use natural resources appropriately (Vare and Scott, 2007). In 1990, the government of Spain passed a national law known as the LOGSE (General Organic Law about the Education System in Spain), which introduced reforms in environmental education into the school curriculum. There is some evidence that from this time on schools in Spain have, slowly but gradually, increased their sustainability strategies for protecting the environment (Murga-Menoyo, 2009). Since the Tbilisi Declaration (UNESCO, 1977) and the UN Conference on Environment and Development (Agenda 21), knowledge, values, attitudes and practical skills have been introduced into some European countries to solve environmental problems through teaching in schools. Aligned with those international regulations, religious schools in Finland, for instance, have included ‘responsibility for the environment, well-being and a sustainable future’ in their current national curriculum (Aarnio-Linnanvuori, 2013). Citation: Likewise, Indonesian religious schools, whose aim is to produce religious individuals and responsible citizens by being self-sufficient in natural resources, have followed the same path (Parker, 2017). Similarly, regional governments have made environmental commitments to future generations by developing initiatives in sustainability such as the Basque Strategy for Sustainable Environmental Development (Government of the Basque Country, 2002) and the Plan of Education for Sustainability (Government of Cantabria, 2005). These plans include specific environmental initiatives that have already been applied in other educational institutions, such as, among others, using public transport instead of cars, or turning offlights when they are not being used, to decrease overall consumption (Shwom and Lorenzen, 2012). In Spain, the aforementioned LOGSE (1990) introduced compulsory environmental education in 1990. As a result, through Agenda 21, schools were monitored in their policies for developing initiatives toward sustainability (UN, 2009). Regions such as the Basque country, Cantabria, the Community of Madrid, Catalonia and the Balearic Islands were pioneers in defining the environmental content to be taught in schools (Murga-Menoyo, 2009). Education in sustainability is also connected with the sacred scriptures (Northcott, 2009; Delio, 2017). It is based on the experience of the natural beauty of Creation, which triggers spiritual feelings of fascination and admiration (Palmer, 2008) that are directly connected to the protection of nature (Johnson, 2002). In this regard, Christianity has inspired the principle of the stewardship of nature (Boff, 1995); from the very beginning, ‘God saw all that he had made, and it was very good’ (Gen, 1:31); in the Greek version, the word ‘good’ is ‘kalon,’ meaning beautiful. Living creatures as well as human beings were made as beautiful things in the ‘image of God’ or the very likeness of the Creator (Gen, 1:27). Among these environmental initiatives, a network of affiliated eco-schools was set up in Spain. This was called the Association for Environmental Education and Consumers (ADEAC, 2019). Nowadays, 519 schools in Spain are integrated into this non-profit organization, which implements programs from the European Foundation for Environmental Education (FEE) (Parris, 2002). As the director of this altruistic organization has recently reported to the research team working on this paper, only approximately 4% of the schools in the network are religious schools. The Two Approaches to Teaching Sustainability in Schools Religious and environmental connections (REC) exist. In the last decade, environmentalists and religious leaders have created overlapping and mixed relationships to raise environmental awareness, with the aim of protecting and preserving natural resources (Sponsel, 2012; Raven, 2016). However, the process of integrating religious rules into respectful attitudes has been complex. Citation: Thinking about the future generations of students in religious schools in Spain, the small size of that impact has driven us to find out which attributes might cause the greening of religious schools. According to Hitzhusen (2006), religious elements enhance education in sustainability because of religion’s environmental values. Likewise, religion has the potential to teach an understanding of the process of life and living creatures as an ontological gift, as an example of a respectful attitude toward nature (Farrior and Lowry, 2001). Nevertheless, to the best of our knowledge, few studies until now have highlighted the challenge of greening religious schools to face global environmental threats. This paper aims to address this challenge by studying the variables that have a positive influence on the challenge of greening religious schools to face the global environmental risk, and the role of teachers’ competencies in relation to this. Literature Review and Development of Hypotheses Taking into account what is expressed in this section, we formulate the following hypotheses: Hypothesis 2 (H2): Cross-sectional environmental competence (CEC) positively influences the connection between religious doctrine and sustainability in religious schools (REC). Hence, the justification of the importance of environmental education as a model of education in values is based on the impossibility in religious schools of maintaining a disagreement between religion, humanity and nature (Jensen and Schnack, 2006). After expressing the relationship between religious doctrine and sustainability in religious schools, we formulate the following hypothesis: Hypothesis 3 (H3): Cross-sectional environmental competence (CEC) positively influences the greening process of religious schools (GRS). Frontiers in Psychology | www.frontiersin.org Literature Review and Development of Hypotheses Current environmental damage provoked by human beings has caused a destructive model of growth in developed and developing countries, and this has been denounced by religious leaders (Pope Paul, 1971; Benedict, 2008). More recently, Pope Francis, in the encyclical letter Laudato Si, has stressed the devastating consequences of this damage not only for the The Lack of Education in Sustainability in Religious Schools Religious education in schools has traditionally addressed moral issues in order to help students to develop their own views March 2020 | Volume 11 | Article 520 Frontiers in Psychology | www.frontiersin.org 2 Religious Schools and Environmental Education Robina-Ramírez et al. environment but also for human beings, namely in worldwide poverty (Raven, 2016). 2019) if the environment is to be protected. These elements help students to be passionate about nature (Uzzell et al., 1995). An ecological culture, a system that prioritizes the relationship between humans and nature, needs to be spread across society (Boulet et al., 2015). Hence, competences in environmental education do not only give protection to the student’s own social and natural environmental safety (Hashim and Denan, 2015; Ponomarenko et al., 2016). Despite these environmental–religious statements, environmentalists and religious leaders have not yet found an amicable agreement that allows them to build one discourse upon the same values and attitudes (Biel and Nilsson, 2005), even though they share those values and attitudes (Crossman, 2011). On the religious side, rules to respect nature were set within the covenant between the Creator and the creatures (Berry, 1988), in order to shape attitudes and actions to protect and restore the environment (Tucker, 2009). From the side of environmentalists, environmental education is based on the same respectful values toward nature (Hitzhusen, 2005). To heal the disagreement with religious schools is key, not only to connecting environmental concepts and understanding why the protection of nature is part of the spiritual covenant (Dudley et al., 2009), but also for avoiding clashes and connecting sustainability and religion by efficiently using their common language (Gookin, 2002). To prioritize the connection between human beings and nature, education in sustainability has to develop systemic and holistic thinking (Lozano, 2006) to connect the environment with social and economic development (Rauch, 2002) and, as well, critical arguments to defend nature from voracious consumerism (Singseewo, 2011). Sustainability as a Cross-Sectional Competence Sustainability as a Cross-Sectional Competence Education in sustainability has currently become a challenge for schools. Schools, in particular, understand the benefits that lie between human development and the preservation of nature, and between the moral dimension of human beings and the environmental role that men and women play on earth. The purpose of education in sustainability is to develop environmental cross-sectional competences (CECs). This training should include ETP (Fien et al., 2008) as well as empirical ones (Gill and Lang, 2018; Robina-Ramírez and Medina-Merodio, 2019). It allows environmental policies to be developed that incorporate the appropriate interdisciplinary skills, competences and values to transform current society into a better environment (Heyl et al., 2013; Hofman, 2015). According to Fien et al. (2008), this interdisciplinary method should express a social-environmental model rather than a basically educational model (Vázquez and Sevillano García, 2011). This means that ‘training for action’ and ‘social and environmental change’ need to be applied inside and outside schools (Heyl et al., 2013; Collins, 2017). According to Jensen and Schnack (2006), highly educated individuals usually show moral behavior to promote their personal integrity. To preserve integrity among students, CSCs are aimed at developing knowledge, skills and rules of behavior (Loe Spanish National Education System, 2006). These competences are linked not only to social and ethical commitment (Haynes, 2002; Yildirim and Ba¸stu˘g, 2010), but also to proactive behavior (Clunies-Ross et al., 2008) that confronts the exploitation of natural resources (Mogensen and Mayer, 2005). However, according to Nekhoroshkov (2016), providing adequate knowledge for students is not sufficient to give them environmental competences. Empirical teaching and learning is based on experience, as educational policies focus not only on cognitive but also on affective processes in order to predispose students to assimilate this training (Ramos et al., 2015). ETP should also include affective emotions. There is no one-to-one correspondence between attitude and behavior unless moral emotions are included (Johnson and Manoli, 2011). Emotions, behaviors and values are deeply connected to religious and environmental education (Batson et al., 1985; Kals et al., 1999; Fletcher et al., 2005; Robina-Ramírez and Pulido Fernández, 2018). Environmental Teaching Programs (ETP) Hypothesis 1 (H1): The connection between religious doctrine and sustainability in religious schools (REC) positively influences the greening process of religious schools (GRS). Teaching environmental education in schools has played a key role in the educational process of turning young people into responsible citizens (Pascual et al., 2000). Environmental teaching programs (ETP) based on environmental policies help to transform local societies and communities (Pitoska and Lazarides, 2013; Rickenbacker et al., 2019). Sustainability as a Cross-Sectional Competence Environmental knowledge, skill and a willingness to act responsibly toward nature (Torkar and Krašovec, 2019) have to be surrounded by an environmental awareness at school (Goldman et al., 2018; Olsson et al., 2019; Sánchez-Llorens et al., Hence, teachers have to assess students’ attitudes based on the knowledge that the students have (Okur-Berberoglu, 2015), March 2020 | Volume 11 | Article 520 Frontiers in Psychology | www.frontiersin.org 3 Religious Schools and Environmental Education Robina-Ramírez et al. Hypothesis 5 (H5): Environmental teaching programs in religious schools (ETP) positively influence the greening process in religious schools (GRS). and, with the help of affective emotions, to engage with social and environmental goals for the students. As a result, knowledge and emotional and behavioral responses lead students to transform society through practical cases. Applying only traditional educational programs will only make students aware of the problem but will not show them how to act to solve environmental problems, whether these are global or local (Uzzell et al., 1995). Environmental Competencies of Teachers (ECTs) The importance of human resource (HR) qualifications for educational institutions in general and for religious schools in particular has been a recurrent theme for several years now. More concretely, teacher training has become a key issue in introducing environmental education into schools, as we have been repeatedly reminded by international organizations (UNESCO, 1977). Training has been defined as a priority in order to promote sustainability (Fien, 1995). Environmental damage to nature can be local or international. According to Ideland and Malmberg (2015), the process of environmental education in religious schools must focus on the realities of the local communities and the environmental problems at the schools themselves in order to minimize the economic and environmental impact (Afrinaldi et al., 2017). Strategies to improve environmental education in society should be carried out with the effective support of teachers (Bregeon et al., 2008), or new generations will not transform their mind-sets and take up a respectful attitude to nature (Madhawa Nair et al., 2013). Teachers’ environmental knowledge plays a key role in developing the environmental competencies of their students (Mat Said et al., 2003; Guven and Sulun, 2017). Taking into account what has been stated in this section, we formulate the following hypotheses: Hypothesis 4 (H4): Cross-sectional environmental competence (CEC) positively influences environmental teaching programs in religious schools (ETP). Greening the religious schools (GRS) GRS3 GRS4 GRS2 H5 CEC2 ETP3 ETP4 Cross-sectional environmental competence (CEC) Religious and environmental connections (REC) CEC4 CEC3 Environmental competencies of teachers (ECT) H1 H2 H3 H4 H7 H6 ECT1 ECT3 ECT2 GRS1 ETP2 REC1 REC2 REC3 Environmental teaching programmes (ETP) GRS7 CEC1 CEC5 ETP5 GRS8 GRS6 GRS5 ETP1 FIGURE 1 | Conceptual model. Greening the religious schools (GRS) H5 H5 H1 Religious and environmental connections (REC) Environmental teaching programmes (ETP) H3 H2 H4 Cross-sectional environmental competence (CEC) Environmental competencies of teachers (ECT) FIGURE 1 | Conceptual model. March 2020 | Volume 11 | Article 520 Frontiers in Psychology | www.frontiersin.org 4 Religious Schools and Environmental Education Robina-Ramírez et al. TABLE 1 | Scales. Environmental Competencies of Teachers (ECTs) Construct Code Item Sources Greening religious schools (GRSs) GRS1 Students’ general environmental knowledge UNECE, 2005 GRS2 Students’ environmental skills to tackle environmental threats Goldman et al., 2018; Olsson et al., 2019 GRS3 Students’ behavior to protect nature Hashim and Denan, 2015; Robina-Ramírez and Fernández Portillo, 2018; Sánchez-Llorens et al., 2019 GRS4 Students’ critical thinking about the environment Singseewo, 2011 GRS5 Students’ holistic and systematic thinking about the environment Lozano, 2006; Svanström et al., 2008 GRS6 Students’ specific environmental actions at school Ward et al., 2014 GRS7 Students’ proactive thinking about the environment Clunies-Ross et al., 2008 GRS8 Students’ social and ethical commitment to the environment Haynes, 2002; Yildirim and Ba¸stu ˘g, 2010 Religious and environmental connections (RECs) REC1 Connect sustainability and teaching of sacred scriptures through examples Hitzhusen, 2006 REC2 Enhance common values in sustainability and religion Meyfroidt, 2013; Robina-Ramírez and Pulido-Fernández, 2019 REC3 Combine religious and sustainable activities at school Tucker, 2009 Cross-sectional environmental competence (CEC) CEC1 Train students to protect nature in class through critical thinking Morrison et al., 2015 CEC2 Deliver talks in class about environmental injustice and inequalities Jensen and Schnack, 2006 CEC3 Train students to acquire environmental values Biel and Nilsson, 2005 CEC4 Train students to be passionate about nature to avoid environmental threats Uzzell et al., 1995 CEC5 Bring local examples to class about the environment to raise students’ concerns Palmer, 2008 Environmental teaching programs (ETP) ETP1 Promote learning programs among students Gill and Lang, 2018 ETP2 Apply environmental education to local communities Robina-Ramírez and Medina-Merodio, 2019; Robina-Ramírez et al., 2020 ETP3 Developing teaching programs to assess the socio-economic impact on the environment Afrinaldi et al., 2017 ETP4 Address environmental education toward social change for students Collins, 2017 ETP5 Develop affective approach through environmental learning Kals et al., 1999 Environmental competencies of teachers (ECT) ECT1 Teachers have enough environmental knowledge Mat Said et al., 2003; Guven and Sulun, 2017 ECT2 Teachers have a positive attitude toward nature Fien and Tilbury, 1996; Zembylas, 2007 ECT3 Teachers develop skills to set up environmental strategies among students Fien, 1995; Valderrama-Hernández et al., 2017 For instance, a study conducted in five schools in Canada showed that the level of teaching of environmental education in schools is not adequate (Miles et al., 2006). Other studies have highlighted that teachers do not have accurate knowledge about environmental literacy and competencies (Tal, 2010). Frontiers in Psychology | www.frontiersin.org Population and Sample According to the Catholic Schools Organization, there are 1,996 Catholic schools in Spain. They educate 1,217,674 students and have a total of 83,352 teachers of region and biology. In this study our hypotheses were tested with a convenience sample of teachers from 118 religious schools. Through telephone calls and emails, information was collected from 214 teachers from each of the 17 autonomous regions of Spain, between 1st May and 10th July 2019. 57% of the respondent were males, with the predominant age (70% of the total sample) being between 36 and 55. Most of them had been teaching for between 11 and 20 years, predominantly in secondary schools (see Table 2). Model and Measures From the review of the literature, four constructs (REC, CEC, ETP, and ECT) was proposed to measure their impact on greening in religious schools (GRSs). The model is presented in Figure 1. These constructs were designed with the objective of establishing the questionnaire items around the concepts proposed by different authors (see Table 1). The questions in the survey were measured using a Likert scale with seven points to indicate the degree of importance of the factors (Allen and Seaman, 2007). The factors or constructions were measured from 1 (‘strongly disagree’) to 7 (‘strongly agree’). The questionnaire was first validated through qualitative interviews with teachers, six of them face-to-face and 15 in Skype calls. As a result of this validation process, three questions were modified to ensure that the teachers had the correct understanding. Method and Techniques measurement model, we need to study the reliability and validity of the indicators in relation to the latent variables or constructs (Hair et al., 2016). We therefore analyzed the individual loads (λ) or simple correlations of the measures with their respective latent variables (λ ≥0.7 is accepted). Some indicators presented λ < 0.7, so they were deleted from the model (these λ values were the following: GRS5 = 0.516, GRS6 = 0.661, GRS7 = 0.585, CEC2 = 0.346, CEC5 = 0.557, ETP2 = 0.375, ETP5 = 0.667). Partial least squares (PLS) structural equation modeling (SEM) is used for conceptual model design through causal and non- parametric predictive analysis (Hussain et al., 2018). It is, especially when based on a variance model, suitable for analyzing quantitative data in the areas of social sciences and organizational behavior (Fornell and Bookstein, 1982; Hair et al., 2012). The data obtained from the ad hoc questionnaire were analyzed using SmartPLS 3, which is particularly recommended for composite models or constructions (Rigdon et al., 2017). This PLS statistical technique is applied when the data are structured in a series of interrelated dependency relationships between latent variables and indicators (Sarstedt et al., 2016). SmartPLS software 3.2.8 was used (Ringle et al., 2015). The Cronbach coefficient was used as an index of the reliability of the latent variables. The convergent validity of the latent variables was evaluated through the inspection of the average variance extracted (AVE) (accepted if > 0.5). Table 3 also shows that the square root of the average variance extracted (AVE) for each construct is greater than its highest correlation with any other construct. The discriminant validity of the latent variables was verified using the Fornell–Larcker criterion (Fornell and Bookstein, 1982), by examining whether the square root of the average extracted value (AVE) of each item was above the correlations with the other latent variables. In addition, following Henseler et al. (2015), a test was performed to check the lack of Environmental Competencies of Teachers (ECTs) These results were confirmed by the work of Falkenberg and Babiuk (2014), which stressed the low level of environmental knowledge and competences of teachers. This implies there is a need for a defined theoretical and practical learning process in environmental education to train these future educators. However, and in combination with this lack of environmental knowledge and competencies among teachers, complementary works have shown that teachers have positive attitudes toward environmental training (Fien and Tilbury, 1996; Zembylas, 2007). Van Petegem et al. (2007) implemented environmental actions in two universities in the Netherlands with a high and a low level of environmental education. In the second one, the teachers trained the students poorly because of their lack of environmental education. Similar results were found by Valderrama-Hernández et al. (2017): teachers lacked sufficient knowledge and skills to teach their students, because of a lack of training. Taking into account what has been said in this section, we formulate the following hypotheses: Hypothesis 6 (H6): Environmental competencies of teachers (ECTs) positively influence cross-sectional environmental competence (CECs). Hypothesis 7 (H7): Environmental competencies of teachers (ECTs) positively influence religious and environmental connections (RECs). Based on these positive attitudes, training courses have been applied to study their impact on students. March 2020 | Volume 11 | Article 520 Frontiers in Psychology | www.frontiersin.org 5 Religious Schools and Environmental Education Robina-Ramírez et al. TABLE 2 | Sample characterization. Attributes N = 214 Percentage (%) Gender Male 123 57 Female 91 43 Total 214 100 Age Less than 25 5 2 26–35 41 19 36–45 72 34 46–55 78 36 55 forward 18 8 Total 214 100 Teaching experience Less than 3 9 4 From 3 to 10 77 36 From 11 to 20 87 41 More than 20 years 41 19 Total 214 Subject 214 Biology 101 47 Religion 113 53 Total 214 100 Institution Primary education 78 36 Secondary education 92 43 Bachelor 44 21 Total 214 100 Socio-economic standard Low class 12 6 Middle class- High class 212 99 High class 0 0 Total 214 100 Hypothesis 8 (H8): Environmental competencies of teachers (ECTs) positively influence environmental teaching programs in religious schools (ETPs). Hypothesis 8 (H8): Environmental competencies of teachers (ECTs) positively influence environmental teaching programs in religious schools (ETPs). RESULTS Results of the Measurement Model The PLS approach is defined by two steps: the measurement model and the structural model evaluation. To elaborate the Results of the Measurement Model Goodness-of-Fit Test for the Model First, the overall fit of the model was evaluated using the mean residual standard square root (SRMR) indicator. According to Hu and Bentler (1998), the SRMR is the average mean squared discrepancy between the correlations observed and the implicit correlations in the model. For values lower than 0.08, the SRMR indicator is considered to be acceptable for PLS (Henseler et al., 2016). In this study, the SRMR was 0.057, which means that the model fits the empirical data (Hair et al., 2016). Results of the Structural Model Once we had examined the measurement model, we analyzed the relationships between the latent variables. First, we studied the path coefficients relative to each of the hypotheses. For this we tested the model from 5,000 sub-samples in order to verify the statistical significance of each path. From this, we obtained the explained variance (R2) of the endogenous latent variables, and the p-values of the regression coefficients (t-test) were used as indicators of the explanatory power of the model (Table 5). According to Chin (1998), the R2 values obtained for the investigation have the following significance: 0.67 ‘Substantial,’ 0.33 ‘Moderate,’ and 0.19 ‘Weak.’ The result obtained for the principal dependent variable, the greening process of religious schools (GRS), was R2 = 77.8%. Therefore, the evidence shows that the model presented has a solid or substantial predictive capacity. The other endogenous variables are also relevant, with substantial and moderate predictive capacity (for REC, R2 = 0.712, and for ETP R2 = 0.632). However, CEC has a weak capacity for Six of the eight hypotheses were accepted. Among the accepted hypotheses, there were no statistically significant differences in the relationships between the variables in our model (value of p > 0.05). TABLE 4 | Discriminant validity. Fornell–Larcker test Heterotrait–monotrait ratio (HTMT) CEC ECT ETP GRS REC CEC ECT ETP GRS REC CEC 0.838 ECT 0.425 0.895 0.424 ETP 0.770 0.505 0.857 0.769 0.502 GRS 0.709 0.675 0.740 0.850 0.707 0.674 0.735 REC 0.760 0.654 0.667 0.840 0.902 0.761 0.653 0.668 0.849 The discriminant validity was assessed by comparing the square root of each AVE in the diagonal with the correlation coefficients (off-diagonal) for each construct in the relevant rows and columns. TABLE 5 | Path coefficients and statistical significance. Hypotheses β 2.5% 97.5% t Statistics p-values H1 REC →GRS 0.338 0.046 0.670 2.110 0.000*** H2 CEC →REC 0.588 0.430 0.735 7.600 0.000*** H3 CEC →GRS −0.0.64 0.415 0.225 0.391 0.696 H4 CEC →ETP 0.678 0.541 0.808 9.698 0.000*** H5 ETP →GRS 0.342 0.115 0.688 2.342 0.019* H6 ECT →CEC 0.425 0.192 0.624 3.824 0.000*** H7 ECT →REC 0.404 0.278 0.542 5.957 0.000*** H8 ECT →ETP 0.678 0.541 0.808 4.046 0.030* *p < 0.05 [t(0.05; 499) = 1.647]; **p < 0.01 [t(0.01; 499) = 2.333]; ***p < 0.001 [t(0.001; 499) = 3.106] (n = 5000 subsamples). TABLE 5 | Path coefficients and statistical significance. Results of the Measurement Model The PLS approach is defined by two steps: the measurement model and the structural model evaluation. To elaborate the March 2020 | Volume 11 | Article 520 Frontiers in Psychology | www.frontiersin.org 6 Religious Schools and Environmental Education Robina-Ramírez et al. TABLE 3 | Validity and reliability. Latent variables Indicator Loadings Cronbach’s alpha Rho_A (Dijkstra-Henseler) Composite reliability Average variance extracted (AVE) CEC CEC1 0.823 0.877 0.877 0.876 0.702 CEC3 0.811 CEC4 0.877 ECT ECT1 0.922 0.923 0.924 0.923 0.800 ECT2 0.891 ECT3 0.870 ETP ETP1 0.835 0.891 0.904 0.822 0.735 ETP3 0.966 ETP4 0.758 GRS GRS1 0.814 0.923 0.924 0.923 0.705 GRS2 0.892 GRS3 0.841 GRS4 0.829 GRS8 0.822 REC REC1 0.865 0.929 0.930 0.929 0.814 REC2 0.926 REC3 0.915 discriminant validity is better detected with another technique. This test is called the heterotrait–monotrait relationship (HTMT). Table 4 shows that the HTMT ratio for each pair of factors was less than 0.90 (Henseler, 2017). Goodness-of-Fit Test for the Model Results of the Structural Model March 2020 | Volume 11 | Article 520 Frontiers in Psychology | www.frontiersin.org 7 Stone–Geisser test (Q2). Q2 0.109 2 0.374 8 0.478 2 0.495 plains that REC and ETP o the greening process of ists of omitting some of the estimation of the parameters s omitted from the estimated is technique, the predictive demonstrate that the model As can be se Q2 > 0. In the 1974), the valu indicating smal constructs have greater than 0.0 DISCUSIO The paper disc be incorporate and environme hypotheses that that was not depending on th p-values and pa environmental GRS3 GRS2 GRS2 GRS GRS GRS3 GR Religious Schools and Environmental Education Robina-Ramírez et al. TABLE 6 | Coefficient determination (R2) and Stone–Geisser test (Q2). Construct R2 Q2 CEC 0.181 0.109 ETP 0.632 0.374 GRS 0.778 0.478 REC 0.712 0.495 As can be seen in Table 6, all the endogenous constructs have Q2 > 0. In the Stone–Geisser (Q2) test (Geisser, 1974; Stone, 1974), the values are fixed in three steps; 0.02, 0.15 and 0.35, indicating small, medium and high predictive relevance. All our constructs have predictive relevance, since the values of Q2 are all greater than 0.02. TABLE 6 | Coefficient determination (R2) and Stone–Geisser test (Q2). Construct R2 Q2 CEC 0.181 0.109 ETP 0.632 0.374 GRS 0.778 0.478 REC 0.712 0.495 As can be seen in Table 6, all the endogenous constructs have Q2 > 0. In the Stone–Geisser (Q2) test (Geisser, 1974; Stone, 1974), the values are fixed in three steps; 0.02, 0.15 and 0.35, indicating small, medium and high predictive relevance. All our constructs have predictive relevance, since the values of Q2 are all greater than 0.02. As can be seen in Table 6, all the endogenous constructs have Q2 > 0. In the Stone–Geisser (Q2) test (Geisser, 1974; Stone, 1974), the values are fixed in three steps; 0.02, 0.15 and 0.35, indicating small, medium and high predictive relevance. All our constructs have predictive relevance, since the values of Q2 are all greater than 0.02. DISCUSION the environmental competencies of teachers (ECT) (through H4, H6 and H8) with the dependent variable. This demonstrates how knowledge and skill play a key role in greening religious schools. From the results shown in Figure 2, we can say that there are two clear ways of greening religious schools. The first is by developing the cross-sectional environmental competences of students (CEC). The fact that H3 was not fulfilled means it is not possible to make religious schools green only on the basis of students’ competences and in the absence of overlapping religious and environmental teaching. First, religious schools should combine religious teaching with environmental teaching (Sponsel, 2012; Raven, 2016). This teaching has to be based on the common values and knowledge taken from the sacred scriptures, in which Creation stories compel individuals to respect nature (Biel and Nilsson, 2005). Positive attitudes need to be built among teachers of biology and religion to enable them to speak the same language to students (Gookin, 2002). Consequently, the environmental training of teachers is a key issue in introducing environmental education to schools. HR managers in religious schools have to consider innovative programs to create or to reinforce the environmental competences of teachers. An environmental training policy, oriented toward human capital development, will lead to improved educational results and could also be considered as a differentiation strategy. The second way, which is very important in the model as it is the only independent variable not directly affected by any other, is through improving teachers’ competences (ECT). Having training programs especially designed to improve the environmental skills of teachers in religious schools could be considered a good HR policy, and would have a direct positive impact on CEC, REC, and ETP and an indirect positive effect on GRS. To sum up, 77.8% of the greening of religious schools is explained in the model through the selected constructs, where training programs for teachers are revealed as relevant (ECT). The environmental challenge for religious schools can be addressed by taking into account the connections between religion and the environment (REC) (R2 = 0.712) as well as environmental teaching programs (ETP) (R2 = 0.632) and cross- sectional environmental competences (R2 = 0.181). This model is strongly predictive, according to Chin and Newsted (1999). Second, teaching and learning programs have become an interesting tool to help raise environmental awareness in students. DISCUSION They have played a key role among teachers in biology and religion at schools. To make religious schools greener, it is crucial to develop not only CSCs (Mogensen and Mayer, 2005) but also teachers. These programs often give common guidance for students about right and wrong. Such competences need to be updated to cover environmental issues; the programs are usually based on critical thinking but also focus on students’ personal commitment (Lambrechts et al., 2013) and preparing them for action (Cincera and Krajhanzl, 2013). Similarly, they are usually based on rational attributes, without connections to affective reasons that would make students passionate about respecting nature (Uzzell et al., 1995). The results obtained can allow decision-makers to design green strategies based on the role of these educational and religious variables in religious schools. In other words, it is worthwhile and highly recommended to introduce a common language based on the similar values between religion and environmental teaching among students. For this purpose, it would be necessary, first, to train teachers in environmental issues. In addition, on the religious side, the model focuses on the relevance of Creation, encouraging students to consider their links with living creatures to enhance their commitment to environmental protection and preservation (Tucker, 1999). On the biology side, the model encourages the connection between the religious values of sacred scriptures and environmental science (Hungerford and Volk, 1990), in order to approach nature with respect in daily life (Kellert et al., 2002). Third, there is no direct way to make schools greener just by developing the students’ environmental competences; this must be done through combining religious and environmental teaching. In other words, students’ environmental competence needs to be mediated by combined religious and environmental teaching (Jensen and Schnack, 2006). These results are aligned with the experiences of international programs for eco-schools that monitor schools’ designated plans (FEE, 2012). In the case of religious schools in Spain, it would be interesting to learn from international experience, because few of these religious schools are currently interested in greening their academic curriculum. Finally, the output of this research, even acknowledging the limitations derived from the peculiarities of the Spanish context, might shed light on other studies that find no relationship between religion and environmental science or precisely the opposite result (Kanagy and Nelsen, 1995; Clements et al., 2014; Morrison et al., 2015; Arbuckle, 2017). DISCUSION Because of the novelty of our research, this study could be considered as a starting point for future developments in new research contexts with complementary methods. DISCUSION prediction (R2 = 0.181). This explains that REC and ETP are the factors that contribute to the greening process of religious schools (GRS). The paper discusses the environmental attributes that should be incorporated into religious schools to combine religious and environmental teaching. Figure 2 shows, in green, the hypotheses that were validated and, in red, the single hypothesis that was not accepted. The arrows are wider or narrower depending on the values of the supporting parameters (t student, p-values and path coefficients). The wider arrows link students’ environmental competencies (CEC) (through H2 and H4) and The blindfolding technique consists of omitting some of the data for a given construct during the estimation of the parameters and then trying to estimate what was omitted from the estimated parameters (Chin, 1998). Using this technique, the predictive relevance of the model is studied, to demonstrate that the model has predictive capacity. ETP1 E CEC1 ETP3 ETP4 REC1 REC2 REC3 (ETP) 1 3 2 CEC4 CEC3 (ECT) (REC) GRS3 GRS4 GRS2 ECT3 ECT1 ECT2 (CEC) (GRS) GRS8 GRS1 GRS2 GRS1 GRS GRS GRS8 GRS GRS4 GRS3 GR λ= 0.786 t=14,880 λ= 0.779 t=12,04 λ= 0.869 t=17,617 λ= 0.832 t=16,917 λ= 0.924 t=29,97 β= 0.122 t=1,284 β= 0.702 t=10,399 E E λ= 0.946 t=20,089 λ= 0.876 t=23,871 λ= 0.855 t=18,408 λ= 0.934 t=15,646 λ= 0.862 t=14,892 λ= 0.884 t=13,369 λ= 0.788 t=14,796 λ= 0.871 t=19,789 λ= 0.866 t=19,589 λ= 0.814 t=14,214 λ= 0.869 t=17,410 λ= 0.828 t=15,545 β= 0.425 t=3,928 β= 0.367 t=4,075 β= 0.222 t=2,795 β = 0.223 t=1,400 β= 0.685 t=9,790 β= 0.087 t=0,759 β= 0.338 t=2,130 (ET β= 0.367 t=4,075 β= 0.222 t=2,795 β= 0.087 t=0,759 FIGURE 2 | Results. FIGURE 2 | Results. Frontiers in Psychology | www.frontiersin.org 8 March 2020 | Volume 11 | Article 520 Religious Schools and Environmental Education Robina-Ramírez et al. the environmental competencies of teachers (ECT) (through H4, H6 and H8) with the dependent variable. This demonstrates how knowledge and skill play a key role in greening religious schools. in this environmental teaching (ADEAC, 2019), which is incomprehensible if one takes into account the fact that Creation and living creatures are deeply rooted in sacred scriptures as well as in recent encyclical letters and religious documents (Pope Paul, 1971; Benedict, 2008). Several conclusions can be drawn from the results of this paper. REFERENCES doi: 10.1177/ 097340820800200111 ff, L. (1995). Liberation and Ecology. Maryknoll, NY: Orbis Books. Boulet, M., Reid, A., Emery, S., and Hill, A. (2015). “New perspectives on research in environmental and sustainability education,” in Proceedings of the 8th World Environmental Education Congress Planet and People, Barcelona. Fien, J., and Tilbury, D. (1996). Learning for a Sustainable Environment: An Agenda for Teacher Education in Asia and the Pacific. Bangkok: UNESCO. Bregeon, J., Faucheux, S., and Rochet, C. (2008). Report of the Interdepartmental Working Group on Education for Sustainable Development]. Available online at: http://cache.media.education.gouv.fr (accessed July 11, 2019). Fletcher, T., Haynes, J., and Miller, J. (2005). “Effects of grouping by perceived ability on the attitudes of year 10 students towards physical education,” in Proceedings of the International Conference Australian Association for Research in Education (AARE), Sydney. Chin, W. W. (1998). “The partial least squares approach to structural equation modeling,” in Modern Methods for Business Research, ed. G. A. Marcoulides 295 (New York, NY: Lawrence Erlbaum Associates Publishers), 295–336. Flynn, M. (1995). The Culture of Catholic Schools: A Study of Catholic schools, 1972-1993. Homebush, NSW: St Paul Publications. Chin, W. W., and Newsted, P. R. (1999). “Structural equation modelling analysis with small samples using partial least squares,” in Statistical Strategies for Small Sample Research, ed. R. H. Hoyle (Thousand Oaks, CA: Sage), 307–341. Fornell, C., and Bookstein, F. L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. J. Mark. Res. 19, 440–452. doi: 10.1177/002224378201900406 Francis, L. (1986). Roman Catholic secondary schools: falling rolls and pupil attitudes. Educ. Stud. 12, 121–134. Cincera, J., and Krajhanzl, J. (2013). Eco-Schools: what factors influence pupils’ action competence for pro-environmental behaviour? J. Clean. Prod. 61, 117– 121. doi: 10.1016/j.jclepro.2013.06.030 Geisser, S. (1974). A predictive approach to the random effect model. Biometrika 61, 101–107. doi: 10.1093/biomet/61.1.101 Clements, J. M., Xiao, C., and McCright, A. M. (2014). An examination of the “greening of Christianity” thesis among Americans, 1993–2010. J. Sci. Study Relig. 53, 373–391. doi: 10.1111/jssr.12116 Gill, C., and Lang, C. (2018). Learn to conserve: the effects of in-school energy education on at-home electricity consumption. Energy Policy 118, 88–96. doi: 10.1016/j.enpol.2018.03.058 Clunies-Ross, P., Little, E., and Kienhuis, M. (2008). Self-reported and actual use of proactive and reactive classroom management strategies and their relationship with teacher stress and student behaviour. Educ. Psychol. 28, 693–710. doi: 10.1080/01443410802206700 Goldman, D., Ayalon, O., Baum, D., and Weiss, B. (2018). REFERENCES Crossman, J. (2011). Environmental and spiritual leadership: tracing the synergies from an organizational perspective. J. Bus. Ethics 103, 553–565. doi: 10.1007/ s10551-011-0880-3 Aarnio-Linnanvuori, E. (2013). Environmental issues in Finnish school textbooks on religious education and ethics. Nordidactica 1, 131–157. Delio, I. (2017). Is Natural Law “Unnatural?”. Exploring God and Nature Through Teilhard’s Organic Theology. Theol. Sci. 15, 276–288. doi: 10.1080/14746700. 2017.1335063 ADEAC, (2019). Association for the Environmental Education and Consumers. Available online at: http://www.adeac.es [accessed July 15, 2019]. Afrinaldi, F., Tasman, A. M., Zhang, H. C., and Hasan, A. (2017). Minimizing economic and environmental impacts through an optimal preventive replacement schedule: Model and application. J. Clean. Prod. 143, 882–893. doi: 10.1016/j.jclepro.2016.12.033 Dudley, N., Higgins-Zogib, L., and Mansourian, S. (2009). The links between protected areas, faiths, and sacred natural sites. Conserv. Biol. 23, 568–577. doi: 10.1111/j.1523-1739.2009.01201.x Falkenberg, T., and Babiuk, G. (2014). The status of education for sustainability in initial teacher education programmes: a Canadian case study. Int. J. Sustain. High. Educ. 15, 418–430. doi: 10.1108/IJSHE-10-2012-0088 Allen, I. E., and Seaman, C. A. (2007). Likert scales and data analyses. Qual. Prog. 40, 64–65. Arbuckle, M. B. (2017). The interaction of religion, political ideology, and concern about climate change in the United States. Soc. Nat. Resour. 30, 177–194. doi: 10.1080/08941920.2016.1209267 Farrell, A. E., and Jäger, J. (eds) (2006). Assessments of Regional and Global Environmental Risks. Designing Processes for the Effective Use of Science in Decision Making. Washington. DC: RFF Press Book. Batson, C. D., Schoenrade, P. A., and Pych, V. (1985). Brotherly love or self- concern? Behavioural consequences of religion. Adv. Psychol. Relig. 11, 185–208. doi: 10.1016/b978-0-08-027948-0.50019-0 Farrior, M., and Lowry, S. (2001). Building Partnerships with the Faith Community: A Resource Guide for Environmental Groups. Madison, WI: The Biodiversity Project. Benedict, X. V. I. (2008). Address to the Diplomatic Corps Accredited to the Holy See. Rome: Libreria Editrice Vaticana. FEE (2012). Eco-schools. Available online at: http://www.eco-schools.org/page. php?id1/452 (accessed February 10, 2019). (1988). The Dream of the Earth. San Francisco, CA: Sierra Book C Fien, J. (1995). Teaching for a sustainable world: the environmental and development education project for teacher education. Environ. Educ. Res. 1, 21–33. doi: 10.1080/1350462950010102 Biel, A., and Nilsson, A. (2005). Religious values and environmental concern: harmony and detachment. Soc. Sci. Q. 86, 178–191. doi: 10.1111/j.0038-4941. 2005.00297.x Fien, J., Neil, C., and Bentley, M. (2008). Youth can lead the way to sustainable consumption. J. Educ. Sustain. Dev. 2, 51–60. DATA AVAILABILITY STATEMENT The authors are grateful to the Regional Government (Junta de Extremadura) for supporting the research group under the SEJ021 code by the VI Action Plan 2017–2020 at the University of Extremadura through the European Funds (FSE and FEDER). The Regional Government (Junta de Extremadura) has also support the research through the grant GR18106. Furthermore, we would like to thank the reviewers who contributed their valuable time and effort to improve the article’s quality with much appreciated suggestions and comments. All datasets generated for this study are included in the article/supplementary material. CONCLUSION As a result of the increase in environmental threats (Hossain and Purohit, 2018), scholars have focused on making environmental proposals to increase environmental awareness among the population (Van Eijndhoven et al., 2001; Farrell and Jäger, 2006). In this regard, sustainable development is playing a major role (Rauch, 2002). As UNECE (2005) has recommended, sustainable development has to start to be taught in schools. Schools in Spain have started to be more aware of the role nature plays in education. However, religious schools are barely interested March 2020 | Volume 11 | Article 520 Frontiers in Psychology | www.frontiersin.org 9 Religious Schools and Environmental Education Robina-Ramírez et al. AUTHOR CONTRIBUTIONS RR-R collected the data, define the methodology and wrote the manuscript. MS-H revised and corrected the manuscript. CD-C and HJ-N have both complemented the manuscript during the revision process. REFERENCES Available online at: http://www.boe.es [accessed May 03, 2019]. LOGSE, (1990). General Organic Law about the Education System in Spain, LOGSE. Available online at: http://www.boe.es [accessed January 31, 2019]. Hashim, H. H., and Denan, Z. (2015). Importance of preserving the natural environment in the design schools in Malaysia. Procedia Soc. Behav. Sci. 170, 177–186. doi: 10.1016/j.sbspro.2015.01.027 Lozano, R. (2006). Incorporation and institutionalization of SD into universities: breaking through barriers to change. J. Clean. Prod. 14, 787–796. doi: 10.1016/ j.jclepro.2005.12.010 Haynes, F. (2002). The Ethical School: Consequences, Consistency and Caring. Abingdon: Routledge. Madhawa Nair, S., Rashid Mohamed, A., and Marimuthu, N. (2013). Malaysian teacher trainees’ practices on science and the relevance of science education for sustainability. Int. J. Sustain. High. Educ. 14, 71–89. doi: 10.1108/ 14676371311288967 Henseler, J. (2017). Bridging design and behavioral research with variance-based structural equation modeling. J. Advert. 46, 178–192. doi: 10.1080/00913367. 2017.1281780 Henseler, J., Hubona, G., and Ray, P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Ind. Manage. Data Syst. 116, 2–20. doi: 10.1108/imds-09-2015-0382 Mat Said, A., Ahmadun, F. R., Paim, L. H., and Masud, J. (2003). Environmental concerns, knowledge and practices gap among Malaysian teachers. Int. J. Sustain. High. Educ. 4, 305–313. doi: 10.1108/14676370310497534 Henseler, J., Ringle, C. M., and Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 43, 115–135. doi: 10.1007/s11747-014-0403-8 Melkert, A. A., and Vos, R. (2008). Millenium Development Goal 8: Global Partnership for Achieving the Millenium Development Goals, MDG GAP TASK FORCE REport 2008. New York, NY: United Nations Secretariat. Heyl, M., Moyano Díaz, E., and Cifuentes, L. (2013). Environmental attitudes and behaviours of college students: a case study conducted at a Chilean university. Rev. Latinoam. Psicol. 45, 487–500. Meyfroidt, P. (2013). Environmental cognitions, land change, and social–ecological feedbacks: an overview. J. Land Use Sci. 8, 341–367. doi: 10.1080/1747423x. 2012.667452 Hitzhusen, G. E. (2005). Understanding the role of spirituality and theology in outdoor environmental education: a mixed-method characterization of 12 Christian and Jewish outdoor programs. Res. Outdoor Educ. 7, 39–56. Miles, R., Harrison, L., and Cutter-Mackenzie, A. (2006). Teacher education: a diluted environmental education experience. Aust. J. Environ. Educ. 22, 49–59. doi: 10.1017/s0814062600001658 Hitzhusen, G. E. (2006). Religion and environmental education: building on common ground. Can. J. Environ. Educ. 11, 9–25. Mogensen, F., and Mayer, M. (eds) (2005). REFERENCES “(Eco)-schools: trends and divergences,” in A Comparative Study on ECO-School Development Processes in 13 Countries (Vienna: Austrian Federal Ministry of Education, Science and Culture). Hofman, M. (2015). What is an education for sustainable development supposed to achieve e a question of what, how and why. J. Educ. Sustain. Dev. 9, 213–228. doi: 10.1177/0973408215588255 Morrison, M., Duncan, R., and Parton, K. (2015). Religion does matter for climate change attitudes and behavior. PLoS One 10:e0134868. doi: 10.1371/journal. pone.0134868 Hossain, M. M., and Purohit, N. (2018). People’s voice to reduce global environmental risks. Lancet Planet. Health 2:e333. doi: 10.1016/s2542-5196(18) 30164-5 Murga-Menoyo, M. (2009). Educating for local development and global sustainability: an overview in Spain. Sustainability 1, 479–493. doi: 10.3390/ su1030479 Hu, L. T., and Bentler, P. M. (1998). Fit indices in covariance structure modeling: sensitivity to underparameterized model misspecification. Psychol. Methods 3, 424–453. doi: 10.1037/1082-989x.3.4.424 Nekhoroshkov, A. V. (2016). Moral dimensions of youth’s world view in multi- ethnic environment. Int. Electron. J. Math. Educ. 11, 1761–1771. Hungerford, H. R., and Volk, T. L. (1990). Changing learner behavior through environmental education. J. Environ. Educ. 21, 8–21. doi: 10.1080/00958964. 1990.10753743 Northcott, M. (2009). Loving scripture and nature. J. Study Relig. Nat. Cult. 3, 247–253. Hussain, S., Fangwei, Z., Siddiqi, A., Ali, Z., and Shabbir, M. (2018). Structural equation model for evaluating factors affecting quality of social infrastructure projects. Sustainability 10:1415. doi: 10.3390/su10051415 Okur-Berberoglu, E. (2015). The effect of ecopodagogy-based environmental education on environmental attitude of in-service teachers. Int. Electron. J. Environ. Educ. 5, 86–110. doi: 10.1016/j.evalprogplan.2011.11.007 Ideland, M., and Malmberg, C. (2015). Governing ‘eco-certified children’ through pastoral power: critical perspectives on education for sustainable development. Environ. Educ. Res. 21, 173–182. doi: 10.1080/13504622.2013.87 9696 Olsson, D., Gericke, N., Boeve-de Pauw, J., Berglund, T., and Chang, T. (2019). Green schools in Taiwan–Effects on student sustainability consciousness. Glob. Environ. Chang. 54, 184–194. doi: 10.1016/j.gloenvcha.2018.11.011 Palmer, M. (2008). Alliance of Religions and Conservation. Bath: ARC Press. Jensen, B. B., and Schnack, K. (2006). The action competence approach in environmental education. Environ. Educ. Res. 12, 471–486. doi: 10.1080/ 13504620600943053 Parker, L. (2017). Religious environmental education? The new school curriculum in Indonesia. Environ. Educ. Res. 23, 1249–1272. doi: 10.1080/13504622.2016. 1150425 Johnson, B. (2002). On the spiritual benefits of wilderness. Int. J. Wilderness 8, 28–32. Parris, T. M. (2002). Environmental Education Resources for Grades K–12. Environment 44, 3–4. doi: 10.1080/00139157.2002.10543557 Johnson, B., and Manoli, C. (2011). REFERENCES Influence of ‘green school certification’on students’ environmental literacy and adoption of sustainable practice by schools. J. Clean. Prod. 183, 1300–1313. doi: 10.1016/ j.jclepro.2018.02.176 Collins, T. J. (2017). Review of the twenty-three year evolution of the first university course in green chemistry: teaching future leaders how to create sustainable societies. J. Clean. Prod. 140, 93–110. doi: 10.1016/j.jclepro.2015. 06.136 Gookin, J. (2002). “Spirituality: the softer side of education,” in NOLS Environmental Education Notebook, eds J. Gookin, and D. Wells (Lander, WY: NOLS), 7–8. March 2020 | Volume 11 | Article 520 Frontiers in Psychology | www.frontiersin.org 10 Religious Schools and Environmental Education Robina-Ramírez et al. Government of Cantabria, (2005). Plan of Education for Sustainability. Available online at: http://boc.gobcantabria.es [accessed February 21, 2019]. Kates, R. W., Parris, T. M., and Leiserowitz, A. A. (2005). What is sustainable development? Goals, indicators, values, and practice. Environ. Sci. Policy Sustain. Dev. 47, 8–21. doi: 10.1080/00139157.2005.10524444 p g y Government of the Basque Country, (2002). The Basque Strategy for Sustainable g y Government of the Basque Country, (2002). The Basque Strategy for Sustainable Environmental Development. Available online at: http://www.ingurumena.ejgv. Government of the Basque Country, (2002). The Basque Strategy for Sustainable Environmental Development. Available online at: http://www.ingurumena.ejgv. euskadi.net [accessed February 28, 2019]. Kellert, S. R., Farnham, T. J., and Farnham, T. (2002). The Good in Nature and Humanity: Connecting Science, Religion, and Spirituality with the Natural World. Washington, DC: Island Press. Environmental Development. Available online at: http://www.ingurumena.ejgv. euskadi.net [accessed February 28, 2019]. y Guven, G., and Sulun, Y. (2017). Pre-service teachers’ knowledge and awareness about renewable energy. Renew. Sustain. Energy Rev. 80, 663–668. doi: 10.1016/ j.rser.2017.05.286 Kuhlman, T., and Farrington, J. (2010). What is sustainability? Sustainability 2, 3436–3448. doi: 10.3390/su2113436 Hair, J. F. Jr., Hult, G. T. M., Ringle, C., and Sarstedt, M. (2016). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Thousand Oaks, CA: Sage. Lambrechts, W., Mula, I., Ceulemans, K., Molderez, I., and Gaeremynck, V. (2013). The integration of competences for sustainable development in higher education: an analysis of bachelor program in management. J. Clean. Prod. 48, 65–73. doi: 10.1016/j.jclepro.2011.12.034 65–73. doi: 10.1016/j.jclepro.2011.12.034 Hair, J. F., Sarstedt, M., Ringle, C. M., and Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. J. Acad. Mark. Sci. 40, 414–433. doi: 10.1007/s11747-011-0261-6 j j p Loe Spanish National Education System, (2006). LOE, Spanish National Education System. REFERENCES doi: 10.1086/688094 UNECE (2005). UNECE Strategy for Education for Sustainable Development CEP/AC.13/2005/3/Rev1. Paris: UN Economic and Social Council. Rickenbacker, H., Brown, F., and Bilec, M. (2019). Creating environmental consciousness in underserved communities: Implementation and outcomes of community-based environmental justice and air pollution research. Sustain. Cities Soc. 47:101473. doi: 10.1016/j.scs.2019.101473 UNESCO (1977). The Tbilisi Declaration – Intergovernmental Conference on Environmental Education Final Report. Tbilisi: USSR. Uzzell, D. L., Rutland, A., and Whistance, D. (1995). “Questioning Values in Environmental Education,” in Values and the Environment, eds Y. Guerrier, N. Alexander J Chase and M O’Brien (Chichester: Wiley) 172–182 Rigdon, E. E., Sarstedt, M., and Ringle, C. M. (2017). On comparing results from CB-SEM and PLS-SEM: five perspectives and five recommendations. Mark. Zfp 39, 4–16. doi: 10.15358/0344-1369-2017-3-4 Environmental Education,” in Values and the Environment, eds Y. Guerrier, N Alexander, J. Chase, and M. O’Brien (Chichester: Wiley), 172–182. , , , Alexander, J. Chase, and M. O’Brien (Chichester: Wiley), 172–182. Valderrama-Hernández, R., Alcántara, L., and Limón, D. (2017). The complexity of environmental education: teaching ideas and strategies from teachers. Procedia Soc. Behav. Sci. 237, 968–974. doi: 10.1016/j.sbspro.2017.0 2.137 Ringle, C. M., Wende, S., and Becker, J. M. (2015). SmartPLS 3. Boenningstedt: SmartPLS GmbH. Rittel, H. W., and Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy Sci. 4, 155–169. doi: 10.1007/bf01405730 Van Eijndhoven, J., Clark, W. C., and Jäger, J. (2001). “The long-term development of global environmental risk management: conclusions and implications for the future,” in Learning to Manage Global Environmental Risks: A Comparative History of Social Responses to Climate Change, Ozone Depletion, and Acid Rain, Vol. 1, eds W. C. Clark, J. Jaeger, J. van Eijndhoven, and N. M. Dickson (Cambridge, MA: The MIT Press), 181–197. Robina Ramírez, R., and Fernández Portillo, A. (2018). What role does tourist´s educational motivation play in promoting religious tourism among travellers? Ann. Leis. Res. 1–22. doi: 10.1080/11745398.2018.1561309 Robina-Ramírez, R., and Medina-Merodio, J.-A. (2019). Transforming students’ environmental attitudes in schools through external communities. J. Clean. Prod. 232, 629–638. doi: 10.1016/j.jclepro.2019.05.391 Van Petegem, P., Blieck, A., and Pauw, J. B. D. (2007). Evaluating the implementation process of environmental education in pre-service teacher education: two case studies. J. Environ. Educ. 38, 47–54. doi: 10.3200/JOEE.38. 1.47-54519146 Robina-Ramírez, R., Merodio, J. A. M., and McCallum, S. (2020). What role do emotions play in transforming students’ environmental behaviour at school? J. Clean. Prod. 258:120638. REFERENCES The ENV scale in the US: a measure of Children’s environmental attitudes based on the theory of ecological attitude. J. Environ. Educ. 42, 84–97. doi: 10.1080/00958964.2010.503716 Pascual, J. A., Esteban, G., Martínez, R., Molina, J., and Ramirez, J. (2000). La integración de la educación ambiental en la ESO: datos para la reflexión. Enseñ. Cienc. 18, 227–234. Kals, E., Schumacher, D., and Montada, L. (1999). Emotional affinity toward nature as a motivational basis to protect nature. Environ. Behav. 31, 178–202. doi: 10.1177/00139169921972056 Pitoska, E., and Lazarides, T. (2013). Environmental education centers and local communities: a case study. Procedia Technol. 8, 215–221. doi: 10.1016/j.protcy. 2013 11 030 Pitoska, E., and Lazarides, T. (2013). Environmental education centers and local communities: a case study Procedia Technol 8 215 221 doi: 10 1016/j protcy Kanagy, C. L., and Nelsen, H. M. (1995). Religion and environmental concern: challenging the dominant assumptions. Rev. Relig. Res. 37, 33–45. Ponomarenko, Y. V., Zholdasbekova, B. A., Balabekov, A. T., Kenzhebekova, R. I., Yessaliyev, A. A., and Larchenkova, L. A. (2016). Modern methodology and Frontiers in Psychology | www.frontiersin.org March 2020 | Volume 11 | Article 520 11 Religious Schools and Environmental Education Robina-Ramírez et al. techniques aimed at developing the environmentally responsible personality. Int. J. Environ. Sci. Educ. 11, 2877–2885. Torkar, G., and Krašovec, U. (2019). Students’ attitudes toward forest ecosystem services, knowledge about ecology, and direct experience with forests. Ecosyst. Serv. 37:100916. doi: 10.1016/j.ecoser.2019.100916 techniques aimed at developing the environmentally responsible personality. Int. J. Environ. Sci. Educ. 11, 2877–2885. Pope Paul, VI (1971). Apostolic Letter Octogesima Adveniens. Rome: AAS. Tucker, M. E. (2009). “Touching the depths of things: cultivating nature in East Asia,” in Ecology and the Environment: Perspectives from the Humanities, ed. D. Swearer (Cambridge, MA: Harvard Center for the Study of World Religions), 49–64. Ramos, T. B., Montano, M., Joanaz, de Melo, J., Souza, M. P., Carvalho, et al. (2015). Strategic environmental assessment in higher education: portuguese and brazilian cases. J. Clean. Prod. 106, 222–228. doi: 10.1016/j.jclepro.2014. 12.088 Rauch, F. (2002). The potential of education for sustainable development for reform in schools. Environ. Educ. Res. 8, 43–51. doi: 10.1080/ 13504620120109646 Tucker, P. (1999). Normative influences in household waste recycling. J. Environ. Plan. Manag. 42, 63–82. doi: 10.1080/09640569911307 UN (2009). Agenda 21. Available online at: http://www.un.org/esa/dsd/agenda21/ [accessed December 07, 2019]. Raven, P. H. I. (2016). Our World and Pope Francis’. Encyclical, Laudato si’. Q. Rev. Biol. 91, 247–260. REFERENCES doi: 10.1016/j.jclepro.2020.120638 Vare, P., and Scott, W. (2007). Learning for a change: exploring the relationship between education and sustainable development. J. Educ. Sustain. Dev. 1, 191–198. doi: 10.1177/097340820700100209 Robina-Ramírez, R., and Pulido Fernández, M. (2018). Religious Travellers’ Improved Attitude towards. Nat. Sustain. 10:3064. doi: 10.3390/su10093064 Robina-Ramírez, R., and Pulido-Fernández, M. (2019). What role do religious belief and moral emotions play in pilgrimage with regards to respecting nature? Ann. Leis. Res. 1–21. doi: 10.1080/11745398.2019.1703199 Vázquez, C. E., and Sevillano García, M. L. (2011). Programar en Primaria y Secundaria. Madrid: Pearson. Sánchez-Llorens, S., Agulló-Torres, A., Del Campo-Gomis, F. J., and Martinez- Poveda, A. (2019). Environmental consciousness differences between primary and secondary school students. J. Clean. Prod. 227, 712–723. doi: 10.1016/j. jclepro.2019.04.251 Ward, M. N., Wells, B., and Diyamandoglu, V. (2014). Development of a framework to implement a recycling program in an elementary school. Resour. Conserv. Recycl. 86, 138–146. doi: 10.1016/j.resconrec.2014.0 2.013 WCED, (1987). Our Common Future. London: Oxford University Press. World Health Organization [WHO] (2013) Urban Population Growth Available WCED, (1987). Our Common Future. London: Oxford University Press Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., and Gudergan, S. P. (2016). Estimation issues with PLS and CBSEM: Where the bias lies! J. Bus. Res. 69, 3998–4010. doi: 10.1016/j.jbusres.2016.06.007 World Health Organization [WHO], (2013). Urban Population Growth. Available online at: http://www.who.int [accessed February 6, 2019]. Schreiner, P. (ed.) (2000). Religious Education in Europe. A Collection of Basic Information about RE in European Countries. Münster: Intereuropean Commission on Church and School and Comenius-Institut. Yildirim, A., and Ba¸stu˘g, ˙I (2010). Teachers’ views about ethical leadership behaviors of primary school directors. Procedia Soc. Behav. Sci. 2, 4109–4114. doi: 10.1016/j.sbspro.2010.03.648 Ysseldyk, R., Matheson, K., and Anisman, H. (2010). Religiosity as identity: toward an understanding of religion from a social identity perspective. Pers. Soc. Psychol. Rev. 14, 60–71. doi: 10.1177/1088868309349693 Shindler, B. A., and Cramer, L. A. (1999). Shifting public values for forest management: making sense of wicked problems. West. J. Appl. For. 14, 28–34. doi: 10.1093/wjaf/14.1.28 Shwom, R., and Lorenzen, J. A. (2012). Changing household consumption to address climate change: social scientific insights and challenges. Wiley Interdiscip. Rev. Clim. Chang. 3, 379–395. doi: 10.1002/wcc.182 Zembylas, M. (2007). Emotional ecology: the intersection of emotional knowledge and pedagogical content knowledge in teaching. Teach. Teach. Educ. 23, 355– 367. doi: 10.1016/j.tate.2006.12.002 Singseewo, A. (2011). Awareness of environmental conservation and critical thinking of the undergraduate students. Eur. J. REFERENCES Soc. Sci. 25, 136–144. Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Sponsel, L. E. (2012). Spiritual Ecology: A Quiet Revolution. Santa Barbara, CA: ABC-CLIO. Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. J. R. Stat. Soc. Ser. B 36, 111–133. doi: 10.1111/j.2517-6161.1974.tb00994.x Copyright © 2020 Robina-Ramírez, Sánchez-Hernández, Jiménez-Naranjo and Díaz-Caro. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. j Svanström, M., Lozano-Garzia, F. J., and Rowe, D. (2008). Learning outcomes for sustain-able development in higher education. Int. J. Sustain. High. Educ. 9, 339–351. Tal, T. (2010). Pre-service teachers’ reflections on awareness and knowledge following active learning in environmental education. Int. Res. Geogr. Environ. Educ. 19, 263–276. doi: 10.1080/10382046.2010 March 2020 | Volume 11 | Article 520 Frontiers in Psychology | www.frontiersin.org 12
https://openalex.org/W4285384207
https://lirias.kuleuven.be/bitstream/20.500.12942/698709/2/Aplication_of_Association_Rule_mining_PSCC2022_ID1563_FINAL.pdf
English
null
Application of Association Rule Mining in offshore HVAC transmission topology optimization
Electric power systems research
2,022
cc-by
9,289
Stephen Hardy, Dirk Van Hertem, Hakan Ergun KU Leuven Department of Electrical Engineering (ESAT) Heverlee, Belgium and EnergyVille, Genk, Belgium Abstract—This work develops a hybrid optimization method for determining optimal radial transmission topologies for the connection of offshore wind farms combining Association Rule Mining (ARM) and a greedy algorithm. The method is capable of optimally placing offshore substations and accounts for Capital Expenditures (CAPEX), Corrective Maintenance (CM), losses and Expected Energy Not Transmitted (EENT). The stochastic nature of wind is also considered. First, an inequality based apriori algorithm is applied to a randomly generated population of Offshore Wind Power Plant (OWPP) pairs within a specified search domain. This way, a set of simple constraints is obtained reducing the effective combinatorial search space. A verified optimal greedy algorithm is then applied to efficiently search the reduced search space for the lowest cost radial topology to connect offshore wind. The hybrid approach is shown to introduce minimal error given a sufficient sample population while greatly extending the feasible problem size of the greedy search algorithm. TABLE I NOMENCLATURE Symbol Definition Unit A Area of an OWPP concession. [km2] B Boolean defining whether a single export cable is economic for a pair of OWPPs. {B} Set of binary strings: j. (Greedy search) - D Database of transactions. - ϵ Error from eliminated connections. [%] gi Capacity of OWPPi. [MW] G Set of all OWPP capacities g. - Gss Maximum OSS size considered. [MW] G Minimum OWPP capacity considered [MW] h height of OWPP concession. [km] {H} Exhaustive combinatorial search space. (Greedy search) - Ii Item i. - I Set of unique items. - j Binary string. - K Rule making population. - Kc Control population. - κ Member of rule making population. - li Distance of transmission line i. - li,j Distance from node i to node j. - L Set of all lengths li. - L Maximum distance from OWPP to PCC in rule making population. [km] L Minimum distance from OWPP to PCC in rule making population. [km] m Number of items in a Database; D. - n Number of OWPPs. - N Total number of transactions: T. - p Support. [%] pt Support threshold. [%] P Confidence. - R Set of rules discovered. - ρ Wind power density. [MW/km2] ϱ Percentage of candidate connections eliminated. [%] si Capacity of OWPPi in rule making population. [MW] S Set of all capacities si. - tj Physical topology. (Greedy search) - T A transaction in Database D. - {TB} Set of base topologies. This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement no. 765585 and the Blauwe Cluster under project: Cordoba. Stephen Hardy, Dirk Van Hertem, Hakan Ergun KU Leuven Department of Electrical Engineering (ESAT) Heverlee, Belgium and EnergyVille, Genk, Belgium (Greedy search) - {TH} Exhaustive combinatorial topology space. (Greedy search) - τ Computation time. [s] θ Maximum angle at PCC. [o] θ Minimum angle at PCC. [o] θi,j Angle with PCC of OWPPs i and j in rule making population. [o] ∡ Set of all angles θi,j. - w Width of OWPP concession. [km] X,Y Item set. [km] # Block formation of OWPPs. - || Parallel formation of OWPPs. - ⊥ Perpendicular formation of OWPPs. - Index Terms—Circuit topology, machine learning, optimiza- tion, power transmission, wind energy. I. INTRODUCTION In Europe, it is estimated that between 240 and 450 GW of offshore wind will be required by 2050 to meet the C02 reduction targets agreed upon under The Paris Agreement [1], [2]. To date, Europe has installed a cumulative capacity of only 25 GW of offshore wind [3]. But there is reason to be optimistic. For example, the rate of development is increasing. In 2019, a record 3.6 GW of new offshore wind was connected to the European grid and in 2020, despite the difficulties posed by COVID-19, an additional 2.9 GW was added [2], [3]. In Europe, it is estimated that between 240 and 450 GW of offshore wind will be required by 2050 to meet the C02 reduction targets agreed upon under The Paris Agreement [1], [2]. To date, Europe has installed a cumulative capacity of only 25 GW of offshore wind [3]. But there is reason to be optimistic. For example, the rate of development is increasing. In 2019, a record 3.6 GW of new offshore wind was connected to the European grid and in 2020, despite the difficulties posed by COVID-19, an additional 2.9 GW was added [2], [3]. The Offshore Wind Topology Optimization Problem (OW- TOP) describes the problem of transmission network expan- sion offshore. Traditionally, this has focused on optimizing the medium voltage (MV) collection grid in combination with a single point to point connection to a Point of Common Coupling (PCC) onshore. As the industry has matured, how- ever, developed offshore regions have grown substantially in size and this approach is frequently no longer sufficient. In Belgium, for example, the Modular Offshore Grid 2 (MOG2) is a high voltage (HV) transmission network proposed for two wind concession zones. It requires grid planning prior to the The Offshore Wind Topology Optimization Problem (OW- TOP) describes the problem of transmission network expan- sion offshore. Traditionally, this has focused on optimizing the medium voltage (MV) collection grid in combination with a single point to point connection to a Point of Common Coupling (PCC) onshore. As the industry has matured, how- ever, developed offshore regions have grown substantially in size and this approach is frequently no longer sufficient. In Belgium, for example, the Modular Offshore Grid 2 (MOG2) is a high voltage (HV) transmission network proposed for two wind concession zones. Application of Association Rule Mining in Offshore HVAC Transmission Topology Optimization Stephen Hardy, Dirk Van Hertem, Hakan Ergun KU Leuven Department of Electrical Engineering (ESAT) Heverlee, Belgium and En Stephen Hardy, Dirk Van Hertem, Hakan Ergun KU Leuven Department of Electrical Engineering (ESAT) Heverlee, Belgium and EnergyVille, Genk, Belgium I. INTRODUCTION Among meta- heuristics, Genetic Algorithms (GAs) have been the most frequently applied [15]–[20], but are by no means the only one. Within the literature a wide range of alternative algorithms have been investigated including particle swarm [7], minimal spanning tree [8], simulated annealing [9], modified Clark and Wright’s savings algorithm [10] and modified bat algorithm [11]. Machine learning techniques such as ARM, as of yet, have seen limited adoption within the field of power system plan- ning. In a review of the literature on learning assisted optimiza- tion applied to power systems, extensive applications related to energy management, energy forecasting, electricity markets, operation and control, power flow calculations and optimal dispatch can be found, however, power system planning and network expansion has received very little attention [23]–[27]. In this work, ARM is used to obtain dynamically generated constraints and reduce the combinatorial search space of the problem. The greedy search algorithm in [22] is then used to search the reduced search space finding the optimal topology. To the best knowledge of the authors this hybrid optimization approach constitutes the first time ARM has been applied in such a manner. In addition to meta-heuristics, classical mathematical formula- tions have been used. Specific formulations such as stochastic programming [12], [13], modified vehicular routing [14] and cascading, sequential Mixed Integer Program (MIP) [21] have been implemented among others. The advantage of a mathe- matical approach compared to meta-heuristics is a guarantee on global optimality under certain conditions, such as the convexity of the problem. Different approaches often focus on certain aspects of the problem but leave others out. For example in [8] simulated wind profiles and quadratic losses are included but reliability is not considered. In [10], reliability is prioritized to investi- gate cross-substation incorporation but only a few predefined topologies are assessed. In [15] no reliability is included and wind speed is approximated by a Weibull distribution. In [18] reliability is included but the wind turbine power output is considered constant. The remainder of this paper is structured as follows. In the next section the modelling methodology is described, including the sample population and the data mining procedure. This is followed by a description of the combinatorial search space and the hybridization of the existing greedy search algorithm using ARM. I. INTRODUCTION In such cases, if the global solution is found to be infeasible due to additional engineering constraints not considered in the optimisation, the solution may need to be discarded and the problem reformulated. finalization of individual concessions [4]. In such a case, tradi- tional OWTOP approaches that focus on Offshore Substation (OSS) location and optimization of the MV collection circuit layout are not applicable as the final turbine layout is yet to be determined. It is therefore essential that long term planning tools which optimize the HV network considering multiple offshore concessions are developed to properly equip planners and decision makers to move forward. To address these deficiencies, the authors of this paper devel- oped a greedy search algorithm for radial offshore topologies in [22]. This approach can guarantee global optimality while considering electrical losses, system reliability, the stochastic nature of wind and optimally locates an unbounded number of OSSs. In addition, this optimization approach finds not a singular solution topology but a hierarchy of radial topolog- ical options bounded from below by the optimal topology. The algorithm, however, is still limited to a cluster size of about a dozen Offshore Wind Power Plants (OWPPs) due to the combinatorial nature of the search space. As such, this work focuses on extending the feasible problem size of the greedy algorithm by reducing the combinations that need be considered. The Association Rule Mining (ARM) approach is presented as an extension of the greedy search, however, it could just as easily be a pre-processing step to select appropriate candidates for mathematical mixed-integer programming (MIP) formulations. The greedy search is chosen as it has been shown to outperform an MIP due to the unconstrained optimal locating of OSSs [22]. Despite a shift in such a direction being desirable, there is a noticeable gap in the literature in regards to optimizing the High Voltage (HV) network. Of research on the OWTOP, the vast majority focuses on the optimization of the Medium Voltage (MV) collection circuit [5]–[17] compared to the HV transmission system [18]–[22]. The OWTOP is non-linear and non-convex and can involve a large number of binary decision variables, and is classified as an NP-hard problem. As such, finding a global optimal solution is often not feasible without significant simplifica- tions. A common approach has therefore been to apply a meta-heuristic to obtain a high quality but perhaps sub-optimal solution within a reasonable computation time. I. INTRODUCTION It requires grid planning prior to the PSCC 2022 Porto, Portugal — June 27 – July 1, 2022 22nd Power Systems Computation Conference PSCC 2022 2 of solution topologies rather than a single solutions can be difficult. In such cases, if the global solution is found to be infeasible due to additional engineering constraints not considered in the optimisation, the solution may need to be discarded and the problem reformulated. To address these deficiencies, the authors of this paper devel- oped a greedy search algorithm for radial offshore topologies in [22]. This approach can guarantee global optimality while considering electrical losses, system reliability, the stochastic nature of wind and optimally locates an unbounded number of OSSs. In addition, this optimization approach finds not a singular solution topology but a hierarchy of radial topolog- ical options bounded from below by the optimal topology. The algorithm, however, is still limited to a cluster size of about a dozen Offshore Wind Power Plants (OWPPs) due to the combinatorial nature of the search space. As such, this work focuses on extending the feasible problem size of the greedy algorithm by reducing the combinations that need be considered. The Association Rule Mining (ARM) approach is presented as an extension of the greedy search, however, it could just as easily be a pre-processing step to select appropriate candidates for mathematical mixed-integer programming (MIP) formulations. The greedy search is chosen as it has been shown to outperform an MIP due to the unconstrained optimal locating of OSSs [22]. Machine learning techniques such as ARM, as of yet, have seen limited adoption within the field of power system plan- ning. In a review of the literature on learning assisted optimiza- tion applied to power systems, extensive applications related to energy management, energy forecasting, electricity markets, operation and control, power flow calculations and optimal dispatch can be found, however, power system planning and network expansion has received very little attention [23]–[27]. In this work, ARM is used to obtain dynamically generated constraints and reduce the combinatorial search space of the problem. The greedy search algorithm in [22] is then used to search the reduced search space finding the optimal topology. To the best knowledge of the authors this hybrid optimization approach constitutes the first time ARM has been applied in such a manner. of solution topologies rather than a single solutions can be difficult. 22nd Power Systems Computation Conference Porto, Portugal — June 27 – July 1, 2022 C. Association Rule Mining (ARM) ARM was first introduced in [30] to discover relationships within transactional data of supermarkets to better target marketing and improve product placement. It has since been applied to a wide range of fields from medical diagnosis [31] to power system restoration [32]. New applications are continually being discovered. An association rule is defined as an expression of the form: Clusters are created by positioning concessions together along the horizontal and vertical axis. In this paper three topological variations relative to the PCC are considered: the “block” formation denoted by #, the “parallel” formation denoted by ∥and the “perpendicular” formation denoted by ⊥. For each of these formations a representative case for n = 4 OWPPs is shown in fig. 1(b)-(d). X ⇒Y | X ∩Y = ∅ (4) (4) A cluster is described by a set of six characteristics. The first two are the number of concessions; n and the capacities of the concessions; G = {g1, g2, ..., gn}. In addition, θ, θ, L and L shown in fig. 1(c) - (d) are defined. θ and θ are the minimum and maximum angles created by any two OWPPs connected to the PCC. L is the Euclidean distance to the PCC from the nearest OWPP and L the furthest. where X and Y are item sets within a transactional database D. Mining for association rules, relies on two basic properties of D: the support p and the confidence P. Support is defined as: p = |X|/N (5) (5) where |X| is the number of occurrences of item set X and N is the total number of transactions in D. Confidence is defined where |X| is the number of occurrences of item set X and N is the total number of transactions in D. Confidence is defined II. MODELLING si, sj ∈S; li, lj ∈L; θi,j ∈∡ S = {si = P ∈k gi ∈ G k  | si ≤Gss −G} L = {li = L + k|li ≤L and k ∈Z+ 0 } ∡= {θi,j = θ + k|θi ≤θ and k ∈Z+ 0 } (3) A. OWPP Clusters The basic building block of a cluster is the OWPP conces- sion shown in fig 1(a). A concession is modeled as a square of height, h, and width w. The area, A, of the concession is determined by the ratio of the OWPP capacity (MW), g, and regional wind power density ρ (MW/km2) as in (1). (3) A = g ρ (1) ∡= {θi,j = θ + k|θi ≤θ and k ∈Z+ 0 } (1) Here Gss, is a parameter set to the maximum feasible size of a single OSS. This is assumed to be 2 GW in this paper. G is the smallest capacity OWPP in the cluster, which, when subtracted from Gss provides the limit on the maximum capacity of an OWPP within the rule making population. It is important to note that the value of si is the sum of k OWPPs’s capacities; gi. The implication is that whether it is a single OWPP or k OWPPs contributing to capacity si, it is represented by identical descriptive variables. For both L and ∡, k is a step size that discretizes the search space and can be adjusted based on computational requirements. In this work a power density of 5MW/km2 [28] is assumed. The connection point for MV cables in the collector circuit is assumed to be the geometric center of the rectangle which is indicated by the red dot. As it is assumed the turbine locations are unknown, the centre of the concession is deemed the best approximation of the collection circuit connection point that does not inadvertently bias the topology. This assumption is believed justified as the entire collection system consisting of a couple hundred kilometers of MV cable constitutes a minor part (10-15%) of the overall electrical system cost [29]. As a few kilometers is the maximum distance separating the very edge of the concession from the centre, this would constitute an error of about 1% on the overall cost in the worst case scenario. I. INTRODUCTION In the results section, a sensitivity analysis on model parameters is performed, followed by the presentation of results from 18 case studies of different OWPP clusters ranging in size from eight to 21 OWPPs. The cumulative error is tracked in all cases and when feasible, the solution is compared directly to the result with the unmodified greedy algorithm. Finally, the conclusions are presented and sugges- tions for future work are provided. With mathematical formulations, the strict mathematical struc- ture can require a higher level of simplification of the search space compared to meta-heuristics. This may extend beyond what is desirable. For example, restricting the position of OSSs to a few discrete locations and candidate cables to a small set of cross-sections is common. Such simplifications may be essential as the number of binary variables are strongly related to whether the problem is computationally tractable and they grow rapidly with the number of candidate OSS positions. Furthermore, the solution of such problems are often obtained using commercial optimisation solvers, where obtaining a set 22nd Power Systems Computation Conference PSCC 2022 Porto, Portugal — June 27 – July 1, 2022 Porto, Portugal — June 27 – July 1, 2022 3 Fig. 1. Structure of OWPP Clusters. (a) A single concession. (b) A block (#) cluster. (c) A parrallel (∥) cluster. (d) A perpendicular (⊥) cluster. population is drawn without replacement and a single member of the population κ is defined by: κ = f(si, sj, li, lj, θi,j, B), (2) (2) where si and sj are the capacities in MVA of the two OWPPs, i and j, that are being connected. li and lj are the euclidean distances to the PCC in kilometers and θi,j is the angle formed in degrees at the PCC between li and lj. B is a boolean quantity that is equal to one (true) when the lowest cost connection to the PCC for OWPPs i and j is through a single common export cable, and zero (false) when the lowest cost connection is two individual export cables. To ensure each member of the population is representative of the cluster under investigation, the following set of constraints are imposed: Fig. 1. Structure of OWPP Clusters. (a) A single concession. (b) A block (#) cluster. (c) A parrallel (∥) cluster. (d) A perpendicular (⊥) cluster. 22nd Power Systems Computation Conference B. Population Sampling This is by no means a trivial task as the number of combinations of items grows exponentially with the number of items in D. As such, much research has gone into the development of efficient algorithms for finding frequent item sets. Among the most well known are apriori [33], fp-growth [34] and eclat [35]. The algorithms differ in how they search for the frequent item sets. The apriori algorithm uses a breadth first approach, eclat a depth first approach and fp-growth constructs a prefix-tree. It is left to future work to determine if a particular algorithm is most suited for the given application. In this work the apriori algorithm is used. As the apriori algorithm is intended to work on data sets of discrete items, e.g. products within a grocery cart, applying it to OWPP connections requires a pre-conditioning of the data. This is accomplished as follows. Finding association rules that are of interest is a two step process. The first step is to find all frequent item sets satisfying a minimum support level and the second step is to retain only those frequent item sets that have a minimum level of confidence. While the second step is straight forward, the first step involves finding all combinations of items in D. This is by no means a trivial task as the number of combinations of i i ll i h h b f i i D items grows exponentially with the number of items in D. As such, much research has gone into the development of efficient algorithms for finding frequent item sets. Among the most well known are apriori [33], fp-growth [34] and eclat [35]. The algorithms differ in how they search for the frequent item sets. The apriori algorithm uses a breadth first approach, eclat a depth first approach and fp-growth constructs a prefix-tree. It is left to future work to determine if a particular algorithm is most suited for the given application. In this work the apriori algorithm is used. As the apriori algorithm is intended to work on data sets of discrete items, e.g. products within a grocery cart, applying it to OWPP connections requires a pre-conditioning of the data. This is accomplished as follows. For ease of understanding, two examples of valid association rules are provided in (8). D. Combinatorial Search Space A transaction T = {I1, ..., I5} is a subset of I (T ⊂I) consisting of five items derived from the six defining variables of a sample population member κ (2). Four of the five items are derived directly from si, sj, θi,j and B while the fifth is the straight line distance li,j between the OWPPs in question. A member κ may produce a single or many unique transactions. The database D is the set of N transactions derived from the rule making population K. The difficulty of finding the optimal HV transmission topol- ogy that connects a cluster of OWPPs to a PCC onshore increases exponentially with the number of OWPPs due to the combinatorial nature of the search space. A formal description of this search space is derived in [22], details of which are out of the scope of this paper and the authors refer readers to the original paper. What follows is an intuitive description for the sake of understanding how association rules can be used to reduce the size of the space. In [22] the OWPPs within a cluster are represented by cardinal numbers 1 through n and the feasible connected combinations of OWPPs by binary strings 1 through 2n −1 as in: An item set X is a non-empty subset of I (X ⊂I) and is of maximum length five. If the support of an item set is above a specified threshold, i.e. p ≥pt, then the item set is considered a frequent item set. Pseudo code for mining frequent item sets with the apriori algorithm is shown in algorithm 1. ∪(Fk) is the set of all frequent item sets X with length: 2 ≤k ≤5. The apriori algorithm mines the frequent item sets by leverag- ing the downward closer principle which can be seen on line 14 of the pseudo code. The downward closer principle states that an item set of length k can only be frequent if all subsets of length k −1 are also frequent item sets. From the mined frequent item sets, Xk ∈∪(Fk), association rules are found by calculating the subsets of each frequent item, Sk ∈Xk, and creating the relation Sk ⇒(Xk −Sk). The rule is considered An item set X is a non-empty subset of I (X ⊂I) and is of maximum length five. If the support of an item set is above a specified threshold, i.e. B. Population Sampling The first rule (X1 ⇒Y1) is an example of a rule containing the minimum number of items in the Left Hand Side (LHS), while the second rule (X2 ⇒Y2) contains the maximum number of four items in the LHS. Valid rules can of course comprise any length LHS between these two extremes. X1 = {s0 ≥750}, X2 = {s0 ≤250, s1 > 500, l0,1 > 10, θ0,1 > 10}, (8) (8) From a rule making population K we define I = {I1, I2, ..., Im} as a set of m unique items where each item Ii satisfies at least one of the inequalities specified in (7) or is a member of the binary pair B = {0, 1}. Y1 = Y2 = {B = 0}. Rule one states that if an OWPP is greater than or equal to 750 MVA, it is not economic to connect an additional neighbouring OWPP. Rule two states: given two OWPPs seperated by more than 10 km, if one has a capacity no greater than 250 MVA and the other greater than 500 MVA, then it is not cost effective to combine them in a single shore connection if the angle formed at the PCC by their straight line connections to shore is greater than 10o. Ii ≤si, Ii > si ∀si ∈S, Ii ≤θi,j, Ii > θi,j ∀θi,j ∈∡, Ii ≤li,j, Ii > li,j ∀li,j ∈Li,j Ii ≤si, Ii > si ∀si ∈S, Ii ≤θi,j, Ii > θi,j ∀θi,j ∈∡, Ii ≤li,j, Ii > li,j ∀li,j ∈Li,j (7) (7) Ii ≤li,j, Ii > li,j ∀li,j ∈Li,j 22nd Power Systems Computation Conference B. Population Sampling In order to search for association rules, a random rule making population K of OWPP connections is generated. The as: P(X ⇒Y ) = |XY |/|X| (6) P(X ⇒Y ) = |XY |/|X| (6) (6) PSCC 2022 PSCC 2022 Porto, Portugal — June 27 – July 1, 2022 Porto, Portugal — June 27 – July 1, 2022 22nd Power Systems Computation Conference PSCC 2022 valid if the confidence is above the minimum threshold. valid if the confidence is above the minimum threshold. For our purposes a valid association rule consists of item sets with support greater than or equal to the specified support threshold, a confidence of one and a Right Hand Side (RHS) containing the single item B equal to zero. A RHS of one can also be considered and the problem size would reduce substantially, however, the error would also be much higher. Applying rules with a RHS of one versus zero is equivalent to keeping only the connections that have strong evidence of being cost efficient and eliminating all others, rather than eliminating only those with strong evidence indicating them to not be cost effective. which is the conditional probability that the transactions containing X also contain Y . valid if the confidence is above the minimum threshold. For our purposes a valid association rule consists of item sets with support greater than or equal to the specified support threshold, a confidence of one and a Right Hand Side (RHS) containing the single item B equal to zero. A RHS of one can also be considered and the problem size would reduce substantially, however, the error would also be much higher. Applying rules with a RHS of one versus zero is equivalent to keeping only the connections that have strong evidence of being cost efficient and eliminating all others, rather than eliminating only those with strong evidence indicating them to not be cost effective. containing X also contain Y . Finding association rules that are of interest is a two step process. The first step is to find all frequent item sets satisfying a minimum support level and the second step is to retain only those frequent item sets that have a minimum level of confidence. While the second step is straight forward, the first step involves finding all combinations of items in D. D. Combinatorial Search Space 2 shows an exemplary {TB} for n = 4 OWPPs along with the associated binary string j below Porto, Portugal — June 27 – July 1, 2022 Porto, Portugal — June 27 – July 1, 2022 22nd Power Systems Computation Conference PSCC 2022 Algorithm 1: Apriori Algorithm Input: D, pt Output: frequent item sets: ∪(Fk) 1 Function Apriori(D, pt): 2 F1 ←{∀Ii ∈D | : pi ≥pt} 3 k = 2 4 while (Fk−1 ̸= ∅) do 5 Ck = Generate(Fk−1, k) 6 Fk = Prune(Ck, pt) 7 k = k + 1 8 return ∪(Fk) 9 10 Function Generate(Fk−1, k): 11 for (Xi, Xj) in Fk−1 do 12 Xij = (Xi ∪Xj) 13 if (length(Xij) == k) then 14 if (Xi ⊆Fk−1, ∀Xi ∈Xij | : length(Xi) == k −1) then 15 Ck.add(Xij) 16 return Ck 17 18 Function Prune(Ck, pt): 19 for Xi in Ck do 20 if (support(Xi) ≥pt) then 21 Fk.add(Xi) 22 return Fk Algorithm 1: Apriori Algorithm Input: D, pt Output: frequent item sets: ∪(Fk) 1 Function Apriori(D, pt): 2 F1 ←{∀Ii ∈D | : pi ≥pt} 3 k = 2 4 while (Fk−1 ̸= ∅) do 5 Ck = Generate(Fk−1, k) 6 Fk = Prune(Ck, pt) 7 k = k + 1 8 return ∪(Fk) 9 10 Function Generate(Fk−1, k): 11 for (Xi, Xj) in Fk−1 do 12 Xij = (Xi ∪Xj) 13 if (length(Xij) == k) then 14 if (Xi ⊆Fk−1, ∀Xi ∈Xij | : length(Xi) == k −1) then 15 Ck.add(Xij) 16 return Ck 17 18 Function Prune(Ck, pt): 19 for Xi in Ck do 20 if (support(Xi) ≥pt) then 21 Fk.add(Xi) 22 return Fk Fig. 2. An exemplary {TB} for a 4 OWPP cluster [22] Fig. 3. Topology cross over used in generating {TH} [22] Algorithm 1: Apriori Algorithm p q ( ) 1 Function Apriori(D, pt): 2 F1 ←{∀Ii ∈D | : pi ≥pt} 3 k = 2 4 while (Fk−1 ̸= ∅) do 5 Ck = Generate(Fk−1, k) 6 Fk = Prune(Ck, pt) 7 k = k + 1 8 return ∪(Fk) Fig. 3. Topology cross over used in generating {TH} [22] In [22] set theory is used to build on {B} and to develop a binary string based description of the exhaustive combinatorial search space {H}. In addition, a related topological set {TH} is derived. The process of calculating {TH} can be intuitively understood via fig. D. Combinatorial Search Space 3 in which the topologies in {TB} are combined to form new variations from existing combinations. The binary strings shown below each topology act as “building directions” ensuring that the exhaustive set of topological combinations are considered and that all topologies are valid, i.e. no single OWPP appears more than once within a single topology. 10 Function Generate(Fk−1, k): 11 for (Xi, Xj) in Fk−1 do 12 Xij = (Xi ∪Xj) 13 if (length(Xij) == k) then 14 if (Xi ⊆Fk−1, ∀Xi ∈Xij | : length(Xi) == k −1) then 15 Ck.add(Xij) 16 return Ck 22nd Power Systems Computation Conference D. Combinatorial Search Space p ≥pt, then the item set is considered a frequent item set. Pseudo code for mining frequent item sets with the apriori algorithm is shown in algorithm 1. ∪(Fk) is the set of all frequent item sets X with length: 2 ≤k ≤5. {A} = {gi ∈Z+ 0 | i < n}, {B} = {j ∈Nn 2 | 0 < j ≤2n −1}. (9) The apriori algorithm mines the frequent item sets by leverag- ing the downward closer principle which can be seen on line 14 of the pseudo code. The downward closer principle states that an item set of length k can only be frequent if all subsets of length k −1 are also frequent item sets. From the mined frequent item sets, Xk ∈∪(Fk), association rules are found by calculating the subsets of each frequent item, Sk ∈Xk, and creating the relation Sk ⇒(Xk −Sk). The rule is considered (9) Here, Z+ 0 is the set of integers including zero and Nn 2 is the set of base two natural numbers with a maximum length of n digits. A physical topology tj ∈{TB} is defined for each binary string j ∈{B}. Fig. E. Greedy Algorithm - ARM Hybridization As part of [22], a proven globally optimal greedy search al- gorithm is presented that efficiently searches the combinatorial search space and finds the optimal HV topology. A detailed description of the economic model used to calculate lifetime costs of topologies is provided in [36] using cost data from [37]–[39]. The greedy search is effective for clusters up to 12 OWPPs, however, beyond this point the combinatorial growth of the search space is too great and a modified approach, such as the proposed ARM method, is required. It is again important to stress, that an alternative solution approach to the greedy algorithm, such as an MIP, can be used if deemed appropriate. We have chosen the greedy algorithm as it has been shown to outperform an MIP for this problem type [22]. Fig. 2. An exemplary {TB} for a 4 OWPP cluster [22] Fig. 2. An exemplary {TB} for a 4 OWPP cluster [22] In the hybrid greedy-ARM approach, association rules are used to reduce the sizes of sets {TB} and {TH} in order to limit the rate of growth of the search space and increase the feasible problem size. To understand how this occurs consider the topologies in fig. 2 with binary strings [1110] and [1111]. Assume all OWPPs to have a capacity of 250 MVA and the association rule X1 ⇒Y1 in (8) to be a valid rule. Since the total capacity, si, of the three OWPPs in topology [1110] satisfies the condition of item set X1, connecting an additional OWPP of capacity sj, to create topology [1111] is not cost effective so this candidate connection and therefore the topology is excluded from set {TB}. Fig. 2. An exemplary {TB} for a 4 OWPP cluster [22] it. In the figure, OWPPs are shown as red dots, OSS as black dots, the PCC as a green dot, HV transmission lines in black and MV lines in red. Association rules can further be applied to {TH} when generating topologies via the cross over precedure shown in fig. 3. Due to the combinatorial growth of the system, topologies eliminated from set {TB} have a larger impact on computation time than those eliminated from set {TH}. The OSS is optimally placed in each topology via (10), which minimizes the cost of all connected cabling. B. Test Cases The results of the sensitivity analysis are summarized in fig. 4. The results of the sensitivity analysis are summarized in fig. 4. It is apparent that the percentage of candidate connections that can be eliminated (ϱ) varies greatly depending on the layout of the cluster. This is quite logical, as in the perpendicular case, where a maximum of 22.5% of candidate connections in the control population are eliminated, all PCC connections are directly intersected by all OWPPs within the cluster that are situated closer to the PCC. This creates the possibility to combine two OWPPs into a single export cable without having to divert from the shortest path to the PCC. Comparing this to the parallel case where no PCC connection is directly intersected by a neighbouring OWPP, up to 59.7% of candidate connections can be eliminated. Table II summarizes the results from a set of 18 experimen- tal clusters varying in size from 8 to 21 OWPPs. For clusters up to 20 OWPPs, excluding 13, a single capacity is utilized for all OWPPs within the cluster, while for the 13 and 21 OWPPs cases, the various capacities between 250 MW and 500 MW as outlined in fig. 5 are modelled. The distance specified in the table is the average distance of all OWPPs in the cluster to the PCC. The computation times for the unmodified greedy algorithm τg and the hybrid greedy-ARM approach τarm are compared and highlighted in grey and cyan respectively. The transmission topologies of regions with up to twelve OWPPs were optimized using both the unmodified greedy algorithm and the hybrid greedy-ARM algorithm for comparison. Beyond twelve OWPPs the unmodified algorithm is no longer able to compute a solution due to both time and memory constraints. In fig. 6 a visual comparison of the computational times of the two algorithmic variations is provided. Beyond ten OWPPs a sharp divergence of computation time is observed. Although the hybrid algorithm temporally outperforms the unmodified algorithm from ten OWPPs and above, it is beyond twelve OWPPs that the alternative approach is truly beneficial, as the guarantee on optimality provided by the unmodified algorithm warrants the additional computation time. Similar rationale can explain why the minimum support level has a much larger impact in the case of a perpendicularly oriented cluster. A. ARM Sensitivity Analysis A. ARM Sensitivity Analysis Before testing the hybrid algorithm, a sensitity analysis is performed, to determine the impact of the size of the rule making population and minimum support level on ARM. Perpendicular, block and parallel clusters (fig. 1) of 8 OWPPs are studied while varying the rule making population size in steps of 1000, from 1000 to 5000, and considering minimum support levels of one to five percent in steps of one percent. For each of the three layouts, a 5000 member control population, Kc, is generated to quantify both the percentage of connections eliminated (ϱ) as well as the associated error (ϵ). ϱ is the ratio of eliminated members of the population over the entire population and ϵ is the percentage of wrongly eliminated members of the control population over the entire population. Formally, these values are calculated as in (11). Here Kci is the subset of the control population where the antecedent, Xi, of association rule i applies. KB=1 ci is the subset of Kci where the consequent is Yi = B = 1. The set of all rules discovered is denoted by R and the norm implies the number of members within the set. Fig. 4. The variation in the achieved size reduction of the control population (ϱ), computational time (τ) and error (ϵ) in the control population for the perpendicular, block and parrallel 8 OWPPs cases, considering multiple rule making population sizes and minimum support levels. Fig. 4. The variation in the achieved size reduction of the control population (ϱ), computational time (τ) and error (ϵ) in the control population for the perpendicular, block and parrallel 8 OWPPs cases, considering multiple rule making population sizes and minimum support levels. all simulated clusters allows for a better understanding of the variation caused by varying cluster size and layout. As such, in the remaining analysis, a sample population of 2000 and a minimum support level of 2% are used unless specified otherwise. ϱ = ∥ ∥R∥ S i=1 Kci∥ ∥Kc∥ , ϵ = P∥R∥ i=1 ∥KB=1 ci ∥ ∥Kc∥ (11) (11) III. RESULTS III. RESULTS E. Greedy Algorithm - ARM Hybridization min  n X i=1 li · ei  (10) (10) 22nd Power Systems Computation Conference PSCC 2022 Porto, Portugal — June 27 – July 1, 2022 Porto, Portugal — June 27 – July 1, 2022 PSCC 2022 6 Fig. 4. The variation in the achieved size reduction of the control population (ϱ), computational time (τ) and error (ϵ) in the control population for the perpendicular, block and parrallel 8 OWPPs cases, considering multiple rule making population sizes and minimum support levels. 22nd Power Systems Computation Conference Porto, Portugal — June 27 – July 1, 2022 B. Test Cases [MW] [km] OWPPs [Me ] τg [s] τarm [s] ε [%] Perpendicular 250 65 8 1480 226 711 0.07 250 47 9 1434 814 982 1.05 250 65 10 1743 4042 2548 0.42 250 61 12 2199 84580 11862 0.36 Parallel 250 35 8 1081 283 1397 0.06 250 60 9 1603 1593 2439 0.11 250 75 10 2169 6386 2697 0.08 250 54 12 *1807 161906 14050 0.27 Block K=2000 250 85 8 1678 264 1160 0.08 250 59 9 1609 1313 1774 0.89 250 70 10 1953 6567 2577 0.88 250 40 12 1681 112463 2201 0.37 250 75 15 3069 - 176197 1.41 300 47 16 2933 - 18131 0.51 300 65 18 2833 - 1536 0.15 350 65 20 3492 - 6105 0.42 fig.5 55 13 2946 - 4765 3.96 fig.5 31 21 3546 - 25772 4.26 Block K=5000 fig.5 55 13 2946 - 7207 1.16 fig.5 31 21 3545 - 74449 1.06 *hybrid greedy-ARM algorithm solution topology: 1809 Me . COMPARISON OF THE UNMODIFIED GREEDY ALGORITHM TO THE ARM APPROACH. Fig. 6. A log plot comparison of computation times for perpendicular, block and parallel clusters of 8 to 12 OWPPs. Fig. 7. Optimal topology for 5.2 GW cluster consisting of 13 concessions (Left). Optimal topology for 8 GW cluster consisting of 21 concessions (Right). The black dots show the optimal location and number of OSSs. HV export cables in black are at 220 kV and MV cables in red at 66 kV. Fig. 5. Layouts of 5.2 GW cluster of 13 concessions (Left) and 8 GW cluster of 21 concessions (Right). Capacities of OWPPs are displayed in the top left corner of each concession in units of 100 MW. Fig. 7. Optimal topology for 5.2 GW cluster consisting of 13 concessions (Left). Optimal topology for 8 GW cluster consisting of 21 concessions (Right). The black dots show the optimal location and number of OSSs. HV export cables in black are at 220 kV and MV cables in red at 66 kV. errors to acceptable levels of 1.16 % and 1.06 % respectively. In the 21 OWPPs case a very slight (-0.02 %) improvement on the cost of the previous solution resulted. Despite being an insignificant improvement, this still demonstrates the necessity to increase the sample population size as the problem size increases. The solution topologies shown in fig. B. Test Cases [MW] [km] OWPPs [Me ] τg [s] τarm [s] ε [%] Perpendicular 250 65 8 1480 226 711 0.07 250 47 9 1434 814 982 1.05 250 65 10 1743 4042 2548 0.42 250 61 12 2199 84580 11862 0.36 Parallel 250 35 8 1081 283 1397 0.06 250 60 9 1603 1593 2439 0.11 250 75 10 2169 6386 2697 0.08 250 54 12 *1807 161906 14050 0.27 Block K=2000 250 85 8 1678 264 1160 0.08 250 59 9 1609 1313 1774 0.89 250 70 10 1953 6567 2577 0.88 250 40 12 1681 112463 2201 0.37 250 75 15 3069 - 176197 1.41 300 47 16 2933 - 18131 0.51 300 65 18 2833 - 1536 0.15 350 65 20 3492 - 6105 0.42 fig.5 55 13 2946 - 4765 3.96 fig.5 31 21 3546 - 25772 4.26 Block K=5000 fig.5 55 13 2946 - 7207 1.16 fig.5 31 21 3545 - 74449 1.06 *hybrid greedy-ARM algorithm solution topology: 1809 Me . Fig. 5. Layouts of 5.2 GW cluster of 13 concessions (Left) and 8 GW cluster of 21 concessions (Right). Capacities of OWPPs are displayed in the top left corner of each concession in units of 100 MW. Fig. 6. A log plot comparison of computation times for perpendicular, block and parallel clusters of 8 to 12 OWPPs. Fig. 7. Optimal topology for 5.2 GW cluster consisting of 13 concessions (Left). Optimal topology for 8 GW cluster consisting of 21 concessions (Right). The black dots show the optimal location and number of OSSs. HV export cables in black are at 220 kV and MV cables in red at 66 kV. errors to acceptable levels of 1.16 % and 1.06 % respectively. In the 21 OWPPs case a very slight (-0.02 %) improvement on the cost of the previous solution resulted. Despite being an insignificant improvement, this still demonstrates the necessity t i th l l ti i th bl i TABLE II TABLE II TABLE II COMPARISON OF THE UNMODIFIED GREEDY ALGORITHM TO THE ARM APPROACH. version. The final column of table II provides a measure of solution quality in the form of error within the 5000 member control population. A significant increase in error was not detected in the single concession capacity problems even as the number of OWPPs grew beyond twelve and a direct comparison to the optimal solution was no longer possible. In the cases of 13 and 21 OWPPs, where the sizes of the OWPPs are varied, however, the error obtained is significantly different between different sample population sizes. When using a sample population of 2000, an error of 3.96 % and 4.26 % occurred respectively. A second optimization was therefore performed after increasing the rule making populations to K = 5000. This lowered the The final column of table II provides a measure of solution quality in the form of error within the 5000 member control population. A significant increase in error was not detected in the single concession capacity problems even as the number of OWPPs grew beyond twelve and a direct comparison to the optimal solution was no longer possible. In the cases of 13 and 21 OWPPs, where the sizes of the OWPPs are varied, however, the error obtained is significantly different between different sample population sizes. When using a sample population of 2000, an error of 3.96 % and 4.26 % occurred respectively. A second optimization was therefore performed after increasing the rule making populations to K = 5000. This lowered the B. Test Cases 7 are those obtained with K = 5000. Fig. 5. Layouts of 5.2 GW cluster of 13 concessions (Left) and 8 GW cluster of 21 concessions (Right). Capacities of OWPPs are displayed in the top left corner of each concession in units of 100 MW. B. Test Cases In this case, on average, 1.8 times as many candidate connections are eliminated with the minimum sup- port level set at 1% compared to 5%. Both block and parallel formations are largely unaffected by the change in minimum support, indicating the rules enjoy a level of support above 5% in most cases. Varying the rule making sample population size (K) has little impact on the reduction in candidate connections. However, larger populations do result in lower overall error (ε) at the expense of computation time (τ). In this analysis, given the large number of clusters being analyzed and the overall error, even in the worst case, being very low at 1.2%, a large sample population at the expense of increased computation time was not deemed necessary. Furthermore, maintaining consistent values for the population and minimum support level over In all simulations both algorithms found the identical solution with the exception being twelve OWPPs in parallel, where the hybrid greedy-ARM algorithm found a topology costing 1808.9 Me versus the 1807.4 Me with the unmodified al- gorithm. This is a difference of less than 0.1 %, however, it does remind us that the hybrid greedy-ARM algorithm does not provide a guarantee on optimality as with the unmodified 22nd Power Systems Computation Conference PSCC 2022 Porto, Portugal — June 27 – July 1, 2022 Porto, Portugal — June 27 – July 1, 2022 7 Fig. 6. A log plot comparison of computation times for perpendicular, block and parallel clusters of 8 to 12 OWPPs. TABLE II COMPARISON OF THE UNMODIFIED GREEDY ALGORITHM TO THE ARM APPROACH. 22nd Power Systems Computation Conference REFERENCES [1] The Paris Agreement. United Nations Treaty Collection XXVII 7.d. [25] Muhammad Sohail Ibrahim, Wei Dong, and Qiang Yang. Machine learning driven smart electric power systems: Current trends and new perspectives. Applied energy, 272:115237, 2020. [2] Walsh et al. Offshore Wind in Europe, key trends and statistics 2019. Technical report, Wind Europe, 2020. [3] O’Sullivan et. al. Offshore Wind in Europe, key trends and statistics 2020. Technical report, Wind Europe, 2021. [26] Marug´an et. al. A survey of artificial neural network in wind energy systems. Applied energy, 228:1822–1836, 2018. [27] Qiuye Sun and Lingxiao Yang. From Independence to Interconnection- A Review of AI Technology Applied in Energy Systems. CSEE Journal of Power and Energy Systems, 5(1):21–34, 2019. [4] Modular Offshore Grid Elia. https://www.elia.be/en/projects/grid- projects/Modular20Offshore20Grid. Accessed: 19-07-17. [5] Ouahid Dahmani, Salvy Bourguet, Mohamed Machmoum, Patrick Guerin, and Pauline Rhein. Reliability analysis of the collection system of an offshore wind farm. In 2014 Ninth International Conference on Ecological Vehicles and Renewable Energies (EVER), pages 1–6. IEEE, 2014. [28] Rasmus Borrmann Dr. Knud Rehfeldt Anna-Kathrin Wallasch Silke L¨uers. Capacity Densities of European Offshore Wind Farms. Technical report, Federal Maritime and Hydrographic Agency, 2018. [29] BVG Associates. Wind farm costs. Technical report, Catapult Offshore Renewable Energy. [6] P.D Hopewell, F Castro-Sayas, and D.I Bailey. Optimising the Design of Offshore Wind Farm Collection Networks. In Proceedings of the 41st International Universities Power Engineering Conference, volume 1, pages 84–88. IEEE, 2006. [30] Rakesh Agrawal, Tomasz Imieli´nski, and Arun Swami. Mining associa- tion rules between sets of items in large databases. In SIGMOD Record (ACM Special Interest Group on Management of Data), volume 22, pages 207–216, 1993. [7] X. Gong, S. Kuenzel, and B. C. Pal. Optimal Wind Farm Cabling. IEEE Transactions on Sustainable Energy, 9(3):1126–1136, 2018. [31] K.S Lakshmi and G. Vadivu. Extracting Association Rules from Medical Health Records Using Multi-Criteria Decision Analysis. Procedia Computer Science, 115:290–295, 2017. 7th International Conference on Advances in Computing Communications, ICACC-2017, 22-24 August 2017, Cochin, India. [8] Peng Hou, Weihao Hu, Cong Chen, and Zhe Chen. Optimisation of offshore wind farm cable connection layout considering levelised production cost using dynamic minimum spanning tree algorithm. IET renewable power generation, 10(2):175–183, 2016. [32] Dong Liu, Yunping Chen, Youping Fan, and Guang Shen. The appli- cation of association rule mining in power system restoration. In 2006 IEEE Power Engineering Society General Meeting, pages 5 pp.–, 2006. IV. CONCLUSIONS AND FUTURE WORK In this work a novel hybrid method for offshore transmission topology optimization is presented in which ARM is used to dynamically generate constraints to reduce the combina- torial search space of a greedy algorithm. Different control populations are used to quantify the error introduced by the generated constraints. The method is applied to 18 OWPP clusters varying in size from eight to 21 OWPPs. For feasible problem sizes, the solution of the unmodified greedy and hybrid greedy-ARM algorithms are directly compared. The algorithms found identical solutions in all studied cases except 22nd Power Systems Computation Conference PSCC 2022 Porto, Portugal — June 27 – July 1, 2022 22nd Power Systems Computation Conference Porto, Portugal — June 27 – July 1, 2022 22nd Power Systems Computation Conference 8 one where the solution differed by less than 0.1%. For clusters larger than ten OWPPs a significant reduction in computational time is achieved. For problem sizes beyond the capability of the unmodified greedy algorithm, the hybrid greedy-ARM variation was able to find a solution while maintaining a worst case scenario error in the control population of less than 1.5%. This paper has shown the feasibility and utility of such an approach, however, further research into more efficient implementations is still essential in order to fully realize it’s potential as an optimization method. Future research into alternative algorithms to the apriori algorithm, ones that allow constraints to be imposed on mined item sets as only those with a RHS of false are of interest would be beneficial. Also, the relationship between the rule making sample population, minimum support level, cluster size and the capacities of OW- PPs should be established for global applicability. Finally, for general applicability of the optimization method, a generalized procedure to adapt the method, e.g., selection of the rule making algorithm and determination of the control population size, to a wide range of problem types should be investigated. [15] A. M. Jenkins, M. Scutariu, and K. S. Smith. Offshore wind farm inter- array cable layout. In 2013 IEEE Grenoble Conference, pages 1–6, 2013. [16] J.S Gonzalez, A.G.G Rodriguez, J.C Mora, J.R Santos, and M.B Payan. A new tool for wind farm optimal design. pages 1–7, 2009. p g p g [17] Dahmani et al. Optimization of the connection topology of an offshore wind farm network. IEEE. Syst. J. 2015, (9):1519–1528, 2015. IV. CONCLUSIONS AND FUTURE WORK [18] Ouahid Dahmani, Salvy Bourguet, Mohamed Machmoum, Patrick Guerin, Pauline Rhein, and Lionel Josse. Optimization and Reliability Evaluation of an Offshore Wind Farm Architecture, copyright = Copy- right 2017 Elsevier B.V., All rights reserved. IEEE transactions on sustainable energy, 8(2):542–550, 2017. [19] Huang Lingling, Fu Yang, and Guo Xiaoming. Optimization of electrical connection scheme for large offshore wind farm with genetic algorithm. pages 1–4, 2009. [20] Hakan Ergun, Dirk Van Hertem, and Ronnie Belmans. Transmission System Topology Optimization for Large-Scale Offshore Wind Integra- tion. IEEE transactions on sustainable energy, 3(4):908–917, 2012. [21] S.Hardy, H.Ergun, D.Van Hertem, K. Van Brusselen. A Techno- Economic MILP Optimization of Multiple Offshore Wind Concessions. Large-Scale Grid Integration of Renewable Energy in India, 2019. [22] S.Hardy, H.Ergun, D.Van Hertem. A Greedy Algorithm for Calculating an Optimally Bounded From Below Hierarchy of Transmission Network Topologies for Offshore Wind Power. IEEE Transactions on Power Systems 2021, 2020. y [23] Guangchun Ruan, Haiwang Zhong, Guanglun Zhang, Yiliu He, Xuan Wang, and Tianjiao Pu. Review of Learning-Assisted Power System Optimization. 2020. p [24] Zidong Zhang, Dongxia Zhang, and Robert C Qiu. Deep Reinforcement Learning for Power System Applications: An Overview. CSEE Journal of Power and Energy Systems, 6(1):213–225, 2020. REFERENCES [9] Sebastian Lehmann, Ignaz Rutter, Dorothea Wagner, and Franziska Wegner. A Simulated-Annealing-Based Approach for Wind Farm Cabling. In Proceedings of the Eighth International Conference on Future Energy Systems, e-Energy ’17, page 203–215, New York, NY, USA, 2017. Association for Computing Machinery. [33] Fast discovery of association rules., author=Agrawal, Rakesh and Man- nila, Heikki and Srikant, Ramakrishnan and Toivonen, Hannu and Verkamo, A Inkeri and others. Advances in knowledge discovery and data mining, 12(1):307–328, 1996. [10] T. Zuo, Y. Zhang, K. Meng, and Z. Y. Dong. Collector System Topology for Large-Scale Offshore Wind Farms Considering Cross-Substation Incorporation. IEEE Transactions on Sustainable Energy, pages 1–1, 2019. [34] Jiawei Han, Jian Pei, Yiwen Yin, and Runying Mao. Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Ap- proach. Data mining and knowledge discovery, 8(1):53–87, 2004. [11] Yuanhang Qi, Peng Hou, Liang Yang, and Guangya Yang. Simultaneous optimisation of cable connection schemes and capacity for offshore wind farms via a modified bat algorithm. Applied sciences, 9(2):265, 2019. [35] Mohammed J. Zaki. Scalable algorithms for association mining. IEEE Transactions on knowledge and data engineering, 12(3):372–390, 2000. [36] S.Hardy, H.Ergun, D.Van Hertem. Economic Analysis and Comparison of options for HVAC, HVDC and OFAC Offshore Wind Power Connec- tions. IEEE PES Powertech conference - Milan, 2019. [12] M Banzo and A Ramos. Stochastic optimization model for electric power system planning of offshore wind farms. IEEE transactions on power systems, 26(3):1338–1348, 2011. [37] Flament et al. North Sea Grid, Final Report. Technical report, 3E, 2014. [13] S. Lumbreras and A. Ramos. A Benders’ Decomposition Approach for Optimizing the Electric System of Offshore Wind Farms. IEEE Trondheim PowerTech conference, 2011. [38] NSCOGI. Offshore Transmission Technology. Technical report, Euro- pean Network of Transmission System Operators for Electricity, 2012. [39] Chris Hill. Offshore Transmission Benchmarking and Cost Monitoring. Technical report, Catapult, 2016. [14] Joanna Bauer and Jens Lysgaard. The offshore wind farm array cable layout problem: a planar open vehicle routing problem. Journal of the Operational Research Society, 66(3):360–368, 2015. 22nd Power Systems Computation Conference Porto, Portugal — June 27 – July 1, 2022 PSCC 2022 PSCC 2022
https://openalex.org/W4307385104
https://www.nature.com/articles/s41598-022-22686-z.pdf
English
null
Anxiety in the adult population from the onset to termination of social distancing protocols during the COVID-19: a 20-month longitudinal study
Scientific reports
2,022
cc-by
9,708
Anxiety in the adult population from the onset to termination of social distancing protocols during the COVID‑19: a 20‑month longitudinal study OPEN Asle Hoffart1,2*, Daniel J. Bauer3, Sverre Urnes Johnson1,2 & Omid V.· Ebrahimi1,2 The social distancing protocols (SDPs) implemented as a response to the COVID-19 pandemic may seriously influence peoples’ mental health. We used a sample of 4361 Norwegian adults recruited online and stratified to be nationally representative to investigate the evolution of anxiety following each modification in national SDPs across a 20-month period from the onset of the pandemic to the reopening of society and discontinuation of SDPs. The mean anxiety level fluctuated throughout the observation period and these fluctuations were related to the stringency of the modified SDPs. Those with a high initial level almost in unison showed a substantial and lasting decrease of anxiety after the first lifting of SDPs. A sub-group of 9% had developed a persistent anxiety state during the first 3 months. Younger age, pre-existing psychiatric diagnosis, and use of unverified information platforms proved to predict marked higher anxiety in the long run. In conclusion, individuals with a high level of anxiety at the outbreak of the pandemic improved when the social distancing protocols were lifted. By contrast, a sizeable subgroup developed lasting clinical levels of anxiety during the first 3 months of the pandemic and is vulnerable to prolonged anxiety beyond the pandemic period. The COVID-19 pandemic and the accompanying social distancing protocols (SDPs) have been associated with an increase in adverse mental health ­symptoms1. In particular, and not least due to the life-threatening nature of the virus, anxiety symptoms and disorders have ­increased2. A systematic review of data reporting the prevalence of anxiety disorders during the COVID-19 in 2020 estimated an additional 76.2 million (64.3 to 90.6) cases globally, an increase of 25.6% (23.2 to 28.0)3.h g y There are divergent hypotheses about the further course of anxiety beyond the pandemic outbreak. A trauma perspective on reaction to crises such as pandemics suggests that an initial short-term increase in anxiety is fol- lowed by ­recovery4,5. On the other hand, research on previous pandemics have indicated a long-term heightening of anxiety lasting beyond the ­pandemic6. Moreover, a few longitudinal studies extended into 2021 – the longest to July ­20217—have reported that a high anxiety level at the COVID-19 outbreak has persisted or ­increased7–10. www.nature.com/scientificreports www.nature.com/scientificreports Scientific Reports | (2022) 12:17846 Results l Sample characteristics and representativeness. The age of the 4361 participants ranged from 18 to 86 years (M = 36.5, SD = 14.8), 2,152 (49.6%) of them being female (compared to 49.5% females in the popula- tion), and 1543 (35.4%) having a university degree (compared to 35.6% in the population). The percentage of participants with preexisting psychiatric diagnosis was 19.0%, representative of the known rate of psychological disorders in the Norwegian adult population, which is between 16.7% and 25.0%15. The quota of participants sampled from each region of Norway was further proportional to each respective region size, yielding a geo- graphically representative sample of Norway. The demographic composition of participants was stable across the 20-month period of the study, with no particular subgroup revealing disproportional attrition rates across the study period. At the final assessment, 45.0% of the participants were female, 38.4% had a university degree, 18.8% reported a psychiatric diagnosis, and age ranged from 18 to 85 years (M = 38.9, SD = 15.4). Sensitivity analyses. Sensitivity analyses were performed on the portion of participants who had provided complete data across all assessments, thus fully serving as their own controls regarding changes and fluctuations across assessments and modifications of social distancing protocols (SDPs). These analyses replicated the find- ings from the main sample, showing identical change profiles and predictive relationships across all analyses, with the correlation between the matrices containing the parameter estimates from this attrition-controlled sample and the main sample being r = 0.99. Model fit. Fit was excellent for the unconditional LCS model, with χ2 (15) = 73.34, RMSEA = 0.030 (90% CI 0.023 to 0.037), CFI = 0.992, TLI = 0.989, and SRMR = 0.030. The conditional LCS model also revealed good fit upon introduction of the exogenous predictors, with χ2(140) = 436.71, RMSEA = 0.022 (90% CI 0.020 to 0.025), CFI = 0.968, TLI = 0.952, and SRMR = 0.038. When fitting the unconditional LCS model, an improper estimate was obtained for the variance of δηt6. The estimated variance, though negative, was within sampling error of zero. Such estimates can occur even with properly specified models simply due to sampling ­variability16. We thus fol- lowed common practice and restricted the value of the parameter to zero in the final fitted model (see Table 1). Group‑level anxiety profile across the pandemic period. www.nature.com/scientificreports/ younger ­age3, female ­sex3, lower educational ­level11, pre-existing psychiatric ­diagnosis11, being ­unemployed12, worry about job and ­economy12, use of unverified information ­platforms13, and living ­alone11 are associated with more anxiety. y To investigate the questions posed above, statistical models that make change in anxiety as outcome depend- ent on shifts in SDPs and addresses individual developments, that is, within-person changes are needed. This is achieved in latent change score (LCS) models as they make time-dependent change as opposed to time-dependent status the outcome of ­interest14. Moreover, these models estimate within-person change and thus individual dif- ferences in symptom profiles across the pandemic can be revealed. Finally, inspecting individual change profiles may reveal critical points at which individuals undergo a transition into a stable detrimental anxiety state or, conversely, from an anxiety state to a stable non-anxious state.h y y The purpose of the present longitudinal study of the adult Norwegian population was to investigate the evolu- tion of anxiety following each modification of national SDPs across a 20-month period. The period lasted from the onset of the pandemic and the initial implementation of SDPs in March 2020 to the reopening of society and complete discontinuation of SDPs in September 2021. Thus, the study comprehensively investigates the evolution of anxiety from the onset to the termination of SDPs during the COVID-19 pandemic. The following research questions were investigated: (a) Does the population-level change profile of anxiety across modifications of SDPs follow the stringency of the SDPs? (b) Is there variation among individuals in initial level of and changes in anxiety across modifications of SDPs? (c) Do individuals at some point change from a non-anxious state to a stable high level of anxiety, or from an anxiety state to a stable non-anxious state? (d) How does the initial level of anxiety relate to changes from modification to modification of SDPs? (e) To what extent do the factors age, sex, education, psychiatric diagnosis, information platform preference, employment status, worry about job and economy, and living status predict initial levels of and changes in anxiety from modification to modification? (f) What is the connection between anxiety and contemporaneous COVID-19 infection rates? Anxiety in the adult population from the onset to termination of social distancing protocols during the COVID‑19: a 20‑month longitudinal study OPEN Thus, there is a need to examine the temporal development of anxiety in the population until the pandemic is under control and the use of SDPs is terminated.l Moreover, fear of infection and general anxiety may fluctuate as related to stringent SDPs (e.g., lockdown signalling danger), by lightning and removal of SDPs (e.g., less social distancing and more danger of infection), and by reported infection rates. Accordingly, it is of importance to examine to what extent anxiety changes in consort with fluctuations in the stringency of implemented SDPs as well as in infection rates. l g y p Furthermore, it is pertinent to study the individual development of anxiety and the extent to which the course of it varies over individuals. For instance, some individuals may reveal no change, others change from a high to constant low level or, conversely, from a low to a constant high level, with the latter individuals at a greater risk for prolonged anxiety beyond the pandemic.f p g y y p Investigating predictors of these individual differences would help identify those most at risk and allow for efficient deployment of treatment resources. Studies from the early phases of the pandemic have revealed that 1Department of Psychology, University of Oslo, Oslo, Norway. 2Research Institute, Modum Bad Psychiatric Hospital, Postboks 33, N‑3370 Vikersund, Norway. 3Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, USA. *email: asle.hoffart@modum-bad.no | https://doi.org/10.1038/s41598-022-22686-z www.nature.com/scientificreports/ Results l Figure 1 displays the mean-level profile of anxiety over the observation period, with each breaking point in the curve representing an assessment interval. The strictness of the SDPs at the intervals is also displayed. From the introduction of SDPs (T1) to their discon- tinuation (T7), the latent anxiety level changed from 5.6 (SD = 3.8) to 4.5 (SD = 3.1). Across the five in-between modifications, anxiety severity fluctuated between these levels. Between adjacent time points, latent anxiety decreased from T1 and T2, increased from T2 to T3, and decreased from T4 to T5 and from T5 to T6 (see intercepts in Table 1). Thus, anxiety co-varied with the strictness of SDPs, with increases and decreases in strict- ness being associated with subsequent increases and decreases in anxiety, respectively. One exception from the overall pattern occurred from T6 to T7, where no notable anxiety change was observed despite that SDPs were discontinued. The correlation over the observation period between anxiety and strictness was 0.88 and between anxiety and mean daily infection rate in the measurement intervals was − 0.24. Individual variation of anxiety profiles. The population average anxiety profile and the individual change profiles across the 20-month study period are exhibited in Fig. 2. For visualization purposes, the change profiles of a random subset of 200 individuals are displayed, representative of the sample. Individual change profiles of all participants in the study are presented in segments of 400 through 11 subfigures in online Sup- plementary Fig. S1. Scientific Reports | (2022) 12:17846 | Results l https://doi.org/10.1038/s41598-022-22686-z Scientific Reports | (2022) 12:17846 | www.nature.com/scientificreports/ Estimate SE Z p Unconditional model 1· Intercepts ηt1 5.58 0.07 76.44  < 0.001* δηt2  − 0.81 0.11  − 7.54  < 0.001* δηt3 0.62 0.08 8.16  < 0.001* δηt4 0.03 0.07 0.41 0.681 δηt5  − 0.18 0.08  − 2.28 0.023* δηt6  − 0.76 0.08  − 9.28  < 0.001* δηt7 0.01 0.09 0.05 0.957 2· Variances ηt1 18.58 0.51 36.14  < 0.001* δηt2 28.30 0.89 31.85  < 0.001* δηt3 1.76 0.28 6.27  < 0.001* δηt4 0.07 0.20 0.33 0.739* δηt5 1.33 0.20 6.52  < 0.001* δηt6 0.00 NA NA NA δηt7 0.65 0.30 2.20 0.028* 3· Covariances ηt1 ~  ~ δηt2  − 16.34 0.60  − 27.47  < 0.001* ηt1 ~  ~ δηt3 0.20 0.26 0.75 0.451 ηt1 ~  ~ δηt4 0.22 0.24 0.94 0.347 ηt1 ~  ~ δηt5  − 0.59 0.27  − 2.15 0.032* ηt1 ~  ~ δηt6  − 0.95 0.28  − 3.46  < 0.001* ηt1 ~  ~ δηt7 0.05 0.30 0.15 0.879 Conditional model 1· Intercepts ηt1 5.39 0.31 17.32  < 0.001* δηt2  − 1.39 0.41  − 3.36 0.001* δηt3 0.15 0.39 0.38 0.705 δηt4 0.57 0.32 1.78 0.075 δηt5  − 0.07 0.40  − 0.18 0.859 δηt6  − 0.71 0.34  − 2.13 0.033* δηt7  − 0.49 0.34  − 1.44 0.151 2· Variances ηt1 11.13 0.37 30.26  < 0.001* δηt2 22.16 0.77 28.79  < 0.001* δηt3 1.71 0.28 6.07  < 0.001* δηt4 0.07 0.20 0.36 0.718* δηt5 1.17 0.22 5.43  < 0.001* δηt6 0.43 0.24 1.78 0.075 δηt7 0.48 0.32 1.50 0.134 3· Covariances ηt1 ~  ~ δηt2  − 9.89 0.46  − 21.25  < 0.001* ηt1 ~  ~ δηt3 0.01 0.24 0.03 0.979 ηt1 ~  ~ δηt4 0.17 0.21 0.77 0.440 ηt1 ~  ~ δηt5  − 0.34 0.24  − 1.42 0.157 ηt1 ~  ~ δηt6  − 0.95 0.27  − 3.58  < 0.001* ηt1 ~  ~ δηt7  − 0.16 0.27  − 0.58 0.561 4· Regression estimates 4·1· Predictors of ηt1 Age  − 0.72 0.08  − 9.62  < 0.001* Sex  − 1.31 0.14  − 9.42  < 0.001* Education  − 0.18 0.06  − 2.80 0.005* Psychiatric diagnosis 4.04 0.17 23.91  < 0.001* Info. Scientific Reports | (2022) 12:17846 | Results l platform preference  − 0.22 0.28  − 0.78 0.437 Employment status 0.17 0.23 0.74 0.462 Worry job and economy 0.04 0.05 0.80 0.426 Living status  − 0.15 0.22  − 0.71 0.479 Daily infection rate  − 0.10 0.10  − 1.01 0.313 4·7· Predictors of δηt7 Age  − 0.13 0.10  − 1.26 0.205 https://doi.org/10.1038/s41598-022-22686-z Scientific Reports | (2022) 12:17846 | www.nature.com/scientificreports/ Estimate SE Z p Education 0.20 0.09 2.17 0.030* Psychiatric diagnosis 0.20 0.25 0.81 0.419 Info. platform preference 0.73 0.30 2.40 0.016* Employment status  − 0.12 0.24  − 0.50 0.618 Worry job and economy  − 0.04 0.05  − 0.84 0.402 Living status 0.08 0.23 0.36 0.722 Daily infection rate 0.03 0.01 2.10 0.036* Table 1. The results of the unconditional and conditional latent change score (LCS) model of anxiety. ηt1 = Latent intercept at T1 (March 2020); δηt2 = Latent change from T1-T2 (March – July, 2020); δηt3 = Latent change from T2-T3 (July – December, 2020); δηt4 = Latent change from T3-T4 (December 2020 – February, 2021); δηt5 = Latent change from T4-T5 (February – May, 2021); δηt6 = Latent change from T5-T6 (May – August, 2021); δηt7 = Latent change from T6-T7 (August—November, 2021). Age: 0 (18–30 years), 1 (31– 44 years), 2 (45–64 years), 3 (65 years and above). Sex: 0 (females), 1 (males). Education level: 0 (compulsory school), 1 (upper secondary high school), 2 (student), 3 (university degree). Preexisting psychiatric diagnosis: 0 (absence), 1 (presence). Information platform preference: 1 (unmonitored information obtainment sources consisting of social media platforms such as Instagram, Snapchat, TikTok, online forums and blogs, and friends, family and peers), 0 (source-verified platforms encompassing of source-checked and recognized national, regional, and local newspapers, television, and radio channels). Employment status: 0 (unemployed), 1 (employed). Worry about job and economy: 0 (never worry about job and economy), to 12 (worries both about job and economy almost every day). Living status: 0 (not living alone), 1 (living alone). Daily COVID-19 incidence rates were retrieved from the Norwegian Public Health database of infectious disease and matched with the response date of each participant. Most variation in change profiles occurred within the first three months from T1 to T2 (Table 1). The large variation of T2 change scores is reflected in the major presence of intersecting lines between T1 and T2 in Fig. 2. Results l The figure shows that those with a high initial anxiety level almost in unison experienced decreases, many of them considerably. Indeed, the correlation between T1 status and change from T1 to T2 was − 0.62. This negative correlation also reflects that individuals with lower initial levels of anxiety often experienced increases in anxiety from T1 to T2. These increases in anxiety often rose to a clinical level (> = 8), a level that was then prevailingly maintained across the remainder of the pandemic period. Of the 4361 participants, 394 (9.0%) had a clinically important deterioration (increase of minimal 4 points) in anxiety from T1 to T2. Notably, almost all individuals with a stable clinical level of anxiety from T2 to T7 belonged to this sub-group.h y g g p The covariances in the unconditional model (Table 1) show that a higher level of anxiety at T1 was related to more reduction of anxiety from T1 to T2, from T4 to T5, and from T5 to T6. These three periods were all associated with reduced strictness of SDPs. Predictors of anxiety profiles. The effect of each of the exogenous predictors on the initial level and the time-point to time-point changes in anxiety, while controlling for all other predictors in the model, is reported in Table 1. These effects are also displayed in Figs. 3, 4, 5 and 6. hf Younger age, female sex, lower education, pre-existing psychiatric diagnosis, unemployment, and more worry about job and economy were related to higher initial level of anxiety (i.e., ηt1, P-values < 0.05), but these variable values (except unemployment) were also related to more reductions in anxiety from T1 to T2 (Table 1). Younger age and pre-existing psychiatric diagnosis were related to marked higher levels of anxiety over the whole observa- tion period (Fig. 3). Preference for unverified information platforms was related to markedly higher anxiety levels from T2 and onward (Fig. 4), and to a significantly larger anxiety increase from T6 to T7. Females, unemployed, and those living alone had a somewhat higher anxiety level than their counterparts over the observation period (Figs. 5 and 6). Educational level did not influence anxiety beyond baseline, except that those with a university degree had the largest increase from T6 to T7 (Fig. 5). Worry about job and economy had a variable influence with no relationship to the end (T7) level of anxiety (Fig. 6). Results l platform preference 0.15 0.25 0.58 0.560 https://doi.org/10.1038/s41598-022-22686-z Scientific Reports | (2022) 12:17846 | www.nature.com/scientificreports/ Estimate SE Z p Worry job and economy 0.74 0.04 20.58  < 0.001* Living status  − 0.23 0.21  − 1.10 0.273 Daily infection rate 0.28 0.10 2.80 0.005* 4·2· Predictors of δηt2 Age 0.40 0.12 3.38 0.001* Sex 0.96 0.23 4.25  < 0.001* Education 0.28 0.11 2.60 0.009* Psychiatric diagnosis  − 3.69 0.28  − 13.27  < 0.001* Info. platform preference 0.58 0.36 1.61 0.107 Employment status 0.29 0.28 1.02 0.307 Worry job and economy  − 0.64 0.06  − 10.65  < 0.001* Living status 0.68 0.30 2.28 0.023* Daily infection rate 2.84 1.10 2.58 0.010* 4·3· Predictors of δηt3 Age 0.10 0.09 1.16 0.246 Sex  − 0.12 0.17  − 0.68 0.495 Education  − 0.11 0.08  − 1.34 0.179 Psychiatric diagnosis 0.34 0.21 1.63 0.104 Info. platform preference  − 0.01 0.24  − 0.04 0.966 Employment status 0.45 0.21 2.19 0.029* Worry job and economy  − 0.00 0.05  − 0.03 0.980 Living status 0.15 0.20 0.79 0.429 Daily infection rate 0.03 0.06 0.60 0.546 4·4· Predictors of δηt4 Age  − 0.03 0.08  − 0.37 0.711 Sex 0.01 0.16 0.06 0.953 Education  − 0.05 0.08  − 0.64 0.523 Psychiatric diagnosis 0.07 0.20 0.34 0.734 Info. platform preference 0.04 0.25 0.14 0.887 Employment status  − 0.02 0.20  − 0.10 0.925 Worry job and economy  − 0.07 0.04  − 1.65 0.100 Living status  − 0.41 0.20  − 2.06 0.040* Daily infection rate  − 0.11 0.08  − 1.32 0.186 4·5· Predictors of δηt5 Age 0.04 0.09 0.47 0.640 Sex 0.11 0.18 0.61 0.544 Education 0.01 0.08 0.10 0.924 Psychiatric diagnosis 0.13 0.22 0.60 0.548 Info. platform preference  − 0.09 0.27  − 0.32 0.750 Employment status  − 0.04 0.22  − 0.20 0.844 Worry job and economy 0.06 0.05 1.29 0.198 Living status 0.06 0.21 0.26 0.791 Daily infection rate  − 0.06 0.08  − 0.74 0.457 4·6· Predictors of δηt6 Age 0.02 0.10 0.20 0.845 Sex 0.08 0.19 0.45 0.650 Education  − 0.07 0.09  − 0.74 0.459 Psychiatric diagnosis  − 0.04 0.24  − 0.19 0.851 Info. Results l More worry was associated with more increase of anxiety from T3 to T4. Daily infection rate was positively related to anxiety at T1, to anxiety change from T1 to T2, and to anxiety change from T6 to T7. Discussionh Individuals who had an initial high level of anxiety – above or around the clinical cut-off of 8 – almost in unison showed a substantial and lasting decrease of anxiety after the SDPs had been lifted. This is consistent with a trauma perspective on reactions to the ­pandemic4 and may reflect that they after an initial increase of anxiety somehow adapted to the stressors posed by the infec- tion pressure and the SDPs. They remained in a non-anxious state and were predominantly resilient toward new infection waves and re-implementations of strict SDPs. A second change pattern consistent with critical transi- tions was seen for individuals with initially low anxiety who experienced a clinically important increase to a clinical level, which then was maintained throughout the pandemic to the discontinuation of SDPs. This critical increase was situated within the first three months of the pandemic and may have occurred before and/or after the modification of SDPs. In the former case, the individual experienced stressors of a severity that overloaded their resilience and access to environmental resources. The lifting of the SDPs seemed to have little mitigating effect. In the latter case, the anxiety increase may be a response to the SDPs discontinuation. The discontinua- tion may have led to heightened degree of worry about contagion or increased social anxiety. In any case, these individuals remained in a chronic anxiety state and are vulnerable to prolonged anxiety beyond the pandemic. y p g y y p Consistent with previous studies, younger ­age3, female ­sex3, lower ­education11, pre-existing psychiatric ­diagnosis11, ­unemployment12, and more worry about job and ­economy12 were significantly associated with higher initial levels of anxiety. On the other hand, the same predictors were related to greater reductions in anxiety from T1 to T2, probably reflecting that those sub-groups most vulnerable to negative influence of infection rates and SDPs also were more relieved when the infections rates decreased to a minimum and the SDPs were partly discontinued.i p y Younger age, pre-existing psychiatric diagnosis, and use of unverified information platforms predicted higher anxiety in the long run. The lives of young people involve more social contact and activities than those of older people and younger people may therefore suffer more from the SDPs and the ­lockdown18. Unverified platforms may spread exaggerated or false information about the dangers of the pandemic and thus lead to heightened ­anxiety13. Discussionh The mean-level profile of anxiety and the strictness of social distancing protocols (SDPs) over the 20-month observation period. Anxiety change patterns were modelled upon all modifications in national SD over the pandemic period. The dashed lines represent the 95% confidence intervals. Each month is coded in units of 30 days ensuing the starting point March 31, 2020, coded as 0. Figure 1. The mean-level profile of anxiety and the strictness of social distancing protocols (SDPs) over the 20-month observation period. Anxiety change patterns were modelled upon all modifications in national SDPs over the pandemic period. The dashed lines represent the 95% confidence intervals. Each month is coded in units of 30 days ensuing the starting point March 31, 2020, coded as 0. patterns consistent with critical transitions to a new stable ­state17. Individuals who had an initial high level of anxiety – above or around the clinical cut-off of 8 – almost in unison showed a substantial and lasting decrease of anxiety after the SDPs had been lifted. This is consistent with a trauma perspective on reactions to the ­pandemic4 and may reflect that they after an initial increase of anxiety somehow adapted to the stressors posed by the infec- tion pressure and the SDPs. They remained in a non-anxious state and were predominantly resilient toward new infection waves and re-implementations of strict SDPs. A second change pattern consistent with critical transi- tions was seen for individuals with initially low anxiety who experienced a clinically important increase to a clinical level, which then was maintained throughout the pandemic to the discontinuation of SDPs. This critical increase was situated within the first three months of the pandemic and may have occurred before and/or after the modification of SDPs. In the former case, the individual experienced stressors of a severity that overloaded their resilience and access to environmental resources. The lifting of the SDPs seemed to have little mitigating effect. In the latter case, the anxiety increase may be a response to the SDPs discontinuation. The discontinua- tion may have led to heightened degree of worry about contagion or increased social anxiety. In any case, these individuals remained in a chronic anxiety state and are vulnerable to prolonged anxiety beyond the pandemic. patterns consistent with critical transitions to a new stable ­state17. Discussionh The present results demonstrated that the mean anxiety severity fluctuated as a function of the stringency and leniency of SDPs, with increased stringency being associated with heightened anxiety. An exception from this general pattern was that there were no signs of anxiety reduction ensuing the complete discontinuation of SDPs. However, although the message from the government was that the pandemic was under control, the mean infec- tion rate was as high as 933 new cases per day and raised from 424 to 1762 during the last measurement window. This may have prevented anxiety from reducing. Overall, anxiety level correlated strongly with strictness of SDPs over the pandemic, but negligibly with infection rate.h p , g g y The preponderance of variation in changes occurred from the initial implementation of SDPs (T1) to their partial discontinuation three months later (T2). Inspection of individual change profiles revealed two change Scientific Reports | (2022) 12:17846 | https://doi.org/10.1038/s41598-022-22686-z www.nature.com/scientificreports/ T1 T2 T3 T4 T5 T6 T7 2 4 6 8 20 40 60 80 100 0 (March 2020) 3 (June 2020) 6 (Sept 2020) 9 (Dec 2020) 12 (March 2021) 15 (June 2021) 18 (Sept 2021) 21 (Dec 2021) Months (30 day units from March 31 2020) Mean level of anxious symptomatology Oxford Stringency Index Anxiety symptoms SDP stringency Patterns of change in anxiety symptoms across the 20−month study period T1 T2 T3 T4 T5 T6 T7 2 4 6 8 20 40 60 80 100 0 (March 2020) 3 (June 2020) 6 (Sept 2020) 9 (Dec 2020) 12 (March 2021) 15 (June 2021) 18 (Sept 2021) 21 (Dec 2021) Months (30 day units from March 31, 2020) Mean level of anxious symptomatology Oxford Stringency Index Anxiety symptoms SDP stringency Patterns of change in anxiety symptoms across the 20−month study period Figure 1. The mean-level profile of anxiety and the strictness of social distancing protocols (SDPs) over the 20-month observation period. Anxiety change patterns were modelled upon all modifications in national SDPs over the pandemic period. The dashed lines represent the 95% confidence intervals. Each month is coded in units of 30 days ensuing the starting point March 31, 2020, coded as 0. Patterns of change in anxiety symptoms across the 20−month study period Oxford Stringency Index Months (30 day units from March 31, 2020) Figure 1. Discussionh It is reasonable that people with a pre-existing psychiatric diagnosis also are more vulnerable to Scientific Reports | (2022) 12:17846 | https://doi.org/10.1038/s41598-022-22686-z www.nature.com/scientificreports/ Individual change profiles of anxiety symptoms for a random set of 200 participants 0 4 8 12 16 0 (March 2020) 3 (June 2020) 6 (Sept 2020) 9 (Dec 2020) 12 (March 2021) 15 (June 2021) 18 (Sept 2021) 21 (Dec 20 Months (30 day units from March 31, 2020) Mean level of anxious symptomatology Individual change profiles of anxiety symptoms for a random set of 200 participants Figure 2. Individual change profiles in anxiety across modifications in social distancing protocols (SDPs). Through a 20-month period from the introduction of SDPs to their discontinuation. 1 Mean level of anxious symptomatology Figure 2. Individual change profiles in anxiety across modifications in social distancing protocols (SDPs). Through a 20-month period from the introduction of SDPs to their discontinuation. eightened anxiety later. Notably, use of unverified platforms and psychiatric diagnosis did not predict end leve or depression in the same ­sample19.f Also females, unemployed, and those living alone exhibited a heightened overall anxiety level, but differ- ences were less marked. Higher educational level was related to lower initial level of anxiety but predicted more increase of anxiety at reopening (T7). Those with a university degree and students may have been exposed to a larger increase of perceived dangers (e.g., social threats, physical closeness) as a result of the discontinuation of SDPs. Worry about job and economy at the introduction of SDPs (T1) had an impact on anxiety in the early phase of the pandemic but had no relationship to the end (T7) level of anxiety.l p p p y Daily infection rate was related to anxiety early in the pandemic, probably reflecting that there existed more uncertainty about the dangerous consequences of the virus at this stage. In addition, infection rate was related to anxiety change from T6 to T7. This may reflect the steep increase of infected cases after society had been re-opened. p Some important variables were not included the present study. For instance, sleep quality and physical activ- ity have both been found to have decreased during COVID-19 related home ­confinement20, and both variables have been found to be associated with mental wellbeing during ­confinement21, Also during confinement, lower physical activity have been found to be related to poorer ­sleep22,23 and more ­anxiety23. www.nature.com/scientificreports/ www.nature.com/scientificreports/ 3 4 5 6 7 8 0 (March 2020) 3 (June 2020) 6 (Sept 2020) 9 (Dec 2020) 12 (March 2021) 15 (June 2021) 18 (Sept 2021) 21 (Dec 2021) Months (30 day units from March 31, 2020) Mean level of anxious symptomatology Age 18−30 years 31−44 years 45−64 years 65−87 years Change in anxiety symptoms as predicted by age 3 4 5 6 7 8 0 (March 2020) 3 (June 2020) 6 (Sept 2020) 9 (Dec 2020) 12 (March 2021) 15 (June 2021) 18 (Sept 2021) 21 (Dec 2021) Months (30 day units from March 31, 2020) Mean level of anxious symptomatology PsychiatricDiagnosi No Yes Change in anxiety symptoms as predicted by preexisting psychiatric diagnosis Figure 3. Anxiety across the 20-month observation period as predicted by age and preexisting psychiatric diagnosis. Controlled for the influence of all other variables in the model. Figure 3. Anxiety across the 20-month observation period as predicted by age and preexisting psychiatric diagnosis. Controlled for the influence of all other variables in the model. 3 4 5 6 7 8 0 (March 2020) 3 (June 2020) 6 (Sept 2020) 9 (Dec 2020) 12 (March 2021) 15 (June 2021) 18 (Sept 2021) 21 (Dec 2021) Months (30 day units from March 31, 2020) Mean level of anxious symptomatology Employed No Yes Change in anxiety symptoms as predicted by employment status 3 4 5 6 7 8 0 (March 2020) 3 (June 2020) 6 (Sept 2020) 9 (Dec 2020) 12 (March 2021) 15 (June 2021) 18 (Sept 2021) 21 (Dec 2021) Months (30 day units from March 31, 2020) Mean level of anxious symptomatology InfoPlatform Source−verified platforms Unmonitored platforms Change in anxiety symptoms as predicted by information obtainment preferences Figure 4. Anxiety across the 20-month observation period as predicted by employment status and information obtainment. Controlled for the influence of all other variables in the model. 3 4 5 6 7 8 0 (March 2020) 3 (June 2020) 6 (Sept 2020) 9 (Dec 2020) 12 (March 2021) 15 (June 2021) 18 (Sept 2021) 21 (Dec 2021) Months (30 day units from March 31, 2020) Mean level of anxious symptomatology Change in anxiety symptoms as predicted by employment status Figure 4. Anxiety across the 20-month observation period as predicted by employment status and information obtainment. Controlled for the influence of all other variables in the model. Discussionh Thus, physical activity Scientific Reports | (2022) 12:17846 | https://doi.org/10.1038/s41598-022-22686-z www.nature.com/scientificreports/ www.nature.com/scientificreports/ Anxiety across the 20-month observation period as predicted by biological sex and education leve Controlled for the influence of all other variables in the model. 3 4 5 6 7 8 0 (March 2020) 3 (June 2020) 6 (Sept 2020) 9 (Dec 2020) 12 (March 2021) 15 (June 2021) 18 (Sept 2021) 21 (Dec 2021) Months (30 day units from March 31, 2020) Mean level of anxious symptomatology LiveAlone No Yes Change in anxiety symptoms as predicted by living status 3 4 5 6 7 8 0 (March 2020) 3 (June 2020) 6 (Sept 2020) 9 (Dec 2020) 12 (March 2021) 15 (June 2021) 18 (Sept 2021) 21 (Dec 2021) Months (30 day units from March 31, 2020) Mean level of anxious symptomatology WorryJobAndEconomy 0 2 4 6 Change in anxiety symptoms as predicted by worry about job and economy Figure 6. Anxiety across the 20-month observation period as predicted by living status and worry about job and economy. Controlled for the influence of all other variables in the model. 3 4 5 6 7 8 0 (March 2020) 3 (June 2020) 6 (Sept 2020) 9 (Dec 2020) 12 (March 2021) 15 (June 2021) 18 (Sept 2021) 21 (Dec 2021) Months (30 day units from March 31, 2020) Mean level of anxious symptomatology Change in anxiety symptoms as predicted by living status Figure 6. Anxiety across the 20-month observation period as predicted by living status and worry about job and economy. Controlled for the influence of all other variables in the model. In conclusion, the mean anxiety level fluctuated throughout the observation period and these fluctuations were positively related to the stringency of the modified SDPs. A sub-group of 9% who developed a chronic anxi- ety state during the first three months of the pandemic was identified. This sizable subgroup maintained their heightened anxiety level throughout the pandemic and is vulnerable to prolonged anxiety beyond the pandemic period. Therefore, efforts to mitigate detrimental anxiety symptomatology should focus on the early phase of pandemics and future research should identify the particular circumstances and psychological processes leading to and maintaining this chronic anxiety state. Among variables shown in other studies to predict initial anxiety response to the COVID-19 pandemic and associated SDPs, younger age, pre-existing psychiatric diagnosis, and use of unverified information platforms proved to markedly predict higher anxiety in the long run. www.nature.com/scientificreports/ and sleep quality could both contribute to the prediction of anxiety profiles, both independently and in overlap with the studied predictors (e.g., sleep and worry about job and economy).i A major strength of this study was that anxiety was measured at every modification of SDPs until the end of the pandemic containment policies and the proclaimed end of the pandemic. The pandemic was said to be under control and people could return to a normal everyday life. No knowledge of the new omicron variant and the associated infection wave was available during the last measurement window. Thus, the findings represent information about anxiety reactions from the start to what was at the time the perceived end of a pandemic. Other strengths include the large and representative sample, the simultaneous unveiling of population-level and individual change profiles, the state-of-the-art approach to missing data, and the sensitivity analyses on an attrition-controlled sample. p Some limitations should be noted. Although the participants were randomly obtained from a larger sample and stratified to represent population demographics, the initial recruitment through an online procedure may favor particular sub-groups (e.g., younger people) and involve self-selection biases. Efforts were taken to reduce such biases through additional recruitment of participants across a variety of platforms more accessible to the elderly population. The use of self-reports precluded diagnostic assessment of the participants. Potential predic- tors such as sleep and physical activity were not included. Scientific Reports | (2022) 12:17846 | https://doi.org/10.1038/s41598-022-22686-z www.nature.com/scientificreports/ 3 4 5 6 7 8 0 (March 2020) 3 (June 2020) 6 (Sept 2020) 9 (Dec 2020) 12 (March 2021) 15 (June 2021) 18 (Sept 2021) 21 (Dec 2021) Months (30 day units from March 31, 2020) Mean level of anxious symptomatology Sex Female Male Change in anxiety symptoms as predicted by biological sex 3 4 5 6 7 8 0 (March 2020) 3 (June 2020) 6 (Sept 2020) 9 (Dec 2020) 12 (March 2021) 15 (June 2021) 18 (Sept 2021) 21 (Dec 2021) Months (30 day units from March 31, 2020) Mean level of anxious symptomatology Education Compulsory School Student University Degree Upper Secondary High School Change in anxiety symptoms as predicted by education level Figure 5. Anxiety across the 20-month observation period as predicted by biological sex and education level. Controlled for the influence of all other variables in the model. Figure 5. www.nature.com/scientificreports/ Measures should be taken to stimulate people to use verified information platforms about the pandemic. www.nature.com/scientificreports/ T6 (July 4 to August 1, 2021). Lenient SDPs: 48.79, consisting of minor distancing protocols, implemented from June 18. The infection rate was 164 (SD = 69). h T7 (October 24 to November 12, 2021). All SDPs were discontinued from September 24. A vaccine rate of 77% had been reached and the government declared that the pandemic was under control and that people could resume normal life. The infection rate was 933 (SD = 508). h T7 (October 24 to November 12, 2021). All SDPs were discontinued from September 24. A vaccine rate of 77% had been reached and the government declared that the pandemic was under control and that people could resume normal life. The infection rate was 933 (SD = 508). Measurement. Strictness of the national SDPs was measured by the Oxford COVID-19 Stringency ­Index26, which is based on nine metrics, yielding a final strictness score ranging from 0 (no protocols present) to 100 (strictest response possible). The nine metrics include: 1) workplace closures; 2) school closures; 3) cancella- tion of public events; 4) closures of public transport; 5) stay-at-home requirements; 6) restrictions on public gatherings; 7) public information campaigns; 8) restrictions on internal movements; and 9) international travel controls.h The participants reported their age, biological sex, education level, presence of preexisting psychiatric diagno- sis, preferred platform for obtaining information about the pandemic and its mitigation protocols, employment status, worry about job and economy, and living status. The age of the participants was coded into four categories (i.e., 0: 18–30 years; 1: 31–44 years; 2: 45–64 years; and 3: 65 years and above). Females were coded as 0 and males as 1. Education level consisted of four categories (i.e., 0: Compulsory School; 1: Upper Secondary High School; 2: Student; 3: Any University Degree). The presence of preexisting psychiatric diagnosis was coded as 1 and its absence as 0. Use of source-verified platforms encompassing source-checked and recognized national, regional, and local newspapers, television, and radio channels was coded as 0: Source-verified information platform preference; while use of unmonitored information obtainment sources consisting of social media platforms (e.g., Instagram, Snapchat, TikTok), online forums and blogs, and friends, family and peers were coded as 1: Unmonitored information platform preference; Worry about job and economy was measured on a scale from 0: Never worry about job and economy to 12: worries both about job and economy almost every day. www.nature.com/scientificreports/ accordance with the guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology statement (STROBE)24. Digital informed consent was obtained from all participants before completing the questionnaire. accordance with the guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology statement (STROBE)24. Digital informed consent was obtained from all participants before completing the questionnaire. Study design. The study period lasted 20 months from the onset of the pandemic and the introduction of national SDPs in Norway to their complete discontinuation. The design criteria included a) measuring anxiety following each modification of SDPs, b) initiating measurements in a two-week interval between two to four weeks following the modification, and c) stopping data collection instantaneously if novel information was pro- vided concerning forthcoming modifications of SDPs to control for expectations effects. Hence, the timing of the measurements was based on the timing of the implementation of SDPs. Population, recruitment, and procedure. The targeted population for the present study was adults (age >  = 18 years) living in Norway across the period of assessment. The majority of the sample (70%) was obtained using a Facebook Business algorithm, which proportionally targeted each geographic region accord- ing to its relative size (see flowchart in online Supplementary Fig. S2). The 15% adults not present on Facebook were recruited through a systematic dissemination of the survey via national, regional, and local information platforms (i.e., television, radio, and newspapers). This procedure is explained in detail ­elsewhere25. A total of 10,061 adults enrolled in the study at T1. The same participants were recontacted at each assessment. The num- ber participants responding at each assessment was 4,967 at T2, 5,283 at T3, 4,607 at T4, 4,228 at T5, 3,231 at T6, and 3,330 at T7. Stratification of sample. Characteristics not fully representative of the Norwegian adult population were post-stratified to be proportional to their known rate in the general adult population, matching each parameter in the sample to the population parameter to provide a representative sample of the Norwegian adult population. The final stratified and representative sample used in this study consisted of 4,361 of the 10,061 adults, selecting 4361 at T1, 2,151 at T2, 2239 at T3, 1963 at T4, 1811 at T5, 1,405 at T6, and 1426 at T7. Assessment intervals, modifications in SDPs and infection pressure. www.nature.com/scientificreports/ A comprehensive list of nationally implemented SDPs at each assessment interval (i.e., T1–T6) is presented in Supplementary Tables S1– S6. At T7, national SDPs were discontinued. The intervals, the strictness of the SDPs measured by the Oxford COVID-19 Stringency ­Index26, the date of their implementation, and the mean daily infection rate in the inter- vals, retrieved from the Norwegian Public Health database of infectious disease, were as follows:h Assessment intervals, modifications in SDPs and infection pressure. A comprehensive list of nationally implemented SDPs at each assessment interval (i.e., T1–T6) is presented in Supplementary Tables S1– S6. At T7, national SDPs were discontinued. The intervals, the strictness of the SDPs measured by the Oxford COVID-19 Stringency ­Index26, the date of their implementation, and the mean daily infection rate in the inter- vals, retrieved from the Norwegian Public Health database of infectious disease, were as follows:h g T1 (March 31 to April 7, 2020). Strict SDPs: 79.63, implemented from March 13. The infection rate was 191 (SD = 55).h g T1 (March 31 to April 7, 2020). Strict SDPs: 79.63, implemented from March 13. The infection rate was 191 (SD = 55).h T2 (June to July 13, 2020). Lenient SDPs: 40.74, implemented from June 15. The infection rate was 20 (SD = 8). T3 (November 19 to December 2, 2020). Strict SDPs: 56.02, implemented from October 26. The infection rate was 517 (SD = 11). T2 (June to July 13, 2020). Lenient SDPs: 40.74, implemented from June 15. The infection rate was 20 (SD = 8). T3 (November 19 to December 2, 2020). Strict SDPs: 56.02, implemented from October 26. The infection rate was 517 (SD = 11). ( ) T4 (January 23 to February 2, 2021). Increased strictness of SDPs: 70.76, including stronger restrictions on social contact than in T1 and T3, implemented from January 4. The infection rate was 249 (SD = 67).h T4 (January 23 to February 2, 2021). Increased strictness of SDPs: 70.76, including stronger restrictions on social contact than in T1 and T3, implemented from January 4. The infection rate was 249 (SD = 67).h yh T5 (May 8 to May 25, 2021). Decreased strictness of SDPs: 63.61, implemented from April 16. The infection ate was 373 (SD = 76). T6 (July 4 to August 1, 2021). Lenient SDPs: 48.79, consisting of minor distancing protocols, implemented from June 18. The infection rate was 164 (SD = 69). Methodsh The study was ethically approved by The Regional Committee for Medical and Health Research Ethics South East Norway (reference: 125,510) and the Norwegian Centre for Research Data (reference: 802,810). The study was pre-registered prior to collection of data at Clinicaltrials.gov (Identifier: NCT04442204) and conducted in https://doi.org/10.1038/s41598-022-22686-z Scientific Reports | (2022) 12:17846 | www.nature.com/scientificreports/ www.nature.com/scientificreports/ Living status was coded 0: Not living alone and 1: Living alone. Daily COVID-19 incidence rates were retrieved from the Norwegian Public Health database of infectious disease and matched with the response date of each participant. https://doi.org/10.1038/s41598-022-22686-z Scientific Reports | (2022) 12:17846 | www.nature.com/scientificreports/ Figure 7. The unconditional latent change score (LCS) model. Error variances (σ2) are constrained to be equal. The covariances between ηt1 and the latent change scores δηt2−t7 are omitted from the figure to aid visualization. Figure 7. The unconditional latent change score (LCS) model. Error variances (σ2) are constrained to be equ The covariances between ηt1 and the latent change scores δηt2−t7 are omitted from the figure to aid visualizatio The Generalized Anxiety Disorder-7 (GAD-7)27 consists of seven items covering the DSM-IV symptom cri- teria for GAD. Subjects are asked for the presence of symptoms during the past two weeks. The items are scored on a four-point scale ranging from 0 (not at all) to 3 (almost every day). The total score ranges from 0 to 21. The GAD-7 has revealed construct validity and ­reliability27,28 and has been formally translated to ­Norwegian28. As cut-offs were >  = 8 used for clinical ­level15 and >  = 4 for clinically important ­change29. The internal consistency was excellent in this sample, with Cronbach’s α ranging from 0.88 to 0.91 across assessments. Statistical analyses. The statistical analyses of this study were performed using ­R30. A Latent Change Score (LCS)14 model was used to model the development of anxious symptomatology across the 20-month study period. It was specified using the ‘lavaan’ ­package31in R. As the LCS framework concerns within-person and time-dependent change, it is a powerful technique for modeling individual fluctuations related to modifications of SDPs across the pandemic period.i p p First, an unconditional LCS was fitted to the data, modeling the initial level (i.e., denoted as ηt1) of anxious symptomatology at the first assessment interval (T1), and the latent change scores between all adjacent intervals (i.e., T1 to T2; T2 to T3; T3 to T4; T4 to T5; T5 to T6; and T6 to T7), denoted as δηt2, δηt3, δηt4, δηt5, δηt6; and δηt7, respectively (Fig. 7). T1 was coded as month 0 of the study. The residual variances (i.e., σ 2 ε ) were held equal across assessments. www.nature.com/scientificreports/ Appropriate model fit was determined using common evaluation guidelines as indicated by RMSEA ≤ 0.05, TLI ≥ 0.95, CFI ≥ 0.95, and SRMR ≤ 0.0532. Next, the predictors and infection rate were added to yield a conditional LCS model, revealing the extent to which these variables were associated with profiles of change in anxious symptomatology across the 20-month pandemic period. Full Information Maximum Likeli- hood (FIML) was utilized to estimate models on the full data set, allowing for the inclusion of individuals with partially missing ­data33,34. Data availabilityh The data that support the findings of this study are available from the Norwegian Centre for Research Data but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permis- sion of the Regional Committee for Medical and Health Research Ethics South East Norway and the Norwegian Centre for Research Data. Received: 23 June 2022; Accepted: 18 October 2022 Received: 23 June 2022; Accepted: 18 October 2022 References References 1. Brooks, S. K. et al. The psychological impact of quarantine and how to reduce it: Rapid review of the evidence. Lancet 395, 912–920 (2020). y y 3. Santomauro, D. F. et al. Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the covid-19 pandemic. Lancet 398, 1700–1712 (2021). y y ( ) 3. Santomauro, D. F. et al. Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the covid-19 pandemic. Lancet 398, 1700–1712 (2021). e e e ces 1. Brooks, S. K. et al. The psychological impact of quarantine and how to reduce it: Rapid review of the evidence. Lancet 395, 912–920 (2020). 2 M t G G it L D ij d S S l i k E & E lh d I M F f th i (COVID 19) P di t i www.nature.com/scientificreports/ Lavaan: An r package for structural equation modeling and more. 31. Rosseel, Y. Lavaan: An r package for structural equation modeling and more. Version 0.5–12 (beta). J. Stat. Softw. 48, 1–36 (2012). 32. Hu, L. T. & Bentler, P. M. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alterna- tives. Struct. Equ. Modeling 6, 1–55 (1999). 31. Rosseel, Y. Lavaan: An r package for structural equation modeling and more. Version 0.5–12 (beta). J. Stat. Softw. 48, 1–36 (2012). 32. Hu, L. T. & Bentler, P. M. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alterna- tives. Struct. Equ. Modeling 6, 1–55 (1999). g y y 4. Schafer, J. L. & Graham, J. W. Missing data: Our view of the state of the art. Psychol. Methods 7, 147 (2002). www.nature.com/scientificreports/ www.nature.com/scientificreports/ 4. Robinson, E., Sutin, A. R., Daly, M. & Jones, A. A systematic review and meta-analysis of longitudinal cohort studies comparing mental health before versus during the COVID-19 pandemic in 2020. J. Affect. Disord. 296, 567–576 (2022).h g p ff 5. Prati, G. & Mancini, M. The psychological impact of COVID-19 pandemic lockdowns: A review and meta-analysis of longitudina studies and natural experiments. Psychol. Med. 51, 201–211 (2021).l p y 6. DiGiovanni, C., Conley, J., Chiu, D. & Zaborski, J. Factors influencing compliance with quarantine in Toronto during the 2003 SARS outbreak. Biosecur. Bioterror. 2, 265–272 (2004). 7. Pedersen, M. T. et al. Time trends in mental health indicators during the initial 16 months of the COVID-19 pandemic in Denmark BMC Psychiatry 22, 25 (2022). 8. MacDonald, J. J. et al. Depressive symptoms and anxiety during the COVID-19 pandemic: Large, longitudinal, cross-sectiona survey. JMIR Ment. Health 9, e33585 (2022). y ( ) 9. Oka, T. et al. Multiple time measurements of multidimensional psychiatric states from immediately before the COVID-19 p l A l i di l li f h J l i T l P hi 11 573 (2021) y 9. Oka, T. et al. Multiple time measurements of multidimensional psychiatric states from immediately before the COVID-19 pandemic to one year later: A longitudinal online survey of the Japanese population. Transl. Psychiatry 11, 573 (2021). y . Oka, T. et al. Multiple time measurements of multidimensional ps p p y y p to one year later: A longitudinal online survey of the Japanese population. Transl. Psychiatry 11, 573 (2021). y g y y y 10. Hajek, A. et al. Prevalence and determinants of probable depression and anxiety during the COVID-1 tries: Longitudinal evidence from the European COvid Survey (ECOS). J. Affect. Disord. 299, 517–524 0. Hajek, A. et al. Prevalence and determinants of probable depression and anxiety during the COVID-19 pandemic in seven coun tries: Longitudinal evidence from the European COvid Survey (ECOS). J. Affect. Disord. 299, 517–524 (2022). j , p p y g p tries: Longitudinal evidence from the European COvid Survey (ECOS). J. Affect. Disord. 299, 517–524 (2022). 1. Fancourt, D., Steptoe, A. & Bu, F. Trajectories of anxiety and depressive symptoms during enforced isolation due to COVID-19 in England: A longitudinal observational study. Lancet Psychiatry 8, 141–149 (2021). 2. Batterham, P. I. et al. https://doi.org/10.1038/s41598-022-22686-z Scientific Reports | (2022) 12:17846 | Author contributions All authors contributed to the study conception and design. A.H., S.U.J. and O.V.E. were involved in data acquisi- tion. O.V.E. and D.B. analysed the data. All authors contributed to data interpretation. A.H. was responsible for the first draft of the manuscript. All authors contributed to critical revision of the manuscript. All authors had access to the data. O.V.E. and A.H. verified the data, and all authors accepted responsibility for the decision to submit for publication. www.nature.com/scientificreports/ Trajectories of depression and anxiety symptoms during the COVID-19 pandemic in a representative Aus- tralian adult cohort. MJA 214, 462–468 (2021). ( ) 13. Bendau, A. et al. Associations between COVID-19 related media consumption and symptoms of anxiety, depression and COV 19 related fear in the general population in Germany. Eur. Arch. Psychiatry Clin. Neurosci. 271, 283–291 (2021).f 14. McArdle, J. J. A latent difference score approach to longitudinal dynamic structural analysis. In Structural equation modeling: Present and future. A festschrift in honor of Karl Jöreskog (eds Cudeck, R., Jöreskog, K. G., Sörbom, D. & Du Toit, S.) 342–380 (Lincolnwood, IL, Scientific Software International, 2001). (it ) 15. Norwegian Institute of Public Health, Mental illness among adults in Norway. In: Public Health Reports – Health Status in Norway. 2016. (accessed Apr 24, 2020). https://​www.​fhi.​no/​en/​op/​hin/​mental-​health/​psyki​sk-​helse-​hos-​voksne/ h y 6. Chen, F., Bollen, K. A., Paxton, P., Curran, P. J. & Kirby, J. B. Improper solutions in structural equation models: Causes, conse- quences, and strategies. Sociol. Methods Res. 29, 468–508 (2001). q g 7. Hayes, A. M. & Andrews, L. A. A complex systems approach to the study of change in psychotherapy. BMC Med. 18, 1–13 (2020) 17. Hayes, A. M. & Andrews, L. A. A complex systems approach to the study of change in psychotherapy. BMC Med. 18, 1–13 (2020). 18. Bu, F., Steptoe, A. & Fancourt, D. Loneliness during strict lockdown: trajectories and predictors during the COVID-19 pandemic in 38,217 adults in UK. Soc. Sci. Med. 265, 113521 (2020).fh 18. Bu, F., Steptoe, A. & Fancourt, D. Loneliness during strict lockdown: trajectories and predictors during the COVID-19 pandemic in 38,217 adults in UK. Soc. Sci. Med. 265, 113521 (2020).fh 19. Ebrahimi, O. V., Bauer, D. J., Hoffart, A. & Johnson, S. U. The evolution of depressive symptomatology across three waves of the COVID-19 pandemic: A 17-month representative longitudinal study of the adult population. J. Psychopathol. Clin. Sci. (in press). 20. Trabeli, K. et al. Globally altered sleep patterns and physical activity levels by confinement in 5056 individuals: ECLB COVID-19 international online survey. Biol. Sport 38, 495–506 (2021). COVID-19 pandemic: A 17-month representative longitudinal study of the adult population. J. Psychopathol. Clin. Sci. (in press). 20. Trabeli, K. et al. Globally altered sleep patterns and physical activity levels by confinement in 5056 individuals: ECLB COVID-19 international online survey. Biol. Sport 38, 495–506 (2021). g y y 20. Trabeli, K. et al. Competing interests h p g The authors declare no competing interests. Additional information Supplementary Information The online version contains supplementary material available at https://​doi.​org/​ 10.​1038/​s41598-​022-​22686-z. Correspondence and requests for materials should be addressed to A.H. Reprints and permissions information is available at www.nature.com/reprints. Publisher’s note  Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. www.nature.com/scientificreports/ Globally altered sleep patterns and physical activity levels by confinement in 5056 ind international online survey. Biol. Sport 38, 495–506 (2021). y p 21. Trabelsi, K. et al. Sleep quality and physical activity as predictors of mental wellbeing variance in older adults during COVID-19 lockdown: ECLB COVID-19 international online survey. Int. J. Environ. Res. Public Health 18, 4329 (2021). 22. Dergaa, I. et al. COVID-19 lockdown: Impairments of objective measurements of selected physical activity, cardiorespiratory sleep parameters in trained fitness coaches. EXCLI J. 21, 1084–1098 (2022).f i 3. Akbari, H. A. et al. How physical activity behavior affected well-being, anxiety and sleep quality during COVID-19 restrictions in Iran. Eur. Rev. Med. Pharmacol. Sci. 25, 7847–7857 (2021).h i 23. Akbari, H. A. et al. How physical activity behavior affected w f Iran. Eur. Rev. Med. Pharmacol. Sci. 25, 7847–7857 (2021).h 24. von Elm, E. et al. The strengthening the reporting of observa 24. von Elm, E. et al. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. Ann. Intern. Med. 147, 573–577 (2007).f h reporting observational studies. Ann. Intern. Med. 147, 573–57 p g 25. Ebrahimi, O. V., Hoffart, A. & Johnson, S. U. Physical distancing and mental health during the covid-19 pandemic: Factors as ated with psychological symptoms and adherence to pandemic mitigation strategies. Clin. Psychol. Sci. 9, 489–506 (2021). ated with psychological symptoms and adherence to pandemic mitigation strategies. Clin. Psychol. Sci. 9, 489 506 (2021). 26. Hale, T. et al. Variation in government responses to COVID-19. https://​ourwo​rldin​data.​org/​covid-​strin​gency-​index (2020). 26. Hale, T. et al. Variation in government responses to COVID-19. https://​ourwo​rldin​data.​org/​covid-​strin​gency-​index (2020).h 27. Spitzer, R. L., Kroenke, K., Williams, J. B. W. & Löwe, B. A brief measure for assessing generalized anxiety disorder: The GA Arch. Intern. Med. 166, 1092–1097 (2006).f 8. Johnson, S. U., Ulvenes, P. G., Øktedalen, T. & Hoffart, A. Psychometric properties of the general anxiety disorder 7-item (GAD-7) scale in a heterogeneous psychiatric sample. Front. Psychol. 10, 1713 (2019).f g y y 9. Toussaint, T. et al. Sensitivity to change and minimal clinically important difference of the 7-item generalized anxiety disorder questionnaire (GAD-7). J. Affect. Disord. 265, 395–401 (2020). q ( ) ff ( ) 30. R Core Team. R, A language and environment for statistical computing (2021). f 30. R Core Team. R, A language and environment for statistical computing (2021). Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. © The Author(s) 2022 Additional informationh Supplementary Information The online version contains supplementary material available at https://​doi.​org/​ 10.​1038/​s41598-​022-​22686-z. Correspondence and requests for materials should be addressed to A.H. Correspondence and requests for materials should be addressed to A.H. Reprints and permissions information is available at www.nature.com/reprints. Reprints and permissions information is available at www.nature.com/reprints. Publisher’s note  Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Scientific Reports | (2022) 12:17846 | https://doi.org/10.1038/s41598-022-22686-z www.nature.com/scientificreports/ www.nature.com/scientificreports/ Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. © The Author(s) 2022 https://doi.org/10.1038/s41598-022-22686-z Scientific Reports | (2022) 12:17846 |
W2287923862.txt
https://journals.iucr.org/e/issues/2009/11/00/fb2162/fb2162.pdf
en
1-Azidoethoxy-2,3,4,6-tetra-<i>O</i>-acetyl-β-<scp>D</scp>-glucoside
Acta crystallographica. Section E
2,009
cc-by
2,696
organic compounds Acta Crystallographica Section E Orthorhombic, P21 21 21 a = 6.9730 (14) Å b = 14.747 (3) Å c = 19.916 (4) Å V = 2048.0 (7) Å3 Structure Reports Online ISSN 1600-5368 Z=4 Mo K radiation  = 0.11 mm1 T = 293 K 0.30  0.20  0.10 mm Data collection 1-Azidoethoxy-2,3,4,6-tetra-O-acetyl-bD-glucoside Xiao-Hui Yang, Yong-Hong Zhou,* Hong-Jun Liu and Xiao-Xin Guo Enraf–Nonius CAD-4 diffractometer Absorption correction: scan (North et al., 1968) Tmin = 0.967, Tmax = 0.989 3276 measured reflections 2152 independent reflections 1428 reflections with I > 2(I) Rint = 0.036 3 standard reflections every 200 reflections intensity decay: 1% Refinement Institute of Chemical Industry of Forest Products, Chinese Academy of Forestry, Nanjing, 210042, People’s Republic of China Correspondence e-mail: yhzhou1966@yahoo.com.cn R[F 2 > 2(F 2)] = 0.055 wR(F 2) = 0.156 S = 1.06 2152 reflections 266 parameters H-atom parameters constrained max = 0.24 e Å3 min = 0.20 e Å3 Received 16 July 2009; accepted 30 September 2009 Key indicators: single-crystal X-ray study; T = 293 K; mean (C–C) = 0.007 Å; R factor = 0.055; wR factor = 0.156; data-to-parameter ratio = 8.1. In the title compound, C16H23N3O10, the galactopyranoside ring adopts a chair conformation. All the non-H substituents are situated in equatorial positions. There are short intramolecular C—H  O contacts and an intermolecular C—H  O interaction in the structure. Related literature For renewable compounds generated by living organisms that can be turned into useful macromolecular materials, see: Gandini (2008). For industrial applications of lignin, see: Gandini & Belgacem (2002). For attempts to obtain new polyurethanes between lignin and saccharide, see: Hatakeyama & Hatakeyama (2005). Table 1 Hydrogen-bond geometry (Å,  ). D—H  A D—H H  A D  A D—H  A C14—H14A  O4 C15—H15A  O2 C16—H16A  O7 C16—H16A  O9 C9—H9B  O1i 0.98 0.98 0.98 0.98 0.96 2.21 2.32 2.27 2.44 2.48 2.666 2.723 2.702 2.824 3.402 107 104 106 103 160 (6) (6) (6) (5) (6) Symmetry code: (i) x  12; y þ 32; z. Data collection: SMART (Bruker, 2000); cell refinement: SAINT (Bruker, 2000); data reduction: SAINT; program(s) used to solve structure: SHELXS97 (Sheldrick, 2008); program(s) used to refine structure: SHELXL97 (Sheldrick, 2008); molecular graphics: SHELXTL (Sheldrick, 2008); software used to prepare material for publication: SHELXTL. This work was supported by the President of the Chinese Academy of Forestry Foundation (CAFYBB2008009). Supplementary data and figures for this paper are available from the IUCr electronic archives (Reference: FB2162). References Experimental Crystal data C16H23N3O10 Acta Cryst. (2009). E65, o2651 Mr = 417.37 Bruker (2000). SAINT and SMART. Bruker AXS Inc., Madison, Wisconsin, USA. Gandini, A. (2008). Macromolecules, 41, 9491–9504. Gandini, A. & Belgacem, M. N. (2002). J. Polym. Environ. 10, 105–114. Hatakeyama, H. & Hatakeyama, T. (2005). Macromol. Symp. 224, 219–226. North, A. C. T., Phillips, D. C. & Mathews, F. S. (1968). Acta Cryst. A24, 351– 359. Sheldrick, G. M. (2008). Acta Cryst. A64, 112–122. doi:10.1107/S1600536809039737 Yang et al. o2651 supporting information supporting information Acta Cryst. (2009). E65, o2651 [https://doi.org/10.1107/S1600536809039737] 1-Azidoethoxy-2,3,4,6-tetra-O-acetyl-β-D-glucoside Xiao-Hui Yang, Yong-Hong Zhou, Hong-Jun Liu and Xiao-Xin Guo S1. Comment The incessant biological activity in living organisms generates a multitude of compounds, including a variety of monomers and polymers such as saccharide, cellulose, hemicellulose, lignin and so on. More and more scientists are exclusively concerned with those renewable compounds that can be turned into useful macromolecular materials (Gandini, 2008). However, most of lignin as a by-product from the paper industry is being discharged into the environment. This causes serious environmental pollution. Also for this reason industrial applications of lignin have attracted a great deal of attention (Gandini & Belgacem, 2002). In attempt to obtain new polyurethanes between lignin and saccharide (Hatakeyama & Hatakeyama, 2005) and to optimize their properties, the title structure, a new galactopyranoside, 2-azidoethoxy 2,3,4,6-tetra-O-acetyl-β-D-glucopyranoside, has been synthesized and its structure determined. The galactopyranoside ring adopts a chair conformation. There are present four intramolecular C-H···O interactionss (Tab. 1). Each of them forms four five-membered rings. In the crystal structure, the molecules are linked into chains along the a axis by C—H···O interactions (Fig. 2 and Tab. 1). S2. Experimental β-D-glucose pentaacetate (5.0 g, 12.8 mmol) was dissolved in 25 ml of the anhydrous CH2Cl2. 2-azidoethanol (1.9 g, 22.3 mmol) was added to this solution by a syringe. The resulting solution was stirred under argon and cooled to 273 K. BF3.Et2O (2.1 ml, 16.7 mmol) was then added dropwise at 273 K. The mixture was stirred for 1 h at 273 K and then overnight at room temperature. The mixture was diluted with 50 ml CH2Cl2 and washed with cold water and with saturated aqueous NaHCO3 at room temperature, dried over anhydrous sodium sulfate, and concentrated in vacuo to obtain a fawn crude residue that was purified by column chromatography (hexane/EtOAc 2:1) and recrystallization from the solution of hexane/EtOAc (1:1) in order to obtain a pure solid of the title compound. Colourless single crystals suitable for X-ray crystallographic analysis were grown by slow evaporation from an ethyl acetate solution of the title compound. S3. Refinement All the H atoms were located in a difference electron density map. Nevertheless, all the hydrogens were placed into the idealized positions and constrained by riding hydrogen approximation. Cmethyl—Hmethyl=0.96; Cmethylene—Hmethylene=0.97; Cmethine—Hmethine=0.98 Å. UisoHmethyl=1.5UeqCmethyl, UisoHmethylene=1.2UeqCmethylene, UisoHmethine=1.2UeqCmethine. All the methyl groups were allowed to rotate freely about their respective C—C bonds during the refinement. Only 1/8 of the reciprocal space has been measured, therefore Friedel pairs for merging were not available. Acta Cryst. (2009). E65, o2651 sup-1 supporting information Figure 1 The title molecule with the atom-labelling scheme. The displacement ellipsoids drawn at the 30% probability level. Acta Cryst. (2009). E65, o2651 sup-2 supporting information Figure 2 The packing of the title molecules, viewed along the c axis. 1-Azidoethoxy-2,3,4,6-tetra-O-acetyl-β-D-glucoside Crystal data C16H23N3O10 Mr = 417.37 Orthorhombic, P212121 Hall symbol: P 2ac 2ab a = 6.9730 (14) Å b = 14.747 (3) Å c = 19.916 (4) Å V = 2048.0 (7) Å3 Z=4 Acta Cryst. (2009). E65, o2651 F(000) = 880 Dx = 1.354 Mg m−3 Mo Kα radiation, λ = 0.71073 Å Cell parameters from 25 reflections θ = 9–12° µ = 0.11 mm−1 T = 293 K Block, colourless 0.30 × 0.20 × 0.10 mm sup-3 supporting information Data collection Enraf–Nonius CAD-4 diffractometer Radiation source: fine-focus sealed tube Graphite monochromator ω/2θ scans Absorption correction: ψ scan (North et al., 1968) Tmin = 0.967, Tmax = 0.989 3276 measured reflections 2152 independent reflections 1428 reflections with I > 2σ(I) Rint = 0.036 θmax = 25.3°, θmin = 1.7° h = −8→8 k = 0→17 l = 0→23 3 standard reflections every 200 reflections intensity decay: 1% Refinement Refinement on F2 Least-squares matrix: full R[F2 > 2σ(F2)] = 0.055 wR(F2) = 0.156 S = 1.06 2152 reflections 266 parameters 0 restraints 88 constraints Primary atom site location: structure-invariant direct methods Secondary atom site location: difference Fourier map Hydrogen site location: difference Fourier map H-atom parameters constrained w = 1/[σ2(Fo2) + (0.0842P)2 + 0.0427P] where P = (Fo2 + 2Fc2)/3 (Δ/σ)max < 0.001 Δρmax = 0.24 e Å−3 Δρmin = −0.20 e Å−3 Special details Geometry. All esds (except the esd in the dihedral angle between two l.s. planes) are estimated using the full covariance matrix. The cell esds are taken into account individually in the estimation of esds in distances, angles and torsion angles; correlations between esds in cell parameters are only used when they are defined by crystal symmetry. An approximate (isotropic) treatment of cell esds is used for estimating esds involving l.s. planes. Refinement. Refinement of F2 against ALL reflections. The weighted R-factor wR and goodness of fit S are based on F2, conventional R-factors R are based on F, with F set to zero for negative F2. The threshold expression of F2 > 2sigma(F2) is used only for calculating R-factors(gt) etc. and is not relevant to the choice of reflections for refinement. R-factors based on F2 are statistically about twice as large as those based on F, and R- factors based on ALL data will be even larger. Fractional atomic coordinates and isotropic or equivalent isotropic displacement parameters (Å2) O1 N1 N2 N3 O2 C1 H1B H1C O3 C2 H2A H2B O4 C3 H3A x y z Uiso*/Ueq 0.7582 (5) 1.0447 (9) 1.0080 (9) 0.9676 (16) 0.3076 (8) 1.0868 (10) 1.1128 1.2014 0.2457 (5) 0.9245 (9) 0.8978 0.9631 0.4451 (8) 0.0437 (9) 0.0147 0.6069 (2) 0.6905 (4) 0.6436 (4) 0.6099 (5) 0.2527 (2) 0.6426 (5) 0.5794 0.6684 0.40003 (19) 0.6483 (5) 0.7115 0.6193 0.5373 (3) 0.2978 (4) 0.2344 0.05712 (18) 0.1458 (3) 0.1911 (4) 0.2393 (4) 0.0360 (2) 0.0830 (3) 0.0929 0.0630 0.05186 (15) 0.0333 (3) 0.0237 −0.0083 0.18472 (18) 0.1058 (3) 0.1099 0.0722 (10) 0.0961 (17) 0.0987 (18) 0.167 (3) 0.1001 (14) 0.103 (2) 0.123* 0.123* 0.0560 (8) 0.0917 (19) 0.110* 0.110* 0.0927 (13) 0.0820 (17) 0.123* Acta Cryst. (2009). E65, o2651 sup-4 supporting information H3B H3C O5 C4 O6 C5 H5A H5B H5C O7 C6 O8 C7 H7A H7B H7C O9 C8 O10 C9 H9A H9B H9C C10 C11 H11A H11B C12 H12A C13 H13A C14 H14A C15 H15A C16 H16A −0.0647 0.0724 0.6040 (5) 0.2113 (9) 0.2735 (5) 0.6697 (10) 0.6339 0.8048 0.6403 −0.0125 (5) 0.5624 (9) 0.2457 (7) 0.0537 (10) −0.0777 0.0760 0.1360 0.2845 (5) 0.0953 (7) 0.5898 (5) 0.0336 (9) −0.0210 0.0762 −0.0614 0.1978 (8) 0.4448 (8) 0.5502 0.4076 0.5050 (7) 0.6027 0.6755 (7) 0.7714 0.5181 (7) 0.4290 0.4101 (7) 0.4918 0.3439 (6) 0.2403 0.3290 0.3223 0.4482 (2) 0.3097 (3) 0.40451 (19) 0.4265 (4) 0.4465 0.4357 0.3633 0.4706 (3) 0.4791 (3) 0.6740 (3) 0.3357 (4) 0.3390 0.2789 0.3404 0.63294 (19) 0.4111 (3) 0.5863 (2) 0.7316 (3) 0.7666 0.7716 0.6909 0.6792 (3) 0.5767 (3) 0.6141 0.5362 0.5231 (3) 0.4791 0.5413 (3) 0.4970 0.4956 (3) 0.5415 0.4284 (3) 0.3761 0.4733 (3) 0.5161 0.0872 0.1493 0.11247 (15) 0.0612 (2) −0.09523 (15) 0.2258 (3) 0.2700 0.2195 0.2210 −0.1036 (2) 0.1751 (3) −0.23285 (18) −0.1658 (3) −0.1799 −0.1436 −0.2043 −0.12588 (15) −0.1188 (2) −0.03885 (16) −0.1504 (3) −0.1863 −0.1154 −0.1329 −0.1759 (3) −0.1452 (2) −0.1608 −0.1813 −0.0851 (2) −0.0987 0.0177 (2) 0.0028 0.0570 (2) 0.0740 0.0141 (2) 0.0039 −0.0504 (2) −0.0403 0.123* 0.123* 0.0626 (9) 0.0647 (13) 0.0554 (8) 0.0854 (18) 0.128* 0.128* 0.128* 0.0817 (11) 0.0636 (13) 0.0903 (13) 0.0838 (18) 0.126* 0.126* 0.126* 0.0557 (8) 0.0541 (11) 0.0603 (8) 0.0789 (17) 0.118* 0.118* 0.118* 0.0626 (13) 0.0636 (13) 0.076* 0.076* 0.0525 (11) 0.063* 0.0570 (12) 0.068* 0.0520 (11) 0.062* 0.0509 (11) 0.061* 0.0492 (11) 0.059* Atomic displacement parameters (Å2) O1 N1 N2 N3 O2 C1 O3 U11 U22 U33 U12 U13 U23 0.061 (2) 0.115 (4) 0.098 (4) 0.200 (9) 0.148 (4) 0.064 (4) 0.0622 (18) 0.093 (2) 0.086 (3) 0.085 (4) 0.142 (6) 0.0562 (19) 0.126 (5) 0.0532 (16) 0.063 (2) 0.087 (4) 0.114 (5) 0.158 (7) 0.097 (3) 0.117 (6) 0.0526 (18) −0.014 (2) −0.004 (4) −0.005 (3) 0.013 (7) 0.010 (3) −0.009 (4) 0.0000 (16) 0.0038 (19) −0.025 (4) −0.024 (4) −0.005 (8) 0.026 (3) 0.006 (4) 0.0079 (16) −0.021 (2) −0.003 (3) 0.023 (3) 0.058 (6) 0.005 (2) −0.040 (5) −0.0005 (15) Acta Cryst. (2009). E65, o2651 sup-5 supporting information C2 O4 C3 O5 C4 O6 C5 O7 C6 O8 C7 O9 C8 O10 C9 C10 C11 C12 C13 C14 C15 C16 0.071 (4) 0.136 (4) 0.088 (4) 0.073 (2) 0.093 (4) 0.065 (2) 0.109 (5) 0.062 (2) 0.077 (3) 0.107 (3) 0.106 (5) 0.062 (2) 0.053 (3) 0.0659 (19) 0.094 (4) 0.074 (3) 0.072 (3) 0.057 (3) 0.053 (3) 0.055 (3) 0.052 (3) 0.053 (2) 0.127 (5) 0.092 (3) 0.092 (4) 0.075 (2) 0.054 (3) 0.0550 (16) 0.097 (4) 0.098 (3) 0.064 (3) 0.118 (3) 0.090 (4) 0.0580 (16) 0.066 (3) 0.0599 (17) 0.072 (3) 0.059 (3) 0.069 (3) 0.053 (2) 0.065 (3) 0.063 (3) 0.055 (2) 0.051 (2) 0.077 (4) 0.050 (2) 0.066 (4) 0.0399 (17) 0.047 (3) 0.0466 (17) 0.050 (3) 0.085 (3) 0.049 (3) 0.046 (2) 0.055 (3) 0.0475 (17) 0.044 (3) 0.0551 (19) 0.071 (4) 0.054 (3) 0.051 (3) 0.048 (3) 0.054 (3) 0.039 (2) 0.046 (2) 0.043 (3) −0.024 (4) 0.034 (3) −0.022 (3) 0.0134 (19) −0.005 (3) 0.0097 (16) 0.000 (4) 0.011 (2) −0.002 (3) 0.020 (3) −0.018 (4) 0.0098 (16) 0.002 (3) 0.0019 (17) 0.018 (3) −0.004 (3) 0.002 (3) 0.006 (2) 0.003 (2) 0.008 (2) 0.011 (2) 0.012 (2) 0.013 (4) 0.001 (2) −0.001 (3) −0.0103 (18) −0.004 (3) −0.0055 (17) −0.011 (3) −0.016 (2) −0.011 (3) 0.003 (2) −0.007 (3) 0.0027 (16) 0.000 (2) −0.0010 (18) −0.011 (3) −0.012 (3) 0.014 (3) 0.002 (2) −0.006 (2) 0.000 (2) −0.005 (2) −0.004 (2) 0.001 (4) −0.016 (2) 0.003 (3) −0.0057 (15) 0.006 (2) −0.0104 (15) 0.006 (3) −0.014 (2) −0.008 (3) 0.012 (2) −0.013 (3) 0.0056 (15) −0.002 (2) 0.0001 (16) 0.004 (3) 0.003 (3) 0.001 (2) −0.007 (2) −0.009 (2) −0.002 (2) −0.006 (2) −0.010 (2) Geometric parameters (Å, º) O1—C13 O1—C2 N1—N2 N1—C1 N2—N3 O2—C4 C1—C2 C1—H1B C1—H1C O3—C4 O3—C15 C2—H2A C2—H2B O4—C6 C3—C4 C3—H3A C3—H3B C3—H3C O5—C6 O5—C14 O6—C8 O6—C16 C5—C6 Acta Cryst. (2009). E65, o2651 1.373 (5) 1.394 (7) 1.165 (7) 1.467 (7) 1.117 (9) 1.188 (6) 1.505 (9) 0.9700 0.9700 1.366 (5) 1.433 (5) 0.9700 0.9700 1.201 (6) 1.478 (8) 0.9600 0.9600 0.9600 1.360 (6) 1.439 (5) 1.332 (6) 1.437 (5) 1.476 (8) O7—C8 O8—C10 C7—C8 C7—H7A C7—H7B C7—H7C O9—C10 O9—C11 O10—C12 O10—C13 C9—C10 C9—H9A C9—H9B C9—H9C C11—C12 C11—H11A C11—H11B C12—C16 C12—H12A C13—C14 C13—H13A C14—C15 C14—H14A 1.194 (5) 1.184 (6) 1.482 (6) 0.9600 0.9600 0.9600 1.351 (6) 1.445 (6) 1.437 (5) 1.437 (5) 1.472 (7) 0.9600 0.9600 0.9600 1.495 (6) 0.9700 0.9700 1.509 (6) 0.9800 1.507 (7) 0.9800 1.509 (6) 0.9800 sup-6 supporting information C5—H5A C5—H5B C5—H5C 0.9600 0.9600 0.9600 C15—C16 C15—H15A C16—H16A 1.518 (6) 0.9800 0.9800 C13—O1—C2 N2—N1—C1 N3—N2—N1 N1—C1—C2 N1—C1—H1B C2—C1—H1B N1—C1—H1C C2—C1—H1C H1B—C1—H1C C4—O3—C15 O1—C2—C1 O1—C2—H2A C1—C2—H2A O1—C2—H2B C1—C2—H2B H2A—C2—H2B C4—C3—H3A C4—C3—H3B H3A—C3—H3B C4—C3—H3C H3A—C3—H3C H3B—C3—H3C C6—O5—C14 O2—C4—O3 O2—C4—C3 O3—C4—C3 C8—O6—C16 C6—C5—H5A C6—C5—H5B H5A—C5—H5B C6—C5—H5C H5A—C5—H5C H5B—C5—H5C O4—C6—O5 O4—C6—C5 O5—C6—C5 C8—C7—H7A C8—C7—H7B H7A—C7—H7B C8—C7—H7C H7A—C7—H7C H7B—C7—H7C C10—O9—C11 O7—C8—O6 117.6 (4) 114.7 (6) 170.0 (9) 112.5 (6) 109.1 109.1 109.1 109.1 107.8 119.8 (4) 112.2 (5) 109.2 109.2 109.2 109.2 107.9 109.5 109.5 109.5 109.5 109.5 109.5 117.0 (4) 122.3 (5) 128.1 (5) 109.7 (5) 119.1 (4) 109.5 109.5 109.5 109.5 109.5 109.5 122.0 (5) 127.7 (5) 110.1 (5) 109.5 109.5 109.5 109.5 109.5 109.5 116.1 (4) 123.5 (4) C12—O10—C13 C10—C9—H9A C10—C9—H9B H9A—C9—H9B C10—C9—H9C H9A—C9—H9C H9B—C9—H9C O8—C10—O9 O8—C10—C9 O9—C10—C9 O9—C11—C12 O9—C11—H11A C12—C11—H11A O9—C11—H11B C12—C11—H11B H11A—C11—H11B O10—C12—C11 O10—C12—C16 C11—C12—C16 O10—C12—H12A C11—C12—H12A C16—C12—H12A O1—C13—O10 O1—C13—C14 O10—C13—C14 O1—C13—H13A O10—C13—H13A C14—C13—H13A O5—C14—C13 O5—C14—C15 C13—C14—C15 O5—C14—H14A C13—C14—H14A C15—C14—H14A O3—C15—C14 O3—C15—C16 C14—C15—C16 O3—C15—H15A C14—C15—H15A C16—C15—H15A O6—C16—C12 O6—C16—C15 C12—C16—C15 O6—C16—H16A 111.9 (3) 109.5 109.5 109.5 109.5 109.5 109.5 123.2 (5) 125.8 (5) 111.0 (4) 107.9 (4) 110.1 110.1 110.1 110.1 108.4 106.6 (3) 109.2 (4) 114.5 (4) 108.8 108.8 108.8 107.3 (4) 108.9 (4) 108.1 (4) 110.8 110.8 110.8 108.2 (4) 108.9 (3) 111.3 (4) 109.5 109.5 109.5 107.1 (3) 109.2 (4) 110.1 (3) 110.1 110.1 110.1 108.3 (3) 108.8 (3) 111.9 (4) 109.3 Acta Cryst. (2009). E65, o2651 sup-7 supporting information O7—C8—C7 O6—C8—C7 126.0 (5) 110.5 (5) C12—C16—H16A C15—C16—H16A 109.3 109.3 C1—N1—N2—N3 N2—N1—C1—C2 C13—O1—C2—C1 N1—C1—C2—O1 C15—O3—C4—O2 C15—O3—C4—C3 C14—O5—C6—O4 C14—O5—C6—C5 C16—O6—C8—O7 C16—O6—C8—C7 C11—O9—C10—O8 C11—O9—C10—C9 C10—O9—C11—C12 C13—O10—C12—C11 C13—O10—C12—C16 O9—C11—C12—O10 O9—C11—C12—C16 C2—O1—C13—O10 C2—O1—C13—C14 C12—O10—C13—O1 C12—O10—C13—C14 C6—O5—C14—C13 −175 (5) 104.9 (7) −125.6 (6) −62.8 (8) −4.1 (7) 175.6 (4) 7.2 (7) −176.9 (4) −1.7 (7) 177.9 (4) 1.2 (7) 178.3 (4) −173.2 (4) −172.7 (4) 63.1 (5) −69.9 (5) 51.0 (5) −72.1 (6) 171.2 (4) 177.7 (3) −65.0 (5) 113.7 (5) C6—O5—C14—C15 O1—C13—C14—O5 O10—C13—C14—O5 O1—C13—C14—C15 O10—C13—C14—C15 C4—O3—C15—C14 C4—O3—C15—C16 O5—C14—C15—O3 C13—C14—C15—O3 O5—C14—C15—C16 C13—C14—C15—C16 C8—O6—C16—C12 C8—O6—C16—C15 O10—C12—C16—O6 C11—C12—C16—O6 O10—C12—C16—C15 C11—C12—C16—C15 O3—C15—C16—O6 C14—C15—C16—O6 O3—C15—C16—C12 C14—C15—C16—C12 −125.1 (4) −65.4 (5) 178.3 (3) 175.0 (4) 58.7 (5) −127.5 (4) 113.3 (4) 70.1 (4) −170.6 (3) −171.2 (3) −52.0 (5) −114.6 (4) 123.6 (4) −174.5 (3) 66.0 (4) −54.6 (4) −174.1 (4) −73.1 (4) 169.5 (3) 167.2 (3) 49.9 (5) Hydrogen-bond geometry (Å, º) D—H···A D—H H···A D···A D—H···A C14—H14A···O4 C15—H15A···O2 C16—H16A···O7 C16—H16A···O9 C9—H9B···O1i 0.98 0.98 0.98 0.98 0.96 2.21 2.32 2.27 2.44 2.48 2.666 (6) 2.723 (6) 2.702 (6) 2.824 (5) 3.402 (6) 107 104 106 103 160 Symmetry code: (i) x−1/2, −y+3/2, −z. Acta Cryst. (2009). E65, o2651 sup-8
https://openalex.org/W2517000923
https://www.intechopen.com/citation-pdf-url/51283
English
null
Water Quality Modelling of Northern Lakes Case Study (Egyptian Northern Lakes)
InTech eBooks
2,016
cc-by
6,534
Selection of our books indexed in the Book Citation Index in Web of Science™ Core Collection (BKCI) Interested in publishing with us? Contact book.department@intechopen.com Numbers displayed above are based on latest data collected. For more information visit www.intechopen.com Open access books available Countries delivered to Contributors from top 500 universities International authors and editors Our authors are among the most cited scientists Downloads We are IntechOpen, the world’s leading publisher of Open Access books Built by scientists, for scientists 14% 191,000 210M TOP 1% 154 7,200 Chapter 10 Abstract Since the shallow coastal lakes are not only one of the most valuable ecosystems in the world but also some of the most threatened as they receive the wastewater dis‐ charged from the watershed, it was important to develop a more detailed modelling component for the lake system. Nowadays, relative to the present advances in computational sciences, hardware and software, improvement in rivers, catchments and lakes modelling has been only modest since the past few decades. The main objective of the study is to examine and evaluate the impact of alternative water quality management practices in the selected drainage catchment, and their effect on the environmental condition of the lake as an important component of the watershed. A hydrodynamic and water quality model was used to study the current status of coastal lakes subject to the discharges and pollution loadings coming from the agricultural drains and the point sources discharge directly to the lake, through simulating the flow circulation inside the main basin of the lake, the transport and advection of the pollutants due to the effluent discharges from drains and other sources of pollutants, and identify and develop the most critical surface drainage water quality indicators to simulate and predict the temporal and spatial variation of pollution. Keywords: water quality, modelling, coastal lakes, pollution, Mariout Lake Keywords: water quality, modelling, coastal lakes, pollution, Mariout Lake Water Quality Modelling of Northern Lakes Case Study (Egyptian Northern Lakes) Noha Donia Additional information is available at the end of the chapter Additional information is available at the end of the chapter http://dx.doi.org/10.5772/63526 © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, 1. Introduction The aim of modelling of surface water quality is to construct a mathematical model of the water body in order to simulate variation in water quality with the variation in initial and boundary conditions. The modelling is applied to solve problems related to water quality by analysing © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Lake Sciences and Climate Change 176 the occurring phenomena and finding dependencies between them as well as to attempt to predict and quantify effects of the changes in the aquatic environment [1]. Over the past 75 years, engineers have developed water quality models to simulate a wide variety of pollutants in a broad range of receiving waters. In recent years, these receiving water models are being coupled with models of watersheds, groundwater, bottom sediments to provide comprehensive frameworks predicting the impact of human activities on water quality [2]. Mathematical modelling of lakes water quality started to receive high attention in the 1960s. According to [3], mathematical models of lakes have evolved along two different lines. First, there was the extension of the zero‐dimensional model to one‐, two‐ and three‐dimensional models. Then, there were the modelling activities that focused primarily on a better and more detailed description of the chemical‐biological processes [4]. From the survey of the literature, many lake models have been applied in various regions, and as a result of several applications, models have become more and more complex. Modelling of water quality in lakes involves the representations of effluent quality, mixing pattern, physical and chemical processes and biological growths and their role in the removal and release of substances. Such models can be classified into physical, chemi‐ cal or biological models that simulate lakes eutrophication. Another classification may be as long‐term planning models or short‐term operational models. Several water quality studies have been performed on lakes in general and on shallow lakes in particular, for example, [5–9]. The objective of this chapter is to illustrate the technique of building a hydrodynamic and water quality model as application on one of the Egyptian coastal lakes (Mariout Lake). 2. Lake Mariout, one of Egyptian Northern Delta lakes The northern delta lakes provide many economic, environmental and social benefits to the people of Egypt and the Mediterranean. Some of these benefits are easy to quantify. For example, the 1998 catch from the four lakes — Burullus, Idku, Manzala and Mariout — amounted to LE 1.05 billion, or roughly 35 percent of the country's total fish income. The lakes currently provide passive primary and secondary treatment of wastewater that would be equivalent to hundreds of millions of dollars worth of new treatment plants. Other important and valuable benefits are much harder to quantify. It is unknown how much property damage and economic dislocation Lake Mariout prevented in 1992 when Alexandria experienced severe flooding, or how much the lake contributes to agricultural production by buffering against seawater intrusion of groundwater supplies. Beyond Egypt, it is difficult to value the benefit that those wetlands provide to sustain migratory birds of the entire Eastern Mediter‐ ranean/Black Sea region. In the future, with predicted sea level rise and the frequency of coastal storms on the increase, the lakes may be even more important to prevent natural disasters [10]. Water Quality Modelling of Northern Lakes Case Study (Egyptian Northern Lakes) http://dx.doi.org/10.5772/63526 177 Figure 1. Lake Mariout location. Figure 2. Lake Mariout satellite image and sample location. Water Quality Modelling of Northern Lakes Case Study (Egyptian Northern Lakes) http://dx.doi.org/10.5772/63526 1 Figure 1. Lake Mariout location. Figure 1. Lake Mariout location. Figure 2. Lake Mariout satellite image and sample location. Figure 2. Lake Mariout satellite image and sample location. Lake Sciences and Climate Change 178 Lake Mariout is the smallest of the northern lakes and perhaps the most threatened. Lake Mariout lies between Latitude 31° 07’ N and Longitude 29° 57’ E along the Mediterranean coast of Egypt. The lake environment was continuously subjected to quality degradation due to human pressure as well as land reclamation reducing the area of the lake. Lake Mariout is the smallest of the northern lakes and perhaps the most threatened. Lake Mariout lies between Latitude 31° 07’ N and Longitude 29° 57’ E along the Mediterranean coast of Egypt. The lake environment was continuously subjected to quality degradation due to human pressure as well as land reclamation reducing the area of the lake. 2. Lake Mariout, one of Egyptian Northern Delta lakes Currently, the lake is divided artificially into four main basins as shown in Figures 1 and 2, namely, 6000 feddans basin (Main Basin), 5000 feddans basin (South Basin), 3000 feddans basin (West Basin) and 1000 feddans basin (Aquaculture Basin). These ponds are dissected by roads and embankments as follows [11]: • The Main Basin is about 14.77 km2 with an average depth of 0.8 m. This basin receives water from the El‐Nubariya canal and Omoum drain, the heavily polluted water by industrial wastes; and untreated sewage from municipal and industrial outfalls of El‐Qalaa drain had been diverted through the new Richa drain. West Wastewater Treatment Plant effluent had been discharged along the north of the basin. One minor inflow is a discharge of waste from a textile plant into a ditch which crossed Qabarry. The Main Basin is bisected by the Nubariya canal, and the triangular area between this canal and the Omoum drain is also considered as part of the Main Basin. ◦The Western Basin is about 11.59 km2 with average water depths of 0.7 m. Adjacent to this basin, salt marshes are located and are producing 1,000,000 kg of unrefined salt per year. They are surrounded by many industrial and petrochemical companies. ◦The Southern Basin covers 33.77 km2, and is partially divided by El‐Nubariya canal, although breaks in the canal embankments allow water to pass from one sub‐basin to the other. This basin is very shallow and average water depths are 0.68 m. The main source of water is El‐Omoum drain and El‐Nubariya canal. Along the length of the El‐Omoum, a series of breaches allow flow to leave the drain and enter the basin. Along the western boundary, a series of breaches allow exchange of water between the basin and the El‐ Nubariya canal. This basin consists of heavily vegetated areas and fish farms. Also, considerable wetland loss in this portion of the basin was recorded. Many petrochemical and petroleum companies, such as Amria and Misr Petroleum companies, discharge their wastes into the north part of this basin. ◦The (Fisheries) Aquaculture Basin covers 9.44 km2 (849 feddans), and it consists of a series of small basins separated by earthen berms. This facility is a research centre for fish farming and is operated by the Alexandria Governorate. There are two sources of water for this facility. 2. Lake Mariout, one of Egyptian Northern Delta lakes One is small pump stations which pump 400,000 m3/day from Abis drain and which run parallel to the basin. The other is small openings from El‐Omoum drain. ◦The (Fisheries) Aquaculture Basin covers 9.44 km2 (849 feddans), and it consists of a series of small basins separated by earthen berms. This facility is a research centre for fish farming and is operated by the Alexandria Governorate. There are two sources of water for this facility. One is small pump stations which pump 400,000 m3/day from Abis drain and which run parallel to the basin. The other is small openings from El‐Omoum drain. Comparison of the chemical composition of Lake Mariout water with that of proper sea water and drainage water shows that the lake water presents an intermediate composition between both sea and drainage water. This phenomenon can be explained by seepage from the sea. Such explantation is supported by the low level of water and by the water balance which is supported by older data of the salt content of wells in Mariout region. There are three main canals (El‐Qalaa, El‐Omoum and El‐Nubariya) that are considered the main inflows to the lake. El‐Qalaa drain is located at north‐east while El‐Omoum and Water Quality Modelling of Northern Lakes Case Study (Egyptian Northern Lakes) http://dx.doi.org/10.5772/63526 179 El‐Nubariya canals are at the east and south of the lake, respectively. Other inflows are the water treatment plant (WTP) and the discharges from the petrochemical area nearby the north western basin. El‐Omoum and El‐Nubariya canals are less polluted drains, considering their nutrients (N, P) and DO concentrations. El‐Omoum receives mainly agricultural drainage water; moreover, the drain receives both raw and treated waste‐ water from several defined and undefined sources. Therefore, these drains also contribute to the nutrient loadings in the lake, but to a lesser extent. Additionally, non‐point sources such as agricultural run‐off containing pesticides and fertilizers are also contributing to the deterioration of the environmental quality of the lake [12]. As a result of the high nutrient loading, the lake has become anthropogenic‐polluted and eutrophic. Eutrophication of lakes is a natural process that can be accelerated by man's activities that introduce an excess of nutrients together with other pollutants. Main sources of nutrients and pollutants can include: human sewage, industrial waste, farm and urban run‐off. Currently, the lake is 60% covered by aquatic vegetation (Phragmites australis and Eichornia crassipes). 2. Lake Mariout, one of Egyptian Northern Delta lakes High nutrients and low DO concentrations have been observed specially at the Main Basin, which in turn affects the ecological processes occurring in the lake and therefore its whole environmental condition [13]. Applying a hydrodynamic and water quality numerical modelling study at Lake Mariout will help to give some answers to both planning and technical questions of water quality managers, decision makers and those of technical engineers working on the sampling, monitoring and analysis of water quality parameters. Specifically, the main objectives of the hydrodynamic and water quality numerical model study can be summarised as follows: ◦Studying the current status of the Lake Mariout and using the available data to simulate the Main Basin of Lake Mariout subject to the discharges and pollution loadings coming from the agricultural drains and the point sources discharge directly to the lake. ◦Investigate the flow circulation inside the Main Basin of Lake Mariout and its effect in minimizing the negative impacts on the water quality of the lake. ◦Investigate the flow circulation inside the Main Basin of Lake Mariout and its effect in minimizing the negative impacts on the water quality of the lake. ◦Investigate the transport and advection of the pollutants due to the effluent discharges from drains and other sources of pollutants. • Identify and develop the most critical surface drainage water quality indicators to simulate and predict the temporal and spatial variation of pollution. • Examine and evaluate different modelling scenarios to study the impact of alternative water quality management practices in the selected drainage catchment, and their effects on the environmental condition of the lake as an important component of the watershed. • Perform sensitivity analysis for modelling parameters and variables, showing the response of the model to influential parameters and coefficients used in the modelling process, especially those with high degree of uncertainties on their values. • Perform sensitivity analysis for modelling parameters and variables, showing the response of the model to influential parameters and coefficients used in the modelling process, especially those with high degree of uncertainties on their values. 2. Lake Mariout, one of Egyptian Northern Delta lakes • To achieve the study objectives, the following scope of work can be summarised as follows: • To achieve the study objectives, the following scope of work can be summarised as f Lake Sciences and Climate Change 180 • Data collection including both hydrographic and bathymetric survey for the Main Basin of Lake Mariout, which is necessary to fulfil the hydrodynamic and water quality simulations of the numerical model of the main basin of Lake Mariout. • Develop a two‐dimensional hydrodynamic and water quality numerical flow model to simulate the flow pattern in the lake vicinity of the study area, and the discharges and pollution loadings coming from the agricultural drains and the point sources discharge directly to the lake. • After the model development, calibration is conducted in order that the model will be ready for different potential model scenarios. This will help to investigate the impact of alternative water quality management processes and their effects on the environmental condition of the lake. The analysis of the model scenarios forms the basis to assess and select the optimum solution for minimizing the pollution coming from the agriculture drains and other point source of pollution to the lake. 3. Data collection and field measurements The setup, testing and application of a lake model of hydrodynamics and water quality require a variety of different data sets to specify boundary or input conditions and for model calibra‐ tion and verification. In case of Mariout Lake, data collection includes historical data on the wind conditions, water temperature, evaporation rate and the precipitation rate in the project site. Wind data were extracted from the work of [14], the data show that the predominant wind direction is 22.5° NW with a wind speed of approximately 3.75 m/s. The average monthly temperature in Lake Mariout ranged from 13 to 29°C in a study carried by [15]. The annual average evapotranspi‐ ration used in the model was calculated with the Penman‐Monteith method [16], where the crop coefficient Kc (reed) used in the calculation was extracted from a study based on field experiment and measurements carried out in three locations in the UK [17]. The precipitation value used in the model corresponds to the average precipitation of year 2007, (0.66 mm/day) as presented in the Lake Mariout data acquisition report (NIOF, 2007[sn1]). The topography and bathymetry data used in the model were provided by NIOF in a DEM format with resolution of 45 m reference is made to [18]. Field measurements were carried out in coordination with the National Institute of Oceanog‐ raphy and Fisheries (NIOF) for 2 weeks. The samples were taken from nine sites representing the Main Basin and discharge points of Qalaa drain, Omoum drain, Nubariya canal and El‐ Max pumping station as shown in Figure 2; the measurements comprised the following: • Water flows (m3/h) which determines the inflow, outflow in the Main Basin. • Water flows (m3/h) which determines the inflow, outflow in the Main Basin. • Water levels within the basin to a fixed point. • Basic physical parameters: temperature, salinity and total suspended matter. Water Quality Modelling of Northern Lakes Case Study (Egyptian Northern Lakes) http://dx.doi.org/10.5772/63526 181 • Organic matter of the lake. • Nutrient variables: ammonia, nitrates and phosphorus compounds. • Biological data including: chlorophyll‐a, phytoplankton, zooplankton. • Biological data including: chlorophyll‐a, phytoplankton, zooplankton. • Microbiological data: faecal coliform and total coliform. Results of field measurements of hydraulic parameters are shown in Table 1 and results of field measurements of water quality parameters are shown in Table 2. Site no. 3. Data collection and field measurements Site name Cross section (m2) Average weekly water velocities (m/s) Average weekly water discharges (m3/hour) 2 Nubariya canal (desert road) 122.00 0.44 192480 3 Omoum Drain (desert road) 097.00 0.42 146658 5 Fisheries Hole in dam 001.60 0.30 001699 6 End Omoum diversion before Nubaria 136.00 0.11 053000 7 El‐Max Pumping Station 243.00 0.30 263193 8 Western Water Treatment Plant 003.40 1.22 015105 9 Qalaa Drain outlet in Main Basin 008.90 0.86 027602 Table 1. Water flow measurements. Code Temp °C Trans cm EC mS/cm TDS g/l TSS g/l  Sal ‰  pH DO mg/l BOD mg/l COD mg/l NH3 µg/l  NO2 µg/l  NO3 µg/l  TN µg/l  PO4 µg/l  Tp µg/l  West Nubaria PS 25.7 35 7.68 4.82 0.040 4.81 7.18 7.38 4.90 22.09 971 89.6 332.6 1981.2 54.2 115.36 Nubaria Canal Desert Road 22.1 60 5.26 3.49 0.034 3.48 7.68 5.60 4.12 21.64 723 106.4 529.4 1844.7 66.7 161.04 Ommoun Desert road 22.3 60 3.45 2.34 0.034 2.33 7.52 5.82 4.66 20.22 2164 150.5 470.1 3492.6 194.7 566.64 End of Qalaa Diversion Canal before Nubaria Canal 22.8 15 2.39 1.21 0.111 1.21 7.33 0.00 111.56 88.96 19956 0.00 0 22856.1 915.2 1203.84 Western WTP 24.6 10 1.99 1.14 0.125 1.14 7.12 0.00 140.12 92.92 20996 0.00 0 24869.3 1019.7 1335.84 Main Basin 21.1 40 3.65 2.40 0.034 2.39 8.68 9.12 5.06 32.32 2640 102 150.8 3886.> 165.8 436.92 Noha El Max station 21.3 35 5.9 3.59 0.043 3.58 7.32 5.42 4.92 40.84 4610 92.6 212.5 6365.7 190.3 528.24 Fisheries hole in dam 22.1 15 2.41 1.28 0.115 1.28 7.67 0.00 120.04 90.69 19670 0.00 0 22886.4 928.4 1244.76 End of Qalaa drain 23.8 20 2.34 1.26 0.109 1.26 7.22 0.00 123.12 89.50 20030 0.00 0 23386.1 905.3 1236.84 Table 2 Measured water quality parameters in Mariout Lake • Microbiological data: faecal coliform and total coliform. Site no. Table 2. Measured water quality parameters in Mariout Lake. 3. Data collection and field measurements The following section represents the hydrodynamic and water quality modelling studies that were carried out to investigate the efficiency of the water circulation system and water quality parameters inside the Main Basin of Mariout Lake. The model setup, calibration and the analyses of the results of model scenarios are included. Depending on the model results and analysis, the conclusions and recommendations are presented. 4.1. Setup of the hydrodynamic model The hydrodynamic model simulates the flow pattern in the Main Basin vicinity. All parameters and variables in the model have units according to the SI conventions. The coordinate system used for the model is in WGS‐84 Geographic UTM system Zone 35. All metric coordinates in this report will be given in this coordinate system. The depths and water level information in the flow model are defined relative to a levelling datum, which is equal to mean sea level (MSL). The following sections present the steps of development of Mariout hydrodynamic model. 4. Water quality model development Delft3D Software Package of Delft Hydraulics, the Netherlands, was used to develop the hydrodynamic numerical flow and water quality model which simulates the flow pattern and the water quality inside the lake. Delft3D is a integrated, powerful and flexible software, which was developed by Deltares, the Netherlands. The hydrodynamic and water quality modules were used in this study. Consequently, a brief explanation of these modules is in the following section. The FLOW module of Delft3D is basically a multi‐dimensional (2D and 3D) hydrodynamic (and transport) simulation which calculates non‐steady flow and transport phenomena resulting from tidal and meteorological forcing on a curvilinear, boundary‐fitted grid [19]. The WAQ module of Delft3D for water quality modelling the spatial resolution generally consists of the resolution of the underlying flow field as generated by the hydrodynamic model itself or of flows on integer multiples of those hydrodynamic grid cells. For water quality modelling, there also is external forcing in the form of waste loads, meteorology, open boundary concen‐ trations, etc. [20]. 3. Data collection and field measurements Site name Cross section (m2) Average weekly water velocities (m/s) Average weekly water discharges (m3/hour) 2 Nubariya canal (desert road) 122.00 0.44 192480 3 Omoum Drain (desert road) 097.00 0.42 146658 5 Fisheries Hole in dam 001.60 0.30 001699 6 End Omoum diversion before Nubaria 136.00 0.11 053000 7 El‐Max Pumping Station 243.00 0.30 263193 8 Western Water Treatment Plant 003.40 1.22 015105 9 Qalaa Drain outlet in Main Basin 008.90 0.86 027602 Table 1 Water flow measurements Code Temp °C Trans cm EC mS/cm TDS g/l TSS g/l  Sal ‰  pH DO mg/l BOD mg/l COD mg/l NH3 µg/l  NO2 µg/l  NO3 µg/l  TN µg/l  PO4 µg/l  Tp µg/l  West Nubaria PS 25.7 35 7.68 4.82 0.040 4.81 7.18 7.38 4.90 22.09 971 89.6 332.6 1981.2 54.2 115.36 Nubaria Canal Desert Road 22.1 60 5.26 3.49 0.034 3.48 7.68 5.60 4.12 21.64 723 106.4 529.4 1844.7 66.7 161.04 Ommoun Desert road 22.3 60 3.45 2.34 0.034 2.33 7.52 5.82 4.66 20.22 2164 150.5 470.1 3492.6 194.7 566.64 End of Qalaa Diversion Canal before Nubaria Canal 22.8 15 2.39 1.21 0.111 1.21 7.33 0.00 111.56 88.96 19956 0.00 0 22856.1 915.2 1203.84 Western WTP 24.6 10 1.99 1.14 0.125 1.14 7.12 0.00 140.12 92.92 20996 0.00 0 24869.3 1019.7 1335.84 Main Basin 21.1 40 3.65 2.40 0.034 2.39 8.68 9.12 5.06 32.32 2640 102 150.8 3886.> 165.8 436.92 Noha El Max station 21.3 35 5.9 3.59 0.043 3.58 7.32 5.42 4.92 40.84 4610 92.6 212.5 6365.7 190.3 528.24 Fisheries hole in dam 22.1 15 2.41 1.28 0.115 1.28 7.67 0.00 120.04 90.69 19670 0.00 0 22886.4 928.4 1244.76 End of Qalaa drain 23.8 20 2.34 1.26 0.109 1.26 7.22 0.00 123.12 89.50 20030 0.00 0 23386.1 905.3 1236.84 Table 2. Measured water quality parameters in Mariout Lake. Lake Sciences and Climate Change 182 The following section represents the hydrodynamic and water quality modelling studies that were carried out to investigate the efficiency of the water circulation system and water quality parameters inside the Main Basin of Mariout Lake. The model setup, calibration and the analyses of the results of model scenarios are included. Depending on the model results and analysis, the conclusions and recommendations are presented. 4.1.1. Grid generation The first step in the schematization process is the design and generation of the computational grid. The computational grid is a curvilinear grid to avoid the stair case problem which affects the numerical accuracy. In the design of a curvilinear grid, it is important to follow the land boundaries as good as possible. For the generation of a computational grid, the following items are important: • the areas which require the highest resolution; • the orthogonality of individual cells; Water Quality Modelling of Northern Lakes Case Study (Egyptian Northern Lakes) http://dx.doi.org/10.5772/63526 18 183 • the spatial variation of the dimensions of the cells; • the total number of computational points. The resulting computational grid is a compromise between the above items, the selected dimensions of the model and the location of the boundaries. The general layout of the computational grid of the Mariout model is given in Figure 2. 4.1.2. Depth schematization 4.1.2. Depth schematization The schematization of the land boundaries and the water depths have been derived from the hydrographic survey data. The bathymetric data have been mapped through an interpolation procedure on the computational grid of Mariout model. In this way, each coordinate of the computational grid of the model is given a depth value. The transition between the regions covered by different bathymetric data sources have been checked and smoothed where necessary. 4.1.4. Parameter settings A uniform water density of 1025 kg/m3 was used, representing the salt water density. The acceleration of gravity was set to 9.81m/s2. The value for the horizontal eddy viscosity is set to 1.0 m2/s. The time step was selected for the model simulations based on the grid size and the Courant Number. Time step of 0.5 min (30 s) was used in the simulations. This time step fulfils the numerical criteria and the Courant Number requirements. 4.1.3. Boundary conditions In the flow simulations of a specific area with two open boundaries, it is preferable to set up one boundary as a discharge boundary and the other one as a water level boundary. In Lake Mariout model, the open boundary for Nubariya Canal and Omoum Drain were selected as a discharge boundary. The boundary at El‐Max Pumping station was selected as water level boundary, while other sources like Qalaa drain and the West Water Treatment Plant were Figure 3. Model schematization with all boundaries and sources of discharge. Figure 3. Model schematization with all boundaries and sources of discharge. Lake Sciences and Climate Change 184 simulated as source point discharge. During the calibration phase, the discharges and water level measurements at the location of the open boundaries and at the other sources of water were used in the model. In the model scenarios (production simulations), the discharge data imposed in the discharge boundary is based on the dominant flow condition. The water levels associated with these discharges were used for each scenario as a water level boundary. The relevant water levels associated to these discharges were obtained from the historical data available about the Lake Mariout. Figure 3 shows the model schematization with all bounda‐ ries and the source points of discharges. 4.2. Water quality model setup To apply the Delft3D‐WAQ module, the following steps must be followed: • Get the result from the hydrodynamic simulation and make it suitable for application in the water quality simulation (coupling process). • Get the result from the hydrodynamic simulation and make it suitable for application in the water quality simulation (coupling process). • Selection of the substances and water quality processes to be included in the model. • Preparation of initial conditions, boundary conditions, waste loads, simulation time, output variables and identification of monitoring points. • Run the simulation and check the output. • Calibrate and verify the model. 4.2.1. Selection of the processes involved in the water quality model 4.1.5. Model calibration During the model calibration, the measured depth averaged flow velocities and water levels which were carried out by the National Institute of Oceanography and Fisheries (NIOF) were compared with the model results. Tuning of the roughness parameter in the model was carried Figure 4. Flow velocity comparison at point fisheries hole in dam. Figure 4. Flow velocity comparison at point fisheries hole in dam. Water Quality Modelling of Northern Lakes Case Study (Egyptian Northern Lakes) http://dx.doi.org/10.5772/63526 185 out to obtain the best match between the model and the field measurements. Manning roughness coefficient was varied between 0.02 at non‐vegetated area and 0.06 at the heavy vegetated area along the model area to give the best match between the measurements and the model computations. Figure 4 shows the comparison between the measured and computed flow velocity values. The results for water level and currents were in good agreement with the measurements, which confirms that the model simulates the flow pattern in the main basin of Lake Mariout in the right way. 4.2.2. Model boundary conditions and observation locations Average historical monthly values have been selected for initial conditions of water quality parameters inside the lake. The continuity parameter which checks the mass balance of the model was set to 1 g/m3. The model simulation period was selected as the same period for the hydrodynamic modelling, namely, for 1 month. Water quality model time step was set to 1 min. The default values were taken as input for some selected modelled substances, that they are by default constant in time and space. However, process parameters are changed in the process parameters data group because they can vary in time and/or space. Initially, process parameters will have the default value that is taken from the PLCT. The water quality model boundary sections are selected to be the same boundary sections for the hydrodynamic model at the locations of the main input sources to the lake, where all discharges enter the lake shown in Figure 3. At the two sections for the Omoum drain outlet and Nubariya canal outlet, concentrations for different modelled parameters are defined as time‐varying boundary conditions. The concentrations used at the boundaries are time series average monthly concentrations for the modelling period. 4.2.1. Selection of the processes involved in the water quality model In Delft3D‐WAQ module, the constituents of a water system are divided into functional groups. A functional group includes one or more substances that display similar physical and/ or (bio)chemical behaviour in a water system. Functional groups can interact with each other directly or indirectly. PLCT (Processes Library Configuration Tool) is used to choose the substances and water quality processes to be modelled. The selected substances groups and parameters are described in Table 3. Substance group Selected model parameters Associated processes General Continuity, water temperature, salinity Temperature and heat exchange Oxygen‐BOD BOD‐COD‐DO Mineralization BOD and COD, sedimentation COD, re‐aeration of oxygen Suspended matter Inorganic matter (TSM) Sedimentation, resuspension Eutrophication Ammonium (NH4), nitrate (NH3), ortho‐phosphate (PO4) Nitrification of ammonium Denitrification of nitrates Suspended matter Inorganic matter (TSM) Table 3. Model parameters and associated processes. Lake Sciences and Climate Change 186 4.2.2. Model boundary conditions and observation locations 4.2.3. The water quality model calibration Figure 5 shows the simulation of dissolved oxygen in Mariout Lake as an example of output from the model. In this study, the water quality model calibration is done on the conventional water quality parameters or oxygen group, nutrients group and coliform group (faecal and total) and process parameters are adjusted for of calibration. The model calibration was carried Figure 5. Simulation of dissolved oxygen in Lake Mariout. Figure 5. Simulation of dissolved oxygen in Lake Mariout. Water Quality Modelling of Northern Lakes Case Study (Egyptian Northern Lakes) http://dx.doi.org/10.5772/63526 187 out by visual comparison of simulations and measurements in graphs, together with the calculation of the statistical error values such as mean relative error (MRE), the root mean square error (RMSE) to examine the performance of the model. The simulated water quality parameters were plotted in graphs to make comparisons with respect to the observations in Lake Mariout during field survey, which were used to check how the simulations fit the observations. Besides, MRE was used to quantify the agreement of the model, by dividing the residuals by the observed values. In this study, the calculation of RE and MRE was based on the following equations: RE=(Csim- ) 100   Cobs Cobs Sum RE n ´ ¸ ¸ where Csim and Cobs are the simulated and observed values, respectively, and n is the number of cases. The MRE denotes the mean relative difference between simulations and observations. where Csim and Cobs are the simulated and observed values, respectively, and n is the number of cases. The MRE denotes the mean relative difference between simulations and observations. Table 4 shows the different values of RE and MRE for the modelled parameters at this level. Figure 6 shows the calibration results of dissolved oxygen that shows good agreement with field measurements It is noted that at the entrance of the Qalaa drain to the lake, the DO has the lowest values; in general, the DO measurements are close to the simulated results with an RME value of 5.11%. Figure 6 shows the calibration results of dissolved oxygen that shows good agreement with field measurements. Location/parameter DetN (RE%) NH4 (RE%) N03 (RE%) CBOD5 (RE% COD (RE%) DO (RE%) FCOLI (RE%) TCOLI (RE%) Omoum Drain 5.13 5.87 1.70 3.41 1.84 0.40 27.78 0.64 WWTP 10.98 8.96 14.63 13.23 10.35 9 19.31 0.07 Fisheries Hole 3.36 1.36 6.54 1.69 4.00 9 10.14 1.11 Elmax 1.88 9.03 3.36 2.97 7.30 7.7 0.03 9.77 Main Basin Middle 0.09 8.46 6.87 6.93 11.51 0 2.39 3.22 Nobariya Canal 0.75 2.69 0.52 2.69 0.04 0.70 6.09 1.18 Qalaa Drain 10.89 4.57 6.87 4.08 4.19 9 0.41 13.31 MRE 4.72 5.01 5.79 5 5.6 5.11 9.45 4.19 Table 4. Relative error for the calibrated model parameters. Table 4. Relative error for the calibrated model parameters. Table 4. Relative error for the calibrated model parameters. The simulated BOD and COD results are very close to the measured values at most locations within the lake, and the MRE value is around 5% for BOD5 and 5.6% for COD. For eutrophi‐ cation parameters group, the values show agreement between measured and modelled parameters with mean relative error 4.7% for DetN, 5% for NH4 values and 5.7% for PO4 values that are considered acceptable for this kind of water quality modelling. For bacterial parame‐ ters, the faecal coliform values show a difference between simulated and observed values at Lake Sciences and Climate Change 188 locations in the Omoum drain outlet station, with a relative error of 27%. RE=(Csim- ) 100   Cobs Cobs Sum RE n ´ ¸ ¸ This could be due to the low‐velocity distributions at these locations around the lake edges; but the overall MRE for all measurement locations is within an acceptable range of 9% for faecal coliform and 4.2% for total coliform. Figure 6. Comparison between measured and modelled DO. Figure 6. Comparison between measured and modelled DO. 5. Conclusions Unfortunately, Lake Mariout, one of the Egyptian coastal lakes, suffers from almost all possible environmental problems. In order to evaluate the environmental condition of the Lake Mariout, a 3D hydrodynamic and water quality model that simulates the lake response to pollution loading from the watershed has been developed using the Delft3D hydrodynamic module coupled with the DWAQ module. The model refers to the lake's Main Basin model including watershed simulation scenarios. First, the 2D hydrodynamic model was developed to simulate the hydrodynamic behaviour of the lake through simulating the water velocity, current and flow within the lake basin. The developed, well‐structured hydrodynamic model was also capable of describing the physical and hydrodynamic processes of the water system. Second, a reliable water quality model lake system in this research work is coupled with the developed and calibrated hydrodynamic 2D model. The basic water quality modelling component simulates the main water quality parameters including the oxygen compounds (BOD, COD, DO), nutrients compounds (NH4, TN, TP) and finally the temperature, salinity and inorganic matter. The calibration was conducted to compare the model results with the observed data at the different locations for both the hydrodynamic and the water quality models. The model results Water Quality Modelling of Northern Lakes Case Study (Egyptian Northern Lakes) http://dx.doi.org/10.5772/63526 189 and calculations are in reasonable agreement with the measured concentrations. This devel‐ oped calibrated model is able to predict the basic water quality indicators of the lake system and ready to conduct any scenarios for watershed water quality management. Acknowledgements Special thanks to the Alexandria Coastal Zone Management Project (2010–2015) financed by the Global Environment Facility (GEF) managed through the World Bank in coordination with the Egyptian Environmental Affairs Agency (EEAA) for providing the data required to accomplish this work. Noha Donia Address all correspondence to: ndonia@gmail.com Institute of Environmental studies and Researches, Ain Shams University, Cairo Institute of Environmental studies and Researches, Ain Shams University, Cairo References [1] Chapra S., Surface Water Quality Modeling. 1997; MacGraw Hill, N.Y. [2] Chapra S. C., Engineering water quality models and TMDLs. Journal of Water Resour‐ ces Planning and Management, 2003; Vol. 129(4): pp. 245–355. [3] Jorgensen S. E., Ecological modeling of lakes. In Orlob G.T., Mathematical Modelling of Water Quality: Streams, Lakes and Reservoirs. 1983; John Wiley & Sons, New York, ISBN 047‐1100315. [4] Jorgensen S. E., Kamp‐Nielsen L., Christensen T., Windolf‐Nielsen J., Westergaard B. Validation of a prognosis based upon a eutrophication model. Ecological Model, 1986; Vol. 32: pp. 165–182. [5] Collins C. D., Evaluating Water Quality for Lake Management. Final Report. Technical Report, 1988; PB‐89‐148159/XAB. New York State Museum, Albany, NY, USA. [6] Stephan G. H., Fang X., Model simulations of dissolved oxygen characteristics of Minnesota lakes: past and future. Environmental Management, 1993; Vol. 18(1): pp. 73– 92. Lake Sciences and Climate Change 190 [7] Sagehashi M., Sakoda A., Suzuki, M. A mathematical model of a shallow and eutrophic lake (the Keszthely Basin, Lake Balaton) and simulation of restorative manipulations. Water Research, 2001; Vol. 35(7): pp. 1675–1686. [8] Buttcher D., Approaches for Nutrient Management in the Lake Okeechobee Watershed, Symposium Handbook, Practical Management for Good Lake Water Quality. 2003; New Zealand. [9] Zacharias I., Gianni A., Hydrodynamic and dispersion modeling as a tool for restora‐ tion of coastal ecosystems. Application to a re‐flooded. Environmental Modelling and Software, 2008; Vol. 23(6): pp. 751–767. [10] EEAA (The Egyptian Environmental Affairs Agency), Annual Report for the Environ‐ mental Monitoring Program for the Northern Lakes, 2012; Ministry of Environment, Egypt. [11] ALAMIM (Alexandria Lake Mariout Integrated Management), Integrated Action Plan, EC‐SMAP III, March 2009; American Public Health. [12] Hossam M. N., Salem A. A. S., Evaluation of drainage water quality for reuse: a case study of the Omoum drain in Egypt. Lowland Technology International, 2003; Vol. 5(2): pp. 27–38. [13] Mateo M. Á., Lake Mariout: An Ecological Assessment, Laura Serrano and Oscar Serrano (CEAB‐CSIC), WADI Project (Water Demand Integration; INCOCT‐ 2005‐ 015226) and CEDARE (Centre for the Development of the Arabic Region), 2009. [14] SOGREAH, Alexandria Integrated Coastal Zone Management AICZM, Egyptian Pollution Abatement Project EPAP II,). Base line Conditions, 2008. [15] Mahlis A. M., El‐Wakeel S. K., Morcos S. A., The major cations in Lake Mariout waters. Hydrobiologica, 1970; Vol. 36(2): pp. 253–274. [16] Allen R. G., Pereira L. References S., Raes D., Smith M., Crop Evapotranspiration Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage, Paper 56. 1998; FAO, Rome. [17] Fermor P. M., Gilbert J. C., Gowing D. J. G., Reedbed evapotranspiration rates in England. Hydrological Processes, 2001; Vol. 15(4): pp. 621–631. [18] NIOF (National Institute of Oceanography and fisheries). Lake Mariout Data Acquis‐ ition. 2008. [19] Delft3D‐FLOW, Simulation of Multi‐Dimensional Hydrodynamic and Transport Phenomena, Including Sediments. 2015; Delaters, The Netherlands. [20] D‐Water Quality, Water Quality and Aquatic Ecology Modelling Suite. 2015; Delaters, The Netherlands.
https://openalex.org/W3046207823
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0236593&type=printable
English
null
Analysis on urban scaling characteristics of China’s relatively developed cities
PloS one
2,020
cc-by
10,296
RESEARCH ARTICLE Analysis on urban scaling characteristics of China’s relatively developed cities RESEARCH ARTICLE Xingchao LiuID*, Zhihong Zou School of Economics and Management, Beihang University, Beijing, China * liuxingchao1408@163.com * liuxingchao1408@163.com a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Liu X, Zou Z (2020) Analysis on urban scaling characteristics of China’s relatively developed cities. PLoS ONE 15(7): e0236593. https://doi.org/10.1371/journal.pone.0236593 Citation: Liu X, Zou Z (2020) Analysis on urban scaling characteristics of China’s relatively developed cities. PLoS ONE 15(7): e0236593. https://doi.org/10.1371/journal.pone.0236593 Editor: Bing Xue, Institute for Advanced Sustainability Studies, GERMANY Received: March 27, 2020 Accepted: July 8, 2020 Published: July 29, 2020 Peer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: https://doi.org/10.1371/journal.pone.0236593 Abstract China is undergoing rapid urbanization, but the speed and stage of urban development are quite heterogeneous among different regions and city types. Understanding the urban scal- ing characteristics of China’s relatively developed cities is important for addressing environ- mental and social challenges. Within the scope of 114 third-tier-and-above Chinese cities, the research calculate the scaling parameters of various urban development variables with respect to urban population and urban GRP in different city types based on urban scaling quantitative models. Also, univariate and multivariate regression analyses were performed on the factors affecting urban electricity consumption. The research results show that the urban scaling characteristics of Chinese cities differ between different types of cities, indus- trial cities show unique scaling features compared to commercial cities and mixed-economy cities. Additionally, urban electricity consumption is found to be closely related to urban pop- ulation, urban construction land area and street lamp number. The results can help different types of cities make targeted policies and provide insights for reducing resource consump- tion during the urbanization process. OPEN ACCESS Citation: Liu X, Zou Z (2020) Analysis on urban scaling characteristics of China’s relatively developed cities. PLoS ONE 15(7): e0236593. https://doi.org/10.1371/journal.pone.0236593 Editor: Bing Xue, Institute for Advanced Sustainability Studies, GERMANY Received: March 27, 2020 Accepted: July 8, 2020 Published: July 29, 2020 PLOS ONE PLOS ONE 1. Introduction At present, China’s urbanization is rapidly progressing. By 2018, China’s urbanization rate had reached 59.58% (From the National Bureau of Statistics). The sizes and numbers of Chinese cities are both growing rapidly [1]. Although China’s urbanization rate is quite fast in the world, its urbanization process still lags behind other countries [2, 3]. Besides, the complex Chinese national conditions give China’s urbanization unique characteristics [4]. Due to this excessive urbanization speed, Chinese cities’ industrial structure, resource allocation, and tech- nological progress do not match with their degree of development [5]. Mastering the process of urbanization in China needs quantitative models in the urban scaling study area. Copyright: © 2020 Liu, Zou. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are available from the China Economic and Social Development Statistical Database of the China National Knowledge Infrastructure (CNKI). Data were retrieved from the China City Statistical Yearbook (http://data.cnki.net/Yearbook/Single/ City is the principal place of human life, and people have always maintained great interest in the development of urban systems [6]. However, due to the existence of various ever-chang- ing systems such as society, economy, and infrastructure, cities can seem very complicated on the surface [7]. The explosive growth and rapid expansion of urban systems have led to fierce 1 / 18 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE Urban scaling characteristics of China N2020050229) and the China City Construction Statistical Yearbook (http://data.cnki.net/yearbook/ Single/N2019060082). The authors of this study had no special access privileges in accessing the data sets which other interested researchers would not have. N2020050229) and the China City Construction Statistical Yearbook (http://data.cnki.net/yearbook/ Single/N2019060082). The authors of this study had no special access privileges in accessing the data sets which other interested researchers would not have. competition for space and resources between different urban systems, so the sizes and shapes of cities follow specific rules [8–10]. In fact, city systems correspond with life characteristics of biological systems [11, 12]. In biological systems, there is a sub-linear power-law relationship between the quality of mammalian species and the metabolic rate of organisms [13, 14]. This allometric growth scale law is modeled as a common feature observed by all biological systems [15]. 1. Introduction The similarity between biological systems and urban systems makes it possible to con- clude universal applicable urban scaling laws based on the general allometric growth scale models in biology [16]. Funding: The author(s) received no specific funding for this work. Competing interests: The authors have declared that no competing interests exist. Competing interests: The authors have declared that no competing interests exist. By following the growth model of biological system, Bettencourt and his colleagues mod- eled the general scaling of urban systems: most characteristics of urban wealth creation and material energy use show index extensions with the increase of urban population and popula- tion interactions [16, 17]. In different geographies or different city scales, the scaling parame- ters of homogeneous indicators remain consistent [18, 19]. The urban indicators depicting the development of urban systems can be classified into three categories: innovative wealth indicators related to social wealth and social nature, such as inventions, crime rates and so on; physical energy indicators related to individual needs, such as water consumption, electricity consumption and so on [3, 20]; urban infrastructure indica- tors, such as the number of street lights, the length of the water supply pipeline, and so on [21]. Different categories of urban indicators present different characteristics as a city expands [22, 23]. A city’s innovative wealth indicators tend to exhibit super-linear growth proportionality with city expansion [24]. Cities promote urban economic growth, wealth creation, and new ideas by attracting creative and innovative individuals [22, 25]. With the growth of urban tal- ents and innovation, a city’s socio-economic performance will exceed the proportional growth of the urban population [26]. The per capita invention and creativity of larger cities are signifi- cantly higher than those of smaller cities, and the gap is further increasing, which indicates that a city’s innovative inventions have super-linear proportional relationships with the popu- lation growth [27–30]. The material and energy indicators of cities tend to be linearly proportional to the expan- sion of cities due to the close correlations with individual needs [31]. Scholars such as Kennedy explored the material and energy flows of 27 megacities with a population of more than 10 mil- lion to verify the consistency between the laws of resource flows in megacities and the general laws of urban scaling [32]. 1. Introduction Further, the material and energy flow research on Chinese cities provides supporting evidence for the linear relationships between material energy indicators and city scaling [33]. Urban infrastructure indicators tend to obey sub-linear scaling laws as cities expand, that is, as the city population grows, the physical network usually grows more slowly than the city’s scale growth [34, 35]. This is mainly because of the existence of economies of scale [36]. Among the studies of urban scaling laws, how to determine the geographical extent of cities has always been a focus of discussion [37]. The criteria used to classify cities makes a big differ- ence in the effectiveness of urban scaling models [6, 9]. Urban scale parameters are sensitive to urban partition and population size in the process of urban scaling [35, 38]. Research using public census data will continue to dominate the mainstream [39]. China’s urban development is hugely unbalanced. Cities of different development levels in different regions show disordered states for both geographical and policy reasons. Based on numerous previous studies, the urban scaling laws can be more obvious in more developed cit- ies. This study focuses on relatively developed cities in China, i.e., cities of the third tier and above on a five-tier scale. These cities have urban administrative units that are subject to high levels of urbanization and are thus more likely to belong to the same “urban system” [7]. 2 / 18 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE Urban scaling characteristics of China With the development of the urban economy, the importance of primary industry will gen- erally decline, while the proportion of secondary and tertiary industries will rise rapidly [40, 41]. The differences between the proportions of the first, second and third industries in differ- ent cities could lead to different scaling characteristics; thus, exploring the differences in scal- ing laws between different types of cities is taken into account in our work, while previous studies have ignored the impact of city type. In term of variable selection, we have included many more indicators. As independent vari- ables, both urban population and urban GRP are used to describe the scaling characteristics of cities. A broader variety of indicators concerning sustainable urban development are also included as response variables and are analyzed at finer levels. China’s urbanization process consumes a lot of energy, and electricity is an essential com- ponent [33, 42]. 1. Introduction Electricity is not only the necessary energy directly needed in the commercial and industrial development of cities, but also urban residents’ most vital energy in daily life [43, 44]. Most importantly, electricity consumption is one of the primary sources of CO2 emis- sions [45]. To analyze the electricity consumption during urban scaling, univariate and multi- variate regression analysis were conducted on the factors affecting urban electricity consumption in different types of cities. According to the analysis results, policies are recommended. The main objectives of this research include the following aspects: Calculation of the scaling parameters of urban development indicators as a function of urban population and urban GRP within the scope of 114 Chinese third-tier-and-above cities, and analysis of whether the scaling characteristics of different types of indicators are consistent with Bettencourt’s conclusions; Exploring the differences in urban scaling laws between industrial cities, commercialized cities and mixed-economy cities, and analyzing the reasons for the differences; Carrying out univariate and multivariate regression analysis on the factors affecting urban electricity consumption of different types of cities and providing some suggestions according to the research results. PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 2.1 Research data 2.1.1 Data sources. The research data mainly come from the China Urban Statistical Yearbook—2017 issued by the Department of Urban Social and Economic Investigation and the China Urban Construction Statistical Yearbook—2016 issued by the Ministry of Housing and Urban-Rural Development of the People’s Republic of China [46, 47]. The data from the two yearbooks was cross-checked for data revision, and the China eco- nomic and social development statistical database was searched for the remaining missing data [48]. The processed data table containing 51 development variables of 263 Chinese cities was assembled as the original research data. 2.1.2. Selection of research cities and description of variables. As the development of China at this stage is unbalanced and insufficient, the development status varies significantly from city to city. As the level of urban development becomes higher, the laws followed by urban development are more pronounced. Therefore, selecting Chinese cities with better development could help to improve the pertinence of the research. "2016 China Business Charm Ranking" was published by the "New First tier City Research Institute", a data news project of China Business Weekly, which ranked 338 Chinese prefec- ture-level cities on five dimensions of plasticity, including the concentration of business resources, urban hubs, urban people’s activity, lifestyle diversity and future. According to the PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 3 / 18 PLOS ONE Urban scaling characteristics of China ranking results, there are 4 first tier cities, 15 new first tier cities, 30 second tier cities, 70 third tier cities, 90 fourth tier cities and 129 fifth tier cities. Based on the original data table and city classification results of the ranking, 114 cities, including 4 first tier cities, 15 new first tier cities, 27 second tier cities and 68 third tier cities, were selected for the research. The 114 selected cit- ies are all third-tier-and-above cities. Their urban development is relatively mature and the construction of urban infrastructure is relatively better. The urban population, urban GRP and urban development resource consumption of the 114 cities account for the vast majority of Chinese cities. Exploring the scaling laws of these cities could help in understanding the overall urban development pace in China. The 114 cities were divided into three different types of cities by the classification criteria proposed by Nelson [49]. 2.1 Research data Specifically, cities in which the proportion of secondary industry GRP is higher than the national average (the average of 263 cities) plus one standard deviation (58.00%) were classified as industrial cities; cities in which the proportion of tertiary GRP is higher than the average level plus one standard deviation (57.15%) were classified as commer- cial cities, and the rest were classified as mixed-economy cities. The classification results gave 14 industrial cities, 27 commercial cities and 73 mixed-economy cities in a total of 114 cities. The 25 variables related to urban scaling selected in the research include urban population, GRP, total urban gas supply, total urban water supply, total urban electricity consumption, and so on The administrative areas of the selected variables are municipal districts The The 25 variables related to urban scaling selected in the research include urban population, GRP, total urban gas supply, total urban water supply, total urban electricity consumption, and so on. The administrative areas of the selected variables are municipal districts. The municipal district usually has high-level urbanization, massive population density and higher urban GRP. The municipal districts in China best fit the definition of cities in similar research studies. and so on. The administrative areas of the selected variables are municipal districts. The and so on. The administrative areas of the selected variables are municipal districts. The municipal district usually has high-level urbanization, massive population density and higher urban GRP. The municipal districts in China best fit the definition of cities in similar research studies. where Y(t) indicates the material resource or social activities; Y(0) is the normalization PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 2.2 Urban scaling model The calculation model commonly used in urban scaling research is the quantitative model pro- posed by Bettencourt and his colleagues: YðtÞ ¼ Yð0Þ  NðtÞ b ð1Þ ð1Þ N(t) represents a measure of the size of the urban population at time t; Y(0) is a normalized constant; Y(t) can represent a measure of material resources or social activity (e.g., wealth, pat- ents and water consumption); the index β represents the general scaling parameter of urban development indicators with respect to population size. The model applies to cities in different years and different regions. The leading urban development indicators were divided into infrastructure categories, indi- vidual demand categories and innovative wealth categories. The three types of urban indica- tors showed different scaling characteristics in the process of urban expansion. Between the different types of urban scaling indicators as the population size expands, the main differences are the general scaling parameter β values: β1 usually correspond to individual demands; β1.1–1.5>1 is usually related to social innovation wealth; β0.85<1 is usually associated with urban infrastructure. The differences in β values indicate different categories of indicators and show different scaling ratios as the urban population changes. As a direct variable reflecting the degree of urban economic development, urban GRP plays a vital role similar to that of the urban population in the expansion of cities; thus, GRP was introduced into the model as a reactive indicator. Similar to model (1), the quantitative model of urban development indicators as a function of urban GRP can be described as: YðtÞ ¼ Yð0Þ  ðGRPÞ b ð2Þ ð2Þ 4 / 18 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE Urban scaling characteristics of China constant; the general scaling parameter β represents how different urban development indica- tors vary with GRP. In order to facilitate the calculation, formula (2) is generally paired in the actual calculation process with: lnðyÞ ¼ c þ b  lnðxÞ ð3Þ ð3Þ where y represents the urban development indicators that need to be explained, such as urban electricity consumption; x represents the urban scaling variables used to explain y, and in the model of this study x is urban population and urban GRP; c is the normalization constant; b represents the general scaling parameters of urban development indicators as a function of urban population or urban GRP. 3. Results and discussion The urban scaling parameters of various urban development indicators were calculated using the urban scaling models and the 2016 urban development yearbook data. A few urban devel- opment indicators that show better fitting effects are shown in our results. In addition, univari- ate and multivariate regression analyses were conducted on the factors affecting electricity consumption of different types of cities. Based on the results, some suggestions are made for reducing urban electricity consumption. 2.2 Urban scaling model The exploration of urban electricity consumption mainly uses multivariate regression anal- ysis, and its calculation formula can be expressed as: lnðelectricityÞ ¼ c þ X n i¼1 bilnðindicatoriÞ ð4Þ ð4Þ where electricity represents the city’s electricity consumption, which includes the city’s total electricity consumption, urban industrial electricity consumption and urban residents’ elec- tricity consumption; c is the normalization constant; indicatori represents the variables affect- ing electricity consumption; bi serve as the parameters of explanatory variables of urban electricity consumption. PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 3.1 On urban scaling laws Section 3.1.1 explores the overall scaling characteristics of China’s third-tier-and-above cities and section 3.1.2 analyses the differences in the scaling laws between three different types of cities. 3.1.1 Scaling laws of all third-tier-and-above cities. Fig 1 shows the unitary regression results of urban GRP and urban population on a logarithmic scale. As can be seen from Fig 1, for China’s 114 third-tier-and-above cities, urban GRP shows a super-linear scaling relationship with the urban population (b = 1.111, R2 = 0.752), which is mainly due to the bidirectional positive feedback between the two. Cities with higher GRP are more mature and have more employment opportunities, thus attracting more urban popula- tion. More urban population could promote the further increase of urban GRP. As a result, urban GRP expands in a super-linear manner with urban population increase. Table 1 shows the scaling parameters of different urban development variables relative to urban population and urban GRP. In Table 1, it can be seen that urban development indicators related to individual needs, including total urban water supply, total urban electricity supply, fixed asset investment, built- up area and drainage pipeline length, scale linearly with the urban population. 5 / 18 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE Urban scaling characteristics of China Fig 1. Logarithmic regression of urban population and urban GRP. (A) The blue bubble corresponds to the logarithmic population and GRP of each city; (B) The blue slash represents the logarithmic regression line of urban population and urban GRP. https://doi.org/10.1371/journal.pone.0236593.g001 Fig 1. Logarithmic regression of urban population and urban GRP. (A) The blue bubble corresponds to the logarithmic population and GRP of each city; (B) The blue slash represents the logarithmic regression line of urban population and urban GRP. https://doi.org/10.1371/journal.pone.0236593.g001 Fig 1. Logarithmic regression of urban population and urban GRP. (A) The blue bubble corresponds to the logarithmic population and GRP of each city; (B) The blue slash represents the logarithmic regression line of urban population and urban GRP. https://doi.org/10.1371/journal.pone.0236593.g001 https://doi.org/10.1371/journal.pone.0236593.g001 Urban development indicators related to urban infrastructure including road area, park area and street light number expand sub-linearly with the urban population, mainly due to the existence of economies of scale. PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE PLOS ONE Urban scaling characteristics of China Table 1. Scaling parameters of urban variables with urban population and urban GRP. LN(RV) With respect to LN(POP): First, Second and Third tier cities (n = 114) With respect to LN(GRP): First, Second and Third tier cities (n = 114) b Linearity Adj-R2 b Linearity Adj-R2 TGS 1.247 Super-L 0.508 1.004 L 0.552 TWS 1.047 L 0.709 0.894 L 0.848 WSEC 0.994 L 0.669 0.853 L 0.81 FAI 0.947 L 0.667 0.807 Sub-L 0.794 CLA 0.856 L 0.748 0.717 Sub-L 0.853 DPL 0.916 L 0.635 0.784 Sub-L 0.765 RA 0.868 Sub-L 0.68 0.737 Sub-L 0.803 PA 0.788 Sub-L 0.503 0.669 Sub-L 0.594 GCA 0.932 L 0.637 0.816 Sub-L 0.802 SLN 0.761 Sub-L 0.548 0.675 Sub-L 0.707 LN(GDP)~LN(POP):b = 1.111, Adjusted R2 = 0.752 RV: Response variable TGS: Total gas supply; TWS: Total water supply; WSEC: Whole society electricity consumption; FAI: Fixed asset investment; CLA: Construction land area; DPL: Drainage pipe length; RA: Road area; PA: Park area; GCA: Green coverage area; SLN: Street lamp number. Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2: Adjusted R2. https://doi org/10 1371/journal pone 0236593 t001 Table 1. Scaling parameters of urban variables with urban population and urban GRP. TGS: Total gas supply; TWS: Total water supply; WSEC: Whole society electricity consumption; FAI: Fixed asset investment; CLA: Construction land area; DPL: Drainage pipe length; RA: Road area; PA: Park area; GCA: Green coverage area; SLN: Street lamp number. Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2: Adjusted R2. and these indicators can be collectively referred to as urban construction indicators. Urban GRP development is accompanied by energy consumption, while the restriction of material energy use efficiency makes the urban energy consumption follow certain linear proportional relationships with GRP increases. Also, the R2 values of the fitting equations between urban GRP and the indi- cators are significantly larger than those of the fitting equations between urban population and the indicators. This indicates that compared with the urban population, urban development indi- cators show stronger correlations with urban GRP, which means Chinese urban scaling character- istics could be better measured by urban GRP than the urban population. It is worth noting that in urban material energy indicators, the total urban gas supply shows significantly different scaling characteristics comparing to water supply and electricity supply. RV: Response variable TGS: Total gas supply; TWS: Total water supply; WSEC: Whole society electricity consumption; FAI: Fixed asset investment; CLA: Construction land area; DPL: Drainage pipe length; RA: Road area; PA: Park area; GCA: Green coverage area; SLN: Street lamp number. Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2: Adjusted R2. 3.1 On urban scaling laws The construction and operation of the same infrastructure at higher density are more efficient, more economically viable and often result in higher quality services and solutions that are not possible in smaller locations, therefore often leading to economies of scale, which in turn leads to slower urban infrastructure construction speed. It’s worth noting that green coverage area expands linearly with population. Green coverage area includes not only park green area, but also residential green area and transportation green area, thus green coverage area is closely related to individual needs which leads to the linear relationship with population. In general, the scaling parameter values of different types of urban development indicators are consistent with the conclusions that Bettencourt and colleagues have presented. In Table 1, indicators related to urban energy consumption, including urban total gas sup- ply, urban total water supply, and urban total electricity supply, scale linearly with urban GRP. Other indicators including fixed asset investment, construction land area, drainage pipeline length, road area, park area and street light number show sub-linear scaling with urban GRP, 6 / 18 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE PLOS ONE Urban scaling characteristics of China Table 2. Regression results of urban gas supply concerning urban population and urban GRP. LN(RV) With respect to LN(POP): First, Second and Third tier cities (n = 114) With respect to LN(GRP): First, Second and Third tier cities (n = 114) b Linearity Adj -R2 b Linearity Adj-R2 TGS 1.247 Super-L 0.508 1.004 L 0.552 TNGS 1.439 Super-L 0.44 1.183 Super-L 0.488 TNGS(FR) 1.280 Super-L 0.403 1.025 L 0.423 TGS-LPG 1.046 L 0.27 0.917 L 0.335 TGS-LPG(FR) 0.837 Sub-L 0.196 0.713 Sub-L 0.227 RV: Response variable TGS: Total gas supply; TNGS: Total natural gas supply; TNGS(FR): Total natural gas supply for residents; TGS-LPG: Total gas supply of LPG (Liquefied Petroleum Gas); TGS-LPG(FR): Total gas supply of LPG for residents Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2: Adjusted R2. Table 2. Regression results of urban gas supply concerning urban population and urban GRP. p TGS: Total gas supply; TNGS: Total natural gas supply; TNGS(FR): Total natural gas supply for residents; TGS-LPG: Total gas supply of LPG (Liquefied Petroleum Gas); TGS-LPG(FR): Total gas supply of LPG for residents Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2: Adjusted R2. https://doi.org/10.1371/journal.pone.0236593.t002 lower safety and combustion efficiency, to natural gas, with higher safety and combustion effi- ciency. The urban residents also gradually abandon the use of liquefied petroleum gas and accept natural gas with unified transportation, so the super-linear scaling relationship between urban gas supply and urban population is mainly due to the increase in urban natural gas use. Fig 2 shows that the increasing urban scale drives the construction of urban infrastructure, which leads to a considerable increase in the length of urban natural gas transmission pipe- lines, so the consumption of urban natural gas is greatly promoted. In conclusion, the super- linear scaling relationship between urban gas supply and urban population is mainly due to the rapid increase in the length of urban natural gas pipelines. 3.1.2 Research on the scaling laws of different types of cities. According to the classifi- cation results of 114 cities, the urban scaling laws of the 14 industrial cities, 27 commercial cit- ies, 73 mixed-economy cities are explored separately. Fig 3 shows the proportional amounts of the average values of urban development indica- tors in three different types compared with the total average. PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE The total gas supply scales super-linearly with the urban population (b = 1.247), while the total urban water supply and the urban electricity supply show linear proportional characteristics with urban population changes (b = 1.047, b = 0.994). In Table 1, the correlation between total urban gas supply and urban population is signifi- cantly weaker than that between the urban population and the total urban water supply or the total urban electricity consumption. In cities, the use of urban gas supply is applicable mainly for residential households. Urban gas supply is not a necessary choice for residents because urban households have more options for cooking and heating methods, while urban water and electricity are necessary conditions for residents’ family life. Therefore, the correlation between urban gas supply and urban population is significantly weaker. Urban gas mainly includes natural gas and liquefied petroleum gas. Table 2 shows the scal- ing parameter values of different types of urban gas. According to Table 2, the urban natural gas supply scales super-linearly with urban popula- tion and urban GRP and the urban LPG supply scales linearly with urban population and urban GRP, but the household LPG consumption scales sub-linearly with urban population and urban GRP. Generally speaking, urban natural gas in cities is mainly transported by natu- ral gas pipelines, while liquefied petroleum gas is mainly supplied by gas tanks. With the increase in city scale, the urban gas supply gradually shifts from liquefied petroleum gas, with 7 / 18 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE As can be seen from Fig 3, all average values of development indicators in industrial cities are much lower than the total average, indicating that the third-tier-and-above industrial cities are relatively poorly developed. The number of commercial cities accounts for 23.7%, but all average values of development indicators in commercial cities are much lower than the total average, indicating that commercial cities are more attractive to Chinese people and have bet- ter development. The number of mixed-economy cities accounts for 64.0%, and the average values of their indicators are slightly under this value, but the gaps are smaller than industrial cities, indicating that Chinese mixed-economy cities are still in a period of development and transformation with no distinctive scaling characteristics. Table 3 shows the scaling parameter calculation results of several urban development indi- cators of three different types of cities. In Table 3, it can be seen that almost all urban development indicators fail to fit well with the urban population, and it seems that the development of China’s industrial cities does not follow the general urban scaling laws. The rapid development of the secondary industry in industrial cities is worsening the ecological environment of cities, thus leading to the migration of urban residents, which can offset the immigration of urban population attracted by eco- nomic growth, so the population growth in industrial cities did not increase significantly with urban development. However, the development of industrial cities will lead to the increase of GRP inevitably, so the urban development indicators of industrial cities show good correla- tions with urban GRP. 8 / 18 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE Urban scaling characteristics of China Fig 2. Trend of urban natural gas pipeline length with the urban population. (A) The blue bubble corresponds to the logarithm of the population and the length of the gas pipeline; (B) The blue oblique line represents the logarithmic regression line between urban population and urban natural gas pipeline length. Fig 2. Trend of urban natural gas pipeline length with the urban population. (A) The blue bubble corresponds to the logarithm of the population and the length of the gas pipeline; (B) The blue oblique line represents the logarithmic regression line between urban population and urban natural gas pipeline length. https://doi.org/10.1371/journal.pone.0236593.g002 Fig 2. Trend of urban natural gas pipeline length with the urban population. PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE (A) The dark blue bars, light blue bars and gray blue bars respectively represent the proportions of the average values of urban development indicators in mixed economy cities, industrial cities, commercial cities compared with the total average. https://doi.org/10.1371/journal.pone.0236593.g003 PLOS ONE (A) The blue bubble corresponds to the logarithm of the population and the length of the gas pipeline; (B) The blue oblique line represents the logarithmic regression line between urban population and urban natural gas pipeline length. Fig 2. Trend of urban natural gas pipeline length with the urban population. (A) The blue bubble corresponds to the logarithm of the population and the length of the gas pipeline; (B) The blue oblique line represents the logarithmic regression line between urban population and urban natural gas pipeline length. https://doi.org/10.1371/journal.pone.0236593.g002 https://doi.org/10.1371/journal.pone.0236593.g002 The urban scaling characteristics of commercial cities conform to the general urban scaling laws basically and their urban scaling laws are the most apparent. Urban development indica- tors show perfect fitting effects with urban population and GRP in commercial cities. Com- mercial cities mainly depend on the development of the tertiary industry. The production and consumption of goods and the existence of consumers are critical factors for commercial urban development. Therefore, for commercial cities, more urban population and more potential consumers will bring faster urban development and higher urban GRP. In China, the most developed cities are all commercial cities. On the whole, the development of Chinese commercial cities is relatively mature and their scaling laws are more visible. The urban development of mixed-economy cities combines the development characteristics of the other two types of cities. Although the urban development indicators have discernable correlations with urban population and urban GRP, the correlation intensity is weaker than that of commercial cities and stronger than that of industrial cities. For mixed-economy cities, balancing the development of the secondary industry and tertiary industry is an important issue. The ambiguity of the urban type attribute will affect the formulation of urban policies, thus reducing the attractiveness and development potential of cities, which will ultimately affect the health of urban development. 9 / 18 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE Urban scaling characteristics of China Fig 3. Proportions of average values of development indicators for different types of cities compared with the total average. (A) The dark blue bars, light blue bars and gray blue bars respectively represent the proportions of the average values of urban development indicators in mixed economy cities, industrial cities, commercial cities compared with the total average. Fig 3. Proportions of average values of development indicators for different types of cities compared with the total average. PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 3.2 Research on influencing factors of urban electricity consumption Among the indicators reflecting the state of urban development, urban electricity consump- tion is an essential one. Electricity is an indispensable resource in the process of industrial development and urban residents’ living, and the massive consumption of electricity will inevi- tably exacerbate the destruction of the ecological environment. The univariate and multivari- ate regression analysis of influencing factors of urban electricity consumption for different types of cities can help us put forward some advice for efficient electricity use. 3.2.1 Univariate regression analysis of factors affecting urban electricity consump- tion. Table 4 lists the univariate regression results of the urban area, population, construction land area, street lamp number and per capita GRP concerning total electricity consumption, industrial electricity consumption, and household electricity consumption. Correlation analysis of the urban electricity consumption reveals the population size effect, urban form effect and urban infrastructure effect, that is, urban population, construction land area and street lamp number positively correlate with urban electricity consumption. How- ever, urban area and per capita GRP have little impact on urban electricity consumption. Urban area includes not only construction land but also land to be developed. The land area to be developed in different cities is very different from and consumes less electricity than con- struction land, so the urban area is weakly related to urban electricity consumption. The per Urban area includes not only construction land but also land to be developed. The land area to be developed in different cities is very different from and consumes less electricity than con- struction land, so the urban area is weakly related to urban electricity consumption. The per PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 10 / 18 PLOS ONE Urban scaling characteristics of China Table 3. Scaling parameters of urban development indicators with urban population and GRP in different city types. https://doi.org/10.1371/journal.pone.0236593.t003 3.2 Research on influencing factors of urban electricity consumption City type LN(RV) With respect to LN(Population) With respect to LN(GRP) b Linearity Adj-R2 b(Std.Error) Linearity Adj -R2 City-I (n = 14) TGS -1.236 Negative 0.063 -0.368 - -0.046 TWS -0.769 - -0.002 1.218 Super-L 0.502 WSEC 0.924 L 0.029 1.487 Super-L 0.674 FAI -0.287 - -0.072 0.062 - -0.082 CLA 0.078 - -0.08 0.750 Sub-L 0.601 DPL 0.432 - -0.06 0.982 L 0.269 RA -0.374 - -0.031 0.751 Sub-L 0.523 PA -0.127 - -0.079 0.380 Sub-L 0.025 GCA -1.241 Negative 0.200 0.622 Sub-L 0.119 SLN 0.536 Sub-L 0.031 0.326 Sub-L 0.038 LN(GDP)~LN(POP):b = 0.133, Adjusted R^2 = -0.076 City-C (n = 27) TGS 1.125 Super-L 0.689 0.876 L 0.646 TWS 1.067 L 0.875 0.880 L 0.901 WSEC 1.067 L 0.927 0.853 L 0.9 FAI 0.907 L 0.834 0.765 Sub-L 0.9 CLA 0.873 L 0.875 0.725 Sub-L 0.902 DPL 0.826 Sub-L 0.743 0.740 Sub-L 0.908 RA 0.840 Sub-L 0.78 0.727 Sub-L 0.888 PA 0.750 Sub-L 0.61 0.657 Sub-L 0.712 GCA 0.985 L 0.756 0.880 L 0.921 SLN 0.723 Sub-L 0.607 0.649 Sub-L 0.746 LN(GDP)~LN(POP):b = 1.148, Adjusted R^2 = 0.868 City-M (n = 73) TGS 1.296 Super-L 0.458 1.067 L 0.543 TWS 1.042 L 0.649 0.889 L 0.823 WSEC 0.900 L 0.515 0.827 Sub-L 0.763 FAI 1.024 L 0.633 0.883 L 0.823 CLA 0.888 L 0.73 0.707 Sub-L 0.818 DPL 0.988 L 0.621 0.802 Sub-L 0.714 RA 0.912 L 0.638 0.743 Sub-L 0.739 PA 0.802 Sub-L 0.446 0.657 Sub-L 0.523 GCA 0.900 L 0.600 0.754 Sub-L 0.735 SLN 0.810 Sub-L 0.509 0.721 Sub-L 0.705 LN(GDP)~LN(POP):b = 1.077, Adjusted R2 = 0.663 City-I: Industrial cities; City-C: Commercial cities; City-M: Mixed-economy cities; RV: response variable; TGS: Total gas supply; TWS: Total water supply; WSEC: Whole society electricity consumption; FAI: Fixed asset investment; CLA: Construction land area; DPL: Drainage pipe length; RA: Road area; PA: Park area; GCA: Green coverage area; SLN: Street lamp number. Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2:Adjusted R2. Table 3. Scaling parameters of urban development indicators with urban population and GRP in different city types. rban development indicators with urban population and GRP in different city types. City-I: Industrial cities; City-C: Commercial cities; City-M: Mixed-economy cities; RV: response variable; TGS: Total gas supply; TWS: Total water supply; WSEC: Whole society electricity consumption; FAI: Fixed asset investment; CLA: Construction land area; DPL: Drainage pipe length; RA: Road area; PA: Park area; GCA: Green coverage area; SLN: Street lamp number. PLOS ONE PLOS ONE Urban scaling characteristics of China Table 4. Univariate regression results of electricity consumption in Chinese third-tier-and-above cities. LN(IV) With respect to LN(electricity use): First, second and third cities(n = 114) City-wide(WSEC) Industry Household b Linearity Adj-R2 b Linearity Adj-R2 b Linearity Adj-R2 UA 0.473 Sub-L 0.153 0.459 Sub-L 0.104 0.487 Sub-L 0.18 POP 0.994 L 0.669 1.033 L 0.532 1.003 L 0.755 CIA 1.051 L 0.738 1.087 L 0.574 1.011 L 0.763 SLN 0.961 L 0.64 1.021 L 0.533 0.941 L 0.684 P-GRP 0.908 L 0.193 0.985 L 0.167 0.841 Sub-L 0.18 IV: Independent variable; WSEC: Whole society electricity consumption UA: Urban area; Pop: Population; CLA: Construction land area; SLN: Street Lamp number; P-GRP: Per capita GRP Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2: Adjusted R2. Table 4. Univariate regression results of electricity consumption in Chinese third-tier-and-above cities. IV: Independent variable; WSEC: Whole society electricity consumption p y y p UA: Urban area; Pop: Population; CLA: Construction land area; SLN: Street Lamp number; P-GRP: Per capita GRP Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2: Adjusted R2. he compositions of electricity consumption in different types of cities are different. The compositions of electricity consumption in different types of cities are different. According to Fig 4, it can be found that the power consumption of industrial cities is mainly concentrated in industrial electricity consumption, while household electricity consumption and other electricity consumption are relatively small. Compared with industrial cities, com- mercial cities and mixed-economy cities use significantly less industrial electricity, and house- hold electricity and other types of electricity consume relatively more. The different compositions of electricity consumption may affect the scale characteristics of electricity con- sumption in different types of cities. y yp y y compositions of electricity consumption may affect the scale characteristics of electricity con- sumption in different types of cities. p yp According to Table 5, the total electricity consumption of industrial cities has strong super- linear scaling relationships with urban construction land area and weak correlation with the Table 5. Univariate regression results of urban electricity consumption in different types of cities. IV: Independent variable; EU: Electricity use; WSEC: Whole society electricity consumption; UA: Urban area; POP: Population; CLA: Construction land area; SLN: Street lamp number; P-GRP: Per capita GRP U: Electricity use; WSEC: Whole society electricity consumption; UA: Urban area; POP: Population; CLA: Construction land : Per capita GRP p p Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2: Adjusted R2. y y y y IV: Independent variable; EU: Electricity use; WSEC: Whole society electricity consumption; UA: Urban area; POP: Population; CLA: Construction land area; SLN: St t l b P GRP P it GRP IV: Independent variable; EU: Electricity use; WSEC: Whole society electricity consumption; UA: Urban area; POP: Popula Street lamp number; P-GRP: Per capita GRP City-I: Industrial cities; City-C: Commercial cities; City-M: Mixed-economy cities p p Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2: Adjusted R2. https://doi.org/10.1371/journal.pone.0236593.t005 ; WSEC: Whole society electricity consumption; UA: Urban area; POP: Population; CLA: Construction land area; SLN: ; p Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2: Adjusted R2. Street lamp number; P-GRP: Per capita GRP Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2: Adjusted R2. -C: Commercial cities; City-M: Mixed-economy cities GRP Sub-Linear; Adj-R2: Adjusted R2. s://doi.org/10.1371/journal.pone.0236593.t005 3.2 Research on influencing factors of urban electricity consumption Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2:Adjusted R2. City-I: Industrial cities; City-C: Commercial cities; City-M: Mixed-economy cities; RV: response variable; TGS: Total gas supply; TWS: Total water supply; WSEC: Whole society electricity consumption; FAI: Fixed asset investment; CLA: Construction land area; DPL: Drainage pipe length; RA: Road area; PA: Park area; GCA: Green coverage area; SLN: Street lamp number. Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2:Adjusted R2. City-I: Industrial cities; City-C: Commercial cities; City-M: Mixed-economy cities; RV: response variable; TGS: Total gas supply; TWS: Total water supply; WSEC: Whole society electricity consumption; FAI: Fixed asset investment; CLA: Construction land area; DPL: Drainage pipe length; RA: Road area; PA: Park area; GCA: Green coverage area; SLN: Street lamp number. Super-L: Super-Linear; L: Linear; Sub-L: Sub-Linear; Adj-R2:Adjusted R2. capita GRP can be used to measure the affluence of the residents in different regions, but the affluence of urban residents does not have much effect on consumption of essential living resources such as electricity, so the per capita GRP and electricity consumption present a weak correlation. capita GRP can be used to measure the affluence of the residents in different regions, but the affluence of urban residents does not have much effect on consumption of essential living resources such as electricity, so the per capita GRP and electricity consumption present a weak correlation. Table 5 lists the univariate regression results of total electricity consumption, industrial electricity consumption and household electricity consumption relative to the urban area, pop- ulation, construction land area, street lamp number and per capita GRP in different types of cities. 11 / 18 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE City type LN(IV) With respect to LN(EU) City-wide EU(WSEC) Industry Household b Linearity Adj-R2 b Linearity Adj-R2 b Linearity Adj-R2 City-I (n = 14) UA 0.447 Sub-L 0.114 0.517 Sub-L 0.097 0.114 Sub-L -0.068 POP 0.924 L 0.019 0.883 L -0.019 1.532 Super-L 0.324 CLA 1.706 Super-L 0.805 2.094 Super-L 0.828 0.494 Sub-L 0.049 SLN 0.978 L 0.230 1.105 Super-L 0.189 0.822 Sub-L 0.281 P-GRP 0.983 L 0.164 1.287 Super-L 0.206 -0.096 Negative -0.087 City-C (n = 27) UA 0.689 Sub-L 0.274 0.739 Sub-L 0.187 0.735 Sub-L 0.348 POP 1.067 L 0.927 1.254 Super-L 0.800 1.010 L 0.903 CLA 1.105 Super-L 0.86 1.264 Super-L 0.704 1.044 L 0.862 SLN 1.106 Super-L 0.765 1.339 Super-L 0.701 1.038 L 0.730 P-GRP 1.782 Super-L 0.364 2.050 Super-L 0.296 1.842 Super-L 0.430 City-M (n = 73) UA 0.293 Sub-L 0.055 0.250 Sub-L 0.028 0.325 Sub-L 0.082 POP 0.900 L 0.515 0.840 Sub-L 0.375 0.943 L 0.644 CLA 0.990 L 0.668 0.959 L 0.525 0.981 L 0.737 SLN 0.848 Sub-L 0.586 0.834 Sub-L 0.475 0.847 Sub-L 0.667 P-GRP 0.662 Sub-L 0.146 0.690 Sub-L 0.132 0.616 Sub-L 0.142 Univariate regression results of urban electricity consumption in different types of cities. Table 5. Univariate regression results of urban electricity consumption in different types of cities. Table 5. Univariate regression results of urban electricity consumption in different types of citie City-I: Industrial cities; City-C: Commercial cities; City-M: Mixed-economy cities 12 / 18 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE Urban scaling characteristics of China Fig 4. Electricity consumption compositions of different types of cities. (A) The blue bars, brown bars and gray bars represent the proportions of industrial electricity, commercial electricity and other types of electricity respectively. https://doi.org/10.1371/journal.pone.0236593.g004 Fig 4. Electricity consumption compositions of different types of cities. (A) The blue bars, brown bars and gray bars represent the proportions of industrial electricity, commercial electricity and other types of electricity respectively. https://doi.org/10.1371/journal.pone.0236593.g004 https://doi.org/10.1371/journal.pone.0236593.g004 urban population. The industrial electricity consumption of industrial cities accounts for a large proportion, so that the electricity consumption of industrial cities is mainly affected by industrial development. The development of industrial cities depends on the production of industrial enterprises, which are engaged in the exploitation and processing of natural resources. For industrial cities, the increase of construction land area usually means the devel- opment of urban industry, which requires further exploitation of resources. PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE PLOS ONE Urban scaling characteristics of China Table 6. Multivariate regression results of urban electricity consumption. LN(EU) City type LN(Independent variable) b Adj- R2 Urban area Population Construction land area Street lamp number Per capita GRP City-wide EU (WSEC) City-A - 0.322 0.769 - - 0.753 City-I - 0.793 1.682 - - 0.870 City-C -0.180 0.750 0.471 - - 0.952 City-M - - 0.702 0.323 - 0.694 Industrial EU City-A - 0.582 - 0.578 - 0.599 City-I - - 2.094 - - 0.828 City-C - 1.254 - - - 0.800 City-M - - 0.644 0.352 - 0.549 Household EU City-A - 0.441 0.371 0.293 - 0.827 City-I - 1.282 - 0.669 - 0.515 City-C - 0.881 - - 0.626 0.939 City-M - - 0.657 0.360 - 0.776 City-A: All cities; City-I: Industrial cities; City-C: Commercial cities; City-M: Mixed-economy cities; EU: Electricity use; WSEC: Whole society electricity consumption; Adj-R2: Adjusted R2.  Indicates whether the urban scaling parameter value is different from 0 (p < 0.001; p < 0.01; p < 0.05;). Table 6. Multivariate regression results of urban electricity consumption. LN(Independent variable) b City-A: All cities; City-I: Industrial cities; City-C: Commercial cities; City-M: Mixed-economy cities; EU: Electricity us Adj-R2: Adjusted R2. City-A: All cities; City-I: Industrial cities; City-C: Commercial cities; City-M: Mixed-economy cities; EU: Electricity use; WSEC: Whole society electricity consumption; Adj-R2: Adjusted R2.  Indicates whether the urban scaling parameter value is different from 0 (p < 0.001; p < 0.01; p < 0.05;). https://doi.org/10.1371/journal.pone.0236593.t006 construction land area reflect the development trend of cities indirectly. The increase of urban population and construction land indicates the positive development of the urban economy and thus promotes the increase of urban electricity consumption. Street lamp number repre- sents the city’s urban infrastructure construction level. Urban infrastructure includes energy facilities, transportation facilities and communication facilities, all of which are pure consum- ers of electricity resources. More street lamps correlate with better infrastructure construction, thus street lamp numbers show positive relationships with urban electricity consumption. According to the b values in the multivariate regression models, when urban area, popula- tion and construction land area increase by 10%, the total electricity consumption of commer- cial cities will decrease by 1.80%, increase by 7.50% and increase by 4.71% respectively. When population increases by 10%, the industrial electricity consumption of commercial cities will increase by 12.54%. PLOS ONE When other parameters remain unchanged, the per capita GRP in cities will increase by 10%, and the household electricity consumption in commercial cities will increase by 6.26%. Comparing the results of the electricity consumption regression analysis between Table 5 and Table 6, there are many differences in the values of urban scale factors affecting urban electricity consumption. This indicates that the influence factors of urban electricity consump- tion are sensitive to the inclusion of other variables. On the whole, the results of multivariate regression analysis of the factors affecting urban electricity consumption are consistent with the results of univariate regression analysis. The regression results show that Chinese urban electricity consumption is mainly affected by urban population, urban construction land area, and street lamp number, while urban area and per capita GRP have little impact on electricity consumption. PLOS ONE Natural resource exploitation requires a lot of electricity. As a result, the urban electricity consumption will rise super-linearly as construction land area increases. In the process of developing from a coal mining city to a comprehensive industrial city with petroleum, iron, steel and other industries, industrial cities will further aggravate urban electricity consumption. The electricity consumption of commercial cities and mixed-economy cities reflects the impact of the urban population size effect, urban form effect and urban infrastructure effect, and is little affected by urban area and per capita GRP. The differences of the two types of cities are the R2 values of regression models. 3.2.2 Multivariate regression analysis of factors affecting urban electricity consump- tion. Table 6 shows the multivariate regression results of factors influencing the electricity consumption in Chinese third-tier-and-above cities. According to the multivariate regression results in Table 6, urban area and per capita GRP have little impact on the urban electricity consumption of commercial cities, and urban area shows a negative influence. The scaling of the urban area and the growth of urban per capita GRP reflect the rapid transformation of urban commercialization. A large number of labor- intensive urban enterprises may move their production plants to less-developed cities with abundant human resources and low labor costs. Besides, the optimization of urban electricity efficiency in more-developed cities may also alleviate the city’s electricity burden. Therefore, the scaling of the urban area and the growth of per capita GRP could slow down the increase in urban electricity consumption for commercial cities. Urban population, urban construction land area and street lamp number have significant positive influences on urban electricity consumption. The urban population and urban PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 13 / 18 https://doi.org/10.1371/journal.pone.0236593.t006 4. Conclusion In the context of 114 Chinese third-tier-and-above cities, our results show that the overall development patterns in China are consistent with the general urban scaling laws. Previous PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 14 / 18 PLOS ONE Urban scaling characteristics of China studies have rarely been conducted within Chinese cities, and our research can help readers understand the scaling characteristics of them. Urban innovation wealth indicators scale super-linearly with urban population changes, urban infrastructure indicators scale sub-line- arly with urban population changes, and urban material and energy indicators related to indi- vidual demands, except urban gas supply, scale linearly with urban population changes. The urban gas supply shows super-linear scaling with the urban population because of the rapidly increasing provision of urban natural gas transmission pipelines. In addition, the study ana- lyzed the scaling of urban development indicators with GRP which has rarely used as indepen- dent variable. The goodness of fit with urban GRP as the independent variable appears better than that with the urban population, which manifests that the urban scaling characteristics of Chinese cities could be better modeled by urban GRP. The consistency between urban scaling laws and Chinese urban scaling characteristics makes it possible for China to promote urban development by referring to the experience of other countries. In the process of expanding the size of Chinese cities, in addition to considering the needs of the urban population for various development indicators, it should also be considered that the rapid development of the urban economy will also lead to increasing requirements for various indicators. Urban economy should play a more important role in the urban planning and construction process. In the con- text of all cities in China vigorously introducing talents, it should be considered whether the city’s economy is sufficient to support the city’s sustainable development. The development of Chinese cities should be based on people and more on economy. For different types of cities, the differences between the values of scaling parameters indi- cate different development characteristics. The influence of city type on the characteristics of urban scaling has always been ignored. In industrial cities, the urban development indicators have no apparent correlation with urban population, but correlate strongly with urban GRP. Although the development of secondary industry in industrial cities can promote the develop- ment of urban GRP, it is challenging to attract talent. PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 Writing – review & editing: Xingchao Liu, Zhihong Zou. Writing – review & editing: Xingchao Liu, Zhihong Zou. Writing – review & editing: Xingchao Liu, Zhihong Zou. 4. Conclusion Also, the development of industry causes the deterioration of the ecological environment. While the Internet economy and service econ- omy are taking up a greater and greater proportion of the national economy, the traditional industrial economy seems to show more weakness. How industrial cities can balance the rela- tionships between economic development and ecological environment will be a question need- ing careful thought. For mixed-economy cities, their unclear urban attribute makes their development behave in a less straightforward way. The mixed-economy cities need to refer to the development experience of other types of cities for further development. The Chinese gov- ernment should think about the differences between different types of cities and adjust mea- sures to local conditions when making decisions on urban development. Industrial cities can properly transfer economic development centers to commercial development, and at the same time need to coordinate the relationship between the ecological environment and industrial development. Commercial cities need to pay more attention to building livable cities and attract more residents. Mixed-economy cities need clarify the center and direction of develop- ment, so as to improve the speed and quality of development. Univariate and multivariate analyses of factors influencing electricity consumption show that urban electricity consumption is mainly affected by urban population, urban construction land area and street lamp number. To reduce the cities’ electricity consumption, urban resi- dents should pay more attention to saving electricity, and more power-saving facilities should be adopted under urban infrastructure construction. In addition, urban area and per capita GRP have little impact on electricity consumption. Although the correlations are weak, increasing the per capita GRP of urban residents can still play a significant role in slowing down the increase of urban electricity consumption. To fundamentally solve the environmen- tal pollution problems of urban electricity use, cities need to rely on new technologies to PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 15 / 18 PLOS ONE Urban scaling characteristics of China improve the efficiency of urban electricity and develop cleaner energy sources such as solar energy and wind energy. In the future, further analysis on the development characteristics of China’s industrial cities could help build urban scaling models with more generality and utility. Furthermore, the impact of urban development on the biophysical environment is also worthy of further investigation. Author Contributions Author Contributions Data curation: Xingchao Liu. Methodology: Xingchao Liu. Supervision: Zhihong Zou. Writing – original draft: Xingchao L Writing – review & editing: Xingcha Author Contributions Data curation: Xingchao Liu. Methodology: Xingchao Liu. Supervision: Zhihong Zou. Writing – original draft: Xingchao Liu. Writing – review & editing: Xingchao Liu, Zhihong Zou. Data curation: Xingchao Liu. Methodology: Xingchao Liu. Supervision: Zhihong Zou. Writing – original draft: Xingchao Liu. Writing – original draft: Xingchao Liu. References Its Appl. 382, 643–649. 19. Rozenfeld H.D., Rybski D., Jr A.J., Batty M., Stanley H.E., Makse H.A., 2008. Laws of population growth. Proc. Natl. Acad. Sci. U. S. A. 105, 18702–18707. https://doi.org/10.1073/pnas.0807435105 PMID: 19033186 20. Romer P.M., 1986. Increasing Returns and Long-Run Growth. J. Polit. Econ. 94, 1002–1037. 21. Johnson M.T.J., Munshisouth J., 2017. Evolution of life in urban environments. Science (80-.). 358. 22. Bettencourt L.M.A., West G.B., 2010. A unified theory of urban living. Nature 467, 912–913. https://doi. org/10.1038/467912a PMID: 20962823 23. Bettencourt L.M.A., Lobo J., West G.B., 2008. Why are large cities faster? Universal scaling and self- similarity in urban organization and dynamics. Eur. Conf. complex Syst. 63, 285–293. 24. Arbesman S., Christakis N.A., 2011. Scaling of prosocial behavior in cities. Phys. A-statistical Mech. Its Appl. 390, 2155–2159. 25. Bettencourt L.M.A., Lobo J., Strumsky D., West G.B., 2010. Urban Scaling and Its Deviations: Reveal- ing the Structure of Wealth, Innovation and Crime across Cities. PLoS One 5. 26. Lobo J., Bettencourt L.M.A., Strumsky D., West G.B., 2013. Urban Scaling and the Production Function for Cities. PLoS One 8. 27. Bettencourt L.M.A., Lobo J., Strumsky D., 2007. Invention in the city: Increasing returns to patenting as a scaling function of metropolitan size. Res. Policy 36, 107–120. 28. Bai X., Wieczorek A.J., Kaneko S., Lisson S., Contreras A.P., 2009. Enabling sustainability transitions in Asia: the importance of vertical and horizontal linkages. Technol. Forecast. Soc. Change 76, 255– 266. 29. Guan J., Zhang J., Yan Y., 2015. The impact of multilevel networks on innovation. Res. Policy 44, 545– 559. 30. Ning L., Wang F., Li J., 2016. Urban innovation, regional externalities of foreign direct investment and industrial agglomeration: Evidence from Chinese cities. Res. Policy 45, 830–843. 31. Hodson M., Marvin S., Robinson B., Swilling M., 2012. Reshaping Urban Infrastructure: Material Flow Analysis and Transitions Analysis in an Urban Context. J. Ind. Ecol. 16, 789–800. 32. Kennedy C., Stewart I.D., Facchini A., Cersosimo I., Mele R., Chen B., et al., 2015. Energy and material flows of megacities. Proc. Natl. Acad. Sci. U. S. A. 112, 5985–5990. https://doi.org/10.1073/pnas. 1504315112 PMID: 25918371 33. Ramaswami A., Jiang D., Tong K., Zhao J., 2018. Impact of the Economic Structure of Cities on Urban Scaling Factors: Implications for Urban Material and Energy Flows in China. J. Ind. Ecol. 22, 392–405. 34. Lammer S., Gehlsen B., Helbing D., 2006. References 1. Friedmann J., 2006. Four Theses in the Study of China’s Urbanization. Int. J. Urban Reg. Res. 30, 440–451. 2. Gu C., Kesteloot C., Cook I.G., 2015. Theorising Chinese urbanisation: A multi-layered perspective. Urban Stud. 52, 2564–2580. 3. Wu H., Hao Y., Weng J.H., 2019. How does energy consumption affect China’s urbanization? New evi- dence from dynamic threshold panel models. Energy Policy 127, 24–38. 4. Yuan J., Lu Y., Ferrier R.C., Liu Z., Su H., Meng J., et al., 2018. Urbanization, rural development and environmental health in China. Environ. Dev. 28, 101–110. 5. Shen L., Cheng S., Gunson A.J., Wan H., 2005. Urbanization, sustainability and the utilization of energy and mineral resources in China. Cities 22, 287–302. 6. Van Raan A.F.J., Der Meulen G. Van, Goedhart W., 2016. Urban Scaling of Cities in the Netherlands. PLoS One 11. 7. Bettencourt L.M.A., 2013. The Origins of Scaling in Cities. Science (80-.). 340, 1438–1441. https://doi. org/10.1126/science.1235823 PMID: 23788793 8. Batty M., 2013. A Theory of City Size. Science (80-.). 340, 1418–1419. https://doi.org/10.1126/science. 1239870 PMID: 23788792 9. Batty M., 2008. The size, scale, and shape of cities. Science (80-.). 319, 769–771. https://doi.org/10. 1126/science.1151419 PMID: 18258906 10. Schiller F., 2016. Urban transitions: scaling complex cities down to human size. J. Clean. Prod. 112, 4273–4282. 11. Enquist B.J., Brown J.H., West G.B., 1998. Allometric Scaling of Plant Energetics and Population Den- sity. Nature 395, 163–165. 12. West G.B., Brown J.H., Enquist B.J., 1999. The Fourth Dimension of Life: Fractal Geometry and Allo- metric Scaling of Organisms. Science (80-.). 284, 1677–1679. https://doi.org/10.1126/science.284. 5420.1677 PMID: 10356399 13. Kleiber M., 1932. Body size and metabolism. Hilgardia 6, 315–332. 14. Kleiber M., 1947. Body size and metabolic rate. Physiol. Rev. 27, 511–41. https://doi.org/10.1152/ physrev.1947.27.4.511 PMID: 20267758 15. West G.B., Brown J.H., Enquist B.J., 1997. A General Model for the Origin of Allometric Scaling Laws in Biology. Science (80-.). 276, 122–126. https://doi.org/10.1126/science.276.5309.122 PMID: 9082983 16 / 18 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE Urban scaling characteristics of China 16. Bettencourt L.M.A., Lobo J., Helbing D., Kuhnert C., West G.B., 2007. Growth, innovation, scaling, and the pace of life in cities. Proc. Natl. Acad. Sci. U. S. A. 104, 7301–7306. https://doi.org/10.1073/pnas. 0610172104 PMID: 17438298 17. Clauset A., Shalizi C.R., Newman M.E.J., 2009. Power-Law Distributions in Empirical Data. Siam Rev. 51, 661–703. 18. Isalgue A., Coch H., Serra R., 2007. Scaling laws and the modern city. Phys. A-statistical Mech. PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 References Scaling laws in the spatial structure of urban road networks. Phys. A-statistical Mech. Its Appl. 363, 89–95. 35. Arcaute E., Hatna E., Ferguson P., Youn H., Johansson A., Batty M., 2014. Constructing cities, decon- structing scaling laws. J. R. Soc. Interface 12, 20140745. 36. Zipf G.K., 1951. Human behavior and the principle of least effort: an introduction to human ecology. Am J. Psychol. 64, 149. 37. Schwarz N., 2010. Urban form revisited—Selecting indicators for characterising European cities. Landsc. Urban Plan. 96, 29–47. 38. Oliveira E.A., Andrade S.J., Makse H.A., 2015. Large cities are less green. Sci. Rep. 4, 4235. . Oliveira E.A., Andrade S.J., Makse H.A., 2015. Large c 39. Cottineau C., Hatna E., Arcaute E., Batty M., 2017. Diverse cities or the systematic paradox of Urban Scaling Laws. Comput. Environ. Urban Syst. 63, 80–94. 40. Hewings G.J.D., 1988. Studies in Indian urban development: Edwin S. Mills and Charles M. Becker ( Oxford University Press, Oxford, for the World Bank, 1986) pp. viii+214. J. Dev. Econ. 28, 131–134. 41. Moomaw R.L., Shatter A.M., 1996. Urbanization and economic development: a bias toward large cities? J. Urban Econ. 40, 13–37. https://doi.org/10.1006/juec.1996.0021 PMID: 12292335 42. Shi K., Yang Q., Fang G., Yu B., Chen Z., Yang C., et al. 2019. Evaluating spatiotemporal patterns of urban electricity consumption within different spatial boundaries: A case study of Chongqing, China. Energy 167, 641–653. 17 / 18 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020 PLOS ONE Urban scaling characteristics of China 43. Anderson B., Lin S.X., Newing A., Bahaj A.S., James P.A.B., 2017. Electricity consumption and house- hold characteristics: implications for census-taking in a smart metered future. Comput. Environ. Urban Syst. 63, 58–67. 44. Gutierrezpedrero M.J., Tarancon M.A., Rio P. Del, Alcantara V., 2018. Analysing the drivers of the intensity of electricity consumption of non-residential sectors in Europe. Appl. Energy 211, 743–754. 45. Cai B., Zhang L., 2014. Urban CO2 emissions in China: Spatial boundary and performance comparison. Energy Policy 66, 557–567. 46. Department of Urban&Social Economic, 2017. China City Statistical Yearbook-2016. Beijng: China Statistics Press. 47. Ministry of Housing and Urban-Rural Development, 2017. China Urban Construction Statistical Year- book-2016. Beijng: China Statistics Press. 48. China National Knowledge Infrastructure, 2019. China economic and social development statistical database. 49. Nelson H.J., 1955. A Service Classification of American Cities. Econ. Geogr. 31, 189. 18 / 18 PLOS ONE | https://doi.org/10.1371/journal.pone.0236593 July 29, 2020
https://openalex.org/W4292994025
https://www.zora.uzh.ch/id/eprint/220551/1/2022_Huang_1_s2.0_S1569843222001601_main.pdf
English
null
Social media mining under the COVID-19 context: Progress, challenges, and opportunities
International journal of applied earth observation and geoinformation
2,022
cc-by
18,894
Zurich Open Repository and Archive University of Zurich University Library Strickhofstrasse 39 CH-8057 Zurich www.zora.uzh.ch Year: 2022 * Corresponding authors. E-mail addresses: xh010@uark.edu (X. Huang), s.wang6@uq.edu.au (S. Wang), mzhang2@bsu.edu (M. Zhang), tao.hu@okstate.edu (T. Hu), alexander.hohl@ geog.utah.edu (A. Hohl), bingshe@umich.edu (B. She), xigong@umn.edu (X. Gong), jianxin.li@deakin.edu.au (J. Li), xiao.liu@deakin.edu.au (X. Liu), oliver. gruebner@geo.uzh.ch (O. Gruebner), Regina.liu@live.mercer.edu (R. Liu), xiao.li@tamu.edu (X. Li), jackie.zw.liu@connect.polyu.hk (Z. Liu), xinyue.ye@tamu. edu (X. Ye), zhenlong@mailbox.sc.edu (Z. Li). Contents lists available at ScienceDirect Contents lists available at ScienceDirect A B S T R A C T Keywords: COVID-19 Pandemic Social media Big data Data mining Social media platforms allow users worldwide to create and share information, forging vast sensing networks that allow information on certain topics to be collected, stored, mined, and analyzed in a rapid manner. During the COVID-19 pandemic, extensive social media mining efforts have been undertaken to tackle COVID-19 challenges from various perspectives. This review summarizes the progress of social media data mining studies in the COVID-19 contexts and categorizes them into six major domains, including early warning and detection, human mobility monitoring, communication and information conveying, public attitudes and emotions, infodemic and misinformation, and hatred and violence. We further document essential features of publicly available COVID-19 related social media data archives that will benefit research communities in conducting replicable and repro- ducible studies. In addition, we discuss seven challenges in social media analytics associated with their potential impacts on derived COVID-19 findings, followed by our visions for the possible paths forward in regard to social media-based COVID-19 investigations. This review serves as a valuable reference that recaps social media mining efforts in COVID-19 related studies and provides future directions along which the information harnessed from social media can be used to address public health emergencies. Social media mining under the COVID-19 context: Progress, challenges, and opportunities Xiao Huang a,*, Siqin Wang b, Mengxi Zhang c, Tao Hu d,*, Alexander Hohl e, Bing She f, Xi Gong g Jianxin Li h, Xiao Liu h, Oliver Gruebner i, Regina Liu j, Xiao Li k, Zhewei Liu l, Xinyue Ye m, Zhenlong Li n a Department of Geosciences, University of Arkansas, Fayetteville, AR 72701, USA b School of Earth Environmental Sciences, University of Queensland, Brisbane, Queensland 4076, Australia c Department of Nutrition and Health Science, Ball State University, Muncie, IN 47304, USA d Department of Geography, Oklahoma State University, Stillwater, OK 74078, USA e Department of Geography, The University of Utah, Salt Lake City, UT 84112, USA f Institute for social research, University of Michigan, Ann Arbor, MI 48109, USA g Department of Geography & Environmental Studies, University of New Mexico, Albuquerque, NM 87131, USA h School of Information Technology, Deakin University, Geelong, Victoria 3220, Australia i Department of Geography, University of Zurich, Zürich CH-8006, Switzerland j Department of Biology, Mercer University, Macon, GA 31207, USA k Texas A&M Transportation Institute, Bryan, TX 77807, USA l Department of Land Surveying and Geo-informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China m Department of Landscape Architecture and Urban Planning, Texas A&M University, College Station, TX 77840, USA n Geoinformation and Big Data Research Lab, Department of Geography, University of South Carolina, Columbia, SC 29208 a Department of Geosciences, University of Arkansas, Fayetteville, AR 72701, USA b School of Earth Environmental Sciences, University of Queensland, Brisbane, Queensland 4076, Australia c Department of Nutrition and Health Science, Ball State University, Muncie, IN 47304, USA d Department of Geography, Oklahoma State University, Stillwater, OK 74078, USA e Department of Geography, The University of Utah, Salt Lake City, UT 84112, USA f Institute for social research, University of Michigan, Ann Arbor, MI 48109, USA g Department of Geography & Environmental Studies, University of New Mexico, Albuquerque, NM 87131, USA h School of Information Technology, Deakin University, Geelong, Victoria 3220, Australia i Department of Geography, University of Zurich, Zürich CH-8006, Switzerland j Department of Biology, Mercer University, Macon, GA 31207, USA k Texas A&M Transportation Institute, Bryan, TX 77807, USA l Department of Land Surveying and Geo-informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China m Department of Landscape Architecture and Urban Planning, Texas A&M University, College Station, TX 77840, USA n Geoinformation and Big Data Research Lab, Department of Geography, University of South Carolina, Columbia, SC 29208, U l Department of Land Surveying and Geo-informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China m Department of Landscape Architecture and Urban Planning, Texas A&M University, College Station, TX 77840, USA n Geoinformation and Big Data Research Lab, Department of Geography, University of South Carolina, Columbia, SC 29208, USA Available online 19 August 2022 1569-8432/© 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). https://doi.org/10.1016/j.jag.2022.102967 Received 26 March 2022; Received in revised form 17 June 2022; Accepted 5 August 2022 Available online 19 August 2022 1569-8432/© 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Received 26 March 2022; Received in revised form 17 June 2022; Accepted 5 August 2022 Available online 19 August 2022 1569-8432/© 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Social media mining under the COVID-19 context: Progress, challenges, and opportunities DOI: https://doi.org/10.1016/j.jag.2022.102967 DOI: https://doi.org/10.1016/j.jag.2022.102967 DOI: https://doi.org/10.1016/j.jag.2022.102967 Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-220551 Journal Article Published Version The following work is licensed under a Creative Commons: Attribution 4. Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-220551 Journal Article Published Version ollowing work is licensed under a Creative Commons: Attribution 4.0 International (CC BY 4.0) License. Originally published at: Huang, Xiao; Wang, Siqin; Zhang, Mengxi; Hu, Tao; Hohl, Alexander; She, Bing; Gong, Xi; Li, Jianxin; Liu, Xiao; Gruebner, Oliver; Liu, Regina; Li, Xiao; Liu, Zhewei; Ye, Xinyue; Li, Zhenlong (2022). Social media mining under the COVID-19 context: Progress, challenges, and opportunities. International Journal of Applied Earth Observation and Geoinformation, 113:102967. DOI: https://doi.org/10.1016/j.jag.2022.102967 International Journal of Applied Earth Observations and Geoinformation 113 (2022) 102967 1. Introduction there is rising democratization of health communications, which poses a sharp contrast to decades ago, when communications were predomi- nantly controlled by individuals and entities endowed with the power, money, public trust, or platforms required to drive the conversation (Schillinger et al., 2020). The emerging concepts of “Web 2.0” The COVID-19 pandemic has posed a global crisis, causing serious social, economic, and health challenges. Due to social media’s interac- tive nature and popularity amongst users throughout the pandemic, X. Huang et al. International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 (Murugesan, 2007), “Big Data” (Yang et al., 2017), and “Citizen as Sensors” (Goodchild, 2007) have greatly promoted social media as the platforms and virtual communities where users worldwide can create and share information, forming vast sensing networks that allow infor- mation in certain topics to be collected, stored, mined, and analyzed in a rapid manner (Li et al., 2021a; Ye et al., 2021; Gong and Yang, 2020). (Murugesan, 2007), “Big Data” (Yang et al., 2017), and “Citizen as Sensors” (Goodchild, 2007) have greatly promoted social media as the platforms and virtual communities where users worldwide can create and share information, forming vast sensing networks that allow infor- mation in certain topics to be collected, stored, mined, and analyzed in a rapid manner (Li et al., 2021a; Ye et al., 2021; Gong and Yang, 2020). uncertainties in sentiment and emotion acquisition; 6) bots, retweets, and skewed posting behaviors; 7) data sharing. The structure of this review is presented in Fig. 1. We believe that this review can serve as a valuable reference that recaps COVID-19 related social media mining efforts and provide potential future directions for better employing the information harnessed from social media to address future public health emergencies. Since the early stage of the COVID-19 pandemic, governments, local authorities/agencies, and organizations have started to disseminate crucial information to the public via social media platforms. In addition, we have seen a massive influx of opinions, perceptions, and attitudes towards COVID-19 related events and/or public health policies from regular users on social media platforms. If appropriately utilized, the vast amount of minable information in the social media space would allow scholars to address various aspects of COVID-19 challenges. 2.1. Early warning and detection Via a series of analytical ap- proaches, e.g., lasso regression, ridge regression, and elastic net, their study proved the feasibility of social media search indexes in predicting new suspected COVID-19 cases 6–9 days in advance (Qin et al., 2020). Similarly, Li et al. (2020a) analyzed COVID-19 related internet searches (Google and Baidu) and social media data (i.e., Sina Weibo) and demonstrated that for trend data and the number of cases, the highest correlation between these two variables occurred 8–12 days before an increase in confirmed COVID-19 cases, and the highest correlation be- tween trend data and the newly suspected cases occurred 6–8 days before the increase in newly suspected cases. The above studies, as well as other social media based early warning and detection efforts (Lu and Zhang, 2020; Mackey et al., 2020), highlight the necessity of estab- lishing social media surveillance systems that facilitate the identification of disease communication. To address these knowledge deficits, we review existing social media mining efforts related to the COVID-19 crisis, document publicly avail- able data archives, summarize social media mining challenges as well as their potential impacts on derived findings, and envision the future di- rections of social media-based COVID-19 and public health in- vestigations. Due to the strong interdisciplinarity and the fact that we specifically target data mining efforts, a systematic reviewing workflow using keywords and databases for queries fails to provide a satisfactory article pool without intensive post-selection trimming. Thus, we orga- nize this review in a narrative manner. The narrative review has been widely used to obtain a broad perspective on topics of interest. Instead of systematically searching for all relevant literature, it specifically focuses on pivotal papers known to the subject expert. The articles reviewed in this effort are purposively selected by the authors with rich experience in social media mining and who have conducted interdisciplinary COVID-19 investigations using social media data. In the following sections, we group the progress of social media data mining studies to address COVID-19 challenges into six major categories and summarize notable efforts in each category (Section 2). These six categories include 1) early warning and detection; 2) human mobility monitoring; 3) communication and information conveying; 4) public attitudes and emotions; 5) infodemic and misinformation; 6) hatred and violence. Note that the authors’ expertise and research experience well cover the identified six categories. 2.1. Early warning and detection Public health surveillance is critical for monitoring the spread of infectious diseases, rapidly detecting outbreaks, and proposing effective countermeasures. With the support of early warning signs, governments are able to better prepare for public health emergencies such as the COVID-19 pandemic. The initial hotspot of COVID-19 was reported in China before cases were reported in European countries and in the United States (U.S.), which became the new epicenter of the disease as its number of confirmed cases surpassed that of Italy’s on March 26, 2020. The rapid viral spread on a global scale demands public health authorities in many countries to develop mitigation strategies within a rapid timespan. Social media has played a crucial role in supporting traditional surveillance systems for tracking the progress of the COVID- 19 pandemic and informing the judgments and decisions of public health officials and experts (Samaras et al., 2020). The real-time infor- mation from a massive sensor network consisting of millions of social media users provides timely situational awareness that uncovers early warning signs of an upcoming hotspot of cases, greatly facilitating the estimation of disease prevalence in (near) real time. For example, Kogan et al. (2021) found that digital data sources may provide an earlier indication of the epidemic spread than traditional COVID-19 metrics, such as confirmed cases or deaths. By proposing a metric that combines six digital sources, including COVID-19 related Twitter activity, into a multiproxy estimator, their study demonstrated the potential of situational awareness that is derived from digital sources in estimating the probability of an impending COVID-19 outbreak (Kogan et al., 2021). By analyzing a multilingual dataset of tweets (i.e., English, German, French, Italian, Spanish, Polish, and Dutch posts that contain the keyword “pneumonia”), Lopreite et al. (2021) uncovered early-warning signals of the COVID-19 outbreaks in Europe during the winter season 2019–2020, before receiving the first public announce- ments of local sources of infection. This evidence suggests that European countries saw unexpected levels of concerns regarding COVID-19 cases, and whistleblowing came primarily from the geographical regions that eventually turned out to be the new COVID-19 hotspot (Lopreite et al., 2021). Qin et al. (2020) predicted the number of newly suspected or confirmed COVID-19 cases by analyzing social media search indexes for symptoms, coronavirus, and pneumonia. 1. Introduction Extensive social media mining efforts have been made to tackle COVID- 19 issues from various perspectives, including but not limited to case hotspot prediction (Li et al., 2020a), policy compliance monitoring (Huang et al., 2020), misinformation modeling (Cinelli et al., 2020), and sentimental analysis (Nemes and Kiss, 2021). Despite the existing studies, there is a lack of review work that cohesively summarizes the current findings in the COVID-19 context. Tsao et al. (2021) examined 81 peer-reviewed empirical studies relating to COVID-19 and social media published between November 2019 and November 2020. Their review predominantly targeted the early stage of the pandemic; there- fore, it did not capture the major milestones amidst the middle and later stages of the pandemic after the mass vaccination. Other reviews related to social media and public health more broadly merely describe the general functionality and utility of social media in public health appli- cations but lack the focus on social media analytics that are derived via data mining efforts (Giustini et al., 2018; Grajales III et al., 2014; Moorhead et al., 2013). Additionally, these reviews gave scarce atten- tion to the challenges present in different domains of COVID-19 related studies (e.g., Asian hate, lockdown debate, and vaccination prefer- ences)—prevalently discussed on social media platforms. i 2.2. Human mobility monitoring et al., 2021; Zeng et al., 2021) and Australia (Nguyen et al., 2020a). et al., 2021; Zeng et al., 2021) and Australia (Nguyen et al., 2020a). , ; g , g y , Facebook is another popular social media platform with a large global user base. Beginning in the initial phases of the COVID-19 pandemic, Facebook Data for Good began to provide human mobility information to assist with pandemic mitigation. For example, Chang et al. (2021) explored Facebook-derived movement patterns and used meta-population models to assess the potential effects of local travel restrictions imposed within Taiwan. Zachreson et al. (2021) used Facebook mobility data to estimate future spatial patterns of relative transmission risk and examine the degree to which these estimates correlate with observed cases in Australia. Besides these two efforts, Facebook mobility records were employed for mobility monitoring at a continental scale, as well as at a country/sub-country scale, e.g., the U.S. (Holtz et al., 2020; Ilin et al., 2021), the U.K. (Shepherd et al., 2021), Italy (Beria and Lunkar, 2020; Bonaccorsi et al., 2020), Spain (P´erez- Arnal et al., 2021), Japan (Fraser and Aldrich, 2020), Germany (Fritz and Kauermann, 2020), Demark (Edsberg Møllgaard et al., 2022), and Australia (Zachreson et al., 2021). The COVID-19 pandemic highlights the importance of rapid human mobility monitoring. User-generated information from social media platforms (e.g., Twitter, Facebook, Sina Weibo, and Instagram), when coupled with geo-information (i.e., geograohic coordinates and infor- mation on place names), allows human–human, human-place, and place-place interactions to be monitored in an active and less privacy- concerning manner (Huang et al., 2020; Li et al., 2021a), thus serving as an important venue where timely human mobility dynamics can be collected and analyzed to assist with decision making. Despite the ex- istence of many social media platforms, only a small proportion of them permit information mining or open-source aggregated mobility records for researchers and the public, while for some social media platforms (e. g., Facebook and Sina Weibo), certain agreements have to be met to access to the records. Below, we review notable efforts that address COVID-19 challenges by monitoring human mobility dynamics via geotagged social media data. With several categories of publicly available application program- ming interfaces (APIs), Twitter has become the most popular social media platform that allows geographic data mining. These APIs return certain percentages of their total content, with some of them containing geo-information at various levels. 2.1. Early warning and detection We further document essential fea- tures of publicly available COVID-19 social media data archives that will benefit research communities in conducting replicable and reproducible studies (Section 3). In addition, we discuss seven challenges in social media analytics associated with their potential impacts on derived COVID-19 findings, followed by our visions for the possible paths for- ward in regard to social media-based COVID-19 investigations (Section 4). These challenges include 1) biased population spectrum; 2) multi- lingual investigations; 3) posting incentives; 4) positioning accuracy; 5) 2 International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 X. Huang et al. International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 X. Huang et al. Fig. 1. The structure of this review. Fig. 1. The structure of this review. 2.3. Communication and information conveying 2.3. Communication and information conveying 2.3. Communication and information conveying Social media platforms are not only popular among individual users for user/news following, microblogging, and content sharing (Gong and Yang, 2020; Kietzmann et al., 2011) but have also become crucial tools for institutions (such as governments, organizations, and universities, etc.) to disseminate information, foster connections, and even manage crises (Gong and Lane, 2020; Kelly, 2013; Kostkova et al., 2014). Crisis communication refers to the sharing of information among individuals and institutions to improve crisis management and understanding (Na- tional Research Council, 1989). Crisis communication has been resha- ped by social media in numerous ways, including raising public awareness through collaboration and participation, distributing infor- mation and instructions in real time, and monitoring and managing risks with greater efficiency (Olteanu et al., 2015; Reuter et al., 2016; Yoo, 2019). In spite of the virtual nature of social media interactions, the spatial social networks they have formed still reflect the geography of communication (Ye and Andris, 2021). Human interactions in real life and in cyberspace are similar in terms of their social, economic, cultural, and linguistic constraints; thus, spatial social networks tend to mimic real-life patterns (Bild et al., 2015; Stephens and Poorthuis, 2015). Many studies have used social media data to examine crisis communication under the COVID-19 context from a geographic and social network perspective. The majority of the COVID-19 crisis communication research focused on governmental agencies, but some also examined other public health stakeholders, such as non-governmental organiza- tions (NGOs), educational organizations, and the public. strategies. The pandemic has spawned a wealth of complex problems, such as healthcare resource shortages, economic recession, mental health issues, and other social problems, all of which are difficult to resolve by gov- ernments alone. Therefore, it is imperative for public health stake- holders, NGOs, education institutions, and the general public to collaborate with government agencies within and across boundaries to address problems collectively (Head and Alford, 2015; Li et al., 2021b; Roberts, 2000; Weber and Khademian, 2008). After examining the evolution of Twitter-based networks and discourse across 2,588 U.S. NGOs in the first five months of the COVID-19 outbreak, Li et al. (2021b) discovered that social media usage helped NGOs to connect with each other by removing geographical barriers and specialty constraints. Over time, distinct organizational communities emerged around different topics, mostly reflecting theoretical predictions based on Issue Niche Theory (Yang, 2020). 2.3. Communication and information conveying All of these findings provide unprecedented insight into how different public health stakeholders are working collaboratively to combat the pandemic, which can help the entire society prepare for the implantation of crisis communication strategies in anticipation of future global hazards The pandemic has spawned a wealth of complex problems, such as healthcare resource shortages, economic recession, mental health issues, and other social problems, all of which are difficult to resolve by gov- ernments alone. Therefore, it is imperative for public health stake- holders, NGOs, education institutions, and the general public to collaborate with government agencies within and across boundaries to address problems collectively (Head and Alford, 2015; Li et al., 2021b; Roberts, 2000; Weber and Khademian, 2008). After examining the evolution of Twitter-based networks and discourse across 2,588 U.S. NGOs in the first five months of the COVID-19 outbreak, Li et al. (2021b) As the COVID-19 crisis unfolds, government organizations at different levels must act quickly to communicate crisis information to the public in an efficient and effective manner; failure to do so could lead to an increase in fear, uncertainty, and anxiety among the public (Chen et al., 2020b). Based on spatial–temporal analyses, network analyses, and text mining of the U.S. state governors’ crisis communication on Twitter during the pandemic, Gong and Ye (2021) found that the current usage patterns are generally consistent with effective crisis communi- cation principles (listening, informing, providing feedback, and estab- lishing connections) and provided some concrete recommendations for improving the process. One qualitative analysis of how world leaders of the Group of Seven (G7) communicated about the COVID-19 pandemic indicated that 82% of their tweets were informative; many of them dealt with government resources, morale boosting, and political issues (Rufai and Bunce, 2020). According to Zhu et al. (2020), the analysis of Sina Weibo posts related to COVID-19 confirmed that early warnings of crises are vital because public attention to COVID-19 was relatively limited until the Chinese government acknowledged that the novel coronavirus could be transmitted between humans and designated control of the outbreak as a high priority on January 20, 2020. Through analyzing tweets from 292 federal members of the Canadian parliament, Merkley et al. (2020) reported a moment of cross-party consensus on COVID-19 communication. No matter which party the members were from, they emphasized social distancing and proper hand hygiene as a necessity for combatting the COVID-19 pandemic (Merkley et al., 2020). 2.2. Human mobility monitoring However, limitations such as the necessity for users needing pre-existing incentives to make posts and varying positioning accuracy need to be recognized (discussed 3 3 in Section 4.1). X. Huang et al. X. Huang et al. X. Huang et al. International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 in Section 4.1). longitudinal COVID-19 risk communication shifted as secondary threats emerged. In addition, there are studies addressing the best practices in COVID-19 crisis communication on social media. Government agencies can improve public engagement and crisis communication efficiency on social media by leveraging narrative evidence (Gesser-Edelsburg, 2021; Ngai et al., 2020), adopting an empathic communication style (Liao et al., 2020), actively using the dialogic loop rather than media richness (Chen et al., 2020b), and joining forces with leading scientists from various domains (Tsoy et al., 2021) to generate persuasive and potent content. These findings may help government agencies to create communication plans for future crises and assist the public in under- standing, preparing for, and predicting governments’ response strategies. 2.2. Human mobility monitoring Studies have found that the Twitter- derived mobility patterns can approximate commuting patterns (Petutschnig et al., 2021) as well as mobility records released by Apple, Google, and Descartes Labs (Huang et al., 2021). Using 580 million geotagged tweets collected worldwide, Huang et al. (2020) measured human mobility by proposing the concept of single-day distance and cross-day distance, which highlight the users’ daily travel behavior and the users’ displacement between two consecutive days, respectively. Their investigations, conducted at various scales (i.e., global, country, and U.S. states), suggest that Twitter-derived mobility dynamics are amenable to reflect the geographical differences in policy implementa- tions and discrepancies with policy compliance. Notably, Xu et al. (2020) proposed and utilized a Twitter Social Mobility Index, which measures social distancing and travel derived from geotagged Twitter posts, to analyze U.S. weekly travel patterns. Similar efforts were made to monitor global human mobility dynamics (Bisanzio et al., 2020; Lai et al., 2021; Li et al., 2021c; Li et al., 2021d) as well as country/region- specific dynamics where Twitter is widely used, such as the U.S. (Jiang Several other social media platforms were harnessed to address COVID-19 challenges as well, such as U.S.’ Instagram and China’s Tencent and Sina Weibo. Zarei et al. (2020) constructed the first Insta- gram dataset, which featured COVID-19 related posts with locational information. Using Tencent’s mobility data derived from Tencent’s media various platforms, Li et al. (2020d) revealed daily human movement patterns in Sichuan, China (which covers the mobility of 90% of Sichuan citizens) during the initial stages of the COVID-19 outbreak, and Wei et al. (2021) evaluated how people in Wuhan, China reduced their mobility in response to city lockdowns. Another Chinese social media platform, Sina Weibo, also renders geotagged posts that allow researchers to mine the spatiotemporal patterns of human interactions and place visitations (Peng et al., 2020). Social media platforms have proven to be one of the most vital sources of mobility data, enabling researchers to obtain critical insight into human mobility amidst COVID-19. Due to their active sharing characteristics, social media mobility records are less abundant compared to other passively collected records (e.g., mobile phone data, smart cards, or wireless networks), though they are less intrusive, more accessible, and more harmonized (Li et al., 2021c). 2.3. Communication and information conveying The interactions and connections among NGOs and government agencies during the COVID-19 pandemic are well re- flected on social media platforms, reflecting their goals to share infor- mation, build communities, and take action for disaster response. The government agencies played a leading role in the NGO-government collaborations, while NGOs from the Human Services, International and Foreign Affairs, and Public and Societal Benefit sectors, especially the American Red Cross, played a more central role in the NGO collaboration network. The study of social media usage by 189 Greek libraries during the pandemic revealed that although libraries embraced social media quickly as a channel for communication, only a few high- lighted their roles in the promotion of public health by providing timely and reliable information (Koulouris et al., 2020). The COVID-19 pandemic has forced all educational institutions to move from face-to- face to online instruction. Students in higher education use social media primarily to build an online community and to support one another, whereas faculty members use it exclusively for teaching and learning (Sobaih et al., 2020). Based on analyses of tweets from 492 U.S. K-12 school districts in March-April 2020, Michela et al. (2022) found that these districts followed recommendations for social media crisis communication by posting more announcements and engaging more collaboratively during the early pandemic phases, and by sharing more community-building contents later. Crisis communication among the general public is also crucial to disaster response. Yu et al. (2021) analyzed 10,132 COVID-19 related online comments on TripAdvisor and discovered a dynamic shift in risk perceptions and communication in- tensities among the general public as a result of the pandemic’s rapid and unpredictable spread. During the COVID-19 pandemic, many in- stances of stereotyping and discrimination toward Asian Americans and the elderly population have been posted on social media, many of which are associated with stigmatizing and blaming these populations (Croucher et al., 2020; Meisner, 2021). Meisner (2021) urged the public to be aware of and to resist ageism that devalues later life in crisis communication. 2.4. Public attitudes and emotions The advanced AI models include the Valence Aware Dictionary for sEntiment Reasoning (VADER) (Wang et al., 2022) and the National Research Council Canada Lexicon model (NRCLex) (Hu et al., 2021), both of which target English-based contents, as well as the XLM-R or XLM-T model (Conneau et al., 2019; Imran et al., 2022) and the Hugging Face (Barbieri et al., 2021), which targets multilingual contents. More nuanced reviews and surveys of the models and algorithms used in sentiment analysis can be found in Alsaeedi and Khan (Alsaeedi and Khan, 2019) and Medhat et al. (2014). Social media generates a massive amount of information related to the COVID-19 pandemic every day, and manual identification of misinformation is time- and labor-consuming. As an alternative solution, advanced machine learning techniques have been deployed to detect misinformation automatically. The accuracy of misinformation detec- tion models relies on sufficient and reliable datasets. Thus, many efforts have been made to provide high-quality social media misinformation datasets. Researchers collected ground-truth data from fact-checking websites (Ceron et al., 2021; Saakyan et al., 2021; Shahi and Nandini, 2020) and reliable websites (Cui and Lee, 2020; Zhou et al., 2020) for the misinformation detection task. Specifically, FakeCovid (Shahi and Nandini, 2020) is a multilingual cross-domain fact-check news dataset that contains 5,182 articles circulated in 105 countries (40 languages) from 92 fact-checkers. CoAid is a healthcare domain dataset containing 4,521 true news articles and claims from reliable media outlets (e.g., Healthline, ScienceDaily, and WHO) (Cui and Lee, 2020). CoAid collects fake news by retrieving URLs from multiple fact-checking websites such as LeadStories, PolitiFact, and FactCheck. ReCOVery is a multimodal repository for COVID-19 news credibility research, which contains 1,364 news articles from 22 reliable websites (e.g., National Public Radio and Reuters) and 665 news articles from 38 unreliable websites (e. g., Human Are Free and Natural News). Empirically, sentiment-based studies that employ social media data were typically used to evaluate the public’s attitudes and sentiments towards COVID-19 related policy implementations, including mask- wearing, economic support, and school closure (Ewing and Vu, 2021; Kwok et al., 2021; Manguri et al., 2020; Niu et al., 2021). Others have investigated the public’s opinion and awareness of COVID-19 related events (e.g., protests against lockdown, vaccination, and university reopening) and speeches/comments of political leaders (e.g., Donald Trump) (Hu et al., 2021; Jang et al., 2021). Current studies have been conducted in several countries such as the U.S. 2.4. Public attitudes and emotions 2.4. Public attitudes and emotions period of disease outbreak, there exists a vast amount of information that is false or misleading in nature and is present in physical and digital environments. During the COVID-19 crisis, misinformation can spread faster and farther on social media platforms than the virus itself. Ac- cording to a Reuters report, the number of English-language fact-checks rose more than 900% from January to March 2020 (Brennen et al., 2020). This information covers a wide range of topics, e.g., “5G virus is true”, “eating garlic can prevent coronavirus”, and “Bill Gates is plan- ning to microchip the world through a COVID-19 vaccine”. Such misinformation and the resulting risk-taking behaviors can lead to mistrust in health authorities and undermine public health response. In light of this context, scholars around the world have started to investi- gate misinformation spread on social media platforms. The COVID-19 pandemic has led to a major uprise in studies that apply sentiment analysis towards social media platforms’ text-based content in order to gauge the public’s attitude and sentiment revolving both the pandemic and related categories, such as public health policies (e.g., mask-wearing) and/or events (e.g., vaccination) (Ewing and Vu, 2021; Kwok et al., 2021; Manguri et al., 2020). Senti- ment analysis is thought to enable the derivation of the users’ emotional response to a particular event or phenomena via the text-based contents that they post (e.g., words, expressions, languages, and syntaxes) (Agarwal et al., 2011; Kouloumpis et al., 2011). Moreover, social media- based sentiment studies have also been used to indicate the public’s awareness, opinions, or mental health signals based on the quantifica- tion and intensity of sentiments (e.g., positive V.S. negative, or opti- mistic V.S. pessimistic) and the type of emotions (e.g., fear, sadness, joy, and surprise) (Coppersmith et al., 2014). Such studies are further able to supplement survey-based mental health assessments, enabling re- searchers to mitigate issues such as a limited data pool (e.g., limited spatial and temporal data coverage, data under-representativeness) (Balcombe and De Leo, 2020). Sentiment research that seeks to quan- tify sentiments via social media data typically relies on advanced measuring techniques, including artificial intelligence (AI) models and machine and/or deep learning algorithms (Ewing and Vu, 2021; Hu et al., 2021; Kwok et al., 2021; Wang et al., 2020a; Wang et al., 2022). 2.4. Public attitudes and emotions (Jang et al., 2021; Lyu et al., 2021), the U.K. (Cheng et al., 2021; Rahman and Islam, 2022), Australia (Ewing and Vu, 2021; Wang et al., 2022), India (Barkur and Vibha, 2020), China (Li et al., 2020a; Wang et al., 2020a), Europe (Kruspe et al., 2020), as well as across multiple countries (Boon-Itt and Skunkan, 2020; Matoˇsevi´c and Bevanda, 2020; Rowe et al., 2021). Existing studies focus predominantly on solely English-based content, while a smaller proportion uses either content that is in Chinese and retrieved from Weibo (the largest social media platform in China) (Li et al., 2020a; Wang et al., 2020a) or non-verbal content (e.g., emoticons) (Yamamoto et al., 2014); scarce attention has been allotted to sentiment analysis involving multilingual content (discussed in Section 4.1.2). Another research direction is to collect misinformation-related posts from social media users to explore user engagement (Cui and Lee, 2020; Kim et al., 2021; Li et al., 2020c) and public opinion (Gupta et al., 2020; Wang et al., 2020b; Xue et al., 2020; Yin et al., 2020). Misinformation detection is essentially a classification task. The common workflow is to develop a dataset with true and false labels for model training, adjust the model based on the results of the test set, and apply it to unknown data in order to generate predictions. Machine learning (ML) and deep learning (DL) models have been widely used for misinformation detec- tion (Alenezi and Alqenaei, 2021; Elhadad et al., 2020; Gundapu and Mamidi, 2021; Kar et al., 2020; Koirala, 2020). Traditional ML models, such as decision trees, support vector machines, and logistic regression, usually serve as baseline models in fake news detection model experi- ments. Al-Rakhami and Al-Amri (2020) proposed an ensemble frame- work for misinformation detection by using traditional ML and conducting extensive experiments on a self-collected Twitter dataset. Their work demonstrates that a combination of models outperforms a single model. For DL models, a variety of models have been used to address the COVID-19 misinformation identification challenge, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Bidirectional Encoder Representations from Transformers (BERT) (Al-Rakhami and Al-Amri, 2020), to list a few. Alkhalifa et al. (2020) introduced a CNN-based classification system with different preprocessing and embedding methods to classify COVID- 19 rumors. An ensemble deep learning technique that was implemented to detect misleading information for COVID-19 had achieved satisfac- tory performance (Elhadad et al., 2020). 2.4. Public attitudes and emotions Other two advanced models, i. e., BiLSTM (Boukouvalas et al., 2020; Dharawat et al., 2020; Hossain et al., 2020; Kumar et al., 2021) and BiGRU (Cui and Lee, 2020; Elhadad et al., 2020), have also been widely adopted in recognizing misinfor- mation on social media. The recent development of BERT has pushed 2.3. Communication and information conveying Wang, Hao, and Platt (2021) analyzed 13,598 COVID-19-relevant tweets from 67 U. S. federal and state-level government agencies from January to April 2020. They identified inconsistencies and incongruities in four crucial prevention topics and found that communications coordination increased over time. Using tweets from Texas-based public health agencies, Liu, Xu, and John (2021) examined interagency coordination at different stages of the pandemic. In addition to stage-specific varia- tions in peer-to-peer and federal-to-local coordination, they also observed consistency in content across stages, i.e., state and federal agencies acting as agenda setters (Liu et al., 2021). Studying 138,546 tweets from 696 public health agency accounts from February 1 to March 31, 2020, Sutton, Renshaw, and Butts (2020) observed that 4 X. Huang et al. X. Huang et al. International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 3.1. Social networks Twitter plays a significant role in featuring COVID-19 related research, and its original data includes user information, content, post time, and more. However, due to privacy concerns, the publication of personal Twitter data is not permissible. Therefore, after collecting COVID-19 related tweets, many researchers publicly share Twitter IDs to allow ease of access. With these Twitter IDs, users can hydrate tweets and access original information via the Twitter API. For example, Chen et al. (2020a) used Twitter’s search API to gather global wide historical COVID-19 related Tweets based on the keywords (i.e., Coronavirus, Koronavirus, Corona, covid-19, and N95) dating back to January 21, 2020. Their team has shared their repository, which contains an ongoing collection of tweet IDs. So far, it is the most popular Twitter dataset cited by researchers across the world. q In response to the rapid dissemination of such malicious content, the scientific community has responded with a series of actions that are of similar fervor: for instance, annotated tweet datasets for the detection of racism and sexism were readily available before the pandemic (David- son et al., 2017; Waseem and Hovy, 2016) in many languages other than English, i.e., a dataset of Spanish tweets for misogyny detection (Fersini et al., 2018), an Arabic dataset for detection of hate speech and fake news (Ameur and Aliane, 2021), and an annotated dataset of abusive language in German (Wich et al., 2021). Early work on social media mining during COVID-19 established the theoretical groundwork for detecting hate speech on social media by using keyword-based classi- fiers. Nguyen et al. (2020b) found evidence of increased negative sentiment towards Asians associated with the “#chinesevirus” hashtag in early 2020 (Nguyen et al., 2020b). Anti-Chinese and anti-Asian at- tacks on social media platforms were mainly targeting eating habits, hygiene, and in general, culture (Stechemesser et al., 2020). Lastly, exploratory work during the early stages of the pandemic includes the application of space–time scan statistics (Kulldorff, 1997) to assess the spatiotemporal distribution of geotagged tweets regarding Asian hate (Hohl et al., 2022). Although the act of sharing raw Twitter data is restricted, many re- searchers share their findings with the public via advanced approaches, such as releasing their findings regarding the sentiment, emotions, and topics of users’ tweets. For example, Lopez and Caleb (2021) collected over 2.2 billion tweets across the globe in multiple languages. 2.6. Hatred and violence In the past two years, we have witnessed a tremendous surge in the use of social media platforms during the COVID-19 pandemic to study misinformation, public opinion, human behavior, infodemic, and more. Social media platforms can be categorized as social networks (e.g., Twitter, Sina Weibo, and Facebook), media sharing networks (e.g., YouTube), and discussion forums (e.g., Reddit). However, limited social media datasets are shared with the public, hindering collaborative research and increasing the crisis of research reproducibility and repli- cability. As a result, this section summarizes and compares the most popular and publicly available social media datasets in terms of geo- location, content, advanced data analytics, geographic coverage, time coverage, and selected citations, as shown in Table 1. Since the first confirmed case of COVID-19 in the U.S. on January 19, 2020 (Hossain et al., 2020), hateful and xenophobic language has surged on social media. This was quickly followed by prejudice and discrimi- natory acts against minorities, particularly the Asian and Asian Amer- ican population (Croucher et al., 2020; Fan et al., 2020). Notably, during the period of March 19, 2020, to September 30, 2021, the Stop AAPI (Asian American and Pacific Islander) Hate reporting center recorded a total of 10,370 hate incidents against Asians and Asian Americans (Horse et al., 2021). Today, racism is recognized as a public health threat by the American Medical Association, as the connection between hateful social media posts and offline racially and religiously aggravated crime has previously been documented (Williams et al., 2020). Moreover, for both traditional media and social media, the spread of hate during COVID-19 on such platforms results in potentially negative effects on population health, and such an observation has also been previously recorded (Gao et al., 2020a; Quintero Johnson et al., 2021). Malicious content like racism and disinformation is spreading quickly beyond the control of individual social media platforms, thereby subverting their efforts to moderate content (Velasquez et al., 2021). 2.5. Infodemic and misinformation With the rapid dispersion of COVID-19, a tsunami of related infor- mation rushed across the internet. Yet, such information remains unfiltered, and many contain misinformation, rumors, and conspiracy theories. On this influx of information, the World Health Organization’s (WHO) Director, General Tedros proclaimed, “We’re not just fighting an epidemic; we’re fighting an infodemic”. Thus, on February 15, 2020, at the Munich Security Conference, Tedros officially coined this phenom- enon as the “Infodemic”, which describes a situation where, during a 5 X. Huang et al. International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 natural language processing to a new level, thanks to its capability in capturing both left and right contexts, given its bidirectional design. Some BERT variants were adopted for COVID-19 misinformation detection (Alkhalifa et al., 2020; Glazkova et al., 2021; Heidari et al., 2021; Perrio and Madabushi, 2020; Tziafas et al., 2021). The multilin- gual BERT (mBERT) is a notable variant trained on Wikipedia andcon- siders a total of 104 languages. COVID-Twitter-BERT was trained on the 160 million COVID-19 related corpus on the Crowdbreaks platform and performed very well on many textual representations related to COVID- 19 (Müller et al., 2020). speech detection (e.g., labeled social media posts) were circumvented through the usage of unsupervised progressive domain adaptation based on a deep-learning language model (Bashar et al., 2021). Lastly, efforts to analyze the effects of content moderation policies on the propagation of malicious posts (within social media platforms) using mathematical models produced encouraging results, accompanied by actionable sug- gestions towards slowing the spread of online hate (Velasquez et al., 2021). 3.1. Social networks Addi- tionally, they employed state-of-art algorithms to analyze sentiment and recognize named entities in Twitter content. Such aggregated informa- tion facilitates the researchers’ exploration and hypothesis testing on social discourse regarding the COVID-19 pandemic (Lopez and Galle- more, 2021). Locations and medical emergencies are intrinsically linked. Geo- tagged tweets are able to provide real-time information about human activities at a low cost and high spatial and temporal resolutions. They also enable researchers to, using geography as a common variable, join attributes across various datasets (e.g., sociodemographic) (Hu and Wang, 2020). Due to this advantage, Qazi et al. (2020) released the GeoCoV19 dataset, which contains around 378,000 geotagged tweets and 5.4 million tweets with locational information at the country, state, and city levels. Further, Lamsal (2021)’s publication of tweet IDs enabled individuals who hydrate these IDs access to the geotagged datasets. Other studies, though aspatial, have focused on identifying anti- Asian hate and counterspeech on social media via using BERT (He et al., 2021). BERT was used to identify hate-related keywords that targeted older people during the pandemic (Vishwamitra et al., 2020) and fine-tuned to analyze COVID-19 content on Twitter (Müller et al., 2020). This approach utilizes word embeddings in conjunction with machine learning to classify tweets, therefore providing an advantage over the keyword-based classifiers’ method of incorporating word context. Such a method was used for analyzing the dehumanization towards LGBTQ people in articles in the New York Times (Mendelsohn et al., 2020). Further, crowdsourcing and ensemble learning algorithms were utilized to detect hate on social media in Germany (Garland et al., 2020, 2022). Amidst sudden changes during the early stages of the pandemic, issues with obtaining costly training data regarding hate Sina Weibo, commonly referred to as the “Chinese Twitter”, is the leading social media platform in China, with 497 million active monthly users in 2019 (Fu and Zhu, 2020). Given that China was the earliest country to report COVID-19 outbreaks, many researchers have shared and utilized datasets from Sina Weibo to analyze misinformation. For example, Leng et al. (2020) crawled Sina Weibo posts via Weibo API 6 X. Huang et al. X. Huang et al. from December 7, 2019, to April 4, 2020, and shared the datasets on Harvard Dataverse. Fu and Zhu (2020) collected 11,362,502 posts be- tween December 1, 2019, and February 27, 2020, which contains at recommended videos, can be collected through the YouTube Data API. 3.1. Social networks Fu and Zhu (2020) collected 11,362,502 posts be- tween December 1, 2019, and February 27, 2020, which contains at least one outbreak-related keyword (e.g., mask, virus, or coronavirus). from December 7, 2019, to April 4, 2020, and shared the datasets on Harvard Dataverse. Fu and Zhu (2020) collected 11,362,502 posts be- tween December 1, 2019, and February 27, 2020, which contains at least one outbreak-related keyword (e.g., mask, virus, or coronavirus). recommended videos, can be collected through the YouTube Data API. For example, Papadamou et al. (2020) collected COVID-related videos and recommendations through the API to analyze the effect of a user’s watch history on video recommendations. Notably, YouTube has also served as a source of COVID-19 misinformation (Allington et al., 2021). These videos are often linked by content on other social media sites, including Reddit, Twitter, and Facebook. Knuutila et al. (2021) dis- played a dataset of COVID-related video identifiers that were removed by YouTube, though the video’s metadata were recovered through archive.org’s Wayback Machine. Researchers have also actively studied the content of YouTube videos, as it could be both useful as a source of information (D’Souza et al., 2020) and play a role in spreading recommended videos, can be collected through the YouTube Data API. For example, Papadamou et al. (2020) collected COVID-related videos and recommendations through the API to analyze the effect of a user’s watch history on video recommendations. Notably, YouTube has also served as a source of COVID-19 misinformation (Allington et al., 2021). These videos are often linked by content on other social media sites, including Reddit, Twitter, and Facebook. Knuutila et al. (2021) dis- played a dataset of COVID-related video identifiers that were removed by YouTube, though the video’s metadata were recovered through archive.org’s Wayback Machine. Researchers have also actively studied the content of YouTube videos, as it could be both useful as a source of information (D’Souza et al., 2020) and play a role in spreading 3.1. Social networks For example, Papadamou et al. (2020) collected COVID-related videos and recommendations through the API to analyze the effect of a user’s Public available COVID-19 related social media datasets. 3.1. Social networks Data Provider Dataset Name Geolocation Included ID Only Text Advanced Analysis/ secondary data Geographic Coverage Temporal Coverage Publication Twitter COVID-19 Twitter Dataset with Latent Topics, Sentiments and Emotions No No No Sentiment and emotion Global/country 1/28/2020 – 9/1/2021 (Gupta et al., 2020) COVID-19-TweetIDs No Yes No No Global 01/21/ 2020–02/11/ 2022 (Chen et al., 2020a) Coronavirus (COVID-19) tweets dataset No No No Sentiment Global 03/20/ 2020–02/12/ 2022 (Lamsal, 2021) Coronavirus geo-tagged tweets datasets Yes No No Sentiment Global 03/20/ 2020–02/12/ 2022 (Lamsal, 2021) Covid-19 Twitter chatter dataset for scientific use No Yes No No Global/country 03/22/ 2020–02/12/ 2022 (Banda et al., 2021) CoronaVis: A Real-time COVID- 19 Tweets Analyzer No Yes No No Global 03/05/ 2020–12/31/ 2020 (Kabir and Madria, 2020) An Augmented Multilingual Twitter dataset for studying the COVID-19 infodemic Yes No No Sentiment, entity recognition, mentions, and hashtags Global/Country 01/01/ 2020–12/31/ 2021 (Lopez and Gallemore, 2021) GeoCoV19: A Dataset of Hundreds of Millions of Multilingual COVID-19 Tweets with Location Information Yes No No Sentiment and entity recognition Global/location 02/01/ 2020–03/31/ 2022 (Qazi et al., 2020) COVID-19 Twitter Dataset No Yes No No Global 04/01/ 2020–09/31/ 2020 (Gruzd and Mai, 2020) Preliminary Extraction from Geotweet Archive v2.0 for COVID-19 Tweets Yes Yes No No Global/location 03/01/ 2020–04/30/ 2020 Sina Weibo Weibo COVID dataset No No Yes No China 12/07/ 2020–04/04/ 2020 (Leng et al., 2020) COVID-19 related Weibo Data No No Yes No China 12/01/ 2019–02/27/ 2020 (Fu and Zhu, 2020) Reddit Reddit Mental Health Dataset No No Yes Sentiment and emotion 28 mental health and non- mental health subreddits 01/01/ 2018–01/01/ 2020 Coronavirus subreddit No No Yes Sentiment and topic modeling r/Coronavirus subreddit 01/20/ 2020–01/31/ 2021 The Reddit COVID dataset No Yes Sentiment posts and comments mentioning COVID in their title and body text N/A- 25/10/ 2021 (Tan, 2021) Youtube YouTube’s Pseudoscientific Video Recommendations No No Yes No Search terms: ’covid-19′, ’coronavirus’, ’anti- vaccination’, ’anti-vaxx’, ’anti-mask’, or ’flat earth’ (Papadamou et al., 2020) Covid-related misinformation videos No Yes No No Global 11/ 012019–06/ 30/2020 Instagram COVID19 Instagram Post IDs No Yes No No Global 01/05/ 2020–3/30/ 2020 (Zarei et al., 2020) ID Only Text Advanced Analysis/ secondary data Geographic Coverage Temporal Coverage Publication No No Sentiment and emotion Global/country 1/28/2020 – 9/1/2021 (Gupta et al., 2020) Yes No No Global 01/21/ 2020–02/11/ 2022 (Chen et al., 2020a) No No Sentiment Global 03/20/ 2020–02/12/ 2022 (Lamsal, 2021) No No Sentiment Global 03/20/ 2020–02/12/ 2022 (Lamsal, 2021) Yes No No Global/country 03/22/ 2020–02/12/ 2022 (Banda et al., 2021) Yes No No Global 03/05/ 2020–12/31/ 2020 (Kabir and Madria, 2020) No No Sentiment, entity recognition, mentions, and hashtags Global/Country 01/01/ 2020–12/31/ 2021 (Lopez and Gallemore, 2021) No No Sentiment and entity recognition Global/location 02/01/ 2020–03/31/ 2022 (Qazi et al., 2020) Yes No No Global 04/01/ 2020–09/31/ 2020 (Gruzd and Mai, 2020) Yes No No Global/location 03/01/ 2020–04/30/ 2020 No Yes No China 12/07/ 2020–04/04/ 2020 (Leng et al., 2020) No Yes No China 12/01/ 2019–02/27/ 2020 (Fu and Zhu, 2020) No Yes Sentiment and emotion 28 mental health and non- mental health subreddits 01/01/ 2018–01/01/ 2020 No Yes Sentiment and topic modeling r/Coronavirus subreddit 01/20/ 2020–01/31/ 2021 No Yes Sentiment posts and comments mentioning COVID in their title and body text N/A- 25/10/ 2021 (Tan, 2021) No Yes No Search terms: ’covid-19′, ’coronavirus’, ’anti- vaccination’, ’anti-vaxx’, ’anti-mask’, or ’flat earth’ (Papadamou et al., 2020) Yes No No Global 11/ 012019–06/ 30/2020 Yes No No Global 01/05/ 2020–3/30/ 2020 (Zarei et al., 2020) from December 7, 2019, to April 4, 2020, and shared the datasets on Harvard Dataverse. 4.1.2. Multilingual investigations Social media data presents Social media data presents several advantageous characteristics, such as facilitating the process of intra- and inter-continental in- vestigations due to its breadth of foreign languages and allowing com- parisons between data derived from different regions where cellphone records from certain providers can differ geographically. Despite their advantages, multilingual posts in the social media space pose challenges towards contextual interpretation. For example, every month, there are over 330 million active Twitter users across the world, using tens of languages, with English (31.8%), Japanese (18.8%), and Spanish (8.46%) as the three most popular languages (VICINITAS, 2018). Cur- rent studies that extract situational awareness and perform sentiment/ emotion analysis on COVID-19 related posts tend to focus on mono- lingual posts (Griffith et al., 2021; Mansoor et al., 2020; Shofiya and Abidi, 2021) or multilingual posts with naïve translating approaches (Lin et al., 2021; Zhang et al., 2021). When applied to study areas with two or more dominant languages though, such investigative procedures ultimately ignore specific groups of people and introduce uncertainties when summarizing emotions and sentimental preferences across different languages. Despite the development in multilingual trans- lation, which is supported by the advances in natural language pro- cessing techniques, the potential biases in extracting and quantifying sentiment and emotions across different languages are still deserving further exploration. Quora is a popular question-and-answer (Q&A) website where users are allowed to ask questions and connect with people who contribute unique insights and quality answers. The COVID-19 pandemic has greatly stimulated people’s interest in asking and answering COVID-19 related questions, and a large amount of content can be harnessed for COVID-19 studies. George et al. (2020), for example, analyzed the content, type, and quality of Q&As in Quora regarding the pandemic and compared the information with that on the WHO website by manually categorizing the tone of the question as either positive, negative or ambivalent and grading questions for accuracy, authority, popularity, readability, and relevancy. Another notable effort is by McCreery et al. (2020), who designed a fine-tuning neural network approach trained by Quora question pairs to identify similar posted questions. Reddit, one of the most widely used discussion forums, allows registered users to submit content to the site, such as links, text posts, images, and videos, among which lots of content are related to current events. 3.2. Media sharing networks (YouTube and Instagram) A common approach is to select the most viewed videos by search queries and analyze the video content along with its metadata. Basch et al. (2020) identified the 100 most gi widely viewed YouTube videos in January 2020, using the search term “Coronavirus”. Their analysis revealed that only one-third of the videos covered key prevention behaviors. Instagram data, including post comments, geotags, and captions, could be retrieved with open-source tools such as the Instaloader. Re- searchers are able to share data through the Post IDs. For example, Zarei et al. (2020) used the Instagram Hashtag search API to retrieve public posts with a set of COVID-19 hashtags and crawl the reactions (com- ments or likes) for further analysis. Researchers have previously applied Natural Language Processing and deep learning techniques to Instagram posts as well. For example, Mackey et al. (2020) analyzed illicit COVID- 19 product sales from Twitter and Instagram posts using unsupervised topic modeling and a recurrent neural network with long short-term memory (LSTM) unit to identify online sellers. 4.1.2. Multilingual investigations Social media data presents A popular method to collect Reddit data is through the PushShift API, which serves as a copy of Reddit objects. For example, Low et al. (2020) introduced the Reddit Mental Health Dataset that contains posts from 28 subreddits from 2018 to 2020. Reddit data provide a new lens for researchers to study emotion, gender differences, and mental health during the COVID-19 pandemic. Text mining and natural language processing techniques are the major analytical tools employed in research. Naseem et al. (2020) leveraged Non-negative Matrix Factor- ization (NMF) topic modeling on Reddit posts to study life during the pandemic and the effects of social distancing. Aggarwal et al. (2020) analyzed emotions through the Valence-Arousal-Dominance (VAD) affect representation. Word embeddings of Reddit data were used to train beta regression models in order to predict VAD scores. The results revealed considerable differences between male and female authors across all three emotional dimensions. 3.3. Discussion forums Discussion forums, e.g., Quora, Yahoo answers (shut down on May 4, 2021), Infobot, and Reddit, provide users with online spaces to discuss news and answer questions, where the public comments and statements can be collected by researchers to study the influences of COVID-19. Among the above-mentioned discussion forums, Quora and Reddit are the two commonly used forums that enabled for many COVID-19 studies. 4.1.3. Posting incentives For geotagged social media posts, the active sharing characteristics of social media data inevitably lead to a “warped reality”, when compared to actual human-to-human interactions and place visitations. That is to say, human mobility patterns extracted from the social media space are a biased representation of actual human mobility. For example, geotagged social media posts derived from check-in records generally have to satisfy two requirements: 1) users are geographically close to the check-in locations (or at least they claim themselves to be); 2) the check-in locations are worth posting (i.e., “interesting” enough for them to create a post). In comparison, geolocations obtained via passive collecting means (e.g., WIFI, Call Detail Records, and GPS signals) only need to satisfy the former requirement. Such a biased and inevitably generalized representation may lead to uncertainties or even mistakes when they are applied to the decision-making process for COVID-19 mitigation. For sentiment and emotion mining, studies have shown 4.1. Challenges 4.1. Challenges 4.1.1. Biased population spectrum 3.2. Media sharing networks (YouTube and Instagram) Media sharing networks such as YouTube and Instagram have also been important channels where people receive COVID-19 information through venues such as videos and photos. The YouTube Data API could be used to find videos through search queries. Video metadata, including title descriptions, tags, video statistics, comments, as well as the 7 X. Huang et al. International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 in 2025 (Tankovska, 2021). Despite this growing trend, however, there has been an argument that the current demographics of social media active users are unrepresentative of the entire population across the world in terms of age, gender, race, education, or socioeconomic status. Jiang et al. (2019) found that Twitter users in the entire U.S. are biased towards certain age groups (18–29 and 30–39), females, and people with Bachelor’s and Graduate degrees). They also discovered that U.S. Twitter users’ spectrum presents strong spatial non-stationarity, sug- gesting that the biases of Twitter users vary by geographical location (Jiang et al., 2019). Facebook users are most represented by individuals between the ages of 25 and 35 years (Barnhart, 2022). The demographic representation on one of China’s largest social media platforms, Sina Weibo, also has a user demographic that is considerably different from that of the national population statistics, with males composing 56.3% of users, 20–35 years old comprising 82% of users, and with 91% of users with Bachelor’s degrees (Weibo-Sina, 2017). Such biases are also observed in other social media platforms, including WeChat and Insta- gram. Thus, it remains debatable whether place visitations, mobility patterns, sentiment, or emotions captured from social media space are representative of those of the entire population. Applying such findings derived from a small minority towards the general public is cautioned against, unless they are statistically compared with and supported by other means of data collection that are less biased, such as question- naires and surveys. misinformation (Li et al., 2020b). A common approach is to select the most viewed videos by search queries and analyze the video content along with its metadata. Basch et al. (2020) identified the 100 most widely viewed YouTube videos in January 2020, using the search term “Coronavirus”. Their analysis revealed that only one-third of the videos covered key prevention behaviors. misinformation (Li et al., 2020b). 4. Challenges and our paths forward 4.1. Challenges 4.1.1. Biased population spectrum In 2020, social media platforms were used by over 3.6 billion people worldwide, and this number is projected to increase to almost 4.4 billion 8 X. Huang et al. International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 1,000 most active accounts that mention COVID. Within these accounts, 127 (12.7%) were identified as highly likely to be bots. In an early study involving Weibo, a random sample of roughly 30,000 users was found to contain 57% of either inactive users or “zombie accounts” due to these accounts’ lack of consistent postings over time (Fu and Chau, 2013). The method by which social media bots are handled in social media analytics is important for studies that address COVID-19 challenges by mining information from authentic human users. Despite the bots composing a smaller population than that of authentic human users, relatively high posting volumes can greatly contaminate researchers’ data. However, we have yet to find an automatic and correct approach to identifying bots. Hence, this issue remains a challenge. In addition, we must acknowledge the skewed posting behaviors of social media users, given that a majority of social media posts come from a minority of users. For example, 80% of tweets come from the top 10% of the most active users (Wojcik and Hughes, 2019), which means that our analysis of a collec- tion of social media posts is likely to be skewed towards a small subset of users. Optimized weighting mechanisms based on posting frequencies and user ID indexed analytical workflows can be adopted to address this issue. However, our literature review suggests that few efforts have considered such a skewed user representation when performing social media mining in the context of COVID-19. The question of how re- posting behaviors should be managed is yet another challenge because there is a multitude of methods to account for re-posting, which may alter the analytical results. Despite the fact that many studies have designated re-posts as an agreement to the original post, Metaxas et al. (2014) found that, on many occasions, this assumption may actually not be the case. that bursts of posting tend to occur following major events (Pohl et al., 2012; Zhou and Chen, 2014). In other words, a considerable amount of social media posts are event/news-driven. 4.1.6. Bots, retweets, and skewed posting behaviors From 50 million tweets, Al-Rawi & Shukla (2020) identified the top 4.1.5. Uncertainties in sentiment and emotion Uncertainties in sentiment analysis and the emotions that it extracts from social media posts have been widely acknowledged. Despite the fact that advanced natural language processing techniques, when applied to multilingual posts, enable reliable translation for certain languages, they still have relatively less consistency and lower perfor- mances for those that are less spoken (Balahur and Jacquet, 2015). This leads to increased uncertainties in the results of sentiment and emotion analysis when they are applied to multilingual regions, especially in those with less spoken languages. Certain social media platforms, such as Twitter and Weibo, have character limits, creating oddities (e.g., the usage of abbreviations and acronyms) found in posts that would other- wise not be present in normal language. Furthermore, the unique character-limit restrictions imposed on posts made on certain social media platforms demand the application of word vectors trained spe- cifically from short-text documents instead of the ones that are from popular word representation models, such as Global Vectors for Word Representation (GloVe) (Pennington et al., 2014) and Embeddings from Language Models (ELMo) (Peng et al., 2019). In addition, within the context of COVID-19, we should note that certain words have senti- mental tendencies that are opposite to their original meaning. For example, the sentence “I have been tested positive” has a negative senti- ment polarity, despite the fact that the word “positive” presents a strong positive polarity in many sentiment analysis models. Another challenge is the treatment of neutral reporting of valenced information, e.g., “the daily death toll dropped to 1,000” and “100 more have been tested positive today”. It is unclear whether these statements should be considered as neutral unemotional reporting of developments or assumed that users are in negative/positive emotional states. 4.1.4. Positioning accuracy The levels to which social media data are geotagged vary greatly (depending on the social media platforms’ terms of use and users’ spe- cific settings), posing challenges to studies that prefer certain geoloca- tional accuracy for social media posts. In general, the geotagging levels include country, first-level subdivision, second-level subdivision, city, neighborhood/point of interest (POI), and exact coordinates. A study conducted by Li et al. summarized the positioning levels of 1.4 billion geotagged tweets worldwide: 1.1 billion (79%) at the city level, 138.1 million (9.8%) at the first-level subdivision (state or province), 90.4 million (6.4%) with exact coordinates, 46.2 million (3.3%) at country level, and 21.4 million (1.5%) at neighborhood/point of interest (Li et al., 2021a). Certainly, different social media platforms have varying preferences towards certain positioning levels. For example, Sina Weibo check-in data returned from Sina Weibo API are mostly positioned at the POI level (Hu et al., 2019), whereas Facebook Data for Good only pro- vides re-aggregated data at certain administrative levels due to privacy concerns (Edsberg Møllgaard et al., 2022). The varying positioning levels of social media posts impose a great influence on the statistical findings of studies that summarize statistics within certain geographic units due to the modifiable areal unit problem (MAUP). For applications that demand accurate human moving patterns, integrating social media posts with mixed positioning levels produces significant uncertainties that should not be overlooked. 4.1.1. Biased population spectrum Therefore, the question as to whether emotions and sentiments from event-triggered posts largely reflect options towards the event itself or the general topic remains to be explored. Unfortunately, it remains a challenge to grasp the contextual meaning behind sentiments and emotions using the current natural language processing techniques. 4.1.7. Data sharing Data sharing in social media, especially during the COVID-19 pandemic, has become a crucial driving force in motivating social media studies to address COVID-19 challenges. Properly shared social media data archives support validity by advancing reproducibility, replicability, and comparability, addressing the ‘digital divides’ in data accessibility and saving efforts in the data collection processes (Weller and Kinder-Kurlanda, 2016). However, existing efforts often fail to be grounded in the general principles that underlie institutionalized data archiving and sharing, as the lack of standardized metadata, consistent documentation, and sustainable claim in current COVID-19 social media sharing efforts can be clearly observed. The lack of guidance for social media data sharing, especially during the COVID-19 pandemic, leads to sharing procedures that vary by different social media research com- munities. Thus, the current practices of social media data sharing need to be coherent and universally agreed upon in order to benefit not only future COVID-19 studies but also investigations on other public health emergencies. 4.2. Future directions Based on the aforementioned challenges, we propose a number of research directions along which future efforts can be made to broaden and deepen the current research paradigm. These future directions are discussed in the context of the quantity and quality of social media data, the techniques used to process social media data, its application across multi-disciplines, and data archiving and sharing. First, future efforts should be made to have a better understanding of the nature of social media data and to improve the quantity and quality of social media data. In particular, efforts towards enriching social media data with the demographic attributes of social media users under the protection of data privacy are much needed. Social media users’ demographic attributes affect their participation in the social network and further influence their behaviors (e.g., mental health status) (Sin- nenberg et al., 2017). Obtaining users’ demographic attributes can be difficult because they cannot be directly collected from social media platforms. However, such demographic information, including age, 4.1.6. Bots, retweets, and skewed posting behaviors From 50 million tweets, Al-Rawi & Shukla (2020) identified the top 9 X. Huang et al. International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 gender, socioeconomic status, religion, and personality type, can be extrapolated from a user’s tweets via machine learning, with an accu- racy ranging from 60% to 90% (Bi et al., 2013; Burger et al., 2011; Ikeda et al., 2013; Pennacchiotti and Popescu, 2011; Rao et al., 2010). This is an underutilized resource for studies using social media data and can be applied towards understanding the subjects of investigation and reducing sampling biases. More specifically, studies based on individual tweets rather than individual users face the issue of skewed data prob- lems, given that one user may post multiple tweets in a certain period of time. It can be addressed by the user indexed analytics, which is based on users’ ID (e.g., as individuals or organizations). Such demographic information would also enable us to calibrate and justify the represen- tativeness and reliability of social media data by cross-data validation based on other data sources (e.g., survey or census data). and anonymity of social media users. Sharing social media data, though they are largely claimed as ’anonymized’, via public repositories and platforms should be supported by discussions of obtaining consent and/ or ethical approval for research purposes (Fadda et al., 2022). 5. Conclusion Second, future work could explore new approaches and techniques in data retrieval, processing, and analytics to provide potential solutions to conquer the constraints inherent in social media data-based studies. For data retrieval, using Twitter APIs has been the most common approach to retrieve tweets that target certain topics. In early 2021, a new academic-oriented API was released by Twitter, which grants free access to full-archive search for researchers to obtain more precise, complete, and unbiased data, greatly benefitting future Twitter-based analytics thanks to its increased data representativeness (Twitte, 2021). Facebook posts can be retrieved via CrowdTangle API, a public tool owned and operated by Facebook (CrowdTangle, 2016). However, the representa- tiveness of retrieved Facebook posts deserves further investigation (Yang et al., 2021). Posts in the discussion forums, such as Reddit and Quora, are valuable sources to gauge public attention. Additional cau- tions are needed when retrieving topic-relevant questions and answers. In addition, further efforts are encouraged to conduct cross-comparison on analytical results from different social media platforms, given that social media platforms can have user bases that vary in population spectrum. For data processing and analytics, technical solutions lie in the rapid development of computational skills and platforms (e.g., artificial intelligence, digital twins, and crowdsourcing) as they are more effective and efficient ways to quantify human behaviors (e.g., fuzzy logic lexical metrics and multilingual sentiment analysis). Com- parison studies across different methods for data pre-processing are also needed. Taking Twitter as an example, analytical results might be different when using tweets V.S. retweets, tweets with or without URLs, tweets including emoticons or not, and tweets generated by robots or not. We also need to establish standards for social media data reporting and a generic metadata architecture to better compare the scalability, replication, and reliability of social media data-based studies. Social media have been widely used as platforms and virtual com- munities where users worldwide can create and share information. The vast sensing network constituted by millions of active users and billions of posts allow information on certain topics to be mined and analyzed in a rapid manner. During the COVID-19 pandemic, we have witnessed extensive social media data mining efforts with diversified data mining techniques. These efforts address COVID-19 challenges from various perspectives, including early warning and detection, human mobility monitoring, communication and information conveying, gauging public attitudes and emotions, monitoring infodemic and misinformation, and mitigating hatred and violence. 4.2. Future directions This is particularly important for datasets containing information of users’ profiles due to the fact that such datasets have the risk of being identi- fiable via cross-referencing data attributes (Sinnenberg et al., 2017). Under the protection of data sharing regulations and the spirit of reproductivity, we should endeavor to facilitate the sharing of the pro- cessed social media data via public repositories and platforms and establish reproducible workflow that can be employed by end-users without a coding background. 5. Conclusion We also notice that an increasing number of COVID-19 related social media datasets have been made publicly available to benefit research communities by promoting repli- cability and reproducibility. Despite the remaining challenges (e.g., biased population spectrum and difficulty in multilingual in- vestigations), we believe the future is bright for social media analytics to address future public health emergencies. CRediT authorship contribution statement Xiao Huang: Conceptualization, Resources, Writing – original draft, Writing – review & editing, Supervision. Siqin Wang: Supervision, Conceptualization, Writing – original draft, Writing – review & editing. Mengxi Zhang: Supervision, Conceptualization, Writing – original draft, Writing – review & editing, Supervision. Tao Hu: Supervision, Conceptualization, Writing – original draft, Writing – review & editing. Alexander Hohl: Writing – original draft. Bing She: Writing – original draft. Xi Gong: Writing – original draft. Jianxin Li: Writing – original draft. Xiao Liu: Writing – original draft. Oliver Gruebner: Writing – review & editing. Regina Liu: Writing – original draft, Writing – review & editing. Xiao Li: Conceptualization, Writing – review & editing. Zhewei Liu: Writing – review & editing. Xinyue Ye: Conceptualization. Zhenlong Li: Conceptualization, Writing – review & editing. Third, we call for investigations on social media bi-directional communications (e.g., organization-to-individual, individual-to-indi- vidual, and individual-to-organization) before, during, and after the COVID-19 pandemic as well as during other disruptive events. We also call for broader potential and opportunities for using social media data in multidisciplinary studies across social, geographic, environmental, and computational sciences to better understand the impact of COVID- 19 on human-environment interaction. In addition to the popular do- mains mentioned in Section 2, social media data can be applied to a wider network of fields under the context of the COVID-19 pandemic, such as commercial industry, transportation, security and information management, and social phycology. For example, social media data has great potential for understanding and addressing COVID-19 related cyber-bullying (Das et al., 2020), detecting suicide (Morese et al., 2022) or mental disorders within a certain population (Sher, 2020), and evaluating the recovery of restaurants (Laguna et al., 2020) and hospi- tality industry (Park et al., 2020). Social media data provides a unique opportunity to support governments and public/private sectors by monitoring the recovery of human society in the later stages of the pandemic and preparing for future public health emergencies and crises. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Agarwal, A., Xie, B., Vovsha, I., Rambow, O., Passonneau, R.J., 2011. Sentiment analysis of twitter data, Proceedings of the workshop on language in social media (LSM 2011), pp. 30-38. Alkhalifa, R., Yoong, T., Kochkina, E., Zubiaga, A., Liakata, M., 2020. QMUL-SDS at CheckThat! 2020: determining COVID-19 tweet check-worthiness using an enhanced CT-BERT with numeric expressions. arXiv preprint arXiv:2008.13160. pp Aggarwal, J., Rabinovich, E., Stevenson, S., 2020. Exploration of gender differences in COVID-19 discourse on reddit. arXiv preprint arXiv:2008.05713. Agarwal, A., Xie, B., Vovsha, I., Rambow, O., Passonneau, R.J., 2011. Sentiment analysis of twitter data, Proceedings of the workshop on language in social media (LSM 2011), pp. 30-38. Aggarwal, J., Rabinovich, E., Stevenson, S., 2020. Exploration of gender differences in COVID-19 discourse on reddit. arXiv preprint arXiv:2008.05713. Alenezi, M.N., Alqenaei, Z.M., 2021. Machine learning in detecting COVID-19 misinformation on twitter. Future Internet 13, 244. Alkhalifa, R., Yoong, T., Kochkina, E., Zubiaga, A., Liakata, M., 2020. QMUL-SDS at CheckThat! 2020: determining COVID-19 tweet check-worthiness using an enhanced CT-BERT with numeric expressions. arXiv preprint arXiv:2008.13160. Alenezi, M.N., Alqenaei, Z.M., 2021. Machine learning in detecting COVID-19 misinformation on twitter. Future Internet 13, 244. References Edsberg Møllgaard, P., Lehmann, S., Alessandretti, L., 2022. Understanding components of mobility during the COVID-19 pandemic. Philosophical Transactions of the Royal Society A 380, 20210118. Banda, J.M., Tekumalla, R., Wang, G., Yu, J., Liu, T., Ding, Y., Chowell, G., 2021. A large- scale COVID-19 Twitter chatter dataset for open scientific research—an international collaboration. Epidemiologia 2 (3), 315–324. y Elhadad, M.K., Li, K.F., Gebali, F., 2020. Detecting misleading information on COVID-19. IEEE Access 8, 165201–165215. p g , Barbieri, F., Anke, L.E., Camacho-Collados, J., 2021. Xlm-t: A multilingual language model toolkit for twitter. arXiv preprint arXiv:2104.12250. Ewing, L.-A., Vu, H.Q., 2021. Navigating ‘home schooling’during COVID-19: Australian public response on twitter. Media International Australia 178, 77–86. Barkur, G., Vibha, G.B.K., 2020. Sentiment analysis of nationwide lockdown due to COVID 19 outbreak: Evidence from India. Asian journal of psychiatry 51, 102089. Fadda, M., Sykora, M., Elayan, S., Puhan, M. A., Naslund, J. A., Mooney, S. J., .et al. 2022. Ethical issues of collecting, storing, and analyzing geo-referenced tweets for mental health research. Digital Health, 8, 20552076221092539. Barnhart, B. (2022, March 2). Social media demographics to inform your Brand’s strategy in 2022. Sprout Social. Retrieved March 13, 2022, from https:// sproutsocial.com/insights/new-social-media-demographics/. Fan, L., Yu, H., Yin, Z., 2020. Stigmatization in social media: Documenting and analyzing hate speech for COVID-19 on Twitter. Proceedings of the Association for Information Science and Technology 57, e313. Basch, C.H., Hillyer, G.C., Meleo-Erwin, Z.C., Jaime, C., Mohlman, J., Basch, C.E., 2020. Preventive behaviors conveyed on YouTube to mitigate transmission of COVID-19: cross-sectional study. JMIR public health and surveillance 6, e18807. gy Fersini, E., Rosso, P., Anzovino, M., 2018. Overview of the Task on Automatic Misogyny Identification at IberEval 2018. Ibereval@ sepln 2150, 214–228. Bashar, M.A., Nayak, R., Luong, K., Balasubramaniam, T., 2021. Progressive domain adaptation for detecting hate speech on social media with small training set and its application to COVID-19 concerned posts. Social Network Analysis and Mining 11, 1–18. i p Fraser, T., Aldrich, D.P., 2020. Social ties, mobility, and covid-19 spread in Japan. Fritz, C., Kauermann, G., 2020. On the interplay of regional mobility, social connectedness, and the spread of COVID-19 in Germany. arXiv preprint arXiv: 2008.03013. Beria, P., Lunkar, V., 2020. Presence and mobility of the population during Covid-19 outbreak and lockdown in Italy. Fu, K.-W., Chau, M., 2013. Reality check for the Chinese microblog space: a random sampling approach. PLoS ONE 8, e58356. References S., Simon, F. M., Howard, P. N., & Nielsen, R. K. (2020). Types, sources, and claims of COVID-19 misinformation (Doctoral dissertation, University of Oxford). Burger, J.D., Henderson, J., Kim, G., Zarrella, G., 2011. Discriminating gender on twitter. Association for Computational Linguistics. Glazkova, A., Glazkov, M., Trifonov, T., 2021. g2tmn at constraint@ aaai2021: exploiting CT-BERT and ensembling learning for COVID-19 fake news detection, International Workshop on Combating On line Ho st ile Posts in Regional Languages dur ing Emerge ncy Si tuation. Springer 116–127. Ceron, W., de-Lima-Santos, M.-F., Quiles, M.G., 2021. Fake news agenda in the era of COVID-19: Identifying trends through fact-checking content. Online Social Networks and Media 21, 100116. Gong, X., Lane, K.M.D., 2020. Institutional Twitter usage among US geography departments. The professional geographer 72, 219–237. Chang, M.-C., Kahn, R., Li, Y.-A., Lee, C.-S., Buckee, C.O., Chang, H.-H., 2021. Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan. BMC Public Health 21, 1–10. Gong, X., Yang, X., 2020. Social media platforms. The geographic information science & technology body of knowledge 1–9. Gong, X., Ye, X., 2021. Governors Fighting Crisis: Responses to the COVID-19 Pandemic across US States on Twitter. The Professional Geographer 73, 683–701. Chen, E., Lerman, K., Ferrara, E., 2020a. Tracking social media discourse about the covid-19 pandemic: Development of a public coronavirus twitter data set. JMIR public health and surveillance 6, e19273. Goodchild, M.F., 2007. Citizens as sensors: the world of volunteered geography. GeoJournal 69, 211–221. Chen, Q., Min, C., Zhang, W., Wang, G., Ma, X., Evans, R., 2020b. Unpacking the black box: How to promote citizen engagement through government social media during the COVID-19 crisis. Comput. Hum. Behav. 110, 106380. Grajales III, F.J., Sheps, S., Ho, K., Novak-Lauscher, H., Eysenbach, G., 2014. Social media: a review and tutorial of applications in medicine and health care. Journal of medical Internet research 16, e2912. i Griffith, J., Marani, H., Monkman, H., 2021. COVID-19 vaccine hesitancy in Canada: Content analysis of tweets using the theoretical domains framework. Journal of medical Internet research 23, e26874. Cheng, I., Heyl, J., Lad, N., Facini, G., Grout, Z., 2021. Evaluation of Twitter data for an emerging crisis: an application to the first wave of COVID-19 in the UK. Sci. Rep. 11, 1–13. Gruzd, A., Mai, P., 2020. Going viral: How a single tweet spawned a COVID-19 conspiracy theory on Twitter. Big Data & Society 7, 2053951720938405. References Bi, B., Shokouhi, M., Kosinski, M., Graepel, T., 2013. Inferring the demographics of search users: Social data meets search queries. In: Proceedings of the 22nd international conference on World Wide Web, pp. 131–140. Fu, K.-W., Zhu, Y., 2020. Did the world overlook the media’s early warning of COVID- 19? J. Risk Res. 23, 1047–1051. Bild, D.R., Liu, Y., Dick, R.P., Mao, Z.M., Wallach, D.S., 2015. Aggregate characterization of user behavior in Twitter and analysis of the retweet graph. ACM Transactions on Internet Technology (TOIT) 15, 1–24. Gao, J., Zheng, P., Jia, Y., Chen, H., Mao, Y., Chen, S., Wang, Y., Fu, H., Dai, J., 2020a. Mental health problems and social media exposure during COVID-19 outbreak. PLoS ONE 15, e0231924. Garland, J., Ghazi-Zahedi, K., Young, J.-G., H´ebert-Dufresne, L., Galesic, M., 2020. Countering hate on social media: Large scale classification of hate and counter speech. arXiv preprint arXiv:2006.01974. Bisanzio, D., Kraemer, M.U., Bogoch, I.I., Brewer, T., Brownstein, J.S., Reithinger, R., 2020. Use of Twitter social media activity as a proxy for human mobility to predict the spatiotemporal spread of COVID-19 at global scale. Geospatial health 15. Garland, J., Ghazi-Zahedi, K., Young, J.-G., H´ebert-Dufresne, L., Galesic, M., 2022. Impact and dynamics of hate and counter speech online. EPJ Data Sci. 11, 3. Bonaccorsi, G., Pierri, F., Cinelli, M., Flori, A., Galeazzi, A., Porcelli, F., Schmidt, A.L., Valensise, C.M., Scala, A., Quattrociocchi, W., 2020. Economic and social consequences of human mobility restrictions under COVID-19. Proc. Natl. Acad. Sci. 117, 15530–15535. George, J., Gautam, D., Kesarwani, V., Sugumar, P.A., Malhotra, R., 2020. What Does the Public Want to Know About The COVID-19 Pandemic? A Systematic Analysis of Questions Asked in The Internet. medRxiv. https://doi.org/10.1101/ 2020.09.15.20192039. Boon-Itt, S., Skunkan, Y., 2020. Public perception of the COVID-19 pandemic on Twitter: sentiment analysis and topic modeling study. JMIR Public Health and Surveillance 6, e21978. Gesser-Edelsburg, A., 2021. Using narrative evidence to convey health information on social media: the case of COVID-19. Journal of Medical Internet Research 23, e24948. Boukouvalas, Z., Mallinson, C., Crothers, E., Japkowicz, N., Piplai, A., Mittal, S., Joshi, A., Adalı, T., 2020. Independent component analysis for trustworthy cyberspace during high impact events: an application to Covid-19. arXiv preprint arXiv: 2006.01284. Giustini, D., Ali, S.M., Fraser, M., Boulos, M.N.K., 2018. Effective uses of social media in public health and medicine: a systematic review of systematic reviews. Online journal of public health informatics 10. Brennen, J. References Finally, there is a need for universal guidelines that address the ethics of social media research, with a focus on maintaining the privacy 10 X. Huang et al. International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 CrowdTangle. 2016. Content discovery and Social Monitoring Made Easy. CrowdTangle. Retrieved June 14, 2022, from https://www.crowdtangle.com/. Allington, D., Duffy, B., Wessely, S., Dhavan, N., Rubin, J., 2021. Health-protective behaviour, social media usage and conspiracy belief during the COVID-19 public health emergency. Psychol. Med. 51, 1763–1769. Retrieved June 14, 2022, from https://www.crowdtangle.com/. Cui, L., Lee, D., 2020. Coaid: Covid-19 healthcare misinformation dataset. arXiv preprint arXiv:2006.00885. g y y Al-Rakhami, M.S., Al-Amri, A.M., 2020. Lies kill, facts save: detecting COVID-19 misinformation in twitter. IEEE Access 8, 155961–155970. D’Souza, R.S., D’Souza, S., Strand, N., Anderson, A., Vogt, M.N., Olatoye, O., 2020. YouTube as a source of medical information on the novel coronavirus 2019 disease (COVID-19) pandemic. Global public health 15, 935–942. Al-Rawi, A., Shukla, V., 2020. Bots as active news promoters: A digital analysis of COVID-19 tweets. Information 11, 461. Das, S., Kim, A., & Karmakar, S. (2020). Change-point analysis of cyberbullying-related twitter discussions during covid-19. arXiv preprint arXiv:2008.13613. Alsaeedi, A., Khan, M.Z., 2019. A study on sentiment analysis techniques of Twitter data. International Journal of Advanced Computer Science and Applications 10, 361–374. Ameur, M.S.H., Aliane, H., 2021. AraCOVID19-MFH: Arabic COVID-19 Multi-label Fake News & Hate Speech Detection Dataset. Procedia Comput. Sci. 189, 232–241. Davidson, T., Warmsley, D., Macy, M., Weber, I., 2017. Automated hate speech detection and the problem of offensive language. In: Proceedings of the International AAAI Conference on Web and Social Media, pp. 512–515. Ameur, M.S.H., Aliane, H., 2021. AraCOVID19-MFH: Arabic COVID-19 Multi-label Fake News & Hate Speech Detection Dataset. Procedia Comput. Sci. 189, 232–241. Balahur A Jacquet G 2015 Sentiment analysis meets social media Challenges and Balahur, A., Jacquet, G., 2015. Sentiment analysis meets social media–Challenges and solutions of the field in view of the current information sharing context. Elsevier 428–432. Dharawat, A., Lourentzou, I., Morales, A., Zhai, C., 2020. Drink bleach or do what now? Covid-HeRA: A dataset for risk-informed health decision making in the presence of COVID19 misinformation. arXiv preprint arXiv:2010.08743. Balcombe, L., De Leo, D., 2020. An integrated blueprint for digital mental health services amidst COVID-19. JMIR mental health 7, e21718. References Cinelli, M., Quattrociocchi, W., Galeazzi, A., Valensise, C.M., Brugnoli, E., Schmidt, A.L., Zola, P., Zollo, F., Scala, A., 2020. The COVID-19 social media infodemic. Sci. Rep. 10, 1–10. Gruzd, A., Mai, P., 2020. Going viral: How a single tweet spawned a COVID-19 conspiracy theory on Twitter. Big Data & Society 7, 2053951720938405. Gundapu, S., Mamidi, R., 2021. Transformer based automatic COVID-19 fake news detection system. arXiv preprint arXiv:2101.00180. Gundapu, S., Mamidi, R., 2021. Transformer based automatic COVID-19 fake news detection system. arXiv preprint arXiv:2101.00180. Conneau, A., Khandelwal, K., Goyal, N., Chaudhary, V., Wenzek, G., Guzm´an, F., Grave, E., Ott, M., Zettlemoyer, L., Stoyanov, V., 2019. Unsupervised cross-lingual representation learning at scale. arXiv preprint arXiv:1911.02116. Gupta, R.K., Vishwanath, A., Yang, Y., 2020. COVID-19 Twitter dataset with latent topics, sentiments and emotions attributes. arXiv preprint arXiv:2007.06954. i C S i S k i h S 2021 i i Coppersmith, G., Dredze, M., Harman, C., 2014. Quantifying mental health signals in Twitter, Proceedings of the workshop on computational linguistics and clinical psychology: From linguistic signal to clinical reality, pp. 51-60. He, B., Ziems, C., Soni, S., Ramakrishnan, N., Yang, D., Kumar, S., 2021. Racism is a virus: anti-asian hate and counterspeech in social media during the COVID-19 crisis. In: Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 90–94. Croucher, S.M., Nguyen, T., Rahmani, D., 2020. Prejudice toward Asian Americans in the COVID-19 pandemic: The effects of social media use in the United States. Frontiers. Communication 39. y g, pp Head, B.W., Alford, J., 2015. Wicked problems: Implications for public policy and management. Administration & society 47, 711–739. 11 X. Huang et al. International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 Heidari, M., Zad, S., Hajibabaee, P., Malekzadeh, M., HekmatiAthar, S., Uzuner, O., Jones, J.H., 2021. Bert model for fake news detection based on social bot activities in the covid-19 pandemic, 2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON). IEEE 0103–0109. Laguna, L., Fiszman, S., Puerta, P., Chaya, C., T´arrega, A., 2020. The impact of COVID-19 lockdown on food priorities. Results from a preliminary study using social media and an online survey with Spanish consumers. Food Qual. Prefer. 86, 104028. Lai, S., Floyd, J., Tatem, A., 2021. Preliminary risk analysis of the spread of new COVID- 19 variants from the UK. South Africa and Brazil. References Hohl, A., Choi, M., Yellow Horse, A. J., Medina, R. M., Wan, N., & Wen, M. (2022). Spatial Distribution of Hateful Tweets Against Asians and Asian Americans During the COVID-19 Pandemic, November 2019 to May 2020. In American Journal of Public Health (Vol. 112, Issue 4, pp. 646–649). American Public Health Association. https://doi.org/10.2105/ajph.2021.306653. Lamsal, R., 2021. Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence 51 (5), 2790–2804. g Leng, Y., Zhai, Y., Sun, S., Wu, Y., Selzer, J., Strover, S., Fensel, J., Pentland, A., Ding, Y., 2020. Analysis of misinformation during the COVID-19 outbreak in China: cultural, Leng, Y., Zhai, Y., Sun, S., Wu, Y., Selzer, J., Strover, S., Fensel, J., Pentland, A., Ding, Y., 2020. Analysis of misinformation during the COVID-19 outbreak in China: cultural, social and political entanglements. arXiv preprint arXiv:2005.10414. Li C Ch L J Ch X Zh M P C P Ch H 2020 R i l i Holtz, D., Zhao, M., Benzell, S.G., Cao, C.Y., Rahimian, M.A., Yang, J., Allen, J., Collis, A., Moehring, A., Sowrirajan, T., 2020. Interdependence and the cost of uncoordinated responses to COVID-19. Proc. Natl. Acad. Sci. 117, 19837–19843. Li, C., Chen, L.J., Chen, X., Zhang, M., Pang, C.P., Chen, H., 2020a. Retrospective analysis of the possibility of predicting the COVID-19 outbreak from Internet searches and social media data, China, 2020. Eurosurveillance 25, 2000199. Horse, A.J.Y., Jeung, R., Lim, R., Tang, B., Im, M., Higashiyama, L., Schweng, L., Chen, M., 2021. Stop AAPI hate national report. Stop AAPI Hate: San Francisco, CA, USA. , , , Li, H.-O.-Y., Bailey, A., Huynh, D., Chan, J., 2020b. YouTube as a source of information on COVID-19: a pandemic of misinformation? BMJ global health 5, e002604. Li X X H H X G C A K Y Y X 2021 E i d t t Hossain, T., Logan IV, R.L., Ugarte, A., Matsubara, Y., Young, S., Singh, S., 2020 COVIDLies: Detecting COVID-19 misinformation on social media. Li, X., Xu, H., Huang, X., Guo, C.A., Kang, Y., Ye, X., 2021a. Emerging geo-data sources to reveal human mobility dynamics during COVID-19 pandemic: opportunities and challenges. Computational Urban Science 1, 1–9. Hu, Q., Bai, G., Wang, S., Ai, M., 2019. Extraction and monitoring approach of dynamic urban commercial area using check-in data from Weibo. Sustainable cities and society 45, 508–521. g p , Li, Y., Jiang, B., Shu, K., Liu, H., 2020c. References The effectiveness of Twitter as a communication tool in college recruitment. Texas A&M. University-Kingsville. Lu, Y., Zhang, L., 2020. Social media WeChat infers the development trend of COVID-19. J. Infect. 81, e82–e83. Kietzmann, J.H., Hermkens, K., McCarthy, I.P., Silvestre, B.S., 2011. Social media? Get serious! Understanding the functional building blocks of social media. Bus. Horiz. 54, 241–251. Lyu, J.C., Le Han, E., Luli, G.K., 2021. COVID-19 vaccine–related discussion on Twitter: topic modeling and sentiment analysis. Journal of medical Internet research 23, e24435. , Kim, J., Aum, J., Lee, S., Jang, Y., Park, E., Choi, D., 2021. FibVID: Comprehensive fake news diffusion dataset during the COVID-19 period. Telematics Inform. 64, 101688. Mackey, T., Purushothaman, V., Li, J., Shah, N., Nali, M., Bardier, C., Liang, B., Cai, M., Cuomo, R., 2020a. Machine learning to detect self-reporting of symptoms, testing access, and recovery associated with COVID-19 on Twitter: retrospective big data infoveillance study. JMIR public health and surveillance 6, e19509. Knuutila, A., Herasimenko, A., Au, H., Bright, J., Howard, P.N., 2021. A Dataset of COVID-Related Misinformation Videos and their Spread on Social Media. Journal of Open Humanities Data 7. Kogan, N.E., Clemente, L., Liautaud, P., Kaashoek, J., Link, N.B., Nguyen, A.T., Lu, F.S., Huybers, P., Resch, B., Havas, C., 2021. An early warning approach to monitor COVID-19 activity with multiple digital traces in near real time. Science. Advances 7, eabd6989. i Mackey, T.K., Li, J., Purushothaman, V., Nali, M., Shah, N., Bardier, C., Cai, M., Liang, B., 2020b. Big data, natural language processing, and deep learning to detect and characterize illicit COVID-19 product sales: Infoveillance study on Twitter and Instagram. JMIR public health and surveillance 6, e20794. Manguri, K.H., Ramadhan, R.N., Amin, P.R.M., 2020. Twitter sentiment analysis on worldwide COVID-19 outbreaks. Kurdistan Journal of Applied Research 54–65. Koirala, A., 2020. COVID-19 fake news classification using deep learning. Kostkova, P., Szomszor, M., St. Louis, C., 2014. # swineflu: The use of twitter as an early warning and risk communication tool in the 2009 swine flu pandemic. ACM Transactions on Management Information Systems (TMIS) 5, 1-25. Mansoor, M., Gurumurthy, K., Prasad, V., 2020. Global sentiment analysis of COVID-19 tweets over time. arXiv preprint arXiv:2010.14234. Kouloumpis, E., Wilson, T., Moore, J., 2011. Twitter sentiment analysis: The good the bad and the omg!, Proceedings of the international AAAI conference on web and social media, pp. 538-541. Matoˇsevi´c, G., Bevanda, V., 2020. References TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labels. Data 7, 8. Jang, H., Rempel, E., Roth, D., Carenini, G., Janjua, N.Z., 2021. Tracking COVID-19 discourse on twitter in North America: Infodemiology study using topic modeling and aspect-based sentiment analysis. Journal of medical Internet research 23, e25431. Lin, B., Zou, L., Duffiel, N., Mostafavi, A., Cai, H., Zhou, B., Tao, J., Yang, M., Mandal, D., Abedin, J., 2021. Revealing the Global Linguistic and Geographical Disparities of Public Awareness to Covid-19 Outbreak through Social Media. arXiv preprint arXiv: 2111.03446. Jiang, Y., Huang, X., Li, Z., 2021. Spatiotemporal Patterns of Human Mobility and Its Association with Land Use Types during COVID-19 in New York City. ISPRS Int. J. Geo-Inf. 10, 344. Liu, W., Xu, W., John, B., 2021. Organizational disaster communication ecology: Examining interagency coordination on social media during the onset of the COVID- 19 pandemic. American Behavioral Scientist 65, 914–933. Jiang, Y., Li, Z., Ye, X., 2019. Understanding Demographic and Socioeconomic Bias of Geotagged Twitter Users at the County Level. Cartography and Geographic Information Science 46 (3). 19 pandemic. American Behavioral Scientist 65, 914–933. Lopez, C.E., Gallemore, C., 2021. An augmented multilingual Twitter dataset for studying the COVID-19 infodemic. Social Network Analysis and Mining 11, 1–14. Lopreite, M., Panzarasa, P., Puliga, M., Riccaboni, M., 2021. Early warnings of COVID-19 outbreaks across Europe from social media. Sci. Rep. 11, 1–7. Lopez, C.E., Gallemore, C., 2021. An augmented multilingual Twitter dataset for studying the COVID-19 infodemic. Social Network Analysis and Mining 11, 1–14. L i M P P P li M Ri b i M 2021 E l i f COVID 19 Kabir, M., Madria, S., 2020. CoronaVis: a real-time COVID-19 tweets data analyzer and data repository. arXiv preprint arXiv:2004.13932. Lopreite, M., Panzarasa, P., Puliga, M., Riccaboni, M., 2021. Early warnings of COVID-19 outbreaks across Europe from social media. Sci. Rep. 11, 1–7. k lk C hi G Gh h S S 2020 l Kar, D., Bhardwaj, M., Samanta, S., Azad, A.P., 2020. No rumours please! a multi-indic- lingual approach for COVID fake-tweet detection, 2021 Grace Hopper Celebration India (GHCI). IEEE 1–5. Low, D.M., Rumker, L., Talkar, T., Torous, J., Cecchi, G., Ghosh, S.S., 2020. Natural language processing reveals vulnerable mental health support groups and heightened health anxiety on reddit during covid-19: Observational study. Journal of medical Internet research 22, e22635. Kelly, K.J., 2013. References MM-COVID: A multilingual and multimodal data repository for combating COVID-19 disinformation. arXiv preprint arXiv: 2011.04088. Hu, T., Wang, S., Luo, W., Zhang, M., Huang, X., Yan, Y., Li, Z., 2021. Revealing public opinion towards COVID-19 vaccines with Twitter data in the United States: spatiotemporal perspective. Journal of Medical Internet Research 23 (9), e30854. Li, Y., Shin, J., Sun, J., Kim, H.M., Qu, Y., Yang, A., 2021b. Organizational sensemaking in tough times: The ecology of NGOs’ COVID-19 issue discourse communities on social media. Comput. Hum. Behav. 122, 106838. Hu, Y., Wang, R.-Q., 2020. Understanding the removal of precise geotagging in tweets. Nat. Hum. Behav. 4, 1219–1221. Huang, X., Li, Z., Jiang, Y., Li, X., Porter, D., 2020. Twitter reveals human mobility dynamics during the COVID-19 pandemic. PLoS ONE 15, e0241957. Li, Y., Zeng, Y., Liu, G., Lu, D., Yang, H., Ying, Z., Hu, Y., Qiu, J., Zhang, C., Fall, K., 2020d. Public awareness, emotional reactions and human mobility in response to the COVID-19 outbreak in China–a population-based ecological study. Psychol. Med. 1–8. Huang, X., Li, Z., Jiang, Y., Ye, X., Deng, C., Zhang, J., Li, X., 2021. The characteristics of multi-source mobility datasets and how they reveal the luxury nature of social distancing in the US during the COVID-19 pandemic. Int. J. Digital Earth 14, 424–442. i Li, Z., Huang, X., Hu, T., Ning, H., Ye, X., Huang, B., Li, X., 2021c. ODT FLOW: A Scalable Platform for Extracting, Analyzing, and Sharing Multi-source Multi-scale Human Mobility. PLoS ONE 16 (8), e0255259. Ikeda, K., Hattori, G., Ono, C., Asoh, H., Higashino, T., 2013. Twitter user profiling based on text and community mining for market analysis. Knowl.-Based Syst. 51, 35–47. l h h l k bl Li, Z., Huang, X., Ye, X., Jiang, Y., Martin, Y., Ning, H., Hodgson, M.E., Li, X., 2021d. Measuring global multi-scale place connectivity using geotagged social media data. Sci. Rep. 11, 1–19. Ilin, C., Annan-Phan, S., Tai, X.H., Mehra, S., Hsiang, S., Blumenstock, J.E., 2021. Public mobility data enables covid-19 forecasting and management at local and global scales. Sci. Rep. 11, 1–11. l Liao, Q., Yuan, J., Dong, M., Yang, L., Fielding, R., Lam, W.W.T., 2020. Public engagement and government responsiveness in the communications about COVID- 19 during the early epidemic stage in China: infodemiology study on social media data. Journal of medical Internet research 22, e18796. i Imran, M., Qazi, U., Ofli, F., 2022. References l h b l h Pennacchiotti, M., Popescu, A.-M., 2011. Democrats, republicans and starbucks afficionados: user classification in twitter, Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 430-438. Velasquez, N., Leahy, R., Restrepo, N.J., Lupu, Y., Sear, R., Gabriel, N., Jha, O., Goldberg, B., Johnson, N., 2021. Online hate network spreads malicious COVID-19 content outside the control of individual social media platforms. Sci. Rep. 11, 1–8. Pennington, J., Socher, R., Manning, C.D., 2014. Glove: Global vectors for word representation. In: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP), pp. 1532–1543. VICINITAS, 2018. Research on 100 Million Tweets: What it Means for Your Social Media Strategy for Twitter. g g p g pp P´erez-Arnal, R., Conesa, D., Alvarez-Napagao, S., Suzumura, T., Catal`a, M., Alvarez- Lacalle, E., Garcia-Gasulla, D., 2021. Comparative analysis of geolocation information through mobile-devices under different Covid-19 mobility restriction patterns in Spain. ISPRS Int. J. Geo-Inf. 10, 73. Vishwamitra, N., Hu, R.R., Luo, F., Cheng, L., Costello, M., Yang, Y., 2020. On analyzing covid-19-related hate speech using bert attention. In: 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, pp. 669–676. h h h d b h Wang, J., Zhou, Y., Zhang, W., Evans, R., Zhu, C., 2020a. Concerns expressed by Chinese social media users during the COVID-19 pandemic: content analysis of Sina Weibo microblogging data. Journal of medical Internet research 22, e22152. Perrio, C., Madabushi, H.T., 2020. CXP949 at WNUT-2020 Task 2: Extracting Informative COVID-19 Tweets–RoBERTa Ensembles and The Continued Relevance of Handcrafted Features. arXiv preprint arXiv:2010.07988. Wang, S., Huang, X., Hu, T., Zhang, M., Li, Z., Ning, H., Corcoran, J., Khan, A., Liu, Y., Zhang, J., 2022. The times, they are a-changin’: tracking shifts in mental health signals from early phase to later phase of the COVID-19 pandemic in Australia. BMJ Global Health 7, e007081. Petutschnig, A., Albrecht, J., Resch, B., Ramasubramanian, L., Wright, A., 2021. Commuter Mobility Patterns in Social Media: Correlating Twitter and LODES Data. ISPRS Int. J. Geo-Inf. 11, 15. Wang, X., Zou, C., Xie, Z., Li, D., 2020b. Public opinions towards covid-19 in california and new york on twitter. Pohl, D., Bouchachia, A., Hellwagner, H., 2012. Automatic sub-event detection in emergency management using social media. In: Proceedings of the 21st international conference on world wide web, pp. 683–686. l Wang, Y., Hao, H., Platt, L.S., 2021. References Sentiment analysis of tweets about COVID-19 disease during pandemic, 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO). IEEE 1290–1295. Koulouris, A., Vraimaki, E., Koloniari, M., 2020. COVID-19 and library social media use. Reference Services Review. McCreery, C.H., Katariya, N., Kannan, A., Chablani, M., Amatriain, X., 2020. August). Effective transfer learning for identifying similar questions: matching user questions to COVID-19 FAQs. In: In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 3458–3465. Kruspe, A., H¨aberle, M., Kuhn, I., Zhu, X.X., 2020. Cross-language sentiment analysis of european twitter messages duringthe covid-19 pandemic. arXiv preprint arXiv: 2008.12172. Conference on Knowledge Discovery & Data Mining, pp. 3458–3465. Medhat, W., Hassan, A., Korashy, H., 2014. Sentiment analysis algorithms and applications: A survey. Ain Shams Eng. J. 5, 1093–1113. i Medhat, W., Hassan, A., Korashy, H., 2014. Sentiment analysis algorithms and applications: A survey. Ain Shams Eng. J. 5, 1093–1113. M i B A 2021 A OK B ? I ifi i f i d Kulldorff, M., 1997. A spatial scan statistic. Communications in Statistics-Theory and methods 26, 1481–1496. i Meisner, B.A., 2021. Are you OK, Boomer? Intensification of ageism and intergenerational tensions on social media amid COVID-19. Leisure Sciences 43, 56–61. Kumar, S., Pranesh, R.R., Carley, K.M., 2021. A fine-grained analysis of misinformation in covid-19 tweets. Mendelsohn, J., Tsvetkov, Y., Jurafsky, D., 2020. A framework for the computational linguistic analysis of dehumanization. Frontiers in artificial intelligence 3, 55. Merkley, E., Bridgman, A., Loewen, P.J., Owen, T., Ruths, D., Zhilin, O., 2020. A rare moment of cross-partisan consensus: Elite and public response to the COVID-19 Kwok, S.W.H., Vadde, S.K., Wang, G., 2021. Tweet topics and sentiments relating to COVID-19 vaccination among Australian Twitter users: Machine learning analysis. Journal of medical Internet research 23, e26953. 12 X. Huang et al. International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 Rao, D., Yarowsky, D., Shreevats, A., Gupta, M., 2010. Classifying latent user attributes in twitter, Proceedings of the 2nd international workshop on Search and mining user-generated contents, pp. 37-44. pandemic in Canada. Canadian Journal of Political Science/Revue canadienne de science politique 53, 311–318. Metaxas, P.T., Mustafaraj, E., Wong, K., Zeng, L., O’Keefe, M., Finn, S., 2014. Do retweets indicate interest, trust, agreement? arXiv preprint arXiv:1411.3555. i Reuter, C., Ludwig, T., Kaufhold, M.-A., Spielhofer, T., 2016. References Follow thy neighbor: Connecting the social and the spatial networks on Twitter. Comput. Environ. Urban Syst. 53, 87–95. i Niu, J., Rees, E., Ng, V., Penn, G., 2021. Statistically Evaluating Social Media Sentiment Trends towards COVID-19 Non-Pharmaceutical Interventions with Event Studies. In: Proceedings of the Sixth Social Media Mining for Health (# SMM4H) Workshop and Shared Task, pp. 1–6. Sutton, J., Renshaw, S.L., Butts, C.T., 2020. The first 60 days: American public health Agencies’ social media strategies in the emerging COVID-19 pandemic. Health security 18, 454–460. Olteanu, A., Vieweg, S., Castillo, C., 2015. What to expect when the unexpected happens: Social media communications across crises. In: Proceedings of the 18th ACM conference on computer supported cooperative work & social computing, pp. 994–1009. Tan, M.J.Z., 2021. Topic extraction and sentiment analysis of subreddit (r/Coronavirus). Final Year Project (FYP), Nanyang Technological University. Tankovska, H., 2021. Number of social media users 2025| Statista. Statista. https:// www. statista. com/statistics/278414/number-of-worldwide …. pp Papadamou, K., Zannettou, S., Blackburn, J., De Cristofaro, E., Stringhini, G., Sirivianos, M., 2020. “ It is just a flu”: Assessing the Effect of Watch History on YouTube’s Pseudoscientific Video Recommendations. arXiv preprint arXiv:2010.11638. k k d h l l l www. statista. com/statistics/278414/number-of-worldwide … Tsao, S.-F., Chen, H., Tisseverasinghe, T., Yang, Y., Li, L., Butt, Z.A., 2021. What social media told us in the time of COVID-19: a scoping review. The Lancet Digital Health 3, e175–e194. i Park, E., Kim, W.H., Kim, S.B., 2020. Tracking tourism and hospitality employees’ real- time perceptions and emotions in an online community during the COVID-19 pandemic. Current Issues in Tourism 1–5. Tsoy, D., Tirasawasdichai, T., Kurpayanidi, K.I., 2021. Role of social media in shaping public risk perception during Covid-19 pandemic: a theoretical review. International Journal of Management Science and Business Administration 7, 35. Peng, Y., Yan, S., Lu, Z., 2019. Transfer learning in biomedical natural language processing: an evaluation of BERT and ELMo on ten benchmarking datasets. arXiv preprint arXiv:1906.05474. Twitter. 2021. Twitter API for Academic Research | Products | Twitter Developer Platform. CrowdTangle. Retrieved June 14, 2022, from https://developer.twitter. com/en/products/twitter-api/academic-research. p p Peng, Z., Wang, R., Liu, L., Wu, H., 2020. Exploring urban spatial features of COVID-19 transmission in Wuhan based on social media data. ISPRS Int. J. Geo-Inf. 9, 402. Tziafas, G., Kogkalidis, K., Caselli, T., 2021. Fighting the COVID-19 infodemic with a holistic BERT ensemble. arXiv preprint arXiv:2104.05745. References Domestic and international mobility trends in the United Kingdom during the COVID-19 pandemic: an analysis of facebook data. Int. J. Health Geographics 20, 1–13. Sh L 2020 Th i t f th COVID 19 d i i id t QJM A Ngai, C.S.B., Singh, R.G., Lu, W., Koon, A.C., 2020. Grappling with the COVID-19 health crisis: content analysis of communication strategies and their effects on public engagement on social media. Journal of medical Internet research 22, e21360. N T G t S R J B ll R V k t h S 2020 G l t d T itt Sher, L., 2020. The impact of the COVID-19 pandemic on suicide rates. QJM: An International Journal of Medicine 113 (10), 707–712. Sh fi C Abidi S 2021 S ti t A l i COVID 19 R l t d S i l Di t i International Journal of Medicine 113 (10), 707–712. Shofiya, C., Abidi, S., 2021. Sentiment Analysis on COVID-19-Related Social Distancing in Canada Using Twitter Data Int J Environ Res Public Health 18 5993 ( ), Shofiya, C., Abidi, S., 2021. Sentiment Analysis on COVID-19-Related Social Distancing in Canada Using Twitter Data. Int. J. Environ. Res. Public Health 18, 5993. Shofiya, C., Abidi, S., 2021. Sentiment Analysis on COVID-19-Related Social Distancing in Canada Using Twitter Data. Int. J. Environ. Res. Public Health 18, 5993. S b ih A E E H i A M Ab El A E 2020 R t COVID 19 i hi h Nguyen, T., Gupta, S., Raman, J., Bellomo, R., Venkatesh, S., 2020a. Geolocated Twitter- based population mobility in Victoria, Australia, during the staged COVID-19 restrictions. Critical care and resuscitation: journal of the Australasian Academy of Critical Care Medicine. Sobaih, A.E.E., Hasanein, A.M., Abu Elnasr, A.E., 2020. Responses to COVID-19 in higher education: Social media usage for sustaining formal academic communication in developing countries. Sustainability 12, 6520. i Nguyen, T.T., Criss, S., Dwivedi, P., Huang, D., Keralis, J., Hsu, E., Phan, L., Nguyen, L. H., Yardi, I., Glymour, M.M., 2020b. Exploring US shifts in anti-Asian sentiment with the emergence of COVID-19. Int. J. Environ. Res. Public Health 17, 7032. i i i ll l i i l di i p g y , Stechemesser, A., Wenz, L., Levermann, A., 2020. Corona crisis fuels racially profiled hate in social media networks. EClinicalMedicine 23. Stephens, M., Poorthuis, A., 2015. References Emergency services׳ attitudes towards social media: A quantitative and qualitative survey across Europe. Int. J. Hum Comput Stud. 95, 96–111. Michela, E., Rosenberg, J.M., Kimmons, R., Sultana, O., Burchfield, M.A., Thomas, T., 2022. “We Are Trying to Communicate the Best We Can”: Understanding Districts’ Communication on Twitter During the COVID-19 Pandemic. AERA Open 8, 23328584221078542. Roberts, N., 2000. Wicked problems and network approaches to resolution. International public management review 1, 1–19. Moorhead, S.A., Hazlett, D.E., Harrison, L., Carroll, J.K., Irwin, A., Hoving, C., 2013. A new dimension of health care: systematic review of the uses, benefits, and limitations of social media for health communication. Journal of medical Internet research 15, e1933. Rowe, F., Mahony, M., Graells-Garrido, E., Rango, M., Sievers, N., 2021. Using Twitter to track immigration sentiment during early stages of the COVID-19 pandemic. Data & Policy 3. Rufai, S.R., Bunce, C., 2020. World leaders’ usage of Twitter in response to the COVID-19 pandemic: a content analysis. Journal of public health 42, 510–516. Morese, R., Gruebner, O., Sykora, M., Elayan, S., Fadda, M., Albanese, E., 2022. Detecting suicide ideation in the era of social media: the population neuroscience perspective. Front. Psychiatry. https://doi.org/10.3389/fpsyt.2022.652167. Saakyan, A., Chakrabarty, T., Muresan, S., 2021. COVID-fact: Fact extraction and verification of real-world claims on COVID-19 pandemic. arXiv preprint arXiv: 2106.03794. Müller, M., Salath´e, M., Kummervold, P.E., 2020. Covid-twitter-bert: A natural language processing model to analyse covid-19 content on twitter. arXiv preprint arXiv: 2005.07503. Samaras, L., García-Barriocanal, E., Sicilia, M.-A., 2020. Syndromic surveillance using web data: a systematic review. Innovation in Health Informatics 39–77. Murugesan, S., 2007. Understanding Web 2.0. IT Prof. 9, 34–41. Schillinger, D., Chittamuru, D., Ramírez, A.S., 2020. From “infodemics” to health promotion: a novel framework for the role of social media in public health. Am. J. Public Health 110, 1393–1396. Naseem, S.S., Kumar, D., Parsa, M.S., Golab, L., 2020. Text mining of COVID-19 discussions on Reddit, 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). IEEE, pp. 687-691. Shahi, G.K., Nandini, D., 2020. FakeCovid–A multilingual cross-domain fact check news dataset for COVID-19. arXiv preprint arXiv:2006.11343. National Research Council, 1989. Improving risk communication. Nemes, L., Kiss, A., 2021. Social media sentiment analysis based on COVID-19. Journal of Information and Telecommunication 5, 1–15. Shepherd, H.E., Atherden, F.S., Chan, H.M.T., Loveridge, A., Tatem, A.J., 2021. References Hate in the machine: Anti- Black and anti-Muslim social media posts as predictors of offline racially and religiously aggravated crime. The British Journal of Criminology 60, 93–117. Zarei, K., Farahbakhsh, R., Crespi, N., Tyson, G., 2020. A first instagram dataset on covid- 19. arXiv preprint arXiv:2004.12226. g y gg gy Wojcik, S., Hughes, A., 2019. How Twitter users compare to the general public. Internet, Science & Tech, Pew Research Center. Zeng, C., Zhang, J., Li, Z., Sun, X., Olatosi, B., Weissman, S., Li, X., 2021. Spatial- temporal relationship between population mobility and COVID-19 outbreaks in South Carolina: time series forecasting analysis. Journal of medical Internet research 23, e27045. Xu, P., Dredze, M., Broniatowski, D.A., 2020. The twitter social mobility index: Measuring social distancing practices with geolocated tweets. Journal of medical Internet research 22, e21499. Xue, J., Chen, J., Hu, R., Chen, C., Zheng, C., Su, Y., Zhu, T., 2020. Twitter discussions and emotions about the COVID-19 pandemic: Machine learning approach. Journal of medical Internet research 22, e20550. Zhang, X., Yang, Q., Albaradei, S., Lyu, X., Alamro, H., Salhi, A., Ma, C., Alshehri, M., Jaber, I.I., Tifratene, F., 2021. Rise and fall of the global conversation and shifting sentiments during the COVID-19 pandemic. Humanities and social sciences communications 8, 1–10. Yamamoto, Y., Kumamoto, T., Nadamoto, A., 2014. Role of emoticons for multidimensional sentiment analysis of Twitter. In: Proceedings of the 16th International Conference on Information Integration and Web-based Applications & Services, pp. 107–115. i Zhou, X., Chen, L., 2014. Event detection over twitter social media streams. VLDB J. 23, 381–400. Zhou, X., Mulay, A., Ferrara, E., Zafarani, R., 2020. Recovery: A multimodal repository for covid-19 news credibility research. In: Proceedings of the 29th ACM international conference on information & knowledge management, pp. 3205–3212. , pp Yang, A., 2020. The issue niche theory of nongovernmental and nonprofit organizations’ interorganizational network ecology. Communication Theory 30, 41–63. Yang, C., Huang, Q., Li, Z., Liu, K., Hu, F., 2017. Big Data and cloud computing: innovation opportunities and challenges. Int. J. Digital Earth 10, 13–53. Zhu, Y., Fu, K.-W., Gr´epin, K.A., Liang, H., Fung, I.-C.-H., 2020. Limited early warnings and public attention to coronavirus disease 2019 in China, January–February, 2020: a longitudinal cohort of randomly sampled Weibo users. Disaster medicine and public health preparedness 14, e24–e27. Yang, K. C., Pierri, F., Hui, P. M., Axelrod, D., Torres-Lugo, C., Bryden, J., & Menczer, F. (2021). References Examining risk and crisis communications of government agencies and stakeholders during early-stages of COVID-19 on Twitter. Comput. Hum. Behav. 114, 106568. Qazi, U., Imran, M., Ofli, F., 2020. GeoCoV19: a dataset of hundreds of millions of multilingual COVID-19 tweets with location information. SIGSPATIAL Special 12, 6–15. Waseem, Z., Hovy, D., 2016. Hateful symbols or hateful people? predictive features for hate speech detection on twitter, Proceedings of the NAACL student research workshop, pp. 88-93. Qin, L., Sun, Q., Wang, Y., Wu, K.-F., Chen, M., Shia, B.-C., Wu, S.-Y., 2020. Prediction of number of cases of 2019 novel coronavirus (COVID-19) using social media search index. Int. J. Environ. Res. Public Health 17, 2365. Weber, E.P., Khademian, A.M., 2008. Wicked problems, knowledge challenges, and collaborative capacity builders in network settings. Public administration review 68, 334–349. Quintero Johnson, J.M., Saleem, M., Tang, L., Ramasubramanian, S., Riewestahl, E., 2021. Media Use During COVID-19: An investigation of negative effects on the mental health of Asian versus White Americans. Frontiers in Communication 6, 79. Wei, Y., Wang, J., Song, W., Xiu, C., Ma, L., Pei, T., 2021. Spread of COVID-19 in China: analysis from a city-based epidemic and mobility model. Cities 110, 103010. Rahman, M., Islam, M.N., 2022. Exploring the performance of ensemble machine learning classifiers for sentiment analysis of covid-19 tweets. Sentimental Analysis and Deep Learning. Springer 383–396. Weibo-Sina, 2017. Weibo-Sina Weibo user report on 2017. Weibo-Sina, 2017. Weibo-Sina Weibo user report on 2017. Weller, K., Kinder-Kurlanda, K.E., 2016. A manifesto for data sharing in social media research. In: Proceedings of the 8th ACM Conference on Web Science, pp. 166–172. 13 X. Huang et al. International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 International Journal of Applied Earth Observation and Geoinformation 113 (2022) 102967 Wich, M., R¨ather, S., Groh, G., 2021. German Abusive Language Dataset with Focus on COVID-19, Proceedings of the 17th Conference on Natural Language Processing (KONVENS 2021), pp. 247-252. Yu, M., Li, Z., Yu, Z., He, J., Zhou, J., 2021. Communication related health crisis on social media: a case of COVID-19 outbreak. Current issues in tourism 24, 2699–2705. Zachreson, C., Mitchell, L., Lydeamore, M.J., Rebuli, N., Tomko, M., Geard, N., 2021. Risk mapping for COVID-19 outbreaks in Australia using mobility data. J. R. Soc. Interface 18, 20200657. i Williams, M.L., Burnap, P., Javed, A., Liu, H., Ozalp, S., 2020. References The COVID-19 infodemic: twitter versus facebook. Big Data & Society, 8(1), 20539517211013861. Ye, X., Andris, C., 2021. Spatial social networks in geographic information science. International Journal of Geographical Information Science. https://doi.org/ 10.1080/13658816.2021.2001722. Spelta, A., Pagnottoni, P., 2021. Mobility-based real-time economic monitoring amid the COVID-19 pandemic. Sci. Rep. 11, 1–15. Further reading Docquier, F., Golenvaux, N., Nijssen, S., Schaus, P., Stips, F., 2021. Cross-border mobility responses to covid-19 in Europe: new evidence from facebook data. Manuscript (Universit´e catholique de Louvain). Ye, X., Jourdan, D., Lee, C., Newman, G., Van Zandt, S., 2021. Citizens as sensors for small communities. Journal of Planning Education and Research. https://doi.org/ 10.1177/0739456X211050932. Gao, Z., Wang, S., Gu, J., 2020b. Public participation in smart-city governance: A qualitative content analysis of public comments in urban China. Sustainability 12, 8605. Gao, Z., Wang, S., Gu, J., 2020b. Public participation in smart-city governance: A qualitative content analysis of public comments in urban China. Sustainability 12, 8605. Yin, H., Yang, S., Li, J., 2020. Detecting topic and sentiment dynamics due to COVID-19 pandemic using social media, International Conference on Advanced Data Mining and Applications. Springer, pp. 610-623. Spelta, A., Pagnottoni, P., 2021. Mobility-based real-time economic monitoring amid the COVID-19 pandemic. Sci. Rep. 11, 1–15. Yoo, W., 2019. How risk communication via Facebook and Twitter shapes behavioral intentions: The case of fine dust pollution in South Korea. Journal of Health Communication 24, 663–673. 14
https://openalex.org/W4248643987
http://www.epj-conferences.org/10.1051/epjconf/201713705022/pdf
English
null
Neutral pion form factor measurement by the NA62 experiment
EPJ web of conferences
2,017
cc-by
6,310
1 Introduction High intensity kaon experiments provide great opportunities for precision π0 decay measurements since kaons are a source of tagged neutral pion decays. The NA48/2 experiment at CERN SPS took data in 2003-2004 using simultaneous K+/K−beams, collecting about 2 × 1011 K± decays in the fiducial decay volume. In 2007 a 10 times smaller K± decay sample was collected by the NA62 experiment exploiting an improved set-up of the NA48/2 detector with lower intensity beams and minimum bias trigger conditions. This paper reports neutral pion physics results from both experiments. The preliminary measurement of the π0 electromagnetic transition form factor (TFF) slope parameter is based on a sample of 1.05 × 106 π0 Dalitz (π0 D) decays collected by NA62. Using a sample of ∼1.7 × 107 neu- tral pions tagged in K± →π±π0 D and K± →µ±π0 Dν decays, NA48/2 performed a search for the dark photon A′ through the decay chain π0 →γA′, A′ →e+e−. © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/). Neutral pion form factor measurement by the NA62 experiment Monica Pepe1,2,a 1INFN Sezione di Perugia 2On behalf of the NA62-RK and NA48/2 Collaborations Abstract. The NA62 experiment at CERN collected a large sample of charged kaon decays with a highly efficient trigger for decays into electrons in 2007. A measurement of the electromagnetic transition form factor slope of the neutral pion in the time-like region from about one million fully reconstructed π0 Dalitz decays is presented. Abstract. The NA62 experiment at CERN collected a large sample of charged kaon decays with a highly efficient trigger for decays into electrons in 2007. A measurement of the electromagnetic transition form factor slope of the neutral pion in the time-like region from about one million fully reconstructed π0 Dalitz decays is presented. The limits on dark photon production from a sample of about 1.7 × 107 π0 Dalitz decays collected in 2003-2004 by the earlier kaon experiment at CERN NA48/2 are also reported. The limits on dark photon production from a sample of about 1.7 × 107 π0 Dalitz decays collected in 2003-2004 by the earlier kaon experiment at CERN NA48/2 are also reported. ae-mail: monica.pepe@pg.infn.it , 05022 (2017) 137 EPJ Web of Conferences XIIth Quark Confinement & the Hadron Spectrum , 05022 (2017) 137 EPJ Web of Conferences XIIth Quark Confinement & the Hadron Spectrum DOI: 10.1051/ 713705022 epjconf/201 2 Beam and detector The beam line of the NA48/2 experiment [1] was designed to provide simultaneous K+/K−beams: positive and negative hadron beams were produced in the same beryllium target by impinging 400 GeV/c protons from the CERN SPS accelerator. Charged particles with momenta of (60±3) GeV/c were selected by an achromatic system of four dipole magnets splitting the two beams in the vertical plane and recombining them on a common axis. Kaon decays were collected in a 114 m long fiducial decay region contained in a cylindrical vacuum tank. This line was also used by NA62 in 2007 at lower beam intensity with K+ and K−beams alternatively produced with a momentum range (74±1.4) GeV/c. The beams were mostly composed of π±, with a K± fraction of approximately 6%. , 05022 (2017) 137 EPJ Web of Conferences XIIth Quark Confinement & the Hadron Spectrum , 05022 (2017) 137 EPJ Web of Conferences XIIth Quark Confinement & the Hadron Spectrum DOI: 10.1051/ 713705022 epjconf/201 DOI: 10.1051/ 713705022 epjconf/201 Charged decay product momenta were measured by a magnetic spectrometer consisting of two sets of drift chambers and a central dipole magnet, providing a momentum resolution σ(p)/p = (1.02 ⊕0.044 · p)% in 2003-2004 and σ(p)/p = (0.48 ⊕0.009 · p)% in 2007 (p in GeV/c). A hodoscope consisting of two planes of plastic scintillators segmented into horizontal and vertical strips provided a fast trigger for charged particles with very good (∼150 ps) time resolution. A liquid Krypton calorimeter (LKr), 27 X0 deep, was used to measure electromagnetic energy deposition of photons and electrons with a resolution σE/E = (3.2 √ E ⊕9%/E ⊕0.42)% (E in GeV). The detector was completed by a hadron calorimeter followed by a muon veto system. A detailed description of the experimental apparatus can be found in Ref.[2]. 3 Measurement of the π0 electromagnetic transition form factor slope in NA62 Hadron-photon couplings are fundamental observables in particle physics. They can be de- scribed in terms of form factors merging effects due to the underlying structure of hadrons, hence precision measurements of Transition Form Factors (TFF) are very significant probes to investigate electromagnetic interactions and the internal structure of hadrons. The π0 electromagnetic TFF also enters the prediction of significant observable quantities, such as the rate of the rare decay π0 →e+e− and the hadronic light-by-light scattering contribution to the magnetic moment (g −2)µ of the muon [3]. Improved measurements have been recently made available from studies of the radiative and Dalitz meson decays as well as from meson production in photon-photon processes: precise model independent measurements of the π0 TFF slope parameter are essential to set new stricter constraints on theoretical models. Pions are the lighest mesons, well suited to probe low energy hadron dynamics and copiously produced in kaon decays, therefore kaon experiments are ideal environments for precision studies of the pion properties: since neutral pions are produced in four of the six main decay modes of the charged kaons, the NA62 experiment can also be considered as a π0 factory. (1 −r2/x)1/2. , 05022 (2017) 137 EPJ Web of Conferences XIIth Quark Confinement & the Hadron Spectrum , 05022 (2017) 137 EPJ Web of Conferences XIIth Quark Confinement & the Hadron Spectrum , 05022 (2017) 137 EPJ Web of Conferences DOI: 10.1051/ 713705022 epjconf/201 expected in the allowed kinematic region, it can be parametrized by a linear expression as a function of x, F (x) = (1 + ax), where a is the TFF slope parameter. expected in the allowed kinematic region, it can be parametrized by a linear expression as a function of x, F (x) = (1 + ax), where a is the TFF slope parameter. In the Vector Meson Dominance (VMD) approach [5, 6] F (x) is dominated by the ρ and ω mesons with a predicted value a ≈m2 π0(m−2 ρ + m−2 ω )/2 ≈0.03, which is in agreement with further theoretical studies [7–10]. Radiative corrections play a crucial role in the π0 TFF measurment since their effect on the differential decay rate is comparable to the TFF one: the first study of radiative corrections in the soft-photon approximation [11] was extended by adding virtual photon contributions and photon bremsstrahlung [12] and recently improved in Ref. [13] including one-loop one-photon irreducible contibutions. The latter calculations were implemented in the NA62 Monte Carlo (MC) simulation. Figure 1. Predictions of the π0 D decay x spectrum: Leading Order (black), Leading Order including π0 D TFF contribution with enhanced slope a = 0.3 (red), Leading Order corrected for radiative effects (green). Figure 1. Predictions of the π0 D decay x spectrum: Leading Order (black), Leading Order including π0 D TFF contribution with enhanced slope a = 0.3 (red), Leading Order corrected for radiative effects (green). Different predictions of the π0 D decay x spectrum are compared in Fig. 1 : LO decay x spec- trum, LO x spectrum including TFF effects with slope a = 0.3, 10 times larger than the VMD model expectation, and LO x spectrum corrected for radiative effects. The three curves are very close to each other and barely distinguishable. Different predictions of the π0 D decay x spectrum are compared in Fig. 1 : LO decay x spec- trum, LO x spectrum including TFF effects with slope a = 0.3, 10 times larger than the VMD model expectation, and LO x spectrum corrected for radiative effects. The three curves are very close to each other and barely distinguishable. 3.1 Measurement principle The π0 Dalitz decay π0 D →e+e−γ with BR=(1.174 ± 0.035)% [4] is the second most frequent π0 decay channel occurring when one of the photons has an off-shell mass above 2 electron masses. The measurement of the π0 TFF slope parameter is performed in NA62 from the study of the K± →π±π0 (K2π) decay followed by the π0 D decay. The kinematics of the π0 D decay can be expressed in terms of the x and y Dalitz variables: x = à Mee mπ0 !2 = (pe+ + pe−)2 m2 π0 , y = 2pπ0(pe+ −pe−) m2 π0(1 −x) (1) (1) where the variable kinematic limits are r2 ≤x ≤1 and −β ≤y ≤β, with r = 2me/mπ0 and β = (1 −r2/x)1/2. ng Order (LO) differential π0 D decay width is The Leading Order (LO) differential π0 D decay width is d2Γ(π0 D) dxdy = α 4πΓ(π0 2γ)(1 −x)3 x à 1 + y2 + r2 x ! (1 + δ(x, y))|F (x)|2 (2) (2) where Γ(π0 2γ) is the π0 →γγ decay width, δ(x, y) are the radiative corrections to the process and F (x) is the π0 electromagnetic TFF describing the photon-pion coupling. Since small variations of F (x) are 2 2 , 05022 (2017) 137 EPJ Web of Conferences XIIth Quark Confinement & the Hadron Spectrum 3.2 The data sample A clean sample of π0 mesons is produced in K2π decays: the charged pion is used to tag the production of the π0 and, since no undetected particles are present in the final state, background processes can be suppressed by applying stringent kinematic constraints on the reconstructed particle quantities. The data collected in 2007 by the NA62 experiment were obtained from about 2 × 1010 K± decays in the fiducial region, corresponding to about 5 × 109 π0 mesons from K2π decays. A sample of pure π0 D Dalitz decays with negliglible background was collected using a spectrometer three-track vertex selection and reconstructing the photon in the LKr calorimeter. The final sample amounts to 1.05 × 106 π0 D decays from K± →π±π0 D (K2πD) events with a small contribution from K± →µ±π0 Dν (Kµ3D) decays. µ Figure 2 shows the reconstructed eeγ and π±π0 invariant mass spectra (left and center respectively): the arrows indicate the selected region. The reconstructed spectrum of the x variable 3 3 , 05022 (2017) 137 EPJ Web of Conferences DOI: 10.1051/ 713705022 epjconf/201 XIIth Quark Confinement & the Hadron Spectrum ] 2 [GeV/c γ ee M 0.1 0.11 0.12 0.13 0.14 0.15 0.16 0.17 ) 2 Events / (0.5 MeV/c 10 2 10 3 10 4 10 5 10 Data D 0 π ± π → ± K ν ± µ D 0 π → ± K NA62 Preliminary ] 2 [GeV/c π 2 M 0.45 0.46 0.47 0.48 0.49 0.5 0.51 0.52 0.53 ) 2 Events / (0.5 MeV/c 10 2 10 3 10 4 10 5 10 Data D 0 π ± π → ± K ν ± µ D 0 π → ± K NA62 Preliminary x 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Events / 0.01 10 2 10 3 10 4 10 5 10 Data D 0 π ± π → ± K ν ± µ D 0 π → ± K NA62 Preliminary Figure 2. Reconstructed eeγ (left) and π±π0 (center) invariant mass distributions and x variable spectra (right) for data and MC components. x 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Events / 0.01 10 2 10 3 10 4 10 5 10 Data D 0 π ± π → ± K ν ± µ D 0 π → ± K NA62 Preliminary Figure 2. 3.2 The data sample Reconstructed eeγ (left) and π±π0 (center) invariant mass distributions and x variable spectra (right) for data and MC components. is shown in Fig. 2 (right) for the final sample of π0 D candidates compared to the MC predictions of individual contributions from K2πD and Kµ3D decays. The acceptances evaluated with MC simulations amount to 1.81% for K2πD and 0.02% for Kµ3D decays. is shown in Fig. 2 (right) for the final sample of π0 D candidates compared to the MC predictions of individual contributions from K2πD and Kµ3D decays. The acceptances evaluated with MC simulations amount to 1.81% for K2πD and 0.02% for Kµ3D decays. 3.3 Preliminary result The value of the TFF slope parameter is measured in NA62 by adjusting the MC simulation to the data in order to get the best agreement for the π0 D decay x spectrum obtained from the normalized differential decay width (Eq. (2)) integrated over y. The signal region is defined as x > 0.01 since the event acceptance at low x value is not well reproduced by the simulation: this choice does not affect the final result because the π0 D x spectrum is not sensitive to TFF effects for x value close to zero, as shown in Fig. 1. Table 1. Uncertainties of the π0 TFF slope measurement Table 1. Uncertainties of the π0 TFF slope measurement Source δa(×102) Statistical - data 0.49 Statistical - Mc 0.20 Total statistics 0.53 Beam momentum simulation 0.30 Spectrometer momentum scale 0.15 Spectrometer resolution 0.05 LKr non-linearity and energy scale 0.04 Particle mis-identification 0.08 Accidental background 0.08 Neglected π0 D sources in MC 0.01 Total systematic 0.36 A χ2 fit to the reconstructed x spectrum of data and MC simulation with different slopes is used to extract the TFF slope value using an equipopulous binning. The different hypotheses are tested by reweighing the MC events to create x distributions with different slope values from the same MC sample generated using a constant TFF slope asim = 0.032. The uncertainties on the measurement are listed in Table 1. The preliminary result is: , 05022 (2017) 137 EPJ Web of Conferences DOI: 10.1051/ 713705022 epjconf/201 XIIth Quark Confinement & the Hadron Spectrum x 2 − 10 1 − 10 1 0.99 1 1.01 1.02 1.03 1.04 1.05 Data / MC(a=0) Form factor: best fit band σ 1 ± Form factor: NA62 Preliminary TFF slope 0 π 0.1 − 0.05 − 0 0.05 0.1 Geneva-Saclay (1978) Saclay (1989) SINDRUM I @ PSI (1992) TRIUMF (1992) NA62 (2016) 30k events Fischer et al. 32k events Fonvieille et al. 54k events Meijer Drees et al. 8k events Farzanpay et al. 1M events (preliminary) D 0 π TFF Slope Measurements from 0 π Figure 3. Left: Results of the fit to the TFF showing the data/MC ratio as a function of x for a MC sample weighted to obtain a = 0. The events are divided into 20 equipopulous bins and the marker correspond to the bin barycenter. 3.3 Preliminary result The solid line represents |F (x)|2 with the measured slope value and the dashed lines indicate the 1 σ band. Right: Comparison of the the NA62 preliminary measurement of the TFF slope to those of experiments exploiting the same method. x 2 − 10 1 − 10 1 0.99 1 1.01 1.02 1.03 1.04 1.05 Data / MC(a=0) Form factor: best fit band σ 1 ± Form factor: NA62 Preliminary TFF slope 0 π 0.1 − 0.05 − 0 0.05 0.1 Geneva-Saclay (1978) Saclay (1989) SINDRUM I @ PSI (1992) TRIUMF (1992) NA62 (2016) 30k events Fischer et al. 32k events Fonvieille et al. 54k events Meijer Drees et al. 8k events Farzanpay et al. 1M events (preliminary) D 0 π TFF Slope Measurements from 0 π Figure 3. Left: Results of the fit to the TFF showing the data/MC ratio as a function of x for a MC sample weighted to obtain a = 0. The events are divided into 20 equipopulous bins and the marker correspond to the bin barycenter. The solid line represents |F (x)|2 with the measured slope value and the dashed lines indicate the 1 σ band. Right: Comparison of the the NA62 preliminary measurement of the TFF slope to those of experiments exploiting the same method. a = (3.70 ± 0.53stat ± 0.36syst) × 10−2 = (3.70 ± 0.64) × 10−2 The result is illustrated in Fig. 3 (left) where the effect of a positive TFF slope is clearly seen from the ratio of the reconstructed data to a MC distribution with slope a=0. The red solid line corresponds to a TFF function with the slope equal to the best fit central value, while dashed lines indicate the 1 σ band. This result is the first observation (at about 5.8 σ significance) of a non-zero TFF slope in the time-like momentum transfer region and represents the more precise π0 TFF slope measurement to date. The NA62 measurement can be directly compared to those of other experiments [14–17] obtained from π0 Dalitz decays, as shown in Fig. 3 (right): the analysed statistics is increased by a factor of ∼10 and the overall precision of the preliminary NA62 result improves the one of previous measurements. 4 Search for dark photon in NA48/2 The simplest hidden sector model introduces one extra U(1) gauge symmetry [18] where the interaction of a dark photon (DP) A′ with the visible sector would proceed through kinetic mixing with Standard Model (SM) hypercharge. Such scenarios (with GeV-scale dark matter) provide pos- sible explanations for the observed positron fraction excess in cosmic-rays and also offer a possible solution to the muon gyromagnetic ratio (g−2)µ anomaly [19]. The DP is characterized by two a priori unknown parameters, the mass mA′ and the mixing parameter ε2. It can be produced in π0 decays via the chain π0 →γA′, A′ →e+e−with the expected branching ratio [20]: B(π0 →γA′) = 2ε2 1 −m2 A′ m2 π0  3 B(π0 →γγ) (3) (3) 5 , 05022 (2017) 137 EPJ Web of Conferences DOI: 10.1051/ 713705022 epjconf/201 , 05022 (2017) 137 EPJ Web of Conferences XIIth Quark Confinement & the Hadron Spectrum XIIth Quark Confinement & the Hadron Spectrum which is kinematically suppressed for mA′ approaching the π0 mass. In the DP mass range accessible in pion decays, 2me < mA′ < mπ0, the only allowed tree-level decay of the dark photon in SM fermions is A′ →e+e−due to the high suppression of loop-induced SM decays (A′ →3γ, A′ →νν), hence for a DP decaying only in SM particles B(A′ →e+e−) ≈1 and the expected total width [20] is: ΓA′ ≈Γ(A′ →e+e−) = 1 3αε2mA′ s 1 −4m2e m2 A′ 1 + 2m2 e m2 A′  (4) (4) Since for 2me ≪mA′ < mπ0 the DP mean proper lifetime τA′ satisfies the relation cτA′ = ℏ/ΓA′ ≈0.8µm × Ã10−6 ε2 ! × Ã100MeV/c2 mA′ ! (5) (5) for sufficiently large values of mA′ and ε2 the DP decay is assumed to occurr at the production point: in this case the DP decay signature is identical to that of the Dalitz decay π0 D →e+e−γ (prompt decay). Therefore the π0 D decay represents an irreducible background and determines the measurement sensitivity. 4.1 Event selection The NA48/2 experiment collected a large sample of K± decays in flight providing a sample of pure π0 D reconstructed through K± →π±π0 (K2π) and K± →µ±π0ν (Kµ3) decays. The full NA48/2 data sample is used in this analysis consisting in the search for the decay chains starting from a K2π or Kµ3 decay followed by the prompt decay π0 →γA′, A′ →e+e−. A detailed description of the event selection can be found in Ref.[21]. The selection of both decays requires three-track vertices reconstructed in the fiducial decay region and two opposite sign electrons; charged particle identification is based on the ratio of the energy deposited in the LKr calorimeter to the momentum measured by the spectrometer; a single isolated LKr energy deposition cluster defines the photon candidate. The event selection criteria for the two channels are identical up to the momentum, invariant mass and particle identification conditions applied to classify an event as a K2π or Kµ3 candidate. Table 2. Number of data events passing the K2πD and Kµ3D selection and their acceptances computed with MC simulations.The statistical errors on the acceptances are negligible. K2πD selection Kµ3D selection Data Candidates NK2πD = 1.38 × 107 NKµ3D = 0.31 × 107 Acceptances for K2πD decay Aπ(K2πD) = 3.71% Aµ(K2πD) = 0.11% for Kµ3D decay Aπ(Kµ3D) = 0.03% Aµ(Kµ3D) = 4.17% for K3πD decay Aπ(K3πD) = 0 Aµ(K3πD) = 0.06% ber of data events passing the K2πD and Kµ3D selection and their acceptances computed with MC simulations.The statistical errors on the acceptances are negligible. K2πD selection Kµ3D selection Data Candidates NK2πD = 1.38 × 107 NKµ3D = 0.31 × 107 Acceptances for K2πD decay Aπ(K2πD) = 3.71% Aµ(K2πD) = 0.11% for Kµ3D decay Aπ(Kµ3D) = 0.03% Aµ(Kµ3D) = 4.17% for K3πD decay Aπ(K3πD) = 0 Aµ(K3πD) = 0.06% In addition to the individual DP selections for K2π and Kµ3 decays, a joint DP selection is considered for events passing either the K2π or the Kµ3 criteria: the acceptance of the joint selection is the sum of the acceptances of the two mutually exclusive individual selections. The K± →π±π0π0 (K3π) decay is considered as a background in the Kµ3 sample. The Dalitz decays K2πD and Kµ3D are selected excluding the DP mass cut from the selection criteria. The number of events passing the selection criteria (taking into account cross-feeding between decay modes) are listed in Table 2 together with the relative acceptances. 4.1 Event selection The number of π0 D candidates reconstructed with the joint Dalitz decay selection is 1.69 × 107. In addition to the individual DP selections for K2π and Kµ3 decays, a joint DP selection is considered for events passing either the K2π or the Kµ3 criteria: the acceptance of the joint selection is the sum of the acceptances of the two mutually exclusive individual selections. The K± →π±π0π0 (K3π) decay is considered as a background in the Kµ3 sample. The Dalitz decays K2πD and Kµ3D are selected excluding the DP mass cut from the selection criteria. The number of events passing the selection criteria (taking into account cross-feeding between decay modes) are listed in Table 2 together with the relative acceptances. The number of π0 D candidates reconstructed with the joint Dalitz decay selection is 1.69 × 107. 6 6 , 05022 (2017) 137 EPJ Web of Conferences DOI: 10.1051/ 713705022 epjconf/201 XIIth Quark Confinement & the Hadron Spectrum ) 2 (MeV/c π 2 m 400 420 440 460 480 500 520 540 560 580 600 2 Events / (1 MeV/c 1 10 2 10 3 10 4 10 5 10 6 10 selection: D π 2 K Data D 0 π ± π → ± K ν ± µ D 0 π → ± K ) 2 (MeV/c ee m 0 20 40 60 80 100 120 2 Events / (1 MeV/c 1 10 2 10 3 10 4 10 5 10 6 10 selection: D π 2 K Data D 0 π ± π → ± K ν ± µ D 0 π → ± K ) 4 /c 2 (GeV 2 miss m -0.03 -0.02 -0.01 0 0.01 0.02 0.03 0.04 ) 4 /c 2 GeV 4 − 10 × Events / (5 3 10 4 10 5 10 selection: 3D µ K Data ν ± µ D 0 π → ± K D 0 π ± π → ± K D 0 π 0 π ± π → ± K ) 2 (MeV/c ee m 0 20 40 60 80 100 120 ) 2 Events / (1 MeV/c 1 10 2 10 3 10 4 10 5 10 selection: 3D µ K Data ν ± µ D 0 π → ± K D 0 π ± π → ± K D 0 π 0 π ± π → ± K Figure 4. 4.1 Event selection ) 2 (MeV/c ee m 0 20 40 60 80 100 120 2 Events / (1 MeV/c 1 10 2 10 3 10 4 10 5 10 6 10 selection: D π 2 K Data D 0 π ± π → ± K ν ± µ D 0 π → ± K ) 2 (MeV/c ee m 0 20 40 60 80 100 120 ) 2 Events / (1 MeV/c 1 10 2 10 3 10 4 10 5 10 selection: 3D µ K Data ν ± µ D 0 π → ± K D 0 π ± π → ± K D 0 π 0 π ± π → ± K ents passing the K2πD (top row) and Kµ3D (bottom row) ) 2 (MeV/c ee m 0 20 40 60 80 100 120 2 Events / (1 MeV/c 1 10 2 10 3 10 4 10 5 10 6 10 selection: D π 2 K Data D 0 π ± π → ± K ν ± µ D 0 π → ± K ) 2 (MeV/c ee m 0 20 40 60 80 100 120 1 10 ) 2 (MeV/c ee m 0 20 40 60 80 100 120 ) 2 Events / (1 MeV/c 1 10 2 10 3 10 4 10 5 10 selection: 3D µ K Data ν ± µ D 0 π → ± K D 0 π ± π → ± K D 0 π 0 π ± π → ± K ) 2 (M V/ 00 420 440 460 480 500 520 540 560 580 600 ) 2 (MeV/c π 2 m 400 420 440 460 480 500 520 540 560 580 600 1 ) 4 /c 2 GeV 4 − 10 × Events / (5 10 10 ) 2 Events / (1 MeV/c 10 10 ) 4 /c 2 (GeV 2 miss m -0.03 -0.02 -0.01 0 0.01 0.02 0.03 0.04 ) 4 /c 2 GeV 4 − 10 × Events / (5 3 10 4 10 5 10 selection: 3D µ K Data ν ± µ D 0 π → ± K D 0 π ± π → ± K D 0 π 0 π ± π → ± K Figure 4. Invariant mass distribution of data and MC events passing the K2πD (top row) and Kµ3D (bottom row) selections. Vertical arrows indicate the signal mass regions. 4.1 Event selection A DP signal would appear as a spike in the mee distributions shown in the right column. Figure 4 shows the reconstructed invariant mass spectra for data and MC events passing the Dalitz decay selection: MC samples [21] are normalized to the data using the estimated number NK of total K± decays in the fiducial decay region (NK = (1.57 ± 0.05) × 1011). 4.1 Event selection Invariant mass distribution of data and MC events passing the K2πD (top row) and Kµ3D (bottom row) selections. Vertical arrows indicate the signal mass regions. A DP signal would appear as a spike in the mee distributions shown in the right column. 4.2 Search for dark photon signal ) 2 (MeV/c A’ m 20 40 60 80 100 120 A’) at 90% CL γ → 0 π UL for B( 0 0.5 1 1.5 2 2.5 3 -6 10 × ) 2 (MeV/c A’ m 20 40 60 80 100 120 DP signal local significance -3 -2 -1 0 1 2 3 Figure 5. Left: Estimated local significance of the DP signal for each DP mass value mA′: neighbouring values are strongly correlated since the mass step of the scan is about 6 times smaller than the signal window width. Right: UL at 90% CL on B(π0 →γA′) for each mA′ value. The upper limits at 90% CL on the mixing parameter ε2 for each DP mass value are calculated from the B(π0 →γA′) upper limits using Eq.(3). They are compared in Fig. 6 to other published exclusion limits [23–29]. Also shown in the figure are the band in the (mA′, ε2) plane where the discrepancy between the measured and calculated muon (g −2)µ values falls into the ±2σ range and the region excluded by the electron (g −2)e measurement [19, 30, 31]. The upper limits at 90% CL on the mixing parameter ε2 for each DP mass value are calculated from the B(π0 →γA′) upper limits using Eq.(3). They are compared in Fig. 6 to other published exclusion limits [23–29]. Also shown in the figure are the band in the (mA′, ε2) plane where the discrepancy between the measured and calculated muon (g −2)µ values falls into the ±2σ range and the region excluded by the electron (g −2)e measurement [19, 30, 31]. This result improves the existing UL on the mixing parameter ε2 in the mA′ range 9 −70MeV/c2. In combination with other experimental limits and under the assumption that the DP couples to quarks and mainly decays into SM fermions, this result rules out the DP as possible explanation for the muon (g −2)µ anomaly. The sensitivity on the prompt A′ search is limited by the irreducible π0 D background. Furthermore, since the achievable UL on ε2 scales as the inverse of the square root of the integrated beam flux, only modest improvements using the presented technique are expected with future larger K± samples. 4.2 Search for dark photon signal A scan for a DP signal is performed in the mass range 9MeV/c2 ≤mA′ < 120MeV/c2, where the lower boundary is determined by the limited accuracy of the π0 D background simulation at low mee. For DP masses approaching the upper limit of the mass range the sensitivity to the DP mixing parameter ε2 is not competitive with the existing limits due to the kinematic suppression of the π0 →γA′ decay. For each of the 404 considered DP masses, the number of observed data event Nobs passing the joint 7 , 05022 (2017) 137 EPJ Web of Conferences XIIth Quark Confinement & the Hadron Spectrum , 05022 (2017) 137 EPJ Web of Conferences XIIth Quark Confinement & the Hadron Spectrum DOI: 10.1051/ 713705022 epjconf/201 DP selection is compared to the estimated number of background events Nexp evaluated from MC simulations. The local statistical significance of the DP signal for each mass hypothesis, shown in Fig. 5(Le ft), never exceeds 3σ, therefore no DP signal is observed. Upper limits (UL) at 90% CL on the number of DP candidates NDP for each mass value are computed from Nobs, Nexp and δNexp using the frequentist Rolke-Lopez method [22], while the upper limits at 90% CL on the branching fraction B(π0 →γA′), shown in Fig. 5(Right), are computed under the assumption that B(A′ →e+e−) = 1 (which is a good approximation for mA′ < 2mµ if A′ decays to SM fermions only). Details about the UL computation can be found in Ref. [21]. ) 2 (MeV/c A’ m 20 40 60 80 100 120 DP signal local significance -3 -2 -1 0 1 2 3 ) 2 (MeV/c A’ m 20 40 60 80 100 120 A’) at 90% CL γ → 0 π UL for B( 0 0.5 1 1.5 2 2.5 3 -6 10 × Figure 5. Left: Estimated local significance of the DP signal for each DP mass value mA′: neighbouring values are strongly correlated since the mass step of the scan is about 6 times smaller than the signal window width. Right: UL at 90% CL on B(π0 →γA′) for each mA′ value. 5 Conclusions The NA62 experiment has performed a preliminary measurement of the π0 electromagnetic TFF in the time-like region of momentum transfer from a sample of about one million fully reconstructed π0 D 8 , 05022 (2017) 137 EPJ Web of Conferences DOI: 10.1051/ 713705022 epjconf/201 XIIth Quark Confinement & the Hadron Spectrum ) 2 (MeV/c A’ m 10 2 10 -7 10 -6 10 -5 10 NA48/2 ) σ (3 e 2) − (g µ 2) − (g APEX A1 HADES KLOE WASA E141 E774 BaBar 2ε Figure 6. Upper limits at 90% CL on the mixing parameter ε2 versus the DP mass mA′: the NA48/2 result is compared to other published exclusion limits. ) 2 (MeV/c A’ m 10 2 10 -7 10 -6 10 -5 10 NA48/2 ) σ (3 e 2) − (g µ 2) − (g APEX A1 HADES KLOE WASA E141 E774 BaBar 2ε ) 2 (MeV/c A’ m 10 2 10 -7 10 -6 10 -5 10 NA48/2 ) σ (3 e 2) − (g µ 2) − (g APEX A1 HADES KLOE WASA E141 E774 BaBar 2ε 10 Figure 6. Upper limits at 90% CL on the mixing parameter ε2 versus the DP mass mA′: the NA48/2 result is compared to other published exclusion limits. decays collected in 2007. The preliminary result a = (3.70 ± 0.64) × 10−2, the most precise to date, is compatible with theoretical expectations and consistent with the previous measurements. A search for dark photon A′ produced in the π0 →γA′ decay followed by the prompt A′ →e+e− decay has been performed by the NA48/2 experiment from a sample of about 1.7 × 107 reconstructed π0 D candidates, using data collected in 2003-2004. No DP signal is observed: the final NA48/2 result [21] gives the most stringent upper limits on the mixing parameter ε2 in the A′ mass range 9 −70MeV/c2. References [1] J.R. Batley et al., Eur. Phys. J. C52 875 (2007) [1] J.R. Batley et al., Eur. Phys. J. C52 875 (2007) [2] V. Fanti et al., Nucl.Instrum.Meth. A574 433 (2007) [2] V. Fanti et al., Nucl.Instrum.Meth. A574 433 (2007) [3] A. Nyffeler Phys. Rev.D94 053006 (2016) [4] C. Patrignani et al (Particle Data Group), Chin. Phys.C40 100001 (2016) [4] C. Patrignani et al (Particle Data Group), Chin. Phys.C40 100 [5] M. Gell-Mann and F. Zachariasen Phys. Rev. 124 953 (1961) [5] M. Gell-Mann and F. Zachariasen Phys. Rev. 124 953 (1961) [6] P. Lichard Phys. Rev. D83 037503 (2011) [7] K. Kampf et al. 2006 Eur. Phys. J. C46 191 (2006) [7] K. Kampf et al. 2006 Eur. Phys. J. C46 191 (2006) [8] P. Masjuan, Phys. Rev.D86 094021 (2012) [8] P. Masjuan, Phys. Rev.D86 094021 (2012) [9] M. Hoferichter et al., Eur. Phys. J. C74 3180 (2014) [9] M. Hoferichter et al., Eur. Phys. J. C74 3180 (2014) [10] T. Husek and S. Leupold Eur. Phys. J. C75 586 (2015) [10] T. Husek and S. Leupold Eur. Phys. J. C75 586 (2015) [11] B.E. Lautrup and J.Smith Phys. Rev. D3 1122 (1971) [11] B.E. Lautrup and J.Smith Phys. Rev. D3 1122 (1971) [12] K.O. Mikaelian and J.Smith Phys. Rev. D5 1763 (1972) [12] K.O. Mikaelian and J.Smith Phys. Rev. D5 1763 (1972) [13] T. Husek et al., Phys. Rev. D92 054027 (2015) [13] T. Husek et al., Phys. Rev. D92 054027 (2015) [14] J. Fisher et al., Phys. Lett. B73 359 (1978) [14] J. Fisher et al., Phys. Lett. B73 359 (1978) [15] H. Fonvieille et al., Phys. Lett. B233 65 (1989) [15] H. Fonvieille et al., Phys. Lett. B233 65 (1989) 9 , 05022 (2017) 137 EPJ Web of Conferences XIIth Quark Confinement & the Hadron Spectrum , 05022 (2017) 137 EPJ Web of Conferences DOI: 10.1051/ 713705022 epjconf/201 [16] R. Meijer Drees et al., Phys. Rev.D45 1439 (1992) [17] H. Farzanpay et al., Phys. Lett. B278 413 (1992) [18] B. Holdom, Phys. Lett. B166 196 (1986) [19] M. Pospelov, Phys. Rev. D80 095002 (2009) [20] B.Batell et al., Phys. Rev. D80 095024 (2009) [21] J.R. Batley et al., Phys. Lett. B746 178 (2015) [22] W.A. Rolke and A.M. Lopez, Nucl.Instrum.Meth. A458 745 (2001) [23] S. Andreas et l., Phys. Rev. D86 095019 (2012) [24] D. Babusci et al., Phys. Lett. B720 111 (2013) [25] P. References Adlarson et al., Phys. Lett. B726 187 (2013) [26] G. Agakishev et al., Phys. Lett. B731 265 (2014) [27] H. Merkel et al., Phys. Rev. Lett 112 221802 (2014) [28] S. Abrahamyan et al., Phys. Rev. Lett 107 191804 (2011) [29] J.P. Lees et al., Phys. Rev. Lett 113 201801 (2014) [30] M. Endo et l., Phys. Rev. D86 095029 (2012) [31] H. Davoudiasl et l., Phys. Rev. D89 095006 (2014) [16] R. Meijer Drees et al., Phys. Rev.D45 1439 (1992) [17] H. Farzanpay et al., Phys. Lett. B278 413 (1992) [18] B. Holdom, Phys. Lett. B166 196 (1986) [19] M. Pospelov, Phys. Rev. D80 095002 (2009) [20] B.Batell et al., Phys. Rev. D80 095024 (2009) [21] J.R. Batley et al., Phys. Lett. B746 178 (2015) [22] W.A. Rolke and A.M. Lopez, Nucl.Instrum.Meth. A458 745 (2001) [23] S. Andreas et l., Phys. Rev. D86 095019 (2012) [24] D. Babusci et al., Phys. Lett. B720 111 (2013) [25] P. Adlarson et al., Phys. Lett. B726 187 (2013) [26] G. Agakishev et al., Phys. Lett. B731 265 (2014) [27] H. Merkel et al., Phys. Rev. Lett 112 221802 (2014) [28] S. Abrahamyan et al., Phys. Rev. Lett 107 191804 (2011) [29] J.P. Lees et al., Phys. Rev. Lett 113 201801 (2014) [30] M. Endo et l., Phys. Rev. D86 095029 (2012) [31] H. Davoudiasl et l., Phys. Rev. D89 095006 (2014) [16] R. Meijer Drees et al., Phys. Rev.D45 1439 (1992) [16] R. Meijer Drees et al., Phys. Rev.D45 1439 (1992) [18] B. Holdom, Phys. Lett. B166 196 (1986) [19] M. Pospelov, Phys. Rev. D80 095002 (2009) [20] B.Batell et al., Phys. Rev. D80 095024 (2009) [25] P. Adlarson et al., Phys. Lett. B726 187 (2013) [26] G. Agakishev et al., Phys. Lett. B731 265 (2014) [27] H. Merkel et al., Phys. Rev. Lett 112 221802 (2014) [28] S. Abrahamyan et al., Phys. Rev. Lett 107 191804 (2011) [28] S. Abrahamyan et al., Phys. Rev. Lett 107 191804 (2011 [29] J.P. Lees et al., Phys. Rev. Lett 113 201801 (2014) [29] J.P. Lees et al., Phys. Rev. Lett 113 201801 (2014) [30] M. Endo et l., Phys. Rev. D86 095029 (2012) [30] M. Endo et l., Phys. Rev. D86 095029 (2012) [31] H. Davoudiasl et l., Phys. Rev. D89 095006 (2014) [31] H. Davoudiasl et l., Phys. Rev. D89 095006 (2014) [31] H. Davoudiasl et l., Phys. Rev. D89 09 10
https://openalex.org/W2801376260
https://pubs.rsc.org/en/content/articlepdf/2018/ra/c8ra01408f
English
null
A detailed atomistic molecular simulation study on adsorption-based separation of CO<sub>2</sub> using a porous coordination polymer
RSC advances
2,018
cc-by
6,917
aInstitute of Chemistry, National Autonomous University of Mexico, Circuito Exterior, Ciudad Universitaria, Delegaci´on Coyoac´an C.P. 04510, Mexico City, Mexico. E-mail: pzarabadip@gmail.com; tomasrocharinza@gmail.com bCEITEC - Central European Institue of Technology, Masaryk University, Kamenice 5, CZ-62500 Brno, Czechia. E-mail: pezhman.zarabadi@ceitec.muni.cz RSC Advances RSC Advances Cite this: RSC Adv., 2018, 8, 14144 Received 13th February 2018 Accepted 5th April 2018 DOI: 10.1039/c8ra01408f rsc.li/rsc-advances PAPER on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. ed under a Creative Commons Attribution 3.0 Unported Licence. Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:4 This article is licensed under a Creative Commons Attribution 3.0 U Emission of CO2 is considered as one of the sources of global warming. Besides its currently inevitable production via several processes such as fuel consumption, it also exists in some other gaseous mixtures like biogas. Separation of carbon dioxide using solid adsorbents, for example porous coordination polymers and metal–organic frameworks, is an interesting active area of separation science. In particular, we performed detailed molecular simulations to investigate the response of a recently reported cobalt- based, pillared-layer, porous polymer on the CO2 separation from biogas, natural gas, and flue gas. The effect of the coordinated water molecules to the open metal sites on the corresponding properties was studied and revealed enhanced results even in comparison with HKUST-1. Additionally, our results provide insights on the role of –NO2 groups on the applications examined herein. Overall this study offers valuable insights about secondary building units of the examined materials which we expect to prove useful in the enhancement of carbon dioxide separation and capture. Received 13th February 2018 Accepted 5th April 2018 DOI: 10.1039/c8ra01408f rsc.li/rsc-advances these adsorbents can be achieved by reducing the pressure or elevating the temperature, i.e., Pressure-Swing Adsorption (PSA) and Temperature-Swing Adsorption (TSA), respectively. The particular case of PSA, in which its desorption pressure goes below z1 bar, is called Vacuum-Swing Adsorption (VSA) and it is useful when pressurising the feed stream is not applicable.7 Since the past decade, the usage of solid adsorbents has attracted a considerable amount of attention in several appli- cations. Metal–organic Frameworks (MOFs), a family of Porous Coordination Polymers (PCP), have served many purposes such as gas storage8 and separation9–12 together with catalysis13,14 and different uses in biomedicine15 due to their fascinating struc- tural properties like high surface area, porosity, thermal and chemical stability, and low density. MOFs became more inter- esting than zeolites and carbon-based solid adsorbents because these frameworks provide great exibility through modular synthesis approach which creates the opportunity of producing materials with desired physical and chemical properties.16 This journal is © The Royal Society of Chemistry 2018 A detailed atomistic molecular simulation study on adsorption-based separation of CO2 using a porous coordination polymer Cite this: RSC Adv., 2018, 8, 14144 Pezhman Zarabadi-Poor *ab and Tom´as Rocha-Rinza *a and Tom´as Rocha-Rinza *a di-Poor *ab and Tom´as Rocha-Rinza *a Introduction Carbon dioxide is known as one of the greenhouse gases which is emitted to the atmosphere in many different circumstances such as fuel consumption, and aer that, it contributes to global warming. It can be present in several gas mixtures including biogas, natural gas, and post-combustion ue gas. Consequently, carbon capture and separation have raised signicant interest in academia and industry. More specically, it is of paramount importance to nd plausible approaches to reduce the risks of carbon dioxide emission.1 When it comes to separation of CO2 from mixtures with other gases such as CH4 and N2, there are three main kind of materials used to overcome this task: solvent absorbers, membranes, and solid adsorbents.2 There are, of course, pros and cons for each method. Although amine solvents such as monoethanolamine have been used for more than 60 years, these methods suffer from signicant energy demands for the regeneration step.3,4 On the other hand, despite the high selectivities and low energy requirements associated to the use of membranes, these processes are not the best choice for mixtures with low CO2 partial pressure.5,6 However, the last- mentioned approach started to be used widely because of the development of novel porous adsorbents. The regeneration of There are several parameters that have proved relevant for the ability of PCPs and MOFs in the adsorption of carbon dioxide. One of these variables is the presence of Open Metal Sites (OMS). When one synthesizes MOFs through the combi- nation of metal centres as Secondary Building Units (SBU) and organic linkers,16 solvent molecules, e.g. H2O, coordinate to the metal atoms of SBU and occupy the coordination sphere. However, the effect of this binding of solvent molecules (espe- cially water) on the adsorption and separation ability of these materials has not been clearly established. On the one hand, there are investigations that suggest removal of coordination water molecules results in an increase of carbon dioxide capture This journal is © The Royal Society of Chemistry 2018 14144 | RSC Adv., 2018, 8, 14144–14151 Paper a precision of 1  106 in modeling long-range electrostatic interactions. The Lorentz–Berthelot mixing rules19 were used to calculate the cross-term L-J parameters between atoms i and j as a precision of 1  106 in modeling long-range electrostatic interactions. Introduction The Lorentz–Berthelot mixing rules19 were used to calculate the cross-term L-J parameters between atoms i and j as due to the availability of a larger number of OMS to interact with this gas, while on the other hand, there are reports such as the study of Yazaydin that indicates that the presence of coordi- nation water molecules can improve CO2 adsorption.17 sij ¼ si þ sj 2 ; 3ij ¼ ffiffiffiffiffiffiffi 3i3j p : (2) Thus, we took the endeavour to determine the role of water molecules in the CO2 absorption of MOFs to obtain useful information for the design and synthesis of new systems utilized for carbon dioxide separation. For this purpose, we considered a novel pillared-layered network of Co-nitro- imidazolate-dicarboxylate.18 Because this material exhibits channels and large cages, the authors also studied its gas uptake behaviour which presented promising results. This structure attracted our attention for further studies because it has water molecules coordinated to the SBU. We were also interested in testing the idea suggested by Guo et al.18 about the enhancement of CO2 uptake in virtue of the inclusion of nitro groups in these structures. Specically, we studied: (2) Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. The L-J parameters for framework atoms appart from Co atoms (UFF23) were taken from the Dreiding generic force eld24 and are presented in Table 1. The atomic partial charges of MOF structures were calculated by using the extended charge equil- ibration method developed by Wilmer et al.25 We used 10  10  10 unit cells to ensure that we included enough atoms in the charge calculation process to obtain accurate results and equal values of q on symmetry identical centres. The adsorbate molecules were modelled using the Siepmann's Transferable Potentials for Phase Equilibria Family of Force Fields (TraPPE). We considered the methane molecules as spherical non- charged particles26 which has already been compared with a 5- site model and proven to produce accurate results.27 We described the CO2 and N2 units as three-site rigid species28 (Table 1).  The detailed single component adsorption behaviour of the hydrated and dehydrated forms of the Co-nitroimidazolate- dicarboxylate based MOF discussed above denoted as 1 and 10, respectively.  The adsorption and separation of CO2 from gas mixtures representing biogas, natural gas, and ue gas. Simulation details Gas adsorption isotherms were simulated via the Grand Canonical Monte Carlo (GCMC)19,20 ensemble as implemented in the package Raspa.21 The atomic positions of the structures considered in this work were taken from X-ray single crystal CIF18 les and kept constant during the simulations. The coordination water molecules were carefully located and removed from the original CIF using CrystalMaker™(ref. 22) to have a model for the completely evacuated structure. The non- bonded interactions between gaseous species and MOF atoms were described using a Lennard-Jones (L-J) 12-6 potential with no tail correction and a cut-offvalue of 12.0 ˚A. We also considered the Coulomb potential term for electrostatic inter- actions, into the expression Table 1 UFF, DREIDING, and TraPPE forcefield parameters used for the molecular simulations performed in this investigation Atom type 3 (K) s (˚A) Co 7.04 2.56 C 47.86 3.47 O 48.16 3.03 N 38.95 3.26 H 7.65 2.85 CO2(C) 27.00 2.80 CO2(O) 79.00 3.05 N2(N) 36.00 3.31 N2(COM) 0.00 0.00 CH4 148.00 3.73 RSC Adv., 2018, 8, 14144–14151 | 14145 g g y ( ) have a model for the completely evacuated structure. The non- bonded interactions between gaseous species and MOF atoms were described using a Lennard-Jones (L-J) 12-6 potential with no tail correction and a cut-offvalue of 12.0 ˚A. We also considered the Coulomb potential term for electrostatic inter- actions, into the expression Uij ¼ 43ij "sij rij 12  sij rij 6# þ qiqj 4p30rij ; (1) in which i and j are interacting atoms, rij denotes the distance between these species, sij and 3ij indicate the corresponding L-J potential parameters, and qk is the partial charge of atom k. Introduction We choose these mixtures because they represent important systems from an industrial and academic perspective. The N2 molecule was represented by an L-J core at the center of mass (COM) with a point charge equal to 2q in which q ¼ 0.482. The simulation box dimensions, i.e. N  N  N, were chosen considering that they should be higher than twice the above mentioned cut-offvalue to satisfy the minimum image convention. The gas adsorptions of single component and gas mixtures were simulated by considering 25 pressure points ranging from 0.001–100 bar to construct the adsorption isotherms and to have enough accurate results for curve tting purposes. The pressure values were converted to fugacities which were used throughout the simulations to impose the equilibration between the system and the external gas container using the Peng–Robinson equation of state. The simulations at each pressure point included 5  105 Monte Carlo (MC) cycles. The rst half was used for equilibration and the rest for the computation of the average of thermodynamical properties. An MC cycle consists of M steps, M being the greater of 20 and the number of molecules at the beginning of each given simulation points. Insertion, deletion, translation, and rotation moves We employed atomistic molecular simulations methods plus adsorption theories to obtain unary and binary adsorption isotherms and related parameters to check the performance of the adsorbents addressed herein. We obtained insightful results on the effect of nitro moieties and coordination water molecules which are expected to be valuable in the design and synthesis of novel PCPs/MOFs in the industrial upgrading of different CO2-containing gaseous mixtures. This journal is © The Royal Society of Chemistry 2018 Structures We extracted the relevant reported experimental CO2 uptakes at 298 K from ref. 18 and compared them with our simulation results in order to validate the aforementioned methods and parameters. The resulting correlation with R2 ¼ 0.9820 shows very good agreement between measured and calculated results (Fig. 2). However, the slight difference may come from the defects and impurities in experimental samples while we use perfect crystals for performing the simulations. Fig. 1 shows a representation of 1 and 10. Guo et al.18 indicated the occurrence of different channel types within the structures as follows:  Type I. They are the largest channels with no water mole- cules directly oriented toward the cavity of the framework.  Types II and III. These two kinds of channels are quite similar except that coordination water molecules are oriented towards the channels of sort III. Simulation details This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. We can observe that upon complete removal of coordination water molecules, all the properties shown in Table 2 (apart from the density) increase and consequently the evacuation of H2O can indeed inuence the adsorption properties of the materials under study. in which brackets represent ensemble averages, V stands for the potential energy, and N is the number of molecules. Simulation details We beneted from the Ewald summation technique with Table 1 UFF, DREIDING, and TraPPE forcefield parameters used for the molecular simulations performed in this investigation Atom type 3 (K) s (˚A) Co 7.04 2.56 C 47.86 3.47 O 48.16 3.03 N 38.95 3.26 H 7.65 2.85 CO2(C) 27.00 2.80 CO2(O) 79.00 3.05 N2(N) 36.00 3.31 N2(COM) 0.00 0.00 CH4 148.00 3.73 This journal is © The Royal Society of Chemistry 2018 RSC Adv., 2018, 8, 14144–14151 | 14145 Table 1 UFF, DREIDING, and TraPPE forcefield parameters used for the molecular simulations performed in this investigation Uij ¼ 43ij "sij rij 12  sij rij 6# þ qiqj 4p30rij ; (1) (1) in which i and j are interacting atoms, rij denotes the distance between these species, sij and 3ij indicate the corresponding L-J potential parameters, and qk is the partial charge of atom k. We beneted from the Ewald summation technique with This journal is © The Royal Society of Chemistry 2018 View Article Online RSC Advances Paper  Type IV. This class of channel is aligned towards the z direction and includes the nitro moieties within pores.  Type IV. This class of channel is aligned towards the z direction and includes the nitro moieties within pores. were used in all GCMC calculations. In addition, we utilized identity changes in the simulations of gaseous binary mixtures. were used in all GCMC calculations. In addition, we utilized identity changes in the simulations of gaseous binary mixtures. The molar composition of binary mixtures, i.e., biogas, natural and ue gas, are CO2 : CH4 (0.5 : 0.5), CO2 : CH4 (0.1 : 0.9), and CO2 : N2 (0.1 : 0.9), respectively. The isosteric heat of adsorp- tion, Qst was calculated based on the uctuation method,29 that is, with the formula  Type V. These channels are similar to Type IV but without nitro groups.  Type V. These channels are similar to Type IV but without nitro groups. This identication of channels within the structures makes clear that the removal of water will mainly inuence Type III. We also used the poreblazer algorithm30 to calculate the phys- ical properties of both 1 and 10. The corresponding results are reported in Table 2. Qst ¼ RT  hVN〉 hV〉hN〉 hV2〉 hN2〉 ; (3) (3) Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. Single component adsorption isotherms Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47 This article is licensed under a Creative Commons Attribution 3.0 Unp Fig. 2 Experimental and simulated CO2 uptakes on 1 at 298 K. Fig. 4 Calculated CO2, CH4, and N2 isosteric heats of adsorption on 1 and 10 at 298 K. Fig. 3 Simulated adsorption isotherms of CO2, CH4, and N2 on 1 and 10 at 298 K. Carbon dioxide exhibits the strongest affinity for the avail- able adsorption sites with its isosteric heat of adsorption being almost 10–15 kJ mol1 higher than those for CH4 and N2. We see that Qst(CO2) in 10 exhibits a different behavior as compared to that observed in 1. The carbon dioxide heat of adsorption decays in the dehydrated system up to loadings corresponding to 1 bar pressure (i.e., 48 CO2 molecule per unit cell which contains 56 cobalt atoms, in an almost 1 : 1 ratio). Therefore, it again can be concluded that the OMS play a relevant role in the OMS increases CO2 adsorption but do not rise N2 uptake. These differences can be related to the large quadrupole moment of carbon dioxide as compared with that of nitrogen. To get further insights into the interaction nature of these gases with the studied frameworks, we monitored the isosteric heat of adsorption and host–adsorbate interaction energies as shown in Fig. 4 and 5. The decreasing order of Qst for the different gases is: Qst(CO2) > Qst(CH4) > Qst(N2) (4) Fig. 5 Interaction energies of CO2, N2, and CH4 with 1 and 10 as computed with eqn (1). Fig. 3 Simulated adsorption isotherms of CO2, CH4, and N2 on 1 and 10 at 298 K. ese t of ese eric s as the (4) Fig. 5 Interaction energies of CO2, N2, and CH4 with 1 and 10 as computed with eqn (1). d 10 Fig. 3 Simulated adsorption isotherms of CO2, CH4, and N2 on 1 and 10 at 298 K. OMS increases CO2 adsorption but do not rise N2 uptake. These differences can be related to the large quadrupole moment of carbon dioxide as compared with that of nitrogen. Single component adsorption isotherms Fig. 1 Structure representation of 1 (up) and 10 (down). The used color code is as follows; dark grey: carbon, light grey: hydrogen, blue cobalt, green: nitrogen, red: framework oxygen. The violet-dashed ellipse highlights the coordinated water oxygen. The different channe types are shown with Roman numerals. We rst consider the single component adsorption isotherms of CO2, CH4 and N2 on 1 and 10 shown in Fig. 3. We see that the complete removal of coordination water molecules from the metal centre resulted in a signicant improvement of the carbon dioxide uptake. This effect evidences the role of OMS in CO2 adsorption. Moreover, we also note two remarkable trends concerning the adsorption isotherms of CH4 and N2:  The gas uptake of both gases is notably lower than that of CO2, and  The adsorption behaviour and capacity of methane and nitrogen do not change upon activation. Both observations suggest that 1 and 10 are promising materials for adsorption-based separation of CO2 from different gas mixtures containing nitrogen and methane as its uptake is signicantly higher than it is for the two last-mentioned gases. Furthermore,the CO2 uptake can be enhanced through removal of coordinated water molecules to the metal centres. We emphasise that both CO2 and N2 interact with the MOFs via Coulomb and van der Waals contacts and that the availability of Table 2 Physical properties of 1 and 10 (Vp: pore volume, SA: surface area, PLD: pore limiting diameter, LCD: largest cavity diameter) Structure Density (g cm3) Vp (cm3 g1) SA (m2 g1) PLD (˚A) LCD (˚A) 1 0.870 0.741 1587 5.74 8.38 10 0.806 0.855 2026 6.41 10.16 This journal is © The Royal Society of Chemistry 2018 Table 2 Physical properties of 1 and 10 (Vp: pore volume, SA: surface area, PLD: pore limiting diameter, LCD: largest cavity diameter) Fig. 1 Structure representation of 1 (up) and 10 (down). The used color code is as follows; dark grey: carbon, light grey: hydrogen, blue: cobalt, green: nitrogen, red: framework oxygen. The violet-dashed ellipse highlights the coordinated water oxygen. The different channel types are shown with Roman numerals. 14146 | RSC Adv., 2018, 8, 14144–14151 Fig. 4 Calculated CO2, CH4, and N2 isosteric heats of adsorption on 1 and 10 at 298 K. RSC Advances View Article Online View Article Online CO 298 Paper OMS increases CO2 adsorption but do not rise N2 uptake. Single component adsorption isotherms These differences can be related to the large quadrupole moment of carbon dioxide as compared with that of nitrogen. To get further insights into the interaction nature of these gases with the studied frameworks, we monitored the isosteric heat of adsorption and host–adsorbate interaction energies as shown in Fig. 4 and 5. The decreasing order of Qst for the different gases is: Carbon dioxide exhibits the strongest affinity for the avail- able adsorption sites with its isosteric heat of adsorption being almost 10–15 kJ mol1 higher than those for CH4 and N2. We see that Qst(CO2) in 10 exhibits a different behavior as compared to that observed in 1. The carbon dioxide heat of adsorption decays in the dehydrated system up to loadings corresponding to 1 bar pressure (i.e., 48 CO2 molecule per unit cell which contains 56 cobalt atoms, in an almost 1 : 1 ratio). Therefore, it again can be concluded that the OMS play a relevant role in the Fig. 4 Calculated CO2, CH4, and N2 isosteric heats of adsorption on 1 and 10 at 298 K. Fig. 2 Experimental and simulated CO2 uptakes on 1 at 298 K. Fig. 3 Simulated adsorption isotherms of CO2, CH4, and N2 on 1 and 10 at 298 K. Paper RSC Advances Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. RSC Advances RSC Advances OMS increases CO2 adsorption but do not rise N2 uptake. Thes differences can be related to the large quadrupole moment o carbon dioxide as compared with that of nitrogen. To get further insights into the interaction nature of thes gases with the studied frameworks, we monitored the isosteri heat of adsorption and host–adsorbate interaction energies a shown in Fig. 4 and 5. The decreasing order of Qst for th different gases is: Qst(CO2) > Qst(CH4) > Qst(N2) (4 Fig. 2 Experimental and simulated CO2 uptakes on 1 at 298 K. Fig. 3 Simulated adsorption isotherms of CO2, CH4, and N2 on 1 and at 298 K. Paper Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. ess Article. Single component adsorption isotherms To get further insights into the interaction nature of these gases with the studied frameworks, we monitored the isosteric heat of adsorption and host–adsorbate interaction energies as shown in Fig. 4 and 5. The decreasing order of Qst for the different gases is: (4) (4) Fig. 5 Interaction energies of CO2, N2, and CH4 with 1 and 10 as computed with eqn (1). Qst(CO2) > Qst(CH4) > Qst(N2) Qst(CO2) > Qst(CH4) > Qst(N2) This journal is © The Royal Society of Chemistry 2018 RSC Adv., 2018, 8, 14144–14151 | 14147 View Article Online RSC Advances Paper Fig. 6 Simulated binary adsorption isotherms of CO2, CH4 and N2 in biogas (CO2 : CH4, 0.5 : 0.5), natural gas (CO2 : CH4, 0.1 : 0.9), and flue g (CO2 : N2, 0.1 : 0.9) at 298 K. RSC Advances Pap Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Fig. 6 Simulated binary adsorption isotherms of CO2, CH4 and N2 in biogas (CO2 : CH4, 0.5 : 0.5), natural gas (CO2 : CH4, 0.1 : 0.9), and flue gas (CO2 : N2 0 1 : 0 9) at 298 K on isotherms of CO2, CH4 and N2 in biogas (CO2 : CH4, 0.5 : 0.5), natural gas (CO2 : CH4, 0.1 : 0.9), and flue gas Fig. 6 Simulated binary adsorption isotherms of CO2, CH4 and N2 in biogas (CO2 : CH4, 0.5 : 0.5), natural gas (CO2 : CH4, 0.1 : 0.9), and flue gas (CO2 : N2, 0.1 : 0.9) at 298 K. 9 kJ mol1 while the coulombic term lies below 1 kJ mol1 in the absence of OMS and increases up to unity upon activation. adsorption of CO2 up to 1 bar. We note that the OMSs are occupied above this pressure as the heat of adsorption becomes steady for both 1 and 10. Concerning the adsorption of CO2 in 1, this species exhibits L-J and coulombic interaction energies of 15 kJ mol1 and 4– 6 kJ mol1, respectively. Interestingly, when we remove the coordination water molecules, the L-J contribution decreases to 11–12 kJ mol1 while the coulombic component increases up to z20 kJ mol1. Single component adsorption isotherms This effect is consistent with the observations discussed above on the carbon dioxide isosteric heat of adsorption which decreases up to 8 kJ mol1 with the increase of loading. As shown in eqn (1), we are considering van der Waals and Coulomb terms for the interaction energy between two frag- ments. The examination of each term provides useful infor- mation on the nature of contact. The methane molecule has neither a permanent dipole nor quadrupole moment and thus we consider only the L-J contribution. We observe that the CH4– host interaction energy is about 12–13 kJ mol1 and it does not change by increasing the loading. This circumstance shows that methane adsorption sites are still available even at loadings which correspond to pressures as high as 5 bar. We also notice the same trend for nitrogen adsorption in both 1 and 10. The relevant van der Waals interaction energy is around 8– Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. CO2 uptake of 10 in all cases is higher than it is in 1 due to the availability of OMS in the former system. Carbon dioxide is less adsorbed in natural and ue gases because of the smaller amount of this component in these mixtures. Every studied material has, however, a similar behaviour concerning the adsorption of methane and nitrogen. Although the adsorption isotherms of mixtures are important in understanding the capacity of a given material for carbon dioxide capture and detachment, it is necessary to further analyse the calculated data to obtain more detailed insights on the capability of these materials for adsorption-based separation of CO2 from a given mixture. There are several parameters that we should consider for this purpose. For example, the CO2 selectivity of the adsorbent towards methane or nitrogen as obtained through the equation Table 3 shows that in all cases 1 presents much lower values in comparison with HKUST-1 but once we remove all solvent molecules, the parameters enhance siginicantly. The MOF 10 shows promising results for the separation of CO2 from biogas and natural gas through PSA processes. Likewise to HKUST-1, the availability of OMS results in a better interaction with carbon dioxide molecules. The best improvements occur in VSA conditions for biogas, i.e., case 3 in Table 3, which provides better performance even in comparison with HKUST-1. The values corresponding to this last statement are bolded in the same chart. The values of R indicate that slightly lower uptakes at VSA adsorption pressures, e.g., 1 bar, brings the possibility of an easier adsorption sites regeneration. However, the selectivity of 10 toward CO2 is most likely attributed to the higher uptake of carbon dioxide due to the presence of OMS, as indicated by the methane uptake at 1 bar which in both cases 2 and 3 is around 0.25 mmol g1, resulting in an almost doubled APS for 10. a12 ¼ x1 x2 y2 y1  ; (5) (5) where 1 stands for CO2 and 2 denotes CH4 or N2, x refers to the adsorbed amount in mmol g1 and y is the mole fraction in gas phase. We applied the selectivity formula on simulated mixture adsorption isotherms and report the outcome graphs in Fig. 6. Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. The presence of OMS and their previously mentioned inuence on the adsorption of CO2, especially in lower loadings, with 1 present steady values within the whole examined pressure range. The selectivity aCO2/CH4 for biogas and natural gas has almost a constant value at low loading while it decays faster in biogas due to the presence of more CO2 molecules. This condition results in a faster saturation of the available OMS. On the other hand, 10 has a twice higher initial selectivity for CO2 over N2 despite a larger amount of N2 molecules in the ue gas mixture. These observations might be related to the increas- ingly ordered kinetic diameter values of: CO2(3.30 ˚A) < N2 (3.64 ˚A) < CH4 (3.80 ˚A), a factor which can be advantageous for the carbon dioxide molecules to reach adsorption sites more easily than methane and nitrogen. This journal is © The Royal Society of Chemistry 2018 Adsorbate density maps Guo et al.18 suggested that the presence of nitro groups in Type IV channels might enhance CO2 adsorption. To test this state- ment, we investigated the density plots of CO2 and CH4 in 1 and 10 which are obtained using RASPA by dividing the unit cell into voxels and calculating the probability density of adsorbates in each voxel as shown in Fig. 7 and 8. The former plot shows that in both 1 and 10 CO2 molecules are adsorbed in Type III chan- nels. The only difference is that in the 1, carbon dioxide units interact with coordination water molecules whose removal e y n . t e e ) ) ) Table 3 Adsorbent evaluation parameters for 1, 10, and HKUST-1 2 Structure N1 (mmol g1) DN1 (mmol g1) R (%) a APS Case 1: natural gas (PSA) 1 1.04 0.77 74.0 5.4 4.1 10 2.30 1.38 60.0 10.8 14.9 HKUST-1 2.70 1.70 63.0 10.0 17.0 Case 2: biogas (PSA) 1 3.80 2.61 68.7 4.6 12.0 10 6.00 3.56 59.3 6.6 23.5 HKUST-1 8.01 5.34 66.7 4.9 26.2 Case 3: biogas (VSA) 1 1.19 1.05 88.2 4.9 5.1 10 2.44 1.88 77.0 9.8 18.4 HKUST-1 2.81 1.90 67.5 5.5 10.4 2( ) 2 ( .80 ˚A), a factor which can be advantageous for the ide molecules to reach adsorption sites more easily ne and nitrogen. selectivity, there are other parameters that have an ffect on the separation performance of adsorbents. Binary mixture adsorption We have discussed so far the adsorption of unary gases on 1 and 10. Now, we examine the adsorption behaviour of the gases This journal is © The Royal Society of Chemistry 2018 14148 | RSC Adv., 2018, 8, 14144–14151 RSC Advances View Article Online RSC Advances View Article Online RSC Advances View Article Online View Article Online Paper respectively. In eqn (6)–(8) N, 1, and 2 indicate uptake at adsorption (ads) or desorption (des) pressure, CO2, and (CH4 or N2) in the same order. addressed herein when they are mixed with each other. Although we could consider many combinations based on the molar fraction ratios and number of components, we investi- gated three mixtures which are representative of industrially relevant systems: biogas, natural and ue gases2 with the molar compositions mentioned at the end of the “Simulation Details” section. We simulated the adsorption isotherms of binary mixtures using the GCMC (Fig. 6). The occurrence of OMS leads to a signicant improvement in all the adsorption parameters apart from R. The values of this indicator decrease because of the strong interaction of CO2 with the 10 framework which impairs the removal of the adsorbed gases. However, this parameter is still in a reasonable range. We compare now our results with data of HKUST-1 (ref. 2) which is known as a reference MOF with a good performance in CO2 separation. RSC Adv., 2018, 8, 14144–14151 | 14149 Adsorbate density maps is co-workers summarized and introduced different scriptors2,31 such as the working capacity (DN), the ty factor (R) and the adsorption performance score are dened as DN1 ¼ Nads 1  Ndes 1 , (6) R ¼ DN1 N1   100; (7) APS ¼ (a12)  (DN1), (8) Table 3 Adsorbent evaluation parameters for 1, 10, and HKUST-1 2 Structure N1 (mmol g1) DN1 (mmol g1) R (%) a APS Case 1: natural gas (PSA) 1 1.04 0.77 74.0 5.4 4.1 10 2.30 1.38 60.0 10.8 14.9 HKUST-1 2.70 1.70 63.0 10.0 17.0 Case 2: biogas (PSA) 1 3.80 2.61 68.7 4.6 12.0 10 6.00 3.56 59.3 6.6 23.5 HKUST-1 8.01 5.34 66.7 4.9 26.2 Case 3: biogas (VSA) 1 1.19 1.05 88.2 4.9 5.1 10 2.44 1.88 77.0 9.8 18.4 HKUST-1 2.81 1.90 67.5 5.5 10.4 Table 3 Adsorbent evaluation parameters for 1, 10, and HKUST-1 2 Structure N1 (mmol g1) DN1 (mmol g1) R (%) a APS Table 3 Adsorbent evaluation parameters for 1, 10, and HKUST-1 2 Besides selectivity, there are other parameters that have an important effect on the separation performance of adsorbents. Snurr and his co-workers summarized and introduced different of these descriptors2,31 such as the working capacity (DN), the regenerability factor (R) and the adsorption performance score (APS) which are dened as Snurr and his co-workers summarized and introduced different of these descriptors2,31 such as the working capacity (DN), the regenerability factor (R) and the adsorption performance score (APS) which are dened as DN1 ¼ Nads 1  Ndes 1 , (6) R ¼ DN1 N1   100; (7) APS ¼ (a12)  (DN1), (8) 10 6.00 3.56 59.3 6.6 23.5 HKUST-1 8.01 5.34 66.7 4.9 26.2 Case 3: biogas (VSA) 1 1.19 1.05 88.2 4.9 5.1 10 2.44 1.88 77.0 9.8 18.4 HKUST-1 2.81 1.90 67.5 5.5 10.4 This journal is © The Royal Society of Chemistry 2018 Paper View Article Online View Article Online Paper RSC Advances RSC Advances Fig. 7 Density plots of CO2 in biogas within 1 (left) and 10 (right simulated at 298 K and 5 bar. ed under a Creative Commons Attribution 3.0 Unported Licence. We also explored the possible adsorption sites for methane molecules and found out that they are adsorbed in all of the types of examined channels except Type III. Adsorbate density maps Because (i) the interaction of methane with the framework occurs solely through van der Waals contacts, and (ii) the interacting atoms construct the skeleton of the framework, we propose to use SBU with higher affinity to CO2 as well as trying to provide OMS in the nal product to enhance carbon dioxide capture and separation. Finally, the comparison of the properties of 1 and 10 reveal that the differences in their performance for CO2 adsorption and separation can be understood in simple physical interac- tion terms and OMS. Our results indicate that the NO2 groups are not the adsorption sites for the CO2 molecules and hence polar functional groups are not to be held responsible for the different behaviour of the MOFs studied herein. Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM This article is licensed under a Creative Commons Attribution 3.0 Unported L Conclusions and prospects We performed detailed molecular simulations on a Co- nitroimidazolate-dicarboxylate pillared layered polymer and its water-removed structure to investigate the role of coordi- nated H2O molecules in adsorption-based separations of CO2. We concluded that the performance of the material is enhanced by removal of H2O molecules from the cobalt centres to make the secondary building units available to carry out the process. In addition, our results suggest the nitro groups has unimpor- tant effects on the adsorption and separation of carbon dioxide in opposition with the suggestion made in the original report of 1 concerning this matter. Altogether, we suggest that the overall performance of these materials can be enhanced by using SBU with a high affinity for CO2 and that the design should include a large number of open metal sites for the adsorption to take place. Fig. 7 Density plots of CO2 in biogas within 1 (left) and 10 (right) simulated at 298 K and 5 bar. provides the chance for more numerous and stronger interac- tions with cobalt open sites. The same holds true for natural and ue gases which have only a 0.1 molar ratio of CO2. provides the chance for more numerous and stronger interac- tions with cobalt open sites. The same holds true for natural and ue gases which have only a 0.1 molar ratio of CO2. provides the chance for more numerous and stronger interac- tions with cobalt open sites. The same holds true for natural and ue gases which have only a 0.1 molar ratio of CO2. Fig. 8 Density plots of CH4 in biogas within 1 (left) and 10 (right) simulated at 298 K and 5 bar. Acknowledgements The authors acknowledge nancial support from DGAPA/UNAM (project CJIC/CTIC/4721/2015) and computation time from DGTIC/UNAM (grant LANCAD-UNAM-DGTIC-250). P. Z. would like to thank the funding received from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie and it is co-nanced by the South Moravian Region under agreement No. 665860. This article reects only the author's view and the EU is not responsible for any use that may be made of the information it contains. P. Z. also thanks computational resources were provided by the CESNET LM2015042 and the CERIT Scientic Cloud LM2015085, provided under the program Projects of Large Research, Development, and Innovations Infrastructures. Fig. 8 Density plots of CH4 in biogas within 1 (left) and 10 (right) simulated at 298 K and 5 bar. This journal is © The Royal Society of Chemistry 2018 14150 | RSC Adv., 2018, 8, 14144–14151 View Article Online RSC Advances View Article Online Paper Paper RSC Advances 17 A. ¨O. Yazaydin, A. I. Benin, S. A. Faheem, P. Jakubczak, J. J. Low, R. R. Willis and R. Q. Snurr, Chem. Mater., 2009, 21, 1425–1430. Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. 4 A. L. Chaffee, G. P. Knowles, Z. Liang, J. Zhang, P. Xiao and P. A. Webley, Int. J. Greenhouse Gas Control, 2007, 1, 11–18. 4 A. L. Chaffee, G. P. Knowles, Z. Liang, J. Zhang, P. Xiao and 20 O. P. A. Partykiejew and S. Sokolowski, Surface and Interface Science: Solid-Gas Interface II, Wiley-VCH GmbH & Co. KGaA, Weinheim, 2016. , , g, J g, P. A. Webley, Int. J. Greenhouse Gas Control, 2007, 1, 11–18. 5 S. Choi, J. Drese and C. Jones, ChemSusChem, 2009, 2, 796– 854. 21 D. Dubbeldam, S. Calero, D. E. Ellis and R. Q. Snurr, Mol. Simul., 2015, 7022, 1–21. 6 D. D'Alessandro, B. Smit and J. Long, Angew. Chem., Int. Ed., 2010, 49, 6058–6082. 22 CrystalMaker: a crystal and molecular structures program for Mac and Windows; version 9.2.9, https:// www.crystalmaker.com. 7 R. T. Yang, Gas Separation by Adsorption Processes, Butter- worth, Boston, 1987. 23 A. K. Rappe, C. J. Casewit, K. S. Colwell, W. A. Goddard III and W. M. Skiff, J. Am. Chem. Soc., 1992, 114, 10024–10035. 8 J. L. C. Rowsell and O. M. Yaghi, Angew. Chem., Int. Ed., 2005, 44, 4670–4679. 24 S. L. Mayo, B. D. Olafson and W. A. Goddard, J. Phys. Chem., 1990, 101, 8897–8909. 9 S. Keskin, T. M. van Heest and D. S. Sholl, ChemSusChem, 2010, 3, 879–891. 25 C. E. Wilmer, K. C. Kim and R. Q. Snurr, J. Phys. Chem. Lett., 2012, 3, 2506–2511. 10 Y. C. Y. Wang, Z. Hu and D. Zhao, Ind. Eng. Chem. Res., 2017, 56, 4508–4516. 26 M. G. Martin and J. I. Siepmann, J. Phys. Chem. B, 1998, 102, 2569–2577. 11 E. J. L. Hamon and G. D. Pirngruber, Ind. Eng. Chem. Res., 2010, 49, 7497–7503. 27 L. Chen, L. Grajciar, P. Nachtigall and T. Duren, J. Phys. Chem. C, 2011, 115, 23074–23080. 12 S. Cavenati, C. A. Grande, A. E. Rodrigues, C. Kiener and U. Muller, Ind. Eng. Chem. Res., 2008, 47, 6333–6335. 28 J. J. Potoffand J. I. Siepmann, AIChE J., 2001, 47, 1676–1682. 13 J. Lee, O. K. Farha, J. Roberts, K. A. Scheidt, S. T. Nguyen and J. T. Hupp, Chem. Soc. Rev., 2009, 38, 1450–1459. 29 D. Nicholson and N. Parsonage, Computer Simulation and Statistical Mechanics of Adsorption, Academic Press, London, 1982. 14 E. Gkaniatsou, C. Sicard, R. Ricoux, J.-P. Mahy, N. Steunou and C. Serre, Mater. Horiz., 2017, 4, 55–63. This journal is © The Royal Society of Chemistry 2018 RSC Adv., 2018, 8, 14144–14151 | 14151 Notes and references 1 S. Chu, Science, 2009, 325, 1599. 18 X.-Q. Guo, M. Wang, Y.-F. Tang, F. Meng, G.-Q. Jiang and J.-L. Zhu, CrystEngComm, 2016, 18, 1768–1774. 2 Y.-S. Bae and R. Q. Snurr, Angew. Chem., Int. Ed., 2011, 50, 11586–11596. 3 H. Yang, Z. Xu, M. Fan, R. Gupta, R. B. Slimane, A. E. Bland and I. Wright, J. Environ. Sci., 2008, 20, 14–27. 19 M. P. Allen and D. J. Tildesley, Computer Simulation Of Liquids, Oxford Science Publications, Clarendon Press, 1987. Open Access Article. Published on 17 April 2018. Downloaded on 10/24/2024 5:47:29 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. 30 L. Sarkisov and A. Harrison, Mol. Simul., 2011, 37, 1248– 1257. 15 P. Horcajada, R. Gref, T. Baati, P. K. Allan, G. Maurin, P. Couvreur, G. Ferey, R. E. Morris and C. Serre, Chem. Rev., 2012, 112, 1232–1268. 31 Y. G. Chung, D. A. Gomez-Gualdron, P. Li, K. T. Leperi, P. Deria, H. Zhang, N. A. Vermeulen, J. F. Stoddart, F. You, J. T. Hupp, O. K. Farha and R. Q. Snurr, Sci. Adv., 2016, 2, e1600909. 16 J. L. C. Rowsell and O. M. Yaghi, Microporous Mesoporous Mater., 2004, 73, 3–14. RSC Adv., 2018, 8, 14144–14151 | 14151 This journal is © The Royal Society of Chemistry 2018
https://openalex.org/W2592687253
https://bmjopen.bmj.com/content/bmjopen/7/3/e012493.full.pdf
English
null
Retrospective observational study of emergency admission, readmission and the ‘weekend effect’
BMJ open
2,017
cc-by
5,452
Strengths and limitations of the study Objectives: Excess mortality following weekend hospital admission has been observed but not explained. As readmissions have greater age, comorbidity and social deprivation, outcomes following emergency index admission and readmission were examined for temporal and demographic associations to confirm whether weekend readmissions contribute towards excess mortality. ▪Previous studies have been unable to examine the impact of readmissions due to the challenge of data linkage for individual patients. ▪The data set was a continuous aggregate over 5 years within a stable service, thereby reducing the impact of structural changes on emergency admissions. Design: A retrospective observational study. Individual patient Hospital Episode Statistics were linked and 2 categories created: index admissions (not within 60 days of discharge from an emergency hospitalisation) and readmissions (within 60 days of discharge from an emergency hospitalisation). Logistic regression examined associations between admission category, weekend and weekday mortality, age, gender, season, comorbidity and social deprivation. ▪The primary outcome (death) was captured at 30 days, whether or not the patient was in hos- pital or the community. ▸Prepublication history and additional material is available. To view please visit the journal (http://dx.doi.org/ 10.1136/bmjopen-2016- 012493). admission,1–6 although this has not been uni- versal.7 8 The mechanism of this ‘weekend effect’ remains controversial, but could have important implications for the organisation and resourcing of emergency medical ser- vices. It has been proposed that the size and expertise of the weekend hospital workforce influences health outcomes,1 3 6 9 but expla- nations are obscured by the use of large administrative data sets from different geo- graphical and service settings, which are not linked to information about illness severity or the availability of clinicians and treatments inside and outside of secondary care. admission,1–6 although this has not been uni- versal.7 8 The mechanism of this ‘weekend effect’ remains controversial, but could have important implications for the organisation and resourcing of emergency medical ser- vices. It has been proposed that the size and expertise of the weekend hospital workforce influences health outcomes,1 3 6 9 but expla- Received 2 May 2016 Revised 12 October 2016 Accepted 16 December 2016 Setting: A single acute National Health Service (NHS) trust serving a population of 550 000 via 3 emergency departments. Participants: Emergency admissions between 1 January 2010 and 31 March 2015. Outcome measure: All-cause 30-day mortality. Results: Over 5 years there were 128 966 index admissions (74.7% weekday/25.3% weekend) and 20 030 readmissions (74.9% weekday/25.1% weekend). ABSTRACT To cite: Shiue I, McMeekin P, Price C. Retrospective observational study of emergency admission, readmission and the ‘weekend effect’. BMJ Open 2017;7:e012493. doi:10.1136/bmjopen-2016- 012493 To cite: Shiue I, McMeekin P, Price C. Retrospective observational study of emergency admission, readmission and the ‘weekend effect’. BMJ Open 2017;7:e012493. doi:10.1136/bmjopen-2016- 012493 Research Research Open Access Received 2 May 2016 Revised 12 October 2016 Accepted 16 December 2016 23, 2024 by guest. Protected by copyright. Conclusions: Associations with emergency hospitalisation were not identical for index admissions and readmissions. Further research is needed to confirm what factors are responsible for the ‘weekend effect’. uest. Protected by copyright. To cite: Shiue I, McMeekin P, Price C. Retrospective observational study of emergency admission, readmission and the ‘weekend effect’. BMJ Open 2017;7:e012493. doi:10.1136/bmjopen-2016- 012493 Strengths and limitations of the study Adjusted 30-day death rates for weekday/ weekend admissions were 6.93%/7.04% for index cases and 12.26%/13.27% for readmissions. Weekend readmissions had a higher mortality risk relative to weekday readmissions (OR 1.10 (95% CI 1.01 to 1.20)) without differences in comorbidity or deprivation. Weekend index admissions did not have a significantly increased mortality risk (OR 1.04 (95% CI 0.98 to 1.11)) but deaths which did occur were associated with lower deprivation (OR 1.24 (95% CI 1.11 to 1.38)) and an absence of comorbidities (OR 1.17 (1.02 to 1.34)). Conclusions: Associations with emergency hospitalisation were not identical for index admissions 1 January 2010 and 31 March 2015. Outcome measure: All-cause 30-day mortality. Results: Over 5 years there were 128 966 index admissions (74.7% weekday/25.3% weekend) and 20 030 readmissions (74.9% weekday/25.1% weekend). Adjusted 30-day death rates for weekday/ weekend admissions were 6.93%/7.04% for index cases and 12.26%/13.27% for readmissions. Weekend readmissions had a higher mortality risk relative to weekday readmissions (OR 1.10 (95% CI 1.01 to 1.20)) without differences in comorbidity or deprivation. Readmissions within 30 days have been observed to account for 7% of National Health Service (NHS) discharges and are more likely following recent emergency hos- pitalisation.10–12 Compared with index admis- sions, readmissions have characteristics associated with a higher risk of death, includ- ing greater age, comorbidity and social deprivation.11 12 As community services may have less flexibility in their response to unex- pected decompensation of health and social status over the weekend, we hypothesised in advance of data analysis that readmissions could contribute disproportionately towards weekend mortality through an increased risk of: (1) hospitalisation at a weekend; (2) death relative to index admissions and (3) death relative to weekday readmissions. If correct, this would infer that previous 1Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK 2Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK 3Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK Correspondence to Dr Christopher Price; C.I.M.Price@newcastle.ac.uk 1Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK 2Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK 3Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK Correspondence to Dr Christopher Price; C.I.M.Price@newcastle.ac.uk Retrospective observational study of emergency admission, readmission and the ‘weekend effect’ on October 23, 2024 by guest. Protected by copyright. http://bmjopen.bmj.com/ Open: first published as 10.1136/bmjopen-2016-012493 on 2 March 2017. Downloaded from Ivy Shiue,1 Peter McMeekin,2 Christopher Price3 Ivy Shiue,1 Peter McMeekin,2 Christopher Price3 INTRODUCTION Descriptions of survival in large unselected hospital populations have generally reported excess deaths specifically related to weekend Correspondence to Dr Christopher Price; C.I.M.Price@newcastle.ac.uk Shiue I, et al. BMJ Open 2017;7:e012493. doi:10.1136/bmjopen-2016-012493 1 Open Access attempts at case-mix correction were inadequate,1–6 and the weekend effect might also reflect an interaction between community and outpatient services, failure of initial treatments and advancing disease progression fol- lowing an index admission. an index event, and it was assumed that another admis- sion after 60 days was unrelated. Over the 5 years, patients could appear more than once in the index or readmission data set according to the timing of their attendances. If patients were readmitted more than once within 60 days of discharge from an index event, only the first readmission was included in the analysis. attempts at case-mix correction were inadequate,1–6 and the weekend effect might also reflect an interaction between community and outpatient services, failure of initial treatments and advancing disease progression fol- lowing an index admission. g Owing to the challenge of case linkage, previous reports have considered individual admissions rather than patient-level analysis, and were unable to examine the relevance of a second hospitalisation soon after dis- charge. Using linked patient-level data to isolate index admissions from readmissions, we examined associations with the outcome from emergency hospitalisation at a single large NHS healthcare provider over 5 years in order to confirm or refute the presence of a weekend effect and describe relevant sociodemographic characteristics. on October 23, 2024 by guest. Protected by copyright. http://bmjopen.bmj.com/ shed as 10.1136/bmjopen-2016-012493 on 2 March 2017. Downloaded from Weekend admissions were defined as arrival at ED any time from 00:00 on Saturday morning to 24:00 on Sunday night. There was no correction for bank holi- days. The Charlson Comorbidity Index (CCI)14 was cal- culated for each admission and the Index of Multiple Deprivation Score (IMDS)15 was derived from lower super output areas. The main outcome was all-cause 30-day mortality for patients with at least 1-day length of stay, although patients who died on the day of admission were still included in the numerator and denominator. The hospital administration system is routinely updated with the dates of inpatient and community deaths. Crude death rates were adjusted for age and gender. Descriptive statistics and χ2 test were used to describe and compare binary variables. Study setting and population Unscheduled admissions between 1 January 2010 and 31 March 2015 were identified in Hospital Episode Statistics from a single acute hospital trust serving a population of 550 000 via three emergency departments (EDs; table 1).13 The cohort included only ED admissions by ambulance, general practitioner (GP) or self-presentation but did not include hospital transfers or GP admissions directly to an inpatient area. The standard route for unscheduled primary care referrals was via ED. During this interval, unselected patients were admitted to each ED without prehospital redirection, apart from those with suspected myocardial infarction who were diverted to a regional cardiology centre according to ambulance service protocol. Twice daily consultant ward rounds took place on each admissions unit throughout the week and a crit- ical care outreach team was always available. p To allow for heteroscedasticity, SEs were estimated after clustering International Classification of Diseases (ICD)10 diagnoses into groups defined by Clinical Classifications Software (CCS).17 To explore case-mix variations, a second regression analysis examined associa- tions between death following weekend hospitalisation, admission category (index vs readmission), IMDS (top 25% vs bottom 75%) and CCI (0 vs at least 1). Analyses were carried out using SPSS V.22.0 (IBM; more details via http://www-01.ibm.com/software/analytics/spss/) and STATA V.14.0 (STATA, College Station, Texas, USA; more details via http://www.stata.com/) software. Variables and analyses Two admission categories were created from linked indi- vidual patient records: index admissions (not within 60 days of discharge from an emergency hospitalisation) and readmissions (within 60 days of discharge from an emergency hospitalisation). An interval of 60 days was chosen to allow sufficient time for any medical review in outpatients or the community that might be triggered by INTRODUCTION Logistic regression was used to determine any association between admission at a weekend, demographic covariates and death within 30 days (the response variable).4 9 In addition to depriv- ation and comorbidities, a five knot spline approach examined the effect of age (8, 52, 70, 81 and 91 years) and season (16 January, 31 March, 18 June, 17 September and 15 December).16 Open Access Patient involvement Members of the public were not involved in the study concept or design. Table 1 Service coverage across three ED sites ED Total population served People resident per sq mile/ sq km (average) Description A 235 000 6242/2401 Uniform urban and suburban city population all within 10 miles of the ED B 255 000 233/603 Majority of population in 5 towns between 1 and 50 miles from the ED C 60 000 70/27 Majority of population within 5 miles of the ED in a single town, rest widely dispersed in a rural setting ED, emergency department. 2 Shiue I, et al. BMJ Open 2017;7:e012493. doi:10.1136/bmjopen-2016-012493 24 by guest. Protected by copyright. Table 1 Service coverage across three ED sites ED Total population served People resident per sq mile/ sq km (average) Description A 235 000 6242/2401 Uniform urban and suburban city population all within 10 miles of the ED B 255 000 233/603 Majority of population in 5 towns between 1 and 50 miles from the ED C 60 000 70/27 Majority of population within 5 miles of the ED in a single town, rest widely dispersed in a rural setting ED, emergency department. 2 Shiue I, et al. BMJ Open 2017;7:e012493. doi:10.1136/bmjopen-2016-012493 2 Shiue I, et al. BMJ Open 2017;7:e012493. doi:10.1136/bmjopen-2016-012493 RESULTS Table 2 Characteristics of the admission groups All admissions Index admissions only Readmissions only Monday to Friday Saturday+Sunday Monday to Friday Saturday+Sunday Monday to Friday Saturday+Sunday Number 111 388 37 608 96 379 32 587 15 009 5021 Age (median (IQR)) 70 (49, 82) 70 (47, 82) 69 (47, 81) 65 (45, 81) 75 (59, 84) 76 (62, 84) Male (%) 44.9 44.7 45.0 44.6 44.3 45.6 IMDS (median (IQR)) 21.6 (12.1, 34.6) 21.7 (12.1, 34.6) 21.5 (12.0, 34.6) 21.6 (12.1, 34.6) 21.8 (12.4, 35.2) 22.0 (12.8, 35.2) CCI (median (IQR)) 1 (0, 2) 1 (0, 2) 1 (0, 2) 1 (0, 2) 1 (0, 3) 1 (0, 3) Number of deaths by day 30 8521 2975 6679 2291 1840 666 Crude 30-day death rate (%) 7.65 7.91 6.93 7.03 12.26 13.27 Adjusted 30-day death rate (% (95% CI)) 7.66 (7.5 to 7.8) 7.90 (7.6 to 8.2) 6.93 (6.8 to 7.1) 7.04 (6.8 to 7.3) 12.36 (11.8 to 12.9) 13.27 (12.4 to 14.2) CCI, Charlson Comorbidity Index; IMDS, Index of Multiple Deprivation Score. Over 5 years there were 148 996 emergency admissions, comprising 128 966 index cases (74.7% weekday and 25.3% weekend arrival) and 20 030 readmissions within 60 days (74.9% weekday and 25.1% weekend arrival), that is, a readmission rate of 13.4% with the same weekday/weekend distribution as index admissions (p=0.54). By day 30 there were 11 476 (7.7%) deaths. Table 2 shows the distribution of demographic character- istics and deaths according to admission category and timing. Readmissions were older, with higher levels of social deprivation and comorbidity. Readmissions had a significantly greater risk of dying than index admissions. Although there was a relative increase in weekend death rate for readmissions compared with index admissions (7.4% vs 1.6%), there was no significant increase in the 30-day death rates following weekend admission. Saturday+Sunday y g The logistic regression output (table 3) indicated an overall increased risk of dying associated with male gender, very young or old age, increasing comorbidities and greater deprivation. There was a mild seasonal effect. Online supplementary table S1 shows that using a 30-day readmission definition resulted in a very similar output, but a few associations lost statistical significance because of the smaller number of cases. Table 3 shows that weekend admission was associated with a small increased risk of death overall (OR 1.06 (95% CI 1.01 to 1.11)). This was statistically significant for read- missions (OR 1.10 (95% CI 1.01 to 1.20)) but not for index admissions (OR 1.04 (95% CI 0.98 to 1.11)), sug- gesting that admission category should be a data field reported by other ‘weekend effect’ studies. Further regres- sion analysis (table 4) indicated that there was an increased risk of death for weekend index admissions with the least social deprivation (n=32 742; OR 1.24 (95% CI 1.11 to 1.38)) and without comorbidities (n=70 299; OR 1.17 (95% CI 1.02 to 1.34)). There was no additional inter- action between these characteristics. Deaths following weekend readmission did not differ in IMDS or CCI when compared with readmissions between Monday and Friday. on October 2 http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2016-012493 on 2 March 2017. Downloaded from An updated analysis of 14 818 374 admissions during 2013– 2014 showed similar ratios of 1.10 (95% CI 1.08 to 1.11) for Saturday and 1.15 (95% CI 1.14 to 1.17) for Sunday.9 It has been suggested that the excess mortality observed following weekend admission is due to the size of the hospital workforce.1 4 6 9 This seems less likely in our cohort as the effect was not the same within each admission category. One possible explanation is that the higher mortality rate of readmissions implies greater illness severity, which could amplify the impact of any weekend shortfall in initial clinical availability. However, a survival difference between index admission and readmission might also reflect variations in case-mix and overall service provision including care in between hos- pital episodes. Since readmission was defined as a second hospitalisation within 60 days of an unscheduled index discharge, the outcome could be related to medical and social stability when initially leaving hos- pital, the effectiveness and complications of treatment started during the initial admission, and the ability of community and outpatient services to compensate for individuals with rapidly progressive and fluctuating states. Risk factors for readmission have previously been described including age, prior emergency discharge, IMDS and major health conditions (eg, from the CCI)12 and combined into predictive models with c-statistics ranging from 0.50 to 0.72.18 As readmission cohorts display distinct demographic and service-user profiles it would appear simplistic to suggest that the size of the workforce only on the day of readmission is solely responsible for excess mortality. In population-level studies, the CCI has been used to reflect illness burden, but it is insensitive to short-term health changes and an additional association between admission category and survivorship strongly suggests that measures of acute illness severity and clinical care beyond the day of admis- sion are necessary to understand the ‘weekend effect’. The size of the association found between weekend readmission and mortality was similar to that of previous studies. From analysis of 4 317 866 emergency admis- sions across England during 2005–2006, Aylin et al1 reported an overall adjusted odds of death for weekend hospitalisation of 1.10 (95% CI 1.08 to 1.11) compared with patients admitted during a weekday. on October 2 http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2016-012493 on 2 March 2017. Downloaded from Table 3 Associations with 30-day mortality by admission group in 2010–2015 All admissions Index admissions only Readmissions only OR (95% CI) p Value OR (95% CI) p Value OR (95% CI) p Value Male 1.32 (1.19 to 1.47) <0.001 1.29 (1.14 to 1.46) <0.001 1.42 (1.25 to 1.62) <0.001 CCI 1.13 (1.08 to 1.18) <0.001 1.12 (1.08 to 1.18) <0.001 1.10 (1.05 to 1.15) <0.001 IMDS 1.01 (1.00 to 1.01) <0.001 1.01 (1.00 to 1.01) <0.001 1.00 (1.00 to 1.01) 0.035 Weekend admission 1.06 (1.01 to 1.11) 0.023 1.04 (0.98 to 1.11) 0.165 1.10 (1.01 to 1.20) 0.028 Age 1 (youngest) 1.10 (1.08 to 1.13) <0.001 1.10 (1.07 to 1.13) <0.001 1.10 (1.05 to 1.16) <0.001 Age 2 0.97 (0.94 to 0.99) 0.038 0.97 (0.94 to 1.00) 0.066 0.96 (0.90 to 1.02) 0.189 Age 3 0.91 (0.72 to 1.15) 0.420 0.93 (0.73 to 1.18) 0.534 0.88 (0.58 to 1.33) 0.540 Age 4 (oldest) 2.62 (1.47 to 4.69) 0.001 2.46 (1.36 to 4.44) 0.003 3.13 (1.03 to 9.54) 0.044 Date 1 (early year) 0.99 (0.99 to 0.99) <0.001 0.99 (0.99 to 0.99) 0.002 0.99 (0.99 to 0.99) 0.015 Date 2 1.01 (1.00 to 1.03) 0.006 1.01 (1.00 to 1.02) 0.022 1.02 (0.99 to 1.04) 0.070 Date 3 0.96 (0.94 to 0.99) 0.008 0.97 (0.94 to 0.99) 0.026 0.96 (0.91 to 1.01) 0.087 Date 4 (late year) 1.05 (1.02 to 1.08) 0.003 1.05 (1.01 to 1.08) 0.010 1.05 (0.99 to 1.10) 0.096 Age spline knots: 8, 52, 70, 81 and 91 years; date spline knots: 16 January, 31 March, 18 June, 17 September and 15 December. CCI, Charlson Comorbidity Index; IMDS, Index of Multiple Deprivation Score. on October 23, 2024 by guest. Protected by copyright. http://bmjopen.bmj.com/ shed as 10.1136/bmjopen-2016-012493 on 2 March 2017. Downloaded from The size of the association found between weekend readmission and mortality was similar to that of previous studies. From analysis of 4 317 866 emergency admis- sions across England during 2005–2006, Aylin et al1 reported an overall adjusted odds of death for weekend hospitalisation of 1.10 (95% CI 1.08 to 1.11) compared with patients admitted during a weekday. For 14 217 640 unselected English NHS admissions during 2009–2010, Freemantle et al4 reported a HR for death following hos- pitalisation on a Saturday of 1.11 (95% CI 1.09 to 1.13) and for a Sunday of 1.16 (95% CI 1.14 to 1.18). DISCUSSION During 5 years of emergency activity across three EDs there was no significant increase in the overall adjusted 30-day death rate following weekend admission, but a small ‘weekend effect’ was identified by multivariable analysis. The readmission rate of 13.4% within 60 days of discharge was consistent with a previously reported rate of 12.9% at 28 days derived from English Hospital Episode Statistics for acute medical admissions.6 Readmissions had a higher death rate, but the weekday/ weekend distribution was similar to that of index admis- sions. However, multivariable analysis indicated that weekend readmission was associated with a small increase in the risk of death compared with weekday readmission. This was not explained by comorbidities or social deprivation. Shiue I, et al. BMJ Open 2017;7:e012493. doi:10.1136/bmjopen-2016-012493 3 Open Access on October 2 http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2016-012493 on 2 March 2017. Downloaded from Their prognosis may be poorer relative to patients with milder exacerbations of chronic condi- tions who are in regular contact with primary care and consequently are more likely to be admitted in larger numbers on a weekday following GP review. A mixed- methods approach would be helpful to further investi- gate this finding, including qualitative interviews with purposive sampling of patients, the addition of physio- logical data to indicate initial illness severity, cross- referencing with outpatient attendances and linkage to primary care records to observe the timing of any con- tacts leading up to admission. secondary and social care data, including reliable indica- tors of workforce availability and service usage. If behav- ioural factors and admission category do lead to the clustering of new inpatients with greater illness severity at weekends, interventions could seek to improve patient education, reduce premature discharges, enhance com- munication between secondary and primary care, and develop alternatives to emergency admission when a patient deteriorates in the community, for example, a more rapid palliative or elderly care response. In summary, a weak association was identified between 30-day mortality and emergency admission at a weekend, which was statistically significant only for readmissions. A reversal of the usual comorbidity and deprivation trends was observed for death following a weekend index admission, which has not previously been reported and could reflect heterogeneity in health-related behaviours and opportunities for admission. These findings suggest that the ‘weekend effect’ reflects case-mix variations and a whole system responsiveness which cannot be demon- strated through Hospital Episode Statistics alone. Readmissions are likely to have additional complexities from clinical and service perspectives, and the outcome may reflect community as well as hospital responsiveness. We recommend that detailed case-mix characteristics should be considered when examining the potential impact of service provision on patient outcomes. Competing interests None declared. Ethics approval Information governance permission was granted by Northumbria Healthcare NHS Foundation Trust, but ethics approval was not required as the analysis used pseudoanonymised routinely collected data. y p p Previous studies have been unable to examine the impact of readmissions due to the challenge of data linkage for individual patients. We did not consider the impact of multiple readmissions during 60 days as the small size of the corresponding subgroups would have pre- vented meaningful analysis. The specific circumstances of this study cohort should be considered when determining the wider relevance, that is, the results describe outcomes from a single large acute care provider organisation with consistent daily levels of senior medical cover to review emergency admissions, thereby reducing any potential workforce-related weekend effect.6 Although the analysis attempted to correct for case-mix effects, due to survivor- ship bias and the greater illness severity associated with readmission it may have been easier to detect associations with mortality. It is possible that a larger cohort might have also shown a statistically significant weekend effect for index admissions, but it is notable that the association was already evident in the smaller readmission group. The data set was an aggregate over 5 years, but no significant change in service configuration or admission processes occurred during that time. In order to confirm the asso- ciations found and further explore the underlying mechanisms, linkage would be required between primary, Provenance and peer review Not commissioned; externally peer reviewed. Provenance and peer review Not commissioned; externally peer reviewed. Data sharing statement No additional data are available. Data sharing statement No additional data are available. Open Access This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http:// creativecommons.org/licenses/by/4.0/ on October 2 http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2016-012493 on 2 March 2017. Downloaded from g p As the study focussed on emergency admissions, it is not surprising that the overall mortality rate of 7.7% was higher than cohorts which have also included scheduled care.4 9 19 20 It was consistent with a previous in-hospital mortality report of 7.96% among 15 594 emergency medical admissions to a single centre.8 Examinations of unscheduled activity across multiple acute hospital trusts in England have reported an overall crude mortality rate of 5.0%1 and an adjusted case fatality rate of 4.3% (range 2.5–6.4%).6 However, these inpatient population studies included groups in the denominator which could have a lower short-term risk of death such as hospital transfers and direct ward admissions from primary care, and did not count deaths occurring in the community after dis- charge.21 As there are many factors which could influence inpatient mortality, it is important that future reports clearly define the patient groups contributing towards outcomes in order to allow fair comparison and identify mechanisms that may be responsible for temporal trends. on October 23, 2024 by guest. P http://bmjopen.bmj.com/ 93 on 2 March 2017. Downloaded from Contributors IS, CP and PM designed the study; PM and CP acquired the data; IS and PM analysed the data independently; IS and CP drafted the manuscript; IS, PM and CP revised the final manuscript. Funding Financial support was provided by the Dunhill Medical Trust (grant number: R357/0514). Funding Financial support was provided by the Dunhill Medical Trust (grant number: R357/0514). on October 2 http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2016-012493 on 2 March 2017. Downloaded from For 14 217 640 unselected English NHS admissions during 2009–2010, Freemantle et al4 reported a HR for death following hos- pitalisation on a Saturday of 1.11 (95% CI 1.09 to 1.13) and for a Sunday of 1.16 (95% CI 1.14 to 1.18). An updated analysis of 14 818 374 admissions during 2013– 2014 showed similar ratios of 1.10 (95% CI 1.08 to 1.11) for Saturday and 1.15 (95% CI 1.14 to 1.17) for Sunday.9 y y It has been suggested that the excess mortality observed following weekend admission is due to the size of the hospital workforce.1 4 6 9 This seems less likely in our cohort as the effect was not the same within each admission category. One possible explanation is that the higher mortality rate of readmissions implies greater illness severity, which could amplify the impact of any weekend shortfall in initial clinical availability. However, a survival difference between index admission and readmission might also reflect variations in case-mix and overall service provision including care in between hos- pital episodes. Since readmission was defined as a second hospitalisation within 60 days of an unscheduled The influence of case-mix on outcome following weekend hospitalisation was also implied by the observa- tion that index deaths were associated with reversal of typical demographic trends,19 20 and the risks associated with low social deprivation and an absence of comorbid- ities were of greater magnitude than the timing of Table 4 Interactions between 30-day death, social deprivation and comorbidities for weekend admissions Risk of 30-day death after a weekend admission Index admissions only Readmissions only OR (95% CI) p Value OR (95% CI) p Value No comorbidities (CCI=0) 1.17 (1.02 to 1.34) 0.023 1.05 (0.85 to 1.30) 0.638 Least social deprivation (IMDS top quartile) 1.24 (1.11 to 1.38) <0.001 0.95 (0.72 to 1.25) 0.725 No comorbidities × least social deprivation 0.90 (0.72 to 1.13) 0.380 1.09 (0.65 to 1.85) 0.726 No comorbidities was defined as a CCI of zero; least social deprivation represents the top quartile of the IMDS range. CCI, Charlson Comorbidity Index; IMDS, Index of Multiple Deprivation Score. 4 Shiue I, et al. BMJ Open 2017;7:e012493. doi:10.1136/bmjopen-2016-012493 Shiue I, et al. BMJ Open 2017;7:e012493. doi:10.1136/bmjopen-2016-012493 4 Open Access admission. The mechanism is unclear, but as these groups are less likely to include frequent service users, patients might present directly to ED at later stages of an acute illness. REFERENCES 1. Aylin P, Yunus A, Bottle A, et al. Weekend mortality for emergency admissions. A large, multicentre study. Qual Saf Health Care 2010;19:213–17. 2. Ricciardi R, Roberts PL, Read TE, et al. Mortality rate after non-elective hospital admission. Arch Surg 2011;146:545–51. 3. Sharp AL, Choi H, Hayward RA. Don’t get sick on the weekend: an evaluation of the weekend effect on mortality for patients visiting US EDs. Am J Emerg Med 2013;31:835–7. g ; 4. Freemantle N, Richardson M, Wood J, et al. Weekend hospitalisation and additional risk of death: an analysis of inpatient data. J R Soc Med 2012;105:74–84. 5. Ruiz M, Bottle A, Aylin PP. The Global comparators project: international comparison of 30 day in-hospital mortality by day of the week. BMJ Qual Saf 2015;24:492–504. ; 6. Bell D, Lambourne A, Percival F, et al. Consultant input in acute medical admissions and patient outcomes in hospitals in England: a multivariate analysis. PLoS ONE 2013;8:e61476. Shiue I, et al. BMJ Open 2017;7:e012493. doi:10.1136/bmjopen-2016-012493 5 Open Access Open Access 15. Department for Communities and Local Government. The English Indices of Deprivation 2015. http://www.communities.gov.uk/ publications/corporate/statistics/indices2015 (accessed 20 Mar 2016). 7. Clarke MS, Wills RA, Bowman RV, et al. Exploratory study of the ‘weekend effect’ for acute medical admissions to public hospitals in Queensland, Australia. Intern Med J 2010;40:777–83. 7. Clarke MS, Wills RA, Bowman RV, et al. Exploratory study of the ‘weekend effect’ for acute medical admissions to public hospitals in Queensland, Australia. Intern Med J 2010;40:777–83. p Queensland, Australia. Intern Med J 2010;40:777–83. 8. Maggs F, Mallet M. Mortality in out-of-hours emergency medical admissions—more than just a weekend effect. J R Coll Physicians Edinb 2010;40:115–18. 8. Maggs F, Mallet M. Mortality in out-of-hours emergency medical admissions—more than just a weekend effect. J R Coll Physicians Edinb 2010;40:115–18. ) 16. Harrell FE. Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. New York: Springer, 2001. ; 9. Freemantle N, Ray D, McNulty D, et al. Increased mortality associated with weekend hospital admission: a case for expanded seven day services? BMJ 2015;351:h4596. ; 9. Freemantle N, Ray D, McNulty D, et al. Increased mortality associated with weekend hospital admission: a case for expanded seven day services? BMJ 2015;351:h4596. p g 17. Healthcare Cost and Utilization Project (HCUP) Clinical Classifications Software (CCS) for ICD-10-CM/PCS. https://www. hcup-us.ahrq.gov/toolssoftware/ccs10/ccs10.jsp (accessed 22 Mar 2016) y ; 10. Blunt I, Bardsley M, Grove A, et al. Classifying emergency 30 day readmissions in England using routine hospital data 2004–2010: what is the scope for reduction? Emerg Med J 2015;32:44–50. 10. Blunt I, Bardsley M, Grove A, et al. Classifying emergency 30 day readmissions in England using routine hospital data 2004–2010: what is the scope for reduction? Emerg Med J 2015;32:44–50. 11. Hansen LO, Young RS, Hinami K, et al. Interventions to reduce 30 day rehospitalisation: a systematic review. Ann Intern Med 2011;155:520–8. 12. Billings J, Blunt I, Steventon A, et al. Development of a predictive model to identify inpatients at risk of readmission within 30 days of discharge (PARR-30). BMJ Open 2012;2:e001667. 18. Kansagara D, Englander H, Salanitro A, et al. Risk prediction models for hospital readmission: a systematic review. JAMA 2011;306:1688–98. at s t e scope o educt o e g ed J 0 5;3 50 11. Hansen LO, Young RS, Hinami K, et al. Interventions to reduce 30 day rehospitalisation: a systematic review. Ann Intern Med 2011;155:520–8. 12. Open Access Billings J, Blunt I, Steventon A, et al. Development of a predictive d l id if i i i k f d i i i hi 30 d f p g ; 11. Hansen LO, Young RS, Hinami K, et al. Interventions to reduce 30 day rehospitalisation: a systematic review. Ann Intern Med 2011;155:520–8. 11. Hansen LO, Young RS, Hinami K, et al. Interventions to reduce 30 day rehospitalisation: a systematic review. Ann Intern Med 2011;155:520–8. 12. Billings J, Blunt I, Steventon A, et al. Development of a predictive model to identify inpatients at risk of readmission within 30 days of discharge (PARR-30). BMJ Open 2012;2:e001667. 19. Health and Social Care Information Centre. Summary hospital-level mortality indicator. http://www.hscic.gov.uk/SHMI (accessed 22 Mar 2016). p y 12. Billings J, Blunt I, Steventon A, et al. Development of a predictive model to identify inpatients at risk of readmission within 30 days of discharge (PARR-30). BMJ Open 2012;2:e001667. g ( ) p ; 13. England Local Authorities: Population, Land Area & Density. http:// www.demographia.com/db-engla.htm (accessed 22 Jan 2016). ) 20. Campbell MJ, Jacques RM, Fotheringham J, et al. Developing a summary hospital mortality index: retrospective analysis in English hospitals over five years. BMJ 2012;344:e1001. 14. Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40:373–83. p y ; 21. Goodacre S, Campbell M, Carter A. What do hospital mortality rates tell us about quality of care? Emerg Med J 2015;32:244–7. 6 Shiue I, et al. BMJ Open 2017;7:e012493. doi:10.1136/bmjopen-2016-012493
https://openalex.org/W1521803812
https://www.scielo.br/j/ecos/a/chY4jcCHqQWcmnSP6nPrD9K/?lang=pt&format=pdf
Portuguese
null
O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro
Economia e Sociedade
2,007
cc-by
11,602
Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. (1) Trabalho recebido em julho de 2006 e aprovado em novembro de 2006. (2) Professor Titular do Departamento de Ciências Econômicas da Universidade Federal do Rio Grande do Sul (UFRS) e Pesquisador do Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). The innovative eclecticism: Bresser Pereira and the Brazilian The innovative eclecticism: Bresser Pereira and the Brazilian The innovative eclecticism: Bresser Pereira and the Brazilian The innovative eclecticism: Bresser Pereira and the Brazilian development development development development This paper studies the book Development and crisis in Brazil by Luiz Carlos Bresser-Pereira. It aims at checking the author’s contribution to the literature and the understanding of the Brazilian historical process in the 20th Century, beginning with the first issue in 1968 and going through countless reviews until it reached its fifth and final issue in 2003. We hipothesize that as the author considers distinctive theoretical and methodological sources, choosing the elements he considered relevant to the reconstruction of a concrete historical process, he builds an analysis that is organic and coherent, one that is kept along the many issues and is responsible for incorporating new elements to the interpretation of the economic, social and political development of the country. Key words: Brazilian economy; Development; Nationalism. JEL O54. O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro1 Pedro Cezar Dutra Fonseca2 Resumo Este trabalho analisa a obra Desenvolvimento e crise no Brasil, de Luiz Carlos Bresser-Pereira. Seu objetivo é detectar suas contribuições à literatura e ao entendimento do processo histórico brasileiro do século XX, desde sua primeira edição, de 1968, até passar por inúmeras revisões e acréscimos e chegar a sua quinta e última edição, de 2003. Tem-se como hipótese que o autor, ao recorrer a fontes teóricas e metodológicas distintas, e ao delas selecionar os elementos que considerava relevantes para a reconstrução de um processo histórico concreto, constrói uma análise marcada por organicidade e coerência, mantida ao longo de suas várias edições, responsável por incorporar novos elementos à interpretação do desenvolvimento econômico, social e político do Brasil. Palavras-chave: Brasil – Política econômica; Brasil – Política e Governo. (1) Trabalho recebido em julho de 2006 e aprovado em novembro de 2006. (2) Professor Titular do Departamento de Ciências Econômicas da Universidade Federal do Rio Grande do Sul (UFRS) e Pesquisador do Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). Introdução O estudo comparativo das grandes obras de interpretação do Brasil permite que se detecte um fenômeno repetitivo: várias delas não foram escritas de uma só vez, passaram por revisões e complementações muito além do considerado usual para uma nova edição, de modo que a primeira versão acaba por transformar-se em capítulos iniciais de uma obra em permanente construção, ou que precisou passar por várias etapas até ser dada por concluída. Pedro Cezar Dutra Fonseca Pedro Cezar Dutra Fonseca Assim ocorreu com Formação do Brasil contemporâneo – Colônia, de Caio Prado Jr., de 1942, que três anos mais tarde tornou-se aproximadamente um terço de um trabalho mais acabado e consagrado: História Econômica do Brasil. Raymundo Faoro, por sua vez, publicou Os donos do poder em 1958; mas republicou-a em 1975 com nova versão, cujas teses originais foram reforçadas com novos argumentos e farto material empírico, os quais representaram a duplicação, em volume, da versão original. Já A revolução burguesa no Brasil, de Florestan Fernandes, começou ser escrita em 1966; aos capítulos iniciais acrescentam-se novos, de modo que somente na edição de 1974 alcançaria sua versão definitiva. Da mesma forma, Teoria e política do desenvolvimento econômico – para muitos a grande obra-síntese do pensamento de Celso Furtado –, publicada em 1967, sistematiza e amplia vários trabalhos anteriores reunidos em Desenvolvimento e subdesenvolvimento, de 1961, do qual se aproveitaram vários capítulos. Desenvolvimento e crise no Brasil (de ora em diante DCB), de Luiz Carlos Bresser-Pereira, não foge à regra. Seus seis primeiros capítulos foram escritos para a primeira edição, de 1968. Na segunda, de 1970, acrescentou-se um sétimo capítulo; e na terceira, de 1972, adicionou-se um oitavo; já na quarta edição, de 1984, publicada em língua inglesa pela Westview Press, constam dez capítulos. Desta para a quinta e última edição, de 2003, houve alteração substantiva: novos dez capítulos foram acrescentados, juntamente com o subtítulo: “História, economia e política de Getúlio Vargas a Lula”. Este de certo modo sintetiza o objetivo do autor e demarca o período de abrangência de sua análise, “escrita por alguém que participou dela com paixão, vivendo suas grandes esperanças e suas frustrações” (Bresser-Pereira, 2003, p. 22; todas as demais citações em que aparece somente o número da página foram daí extraídas). 1 O desenvolvimento como epicentro Dentre as obras clássicas de interpretação do país, DCB destaca-se por ter por objeto o processo de desenvolvimento brasileiro, o qual se propõe compreender e explicar. Como assume que este processo, em seu sentido pleno, começa a rigor a partir de 1930, este é seu ponto cronológico inicial e todos os recuos históricos constantes ao longo do livro têm como objetivo retomar e esclarecer marcos estruturais necessários para elucidar aspectos de longo prazo da formação econômica, política e social do Brasil emergentes a partir desse ano. Não se trata, portanto, de uma interpretação do Brasil tal como se encontra em Caio Prado Jr. (1970), Sérgio Buarque de Holanda (1979), Celso Furtado (1977), Raymundo Faoro (1979) ou Florestan Fernandes (1981), pois nestes autores havia o propósito de acompanhar o processo histórico desde o período colonial, na busca de raízes estruturantes e peculiaridades da formação histórico- social da nacionalidade. Nem por isso, todavia, a de DCB deixa de ser menos importante ou inovadora. Datada de 1968, sua primeira edição reflete exemplarmente as preocupações e os impasses com que se deparavam os principais intelectuais brasileiros da época: o baixo crescimento verificado no interregno entre o auge cíclico resultante do bloco de investimentos do Plano de Metas e o início do “Milagre”. Metas e o início do “Milagre”. Naquele momento, o esforço intelectual de economistas e demais cientistas sociais centrava-se na busca das causas do que se considerava o esgotamento do processo de substituição de importações, contrastando a “estagnação” então vigente com as expressivas taxas de crescimento econômico, lideradas pelo setor industrial, verificadas desde a década de 1930. O desafio consistia justamente em desvendar as razões do contraste entre a crise ora vivenciada e os períodos anteriores, responsáveis por profundas transformações na sociedade brasileira, com a superação do modelo agroexportador e de uma sociedade marcadamente agrária e “oligárquica”, como então usualmente se definia o período da República Velha. Analisando-se a produção intelectual como discurso, nota-se de imediato a consciência de que uma fase áurea se esgotara já no próprio título da obra, com a oposição desenvolvimento/crise – antonímia recorrente em vários trabalhos da época, como no clássico Auge e declínio do processo de substituição de importações no Brasil, de Maria da Conceição Tavares (1972). Introdução O objetivo principal deste artigo é formular respostas para a questão: no que a análise de Bresser-Pereira em DCB inova, quais suas principais contribuições e o que o personaliza e qualifica com um dos principais intérpretes do desenvolvimento brasileiro desse período? A hipótese básica, a qual se pretende demonstrar, é que, ao abeberar-se em várias fontes teóricas e metodológicas, Bresser-Pereira constrói uma interpretação inovadora, em vários aspectos, ao ter-se como referência outras análises da época. Por outro lado, como ficará evidenciado a seguir, mesmo ao passar por inúmeras atualizações e acréscimos – os capítulos adicionados a sua última edição poderiam ser publicados, caso se quisesse, como novo livro –, DCB guarda unicidade e coerência tanto metodológica como em suas principais proposições e teses, de modo que, de fato, constitui um todo orgânico e uma visão globalizante e abrangente do desenvolvimento econômico, político e social brasileiro do século XX. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 22 O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro Para dar cabo à empreitada, faz-se mister começar com o entendimento do autor sobre o que seja desenvolvimento. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. conomia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 23 1 O desenvolvimento como epicentro A crise interrompera não só uma série histórica de altas taxas de crescimento, mas sonhos de construção de uma nação desenvolvida, socialmente justa e soberana, imaginário do que se convencionou denominar mais tarde de “ideologia nacional-desenvolvimentista”. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 23 23 Pedro Cezar Dutra Fonseca Utilizado inúmeras vezes ao longo da obra, o termo desenvolvimento já no capítulo inicial é definido como processo, ou seja, fenômeno que se desenvolve no tempo; processo, todavia, não linear, pois de transformação; e esta com alcance global, pois parte de modificações na estrutura econômica que “repercutirão nas estruturas política e social e vice-versa” (p. 31). Desde logo, portanto, evidencia-se clara influência do estruturalismo, admitindo-se o desenvolvimento econômico como “preponderante”; todavia, este só poderia ser entendido como tal se capaz de incidir sobre o padrão de vida da população e aumento de bem-estar (p. 31-32). Na genealogia do conceito, nota-se como ponto de partida uma noção em que desenvolvimento emerge como crescimento do PIB; mas, como conceito em construção, vai tomando vulto até alcançar versão mais acabada, na qual se transforma, de fato, em quase sinônimo de aumento de padrão de vida. Coetâneo e partícipe dos debates e análises vigentes à época, Bresser- Pereira enfatiza que a concretização do processo de desenvolvimento exige que o aumento tanto da riqueza como do padrão de vida deva ser auto-sustentado, ou seja, “automático, autônomo e necessário” (p. 33). Se esta pré-condição firme e exigente surpreende o leitor das últimas décadas (já que taxas ínfimas de crescimento para o padrão histórico do Brasil passaram a ser consideradas altas e comemoradas como conquistas pelos governantes...), mais inusitado é o registro de que tal afirmação não aparece apenas na primeira edição, publicada no auge do desenvolvimentismo, mas é reiterada em suas várias edições e reatualizações, mesmo nas mais recentes. Na verdade, há uma tese que perpassa a obra: a de que o processo de desenvolvimento, em país de capitalismo tardio como o Brasil, deva ser entendido como um conjunto de transformações que pode ser sintetizado como revolução. Trata-se da Revolução Nacional Brasileira (categoria analítica, substantivo próprio), iniciada em 1930 e contrastante com o período anterior, “semicolonial”. Apoia-se, para tanto, principalmente em Furtado, nos capítulos 30 a 32 da Formação econômica do Brasil, ao enfatizar o “abalo profundo” da Grande Depressão como variável desencadeadora da alteração da estrutura econômica. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 1 O desenvolvimento como epicentro Mas desde logo argumenta que dela decorreu um conjunto de mudanças mais profundo e complexo, ao extravasar para outras áreas: “Vemos um ruir de velhas estruturas, de antigos preconceitos, de classes esclerosadas, de privilégios arraigados” (p. 35). Furtado, como deixa claro em várias obras suas, enfatizava 1930 como o ponto de inflexão ao deslocar o “centro dinâmico” da economia, de um modelo de crescimento “para fora” a outro, “para dentro”, mas teve extrema cautela tanto ao buscar suas raízes políticas como ao explorar suas conseqüências em outras áreas (ver, Fonseca, 2003). Em algumas ocasiões, francamente depreciou a importância do acontecimento político denominado “Revolução de 30” como fator propulsor de transformações, entendendo que a crise econômica seria suficiente para dar Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 24 O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro conta da mudança, considerada “reflexo imediato das dimensões catastróficas da crise do café” (Furtado, 1971, p. 201, grifos meus). Em outra oportunidade, afirmou que depois de 1930 “as classes que dirigem o país são, no essencial, as mesmas do período anterior” (1964, p. 113). Da mesma forma, chegou, em outra obra, a questionar o significado político da mudança de governo decorrente da “Revolução”: “predominava no país um conservadorismo voltado para a restauração de um passado glorioso” (1961, p. 235). Esta postura metodológica não deixa de ser a mesma de Tavares em “Auge e declínio”, artigo em que a mudança do modelo ocorrida em 1930 é reconstituída atendo-se em variáveis estritamente econômicas, como o estrangulamento externo e seu impacto na economia nacional, sem qualquer referência às dimensões política ou ideológica. Nesse aspecto, pode-se afirmar que DCB, mesmo tendo partido de uma raiz estruturalista ao conceituar desenvolvimento e tê-lo como epicentro da análise, dela se afasta ao considerar o processo como revolução, categoria esta, pelo que se depreende do conjunto da obra, vai buscar nos approaches marxista e weberiano. A percepção do processo como revolução não se reduz à mera retórica, pois dela resultam implicações analíticas, como forçar pensar o desenvolvimento como “historicamente situado” (p. 32), portanto abarcando várias dimensões: “Todos os campos são atingidos: o econômico, o cultural, o social e o político” (p. 35). A partir de 1930 aparecem novas classes sociais, novos atores na cena política e, nesta, as transformações “não são menos notáveis” (p. 37). Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 1 O desenvolvimento como epicentro Nota-se que a recorrência à complexidade do processo histórico brasileiro e a instrumentais teóricos voltados a ultrapassar a ênfase do estruturalismo cepalino e do marxismo tradicional às determinações econômicas já estava, mais ou menos na mesma época, em ebulição no pensamento de outros coevos, como Florestan Fernandes e dos “teóricos da dependência”, o que sugere tratar-se de preocupação compartilhada por vários intelectuais, como se o programa de pesquisa fosse uma imposição das circunstâncias históricas. Em Florestan, por exemplo, também havia a preocupação de se detectar em que ponto do tempo a “revolução burguesa” teria alcançado “um patamar histórico irreversível”, bem como a pretensão de entendê-la como um conjunto de transformações não só econômicas, mas sociais, psicoculturais e políticas (Fernandes, 1981, p. 203). Mas enquanto Florestan Fernandes e Bresser-Pereira inspiravam-se simultaneamente em Marx e Max Weber para entender o alcance das mudanças como revolução, Caio Prado Jr. já havia de certo modo antecipado seu uso, embora mais com sentido político do que como recurso analítico, em 1966, com a publicação de A Revolução Brasileira. Nesta, Prado Jr. lançara mão da dicotomia entre “capitalismo colonial” versus “capitalismo nacional” como recurso para mostrar que o processo de substituição de importações e a industrialização eram insuficientes para o alcance do desiderato de um patamar de autonomia nacional e bem-estar, o que ia de encontro às teses do nacional-desenvolvimentismo de 25 Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. Pedro Cezar Dutra Fonseca Pedro Cezar Dutra Fonseca inspiração cepalina. Bresser-Pereira e Florestan Fernandes utilizaram a mesma dicotomia, mas reinterpretam-na de forma diferente. Enquanto Caio Prado Jr. entendia que ainda se vivia em uma situação colonial e apontava seu rompimento para o futuro, com uma revolução que estava por ser feita, Florestan Fernandes defendeu que a formação da sociedade nacional dera-se no início do século XIX, no bojo do processo de Independência e com o fim do estatuto colonial. Ocorrera em um processo gradual, mas de grande profundidade quanto a seu alcance, já que a autonomia política e as possibilidades de afirmação da ordem social competitiva que lhe seguiram seriam marcos relevantes da “revolução burguesa” no país. Bresser-Pereira por sua vez, entende que só em 1930 há efetivamente o rompimento com o passado “semicolonial” (p. 35). Este é sintetizado em um quadro onde a Revolução Industrial Brasileira é desencadeada “graças à Revolução de 1930”. 1 O desenvolvimento como epicentro O movimento político, portanto, é variável indispensável para a explicar o desenrolar dos acontecimentos, o que contrasta com as tradicionais análises cepalinas. Como se sabe, forte debate se seguiu, nas décadas de 1970 e 1980, sobre as origens da industrialização brasileira e o papel da Grande Depressão da década de 1930 para a passagem de uma sociedade agrária para outra, de cunho urbano- industrial. A aceitação de um crescimento industrial antes daquele ano tornou-se corrente, mesmo entre os antigos cepalinos. Bresser-Pereira, no capítulo 17 de DCB, ao incorporar essas novas análises, passou a defender que a revolução capitalista industrial iniciara no final do século XIX, “acelerou-(se) nos anos 1930 e completou-(se) nos anos 1970” (p. 377). Neste último aspecto, também se afasta das tradicionais análises capalinas, para quem o PSI esgotara-se ao final da década de 1950: apoiando-se em Castro (1985), admite que o mesmo se prolonga até o final da década de 1970, quando se completa a matriz industrial brasileira com os investimentos do II PND. A industrialização completou-se, mas foi insuficiente para concluir o processo de Revolução Nacional Brasileira. Esta continua inacabada, como afirma no prefácio desta última edição (p. 22), interrompida pelo abandono do desenvolvimento como prioridade nas últimas décadas. Daí decorre a exigência de que se proponha e se construa um “Novo Desenvolvimentismo”. 2 Economia, política e classes sociais: a história construída pelos homens Há uma proposição epistemológica que perpassa DCB e integra de todas as suas edições: a necessidade do entrosamento entre economia e política como indispensável para a reconstituição do processo histórico. Poder-se-ia perguntar: que novidade há nisso, já que tal proposição parece trivial e passível de ampla aceitação, esposada hoje por intelectuais dos mais diferentes matizes (mesmo os economistas neoclássicos a incorporaram sob a roupagem de governança)? Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 26 O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro Este artigo pretende justamente resgatar essa proposição como uma das mais importantes de DCB, aspecto marcante da contribuição pessoal de seu autor, responsável à época por inovar a literatura com relação a outras interpretações do processo histórico brasileiro então já elaboradas. Até a publicação de DBC, três linhas teóricas principais disputavam espaço na vida intelectual e acadêmica brasileira, quais sejam: a neoclássico-monetarista, a estruturalista e a marxista. Enquanto a primeira admitia explicitamente a separação entre economia e política, ao partir da dimensão do homo economicus e ao incluir as variáveis sociopolíticas como condição coeteris paribus – o que significa reconhecê-la como variáveis sem, todavia, incorporá-la à análise –, as duas últimas defendiam, pelo menos em tese, que fatores políticos não poderiam ser negligenciados. Não obstante, dominava no marxismo tradicional a dicotomia entre infra e superestrutura, em consonância com o conhecido prefácio de Para a crítica da economia política de Marx. Os marxistas em geral aceitavam a relevância dos “fatores” políticos, mas sem abrir mão da “determinação última” da economia: a política geralmente restringia-se como espaço da luta de classes, quase que “deduzida” da contradição entre grau de desenvolvimento das forças produtivas e relações de produção, relegando-os ao seu papel de superestrutura (portanto, mais variável explicada que explicativa, se quisermos usar esta linguagem). Por outro lado, ao geralmente assumirem a centralidade da categoria imperialismo, acabava-se, com ou sem intencionalidade, por negligenciar as determinações internas como condicionantes do processo histórico – e, por extensão, os embates políticos e ideológicos de seus atores. O caso mais típico para ilustrar esta tendência é a interpretação, por parte do PCB, da “Revolução de 1930” como o enfrentamento entre dois imperialismos; o inglês, decadente e representado por São Paulo, e o norte-americano, emergente, cuja expressão seria a chapa da Aliança Liberal encabeçada por Vargas e João Pessoa. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 2 Economia, política e classes sociais: a história construída pelos homens Em síntese: a explicação histórica centrava-se na categoria modo de produção e nos programas de pesquisa dela decorrentes, como a existência ou não de um modo de produção colonial ou de formações “pré-capitalistas”, assim como de uma burguesia nacional revolucionária. Já os estruturalistas normalmente nem mencionavam as variáveis políticas; uma “estrutura” era vista como um conjunto de relações entre variáveis econômicas, a maior parte delas quantificável e passível de ser incorporada no planejamento. Era corrente o entendimento de que as variáveis político- institucionais incorporavam-se nos modelos como parâmetros. É claro que estruturalistas mais sofisticados, como Celso Furtado, nunca omitiram a existência de condicionantes de ordem política, mas muito pouco os consideraram em seus escritos: eram mais supostos e lembrados do que efetivamente incorporados e explorados nas análises. Essa opção metodológica dos cepalinos foi alvo de severas críticas, principalmente a partir dos últimos anos da década de 1960. Cardoso e Faletto (1979), por exemplo, com o fito de contraporem-se às análises 27 Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. Pedro Cezar Dutra Fonseca Pedro Cezar Dutra Fonseca de cunho estruturalista, iniciam sua “interpretação sociológica” ressaltando a necessidade de incorporação de variáveis políticas e sociais para o entendimento da natureza e da problemática do subdesenvolvimento e da dependência dos países latino-americanos. Francisco de Oliveira, em Crítica à Razão Dualista, polidamente ressalvava que “não se trata, em absoluto, de negar o imenso aporte de conhecimentos bebido diretamente ou inspirado no ‘modelo Cepal’, mas exatamente de reconhecer nele o único interlocutor válido, que ao longo dos últimos decênios contribuiu para o debate e a criação intelectual sobre economia e a sociedade brasileira e a latino-americana” (2003, p. 32). Mas, a seguir, foi impiedoso: p Deve ser acrescentado que a perspectiva deste trabalho incorpora, como variáveis endógenas, o nível político ou as condições políticas do sistema: conforme o andamento da análise, tratará de demonstrar que as ‘passagens’ de um modelo a outro, de um ciclo a outro, não são inteligíveis economicamente ‘em si’, em qualquer sistema que revista características de dominação social. O ‘economiscismo’ das análises que isolam as condições econômicas das políticas é um vício metodológico que anda de par com a recusa em reconhecer-se como ideologia (Oliveira, 2003, p. 29-30). 2 Economia, política e classes sociais: a história construída pelos homens Assim, se Marx foi pelo menos uma das fontes inspiradores da inclusão das classes sociais na análise, inova ao destacar a referida classe média – segmento nunca muito claro ou de difícil definição em análises estritamente marxianas, seja por estas sempre terem como referência o processo produtivo e o papel nele desempenhado por grupos de homens na criação e na apropriação de excedente, o que não faria sentido a existência de uma “classe média”, seja por não haver um estudo sistemático sobre as classes sociais na obra de Marx (Hirano, 1974, p. 81). (a) A classe média – No tratamento das classes sociais, embora DCB sublinhe a importância das classes trabalhadora e empresarial – a esta última Bresser-Pereira (1964) dedicara boa parte de suas primeiras pesquisas, principalmente sobre suas origens étnicas e o papel da imigração em sua constituição –, a marca de sua análise reside, indubitavelmente, no papel relevante que atribui à “classe média”. Assim, se Marx foi pelo menos uma das fontes inspiradores da inclusão das classes sociais na análise, inova ao destacar a referida classe média – segmento nunca muito claro ou de difícil definição em análises estritamente marxianas, seja por estas sempre terem como referência o processo produtivo e o papel nele desempenhado por grupos de homens na criação e na apropriação de excedente, o que não faria sentido a existência de uma “classe média”, seja por não haver um estudo sistemático sobre as classes sociais na obra de Marx (Hirano, 1974, p. 81). Para Bresser-Pereira, todavia, para que o processo de desenvolvimento tenha início faz-se necessário que haja uma revolução política; e, para que esta se efetive, é imprescindível a participação da classe média. Esta tese ocupa papel relevante em sua construção teórica, basta ver os termos nos quais a expressa: “É essencial, todavia, que a classe dominante tradicional – geralmente uma oligarquia de caráter aristocrático – seja substituída no controle político por um grupo de classe média. Essa substituição será tanto mais rápida e completa quanto mais radical for a revolução política” (p. 34). Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 2 Economia, política e classes sociais: a história construída pelos homens Cabe, então, destacar que DCB foi das obras pioneiras no que tange à incorporação do entrosamento entre economia e política; este não é apenas suposto ou defendido teoricamente como tese, mas efetivamente integrado à análise. E isto se dá através de um tributo que se deve, mais uma vez, explicitamente, tanto a Marx como a Max Weber: a incorporação das classes sociais. Até então, tal procedimento restringia-se às análises de intelectuais tidos como “historiadores” ou “sociólogos”, como Caio Prado Jr., Nelson Werneck Sodré, Hélio Jaguaribe e Florestan Fernandes; em DCB, aparece em trabalho nitidamente de Economia – que, assim, assume sua verdadeira dimensão de Economia Política. A conseqüência, portanto, não é nada desprezível, pois empresta novo enfoque aos estudos sobre o desenvolvimento brasileiro: este não brota espontaneamente, não é mero resultado mecânico do estrangulamento externo e nem decorre de uma lei imanente superior. É fruto de decisões, de mudanças que passam a ser incorporadas e dependentes de agentes capazes de introduzi-las e difundi-las. Para haver desenvolvimento, argumenta Bresser-Pereira apoiado em Max Weber, critérios racionais devem predominar sobre os tradicionais, relações impessoais e burocráticas substituir as de caráter pessoal e patrimonial (p. 33). Vêm à tona, nesse momento, duas contribuições suas decorrentes, ou intimamente relacionadas, a esta proposição de entrosamento entre economia e política: (a) o papel das classes médias no processo de desenvolvimento; (b) a existência de pactos políticos que se sucedem ao longo do processo, os quais representam alianças entre classes e segmentos sociais e que se expressam como alianças responsáveis pela constituição de blocos majoritários, indispensáveis para garantir Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 28 O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro patamares viáveis de governança e de governabilidade. Veja-se mais de perto cada um deles. (a) A classe média – No tratamento das classes sociais, embora DCB sublinhe a importância das classes trabalhadora e empresarial – a esta última Bresser-Pereira (1964) dedicara boa parte de suas primeiras pesquisas, principalmente sobre suas origens étnicas e o papel da imigração em sua constituição –, a marca de sua análise reside, indubitavelmente, no papel relevante que atribui à “classe média”. 2 Economia, política e classes sociais: a história construída pelos homens Ilustra como exemplos as revoluções de Cromwell, na Inglaterra, a Francesa de 1789 e a Russa de 1917, mas também países como Índia, México e Egito em que militares ou segmentos médios nacionalistas tomam o poder e rompem com a ordem tradicional e agrária, muitas vezes dando ensejo a uma revolução nacional responsável pela mudança de modelo em prol do desenvolvimento industrial. Ao retornar ao caso brasileiro, ressalta o papel desses setores médios, seja na Proclamação da República, seja na “Revolução de 1930”, as quais interpreta como “revoluções de classe média”. Mas se estes setores perdem o poder ao longo da República Velha – com o que se possibilita a volta das oligarquias ao poder –, após a “Revolução de 1930”, ao contrário, a vitória foi irreversível: “Depois dela, jamais a oligarquia agrário-comercial brasileira voltou a contar com uma parcela sequer do poder que detivera durante séculos” (p. 43). Indo aos meandros de sua interpretação, cabe indagar: em maior nível de concreção, que segmentos sociais são referidos quando se fala de “classe média”? Consciente de sua complexidade, Bresser-Pereira mostra que sob este rótulo costuma-se agregar diferentes segmentos sociais e profissões, e com isto abrindo a possibilidade de agrupá-los de acordo com diferentes cortes analíticos. Estes vão desde classe média “tradicional” versus “emergente”, até sob a ótica de extratos de 29 Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. Pedro Cezar Dutra Fonseca Pedro Cezar Dutra Fonseca renda ou com recorrência à dicotomia classes proprietárias e não proprietárias, nestas últimas incluindo desde funcionários públicos civis e militares até operários especializados. Três tendências marcam a incorporação destes segmentos na sociedade brasileira: (a) sua integração, decorrente da complexidade das atividades produtivas, de comercialização e de administração pública e das empresas privadas; (b) seu o crescimento numérico, ao se mostrar estaticamente a expressiva expansão acompanhando o processo de desenvolvimento industrial, “desmentindo as previsões de Marx e repetindo o já ocorrido nas demais noções industrializadas” (p. 89); e (c) sua diversificação, com novas profissões e novos tipos de atividades decorrentes da própria complexificação do desenvolvimento. É dentro desses novos segmentos que serão recrutados os técnicos e os administradores – a tecnoburocracia –, decorrente do aparecimento de organizações burocráticas e racionais em substituição à antiga dominação tradicional e patrimonialista. A profissionalização torna-se imperativo diante da modernização e do desenvolvimento capitalista. 2 Economia, política e classes sociais: a história construída pelos homens O fato de ser detentor do conhecimento está na base da legitimidade deste segmento, que ganha expressão social e busca espaço nas arenas decisórias, seja na esfera pública ou nas organizações privadas. Seu fortalecimento fica patente após 1964, quando se estabelece um Pacto Burocrático-Autoritário, do qual participa juntamente com militares e empresários, e com a exclusão da classe trabalhadora. (p. 157). A ênfase nesse segmento burocrático pode sugerir, a primeira vista, uma aproximação com o “estamento burocrático” de Faoro. O próprio Bresser-Pereira explicita sua simpatia pela análise deste autor no que tange à formação histórica brasileira, da Colônia à Primeira República (p. 303). Todavia, discorda que esta seja mantida após 1930. Na visão de Faoro, em sua “viagem redonda” na qual sempre a mudança acaba sendo limitada com a perpetuação do “estamento burocrático” nas esferas de poder, a “Revolução de 1930” teria inclusive reforçado seu papel, com a ampliação da esfera estatal e o crescente intervencionismo nos campos da economia e da política nos anos seguintes. Bresser-Pereira, todavia, argumenta com razão – inclusive apoiado em Sérgio Buarque de Holanda –, que, ao assim proceder, Faoro ignora a diferença estabelecida por Max Weber entre patrimonialismo e burocracia racional–legal, bem como as novas instituições e regras administrativas da Era Vargas – como criação do DASP, ingresso no serviço público por concurso e planos de carreira, por exemplo – as quais vão no sentido de contra-arrestar, e não reforçar, o “capitalismo político” e patrimonista da análise de Faoro (p. 312). Ao comparar-se com Faoro, nota-se que a peculiaridade da análise de Bresser-Pereira reside em enfocar com mais destaque o conhecimento técnico e o saber da tecnoburocracia – estes fundamentam seu status e sua pretensão de poder. Já para Faoro é a participação nas instâncias de poder que assegura e perpetua os privilégios do estamento burocrático – o próprio poder, portanto, é pressuposto Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 30 O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro para exercer sua dominação, e não um atributo anterior a ele que viabiliza sua legitimidade. (b) Os pactos políticos – Sua contribuição no que se refere aos pactos políticos pode ser considerada tão ou mais inovadora do que a incorporação das classes e segmentos sociais. 2 Economia, política e classes sociais: a história construída pelos homens Há uma opção metodológica expressa já no primeiro parágrafo do capítulo 4 de DCB que se propõe ultrapassar tanto as análises consideradas pelo autor como “personalistas”, centradas nos personagens históricos, como as estruturalistas, na qual a História decorre e é explicada a partir de uma estrutura econômica, seja a partir de relações funcionais constituintes de um modelo, seja ao molde das análises marxistas assentadas na dicotomia entre infra e superestrutura. Mais uma vez as classes sociais vêm à tona, pois através delas incorpora-se a luta política na reconstituição da História, de modo que esta não é pré-determinada e o jogo de alianças, as ideologias e os embates são importantes para os desfechos: “Focalizaremos nossa atenção especialmente no exame dos interesses dos diversos grupos socioeconômicos e na análise das ideologias que expressam, em termos de valor, seus interesses” (p. 99). Nas palavras do autor, procurava-se uma síntese a qual denominou de “abordagem histórico-estrutural”, em que ao lado das variáveis estruturais não se abandonava de todo o enfoque nos personagens, essenciais no curto prazo e às vezes, mesmo no longo, ao ajudar configurar processos condicionantes de mudanças irreversíveis. Ter-se presente o contexto no qual fora formulada essa opção metodológica por parte do autor auxilia no entendimento de suas razões: dificilmente se pode explicar a crise do início da década de 1960 sem levar em conta fatores de ordem política, os quais desaguariam no golpe militar. De imediato se observa que, enquanto o mundo passava por fase expressiva de crescimento, a economia brasileira ia em direção contrária, agravada na conjuntura com a eleição e renúncia de Jânio Quadros, a resistência militar à posse de Goulart, a solução de compromisso encontrada no parlamentarismo e o posterior plebiscito, que assegurava plenos poderes ao Executivo com o retorno ao presidencialismo. A bipolaridade do mundo da Guerra Fria refletia-se internamente no debate entre nacionalistas (para seus opositores, “comunistas”) e liberais (“entreguistas”) – radicalizado desde a opção de Cuba pelo socialismo e com o crescimento do movimento sindical urbano (CGT), rural (ligas camponesas) e estudantil (UNE). Como explicar os conflitos e os percalços do “nacional- desenvolvimentismo” e da imaginação reformista da época sem levar em conta estes acontecimentos – sociais, políticos, ideológicos –, fatais para o desfecho do que selaria o destino do país para as próximas duas ou três décadas? Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 2 Economia, política e classes sociais: a história construída pelos homens Destarte, não pode deixar de causar surpresa ao leitor acostumado com as análises “econômicas” vigentes até então – ou melhor, com raras exceções, até hoje –, o que encontraria nos próximos capítulos, seja nos escritos na década de Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 31 Pedro Cezar Dutra Fonseca Pedro Cezar Dutra Fonseca 1960 ou mesmo nos recentemente incorporados ao livro. Bresser-Pereira, ao reconstituir cada conjuntura, estabelece um paralelo entre as mudanças econômicas e os pactos políticos responsáveis por sua sustentação ao longo do tempo, trazendo à liça o comportamento dos partidos, das classes sociais e dos principais personagens; discorre sobre as ideologias em conflito, suas intenções e pretensões, com a convicção de que a complexidade do processo histórico ultrapassa de longe as demarcações de área consagradas rigidamente no meio acadêmico (inspiradas na segmentação e na classificação das ciências de tradição positivista). Cada pacto define-se não só pelas classes e segmentos sociais que o sustentam, mas também pela ideologia e valores compartilhados por seus partícipes. Por exemplo: se de 1930 a 1959 havia um Pacto Popular-Nacional vinculado ao “modelo econômico” de substituição de importações, em 1964 este é substituído por um modelo de “Subdesenvolvimento Industrializado”, selado pelo Pacto Burocrático-Autoritário. A expressão “subdesenvolvimento industria- lizado”, hoje incorporada ao vocabulário usual das análises sobre economia brasileira, é inovador e crítico. Inovador, pois consagra em uma mesma expressão elementos até então entendidos como excludentes: no bojo da ideologia nacional- desenvolvimentista, a especialização agrária e exportadora do país estava nas raízes do subdesenvolvimento, e a industrialização era a grande palavra de ordem para superar o atraso, a miséria e as desigualdades da concentração pessoal e regional da renda e da riqueza. E crítico, pois se chocava com o pensamento desenvolvimentista tradicional, inclusive o cepalino, para quem as questões distributivas e a reversão dos indicadores sociais atrelavam-se, de forma subordinada, à própria prioridade do crescimento econômico. Somente a partir da década de 1970, devido a grande concentração de renda verificada ao longo do “Milagre”, indiscutível a partir dos dados do censo daquele ano, a distribuição de renda entrou com força nas análises dos economistas. A própria terceira edição de DCB, de 1972, adicionará, em novo capítulo, discussão sobre a distribuição de renda, cuja temática já fora abordada pelo autor em artigo anterior (Bresser- Pereira, 1970). Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 2 Economia, política e classes sociais: a história construída pelos homens Há certa similaridade entre essa interpretação de pactos que se sucedem com a noção de Gramsci de hegemonia, quando a supremacia de uma classe ou fração de classe sobre outras se viabiliza através da cooptação e/ou aliança com outros segmentos sociais, inclusive os subordinados, conjugando os elementos consensuais à coerção para exercer seu poder. A hegemonia, assim, assemelha-se a um grande pacto que garante a governabilidade por certo tempo e lança mão das instituições e arenas da sociedade civil para se legitimar através do convencimento; uma crise de hegemonia manifesta-se como crise política, quando seu desfecho dificulta ou inviabiliza soluções pactuadas. Para estas se efetivarem não bastam as referidas instituições ou arenas de convencimento, mas que a(s) Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 32 O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro classe(s) favorecida(s) consigam ter certa força também econômica, de modo que não estejam apenas dispostas a pactuar em abstrato, mas também a fazer concessões. Na linguagem de Bresser-Pereira, há uma correspondência entre cada “modelo econômico” e determinado “pacto político” – e a interação entre ambos consagra, para determinada época, um conjunto de valores, idéias e regras que se corporificam em leis, instituições e acordos formais ou informais. Não há como, em se tendo presente este marco teórico, sustentar-se a separação entre economia, política e ideologia. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 3 Da inflação inercial ao novo desenvolvimentismo Na PUC-RJ, Edmar Bacha, Francisco Lopes, André Lara Resende e Pérsia Arida ofereciam também sua contribuição à teoria inercialista – inicialmente rotulada “neo-estruturalista”, pois se inspirava na antiga concepção dos modelos adotados pela Cepal, como o da inelasticidade da oferta agrícola, mas passíveis de generalização para qualquer ponto de estrangulamento, os quais simplificadamente compunham-se de duas equações: uma, responsável pelos fatores primários causadores da elevação dos preços, e outra, em que se especificava a propagação de seus efeitos para o conjunto da economia. Ao contrário da diferença entre “choque” e “tendência” dominante na PUC-RJ, e que reproduzia a dicotomia causa/propagação dos modelos cepalinos, Bresser e Nakano inauguraram a tríade fatores aceleradores, mantenedores e sancionadores da inflação. A nova teoria “sugeria que a solução do problema, embora difícil, não era tão custosa quanto a teoria ortodoxa pretendia” (p. 283). Além do mais, o programa de pesquisa lembrava o antigo estruturalismo em pelo menos outro aspecto essencial e não apenas teórico: perscrutava novo receituário para o combate à inflação, capaz de prescindir do choque ortodoxo. Buscava-se compatibilizar política antiinflacionária com crescimento – antigo sonho dos economistas não ortodoxos (como evidencia o “Plano Trienal” de Celso Furtado, para o governo Goulart), em parte compartilhado, à época, pelos próprios economistas de matriz mais conservadora, como fica visível na própria retórica do PAEG. Na década de 1980, outra motivação de ordem política incitava a pesquisa: a medida em que ficava visível o fim do regime militar, precisava-se construir uma proposta de política econômica diferente da implementada por Delfim Neto, cujos efeitos recessivos eram severamente criticados (naquela época havia o constrangimento de se criticar antes e se fazer exatamente o mesmo após chegar ao poder). Embora dentre os economistas formuladores da teoria da inflação inercial Bresser-Pereira fosse o economista mais estreitamente ligado às idéias de tradição cepalina, a inspiração teórica de seus artigos com Nakano não provinha diretamente do estruturalismo cepalino, mas da contribuição personalíssima de Ignácio Rangel. Já na primeira edição de DCB, em seu capítulo 5, Bresser-Pereira reverenciava a contribuição de “A inflação brasileira” de Rangel (1963). Contrariando as idéias dominantes à época, este entendia que a inflação não era de demanda, mas de custos, já que no país havia crônica escassez de demanda frente à capacidade ociosa existente. Comparava-se a inflação como um “mecanismo de defesa”, cuja função, dentre outras, era estimular a procura insuficiente. 3 Da inflação inercial ao novo desenvolvimentismo Como já foi referido, na última edição de DCB foram incluídos dez capítulos, os quais se somaram à outra dezena, já existente na quarta edição. Eles abarcam o período posterior a 1980, cujos principais temas são a crise fiscal do Estado, a escalada da inflação e a história dos diversos planos voltados a debelá-la, ao lado de descrições e interpretações dos dilemas de política econômica de cada conjuntura. Da mesma forma que nos capítulos escritos nas décadas de 1960 e 1970, tais dilemas, bem como suas soluções dependem de decisões e acordos políticos – e estes são fartamente mencionados, criticados e avaliados. Neste aspecto, a proposta metodológica do autor de entrosar economia e política numa mesma abordagem mantém-se consistentemente ao longo da obra, mas nestes últimos capítulos há a novidade de assumir-se como ator da História: muitas vezes escreve na primeira pessoa (e não só ao analisar o “Plano Bresser”...), vindo a mostrar, em uma fase de sua vida já de maturidade intelectual consolidada, o mesmo espírito de intervenção nos acontecimentos quatro décadas após seus primeiros artigos e livros, empolgado pelos trabalhos do ISEB. Desse período final, destaca-se sua contribuição à teoria inercialista da inflação. Assim como, grosso modo, na década de 1960 dominava o tema do desenvolvimento econômico nos estudos dos economistas e, na década de 1970, o da distribuição de renda, nos anos 1980 do século passado o foco direcionou-se para a inflação. As altas taxas, crescentes mês a mês, deixavam os economistas perplexos, principalmente após o forte ajuste fiscal promovido em 1983 (p. 283). A ortodoxia parecia não encontrar respostas para as dúvidas suscitadas pelo fenômeno; ao contrário de 1964, quando o ajuste de Campos/Bulhões optara pela recessão, mas conseguira debelar a inflação, abria-se agora espaço para os críticos do governo militar não se centrarem apenas no custo social do choque ortodoxo, mas em sua ineficácia. A resposta será encontrada na teoria da inflação inercial. Em um primeiro trabalho, Bresser-Pereira (1981) mostra como a inflação brasileira decorria de aumentos defasados de preços. A seguir, juntamente com Yoshiaki Nakano (1983; 1984), escreveu dois artigos: o primeiro, pioneiro ao proceder uma apresentação Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 33 Pedro Cezar Dutra Fonseca sistemática da teoria inercialista da inflação; e o segundo, com a sugestão de neutralizá-la através da combinação de congelamento e tabelas de conversão. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 3 Da inflação inercial ao novo desenvolvimentismo A convivência de inflação e recessão, que tanto desafiava os economistas conservadores do Primeiro Mundo, encontrava nos trópicos uma resposta criativa e desafiadora. Com ela, a oferta de moeda era endógena, contrariando os modelos Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 34 O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro dominantes: a expansão monetária era mais conseqüência do que causa da inflação, e esta não poderia ser desvendada sem incorporarem-se no modelo a estrutura de custos das empresas oligopolistas e a capacidade ociosa existente, marca estrutural de um mercado estreito e de renda concentrada. A novidade da concepção de Bresser e Nakano não residia, portanto, em mencionar os fatores causadores da inflação ou responsáveis por sua propagação, desafio sobre o qual já se debruçara boa parte dos economistas latino-americanos. A contribuição maior residia em buscar as razões dos fatores mantenedores, responsáveis pela inflação estável em cada novo patamar alcançado. E novamente as classes e segmentos sociais incorporam-se à análise, já que o comportamento das mesmas materializa-se no conflito distributivo: a inflação se mantém porque os agentes econômicos tentam assegurar “sua participação na renda, ou de manter o equilíbrio dos preços relativos, e dado que os aumentos de preços são realizados defasadamente, não tem alternativa senão repassar aumentos de custos para preços, repetir no presente a inflação passada, indexar informalmente seus preços” (p. 287). Assim, a inflação passada, via indexação, transportava-se ao presente; e este, pelo mesmo mecanismo, condenava o futuro. A leitura de DCB mostra que, apesar de sua participação ativa no debate sobre inflação, Bresser-Pereira manifestou-se contra as teses neoliberais ascendentes na década de 1990, principalmente com o “Consenso de Washington”, já nesse ano, como mostra sua Aula Magna na Anpec (Bresser-Pereira, 1990). A estabilidade era imprescindível, mas nunca um fim em si mesma – justificava-se como condição para o crescimento. O próprio “Plano Bresser” tinha como objetivo primordial o combate à inflação; todavia formulara-se-lhe inserido em um plano de médio prazo, Plano de Controle Macroeconômico, portanto tendo como suposto que a estabilidade de preços era passo necessário para a retomada dos investimentos públicos e privados, indispensáveis para a alavancagem de novo ciclo de crescimento. Mas se somente na década de 1990, com o Plano Real, logrou-se êxito no que concerne à inflação, o mesmo não ocorreu com relação ao crescimento. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 3 Da inflação inercial ao novo desenvolvimentismo Faz-se necessário retornar à cena, então, a problemática do desenvolvimento, abandonada na prática pelos sucessivos governos e também nas investigações teóricas dos economistas acadêmicos. O entendimento de que a macroeconomia tem como objeto central o estudo das políticas de estabilização relegou a segundo plano a preocupação com o desenvolvimento; passou a imperar no meio acadêmico um cosmopolitismo preocupante, em que a universalidade e a elegância das teorias são consideradas valores em si, independentemente de sua aplicabilidade e pertinência para um dado contexto histórico particular – fenômeno que reatualiza a controvérsia epistemológica na Economia Política desde seu nascedouro, como mostram as críticas de Malthus e List a Ricardo. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 35 35 Pedro Cezar Dutra Fonseca Crítico da ortodoxia convencional, entendida como incapaz de promover o desenvolvimento como tem mostrado a experiência de vários países latino- americanos, Bresser-Pereira passa, então, a advogar a necessidade de um “Novo Desenvolvimentismo”. Não se trata do retorno ao antigo modelo substitutivo de importações, assentado no fechamento da economia, em taxas de câmbio sobrevalorizadas e em investimentos estatais assegurados por poupança forçada – fontes de inflação que, por necessárias à reprodução do modelo, eram então assumidas como certo “custo do crescimento”, vistas com complacência, como algo com que se deveria conviver. Não cabe aqui expor as teses do “Novo Desenvolvimentismo”, embrionariamente constantes de DCB, mas aprofundadas posteriormente nos trabalho mais recentes do autor.3 Sublinha-se, não obstante, que o “Novo Desenvolvimentismo” não se afasta apenas do “velho” modelo substitutivo, mas também do neoliberalismo: não ignora que caberá ainda ao Estado promover a poupança forçada e investir em setores estratégicos; todavia, naqueles setores com razoável grau de competição, terá mais o papel de defender e garantir a concorrência. Com inspiração em Osborne e Gaebler, desfende-se um Estado gerencial em substituição ao vetusto Estado Patrimonialista – tarefa iniciada, mas não concluída, na Era Vargas. Para a construção da nova estratégia de desenvolvimento é fundamental romper com o antigo modelo que se assentava no desequilíbrio das finanças públicas e no déficit do balanço de pagamentos, portanto fomentadores do endividamento interno e externo. O “Novo Desenvolvimentismo” não é protecionista, o que fazia sentido na época da implantação do parque industrial no país. (3) Veja-se, neste sentido, os artigos disponíveis em: <www.bresserpereira.org.br>. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 3 Da inflação inercial ao novo desenvolvimentismo Por isso, rejeita a sobrevalorização do câmbio e vê nas exportações e na competitividade externa fontes indispensáveis para garantir o crescimento sustentado e a inserção soberana do país na economia internacional. Desta forma, chega-se a uma conclusão surpreendente: “tanto o saber convencional dominante quanto o dominado são insatisfatórios, porque ambos ideológicos e populistas e, por isso, incapazes de equacionar de forma aceitável essa incompatibilidade (distributiva)” (p. 363). Esclarecendo com mais detalhes: ao lado do populismo tradicional, ainda com seguidores, que valorizava o câmbio, aumentava salários nominais e a despesa pública com a boa intenção de garantir demanda efetiva, mas que lograva condenar o crescimento de longo prazo, aparece a figura do “neopopulista neoliberal”. Ambos possuem algo em comum: a apreciação da moeda doméstica, ao visar assegurar uma âncora artificial para a inflação, ao mesmo tempo em que eleva provisoriamente salários reais com propósitos eleitorais. A conseqüência mais dramática de ambos é obstar o crescimento de longo prazo: se o antigo Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 36 O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro populismo imprimia crescimento a curto prazo, mas tolhia sua sustentabilidade, ao comprometer as finanças públicas e o balanço de pagamentos, o novo o impede mesmo a curto prazo. Contudo as aparências não enganam: os dois tipos muitas vezes assumem posições que parecem antagônicas e até debatem esterilmente entre si: sem embargo, sua práxis aponta para a chegada em um mesmo lugar. Não deixa de ser irônico que esta interpretação de Bresser-Pereira antecipa como ambos podem coexistir, como no atual governo, onde a retórica do antigo populismo convive, sem constrangimentos, com a prática “neopopulista liberal”. O livro se encerra, portanto, sem abandonar os objetivos “permanentes” responsáveis por sua razão na crise da década de 1960: a retomada do desenvolvimento e da “revolução nacional”. Esta permanece inconclusa, com a continuidade da péssima distribuição de renda e da excludência social ao lado da dependência financeira e tecnológica. Trata-se de retornar ao nacionalismo não como ideologia totalitária ou com vocação xenófoba, mas no sentido de retomar a prática de utilizar ferramentas e instituições voltadas ao interesse nacional – expressão ideológica de um conjunto de crenças e ideários com que se autodefine a comunidade nacional, em busca de valores comuns. Nada há de retrógrado em se falar de nacionalismo neste contexto, pois não se advoga uma volta ao passado. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. (4) Nesse artigo, Bresser-Pereira sistematiza o debate da época em seis “interpretações”, as quais denomina: (a) vocação agrária; (b) nacional-burguesa; (c) autoritário-modernizante; (d) funcional capitalista; (e) superexploração imperialista; e (f) nova dependência. A perfilhação ou simpatia a esta última, que é a de F. H. Cardoso e E. Faletto, fica evidente ao longo do texto. Na conclusão, pondera: “a interpretação da nova dependência inclui socialistas democratas e social-democratas, ao mesmo tempo que apresenta uma análise mais realista do Brasil” (Bresser-Pereira, 1982, p. 298). 3 Da inflação inercial ao novo desenvolvimentismo Ao contrário de sebastianismo, pretende-se algo que o processo de substituição de importações não propunha, já que se assentava na formulação teórica de uma economia relativamente fechada e com dualidade estrutural entre mercado interno e exportações: a integração do país no mercado mundial. Volta à cena, então, em nova forma, a questão nacional, abandonada pela esquerda desde a época da Teoria da Dependência, quando passou a dar mais ênfase à contradição entre capital e trabalho e à redistribuição de renda. Assim, a primazia ora à “questão nacional” ora às “contradições de classe” – cujo debate tanto empolgou a intelectualidade marxista nas décadas de 1960 e 1970, ao dividir defensores entre uma e outra – segundo Bresser-Pereira não faz sentido em abstrato, posto que resulta de circunstâncias históricas. Explicando melhor: durante o período militar, de certa forma a “questão nacional” era contemplada, porquanto incorporada, mesmo que no contexto autoritário da Doutrina de Segurança Nacional da Escola Superior de Guerra. A ênfase das análises críticas concentrava-se, então, na democratização do país e na crescente concentração de renda. Com o neoliberalismo da década de 1990 a situação se alterou: faz-se premente o retorno à “questão nacional”, mesmo porque, sem tê-la presente – como mostram a ausência de um projeto nacional, a desestruturação de setores produtivos e a falta de investimentos em segmentos-chave da economia –, como pensar em melhor redistribuição de renda e encaminhamento de soluções à “questão social”? O “Novo Desenvolvimentismo” deve assentar-se na poupança interna e na manutenção de taxas de câmbio desvalorizadas ou realistas, como demonstra a experiência exitosa de vários países líderes em crescimento no século Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 37 Pedro Cezar Dutra Fonseca XX e, inclusive, no atual, e sem ter por pressuposto o déficit público permanente. Este força a adoção de taxas cambiais apreciadas, as quais induzem a um crescimento artificial dos salários e do consumo que, por conseqüência, diminuem a poupança doméstica. Logo, resulta de tal política macroeconômica a simples substituição de poupança interna por poupança externa; o país não cresce, aumenta o serviço da dívida e compromete o crescimento de longo prazo. XX e, inclusive, no atual, e sem ter por pressuposto o déficit público permanente. Este força a adoção de taxas cambiais apreciadas, as quais induzem a um crescimento artificial dos salários e do consumo que, por conseqüência, diminuem a poupança doméstica. 3 Da inflação inercial ao novo desenvolvimentismo Logo, resulta de tal política macroeconômica a simples substituição de poupança interna por poupança externa; o país não cresce, aumenta o serviço da dívida e compromete o crescimento de longo prazo. Propor a reincorporação à agenda da “questão nacional”, mesmo com nova roupagem, pode parecer estranho em um contexto em que a mundialização dos processos produtivos e a hegemonia do capital financeiro limitam cada vez mais a margem de atuação dos Estados Nacionais. Paradoxalmente, estes mesmos fenômenos são os responsáveis por exigir que o tema não possa ser ignorado. Seu abandono por parte da intelectualidade crítica do país remonta à década de 1970, com a hegemonia das teses elaboradas no curso de Ciências Sociais da USP e no Cebrap, críticas ao Nacional-Desenvolvimentismo e à Era Vargas, a quem se associou o fenômeno do “populismo”, teses essas em boa medida consubstanciadas na Teoria da Dependência. Cabe, neste ponto, uma pequena digressão sobre a relação entre esta e a contribuição de Bresser-Pereira em DCB. Como é sobejamente conhecido, há várias versões da Teoria da Dependência – como a de F. H. Cardoso e E. Faletto, a de G. Frank, a de R. M. Marini e a de Teotônio dos Santos –, e cada uma reivindica para si pioneirismo. Dentre elas, a que Bresser-Pereira mais se aproximou foi a primeira, como fica claro no oitavo capítulo de DCB e em artigo publicado no início da década de 19804. Em suas diversas formulações, as análises assentadas no conceito de dependência propunham criar um marco alternativo ao da Cepal para explicar o desenvolvimento econômico latino-americano e seus percalços a partir de meados da década de 1960, frente ao abalo decorrente da descrença nas teses subconsumistas e a concentração de renda crescente a acompanhar a industrialização, o que se chocava com o imaginário nacional-desenvolvimentista. Por outro lado, o apoio de amplos segmentos do empresariado nacional aos golpes militares punha em questão o discutido exaustivamente caráter revolucionário da burguesia nacional; esta dava mostras de preferir associar-se ao capital estrangeiro, ao “imperialismo”, a encabeçar uma aliança com os trabalhadores urbanos. Todavia, enquanto alguns teóricos como Frank, Marini e Santos recorriam a teses como “superexploração”, “subimperialismo” e “desenvolvimento do subdesenvolvimento” – a rigor acenando que somente com o socialismo poder-se- Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 3 Da inflação inercial ao novo desenvolvimentismo 38 O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro ia superar o atraso e a excludência social –, Cardoso e Faletto seguiram outro caminho. Nestes permanece a crítica ao caráter revolucionário da burguesia nacional; não se postula, entretanto, que esta desaparecera ou fora esmagada pela internacionalização da economia, posto que optara por associação com o capital estrangeiro e, mesmo que de forma subordinada, consolidou com ele uma aliança que excluía parte dos trabalhadores – embora capaz de incorporar parcelas significativas das classes médias. Esta se viabiliza porquanto não há veto do capital estrangeiro à industrialização; assim, ao contrário das versões anteriores, a de Cardoso e Faletto tem como um de seus sustentáculos a possibilidade de desenvolvimento e dependência coexistirem. Não se está fadado à estagnação nem à miserabilidade crescente, uma vez que este processo, mesmo com as contradições historicamente conhecidas no capitalismo, assenta-se no desenvolvimento das forças produtivas materiais e na inovação, no caso sob a liderança da grande empresa oligopolista. Nas palavras de Bresser-Pereira: Esta aliança estabelece as bases de uma nova dependência – de uma dependência tecnológica e política. Não se trata mais da dependência colonialista, antiindustrializante, que caracterizava a aliança da oligarquia agrário-comercial com o capitalismo internacional do século XIX e primeira metade do século XX. Depois que o capitalismo internacional estabeleceu no Brasil suas próprias indústrias, principalmente nos anos 1950, sua oposição à industrialização brasileira naturalmente desapareceu (p. 178). Claramente esta visão difere da primeira edição de DCB, cuja capa estampava nada menos que Getúlio Vargas. Mas esta aproximação de Bresser- Pereira com a Teoria da Dependência durou pouco, embora tenha raízes mais profundas. Se a “questão nacional” fora e voltaria a ser na década de 1990, com o “Novo Desenvolvimentismo”, o divisor de águas, há importantes pontos, principalmente metodológicos e teóricos, que ajudam a descortinar esta aproximação, mesmo não duradoura. Notem-se, por exemplo, alguns destes marcos, expostos por Cardoso e Faletto (1979) no capítulo inicial de Dependência e Desenvolvimento na América Latina, os quais consideram definidores de sua abordagem: (a) a necessidade de se entender que o desenvolvimento “implica fundamentalmente um processo de relações entre grupos, forças e classes sociais, através do qual alguns destes tentam impor ao conjunto da sociedade a forma de dominação que lhe é própria” (p. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 3 Da inflação inercial ao novo desenvolvimentismo 18); (b) a incorporação na análise, “em sua totalidade, as ‘condições históricas particulares’ – econômicas e sociais – subjacentes aos processos de desenvolvimento, no plano nacional e no plano externo” (p. 21); e, juntamente com estes, (c) “realçar as mencionadas condições concretas – que são de caráter estrutural – e ao destacar os móveis dos movimentos sociais – objetivos, valores, ideologias”, para que se “analise aquelas e estes em suas relações e determinações recíprocas” (p. 21). Ora, não se pode negar que essas proposições básicas de Cardoso e Faletto já estavam incorporadas em de DCB desde sua primeira edição – conquanto sem a Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 39 Pedro Cezar Dutra Fonseca teorização (e, quiçá, a pretensão) que as levasse ao patamar de nova teoria ou abordagem. E, além disso, com a recorrência às mesmas matrizes teóricas, admitidas separadamente por cada um de seus autores como seus marcos referenciais: Max Weber e Marx. A despeito disso, perpassa DCB algo incompatível com as análises dependentistas de qualquer matiz: o desenvolvimento sempre supõe a busca de certo grau de autonomia: não há como separá-lo, sociologicamente, do conceito de nação; há conflitos intransponíveis entre interesses nacionais e capital estrangeiro: este se subordina tão somente à lógica de sua própria afirmação e reprodução, e não há por que esperar – antes o contrário – que ambos sempre sejam coincidentes. Todavia, entre a pura e simples repulsa ao capital estrangeiro e a submissão há largo espaço – cuja mediação, negociação e barganha só podem ser feitas por uma instituição do porte do Estado. Para tanto, exige-se a implementação de políticas de caráter marcadamente nacional e de pactos políticos internos que a sustente, visando ao “interesse geral do país” – portanto, acima de cada uma de suas classes. Não se descarta, para sua consecução, o papel de uma elite – chamemo-la ou não de “burguesia nacional”. Assim, enquanto na Teoria da Dependência a incorporação das classes sociais de certo modo esvaziara a “questão nacional”, pois as alianças entre elas se sobrepunham ao conceito de nação, a leitura de DCB, ao contrário, sugere que a defesa de um projeto de desenvolvimento sustentado e socialmente equilibrado não pode ignorar que as economias dominantes e suas grandes corporações ainda recorrem à política – portanto, a seus governos – para fazer valer seus interesses internacionalmente. 3 Da inflação inercial ao novo desenvolvimentismo De forma alguma dispensam, antes sistematicamente recorrem ao poder diplomático ou militar de seus estados nacionais para impor seus interesses e pontos de vista. Não só há, portanto, espaço para que setores empresariais, trabalhadores e demais segmentos sociais de países como o Brasil se unam em torno de interesses comuns, como talvez seja este o único caminho para encaminhar soluções favoráveis a seus interesses. A assimetria e a concentração de poder político e econômico no plano internacional – semelhante ao que Joan Robinson (1979, p. 235) denominou, em certa ocasião, de “novo mercantilismo”, impõem determinadas regras do jogo que não podem ser ignoradas por países como o Brasil. Em artigo recente, Bresser-Pereira (2005) chega a propor como alternativa à teoria da “dependência-associada” outra, a qual sintetiza no oximoro “teoria do desenvolvimento nacional-dependente”. Nesta retoma a tese de que as elites brasileiras são ao mesmo tempo nacionais e dependentes, vivenciam esta contradição ou ambigüidade; às vezes submetem-se aos ditames da dependência, em outras reafirmam sua identidade nacional. Há espaço, por conseguinte, para a viabilização de um projeto nacional. E este supõe escolha consciente, opção por fins precisos e busca de meios apropriados para os atingir e, sobretudo, convencimento e comunhão de valores – ou seja, o que, em síntese, desde e sempre se denominou de “projeto nacional”. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 40 O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro Por isso, o livro se encerra com uma certeza e com uma conclamação: “Existe, portanto, um espaço para que o novo nacionalismo e o novo desenvolvimentismo voltem a orientar a política econômica e a reforma institucional no Brasil. Para que a Revolução Nacional Brasileira seja retomada” (p. 419). Conclusão A leitura de DCB não deixa dúvidas sobre a diversidade de fontes teóricas distintas que servem de sustentáculo para a consecução de uma análise responsável por incorporar novos elementos e abordagens para a discussão e o entendimento do desenvolvimento brasileiro após 1930. Assim, a recorrência a clássicos como Max Weber, Marx e Keynes associa-se a brasileiros como Celso Furtado e Ignácio Rangel e, com estas referências provenientes de raízes intelectuais díspares, constrói-se uma análise eclética e bem particular do processo histórico. Desde o início da obra, o autor evidencia consciência da envergadura de seu propósito, ao explicitar a multiplicidade de ângulos pelos quais se pode enfocar o país e propor uma representação sistêmica sua, posto que multifacetado e incapaz de ser passível de sínteses sem que anteriormente se proceda com acuidade a abordagem de inúmeras mediações: “No plano econômico, sabemos que o Brasil é um país industrializado, mas subdesenvolvido; no político, que é democrático, mas elitista; no plano social e racial, que é uma sociedade mestiça, heterogênea e injusta; no plano psicossocial, que é um povo não-contratual, tão cordial quanto violento” (p. 12). Como um único approach teórico poderia dar conta da reconstituição desta formação social tão peculiar e complexa? Não haveria mais pretensão que realismo por parte de quem se propõe a tal tarefa, talvez com amparo na unicidade de critérios, de cunho positivista, entre as ciências humanas e as naturais? Se o ecletismo em história da arte é na maior parte das vezes sujeito a diatribes dos críticos, não é o caso ao se tratar do pensamento econômico e político latino-americano e, por conseguinte, das principais interpretações histórico-sociológicas do Brasil. O próprio pensamento cepalino – possivelmente a expressão mais acabada que se teve de um pensamento econômico autóctone –, flui de vertentes formadoras tão dispares à primeira vista, como o nacionalismo de List, o positivismo, o reformismo de Stuart Mill e as contribuições keynesianas sobre demanda afetiva (Fonseca, 2000). Há quem rechace o ecletismo ao lhe cobrar coerência lógica ou paradigmática, da mesma forma que o crítico sisudo prefere tolher a criatividade ao transformar a forma em fôrmas, como no poema de Manuel Bandeira. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. Conclusão Mas nas ciências sociais o ecletismo tem dado bons frutos, sempre repondo o desafio de como idéias surgidas em determinado contexto – na maior parte das vezes o europeu, como o liberalismo, o socialismo, o positivismo e o fascismo, – tomam 41 Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. Pedro Cezar Dutra Fonseca forma e se reproduzem noutro ambiente, adaptando-se e adquirindo um significado próprio que, por sua criatividade, nada tem a ver com qualquer analogia mecânica, ou com mera transposição ou colagem. Sob vários contornos, os intelectuais brasileiros têm se referido a esse fenômeno, desde o Manifesto Antropofágico que propunha devorar as idéias e tendências estrangeiras e após expelir o que não interessava, – ou seja, nacionalizando-as –, até a defesa das idéias “fora do lugar” de R. Schwartz (1973) e a “originalidade da cópia” da F. H. Cardoso (1980). Todavia, ao contrário destes, quer-se aqui ressair não propriamente a transposição ou o uso das idéias de um contexto a outro, mas como a mescla pode possibilitar o novo – algo como a realização, mais por razões pragmáticas que especulativas, do ideal de Victor Cousin. DCB exemplifica, com êxito, o ecletismo inovador. Ao lançar mão do diverso e ao selecionar os elementos que entende fazer sentido e contribuir para a reconstrução de um processo histórico concreto, acaba construindo uma interpretação singular. Algo como um sincretismo que se supera ao refundar-se em sua própria criação – a lembrar a síntese da fenomenologia do espírito de Hegel, para quem o patrimônio da razão autoconsciente não nascera sem predecessores e resultava do trabalho de todas as gerações intelectuais precedentes. Referências bibliográficas BRESSER-PEREIRA, Luiz Carlos. Desenvolvimento e crise no Brasil: história, economia e política de Getúlio Vargas a Lula. 5. ed. São Paulo: Editora 34, 2003. ________. Origens étnicas e sociais dos empresários paulistas. Revista de Administração de Empresas. n. 11, p. 83-106, jun. 1964. ________. Origens étnicas e sociais dos empresários paulistas. Revista de Administração de Empresas. n. 11, p. 83-106, jun. 1964. ________. Dividir ou multiplicar: a distribuição de renda e a recuperação da economia brasileira. Visão, p. 114-123, dez. 1970. ________. Dividir ou multiplicar: a distribuição de renda e a recuperação da economia brasileira. Visão, p. 114-123, dez. 1970. ________. A inflação no capitalismo de Estado (e a experiência brasileira recente). Revista de Economia Política, v. 1, n. 2, p. 3-42, 1981. ________. A inflação no capitalismo de Estado (e a experiência brasileira recente). Revista de Economia Política, v. 1, n. 2, p. 3-42, 1981. ________. Seis interpretações do Brasil. Dados, Rio de Janeiro, v. 25, n. 3, p. 269-306, 1982. ________. A crise da América Latina: Consenso de Washington ou crise fiscal? Pesquisa e Planejamento Econômico, v. 21, n. 1, p. 3-23, abr. 1991. Aula Magna no XVIII Congresso da ANPEC, Brasília, 4 dez. 1990. p. 3-23. ________. Do ISEB e da Cepal à Teoria da Dependência. In: TOLEDO, Caio Navarro (Org.). Intelectuais e política no Brasil: a experiência do ISEB. São Paulo: Revan, 2005. p. 201-232. ________. O novo desenvolvimentismo e a ortodoxia convencional. 2006. Disponível em: <www.bresserpereira.org.br>. Acesso em: 26 mar. 2006. ________. Política administrativa de controle da inflação. Revista de Economia Política, São Paulo, v. 4, n. 3, p. 83-107, jul./set. 1984. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 42 O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro O ecletismo inovador: Bresser-Pereira e o desenvolvimento brasileiro BRESSER-PEREIRA, Luiz Carlos; NAKANO, Yoshiaki. Fatores aceleradores, mantenedores e sancionadores da inflação. In: ENCONTRO NACIONAL DE ECONOMIA, 10, Belém, ANPEC, dez. 1983. Anais... CARDOSO, Fernando Henrique; FALETTO, Enzo. Dependência e desenvolvimento na América Latina: ensaio de interpretação sociológica. 5. ed. Rio de Janeiro: Zahar, 1979. ________. As idéias e seu lugar; Ensaios sobre as teorias do desenvolvimento. Petrópolis: Vozes, 1980. CASTRO, Antônio Barros de; SOUZA, F. E. Pires de. A economia brasileira em marcha forçada. Rio de Janeiro: Paz e Terra, 1985. FERNANDES, Florestan. A revolução burguesa no Brasil. São Paulo: Zahar, 1981. FAORO, Raymundo. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 43 Referências bibliográficas Os donos do poder; Formação do patronato político brasileiro. 7. ed. Porto Alegre: Globo, 1979. 2 v. FONSECA, Pedro Cezar Dutra. As origens e as vertentes formadoras do pensamento cepalino. Revista Brasileira de Economia, Rio de Janeiro, v. 3, n. 54, p. 333-358, jul./set. 2000. ________. Sobre a intencionalidade da política industrializante na década de 1930. Revista de Economia Política, São Paulo, v. 1, n. 89, p. 133-148, jan./mar. 2003. ________. Gênese e precursores do desenvolvimentismo no Brasil. Pesquisa & Debate, São Paulo, v.2, n. 26, p. 225-256, 2004. FURTADO, Celso. Desenvolvimento e subdesenvolvimento. [s.l.: s. ed.], 1961. ________. Formação econômica do Brasil. São Paulo: Nacional, 1971. ________. Dialética do desenvolvimento. Rio de Janeiro: Fundo de Cultura, 1964. ________. Teoria e política do desenvolvimento econômico. São Paulo: Abril Cultural 1983. (Coleção Os Economistas). HIRANO, Sedi. Castas, estamentos e ciências sociais. São Paulo: Alfa-Omega, 1974. HOLANDA, Sérgio Buarque de. Raízes do Brasil. 13.ed. Rio de Janeiro: José Olympio. 1976 OLIVEIRA, Francisco de. Crítica à razão dualista. São Paulo: Boitempo, 2003. PRADO JR., Caio. Evolução política do Brasil. 6. ed. São Paulo: Brasiliense, 1969. ________. História econômica do Brasil. 12. ed. São Paulo: Brasiliense, 1970. ________. A revolução brasileira. 7. ed. São Paulo: Brasiliense, 1987. PRADO JR., Caio. Evolução política do Brasil. 6. ed. São Paulo: Brasiliense, 1969. ________. História econômica do Brasil. 12. ed. São Paulo: Brasiliense, 1970. ________. História econômica do Brasil. 12. ed. São Paulo: Brasiliense, 1970. ________. A revolução brasileira. 7. ed. São Paulo: Brasiliense, 1987. ________. A revolução brasileira. 7. ed. São Paulo: Brasiliense, 1987. ROBINSON, Joan. Contribuições à economia moderna. Rio de Janeiro: Zahar, 1979. RANGEL, Ignácio. A história da dualidade brasileira. Revista de Economia Política, São Paulo, v. 1, n. 4, p. 5-34, out./dez. 1981. SCHWARTZ, Roberto. As idéias fora do lugar. Estudos Cebrap, n. 3, p. 151-161, 1973. TAVARES, Maria da Conceição. Auge e declínio do processo de substituição de importações no Brasil. In: ________. Da substituição de importações ao capitalismo financeiro. Rio de Janeiro: Zahar, 1972. Economia e Sociedade, Campinas, v. 16, n. 1 (29), p. 1-43, abr. 2007. 43
https://openalex.org/W1594927153
https://research-information.bris.ac.uk/files/90223408/art_3A10.1186_2Fs13063_015_0773_3.pdf
English
null
Who does not participate in telehealth trials and why? A cross-sectional survey
Trials
2,015
cc-by
8,851
Foster, A., Horspool, K. A., Edwards, L., Thomas, C. L., Salisbury, C., Montgomery, A. A., & O'Cathain, A. (2015). Who does not participate in telehealth trials and why? A cross-sectional survey. Trials, 16, Article 258. https://doi.org/10.1186/s13063-015-0773-3 Publisher's PDF, also known as Version of record License (if available): CC BY Link to published version (if available): 10.1186/s13063-015-0773-3 Link to publication record on the Bristol Research Portal PDF-document This is the final published version of the article (version of record). It first appeared online via BioMed Central at http://trialsjournal.biomedcentral.com/articles/10.1186/s13063-015-0773-3. Please refer to any applicable terms of use of the publisher. Foster, A., Horspool, K. A., Edwards, L., Thomas, C. L., Salisbury, C., Montgomery, A. A., & O'Cathain, A. (2015). Who does not participate in telehealth trials and why? A cross-sectional survey. Trials, 16, Article 258. https://doi.org/10.1186/s13063-015-0773-3 Foster, A., Horspool, K. A., Edwards, L., Thomas, C. L., Salisbury, C., Montgomery, A. A., & O'Cathain, A. (2015). Who does not participate in telehealth trials and why? A cross-sectional survey. Trials, 16, Article 258. https://doi.org/10.1186/s13063-015-0773-3 Abstract Background: Telehealth interventions use information and communication technology to provide clinical support. Some randomised controlled trials of telehealth report high patient decline rates. A large study was undertaken to determine which patients decline to participate in telehealth trials and their reasons for doing so. Methods: Two linked randomised controlled trials were undertaken, one for patients with depression and one for patients with raised cardiovascular disease risk (the Healthlines Study). The trials compared usual care with additional support delivered by the telephone and internet. Patients were recruited via their general practice and could return a form about why they were not participating. Results: Of the patients invited, 82.9 % (20,021/24,152) did not accept the study invite, either by returning a decline form (n = 7134) or by not responding (n = 12,887). In both trials patients registered at deprived general practices were less likely to accept the study invite. Decline forms were received from 29.5 % (7134/24,152) of patients invited. There were four frequently reported types of reasons for declining. The most common was telehealth-related: 54.7 % (3889/,7115) of decliners said they did not have access or the skills to use the internet and/or computers. This was more prevalent amongst older patients and patients registered at deprived general practices. The second was health need-related: 40.1 % (n = 2852) of decliners reported that they did not need additional support for their health condition. The third was related to life circumstances: 27.2 % (n = 1932) of decliners reported being too busy. The fourth was research-related: 15.3 % (n = 1092) of decliners were not interested in the research. Conclusions: A large proportion of patients declining participation in these telehealth trials did so because they were unable to engage with telehealth or did not perceive a need for it. This has implications for engagement with telehealth in routine practice, as well as for trials, with a need to offer technological support to increase patients’ engagement with telehealth. More generally, triallists should assess why people decline to participate in their studies. Trial registration: The Healthlines Study has the following trial registrations: depression trial: ISRCTN14172341 (registered 26 June 2012) and CVD risk trial: ISRCTN27508731 (registered 05 July 2012). Keywords: Telehealth, Trials, Declines, Recruitment, Non-participation, Refusers Keywords: Telehealth, Trials, Declines, Recruitment, Non-participation, Refusers internet-based health forums. Globally, telehealth is becoming a prominent part of healthcare delivery. © 2015 Foster et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http:// creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Abstract Telehealth interventions are increasingly being tested in randomised controlled trials (RCTs). Some of these tele- health trials have reported high decline rates of over 75 % amongst potential participants [2, 3]. A recent re- view of 37 telehealth studies found an average decline rate of 32 %, but this varied between 4 % and 71 % for the individual studies; and only two studies were RCTs [4]. Decline rates may vary because of the health condi- tion under study. For example, some patient groups are * Correspondence: alexis.foster@sheffield.ac.uk 1School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield S1 4DA, UK Full list of author information is available at the end of the article Who does not participate in telehealth trials and why? A cross-sectional survey Alexis Foster1*, Kimberley A Horspool1, Louisa Edwards2, Clare L Thomas2, Chris Salisbury2, Alan A Montgomery3 and Alicia O’Cathain1 University of Bristol – Bristol Research Portal General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/red/research-policy/pure/user-guides/brp-terms/ RESEARCH Open Access Who does not participate in telehealth trials and why? A cross-sectional survey Alexis Foster1*, Kimberley A Horspool1, Louisa Edwards2, Clare L Thomas2, Chris Salisbury2, Alan A Montgomery3 and Alicia O’Cathain1 TRIALS Foster et al. Trials (2015) 16:258 DOI 10.1186/s13063-015-0773-3 TRIALS TRIALS Foster et al. Trials (2015) 16:258 DOI 10.1186/s13063-015-0773-3 Background “Telehealth is the remote exchange of data between a pa- tient at home and their clinician(s) to assist in diagnosis and monitoring typically used to support patients with Long Term Conditions” [1]. Examples of telehealth in- clude online cognitive behavioural therapy, home moni- toring of health parameters such as blood pressure and Page 2 of 10 Foster et al. Trials (2015) 16:258 regarding the technological aspects of the intervention [2, 8, 18]. Second, some patients do not perceive the inter- vention to be beneficial [3, 18]. Third, some patients prefer face-to-face care, rather than healthcare delivered remotely, which is an integral component of telehealth in- terventions [2]. Fourth, some patients believe that there is no need for the intervention, for example, because routine healthcare is sufficient [3]. Fifth, many patients decline due to poor health [2, 19] or perceive their older age to be a barrier [2]. Sixth, patients are simply not interested [4], but it is not clear whether patients are not interested in the telehealth intervention or the research itself. Seventh, patients simply do not want to participate in the study [18]. Finally, some patients are too busy to participate [18]. These mirror some of the reasons why patients decline to participate in RCTs more generally: patients are not inter- ested or are too busy, are too ill, perceive themselves as ineligible, have transport barriers, have concerns about the intervention or do not want to be randomised [20–22]. known to be especially difficult to recruit, such as those with depression [5]. An alternative explanation is that selection criteria may have differed between trials. It is also possible that the nature of the telehealth interventions being tested affected the decline rates due to varying levels of acceptability amongst potential participants. known to be especially difficult to recruit, such as those with depression [5]. An alternative explanation is that selection criteria may have differed between trials. It is also possible that the nature of the telehealth interventions being tested affected the decline rates due to varying levels of acceptability amongst potential participants. High decline rates in RCTs generally are problematic because they may result in underpowered trials or extended recruitment periods which have resource implications [6]. Additionally, if those declining are not representative of the clinical population, external validity may be compromised [7]. The Healthlines Study The Healthlines Study consists of two linked RCTs of a telehealth intervention, one for patients with depression and one for patients with a raised risk of cardiovascular dis- ease (CVD risk) [23]. The telehealth intervention consisted of up to 12 months of telephone support from a health in- formation advisor and access to a range of online resources, including computerised cognitive behavioural therapy soft- ware packages, support for home monitoring (such as blood pressure monitoring) and links to online educational and support tools. To participate in the trials, patients had to have at least weekly access to an email account and the internet. The trials were approved by the National Research Ethics Service Committee South West-Frenchay (Reference 12/SW/0009) and have the following trial registrations: depression trial: ISRCTN14172341 (registered 26 June 2012) and CVD risk trial: ISRCTN27508731(registered 05 July 2012). To date, only a handful of studies have explored why pa- tients do not participate in telehealth studies [2, 3, 8, 18]. These have been fairly small quantitative studies of 625, 331 and 79 patients [18, 2, 3], with only one qualitative study with 19 patients [8]. There was a review of why pa- tients may not participate in telehealth research, but this was in relation to telehealth studies in general, rather than RCTs specifically [4]. Eight main reasons for declining participation in telehealth trials have been identified. First, patients have concerns, and in some cases anxiety, Background High decline rates may also indicate problems with the acceptability of the interven- tion, with implications for its uptake when delivered in routine practice. This latter issue may be particularly relevant to telehealth trials, since there may be physical barriers in terms of accessing technology [8], as well as psychological barriers such as low confidence in using the technology [9]. Understanding which types of patients do not participate in telehealth trials, and why, may help to improve recruitment rates, external validity and interpretation of trial results. Given the high decline rate in some telehealth trials and the limited literature investigating this topic, it is important to understand more about which patients do not choose to participate in telehealth trials and their reasons for this choice. We utilised recruitment data for two large linked RCTs of telehealth (the Healthlines Study) to undertake a quantitative study of who does not participate in telehealth trials and why. There has been some research examining the types of patients who do not participate in telehealth trials. No gender differences have been found in telehealth trials [2] or telehealth studies which use other methodologies [4]. Older adults are more likely not to participate in tel- ehealth trials [2, 10] due to technological demands and because they have less access to technology [8, 9, 11]. This higher non-participation rate amongst older people also mirrors RCTs more generally [12, 13]. In terms of differences in participation amongst socio-economic groups, one telehealth trial did not find any differences [2]. However, studies of routine telehealth services report lower uptake amongst patients from lower socio- economic groups [14]. This mirrors the evidence based more generally on healthcare research, where there are lower response rates from patients experiencing greater socio-economic deprivation [15, 16]. There is no evidence on participation in telehealth trials by ethnic minority groups. However, these groups are usually under-represented in RCTs in the United Kingdom and North America, partly because a common exclusion criterion is the inability to speak English fluently [17]. Recruitment of patients Data on the age, sex and ethnicity of invited patients was collected from the general practice records. However, ethnicity was poorly recorded in practice records, and the study had to reply on self-report from patients who returned forms. For this reason, ethnicity is missing for non-responders. Levels of socio-economic deprivation were derived from the general practice at which patients were registered. Analysis A two-stage analysis was conducted. The first stage was a comparison of the socio-demographic characteristics of the different response types. This included comparing the acceptors with a combined category of active decliners and non-responders. A comparison of active decliners and non-responders was then conducted to understand the effect of non-response bias on our study of why patients declined. Data were entered into SPSS. Ethnicity was re-categorised from multiple ethnicity cat- egories into a dichotomous variable of White or Black and Minority Ethnicity (BME). A variable was created to capture socio-economic deprivation based on the general practice at which a patient was registered. Deprivation was defined by the decile attributed to a general practice in the National Practice Profiles [24]. Patients registered at practices in deciles 1–5 were coded as ‘deprived’ and patients registered at practices in deciles 6–10 were coded as ‘affluent’. Chi-square and in- dependent t-tests were undertaken to test for differences by age, gender, ethnicity and deprivation. Practice staff sent the selected patients an information pack, including a personalised invitation letter, a patient information booklet, an acceptance form, a decline form and a freepost envelope. Approximately three weeks later, patients who had not responded were re-sent the informa- tion packs. Recruitment of patients Patients were recruited via 43 general practices between June 2012 and July 2013. Searches of practice records were undertaken to identify potential participants. For the depression trial, patients were identified who were aged 18 to 100 years old, and in the preceding three Foster et al. Trials (2015) 16:258 Page 3 of 10 n = 1020/24,152) were sent a decline form with the additional pre-specified reason of ‘I do not understand the study’. This was part of a sub-study where patients were sent a re-designed written patient information sheet to explore whether this increased recruitment [23]. Data on the age, sex and ethnicity of invited patients was collected from the general practice records. However, ethnicity was poorly recorded in practice records, and the study had to reply on self-report from patients who returned forms. For this reason, ethnicity is missing for non-responders. Levels of socio-economic deprivation were derived from the general practice at which patients were registered. months to the search visit were coded as having depres- sion, anxiety or low mood, or who were issued an anti- depressant prescription. Exclusion criteria were applied such as having psychosis, substance abuse issues or de- mentia. For the CVD risk trial, patients were selected who were aged 40 to 74 years and, based on data in rou- tine general practice records, were estimated to have at least a 19 % risk of having a cardiovascular event in the next ten years and had one or more modifiable risk fac- tors (being a smoker, overweight or having high blood pressure). Exclusion criteria were applied including being identified as part of the depression trial or having had a cardiovascular event, such as a heart attack or stroke. General practitioners at each practice were asked to exclude any patients they felt were unsuitable, for example, the recently bereaved [23]. After exclusions, 16,570 patients were invited to participate in the depres- sion trial, and 7582 patients in the CVD risk trial. A larger number of patients were invited in the depression trial because it was anticipated that there would be a lower participation rate. n = 1020/24,152) were sent a decline form with the additional pre-specified reason of ‘I do not understand the study’. This was part of a sub-study where patients were sent a re-designed written patient information sheet to explore whether this increased recruitment [23]. Active decliners compared to non-responders Active decliners compared to non-responders Of the patients who did not accept the study invite, de- cline forms were received from 35.6 % (7134/20,021). The active decliners were compared to non-responders to understand how representative active decliners were of all patients who did not accept the study invite. In both the depression and CVD risk trials, females were more likely to return decline forms compared to males (Depression: 41 %, n = 3049 females versus 29 %, n = 1333 males, P ≤0.001, X2 = 14.67, df = 1; CVD risk: 54 %, n = 907 females versus 42 %, n = 1845 males, P ≤0.001, X2 = 67.95, df = 1). Ethnicity could not be compared be- cause the data were not available for non-responders. In both trials, patients registered at affluent practices were more likely to return decline forms compared to patients registered at deprived practices (Depression: 32 %, n = 3239 affluent versus 29 %, n = 1143 deprived, P ≤0.001, X2 = 14.31, df = 1; CVD risk: 46 %, n = 2001 affluent ver- sus 43 %, n = 751 deprived, P = 0.039, X2 = 4.24, df = 1), although differences were not large. In both trials, pa- tients who returned decline forms were more likely to be older than non-responders (Depression: Mean age: Active decliners: 59.7 years versus Non-responders: 46.5 years, P ≤0.001, t = −45.679; CVD risk: Mean age: Active decliners: 67.4 years versus Non-responders: 64.4 years, P ≤0.001, t = −18.740). Acceptors, active decliners and non-responders I i d i ld f Invited patients could return an acceptance form (accep- tors). On receipt of this form, they were contacted by a researcher to assess their eligibility. Alternatively, patients could return a decline form (active decliners), or choose not to respond (non-responders). The decline form was anonymous, but linked to demographic infor- mation from the general practices through a study ID number. Patients were asked to indicate why they were declining to participate by ticking one or more of the pre-specified reasons provided on the form, including: The second stage involved exploring the reasons why patients declined to participate in the trials. Frequencies and percentages were calculated to understand the prevalence of each reason. The other reasons patients provided for declining were coded by one researcher (AF) and checked by another researcher (KAH). Of the 979 patient-reported ‘other’ comments in the depression trial, the researchers initially disagreed on the coding for 204 (20.8 %). Of the 551 CVD risk ‘other’ comments, there was disagreement on 63 (11.4 %). These comments were discussed and consensus reached on coding.  I do not have regular access to the internet or an email address  I do not feel confident enough with computers  I do not feel confident enough with computers  I am too busy at the moment  I am too busy at the moment  I do not feel I need any more support with my health at this time As a considerable proportion of responders declined because of technology-related reasons, and this issue is intrinsic to telehealth, further analysis was conducted. Responders were categorised as declining for a technology- related reason if they had selected the pre-specified reasons of no internet access or no computer confidence, or if they provided their own reason related to technology issues, such as not having a computer. Technology-related  I am not interested in this research The pre-specified reasons incorporated the common reasons for declining reported in previous literature on uptake in telehealth studies and RCTs more generally. In addition, there was an ‘other reason’ that responders could select, and they were asked to specify this reason in a free text box. A small proportion of patients (4.2 %, Foster et al. Trials (2015) 16:258 Page 4 of 10 decliners were compared with other types of decliners by age, gender, ethnicity and deprivation. Chi-square and independent t-tests were undertaken. t = −0.371). Acceptors, active decliners and non-responders I i d i ld f In the CVD risk trial, however, there was a statistically significant difference, with decliners being younger than acceptors (Mean age: Decliners: 65.75 years versus Acceptors: 66.33 years, P = 0.001, t = −3.321), although the mean difference in age was less than a year. Socio-demographic characteristics Decliners (active decliners and non-responders) compared to acceptors All those that declined the invite (active decliners and non-responders) were compared with those accepting the invite (Tables 2 and 3). In the depression trial, males (86 %, n = 4570) were more likely to decline than females (84 %, n = 9419), P ≤0.001, X2 = 11.43, df = 1. In the CVD risk trial, females (83 %, n = 1675) were more likely to decline than males (78 %, n = 4357 males), P ≤0.001, X2 = 18.26, df = 1. Although the differences were statisti- cally significant, they were not large for the depression trial. Of those whose ethnicity was known, in the depres- sion trial there was no difference in decline rates be- tween white patients (87 %, n = 4152) and BME patients 92 %, n = 82), P = 0.168, X2 = 1.90, df = 1), although num- bers were small. In contrast, there was some evidence in the CVD risk trial that patients from BME groups (82 %, n = 78) were more likely to decline than white patients (70 %, n = 2553), P = 0.08, X2 = 6.94, df = 1). Patients from deprived general practices were more likely to decline compared with patients from affluent general practices in both the depression and CVD risk trials (Depression: 87 %, n = 3947 deprived versus 84 %, n = 10,042 affluent declined, P ≤0.001, X2 = 21.4, df = 1; CVD risk: 85 %, n = 1725 deprived versus 78 %, n = 4307 affluent declined, P ≤0.001, X2 = 42.93, df = 1). In the de- pression trial, there was no difference in the mean age of decliners compared to acceptors (Mean age: Decliners: 50.66 years old versus Acceptors: 50.79, P = 0.710, Responses to the Healthlines Study invitation Overall, 82.9 % (20,021/24,152) of the patients invited did not accept the study invite (Table 1). Most of these patients (n = 12,887) did not respond at all, but decline forms were received from 29.5 % (n = 7134) of all pa- tients invited (Table 1). Response type differed by health condition, with patients with depression more likely not to accept than those with raised CVD risk (84 % depres- sion versus 80 % CVD risk, P ≤0.001, X2 = 452.8, df = 1). Active decliners compared to non-responders Number of reasons for declining Of the 7134 decline forms received, 19 were blank. These have been included in the response type calculations above, but they have been excluded from the reasons for decline analysis below. Ninety-nine percent (n = 7045) of patients who returned a decline form provided a reason for declining to participate in the trial (Depression: 98.9 %, n = 4327; CVD risk: 99.1 %, n = 2718). Most decliners pro- vided only one (Depression: 47.2 %, n = 2062; CVD risk: 39.4 %, n = 1079) or two reasons (Depression: 29.4 %, n = 1287; CVD risk: 33.6 %, n = 922). In both health conditions, over 90 % of decliners selected at least one of the pre-specified reasons on the form (Depression: 90.4 %, n = 3954; CVD risk: 93.8 %, n = 2571). Some patients provided another reason, with more patients in the depression trial doing this compared to the CVD risk trial (Depression: 23.5 %, n = 1021; CVD risk: 16.1 %, n = 441). In both health conditions, a small number of responders specified a reason that was compat- ible with one of the pre-specified reasons (Depression: 62; Table 1 Frequency of response type by health condition Table 1 Frequency of response type by health condition Type of response Accepted Declined Non-responders Total N % N % N % N % Depression RCT 2581 (15.6) 4382 (26.4) 9607 (58.0) 16,570 (100) CVD RCT 1550 (20.4) 2752 (36.3) 3280 (43.3) 7582 (100) Total 4131 (17.1) 7134 (29.5) 12,887 (53.4) 24,152 (100) Foster et al. Trials (2015) 16:258 Page 5 of 10 Table 2 The characteristics of the different response types for the depression trial Accepted n (%) Declined n (%) Non-responders n (%) All N =100 % Gender Female 1825 (16.2) 3049 (27.1) 6370 (56.7) 11,244 Male 756 (14.2) 1333 (25.0) 3237 (60.8) 5326 Ethnicity White 609 (12.8) 4152 (87.2) N/A 4761 BME 7 (7.9) 82 (92.1) 89 Deprivation Affluent 1967 (16.4) 3239 (27.0) 6803 (56.6) 12,009 Deprived 614 (13.5) 1143 (25.1) 2804 (61.5) 4561 Age (mean, (SD)) 50.8 (13.87) 59.7 (15.94) 46.5 (15.85) 50.7 Total 2581 (15.6) 4382 (26.4) 9607 (58.0) N = 16,570 Table 2 The characteristics of the different response types for the depression trial CVD risk: 29). These were added to the frequencies of the pre-specified reasons. Telehealth-related reasons Telehealth-related reasons, in terms of no computer confi- dence and/or no internet access, were prominent pre- specified reasons (Table 4), affecting 54.7 %, n = 3889 of active decliners. A small number of active decliners also specified that they were not participating because they did not like the telehealth intervention (1.4 %, n = 102), pri- marily because it was being delivered remotely rather than face-to-face; because of communication difficulties, such as a visual impairment, which meant that engagement in a telehealth intervention was problematic (1.3 %, n = 92); and because of practical barriers, such as not having a computer (1.3 %, n = 94). Number of reasons for declining A small number of responders ticked the other reason option, but instead of specifying a reason, they wrote a comment, such as “thank you, but no thank you” (Depression: 17; CVD risk: 8); these are not included below. Health need A lack of perceived health need was the second most frequent option in the pre-specified reasons (40.1 %, n = 2852). A small number of people also declined because they were satisfied with their current level of support, such as having regular health checks (3.1 %, n = 222), or they were currently receiving treatment for other health conditions (3.4 %, n = 245). People mainly ticked the pre-specified categories (Table 4), with one in five giving other reasons for de- clining (Table 5). Both the pre-specified reasons and the other reasons were categorised into four domains. These domains were developed thematically based on concep- tual similarities. Patients’ lives The fourth most common reason for declining was be- ing too busy (27.2 %, n = 1932). Some decliners provided other related reasons such as not having space in their life to participate in a trial, which sometimes related to not having the emotional capacity to participate (3.4 %, n = 243); or indicating that it was an inconvenient time to join the study, for example, because of planned time away from home (2.7 %, n = 189). aData on ethnicity was not available for non-responders Research-related reasons A small number of patients (1.6 %, n = 111) specified other rea- sons related to the research, including confidentiality concerns and perceiving the research as a waste of money or resources. trial, females were more likely to decline for a technol- ogy reason than males (P = 0.011, X2 = 6.52, df = 1), al- though there was no such difference in the depression trial (P = 0.508, X2 = 0.44, df = 1). Across both trials, there was no statistically significant difference in the ethnicity of patients who declined because of technology issues and those that did not (Depression: P = 0.590, X2 = 0.29, df = 1; CVD risk: P = 0.281, X2 = 1.16, df = 1), al- though the direction was that technology issues affected more people from BME communities. In both trials, pa- tients were more likely to decline because of technology reasons if they were registered at deprived practices (Depression: P ≤0.001, X2 = 30.98, df = 1; CVD risk: P ≤0.001, X2 = 21.22, df = 1), or older (Depression: P ≤0.001, t = −35.683; CVD risk: P = 0.001, t = −3.352). This age difference was more pronounced in the depres- sion trial, where there was a mean age difference of 15 years between patients who declined for technology reasons and those who declined for non-technology rea- sons compared with a one-year difference for CVD risk. Research-related reasons A lack of interest in the research was given as the fifth most common reason for declining (15.3 %, n = 1092). Related reasons were that patients perceived themselves as unsuitable for the trial, for example, because they did not have depression (1.9 %, n = 134); or the trial could be distressing, such as having to discuss health issues Table 3 The characteristics of the different response types for the CVD risk trial Accepted n (%) Declined n (%) Non-responders n (%) All N =100 % Gender Female 347 (17.2) 907 (44.9) 768 (38.0) 2022 Male 1203 (21.6) 1845 (33.2) 2512 (45.2) 5560 Ethnicitya White 1118 (30.5) 2553 (69.5) N/A 3671 BME 17 (17.9) 78 (82.1) N/A 95 Deprivation Affluent 1235 (22.3) 2001 (36.1) 2306 (41.6) 5542 Deprived 315 (15.4) 751 (36.8) 974 (47.7) 2040 Age (mean, (SD)) 66.3 (5.59) 67.4 (5.24) 64.4 (6.2) 65.87 Total 1550 (20.4) 2752 (36.3) 3280 (43.3) N = 7582 aData on ethnicity was not available for non-responders Table 3 The characteristics of the different response types for the CVD risk trial Page 6 of 10 Foster et al. Trials (2015) 16:258 Table 4 Pre-specified reasons for declining Reason Depression n (%) CVD risk n (%) Both conditions n (%) No internet access 1834 (41.9) 1491 (54.4) 3325 (46.7) No need for additional support with health issues 1717 (39.3) 1135 (41.4) 2852 (40.1) No computer confidence 1580 (36.1) 1225 (44.7) 2805 (39.4) Too busy 1214 (27.8) 718 (26.2) 1932 (27.2) Not interested 648 (14.8) 444 (16.2) 1092 (15.3) Do not understand what the research entailsa 11/215 (5.1) 5/91 (5.5) 16/306 (5.2) Other reason 1021 (23.5) 441 (16.1) 1462 (20.5) Total N = 100 % 4377 2741 7118 aThis option was only on the decline forms for 1020 patients as part of a sub-study. The 5.2 % is based on 306 decliners having this option on the form they returned Table 4 Pre-specified reasons for declining (1.9 %, n = 132). Both these reasons were more prevalent in the depression than in the CVD risk trial. A small number of patients (1.6 %, n = 111) specified other rea- sons related to the research, including confidentiality concerns and perceiving the research as a waste of money or resources. (1.9 %, n = 132). Both these reasons were more prevalent in the depression than in the CVD risk trial. Discussion Although non-participation in telehealth trials is a wide- spread problem and may introduce bias, this issue has only been explored within small-scale studies. Our study appears to be the largest to date to examine two key is- sues related to this problem in patients with long-term conditions: the characteristics of patients who do not participate in telehealth trials (comparing over 24,000 in- vited patients) and the main reasons for not participat- ing (responses from over 7000 patients). In total, 82.9 % of patients did not accept the study invite, which is com- parable to other telehealth trials [2, 3]. Patients from de- prived general practices were less likely to accept the study invite than those from affluent general practices. This contrasts with one telehealth trial which found no difference [2], but it is similar to findings in other health research generally [15, 16]. In the CVD risk trial, youn- ger patients and BME patients were less likely to accept the study invite. However, the differences were small. Older patients were more likely to decline because of technology reasons, and this is consistent with previous research [11]. For example, internet availability rates have been reported as only 26.5 % amongst patients over 74 years old [9]. Consequently, telehealth may be more accessible for health conditions where patients are generally younger, for example, cystic fibrosis. Patients registered at general practices categorised as deprived were more likely to decline because of technology reasons, as found in research regarding the uptake of telehealth in general [14]. Secondly, a common reason for declining was patients not feeling a need for additional support with their health, reflecting previous literature [3]. Health problems could also create a barrier, reflecting an obstacle to par- ticipation in trials in general [2, 19]. However, this result does contrast with other studies about the acceptability of telehealth, which found that poor health was not related to less interest in telehealth [9]. Consequently, it may be that declining the trial due to health issues is related to participation in the trial rather than receiving the intervention. Overall, reasons for declining could be grouped into those that were specific to the telehealth intervention, those that were health need-related, issues related to pa- tients’ lives and research-related reasons. Firstly, a large proportion of patients cited issues specific to telehealth interventions. Technology-related reasons Further analysis was conducted to compare responders who actively declined for technology-related reasons to those who actively declined for non-technology issues (Table 6). Decliners in the CVD risk trial were more likely to offer a technology-related reason than those in the depression trial (P ≤0.001, X2 = 126.93, df = 1). In the CVD risk trial, 63 % (n = 1729) of patients gave at least one reason for declining that was related to technology issues compared with 49 % (n = 2160) in the depression trial. There were some differences in the demographics of patients who declined for technology reasons com- pared with non-technology reasons. In the CVD risk Table 5 Other reasons for declining Category of reason Reason Depression n (%) CVD risk n (%) Both conditions n (%) Health need-related Health issues 195 (4.5) 50 (1.8) 245 (3.4) Satisfied with current support for their health 157 (3.6) 65 (2.4) 222 (3.1) Dissatisfied with health services 21 (0.5) 16 (0.6) 37 (0.5) Patients’ lives No space in their lives to participate in a trial 158 (3.6) 85 (3.1) 243 (3.4) Inconvenient at this time 104 (2.3) 85 (3.1) 189 (2.7) Research-related Perceive themselves as unsuitable 120 (2.7) 14 (0.5) 134 (1.9) Participation could cause distress 104 (2.4) 29 (1.1) 133 (1.9) Issues with the research 68 (1.6) 43 (1.6) 111 (1.6) Telehealth-related Dislikes the proposed intervention 77 (1.8) 25 (0.9) 102 (1.4) Practical barriers to participating 47 (1.1) 47 (1.7) 94 (1.3) Patient has communication difficulties 63 (1.4) 29 (11) 92 (1.3) Unknown Unknown 9 (0.2) 3 (0.1) 12 (0.2) Total N = 100 % 4327 2718 7045 Foster et al. Technology-related reasons Trials (2015) 16:258 Page 7 of 10 Page 7 of 10 Table 6 The characteristics of patients declining due to technology issues Depression CVD risk Characteristic Categories Technology issues N (%) Non-technology issues N (%) Total N =100 % Technology issues N (%) Non-technology issues N (%) Total N =100 % Gender Female 1493 (49) 1550 (51) 3043 601 (66) 304 (34) 905 Male 667 (50) 663 (50) 1330 1128 (61) 709 (39) 1837 Ethnicity White 2054 (49) 2101 (51) 4155 1615 (63) 938 (37) 2553 BME 43 (52) 39 (48) 82 54 (69) 24 (31) 78 Deprivation Deprived 625 (56) 483 (44) 1108 617 (69) 275 (31) 892 Affluent 1510 (47) 1722 (53) 3232 1112 (60) 738 (40) 1,850 Age (Mean (SD)) 67.4 (13.5) 52.3 (14.53) 67.6 (5.03) 66.9 (5.55) Table 6 The characteristics of patients declining due to technology issues Depression Table 6 The characteristics of patients declining due to technology issues This may be because there was a wider age range of pa- tients included in the depression trial compared to the CVD risk trial. This may be because there was a wider age range of pa- tients included in the depression trial compared to the CVD risk trial. in order to engage in these telehealth trials. It is also surprisingly high because in the patient information booklets for the Healthlines trials, it was explained to potential participants that methods were in place to facilitate access. For example, researchers could help patients to set up email accounts, and patients were allowed to use a family member or friend’s email address or computer. Strengths and limitations The key strength of the study is that it explored who does not participate in telehealth trials and the reasons why. It appears to be by far the biggest study exploring non-participation in telehealth trials, as the largest study we have identified included only 625 decliners. It also explores acceptability of telehealth trials in relation to two diverse long-term conditions, which is important as telehealth is often aimed at supporting patients with their long-term conditions [28]. Another important implication relates to the context- ual issues of patients’ lives, with patients choosing not to participate because of health or domestic issues. Given this, triallists could aim to minimise the commitment and burden to participants of both the intervention and the trial. Additionally, there were some differences in the reasons for declining between the depression and CVD risk trials, which indicates that whilst there are similar- ities in telehealth trials, the specific reasons may differ depending on the population from which the trial is recruiting. It is recommended that future telehealth trials include a similar process of exploring why patients decline to participate to help build a picture of issues affecting participation for different health conditions. There were some limitations. First, decline forms were only returned from 35.6 % of patients who did not accept the study invite. We do not know why patients did not respond. We have shown that active decliners were different from those who simply did not respond. These demographic differences may have an impact on the prevalence of the various reasons given for declining. For example, older people were more likely to return de- cline forms, but also to cite technology issues as the rea- son for declining. Therefore, technology reasons may be less of an issue in the wider patient population than in our sample. Second, we know little about the impact of ethnicity. The ethnicity of non-responders was not known in our study and there were only a small number of patients from BME groups in the decline population. Third, it was sometimes unclear whether patients were declining the trial or the telehealth intervention. Fourth, over 90 % of responders selected at least one of the pre- specified reasons for declining. This may be because they identified the key reasons why patients choose not to participate in a telehealth trial. Implications for telehealth trials and routine practice The main implication of this research for telehealth tri- als is that a large proportion of patients with long-term conditions, especially those in more deprived geograph- ical areas, either do not have access to the internet or do not perceive themselves to have the necessary techno- logical skills required for computer-based telehealth interventions. Telehealth interventions may be accept- able to more people if access is facilitated as part of any intervention, particularly for patients in areas of socio- economic deprivation. The implication for routine health care provision is that at present telehealth should not be the only care option because there is a significant pro- portion of the population without sufficient technology skills or access to use it. For example, patients with de- pression would need to be offered cognitive behavioural therapy in forms other than computer-based ones (such as books) or offered considerable technological support. Strengths and limitations However, there is the risk that patients may have selected those reasons because they were easy to tick. It is recommended that some of the other key reasons cited, such as health issues, be included in future decline forms. Fifth, the sample size was large and sometimes statistically significant differ- ences were very small differences and therefore unlikely Finally, a key reason for concern about low participa- tion rates in trials is that this may lead to recruitment bias, with those patients included in the trial not being representative of those for whom the intervention would be provided in routine clinical practice. This was not the most pressing issue here. Most patients declining did so because they felt that telehealth was not suitable for them rather than for reasons related to the research. Discussion They did not have access to a computer or the internet, or sufficient skill to use them; this has been found elsewhere [2, 4, 18]. The proportion of patients in this study declining because of technology reasons was high compared with a recent survey on tele- health, which reported that 68.5 % had computer tech- nology available [9]. Our study and this latter survey were both undertaken as part of the Healthlines Study, and both included patients with depression and raised CVD risk. It may be that people in our study gave this answer as an easy option to decline or that they felt they needed more access to, or confidence with, technology Finally, there were a number of reasons offered that were generic to trials, not just telehealth trials [4, 18, 21, 25, 26]. Some were related to patients’ lives, such as being too busy. We identified an issue from the free text answers around emotional capacity to participate in terms of not having ‘space in their life’, for example, having caring responsibilities. A proportion of patients declined for geographical reasons, for example, because they were moving house or they were frequently away from home (for example, having a second home abroad). Foster et al. Trials (2015) 16:258 Foster et al. Trials (2015) 16:258 Page 8 of 10 These are interesting both in the context of trials and routine practice of telehealth because they challenge a key principle of telehealth, which is that it is suitable for patients who have difficulty attending a general practice in person [27]. There were also some reasons given that were research-related, such as not being interested in participating. It was unclear whether this affected patients’ desire to participate in the trial or to receive the telehealth intervention. A small number of patients declined because they had issues with the research pro- cedures, such as not wanting to be randomised, confi- dentiality concerns or regarding the study as a waste of money. These reasons are consistent with previous lit- erature [25] and need to be better addressed in patient information booklets. However, such reasons were only a small proportion of the reasons that patients declined. to be important. Sixth, this analysis is based on partici- pation in two trials and the findings may be specific to the health conditions and the selection criteria for inviting people. Authors’ contributions AF conducted the analysis and drafted the manuscript. KAH co-coded the ‘other reasons’ and researched the background of the paper. AF, KAH and LE carried out the patient searches and collected the data. LE and CLT developed the decline form process and supported the interpretation of the findings. CS and AAM provided advice on the statistical analysis of the data. AOC provided advice on the analysis of the data and supported the writing of the manuscript. All authors read and commented on the manuscript as well as approving the final version. 11. Mancini J, Nogues C, Adenis C, Berthet P, Bonadona V, Chompret A, et al. Patients’ characteristics and rate of internet use to obtain cancer information. J of Public Health. 2006;28:235–7. 12. Herzog AR, Rodgers WL. Age and response rates to interview sample surveys. J Gerontol. 1988;43:200. 13. Williams B, Irvine L, McGinnis AR, McMurdo MET, Crombie IK. When “no” might not quite mean “no”; the importance of informed and meaningful non-consent: results from a survey of individuals refusing participation in a health-related research project. BMC Health Serv Res. 2007;7:59. 14. Hardiker NR, Grant MJ. Factors that influence public engagement with eHealth: A literature review. Int J Med Inform. 2011;80(1):1–12. Competing interests h h d l h Competing interests The authors declare that they have no competing interests. 10. Newman S, Rixon L, Hirani SP, Cartwright M, Benyon M, Silva L, et al. Whole System Demonstrator Trial. Evaluation of Telehealth and Telecare: Who accepts and rejects the equipment and why. 2011. 2020 Annual Health Summit. 10. Newman S, Rixon L, Hirani SP, Cartwright M, Benyon M, Silva L, et al. Whole System Demonstrator Trial. Evaluation of Telehealth and Telecare: Who accepts and rejects the equipment and why. 2011. 2020 Annual Health Summit. Acknowledgements This study forms part of the Healthlines Study research programme carried out in partnership with NHS Direct and NHS Solent. The programme aims to develop, implement and evaluate new interventions delivered by NHS Direct and NHS Solent to support patients with long-term conditions. This paper outlines independent research funded by the National Institute for Health Research (NIHR) under its Programme Grant for Applied Research (grant reference RP-PG-0108-10011). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. The Healthlines Study also acknowledges the support of the NIHR through the Primary Care Research Network. We thank all the members of the research teams at the Bristol, Sheffield and Southampton study sites; the NHS Direct and NHS Solent staff who developed the intervention content and software and delivered the intervention; and staff at the participating general practices. We also acknowledge the contributions of Hayden Bosworth and Felicia McCant (Duke University), Chris Williams (University of Glasgow), Jen Hyatt (Chief Executive, Big White Wall) and the MRC START research team. This study was designed and delivered in collaboration with the Bristol Randomised Trials Collaboration (BRTC), a UKCRC Registered Clinical Trials Unit in receipt of National Institute for Health Research CTU support funding. 15. Ekholm O, Gundgaard J, Rasmussen NKR, Hansen EH. The effect of health, socio-economic position, and mode of data collection on non-response in health interview surveys. Scand J Public Health. 2010;38:699–706. 16. Harald K, Salomaa V, Jousilahti P, Koskinen S, Vartiainen E. Non-participation and mortality in different socioeconomic groups: the FINRISK population surveys in 1972-92. J Epidemiol Commun H. 2007;61:449–54. 17. Hussain-Gambles M. Ethnic minority under-representation in clinical trials: Whose responsibility is it anyway? J Health Organization Management. 2003;17(2):138–43. 18. Palmas W, Teresi J, Morin PL, Wolf T, Field L, Eimicke JP, et al. Recruitment and enrollment of rural and urban medically underserved elderly into a randomized trial of telemedicine case management for diabetes care. Telemedicine and e-Health. 2006;12(5):601–7. 19. Bentley C, Mountain G, Thompson J, Fitzsimmons DA, Lowrie K, Parker S, et al. A pilot randomised controlled trial of a telehealth intervention in patients with chronic obstructive pulmonary disease: challenges of clinician-led data collection. Trials. 2014;15:313. 20. Lakerveld J, IJzelenberg W, van Tulder W, Hellemans I, Rauwerda J, van Rossum A, et al. Motives for (not) participating in a lifestyle intervention trial. BMC Med Res Methodol. 2008;8:17. Conclusions b h l In both trials, patients from deprived general practices were more likely to decline the study invite. Patients provided a range of reasons for declining to participate in a telehealth trial, and these reasons were generally consistent with the literature from the few other tele- health trials, as well as from trials more generally. Some reasons were specific to telehealth, such as not having Page 9 of 10 Page 9 of 10 Foster et al. Trials (2015) 16:258 internet access; others were generic to all studies, such as being too busy. However, some reasons were specific to individuals’ health needs, and so were different across the two groups of long-term conditions recruited to this study. The primary reason for declining was due to tech- nology issues; this was the case for patients who were registered at general practices in deprived areas. This has implications for the feasibility of both telehealth tri- als and telehealth in routine practice. For some patients, it was not clear if they were declining to participate in the trial or the intervention per se, for example, patients who said that they were not interested. If the latter, it raises questions about the acceptability of the telehealth intervention. It is recommended that other trials also explore why patients are not participating to facilitate a greater understanding of non-participation. Abbreviations BME Bl k d 9. Edwards L, Thomas C, Gregory A, Yardley L, O’Cathain A, Montgomery AA, et al. Are people with chronic diseases interested in using telehealth? A cross-sectional postal survey. J Med Internet Res. 2014;16(5):e123. 9. Edwards L, Thomas C, Gregory A, Yardley L, O’Cathain A, Montgomery AA, et al. Are people with chronic diseases interested in using telehealth? A cross-sectional postal survey. J Med Internet Res. 2014;16(5):e123. Competing interests The authors declare that they have no competing interests. References 1. Telecare Services Association. What is telehealth? http:// www.telecare.org.uk/consumer-services/what-is-telehealth. 1. Telecare Services Association. What is telehealth? http:// www.telecare.org.uk/consumer-services/what-is-telehealth. 2. Mair FS, Goldstein P, Shiels C, Roberts C, Angus R, O’Connor J, et al. Recruitment difficulties in a home telecare trial. J Telemed and Telecare 2006;12:26–8. 2. Mair FS, Goldstein P, Shiels C, Roberts C, Angus R, O’Connor J, et al. Recruitment difficulties in a home telecare trial. J Telemed and Telecare. 2006;12:26–8. 3. Subramanian U, Hopp F, Lowery J, Woodbridge P, Smith D. Research in home-care telemedicine: Challenges in patient recruitment. Telemed J E Health. 2004;10:155–61. 3. Subramanian U, Hopp F, Lowery J, Woodbridge P, Smith D. Research in home-care telemedicine: Challenges in patient recruitment. Telemed J E Health. 2004;10:155–61. 4. Gorst S, Armitage C, Brownsell S, Hawley M. Home telehealth uptake and continued use among heart failure and chronic obstructive pulmonary disease patients: A systematic review. Ann Behav Med. 2014;45(3):323–36. 5. Hughes-Morley A, Young B, Bower P. Factors affecting recruitment into depression trials: systematic review and meta-synthesis of qualitative evidence. Trials. 2013;14:82. 6. Sully B, Julious S, Nicholl J. A reinvestigation of recruitment to randomised, controlled, multicenter trials: a review of trials funded by two UK funding agencies. Trials. 2013;14:166. 7. Jones R, Jones RO, McCowan C, Montgomery A, Fahey T. The external validity of published randomized controlled trials in primary care. BMC Fam Practice. 2009;10:5. 8. Sanders C, Rogers A, Bowen R, Bower P, Hirani S, Cartwright M, et al. Exploring barriers to participation and adoption of telehealth and telecare within the Whole System Demonstrator trial: a qualitative study. BMC Health Serv Res. 2012;12:220. 8. Sanders C, Rogers A, Bowen R, Bower P, Hirani S, Cartwright M, et al. Exploring barriers to participation and adoption of telehealth and telecare within the Whole System Demonstrator trial: a qualitative study. BMC Health Serv Res. 2012;12:220. Abbreviations BME: Black and minority ethnic; CVD: Cardiovascular disease; RCT: Randomised controlled trial. Abbreviations BME: Black and minority ethnic; CVD: Cardiovascular disease; RCT: Randomised controlled trial. Received: 6 January 2015 Accepted: 21 May 2015 Abbreviations BME: Black and minority ethnic; CVD: Cardiovascular disease; RCT: Randomised controlled trial. the management of long-term conditions: study protocol for two linked randomized controlled trials. Trials. 2014;15:36. 24. Public Health England: National General Practice Profiles. http:// fingertips.phe.org.uk/profile/general-practice/data. 25. Cox K, McGarry J. Why patients don’t take part in cancer clinical trials: an overview of the literature. Eur J Cancer Care. 2003;12(2):114–22. 26. Parker Oliver D, Demiris G, Wittenberg-Lyles E, Washington K, Porock D. Recruitment challenges and strategies in a home-based telehealth study. Telemedicine Journal and e-Health. 2010;16(7):839–43. 27. Kessler D, Lewis G, Kaur S, Wiles N, King M, Weich S, et al. Therapist- delivered internet psychotherapy for depression in primary care: a randomised controlled trial. Lancet. 2009;374(9690):628–34. 28. McLean S, Protti D, Sheikh A. Telehealthcare for long term conditions. BMJ. 2011;342:120. Author details 1 21. Jenkins V, Farewell V, Farewell D, Darmanin J, Wagstaff J, Langridge C, et al. Drivers and barriers to patient participation in RCTs. British J Cancer. 2013;108(7):1402–7. 1School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield S1 4DA, UK. 2Centre for Academic Primary Care, NIHR School for Primary Care Research, School of Social and Community Medicine, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol BS8 2PS, UK. 3Nottingham Clinical Trials Unit, University of Nottingham, C Floor, South Block, Queen’s Medical Centre, Nottingham NG7 2UH, UK. 22. Barnes M, Wiles N, Morrison J, Kessler D, Williams C, Kuyken W, et al. Exploring patients’ reasons for declining contact in a cognitive behavioural therapy randomised controlled trial in primary care. Brit J Gen Pract. 2012;62. 23. Thomas CL, Man M, O’Cathain A, Hollinghurst S, Large S, Edwards E, et al. Effectiveness and cost-effectiveness of a telehealth intervention to support Page 10 of 10 Page 10 of 10 Foster et al. Trials (2015) 16:258 28. McLean S, Protti D, Sheikh A. Telehealthcare for long term conditions. BMJ. 2011;342:120. Foster et al. Trials (2015) 16:258 the management of long-term conditions: study protocol for two linked randomized controlled trials. Trials. 2014;15:36. 24. Public Health England: National General Practice Profiles. http:// fingertips.phe.org.uk/profile/general-practice/data. 25. Cox K, McGarry J. Why patients don’t take part in cancer clinical trials: an overview of the literature. Eur J Cancer Care. 2003;12(2):114–22. 26. Parker Oliver D, Demiris G, Wittenberg-Lyles E, Washington K, Porock D. Recruitment challenges and strategies in a home-based telehealth study. Telemedicine Journal and e-Health. 2010;16(7):839–43. 27. Kessler D, Lewis G, Kaur S, Wiles N, King M, Weich S, et al. Therapist- delivered internet psychotherapy for depression in primary care: a randomised controlled trial. Lancet. 2009;374(9690):628–34. 28. McLean S, Protti D, Sheikh A. Telehealthcare for long term conditions. BMJ. 2011;342:120. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit
https://openalex.org/W4214880755
https://www.researchsquare.com/article/rs-14087/v1.pdf
English
null
System for the analysis of human balance based on accelerometers and support vector machines
Research Square (Research Square)
2,020
cc-by
9,975
System for the analysis of human balance based on accelerometers and support vector machines Vinícius do Couto Pinheiro ( pinheiro vinicius@gmail com ) Vinícius do Couto Pinheiro  (  pinheiro.vinicius@gmail.com ) Universidade de Brasilia https://orcid.org/0000-0003-0929-0342 System for the analysis of human balance based on accelerometers and support vector machines Vinícius do Couto Pinheiro  (  pinheiro.vinicius@gmail.com ) Universidade de Brasilia https://orcid.org/0000-0003-0929-0342 Jake Carvalho do Carmo  Universidade de Brasilia Cristiano Jacques Miosso  Universidade de Brasilia Research Keywords: Posted Date: February 14th, 2020 DOI: https://doi.org/10.21203/rs.2.23520/v1 License:   This work is licensed under a Creative Commons Attribution 4.0 International License.   Read Full License System for the analysis of human balance based on accelerometers and support vector machines Vinícius do Couto Pinheiro  (  pinheiro.vinicius@gmail.com ) Universidade de Brasilia https://orcid.org/0000-0003-0929-0342 Jake Carvalho do Carmo  Universidade de Brasilia Cristiano Jacques Miosso  Universidade de Brasilia Research Keywords: Posted Date: February 14th, 2020 DOI: https://doi.org/10.21203/rs.2.23520/v1 License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Keywords: DOI: https://doi.org/10.21203/rs.2.23520/v1 Abstract Introduction: Disturbances in balance control lead to movement impairment and severe discomfort, dizziness, and vertigo. They can also lead to serious accidents, due to the loss of balance in critical conditions. It is important to monitor the level of balance in order to determine the risk of a fall and to evaluate progress during treatment. Some solutions exist, such as those based on cameras and force platforms, but they are generally restricted to indoor environments. We propose and evaluate a system, based on accelerometers and support vector machines (SVMs), that indicates the user’s postural balance variation by monitoring signals related to balance, and which can be used in indoor and outdoor environments. pinheiro.vinicius@gmail.com, Brazil 2Electrical Engineering Graduate Program, University of Bras´ılia, Departamento de Engenharia El´etrica, Faculdade de Tecnologia, UnB - Asa Norte, 70910-900 Bras´ılia, DF, jake@unb.br, Brazil 2Biomedical Engineering Graduate Program, University of Bras´ılia at Gama, 72444-240 Gama, DF, miosso@ieee.org, Brazil †Equal contributor Methodology: The proposed system consists of a second-skin shirt, six accelerometers, a 328 ATMEGA microcontroller, and a local storage module. For the training phase, we used the accelerometer signals acquired from a single subject under monitored conditions of balance and intentional imbalance, and used the scores provided by a validated commercial solution (the SWAY ® software) for establishing the reference target values. Based on these targets, we trained an SVM to classify the signal into n levels of balance (with n varying from 2 to 7) and later evaluated the performance using cross validation by random resampling. We also developed an SVM approach for estimating the center of pressure based on the signals from the accelerometers, by using as reference targets the results from a force platform by AMTI ®. We considered five possible regions for the center of mass, and our system was used to determine the correct region using the accelerometer signals. For validation, we performed experiments with a subject who was first standing, and later walking, performing a body rotation, and performing sudden intentional drops. Later the subject was requested to stand and then incline in four main directions, so the different centers of pressure (COPs) could be computed by our system and compared to the results from the force platform. We also performed tests with a dummy and a John Doe doll, in order to observe the system’s behavior in the presence of a sudden drop or a lack of balance. Pinheiro et al. System for the analysis of human balance based on accelerometers and support vector machines *Correspondence: pinheiro.vinicius@gmail.com 1Electrical Engineering Graduate Program, University of Bras´ılia, Departamento de Engenharia El´etrica, Faculdade de Tecnologia, UnB - Asa Norte, 70910-900 Bras´ılia, DF, *Correspondence: pinheiro.vinicius@gmail.com 1Electrical Engineering Graduate Program, University of Bras´ılia, Departamento de Engenharia El´etrica, Faculdade de Tecnologia, UnB - Asa Norte, 70910-900 Bras´ılia, DF, pinheiro.vinicius@gmail.com, Brazil 2Electrical Engineering Graduate Program, University of Bras´ılia, Departamento de Engenharia El´etrica, Faculdade de Tecnologia, UnB - Asa Norte, 70910-900 Bras´ılia, DF, jake@unb.br, Brazil 2Biomedical Engineering Graduate Program, University of Bras´ılia at Gama, 72444-240 Gama, DF, miosso@ieee.org, Brazil †Equal contributor *Correspondence: pinheiro.vinicius@gmail.com 1Electrical Engineering Graduate Program, University of Bras´ılia, Departamento de Engenharia El´etrica, Faculdade de Tecnologia, UnB - Asa Norte, 70910-900 Bras´ılia, DF, pinheiro.vinicius@gmail.com, Brazil 2Electrical Engineering Graduate Program, University of Bras´ılia, Departamento de Engenharia El´etrica, Faculdade de Tecnologia, UnB - Asa Norte, 70910-900 Bras´ılia, DF, jake@unb.br, Brazil 2Biomedical Engineering Graduate Program, University of Bras´ılia at Gama, 72444-240 Gama, DF, miosso@ieee.org, Brazil †Equal contributor DOI: https://doi.org/10.21203/rs.2.23520/v1 License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License RESEARCH *Correspondence: pinheiro.vinicius@gmail.com 1Electrical Engineering Graduate Program, University of Bras´ılia, Departamento de Engenharia El´etrica, Faculdade de Tecnologia, UnB - Asa Norte, 70910-900 Bras´ılia, DF, *Correspondence: pinheiro.vinicius@gmail.com 1Electrical Engineering Graduate Program, University of Bras´ılia, Departamento de Engenharia El´etrica, Faculdade de Tecnologia, UnB - Asa Norte, 70910-900 Bras´ılia, DF, pinheiro.vinicius@gmail.com, Brazil 2Electrical Engineering Graduate Program, University of Bras´ılia, Departamento de Engenharia El´etrica, Faculdade de Tecnologia, UnB - Asa Norte, 70910-900 Bras´ılia, DF, jake@unb.br, Brazil 2Biomedical Engineering Graduate Program, University of Bras´ılia at Gama, 72444-240 Gama, DF, miosso@ieee.org, Brazil †Equal contributor Introduction Postural stability refers to the ability to keep the human body in balance and is a fundamental condition for most human activities, especially locomotion. Poor balance usually affects performance in motor activities of daily living and is also one of the major factors in the risk of a fall [1, 2, 3]. Although stable control of posture and balance is automatic for people under normal conditions, it is a challenge for persons with vestibular deficiency, children with cerebral palsy, the elderly, and others who lack stability due to pathologies, deformities or injuries [4, 5, 6]. Trauma resulting from falls, especially in elderly people who live most of their daily life out of contact with the rest of society, are the most significant causes of fractures, injuries and deaths [5]. Falls can cost approximately 10 billion dollars annually worldwide [7, 6]. Elderly residents in long-term care homes fall for a variety of reasons and are more likely to suffer injuries due to falls than those living in the community [8]. The main factors that contribute to falls are a decrease in body weight and osteoporosis [8]. The higher mortality among the elderly results from complications of injuries resulting from falls, including head trauma, pulmonary embolism, pneumonia and hip fractures [9, 10]. There are also risks associated not only with falls, but also with other factors related to the loss of stability in people with a balance problem, e.g., persons with a neurological disorder, physical deformity or arthritis [11, 6]. Such risks involve a reduction in the quality of life due to an excessively cautious gait, instability, excessive fear of falling, and abnormal postural responses [3, 6]. These risks result in secondary characteristics, such as depressive symptoms, increased anxiety, mild extrapyramidal symptoms, and mild cognitive decline [12, 11]. Balance problems can affect humans of various ages, with several pathological conditions, in different ways. In order to generate an improvement in the living conditions of these people, there has been much research in this area [13, 14, 15]. In view of the importance of monitoring balance signals, the development of devices for the detection and prevention of all types of falls has become a much discussed topic [16, 17, 6]. Abstract Results and Discussion: The results show that the system can classify the acquired signals into two to seven levels of balance, with success rates ranging from 92.5% (for seven levels) to 98.3%, in 1000 sessions of random resampling. With two levels of balance, the system attains in the best case an accuracy of 98.9%. The average accuracy with two levels of balance was significantly greater than 93% (p=0.045) and the accuracy was significantly greater than 97% (p=0.044). With seven levels of balance, the accuracy was significantly greater than 94% (p=0.046) and the precision was significantly greater than 80% (p=0.049). The tests performed with the dolls show that the system is able to distinguish between the conditions of a sudden drop and of a recovery of balance after losing one’s balance. In this case, the average accuracy was greater than 95% (p=0.043) and the precision was greater than 95% (p=0.026). The system was also able to infer the centroid of each COP region with an error lower than 0.9cm (p=0.0045). These results suggest that the system can be used to detect variations in balance and, therefore, to indicate the risk of a fall even in outdoor environments. Keywords: postural balance; balance signals processing; support vector machines; images processing; accelerometers Page 2 of 16 Pinheiro et al. Introduction For the detection and prevention of falls, some biomedical engineering systems have been developed: (i) robotic prostheses that use electromyographic signals to better synchronize joint movement, such as real-time biofeedback [18]; (ii) interac- tive systems (virtual robots) that present periodic auditory stimuli and determine a synchronism with the patient’s uncoordinated steps [19]; (iii) gait monitoring through pressure sensors built into the shoes [20, 21]. Among these processes, there is also the possibility of remote monitoring systems with Wi-Fi and Bluetooth con- nections [22]. However, many of these rehabilitation and monitoring systems are limited to closed environments, laboratories, or clinics [1, 15], with restricted mobility due to excessive wiring. Others are also limited in this way because they depend on static platforms, or because they require the help of cameras, as in the case of home mon- itoring systems (residential installations) [10]. There are also other dynamic but costly monitoring solutions, such as the Vicon system, used in robotic tracking, vir- tual reality and ergonomic studies [23, 1]. A different approach using accelerometers and/or gyroscopes has also been developed [3, 24, 17, 25, 26, 27, 5], where changes Page 3 of 16 Pinheiro et al. in the acceleration and rotacional velocity are continually analyzed to determine whether the individual’s body is falling or not. If an individual falls, the device can employ GPS and a wireless transmitter to determine the location and issue an alert in order to get assistance. But these projects only indicate if there was a fall and do not detect if the patient lost their balance [16]. Another solution available is the force platform. Considered the gold standard, it is a device on the floor that has force sensors. The device allows monitoring the distribution of the person’s reaction forces on the platform. This gives an idea of the postural balance and allows the user to shift their weight, without taking their feet offthe platform, while monitoring its center of pressure. Introduction Although it is the gold standard, the platform has limitations, such as: the user has to move to the place where the platform is, as it is fixed; it does not monitor throughout the day; it cannot monitor walks; it is unable to detect changes in balance throughout the day, thus making it infeasible to be use, for example, to study a person’s balance over the course of the day and what possible situations are leading to a loss of balance. There are also mobile approaches to try to monitor balance, such as the SWAY application, which allows determining levels of balance, but it requires the person to place a cellular device in the sternum bone and perform specific tests. It also does not allow continual monitoring. In view of these limitations, the present paper proposes a system that allows continually measuring signals related to the balance. The system is installed on a shirt where accelerometer type sensors are installed, since the accelerometer-based approach makes it easier to quantify postural impairments compared to the conven- tional protocol with force plates, which are more expensive and not portable [27]. Accelerometers are particularly promising as they can be easily used in clinics [3], and a person can wear the system’s shirt during their daily activities, thus provid- ing the signals related to the user’s balance over the course of the day. From these signals, a classification of levels of balance is implemented. That is, there will be direct information from the sensors as well as the balance levels that are generated, and this continually generates information about postural balance throughout the course of the day. The system has been validated by comparing the data obtained with the results from a force platform, and also with the SWAY application. It has proved to be possible to monitor the balance levels through the use of the proposed system. Methods We present the development and evaluation of a system for acquiring signals re- lated to human postural balance and for automatically classifying these signals into different levels of balance over time. The system includes a second-skin shirt equipped with accelerometers, multi- plexers, a real time clock (RTC) module, and an SD card recorder. An Arduino microcontrolled board controls each module, processing and storing the acquired signals. Figure 1 shows a diagram of the complete system. First note that the system acquires the data from the accelerometers and, through classifiers, is able to define Page 4 of 16 Pinheiro et al. levels of balance (including states of imbalance). For training and validating the classifier, we used the SWAY software, already validated in the literature, which returns scores corresponding to the levels of balance. A dummy and a John Doe doll were also used to simulate sudden falls and recovery of balance, for the evaluation of disturbed static balance. Also note in Fig. 1 that the classification of signals into balance levels is based on support vector machines (SVMs), which must be trained before use. For training, we used a supervised strategy, in which several example signals corresponding to known class labels are presented to the classifier, as illustrated in Fig. 1(b). This allows us to determine the support vectors based on a numerical optimization procedure, and by using the support vectors we can later apply the system to new, unlabeled signals in order to determine the corresponding balance levels. This classification of unkown signals represents the system in its normal operation mode (as opposed to the training stage), as shown in Fig. 1(c). Hardware The prototype was simulated by the Proteus® software in its ISIS environment. In the next step, tests were done on a protoboard of the already simulated circuit. In the initial tests, we verified the acquisitions of the accelerometers that were con- nected to the multiplexers, as well as their Arduino programming code. Connections were made to the six accelerometers with three 4051 multiplexers, one for each axis of displacement. All six X -axes were connected to the inputs of one multiplexer. The same logic was implemented for the Y - and Z-axes. The outputs of the multiplexers were connected to the analog pins of one Arduino Uno. Once the data digitalized by the microcontroller was verified, the SD card module and the clock and calendar module were included in the following steps and their schedules attached to the initial programming code. The prototype made with the simulated circuit was tested and implemented on the back of a second-skin type shirt. The shirt fits and molds to the user’s body without limiting its movement. It also keeps the sensors in the same place during the experiments. The use of this shirt makes it more practical and ergonomic than other alternatives, such as elastics or velcros, which tend to cause discomfort to the user. The six plates, containing the ADXL335 accelerometer, were arranged according to Figure 2: the center pocket corresponds to the location of the acquisition circuit (SD, RTC and Arduino Uno modules), and a small pocket holds the battery. The accelerometers were distributed near the border between the cervical and thoracic spine, on top of each scapula, near the border between the thoracic and lumbar spine and at each junction of the lower posterior iliac spine. These points were selected because they are the places where there are greater perceptions by the accelerometers of the variation of inclinations of the body. Software Software The code implemented in the Arduino Uno controls the acquisition and variation of the accelerometers and the recording on the SD card. In the main code there was implemented an operating mode that writes to the SD card. Page 5 of 16 Pinheiro et al. Real time acquisition In this step the acquisition and validation of the acquired signals were made using the software developed in MatLab. The code was imple- mented to read the serial port (USB), plotting in real time. This way, it is possible to clearly perceive the changes in angle read by the accelerometer. For the trans- mission of the X and Y signals from the accelerometers, it was empirically realized that there was no delay in the reading when the sensors underwent sudden move- ments. Using this data, a classifier was trained to predict the static and dynamic body balance. Classifier training algorithm for static case In order to obtain data with which to start the training process, a routine was developed for data acquisition. The routine consists of setting up the prototype shirt to acquire the training data and using the SWAY application to get the scores used as reference. For the SWAY procedure, the user first presses the mobile device against the sternum bone and, when a sound signal is received, is asked to move in a predetermined direction as far as can be reached, while also trying to stay balanced. After the second signal is received, the user returns to the initial position. Using this routine, 30 acquisitions were performed for each of the 5 different modes: front, back, left, right and stopped. All data aquired from the prototype shirt along with the corresponding scores from the application were stored for later processing. In order to process all the data acquired, a program was developed in MatLab. The first step was to analyse the data, which was done by plotting 18 graphs corre- sponding to the three axes of the six accelerometers for all 150 routines. Then, the data was segmented in order to separate the portion of the signal that corresponds to the moment of greatest instability (for the inclined cases: front, back, left and right) or greatest stability (for the erect case). Software This process discards the moments in which the SD card is inserted and removed from the module (where there can be observed a great trembling of the signal), as well as the moments of displacement from the initial position to the position of instability and of displacement from the position of instability to the initial position. In this way, it can be observed that the signal is no longer in a larger band and is concentrated in a narrower band, corresponding better to the moments of instability or stability, depending on the routine performed. The study group, after attempting to determine how many seconds were needed to tell whether or not a person was balanced, determined that approximately two seconds would be sufficient to do this. Thus, it was determined that the classifier shoud also have two seconds to predict the balancing state, that is, the classification is performed in a signal of two seconds of duration, separated by applying a win- dow to the full signal. The group also determined that the displacements between consecutive windows would be one second, thus avoiding the loss of any part of the information. Also a window of the Hamming type was selected, since, besides presenting good spectral behavior, it avoids the appearance of spurious peaks. We also added to the information vectors the frequencies of the signal variation and the RMS values corresponding to each defined window. Now the classifier can verify if there is a large frequency variation or if some sensor value is higher than the others and thus infer whether the user is unbalanced or not. Pinheiro et al. Pinheiro et al. Page 6 of 16 After this stage, we started the training phase of the classifier and performance evaluation of the trained system. For training we presented windows of the signals with known balance levels (from the SWAY outputs), and this information was used to adjust the parameters of the SVM. In particular, the parameters called the receiver operation characteristics (ROC) [28, 29] were determined. To evaluate the performance, the hit and error rates were calculated after training. It should be noted that the performance may vary according to the selected train- ing examples. Thus, a common procedure in the study of classifiers is to randomly vary the training set and to evaluate the performance for each tested combina- tion [30]. Software During this evaluation, the trained system is applied both to the signals used for training and to the signals reserved exclusively for validation. In this re- search, 60% and 80% were used for training. The performance of each combination, in terms of the histograms of the error rates, was then recorded and the best perfor- mance, which reflects the best hit rates achieved in all training, is also highlighted. The dependence of the performance on the training examples is due to the fact that some sample sets may better reflect the variability of the input signals and thus allow for better generalization. Therefore, the evaluation of different combina- tions of examples may show the average performance and its variability, so care has been taken to increase the number of combinations of examples until the average performance converged. Four experiments were performed to observe the behavior of the system in relation to the levels of balance (including states of imbalance), with 1000 operations each: randomly chosen percentages of 80/20 were used for the training and validation of the SVM with a RBF type kernel. The difference in the experiments were the number of levels of balance and levels considered unbalanced. Thus, we set: Experiment 1 has two levels of balance and one which is unbalanced; Experiment 2 has three levels of balance of which one is unbalanced; Experiment 3 has five levels of balance of which one is a state of imbalance; Experiment 4 has seven levels of balance of which two are unbalanced. The program, in the end, returns histograms containing the error percentages found in each experiment for the training case and for the test case. Validation experiments Disturbed static case experiments Disturbed static case experiments Disturbed static case experiments Procedures were performed with an inert mannikin (sudden drop) and with a John Doe doll (attempt to recover one’s balance). The procedures follow a simple routine (Table 1), where every five seconds, the dummy is pushed, held and returned to its initial position (in the case of the mannikin), or there is a wait for it to return to its initial state of rest (in the case of John Doe), then pushing it back again. Thirty repetitions were executed for each of the four main directions (front, back, left and right) with the two dolls. At this point, using the same principle as in the previous software, the classifier can identify when the user is in the process of recovering balance or is falling. We conducted another set of training and validation sessions for this new exper- iment. In this case, we acquired 30 signals for each of the directions (front, back, right, left), meaning that we pushed both the mannikin and the doll in these direc- tions and collected the signals until fall (in the case of the mannikin) or recovery Page 7 of 16 Pinheiro et al. of balance (in the case of the John Doe doll). Note that the time in a fall is much smaller than in a recovery of balance. This is a problem for the SVM since it expects always the same number of inputs. To adress this problem, a few different strategies were tested: (i) we padded the smaller length signals with zeros (right zero-padding); (ii) we extended the smaller lenght signals with the latest sensor data (final sample extension); (iii) we considered as inputs the smallest interval only (thus removing the time intervals exceeding the fastest fall); (iv) we considered as inputs a fraction of the lowest interval. In terms of accuracy, specificity, sensitivity, and precision, strategies (ii) and (iii) provided the best results, suggesting that it is possible to decide between a fall and a recovery of balance by looking only at the beginning of the response to the perturbation (strategy iii, as if the way the body responds in the beginning is the determining condition), or by extending the last samples (strategy ii, as if the final samples only reaffirm the equilibrium condition). Disturbed static case experiments On the other hand, completing with zeros seems to represent a different range value that damages the classifier’s performance, whereas using even smaller time segments, when compared to (iii), only reduces the amount of useful information provided to the classifier. We performed 1000 training/validation sessions, using in each case 80% of the available data for training and the remaining data for validation. Therefore, the validation always considered data that was not used during the training stage. In each training/validation session, we used the RBF kernel, and two types of inputs: (i) the matrix of signals collected by our sensors installed on the John Doe doll, representing the condition of perturbation followed by balance recovery; (ii) the matrix of signals collected by our sensors installed on the mannikin, representing the condition of perturbation followed by fall. In both cases, the perturbation cor- responds to the doll or mannikin being pushed, each time in one of four possible directions (front, back, right, left). Comparison with the AMTI force platform Comparison with the AMTI force platform The procedures of the next experimental phase had the objective of evaluating if it is possible to use the accelerometer signals from the proposed system to evaluate the COP, as they would be provided by a force platform. For this purpose, signals from the proposed system and the AMTI force platform were collected simultaneously while the volunteer performed a sequence of predetermined movements. The routine of this procedure was as follows: the user climbs on the platform at the same time as the prototype shirt system starts to record, and, every seven seconds, the user changes their position in the following order: stopped, front, right, left, back (Ta- ble 2). The research group chose to change the position every seven seconds since it was estimated there should be two seconds for the position to change and approxi- mately five seconds stopped in each position. The user always tries to maintain the maximum stability in each position, without losing balance. The total acquisition time under this condition was 196 seconds. Since the participant maintained each position for seven seconds at a time, this allowed us to collect five complete cycles of measurements (for a total of 175 seconds, considering all five positions), plus an additional cycle in the sustained position, an additional cycle in the front position, and an additional cycle in the right position. Pinheiro et al. Pinheiro et al. Page 8 of 16 In this experiment, since the data were written in the following sequence: stopped, front, right, left and back, it was also necessary to segment the data as in the previous experiments, both for the accelerometers and for the AMTI platform data. To make the comparison, only the stable regions of the data (segmented parts) were used. But because there was no synchronization between the AMTI platform and the prototype shirt, it was not possible to know exactly which samples of the accelerometer signal correspond to which samples of the platform signal. Therefore, the signal was segmented to separate the corresponding regions where the user is more stable. Subsequently, the accelerometer signals and the platform signals were averaged. In order to match the accelerometer and platform signals, polynomial and en- semble interpolations were made in the accelerometer’s data, for all the acquisition sessions. Comparison with the AMTI force platform At this stage, tests were made varying the percentage of data used for training from 55% to 95%, using steps of 5%, the remaining being used only for validation. Another approach evaluated was the definition of different classes associated with the regions of stable pressure exerted by the participant on the platform. Thus, one class was assigned for vertical positioning, and one each for forward, right, left and back. For each of these five classes, the centroids of the COPs evaluated by the platform were calculated at each step of each acquisition session. Then, the classifier was trained to associate the measured accelerometer signals with the evaluated centroids. Again, different proportions for training data were tested and the remaining ones were used for validation. The purpose is to evaluate the performance of the system when mapping ac- celerometer signals to signals of COP. To this end, we calculated the errors between the centroids defined by the classifier and the COP provided by the platform. The observed errors were subjected to a statistical test to determine, with a level of con- fidence, the error band associated with the estimation of COP using the proposed system. Static case After training the system, which uses the information obtained from the prototype shirt and SWAY application scores, the program returned the results of the best trained systems for each of the conditions of the experiments presented. The data is in Table 3, indicating the percentage of error in each experiment for training and validation. According to the data contained in the table, it can be seen that the more balance levels are used for the training, the greater the probability of error and the lower the accuracy, precision, sensitivity and specificity. This is due to the fact that there is not enough data for the parameters in question. Thus, if there were more data available for training, it could possibly return better trained systems with better reliability parameters. There is the case where the error percentage of Test 3 was greater than that of Test 4 and, therefore, the sensitivity and precision of Test 3 were also smaller than Test 4. This is due to the fact that the randomly chosen samples for the best Test 4 were samples with more information for the training than the randomly chosen samples for the best Test 3. Through the obtained results, it can be seen that in Experiment 1 the greatest amount of errors for training was around 3.6%; in Experiment 2, around 5.9%; in Experiment 3, around 8.7%; and in Experiment 4, around 8.8%. Now, noting the number of errors for validation, the majority in Experiment 1 was around 5%; in Experiment 2, around 7.7%; in Experiment 3, around 12.5%; and in Experiment 4, around 11.8%. As expected, the error percentage for the validation of the trained systems is slightly higher than the error percentage for the training. However, a signal type not represented in the training set might appear in the validation set, causing errors. The results emphasize that the more balance levels are considered for training, the greater the chance of error for both training and validation. An observation to be made is that the error percentage for validation in Experiment 4 was lower than in Experiment 3. Although more levels of balance were used in Experiment 4, there was also one more level of imbalance than in Experiment 3. Method of analysis Statistical tests were performed for the static case, the perturbed static case, and the AMTI force platform experiments. Having in hand the acuracies, precisions, sensitivities and specificities of the experiments of the static case and the disturbed static case, we analyzed the question of the normality of the distribution of each parameter, using the Shapiro–Wilk and Kolmogorov–Smirnov tests for large samples and Lilliefors for small samples. We consider that a p value less than 5% indicates that the distribution of the parameter is not normal and a p value greater than 20% indicates that the distribution is normal. If the three tests have discrepant values, nonparametric tests must be used to determine the reliability of each parameter. If the distribution of the parameter is normal, Student’s t-test was used, but if the distribution is not normal, the Wilcoxon test was used. The same reasoning was employed for the force platform tests, where the parameter analyzed was the difference between the data provided by the shirt and that provided by the platform. Page 9 of 16 Pinheiro et al. Static case It is likely that the use of one more level of imbalance would have improved the performance of the trained system when compared to Experiment 3, which had fewer levels. In order to verify this statement, new experiments with five and seven levels of balance were made, considering one and two of them to be unbalanced. After the test, the error percentage for the validation of the trained systems con- tinued a little greater than the error percentage for training. It was expected that, after increasing the number of balance levels, the error percentage would increase as well and, when analyzing the case where only the number of balance levels from five to seven was increased, it is noticed that the number of error occurrences is higher and the percentage of error was slightly lower for the training, which still confirms that increasing the number of balance levels increases the error. Under this condition, five levels were still used, but there was the difference that one more level was considered unbalanced (three balanced and two unbalanced). It can be seen that although the number of error occurrences was slightly lower, the error Page 10 of 16 Pinheiro et al. percentage for the training increased by about 1%, which also increased the overall error. Comparing the cases where the seven levels were maintained, but there was the difference that one more level was considered unbalanced (five balanced and two unbalanced), we note that the number of error occurrences decreased and the per- centage of error for training remained approximately the same. In the case where the number of balance levels was changed from five to seven, but maintaing two of them as unbalanced, the number of error occurrences decreased and the error percentage as well. According to the obtained results, it can be concluded that increasing the number of levels of balance, or increasing the number of levels considered as unbalanced, increases the general error. However, for the data provided for the system, using two unbalanced levels out of seven levels in all, a better trained system was generated than the system of five levels, of which on was unbalanced. Hence, it can be stated that the data provided for the system considering seven levels, including one level of imbalance, generates a better trained system than considering five levels with one of them unbalanced. Static case The three normality tests indicated that none of the parameters followed a normal distribution, and so to determine the confidence interval, the Wilcoxon test was used. Table 4 shows the lower bounds for the evaluated performance metrics, for each experiment and considering a 95% confidence interval. As already confirmed, the more levels, the worse the results, due to the lack of information to better train the classifier. Also, as previously reported, Experiment 4 had better results than Experiment 3, which indicates that although the case of seven levels with two of them considered unbalanced, the system, with this infor- mation, proved to be more well-trained than the case of five levels with one of them considered unbalanced. Disturbed static case The program returned, as results of the best trained systems, the data of Table 5 and the results containing the percentages of errors and their respective error oc- currences for the training and validation for Test 1 (matrix completed with the last observed values) and for Test 2 (matrix with the duration times equal to the time of the signal that stabilizes the fastest). Among the 1000 operations, the pro- gram managed to train two systems in both tests with 100% accuracy, precision, sensitivity and specificity. These systems showed a high degree of reliability. In Test 1, when using the matrix completed with the last observed values, the system basically evaluates the end of the signal, so it only compares the difference in the user’s positions and whether or not the user is vertical. Also, the most chal- lenging issue would be to detect the moment before the user’s fall [31]. As can be observed, the training was perfect, because in the 1000 operations the error was 0%. In the validation tests, it can be seen that most of the operations presented very low percentages of error, less than 2%, which indicates a reliable system with a low error. In Test 2, using the matrix with duration equal to the time of the signal that stabilizes the fastest, the system evaluates what would be closer to reality, that is, it Page 11 of 16 Pinheiro et al. evaluates whether the person is in the process of losing their balance or falling, before getting to the floor. There are very low error percentages for training, less than 1% for all 1000 operations, and most of the validation operations had a percentage error of less than 4%, which also gives a reliable and low error system, but not as good as the system that was trained perfectly with a trivial operation, as was the case with Test 1. In order to shorten the duration of the signal, so that the system identifies as soon as possible a lack of balance or a fall, a study was made to know how many characteristics should be adopted in order to have a low error percentage. It was concluded that with five columns of information the program already manages to train systems with a very low error percentage, and the use of more information does not add much value to improve this percentage. Disturbed static case Thus, less information is used because there is a redundancy in the signals from different accelerometers, due to the rigidity of the doll. But this information could be important in more complex processes, such as the human torso. In addition, redundancy could be useful because of a potential loss of signals from some plates. The parameters of this case, for the three normality tests, also did not approach a normal distribution. To analyze the confidence interval, the Wilcoxon test was also used, generating the following results: For Test 1 (use of extended matrix), with 95.8% confidence that the accuracies are equal to or above 97%, and with 95.8% confidence that the sensitivities are equal to or above 95%. Precision and specificity gave 100% confidence for all 1000 operations, so it was not necessary to perform a statistical analysis for these parameters. For Test 2 (use of segmented matrix), with 95.7% confidence the accuracies are equal to or above 95%, and with 97.4% confidence the precisions are equal to or above 95%, 95.5% confidence the sensitivities are equal to or above 95% and 95.5% confidence the specificities are equal to or above 95%. Comparison with the AMTI platform Comparing the proposed system and the force platform within each group, both in polynomial interpolation and ensemble, a very small error was noticed. But, when joining more than one group of information, the errors increased, indicating the classifier was overfitting. From this information, the issue arose that, with each climb onto the force platform, the COP moved, in addition to the direction in which the experiments were carried out. Therefore, within each group, the interpolations gave coherent results, due to the overfitting, but when joining the groups, the information was not consistent. A possible suggestion for future work would be to acquire more data for training and, later, do a finer interpolation. In the latter approach, after separating the force platform data, from the stable pressure regions, into classes, the centroid for each of these classes was calculated with information from all groups of acquisitions. Then, the classifier was trained with different proportions of data (90% for training and 10% for validation) and the predicted output was compared to the centroids provided by the platform. The data of the accelerometers of each class was very close to the centroids of the respective class provided by the platform, both in training and validation, which Page 12 of 16 Pinheiro et al. suggests that the system allows calculating an approximate value of the positions of the COP from the data of the accelerometers (Figure 4). For a more detailed analysis, the error between the centroids of the COPs measured by the proposed system and the positions of the COPs given by the platform was also calculated. When observing the training, it can be seen that the classifier was able to identify all the classes for all the samples used for training. During validation, most classes were also identified correctly. There were a few cases where the classifier was not able to identify which class pertained to some samples. Therefore, for these cases, a maximum error is attributed, which is the largest distance between the centroids and the origin. The idea is: if the system does not identify a class, the zero point is conventionalized as the exit centroid; thus the largest distance that can be contained is the greatest distance between the centroids and the origin of the coordinate system. A thousand sessions of training and validation were done. Comparison with the AMTI platform In each session, the errors between the centroids estimated by the proposed system and the force platform were calculated. Based on the errors of each session, a statistical analysis was performed to evaluate the confidence in rejecting the null hypothesis that the mean error between the proposed system estimate and the force platform is greater than 0.9 cm. Finally, the mean is calculated for the p values obtained in the 1000 sessions. Table 6 shows the p values obtained when the error was evaluated for inputs used in training and for validation inputs. The results suggest that the system can estimate the COPs with an average er- ror of less than 0.9 cm, using only accelerometer signals. Note that this estimate is based on classes corresponding to regions in the two-dimensional space defined by the COPs. The subdivision of these regions using more classes may potentially increase the accuracy with which the COP is estimated. However, this would prob- ably require more examples of training, so that there would be enough points in each class. A proposal for future work is, for example, to repeat this experiment with ten times more points and subdivide the classes into smaller regions. Conclusion In this research, we evaluated a system for estimating both the level of balance and the class of pressure center, based on accelerometers positioned on the participant’s torso, using a second-skin type shirt. In evaluating the system’s performance, we compared the estimated levels of balance with those provided by a commercially available mobile solution, and with the pressure center class acquired from a static force platform. The experimental results show that the proposed system achieves an average ac- curacy between 96.6% and 98.9% when evaluating the balance level into two to seven classes (of which one or two are states of imbalance, depending on the case), and an error significantly lower than 0.9 cm when evaluating the center of pressure (p = 0.0042). These results suggest that the chosen characteristics extracted from the accelerometer signals provide the needed information for both the classification of the degree of balance and the center of pressure. They also suggest that this approach is viable for an outdoor evaluation of balance, as the equipment does not rely on heavy static devices and the processing is performed locally. In comparison Page 13 of 16 Pinheiro et al. with the mobile solution used as a reference, our solution does not require partic- ipants to hold a device in a special position, thus altering their normal behavior, and can be used while performing other activities. Since the classified data is available as the output of a microcontroller that can be easily connected to other devices, we would like, as a future work, to evaluate the use of the proposed equipment as a monitor for balance loss during daily activities, by connecting it to a speaker for generating an alarm and to a communication device to alert relatives in the case of a fall. Another possible investigation would involve the evaluation of the level of balance during physical exercises, specially if one combines the device with an electromyography system, in order to correlate the level of balance with physiological parameters such as muscle fatigue. List of abbreviations COP – Center of pressure ROC – Receiver Operation Characteristics RTC – Real time clock SVM – Support Vector Machines Author details 1Electrical Engineering Graduate Program, University of Bras´ılia, Departamento de Engenharia El´etrica, Faculdade de Tecnologia, UnB - Asa Norte, 70910-900 Bras´ılia, DF, pinheiro.vinicius@gmail.com, Brazil. 2Electrical Engineering Graduate Program, University of Bras´ılia, Departamento de Engenharia El´etrica, Faculdade de Tecnologia, UnB - Asa Norte, 70910-900 Bras´ılia, DF, jake@unb.br, Brazil. 3Biomedical Engineering Graduate Program, University of Bras´ılia at Gama, ´Area Especial, Proje¸c˜ao A, UnB - Setor Leste, 72444-240 Gama, DF, miosso@ieee.org, Brazil. Acknowledgements Acknowledgements VP thanks the Coordination of Superior Level StaffImprovement (CAPES) for financial support for his research. VP thanks the Coordination of Superior Level StaffImprovement (CAPES) for financial support for his research. Funding Funding This study was financed in part by the Coordena¸c˜ao de Aperfei¸coamento de Pessoal de N´ıvel Superior – Brasil (CAPES) – Finance Code 001. g This study was financed in part by the Coordena¸c˜ao de Aperfei¸coamento de Pessoal de N´ıvel Superior – Brasil (CAPES) – Finance Code 001. Author’s contributions VP designed and implemented most of the circuits and software, conducted the experiments, and part of the analyses, and wrote parts of the text. CJM advised the research, helped in developing the hardware and software, conducted part of the analyses, and wrote parts of the text. JCC coadvised the research, conducted part of the analyses, and wrote parts of the text. All the authors read and approved the manuscript. Availability of data and material Not applicable. Availability of data and material Not applicable. Competing interests The authors declare that they have no competing interests. 1. Yang, Y., Pu, F., Li, y., Li, S., Fan, Y., Li, D.: Reliability and Validity of Kinect RGB-D Sensor for Assessing Standing Balancer. IEEE Sensors Journal 14(5), 1633–1638 (2014) 2. Chiari, L.: Wearable systems with minimal set-up for monitoring and training of balance and mobility. In: 33rd Annual International Conference of the IEEE EMBS, pp. 5828–5832 (2011) 3. Mancini, M., Smulders, K., Cohen, R. G., Horak, F. B., Giladi, N., Nutt, J. G.: The clinical significance of freezing while turning in Parkinson’s disease. Neuroscience 343, 222–228 (2017) 4. M. Ferdjallah, G. F. Harris, P. A. Smith, S. Hassani, P. Johnson, K. Reiners: Postural stability assessment and orthotics. In: Pediatric Gait, 2000. A New Millennium in Clinical Care and Motion Analysis Technology, pp. 69–77 (2000) Declarations Ethics approval and consent to participate Ethics approval and consent to participate We submitted the acquisition protocol to the ethics committee of the College of Health Sciences, at the University of Brasilia. The ethics committee approval is available at https://plataformabrasil.saude.gov.br, under the Ethics Evaluation Certificate (CAAE, from the Portuguese form Certificado de Apresenta¸c˜ao para Aprecia¸c˜ao ´Etica) N. 26647619.1.0000.0030. Consent for publication Not applicable. Consent for publication Not applicable. Availability of data and material Not applicable. 4. M. Ferdjallah, G. F. Harris, P. A. Smith, S. Hassani, P. Johnson, K. Reiners: Postural stability assessment and orthotics. In: Pediatric Gait, 2000. A New Millennium in Clinical Care and Motion Analysis Technology, pp. 69–77 (2000) References 1. Yang, Y., Pu, F., Li, y., Li, S., Fan, Y., Li, D.: Reliability and Validity of Kinect RGB-D Sensor for Assessing Standing Balancer. IEEE Sensors Journal 14(5), 1633–1638 (2014) ( ) ( ) 2. Chiari, L.: Wearable systems with minimal set-up for monitoring and training of balance and mobility. In: 33rd Annual International Conference of the IEEE EMBS, pp. 5828–5832 (2011) ( ) 3. Mancini, M., Smulders, K., Cohen, R. G., Horak, F. B., Giladi, N., Nutt, J. G.: The clinical significance of freezing while turning in Parkinson’s disease. Neuroscience 343, 222–228 (2017) 4. M. Ferdjallah, G. F. Harris, P. A. Smith, S. Hassani, P. Johnson, K. Reiners: Postural stability assessment and orthotics. In: Pediatric Gait, 2000. A New Millennium in Clinical Care and Motion Analysis Technology, pp. 69–77 (2000) Page 14 of 16 Pinheiro et al. 5. Majumder, S., Mondal, T., Deen, M. J.: Wearable Sensors for Remote Health Monitoring. Sensors 17(130) (2017) ( ) 6. Rucco, R., Sorriso, A., Liparoti, M., Ferraioli, G., Sorrentino, P., Ambrosanio, M., Baselice, F.: 6. Rucco, R., Sorriso, A., Liparoti, M., Ferraioli, G., Sorrentino, P., Ambrosanio, M., Baselice, F.: Type and Location of Wearable Sensors for Monitoring Falls during Static and Dynamic Tasks in Healthy Elderly: A Review. Sensors 18(5) (2018) Type and Location of Wearable Sensors for Monitoring Falls during Static and Dynamic Tasks in Healthy Elderly: A Review. Sensors 18(5) (2018) 7. Honeycutt, P. H., Ramsey, P.: Factors Contributing to Falls in Elderly Men Living in the Community. Geriatric Nursing 23(5), 250–257 (2002) 8. Vance, J.: The clinical practice guideline for falls and fall risk 9. Seidler, E. D., Stelmach, G. E.: Reduction in sensoriomotor control with age. Oxford 47(3), 386–394 (1995) 10. Chen, Y. C., Lin, Y. W.: Indoor RFID gait monitoring system for fall detection. In (ISAC), 2010 2nd International Symposium on, pp. 207–121 (2010) 11. Guyton, A. C.: Tratado de Fisiologia M´edica, 6th edn. Guanabara, Rio de Janeiro (1986) 12. Huber-Mahlin, V., Gilado, N., Herman, T., Perez, C., Gurevich, T., Hausdorff, J. M.: Pro nature of a higher level gait disorder: a 3-year prospective study. J Neurol 257, 1279–1286 (2010) 13. England, J. D., Franklin, G., Gjorvad, G.: Quality improvement in neurology: Distal symmetric polyneuropathy quality measures. Neurology 82, 1745–1748 (2014) 13. England, J. D., Franklin, G., Gjorvad, G.: Quality improvement in neurology: Distal symmetric polyneuropathy quality measures. Neurology 82, 1745–1748 (20 14. References In: 2010 IEEE/ASME / ( ) ( ) 21. Bae, J., Kong, K., Tomizuka, M.: Design of a mobile gait monitoring system. In: 2010 IEEE International Conference on Advanced Intelligent Mechatronics pp 2293 2298 (2010) / ( ) ( ) 21. Bae, J., Kong, K., Tomizuka, M.: Design of a mobile gait monitoring system. In: 2010 International Conference on Advanced Intelligent Mechatronics, pp. 2293–2298 (2010) ., Tomizuka, M.: Design of a mobile gait monitoring system. In 21. Bae, J., Kong, K., Tomizuka, M.: Design of a mobile gait monitoring system. In: 201 International Conference on Advanced Intelligent Mechatronics, pp. 2293–2298 (2010) 22. Zhang, W., Zhu, X., Han, S., Byl, N, Mok, A. K., Tomizuka, M.: Design of a Network-based Mobile Gait Rehabilitation System. International Conference on Robotics and Biomimetics - Proceedings of the 2012 IEEE, 1773–1778 (2012) 23. VICON: VICON. Em http://www.vicon.com. ´Ultimo acesso: 17/5/2014 (2014) ` ´ ´ ´ ´ ´ 24. Camps, J., Sam`a, A., Mart´ın, M., Rodr´ıguez-Mart´ın, D., P´erez-L´opez, C., Arostegui, J. M. M., Cabestany, J., Catal`a, A., Alcaine, S., Mestre, B., Prats, A., Crespo-Maraver, M. C., Counihan, T. J., Browne, P., Quinlan, L. R., Laighin, G. O., Sweeney, D., Lewy, H., Vainstein, G., Costa, A., Annicchiarico, R., Bay´es, A., Rodr´ıguez-Molinero, A.: Deep learning for freezing of gait detection in Parkinson’s disease patients in their homes using a waist-worn inertial measurement unit. Knowledge-Based Systems 139, 119–131 (2018) 25. Chen, H., Xiong, F., Wu, D., Zheg, L., Peng, A., Hong, X., Tang, B., Lu, H., Shi, H., Zheng, H.: Assessing impacts of data volume and data set balance in using deep learning approach to human activity recognition. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1160–1165 (2017) ( ) 26. Bernad-Elazari, H., Herman, T., Mirelman, A., Gazit, E., Hausdorff, J. M.: Objective characterization of daily living transitions in patients with Parkinson’s disease using a single body-fixed sensor. J Neurol. 263(8), 1544–51 (2016) 27. Rovini, E., Maremmani, C., Cavallo. F.: How Wearable Sensors Can Support Parkinson’s Disease ( ) ( ) 27. Rovini, E., Maremmani, C., Cavallo. F.: How Wearable Sensors Can Support Parkinson’s Disease Diagnosis and Treatment: A Systematic Review. Frontiers in Neuroscience 11(555) (2017) , , pp Diagnosis and Treatment: A Systematic Review. Frontiers in Neuroscience 11(555) (2017) 28. Fawcett, T.: An introduction to ROC analysis. Pattern Recognition Letters 27(8), 861–874 (2006) 29. Oberkampf, W. L., Roy, C. J.: Verification and Validation in Scientific Computing, p. References Chai, Y., Ren, J., Han, W., Li, H.: Human gait recognition: Approaches, datasets and challenges. In: Imaging for Crime Detection and Prevention 2011 (ICDP 2011), 4th International Conference on, pp. 1–6 (2011) 14. Chai, Y., Ren, J., Han, W., Li, H.: Human gait recognition: Approaches, datasets and challenges. In: ( ) ( ) 15. Bilro, L., Pinto, J. L., Oliveira, J, Nogueira, R.: Gait monitoring with a wearable plastic optical sensor. In: Sensors, 2008 IEEE, pp. 787–790 (2008) 6. Jia, N.: Detecting Human Falls with a 3-Axis Digital Acceler g g g g ( ) ( ) 17. Chen, S., Lach, J., Lo, B., Yang, G. Z.: Toward Pervasive Gait Analysis With Wearable Sensors: A Systematic Review. IEEE Journal of Biomedical and Health Informatics 20(6), 1521–1537 (2016) 17. Chen, S., Lach, J., Lo, B., Yang, G. Z.: Toward Pervasive Gait Analysis With Wearable Sensors: A Systematic Review. IEEE Journal of Biomedical and Health Informatics 20(6), 1521–1537 (2016) Systematic Review. IEEE Journal of Biomedical and Health Informatics 20(6), 1521–1537 (2016) 18. Hidler, J., Neckel, N.: Inverse-Dynamics Based Assessment of Gait using a Robotic Orthosis. I 18. Hidler, J., Neckel, N.: Inverse-Dynamics Based Assessment of Gait using a Robotic Orthosis. In Proceedings of the 28th IEEE EMBS Annual International Conference pp 2293–2298 (2006) 18. Hidler, J., Neckel, N.: Inverse-Dynamics Based Assessment of Gait using a Robotic Orthosis. In: Proceedings of the 28th IEEE EMBS Annual International Conference, pp. 2293–2298 (2006) Proceedings of the 28th IEEE EMBS Annual International Conference, pp. 2293–2298 (2006) 19 Muto T Herzberger B Hermsdoerfer J Poeppel E Miyake Y Vi t l R b ti f I t ti Proceedings of the 28th IEEE EMBS Annual International Conference, pp. 2293–2298 (2006) 19. Muto, T., Herzberger, B., Hermsdoerfer, J., Poeppel, E., Miyake, Y.: Virtual Robotics for Interactive Gait Trainng - Improving Regularity and Dynamic Stability of the Stride Patterns. IEEE/ICME International 19. Muto, T., Herzberger, B., Hermsdoerfer, J., Poeppel, E., Miyake, Y.: Virtual Robotics for Interactive Gait Trainng - Improving Regularity and Dynamic Stability of the Stride Patterns. IEEE/ICME International Conference - Complex Medical Engeneering, 2007, 1240–1247 (2007) 20. Kong, K., Tomizuka, M.: A Gait Monitoring System Based on Air Pressure Sensors Embedded in a Shoe. IEEE/ASME Transactions on Mechatronics 14(3), 358–370 (2009) / ( ), ( ) 21. Bae, J., Kong, K., Tomizuka, M.: Design of a mobile gait monitoring system. References 767. Cambridge University Press, New York (2010) 30. Cawley, G., Talbot, N.: Efficient approximate leave-one-out cross-validation for kernel logistic regression. Machine Learning 71(2), 243–264 (2008) g ( ), ( ) 31. Cristianini, N., Taylor, J. S.: An Introduction to Support Vector Machines and Other Kernel-based Learning Methodss, 1st edn., p. 190. Cambridge University Press, United Kingdom (2000) Figures Figures [width=125mm]mainschematic [width=125mm]mainschematic Figure 1 Schematic describing the complete balance system. Note that there are two operation stages: the training stage, when we use kwnon data associated to different balance levels to tune the system, and the operation stage, when the system is used under real conditions to properly classify the current balance level. Page 15 of 16 Pinheiro et al. [width=80mm]shirt Figure 2 Disposition of the balance sensors over the developed shirt. [width=120mm]Hardware Figure 3 Block diagram describing the whole system for balance and pressure center measurement based on accelerometers. [width=120mm]trainamti Figure 4 Pressure centers estimated in the training phase by the platform (blue markers) and centroids generated by the proposed system (red crosses). Tables Table 1 Sketch dummy. Script of time established for realization of experiment with dummy and John Doe doll simulating a sudden fall and an attempt to reestablish the balance. Action Time (seconds) Initial position 0–5 Push 5 Return to initial position 5–10 Push 10 Return to initial position 10–15 Push 15 Return to initial position 15–20 ... ... Push 145 Return to initial position 145–150 Action Time (seconds) Initial position 0–5 Push 5 Return to initial position 5–10 Push 10 Return to initial position 10–15 Push 15 Return to initial position 15–20 ... ... Push 145 Return to initial position 145–150 Table 2 Script AMTI. Time course established for the realization of an experiment on the AMTI force platform. Table 2 Script AMTI. Time course established for the realization of an experiment on the AMTI force platform. Action Time (seconds) Stop 0–7 Front 7–14 Right 14–21 Left 21–28 Back 28–35 Stop 35–42 Front 42–49 ... ... Front 182–189 Right 189–196 Page 16 of 16 Pinheiro et al. Table 3 Results of the best systems trained for the static case: Experiment 1 (2 balance levels, 1 being unbalanced), Experiment 2 (3 balance levels, 1 being unbalanced), Experiment 3 (5 balance levels, 1 being unbalanced) and Experiment 4 (7 balance levels, 2 being unbalanced). Experiment 1 Experiment 2 Experiment 3 Experiment 4 Error percentage 1.7 3.9 7.1 6.3 True positives 253 79 18 51 True negatives 95 261 325 291 False positives 1 11 3 4 False negatives 3 1 6 6 Accuracy (%) 98.9 96.6 97.4 97.2 Precision (%) 99.6 87.8 85.7 92.7 Sensitivity (%) 98.8 98.8 75.0 89.5 Specificity (%) 98.9 98.8 99.1 98.6 Table 4 Lower bound for the measured performance metrics for each experiment, considering a 95% confidence interval. The bounds are computed based on 1000 training/validation sessions. Table 4 Lower bound for the measured performance metrics for each experiment, considering a 95% confidence interval. The bounds are computed based on 1000 training/validation sessions. Sensitivity Accuracy Precision Specificity Experiment 1 91% 93% 97% 91% Experiment 2 90% 90% 72% 90% Experiment 3 36% 92% 46% 36% Experiment 4 77% 94% 80% 77% Table 5 Results of the best systems trained for the disturbed static case. Figures Figures Tables Test 1 Test 2 Error percentage 0 0 True positives 24 24 True negatives 24 24 False positives 0 0 False negatives 0 0 Accuracy (%) 100 100 Precision (%) 100 100 Sensitivity (%) 100 100 Specificity (%) 100 100 Table 5 Results of the best systems trained for the disturbed static case. Table 5 Results of the best systems trained for the disturbed static case. Table 6 Reliability results for training and validation of the COP estimates using the proposed system, with reference to the force platform. Test p value for null hypothesis Distance (cm) Training 0.0030 0.9 Validation 0.0042 0.9 Table 6 Reliability results for training and validation of the COP estimates using the proposed system, with reference to the force platform. Test p value for null hypothesis Distance (cm) Training 0.0030 0.9 Validation 0.0042 0.9 Figures Figure 1 Schematic describing the complete balance system. Note that there are two operation stages: the training stage, when we use known data associated to different balance levels to tune the system, and the operation stage, when the system is used under real conditions to properly classify the current balance level. Figure 2 Disposition of the balance sensors over the developed shirt. Figure 2 Figure 2 Disposition of the balance sensors over the developed shirt. Disposition of the balance sensors over the developed shirt. Disposition of the balance sensors over the developed shirt Figure 3 Block diagram describing the whole system for balance and pressure center measurement based on accelerometers. Figure 4 Pressure centers estimated in the training phase by the platform (blue markers) and centroids generated by the proposed system (red crosses). Pressure centers estimated in the training phase by the platform (blue markers) and centroids generated by the proposed system (red crosses).
https://openalex.org/W3119372097
https://www.frontiersin.org/articles/10.3389/fpubh.2020.552198/pdf
English
null
Neighborhood Environment and Objectively Measured Sedentary Behavior Among Older Adults: A Cross-Sectional Study
Frontiers in public health
2,021
cc-by
4,400
Shao-Hsi Chang 1, Ru Rutherford 2, Ming-Chun Hsueh 3*†, Yi-Chien Yu 1, Jong-Hwan Park 4*†, Sendo Wang 5 and Yung Liao 2 1 Department of Physical Education, National Taiwan Normal University, Taipei, Taiwan, 2 Department of Health Promotion and Health Education, National Taiwan Normal University, Taipei, Taiwan, 3 Graduate Institute of Sport Pedagogy, University of Taipei, Taipei, Taiwan, 4 Health Convergence Medicine Laboratory, Biomedical Research Institute, Pusan National University Hospital, Busan, South Korea, 5 Department of Geography, National Taiwan Normal University, Taipei, Taiwan Edited by: Heather Honoré Goltz, University of Houston–Downtown, United States Background: We examined the relationships between objectively assessed neighborhood environment and the patterns of sedentary behavior among older adults. Methods: A total of 126 community-dwelling older adults (aged 65 years or above) were recruited. Data on neighborhood environmental attributes (resident density, street intersection density, sidewalk availability, accessible destinations, and accessible public transportation), accelerometer-assessed total time and patterns of sedentary behavior (number and duration of bouts), and sociodemographic characteristics were collected. Multiple linear regression models were developed. Reviewed by: Angela M. Goins, University of Houston–Downtown, United States Patricia M. Alt, Towson University, United States *Correspondence: Ming-Chun Hsueh boxeo@utaipei.edu.tw Jong-Hwan Park jpark@pnuh.co.kr Reviewed by: Angela M. Goins, University of Houston–Downtown, United States Patricia M. Alt, Towson University, United States *Correspondence: Ming-Chun Hsueh boxeo@utaipei.edu.tw Jong-Hwan Park jpark@pnuh.co.kr Results: After adjustment for potential confounders, greater sidewalk availability was negatively related to the number of sedentary bouts (β = −0.185; 95% CI: −0.362, 0.015; p = 0.034) and sedentary bout duration (β = −0.180; 95% CI: −0.354, −0.011; p = 0.037). †These authors have contributed equally to this work Conclusions: This study revealed that a favorable neighborhood environment characterized by sidewalk availability is negatively associated with sedentary behavior patterns in Taiwanese older adults. These findings are critical to inform environmental policy initiatives to prevent sedentary lifestyle in older adults. Specialty section: This article was submitted to Aging and Public Health, a section of the journal Frontiers in Public Health Keywords: sedentary behavior pattern, environment, accelerometer, urban older adults, walkability Received: 17 April 2020 Accepted: 28 October 2020 Published: 12 January 2021 ORIGINAL RESEARCH published: 12 January 2021 doi: 10.3389/fpubh.2020.552198 Keywords: sedentary behavior pattern, environment, accelerometer, urban older adults, walkability Citation: As is the case with many countries around the world, the population of older adults is increasing rapidly in Taiwan. In 2018, older adults accounted for 14.05% of the total population, and Taiwan will become a super-aged society by 2026 (1). Maintaining a healthy lifestyle is a key determinant of older adults’ health (2, 3). It is well-documented that older adults should engage in sufficient levels of physical activity in order to obtain substantial health benefits (4). In addition to physical activity, emerging evidence has shown that prolonged sedentary time is related to negative health impacts in older populations, such as higher risks of metabolic syndrome, cardiovascular diseases, type 2 diabetes, reduced bone density, and all-cause mortality (5, 6). Given the negative health impacts Chang S-H, Rutherford R, Hsueh M-C, Yu Y-C, Park J-H, Wang S and Liao Y (2021) Neighborhood Environment and Objectively Measured Sedentary Behavior Among Older Adults: A Cross-Sectional Study. Front. Public Health 8:552198. doi: 10.3389/fpubh.2020.552198 January 2021 | Volume 8 | Article 552198 Frontiers in Public Health | www.frontiersin.org Sidewalk Availability and Sedentary Behavior Patterns Chang et al. of sedentary behavior, it is worthwhile to further explore the factors associated with older adults’ sedentary behavior in order to design effective behavioral change programs. of neighborhood environmental attributes with total sedentary time (15, 16) or domain-specific sedentary behavior (17–19) in older adults. These studies have revealed important results for older adults (aged 65 years or above) regarding the relationship between neighborhood environment and sedentary behavior. However, these previous studies have been limited in that they have employed self-reported sedentary measures (17, 18) or total objectively measured sedentary time (15, 16). To enhance the evidence base used for advising policy and urban design initiatives, this study aims to prove the relationships between neighborhood environment and the patterns of objectively assessed sedentary behavior among older persons. g g g Manipulating neighborhood environments is a promising strategy for ensuring active aging and is anticipated to have forward-looking, long-lasting effects on the health-related behaviors of large amounts of older adults (7). For example, built environment characteristics (e.g., sidewalk availability and accessible public transportation) are related to physical activity (8) and active transport (9), pedestrian accidents (10), and several health-related behaviors (11, 12). Citation: In particular, older adults tend to spend more time in their own residential neighborhood than people in other age groups, and thus their health behaviors are more likely influenced by the neighborhood built environment (13). This may highlight the importance of developing effective strategies to reduce older adults’ sedentary behavior through urban design and planning initiatives. In addition, most of the previous evidence was obtained using subjective environmental questionnaires, which capture different constructs of the street environmental characteristics than those measured by objective evaluations of environments (14). For example, street intersection density and sidewalk availability cannot be accurately determined through subjective measures. As such, a better understanding of objectively measured neighborhood environmental factors associated with sedentary behavior in older adults can be informative and of value in designing effective behavioral change programs. In addition, existing studies on this issue have investigated the relationship Participants p A total of 199 older adults (aged ≥65 years) who lived in the community were recruited from April to September 2018 in Taipei, Taiwan. The participants were recruited through local advertisements and announcements. Potential participants were ineligible if they were unable to walk (n = 5) or under 65 years of age (n = 24). In all, 170 participants completed the sociodemographic questionnaire with the assistance of a team of trained research assistants. Furthermore, each of the participants was asked to wear an accelerometer device for seven consecutive days. Of these, 22 participants declined to wear the accelerometer, and 22 participants had incomplete and/or missing data for the self-administered questionnaire. Finally, a total of 126 FIGURE 1 | Flow chart of participant selection. FIGURE 1 | Flow chart of participant selection. January 2021 | Volume 8 | Article 552198 Frontiers in Public Health | www.frontiersin.org 2 Sidewalk Availability and Sedentary Behavior Patterns Chang et al. TABLE 1 | Personal and accelerometer-related attributes of participants. Variables Category Total sample (n = 126), N (%) Age, M (SD) 69.9 (5.0) BMI (kg/m2) 24.2 (3.4) Gender Men 36 (28.6) Women 90 (71.4) Marital status Married 83 (65.9%) Unmarried 43 (34.1%) Living status Living with others 112 (88.9%) Living alone 14 (11.1%) Educational level Tertiary education 27 (21.4%) No tertiary education 99 (78.6%) Employment Yes 4 (3.2%) No 122 (96.8%) Perceived health Good 38 (30.2%) Poor 88 (69.8%) Wear time (min/day), M (SD) 920.5 (85.0) Total sedentary time (min/day), M (SD) 603.8 (75.6) Number of sedentary bouts (times/day), M (SD) 6.1 (2.0) Sedentary bouts duration (min/day), M (SD) 273.3 (103.3) Tertiary education: university or college degree or higher. N, number; M, mean; SD, standard deviation; BMI, body mass index. TABLE 1 | Personal and accelerometer-related attributes of participants. participants completed the questionnaire and also wore an accelerometer for seven consecutive days. Each participant who completed the questionnaire and wore the accelerometer for the full period of time requested received a convenience store voucher worth US$7. A flow diagram of the study recruiting process is presented as Figure 1. Signed informed consent from each of the participants was required before the participant took part in the study. We obtained ethical approval for the study from the Research Ethics Committee of National Taiwan Normal University (REC number: 201711HM003). Neighborhood Environmental Attributes Neighborhood Environmental Attributes Geographic information system software (ArcGIS; ESRI, Redlands, CA) was used to assess neighborhood built environmental attributes, which refer to human-made surroundings, including houses, sidewalks, streets, leisure/utilization destinations, and public transportations. According to previous studies (22, 23), we included five neighborhood built environmental factors: (1) Resident density (number of population per square kilometer); (2) street intersection density (the number of intersections per square kilometer); (3) sidewalk availability (the sum of the areas (square meter) of a paved path of a road, according to the open data of the National Development Council of Taiwan (24); (4) accessible destination (the amount of 30 different types of destination, including convenience stores, supermarkets, hardware shops, fruit stores, dry cleaning stores, coin laundromats, clothing stores, post offices, libraries, book stores, fast food stores, cafés, banks, restaurants, video shops, video rental shops, pharmacies, drug stores, hairdressers, parks, gyms, fitness clubs, sports facilities, kindergartens, elementary schools, junior high schools, high schools, 2-year colleges, 4-year colleges, and universities in the residential village (25, 26); and (5) accessible public transportation [the amount of mass rapid transit (MRT) exits, train stations, high speed rail stations, and bus stops in the residential village]. We used each participant’s geocoded residential neighborhood as a unit for calculating these five environmental measures of built environment, which has been reported as a valid scale (27). Please find the summary of neighborhood environmental attributes in Table 2. Statistical Analyses Data were analyzed from 126 community-residence older adults who provided valid information in regard to the study variables. Chi-square tests were conducted to compare the differences of characteristics between included and excluded participants. Standard multiple linear regression, the enter method, was used to analyze the associations between neighborhood walkability attributes and the patterns of objectively measured sedentary behavior with adjustment for covariates [age, marital status, educational attainment, working status, living status, perceived health, body mass index (BMI), and accelerometer wear time]. All statistical data were analyzed with IBM SPSS, version 23.0 (SPSS Inc., IBM, Chicago, IL, USA). The significance level was set at p < 0.05. Participants Objectively Measured Sedentary Behavior Triaxial ActiGraph (wGT3X-BT, Pensacola, FL, USA) accelerometer model was used to assess sedentary behavior. Participants were advised to carry the accelerometer on their waist, which recorded movement on three axes for ensuing 7 days. Valid data were collected from accelerometers worn by participants for at least 3 days with 1 weekend day. For each valid day, ≥600 min (≥10 h) of wear time is required, excluding sleep time. Following the method used in previous studies (20, 21), total sedentary time (time spent sitting, min/day), number of sedentary bouts ≥30 min (times/day), and duration of sedentary bouts ≥30 min (min/day) were calculated for the analysis. Each minute with an accelerometer count below 100 counts/min was considered sedentary time. The drop time of a sedentary bout was set at 2 min for data analysis. Accelerometer data were analyzed using ActiLife (software, version 6.13.3, Pensacola, FL, USA). Frontiers in Public Health | www.frontiersin.org RESULTS Objectively assessed attributes Total sample β 95% CI p Total sedentary time Resident density −0.005 (−0.167, 0.157) 0.949 Street intersection density −0.032 (−0.193, 0.128) 0.689 Sidewalk availability −0.140 (−0.298, 0.016) 0.078 Accessible destination −0.089 (−0.246, 0.066) 0.257 Accessible public transportation −0.102 (−0.260, 0.054) 0.196 Number of sedentary bouts Resident density 0.028 (−0.151, 0.208) 0.753 Street intersection density −0.008 (−0.186, 0.169) 0.925 Sidewalk availability −0.185 (−0.362, 0.015) 0.034* Accessible destination −0.124 (−0.297, 0.047) 0.154 Accessible public transportation −0.136 (−0.310, 0.036) 0.119 Sedentary bouts duration Resident density 0.052 (−0.124, 0.229) 0.559 Street intersection density 0.023 (−0.152, 0.199) 0.790 Sidewalk availability −0.180 (−0.354, −0.011) 0.037* Accessible destination −0.134 (−0.305, 0.034) 0.116 Accessible public transportation −0.132 (−0.304, 0.037) 0.123 Adjusted for gender, age, marital status, educational level, working status, living status, perceived health, body mass index (BMI), and device wear time. CI, confidence interval; SD, standard deviation. *p < 0.05. TABLE 2 | Summary of neighborhood environmental attributes. Attributes Description M (SD) Resident density The number of population per square kilometer 30594.27 (14698.35) Street intersection density The number of intersections per square kilometer 211.21 (92.66) Sidewalk availability The sum of the areas (square meter) of a paved path of a road 3603.10 (2704.94) Accessible destination The total amount of 30 destination types 14.8 (11.73) Accessible public transportation The amount of MRT exits, train stations, high speed rail stations, and bus stops 23.00 (18.00) M, mean; MRT, mass rapid transit; SD, standard deviation. TABLE 3 | Relationships between neighborhood environmental attributes and objectively measured sedentary behavior patterns in older adults. M, mean; MRT, mass rapid transit; SD, standard deviation. study population was married (65.9%) and lived with others (88.9%), had no University or higher education (78.6%), was not employed (96.8%), perceived health as poor (69.8%), and presented a BMI mean (SD) of 24.2 (3.4). Table 2 shows the mean and standard deviation M (SD) of each neighborhood attributes. The M (SD) of resident density was 30594.27 (14698.35); street intersection density was 211.21 (92.66); sidewalk availability was 3603.10 (2704.94); accessible destination was 14.8 (11.73); and accessible public transportation was 23.00 (18.00). The mechanism underlying the relationship between sidewalk availability and older adults’ prolonged sedentary bouts remains unclear since only a few studies have examined this issue. RESULTS Table 1 shows the characteristics of the sample. Chi-square tests showed proportional differences in age and marital status between included and excluded participants (data not shown). The mean age was 69.9 ± 5.0 years. A total of 126 participants (men, 36; women, 90) were included in this study. Most of the Table 1 shows the characteristics of the sample. Chi-square tests showed proportional differences in age and marital status between included and excluded participants (data not shown). The mean age was 69.9 ± 5.0 years. A total of 126 participants (men, 36; women, 90) were included in this study. Most of the January 2021 | Volume 8 | Article 552198 Frontiers in Public Health | www.frontiersin.org 3 Sidewalk Availability and Sedentary Behavior Patterns Chang et al. TABLE 2 | Summary of neighborhood environmental attributes. Attributes Description M (SD) Resident density The number of population per square kilometer 30594.27 (14698.35) Street intersection density The number of intersections per square kilometer 211.21 (92.66) Sidewalk availability The sum of the areas (square meter) of a paved path of a road 3603.10 (2704.94) Accessible destination The total amount of 30 destination types 14.8 (11.73) Accessible public transportation The amount of MRT exits, train stations, high speed rail stations, and bus stops 23.00 (18.00) M, mean; MRT, mass rapid transit; SD, standard deviation. study population was married (65.9%) and lived with others (88.9%), had no University or higher education (78.6%), was not employed (96.8%), perceived health as poor (69.8%), and presented a BMI mean (SD) of 24.2 (3.4). Table 2 shows the mean and standard deviation M (SD) of each neighborhood attributes. The M (SD) of resident density TABLE 3 | Relationships between neighborhood environmental attributes and objectively measured sedentary behavior patterns in older adults. RESULTS It is possible that neighborhood built environments with favorable sidewalk availability can assist older adults’ mobility among their nearby surroundings (28), such as when taking walks from home for errands or to leisure destinations. Furthermore, it is also possible that neighborhoods with favorable sidewalk availability can enhance pedestrian safety in urban environments (29). Consequently, older adults might spend more time participating in physical activity in their neighborhoods, thereby avoiding prolonged bouts of sedentary behavior and having fewer bouts of sedentary behavior in general. Prospective studies are needed in the future, however, to further investigate the relationship between sidewalk availability and older adults’ prolonged bouts of sedentary behavior. Table 3 shows the results of the regression analysis of the categorical environmental attributes. After adjustment for potential confounders, only one objectively measured environmental attribute (sidewalk availability) was negatively associated with the number of sedentary bouts (β = −0.185; 95% CI: −0.362, 0.015; p = 0.034) and sedentary bout duration (β = −0.180; 95% CI: −0.354, −0.011; p = 0.037). Frontiers in Public Health | www.frontiersin.org REFERENCES 8. Barnett DW, Barnett A, Nathan A, Van Cauwenberg J, Cerin E. Built environmental correlates of older adults’ total physical activity and walking: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. (2017) 14:103. doi: 10.1186/s12966-017-0558-z 1. National Development Council of Taiwan. Available online at: https://pop- proj.ndc.gov.tw/ (accessed January 6, 2020). 1. National Development Council of Taiwan. Available online at: https://pop- proj.ndc.gov.tw/ (accessed January 6, 2020). 9. Smith M, Hosking J, Woodward A, Witten K, MacMillan A, Field A, et al. Systematic literature review of built environment effects on physical activity and active transport - an update and new findings on health equity. Int J Behav Nutr Phys Act. (2017) 14:158. doi: 10.1186/s12966-017-0613-9 2. Kralj C, Daskalopoulou C, Rodríguez-Artalejo F, García-Esquinas E, Cosco TD, Prince M, et al. Healthy Ageing: A Systematic Review of Risk Factors. London: ATHLOS Consortium. (2018). 3. Daskalopoulou C, Stubbs B, Kralj C, Koukounari A, Prince M, Prina, et al. Physical activity and healthy ageing: a systematic review and meta- analysis of longitudinal cohort studies. Ageing Res Rev. (2017) 38:6– 17. doi: 10.1016/j.arr.2017.06.003 10. Congiu T, Sotgiu G, Castiglia P, Azara A, Piana A, Saderi L, et al. Built environment features and pedestrian accidents: an italian retrospective study. Sustainability. (2019) 11:1064. doi: 10.3390/su11041064 11. Rahmanian E, Gasevic D. The association between the built environment and dietary intake -a systematic review. Asia Pac J Clin Nutr. (2014) 23:183–96. doi: 10.6133/apjcn.2014.23.2.08 4. Nelson ME, Rejeski WJ, Blair SN, Duncan PW, Judge JO, King A C, et al. Physical activity and public health in older adults: recommendation from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc. (2007) 39:1435–45. doi: 10.1249/mss.0b013e3180 616aa2 12. Schulz M, Romppel M, Grande G. Built environment and health: a systematic review of studies in Germany. Int J Public Health. (2016) 40:8– 15. doi: 10.1093/pubmed/fdw141 5. Thorp AA, Owen N, Neuhaus M, Dunstan DW. Sedentary behaviors and subsequent health outcomes in adults a systematic review of longitudinal studies, 1996-2011. Am J Prev Med. (2011) 41:207–15. doi: 10.1016/j.amepre.2011.05.004 13. World Health Organization. Active Ageing: A Policy Framework. Geneva: World Health Organization (2002). 14. Shatu F, Yigitcanlar T, Bunker J. Shortest path distance vs. least directional change: empirical testing of space syntax and geographic theories concerning pedestrian route choice behaviour. J Transp Geogr. (2019) 74:37– 52. doi: 10.1016/j.jtrangeo.2018.11.005 6. FUNDING This work was supported by MOST 108-2410-H-003-117 (S-HC), MOST 106-2410-H-003-144-MY2 (M-CH), and MOST 107- 2410-H-003-117-MY2 (YL) through a personal grant from the Ministry of Science and Technology of Taiwan. The Ministry of Science and Technology of Taiwan was not involved in the study design, data collection, analysis, interpretation, and writing of the manuscript. This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2017R1C1B5017549). This research was financially supported by the Ministry of Small and Medium- sized Enterprises (SMEs) and Startups (MSS), Korea, under the Regional Specialized Industry Development Plus Program (R&D, Project number) supervised by the Korea Institute for Advancement of Technology (KIAT). DATA AVAILABILITY STATEMENT The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. ETHICS STATEMENT The studies involving human participants were reviewed and approved by the Research Ethics Committee of the National Taiwan Normal University. The patients/participants provided their written informed consent to participate in this study. DISCUSSION This study is the first to examine the relationships between objectively assessed neighborhood environmental attributes and the patterns of objectively assessed sedentary behaviors among urban community-residing older adults in Taiwan. We found that the availability of favorable neighborhood sidewalks was negatively related to both the number and duration of 30- min sedentary bouts in our sample. Our findings extend previous findings concerning this issue (15–18) and highlight the important role of neighborhood environments in older adults’ sedentary behavior patterns. In terms of informing policies regarding healthy and age-friendly cities in Taiwan, our results could be taken to suggest that increasing sidewalk availability in neighborhoods could be an effective strategy for preventing older adults’ prolonged sedentary behavior. There were several limitations to this study. First, our study was based on a cross-sectional design; accordingly, we were not able to draw a causal relationship between neighborhood environments and older adults’ sedentary behavior. Second, the neighborhood environmental attributes for each participant were obtained using the location of each participant’s residential neighborhood but not the participant’s exact residential address. Most Taiwanese older adults are reluctant to disclose their exact residential address, which was the reason for this limitation (27). Nevertheless, the residential neighborhood has been widely used as a validated geographic unit for January 2021 | Volume 8 | Article 552198 4 Sidewalk Availability and Sedentary Behavior Patterns Chang et al. CONCLUSION This study is the first to find that in urban areas, favorable neighborhood environments are negatively associated with sedentary behavior patterns in a sample of community-dwelling older Taiwanese adults. As such, neighborhood environments with favorable sidewalk availability could be supportive in preventing older adults’ prolonged bouts of sedentary behavior. These findings are critical for informing environmental policy initiatives to prevent sedentary lifestyles among older adults. AUTHOR CONTRIBUTIONS measuring walkability attributes in neighborhoods (30). Third, other environmental attributes that may be related to physical activity and sedentary behavior, such as green spaces and public open spaces, were not examined in the present study. Future studies examining such attributes are warranted. Finally, the sample of our study was limited by the restricted number of participants, who mostly consisted of female participants living in urban settings. Conceptualization was carried out by S-HC, M-CH, SW, and YL. The methodology was provided by RR, M-CH, and Y-CY. The software was obtained by RR, M-CH, and Y-CY. The investigation was conducted by S-HC and MH. Resources were provided by S-HC, M-CH, J-HP, and YL. Data curation was performed by RR, M-CH, and SW. Writing–original draft preparation was done by S-HC, RR, Y-CY, and YL. Writing– review and editing were done by S-HC, RR, M-CH, SW, J-HP, and YL. Supervision was performed by S-HC, M-CH, and J-HP. Funding acquisition was performed by S-HC, M-CH, J-HP, SW, and YL. All authors contributed to the article and approved the submitted version. REFERENCES De Rezende LFM, Lopes MR, Rey-López JP, Matsudo VKR, do Carmo Luiz O. Sedentary behavior and health outcomes: an overview of systematic reviews. PLoS ONE. (2014) 9:e105620. doi: 10.1371/journal.pone. 0105620 15. Todd M, Adams MA, Kurka J, Conway TL, Cain KL, Buman MP, et al. GIS-measured walkability, transit, and recreation environments in relation to older Adults’ physical activity: a latent profile analysis. Prev Med. (2016) 93:57–63. doi: 10.1016/j.ypmed.2016.09.019 7. Sallis JF, Owen N, Fisher EB. Ecological models of health behavior, in Health behavior and health education: theory, research, and practice. San Francisco, CA: Jossey Bass 4th 260 ed. (2008). 465-85. January 2021 | Volume 8 | Article 552198 Frontiers in Public Health | www.frontiersin.org 5 Sidewalk Availability and Sedentary Behavior Patterns Chang et al. 16. Van Holle V, Van Cauwenberg J, De Bourdeaudhuij I, Deforche B, Van de Weghe N, Van Dyck D. Interactions between neighborhood social environment and walkability to explain belgian older adults’ physical activity and sedentary time. Int J Environ Res Publ Health. (2016) 13:569 doi: 10.3390/ijerph13060569 25. Brownson RC, Hoehner CM, Day K, Forsyth A, Sallis JF. Measuring the built environment for physical activity: state of the science. Am J Prev Med. (2009) 36:S99–123 doi: 10.1016/j.amepre.2009.01.005 26. Saelens, BE, Sallis, JF, Frank LD. Environmental correlates of walking and cycling: findings from the transportation, urban design, and planning literatures. Ann Behav Med. (2003) 25:80–91. doi: 10.1207/S15324796ABM2502_03 17. Liao Y, Sugiyama T, Shibata A, Ishii K, Inoue S, Koohsari MJ, et al. Associations of perceived and objectively measured neighborhood environmental attributes with leisure-time sitting for transport. J Phys Act Health. (2016) 13:1372–77. doi: 10.1123/jpah.2016-0073 27. Liao Y, Lin CY, Lai TF, Chen YJ, Kim B, Park JH. Walk score R⃝and its associations with older adults’ health behaviors and outcomes. Int J Environ Res Publ Health. (2019) 16:622. doi: 10.3390/ijerph16040622 Health. (2016) 13:1372–77. doi: 10.1123/jpah.2016-0073 18. Koohsari MJ, Sugiyama T, Shibata A, Ishii K, Hanibuchi T, Liao Y, et al. Walk Score R⃝and Japanese adults’ physically-active and sedentary behaviors. Cities. (2018) 74:151–55. doi: 10.1016/j.cities.2017.11.016 28. Wendel-Vos W, Droomers M, Kremers S, Brug J, Van Lenthe F. Potential environmental determinants of physical activity in adults: a systematic review. Obes Rev. (2007) 8:425–40. doi: 10.1111/j.1467-789X.2007.00370.x 19. Hsueh MC, Lin CY, Huang PH, Park JH, Liao Y. Cross-Sectional Associations of Environmental Perception with Leisure-Time Physical Activity and Screen Time among Older Adults. J Clin Med. (2018) 7:56. doi: 10.3390/jcm70 30056 29. Frontiers in Public Health | www.frontiersin.org January 2021 | Volume 8 | Article 552198 REFERENCES Shatu F, Yigitcanlar T. Development and validity of a virtual street walkability audit tool for pedestrian route choice analysis—SWATCH. J Transp Geogr. (2018) 70:148–60. doi: 10.1016/j.jtrangeo.2018.06.004 20. Liao Y, Hsu HH, Shibata A, Ishii K, Koohsari MJ, Oka K. Associations of total amount and patterns of objectively measured sedentary behavior with performance-based physical function. Prev Med Rep. (2018) 12:128– 34. doi: 10.1016/j.pmedr.2018.09.007 30. Leslie E, Saelens B, Frank L, Owen N, Bauman A, Coffee N, et al. Residents’ perceptions of walkability attributes in objectively different neighbourhoods: a pilot study. Health Place. (2005) 11:227–36. doi: 10.1016/j.healthplace.2004.05.005 21. Tremblay MS, Aubert S, Barnes JD, Saunders TJ, Carson V, Latimer- Cheung AE, et al. Sedentary behavior research network (sbrn) – terminology consensus project process and outcome. Int J Behav Nutr Phys Act. (2017) 14:75. doi: 10.1186/s12966-017-0525-8 Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. 22. Liao Y, Shibata A, Ishii K, Koohsari MJ, Inoue S, Oka K. Can neighborhood design support walking? Cross-sectional and prospective findings from Japan. J Transp Health. (2018) 11:73–9. doi: 10.1016/j.jth.2018. 10.008 Copyright © 2021 Chang, Rutherford, Hsueh, Yu, Park, Wang and Liao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. 23. Saelens BE, Handy SL. Built environment correlates of walking: a review. Med Sci Sports Exerc. (2008) 40:S550. doi: 10.1249/MSS.0b013e31817c67a4 24. National Development Council of Taiwan. Available online at: https://data. gov.tw/dataset/58791 (accessed January 6, 2020). January 2021 | Volume 8 | Article 552198 Frontiers in Public Health | www.frontiersin.org 6
https://openalex.org/W4362425591
https://figshare.com/articles/journal_contribution/Supplementary_Data_from_Associations_of_Matrix_Metalloproteinase-9_Protein_Polymorphisms_with_Lymph_Node_Metastasis_but_not_Invasion_of_Gastric_Cancer/22439793/1/files/39890628.pdf
English
null
Supplementary Data from Associations of Matrix Metalloproteinase-9 Protein Polymorphisms with Lymph Node Metastasis but not Invasion of Gastric Cancer
null
2,023
cc-by
2,009
Supplemental Table 1. Associations of MMP-9 polymorphisms with clinicopathological features of gastric cancer Supplemental Table 1. Associations of MMP-9 polymorphisms with clinicopathological features of gastric cancer Polymorphism MMP-9 R279Q MMP-9 P574R Genotype QQ+RQ n (%) RR n (%) p RR+PR n (%) PP n (%) p Gender 0.73* 0.39* Female (n=26) 13 (37) 13 (33) 13 13 Male (n=48) 22 (63) 26 (67) 19 29 Total (n=74) 35 (100) 39 (100) 32 (100) 42 (100) Age§ 0.51†, 0.36∮ 0.75†, 0.80∮ 1 (n=3) 3 (9) 0 (0) 3 (9) 0 (0) 2 (n=6) 0 (0) 6 (15) 0 (0) 6 (14) 3 (n=7) 5 (14) 2 (5) 3 (9) 4 (10) 4 (n=22) 12 (34) 10 (26) 11 (34) 11 (26) 5 (n=26) 8 (23) 18 (46) 8 (25) 18 (43) 6 (n=10) 7 (20) 3 (8) 7 (22) 3 (7) Total (n=74) 35 (100) 39 (100) 32 (100) 42 (100) Location 0.34† 0.30† Cardia (n=16) 9 (26) 7 (18) 9 (28) 7 (17) Corpus (n=6) 3 (9) 3 (8) 2 (6) 4 (10) Antrum (n=45) 21 (60) 24 (62) 19 (59) 26 (62) Pylorus or others (n=7) 2 (6) 5 (13) 2 (6) 5 (12) Total (n=74) 35 (100) 39 (100) 32 (100) 42 (100) Size** 0.83† 0.98† 1cM (n=23) 12 (34) 11 (28) 11 (34) 12 (29) 2cM (n=24) 15 (43) 19 (49) 13 (41) 21 (50) 3cM (n=17) 8 (23) 9 (23) 8 (25) 9 (21) Total (n=74) 35 (100) 39 (100) 32 (100) 42 (100) Average of the size (cM) 1.89 1.95 0.72‡ 1.91 0.90‡ Lauren's classification†† 0.74† 0.76† Intestinal (n=26) 11 (31) 15 (38) 12 (38) 14 (33) Mixed (n=11) 6 (17) 5 (13) 4 (13) 7 (17) Diffuse (n=37) 18 (51) 19 (49) 16 (50) 21 (50) Total (n=74) 35 (100) 39 (100) 32 (100) 42 (100) Invasionξ 0.25* 0.38* Within serosa (n=39) 16 (46) 23 (59) 15 (47) 24 (57) Serosa and beyond (n=45) 19 (54) 16 (41) 17 (53) 18 (43) Total (n=74) 35 (100) 39 (100) OR=0.59 32 (100) 42 (100) OR=0.66 TNMξξ 0.12† 0.20† 1A/1B (n=28) 17 (49) 11 (28) 16 (50) 12 (29) II (n=19) 7 (20) 12 (31) 5 (16) 14 (33) IIIA/IIIB (n=25) 11 (31) 14 (36) 11 (34) 14 (33) IV (n=2) 0 (0) 2 (5) 0 (0) 2 (5) Total (n=74) 35 (100) 39 (100) 32 (100) 42 (100) Lymph node metastasis 0.012* 0.025* No metastasis (n=29) 19 (54) 10 (26) OR=3.4 17 (53) 12 (29) OR=2.8 Metastasis (n=45) 16 (46) 29 (74) 95% CI 15 (47) 30 (71) 95% CI Total (n=74) 35 (100) 39 (100) 1.29-9.17 32 (100) 42 (100) 1.08-7.43 1-year postoperative mortality Survived (n=43) 25 (89) 18 (69) 0.095*' 23 (88) 20 (71) 0.179*' Deceased (n=11) 3 (11) 8 (31) 3 (12) 8 (29) Total (n=54) 28 (100) 26 (100) 26 9100) 28 (100) Haplotype of polymorphisms MMP-9 279R-574P Genotype Non-double homozygotes n (%) Double homozygotes n (%) p Lymph node metastasis 0.008*' No metastasis (n=29) 20 (56) 9 (24) OR=4.03 Metastasis (n=45) 16 (44) 29 (76) 95% CI Total (n=74) 36 (100) 38 (100) 1.49-10.90 1-year postoperative mortality 0.09*' Survived (n=29) 26 (90) 17 (68) OR=4.08 Deceased (n=45) 3 (10) 8 (32) 95% CI Total (n=54) 28 (100) 26 (100) 0.95-17.58 §Numbering system for the age, 1, 20-29;2,30-39;3,40-49;4,50-59;5,60-69;6, 70-79. §§Differentiation grades were grouped into two categories, '1' included highly, moderately and poorly differentiatied adenocarcinoma; Footnotes for the other symbols are the same as in Supplemental Table 1. 2' included undifferentiated carcinoma and mucinous adenocarcinoma. all non-RR-PP 0.011 13.81 1.84-103.56 87% Different multivariate analyses are denoted by different alphabet letter Associations with lymph node metastasis Analysis Factor Dichotomized comparison P Adjusted OR 95% CI correct prediction A 279RR RR vs. RQ or QQ 0.0032 5.74 1.80-18.34 73% B 574PP PP vs. RP or RR 0.0119 4.17 1.37-12.69 71% C Gender Male vs. female 0.2054 1.95 0.69-5.51 69% C AGE >60 vs. <=60 0.7688 0.86 0.31-2.36 69% C 279RR-574PP (adjusted for gender and age) RR-PP vs. all non-RR-PP 0.0071 4.01 1.46-11.03 69% D Lauren's classification Intestinal/mixed vs. diffuse 0.37 1.60 0.57-4.51 65% D 279RR-574PP (additionally adjusted for Lauren's classification) RR-PP vs. all non-RR-PP 0.0071 4.05 1.46-11.23 65% E Location Cardia vs. non-cardia 0.0032 15.78 2.51-99.03 73% E 279RR-574PP (additionally adjusted for location of the tumor) RR-PP vs. all non-RR-PP 0.0021 6.09 1.92-19.29 73% F Size of the tumor 1 or 2 cM vs. 3 cM 0.0064 10.85 1.96-60.22 73% F 279RR-574PP (additionally adjusted for size of the tumor) RR-PP vs. all non-RR-PP 0.0030 5.41 1.78-16.46 73% G Depth of invasion Within vs. serosa or over 0.0013 9.02 2.35-34.62 G 279RR-574PP (additionally adjusted for depth of the invasion) RR-PP vs. all non-RR-PP 0.0016 7.40 2.13-25.74 74% Associations with lymph node metastasis Associations with 1-year postoperative survival Associations with 1-year postoperative survival Analysis Factor Dichotomized comparison P Adjusted OR 95% CI correct prediction A 279RR RR vs. RQ or QQ 0.056 4.92 0.96-25.19 80% B 574PP PP vs. RP or RR 0.224 2.65 0.55-12.73 81% C Gender Male vs. female 0.037 0.16 0.028-0.89 81% C AGE >60 vs. <=60 0.324 2.20 0.46-10.53 81% C 279RR-574PP (adjusted for gender and age) RR-PP vs. all non-RR-PP 0.035 5.96 1.13-31.34 81% D Lauren's classification Intestinal/mixed vs. diffuse 0.088 4.39 0.80-24.03 89% D 279RR-574PP (additionally adjusted for Lauren's classification) RR-PP vs. all non-RR-PP 0.026 7.84 1.28-48.02 89% E Location Cardia vs. non-cardia 0.188 3.19 0.57-17.90 81% E 279RR-574PP (additionally adjusted for location of the tumor) RR-PP vs. all non-RR-PP 0.031 6.50 1.18-35.74 81% F Size of the tumor 1 or 2 cM vs. 3 cM 0.049 5.56 1.00-30.76 81% F 279RR-574PP (additionally adjusted for size of the tumor) RR-PP vs. all non-RR-PP 0.025 8.18 1.30-51.37 81% G Depth of invasion within vs. serosa or over 0.028 7.73 1.25-47.91 87% G 279RR-574PP (additionally adjusted for depth of the invasion) RR-PP vs. **Size was taken by measuring the maximum diameter of the tumor in single digit number of centimeters. ††Gastric cancer was classified histologically according to the criteria of Lauren (Lauren 1965); ∮p was calculated by chi-test with parameter dichotomization (=<60 and >60). tal Table 2. Associations of clinicopathological features with lymph node metastasis of gastric cancer Supplemental Table 2. Associations of clinicopathological features with lymph node met Lymph node metastasis All cases n (%) Cases with no metastasis n (%) Cases with metastasis n (%) p Gender 0.16* Female 26 (35) 13 (45) 13 (29) Male 48 (65) 16 (55) 32 (71) Total 74 (100) 29 (100) 45 (100) Age§ 0.79† 1 3 (4) 1 (3) 2 (4) 2 6 (8) 2 (7) 4 (9) 3 7 (9) 3 (10) 4 (9) 4 22 (30) 9 (31) 13 (29) 5 26 (35) 9 (31) 17 (38) 6 10 (14) 5 (17) 5 (11) Total 74 (100) 29 (100) 45 (100) Location 0.022* Cardia 16 (22) 2 (7) 14 (31) Corpus 6 (8) 3 (10) 3 (7) Antrum 45 (61) 23 (79) 22 (49) Pylorus and others 7 (9) 1 (3) 6 (13) Total 0 (0) (0) (0) Size** 0 (0) (0) (0) 0.008† 1cM 23 (31) 13 (45) 10 (22) 2cM 34 (46) 14 (48) 20 (44) 3cM 17 (23) 2 (7) 15 (33) Total 74 (100) 29 (100) 45 (100) Average(cm) 1.92 1.62 2.11 0.004‡ Invasion Within serosa 39 (53) 21 (72) 18 (40) 0.006* Serosa and beyond 35 (47) 8 (28) 27 (60) Total 74 (100) 29 (100) 45 (100) Differentiation§§ 1 47 (64) 21 (72) 26 (58) 0.20* 2 27 (36) 8 (28) 19 (42) Total 74 (100) 29 (100) 45 (100) Lauren's classification†† Intestinal/mixed 37 (35) 16 (55) 21 (43) 0.47*, 0.21† Diffuse 37 (50) 13 (45) 24 (53) Total 74 (100) 29 (100) 45 (100) TNMξ 1A/1B 28 (38) 26 (90) 2 (4) 1.36E-07† II 19 (26) 2 (7) 17 (38) IIIA/IIIB 25 (34) 1 (3) 24 (53) IV 2 (3) 0 (0) 2 (4) Total 29 (100) 45 (100) 1-year postoperative mortality Survived 43 (80) 22 (100) 21 (66) 0.002*' Deceased 11(20) 0 (0) 11 (34) 54 22 (100) 32 100) Supplemental Table 3. Multivariate analyses of factors associated with the progression of gastric cancer using logistic regression Associations with lymph node metastasis Analysis Factor Dichotomized comparison P Adjusted OR 95% CI correct prediction A 279RR RR vs. RQ or QQ 0.0032 5.74 1.80-18.34 73% B 574PP PP vs. RP or RR 0.0119 4.17 1.37-12.69 71% C Gender Male vs. female 0.2054 1.95 0.69-5.51 69% C AGE >60 vs. <=60 0.7688 0.86 0.31-2.36 69% C 279RR-574PP (adjusted for gender and age) RR-PP vs. all non-RR-PP 0.0071 4.01 1.46-11.03 69% D Lauren's classification Intestinal/mixed vs. diffuse 0.37 1.60 0.57-4.51 65% D 279RR-574PP (additionally adjusted for Lauren's classification) RR-PP vs. all non-RR-PP 0.0071 4.05 1.46-11.23 65% E Location Cardia vs. non-cardia 0.0032 15.78 2.51-99.03 73% E 279RR-574PP (additionally adjusted for location of the tumor) RR-PP vs. all non-RR-PP 0.0021 6.09 1.92-19.29 73% F Size of the tumor 1 or 2 cM vs. 3 cM 0.0064 10.85 1.96-60.22 73% F 279RR-574PP (additionally adjusted for size of the tumor) RR-PP vs. all non-RR-PP 0.0030 5.41 1.78-16.46 73% G Depth of invasion Within vs. serosa or over 0.0013 9.02 2.35-34.62 G 279RR-574PP (additionally adjusted for depth of the invasion) RR-PP vs. all non-RR-PP 0.0016 7.40 2.13-25.74 74% Associations with 1-year postoperative survival Analysis Factor Dichotomized comparison P Adjusted OR 95% CI correct prediction A 279RR RR vs. RQ or QQ 0.056 4.92 0.96-25.19 80% B 574PP PP vs. RP or RR 0.224 2.65 0.55-12.73 81% C Gender Male vs. female 0.037 0.16 0.028-0.89 81% C AGE >60 vs. <=60 0.324 2.20 0.46-10.53 81% C 279RR-574PP (adjusted for gender and age) RR-PP vs. all non-RR-PP 0.035 5.96 1.13-31.34 81% D Lauren's classification Intestinal/mixed vs. diffuse 0.088 4.39 0.80-24.03 89% D 279RR-574PP (additionally adjusted for Lauren's classification) RR-PP vs. all non-RR-PP 0.026 7.84 1.28-48.02 89% E Location Cardia vs. non-cardia 0.188 3.19 0.57-17.90 81% E 279RR-574PP (additionally adjusted for location of the tumor) RR-PP vs. all non-RR-PP 0.031 6.50 1.18-35.74 81% F Size of the tumor 1 or 2 cM vs. 3 cM 0.049 5.56 1.00-30.76 81% F 279RR-574PP (additionally adjusted for size of the tumor) RR-PP vs. all non-RR-PP 0.025 8.18 1.30-51.37 81% G Depth of invasion within vs. serosa or over 0.028 7.73 1.25-47.91 87% G 279RR-574PP (additionally adjusted for depth of the invasion) RR-PP vs. A, the factors included for logistic regression: gender, age, location and genotype of allele R279Q. Different multivariate analyses are denoted by different alphabet letter. all non-RR-PP 0.011 13.81 1.84-103.56 87% Diff l i i l d d b diff l h b l B, the factors included for logistic regression: gender, age, location and genotype of allele P574R. C, the factors included for logistic regression: gender, age and genotype of haplotype 279R-574P. D, the factors included for logistic regression: gender, age, Lauren's classification and genotype of haplotype 279R-574P. E, the factors included for logistic regression: gender, age, location of the tumor and genotype of haplotype 279R-574P. F, the factors included for logistic regression: gender, age, size of the tumor and genotype of haplotype 279R-574P. G, the factors included for logistic regression: gender, age, depth of the invasion and genotype of haplotype 279R-574P. Supplemental Table 4. Stratified analyses of the associations of MMP-9 SNPs with lymph node metastasis Stratification factor (stratum): invasion Number of cases Non- homozygous 279R-574P Homozygous 279R-574P Total p within stratum* OR p between strata† No metastasis 13 8 21 0.022 5.69 0.54 within serosa Metastasis 4 14 18 Total 17 22 39 No metastasis 7 1 8 0.047 8.75 onto or over serosa Metastasis 12 15 27 Total 19 16 35 Stratification factor (stratum):Lauren's classification Number of cases Non- homozygous 279R-574P Homozygous 279R-574P Total p within stratum* OR p between strata† No metastasis 9 7 16 0.51 1.71 0.044 Intestinal/mixed Metastasis 9 12 21 Total 18 19 37 No metastasis 11 2 13 0.002 13.36 Diffuse Metastasis 7 17 24 Total 18 19 37 *By Fisher's exact test †By Mantel-Haenszel's test and Woolf’s Chi-test Supplemental Table 4. Stratified analyses of the associations of MMP-9 SNPs with lymph node metastasis
https://openalex.org/W2883959232
http://www.scielo.br/pdf/cbab/v18n3/1984-7033-cbab-18-03-325.pdf
English
null
RB036066 - a sugarcane cultivar with high adaptability and yield stability to Brazilian South-Central region
Crop Breeding and Applied Biotechnology
2,018
cc-by
2,956
RB036066 – a sugarcane cultivar with high adaptability and yield stability to Brazilian South-Central region Crop Breeding and Applied Biotechnology 18: 325-329, 2018 Brazilian Society of Plant Breeding. Printed in Brazil http://dx.doi.org/10.1590/1984- 70332018v18n3c48 Crop Breeding and Applied Biotechnology 18: 325-329, 2018 Brazilian Society of Plant Breeding. Printed in Brazil http://dx.doi.org/10.1590/1984- 70332018v18n3c48 Crop Breeding and Applied Biotechnology RB036066 – a sugarcane cultivar with high adaptability and yield stability to Brazilian South-Central region Edelclaiton Daros1, Ricardo Augusto de Oliveira1, José Luis Camargo Zambon1, João Carlos Bespalhok Filho1, Bruno Portela Brasileiro1*, Oswaldo Teruyo Ido1, Lucimeris Ruaro1 and Heroldo Weber1 Abstract: The sugarcane cultivar RB036066 is medium-maturing and has a long period of industrial suitability; in the South-Central region, harvest is recom­ mended between June and September, and it is indicated for planting on medium to highly fertile soils. The cultivar is widely adaptable and has high sugar yield and stability of agricultural production. Key words: Saccharum spp., selection and crop breeding. *Corresponding author: E-mail: brunobiogene@hotmail.com CULTIVAR RELEASE Crop Breeding and Applied Biotechnology - 18: 325-329, 2018 *Corresponding author: E-mail: brunobiogene@hotmail.com Received: 03 July 2017 Accepted: 18 September 2017 1 Universidade Federal do Paraná (UFPR), De­ partamento de Fitotecnia e Fitossanitarismo, 80.035- 050, Curitiba, PR, Brazil PEDIGREE AND BREEDING METHODS In 2003, caryopses were obtained from the cross of the female parent SP70-1143 with the male parent SP77-5181 (Figure 1), at the Flowering and Crossing Station of Serra do Ouro (lat 9º 13’ S, long 35º 50’ W and alt 450 m asl) in Murici, Alagoas, of the Federal University of Alagoas. In the same year, the caryopses were germinated in a greenhouse of the Experimental Station Paranavaí of the Federal University of Paraná, in Paranavaí, Paraná, (lat 23º 05’ S, long 52º 27’ W and alt 503 m asl). The first test phase (T1) was initiated in November 2003, with the planting of a total of approximately 200 thousand seedlings, descendants from hundreds of parents in two production environments (municipalities of Colorado and São Tomé). Individual selection was applied in July 2005, in the ratoon cane stage. In 2005, the first clonal multiplication (phase T2) was carried out, with planting in the same municipalities. Each genotype of phase T2 was planted in two 5 m long furrows, spaced 1.5 m apart, in an experiment arranged in an augmented block design. The clone then named “PRP036066” was selected in 2008 due to its excellent performance throughout three growing seasons. In the next stage (phase T3) in 2010, evaluations and clonal selection were carried out based on data of two growing seasons, at eight locations in the state of Paraná [Mandaguaçú (lat 23º 21’ S, long 52º 05’ W and alt 580 m asl), Bandeirantes (lat 23º 06’ S, long 50º 22’ W and alt 492 m asl), Paranavaí (lat 23º 05’ S, long 52º 27’ W and alt 503 m asl), Colorado (lat 22° 50’ S, long 51° 54’ W and alt 400 m asl), Goioerê (lat 24° 10’ S, long 53° 01’ W and alt 550 m asl), Perobal (lat 23° 54’ S, long 53° 24’ W and alt 410 m asl), Astorga (lat 23° 11’ S, long 51° 09’ W and alt 634 m asl), and São Pedro do Ivaí (lat 23° 52’ S, long 51°41’ W and alt 400 m asl)]. In 2010, the clonal multiplication phase (MPh) was planted and in the following year, the clone now called RB036066 was included in the final test phase of PMGCA, called experimental phase (EPh), conducted at 10 locations in the state of Paraná. E Daros et al. harvesting, with low levels of mineral impurities, suitable for industrial processing. harvesting, with low levels of mineral impurities, suitable for industrial processing. In addition to the above advantages, cultivar RB036066 can maintain high yields in medium-fertile soils, due to its excellent tillering capacity as well as medium-diameter stalks with long internodes, tall plant height and average weight. INTRODUCTION The breeding program of sugarcane (Saccharum spp.) of the Federal University of Paraná [PMGCA/UFPR (www.pmgca.ufpr.br)] is part of the Inter-University Network for the Development of Sugarcane Industry (RIDESA), a network consisting of 10 Federal Universities that have been working successfully on the development of sugarcane cultivars that have different maturation cycles, adequate yields under the different management conditions of the crop, and are suited for the more than 9 million hectares of sugarcane cultivation in Brazil (Barbosa et al. 2015, Carneiro et al. 2015, Iaia et al. 2015, Carneiro et al. 2016, Daros et al. 2017). In the South- central region of Brazil, the cultivation of medium and late-maturing cultivars with high yields managed mechanically is a great challenge, due to the damage caused by the harvest equipment. Cultivar RB036066 should be planted in medium to highly fertile soils; it has a high phenotypic stability for tons of sucrose per hectare (TSH) and is extremely responsive to environmental improvements, responding with significant yield increases. However, the main characteristics of this new cultivar are a rapid initial growth and high tillering capacity, contributing to an excellent plant canopy closure in cane fields. The high potential sugar yield, coupled with wide adaptability and high yield stability, ensure high crop yields throughout the growing seasons. The recommended time for harvesting RB036066 in the South-central region of Brazil is in the middle of the growing season, between June and September, but due to the long period of industrial suitability, harvest can be extended until the end of the growing season, between October and November. It has upright growth and tall plant height, resulting in excellent suitability for mechanical 1 Universidade Federal do Paraná (UFPR), De­ partamento de Fitotecnia e Fitossanitarismo, 80.035- 050, Curitiba, PR, Brazil Crop Breeding and Applied Biotechnology - 18: 325-329, 2018 325 E Daros et al. PERFORMANCE The results of the experiments carried out in the mills and distilleries of the state of Paraná confirmed the superior performance of cultivar RB036066 over the standard cultivar RB867515, mainly in medium to highly fertile soils, as shown by the results obtained by the method of stability and adaptability, proposed by Eberhart and Russell (1966) (Figure 2). The yield stability in the different test environments was high, indicating a better performance for yield traits in medium to highly fertile soils. Figure 2. Phenotypic performance of RB036066 and RB867515 in 10 environments in plant cane, ratoon cane and second ratoon crops, in Paraná, Brazil. The phenotypic adaptability of cultivar RB036066 was also high, indicating an excellent yield response when grown in high-fertility environments (Figure 2). When comparing cv. RB036066 with cv. RB867515, there was an increase in TCH of 14.42% in the mean of three growing seasons (Table 1). This characteristic of high agricultural yield (108.63 Mg ha-1) associated with the sucrose content induced an increase in sugar yield of more than 25%. The maturation curve of cultivar RB036066 was evaluated in several environments in the state of Paraná, according to the methodology described by Fernandes (2003). Based on the sucrose percentage in cane juice (SPC%), the cultivar was classified as medium-maturing, indicating the cultivar for harvesting from June onwards, in the South-central region of Brazil (Figure 3). Figure 2. Phenotypic performance of RB036066 and RB867515 in 10 environments in plant cane, ratoon cane and second ratoon crops, in Paraná, Brazil. In a comparison of the maturation curve of cv RB036066 with that of cultivars usually harvested in the middle and Table 1. PEDIGREE AND BREEDING METHODS In the EPh, yield traits such as ton of sugarcane per hectare and sucrose content, as well as their adaptability and yield stability were evaluated in the different soil and climate conditions of the North and Northwest regions of the State of Paraná (Figure 2). The EPh phase lasted three growing seasons. During this period, the reaction to the main diseases of the South-central sugarcane region was also evaluated. Between 2011 and 2012, experiments were conducted to evaluate the maturation period of RB036066 at nine locations in the state of Paraná. Prior to the release of RB036066 for planting throughout Brazil, the data of 54 growing seasons were analyzed, from the first cut (10 growing seasons) to the third cut (6 growing seasons). The results confirmed the main qualities of the cultivar, in particular the high sucrose yield, associated with high stability and wide adaptability to medium to high-yield environments. 326 Crop Breeding and Applied Biotechnology - 18: 325-329, 2018 Figure 1. Pedigree of cultivar RB036066. Figure 1. Pedigree of cultivar RB036066. Figure 1. Pedigree of cultivar RB036066. Crop Breeding and Applied Biotechnology - 18: 325-329, 2018 326 RB036066 – a sugarcane cultivar with high adaptability and yield stability to Brazilian South-Central region Since 2011, when the results were corroborated in several environments in the State of Paraná, there was an interest of the sugarcane mills and ethanol distilleries to install multiplication areas of RB036066 to evaluate the cultivar performance under the different management conditions of the producing units, representing different commercial farming systems. In this period, the cultivar stood out due to its excellent performance in the mechanically harvested areas, mainly because of its upright growth habit and tall plant height, with no lodging, even in sugarcane plantations in the final stage of the crop cycle. This information further stimulated its multiplication since 2015, especially after the national release of the RB cultivar group (Daros et al. 2015). In June 2016, the Federal University of Paraná applied for the protection of cv. RB036066 by the National Service of Cultivar Protection (SNPC) and registration by the National Registry of Cultivars (RNC) of the Ministry of Agriculture, Livestock and Supply (MAPA). The definitive protection occurred on March 2017 (protocol no. 21806.000218/2016-34). = tons of sucrose per hectare and SPC = sucrose percentage in cane juice (apparent percentage of sucrose); * Relative yield of the 5 as reference. € TCH = tons of cane per hectare, TPH = tons of sucrose per hectare and SPC = sucrose percentage in cane juice (apparent percent variable, considering cultivar RB867515 as reference. PERFORMANCE Comparison of RB036066 with RB867515, an important early-maturing cultivar, evaluated in the state of Paraná, from 2011 to 2014, based on the means of growing seasons Crop Cultivars TCH€ (%)* TPH (%)* SPC (%) (%)* First-ratoon RB867515 105.34 100 12.31 100 11.69 100 RB036066 118.6 112.588 13.38 108.692 11.28 96.4927 Second-ratoon RB867515 100.26 100 12.72 100 12.69 100 RB036066 111.1 110.812 15.85 124.607 14.27 112.451 Third-ratoon RB867515 79.23 100 9.69 100 12.23 100 RB036066 96.2 121.419 14.43 148.916 15 122.649 Mean RB867515 94.94 100 11.58 100 12.2 100 RB036066 108.63 114.42 14.55 125.648 13.52 110.82 € TCH = tons of cane per hectare, TPH = tons of sucrose per hectare and SPC = sucrose percentage in cane juice (apparent percentage of sucrose); * Relative yield of the variable, considering cultivar RB867515 as reference. 066 with RB867515, an important early-maturing cultivar, evaluated in the state of Paraná, from 2011 of growing seasons Table 1. Comparison of RB036066 with RB867515, an important early-maturing cultivar, evaluated in t to 2014, based on the means of growing seasons Crop Breeding and Applied Biotechnology - 18: 325-329, 2018 327 E Daros et al. at the end of the growing season, the sucrose level of cv RB036066 was higher than that of cv RB867515 between June and November in the restrictive soils, i.e., with low to medium fertility, and similar to that of cultivar RB855536 in the same period in favorable soils (Bandeirantes and São Pedro do Ivaí), i.e., with high fertility. at the end of the growing season, the sucrose level of cv RB036066 was higher than that of cv RB867515 between June and November in the restrictive soils, i.e., with low to medium fertility, and similar to that of cultivar RB855536 in the same period in favorable soils (Bandeirantes and São Pedro do Ivaí), i.e., with high fertility. It is noteworthy that sucrose (SPC%) concentrations were higher from June onwards, and remained stable until November, as well as the mean maturation control cultivar in favorable environments. Therefore, this new cultivar is an excellent alternative for planting when high stalk and sugar yields during the harvest from June to November in the South-central region are desired. PERFORMANCE In years with high flowering induction in sugarcane plantations, cultivar RB036066 showed sporadic flowering, but evaluations of density and stalk sucrose content, losses were lower than for other cultivars on the market usually used as control in the final test phase (EPh). On the other hand, the adequate management of cultivar RB036066 enabled harvesting between June and September, with high agricultural yields, extending the period of industrial suitability of this new sugarcane cultivar even further. Cultivar RB036066 has good plant health, is resistant to brown rust (Puccinia melanocephala Syd. and P. Syd.) and tolerant to orange rust of sugarcane (Puccinia kuehnii EJ Butler), and to sugarcane smut (Sporisorium scitamineum (Syd.) M. Piepenbr, M. Stoll & Oberw.). Cultivar RB36066 was evaluated for the presence of the Bru1 gene, which confers resistance to brown rust, caused by Puccinia melanocephala. Two markers (R12H16 and 9O20-F4-RsaI) that are strongly associated with Bru1 gene were used. Amplification conditions and restriction using the RsaI enzyme were carried out according to Costet et al. (2012). The presence of the Bru1 gene was confirmed in RB36066 for both markers evaluated. OTHER TRAITS According to the official descriptors for sugarcane (SNPC/MAPA), cultivar RB036066 has an upright growth habit and the stalks have curved internodes, an oval section, arranged in a slight zigzag pattern, medium to long length, and mean diameter, with yellow-purple and purple-green color when exposed to sun, without wax or cracks. The sugarcane heart is purple green, with little wax, medium length and oval cross section. The quantity of slightly dark green leaves is regular, the leaf architecture arched, with ascending ligule and medium, lanceolate auricles, distributed unilaterally. Figure 3. Maturation curves of RB036066 and two other important sugarcane cultivars planted at four different locations in the South-central region of Brazil. Figure 3. Maturation curves of RB036066 and two other important sugarcane cultivars planted at four different locations in the South-central region of Brazil. Crop Breeding and Applied Biotechnology - 18: 325-329, 2018 328 RB036066 – a sugarcane cultivar with high adaptability and yield stability to Brazilian South-Central region The growth ring is yellow-green, medium wide and medium salient. The root area is medium wide, medium salient, with bud insertion close to the leaf scar. Clear presence of wax in the root node region. The bud is oval, slightly prominent, medium-sized, occasionally exceeding the growth ring, with narrow flower cushion, germ pore in apical position surrounded by hairs. The growth ring is yellow-green, medium wide and medium salient. The root area is medium wide, medium salient, with bud insertion close to the leaf scar. Clear presence of wax in the root node region. The bud is oval, slightly prominent, medium-sized, occasionally exceeding the growth ring, with narrow flower cushion, germ pore in apical position surrounded by hairs. MAINTENANCE OF SEEDLINGS AND DISTRIBUTION The seedlings of cultivar RB036066 are maintained and distributed by the Sugarcane Breeding Program of the Department of Plant Science and Plant Health of the Federal University of Paraná, 80.035-050, Curitiba, PR, Brazil. reveals a narrow genetic basis for brown rust resistance in modern sugarcane cultivars. Theoretical and Applied Genetics 125: 825-836. reveals a narrow genetic basis for brown rust resistance in modern sugarcane cultivars. Theoretical and Applied Genetics 125: 825-836. REFERENCES Barbosa GVS, Oliveira RA, Cruz MM, Santos JM, Silva PP, Viveiros AJA, Sousa AJR, Ribeiro CAG, Soares L, Teodoro I, Sampaio Filho F, Diniz CA and Torres VLD (2015) RB99395: Sugarcane cultivar with high sucrose content. Crop Breeding and Applied Biotechnology 15: 187-190. Barbosa GVS, Oliveira RA, Cruz MM, Santos JM, Silva PP, Viveiros AJA, Sousa AJR, Ribeiro CAG, Soares L, Teodoro I, Sampaio Filho F, Diniz CA and Torres VLD (2015) RB99395: Sugarcane cultivar with high sucrose content. Crop Breeding and Applied Biotechnology 15: 187-190. Daros E, Oliveira RA and Barbosa GVS (eds) (2015) 45 anos de variedades RB de cana-de- açúcar: 25 anos de Ridesa. Graciosa, Curitiba, 156p. Daros E, Oliveira RA, Zambon JLC, Bespalhok Filho JC, Brasileiro BP, Ido OT, Ruaro L and Heroldo Weber (2017) RB036088 – a sugarcane cultivar for mechanical planting and harvesting. Crop Breeding and Applied Biotechnology 17: 84-88. Carneiro MS, Chapola RG, Fernandes Júnior AR, Cursi DE, Barreto FZ, Balsalobre TWA and Hoffmann HP (2015) RB975952 – Early maturing sugarcane cultivar. Crop Breeding and Applied Biotechnology 15: 193-196. Eberhart SA and Hussell WA (1966) Stability parameters for comparing varieties. Crop Science 6: 36-40. Carneiro MS, Chapola RG, Fernandes Júnior AR, Cursi DE, Barreto FZ, Balsalobre TWA and Hoffmann HP (2016) RB975242 and RB975201 - Late maturation sugarcane varieties. Crop Breeding and Applied Biotechnology 16: 365-370. This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Fernandes AC (2003) Cálculos na agroindústria da cana-de-açúcar. 2nd edn, EME, Piracicaba, 240p. Fernandes AC (2003) Cálculos na agroindústria da cana-de-açúcar. 2nd edn, EME, Piracicaba, 240p. Iaia AM, Oliveira RA, Melo LJOT, Daros E, Simões Neto DE, Bastos GQ, Oliveira FJ, Chaves A and Melo TTAT (2015) RB002504 – New early-maturing sugarcane cultivar. Crop Breeding and Applied Biotechnology 15: 45-47. Costet L, Cunff L LE, Royaert S, Raboin LM, Hervouet C, Toubi L, Telismart H, Garsmeur O, Rouselle Y, Pauquet J, Nibouche S, Glaszmann JC, Hoarau JY and D’Hont A (2012) Haplotype structure around Bru1 This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Crop Breeding and Applied Biotechnology - 18: 325-329, 2018 329
https://openalex.org/W2591962833
https://www.biogeosciences.net/15/137/2018/bg-15-137-2018.pdf
English
null
Microbial methanogenesis in the sulfate-reducing zone of sediments in the Eckernförde Bay, SW Baltic Sea
Biogeosciences
2,018
cc-by
16,968
Microbial methanogenesis in the sulfate-reducing zone of sediments in the Eckernförde Bay, SW Baltic Sea Johanna Maltby1,a, Lea Steinle2,1, Carolin R. Löscher3,1, Hermann W. Bange1, Martin A. Fischer4, Mark Schmidt1, and Tina Treude5,6 altby1,a, Lea Steinle2,1, Carolin R. Löscher3,1, Hermann W. Bange1, Martin A. Fischer4, Mark 5 6 Johanna Maltby1,a, Lea Steinle2,1, Carolin R. Löscher3,1, Hermann W. Bange1, Martin A. Fi and Tina Treude5,6 1GEOMAR Helmholtz Centre for Ocean Research Kiel, Department of Marine Biogeochemistry, 24148 Kiel, Germany 2Department of Environmental Sciences, University of Basel, 4056 Basel, Switzerland 3Nordic Center for Earth Evolution, University of Southern Denmark, 5230 Odense, Denmark 4Institute of Microbiology, Christian-Albrecht-University Kiel, 24118 Kiel, Germany 5Department of Earth, Planetary, and Space Sciences, University of California Los Angeles (UCLA), Los Angeles, California 90095-1567, USA 5Department of Earth, Planetary, and Space Sciences, University of California Los Angeles (UCL Los Angeles, California 90095-1567, USA 6Department of Atmospheric and Oceanic Sciences, University of California Los Angeles (UCLA), Los Angeles, California 90095-1567, USA Department of Atmospheric and Oceanic Sciences, University of California Los Angeles (UCLA), os Angeles, California 90095-1567, USA resent address: Natural Sciences Department, Saint Joseph’s College, Standish, Maine 04084, USA orrespondence: Johanna Maltby (jmaltby@sjcme.edu) and Tina Treude (ttreude@g.ucla.edu) Correspondence: Johanna Maltby (jmaltby@sjcme.edu) and Tina Treude (ttreude@g.ucla.edu Received: 4 February 2017 – Discussion started: 7 March 2017 Received: 4 February 2017 – Discussion started: 7 March 2017 Revised: 30 October 2017 – Accepted: 8 November 2017 – Published: 10 January 2018 Received: 4 February 2017 – Discussion started: 7 March 2017 Received: 4 February 2017 – Discussion started: 7 March 2017 Revised: 30 October 2017 – Accepted: 8 November 2017 – Published: 10 January 2018 Revised: 30 October 2017 – Accepted: 8 November 2017 – Published: 10 January 2018 Abstract. Benthic microbial methanogenesis is a known source of methane in marine systems. In most sediments, the majority of methanogenesis is located below the sulfate- reducing zone, as sulfate reducers outcompete methanogens for the major substrates hydrogen and acetate. The coex- istence of methanogenesis and sulfate reduction has been shown before and is possible through the usage of non- competitive substrates by methanogens such as methanol or methylated amines. However, knowledge about the magni- tude, seasonality, and environmental controls of this noncom- petitive methane production is sparse. In the present study, the presence of methanogenesis within the sulfate reduc- tion zone (SRZ methanogenesis) was investigated in sed- iments (0–30 cm below seafloor, cm b.s.f.) of the season- ally hypoxic Eckernförde Bay in the southwestern Baltic Sea. Microbial methanogenesis in the sulfate-reducing zone of sediments in the Eckernförde Bay, SW Baltic Sea Water column parameters such as oxygen, temperature, and salinity together with porewater geochemistry and ben- thic methanogenesis rates were determined in the sampling area “Boknis Eck” quarterly from March 2013 to Septem- ber 2014 to investigate the effect of seasonal environmental changes on the rate and distribution of SRZ methanogene- sis, to estimate its potential contribution to benthic methane emissions, and to identify the potential methanogenic groups responsible for SRZ methanogenesis. The metabolic path- way of methanogenesis in the presence or absence of sul- fate reducers, which after the addition of a noncompetitive substrate was studied in four experimental setups: (1) un- altered sediment batch incubations (net methanogenesis), (2) 14C-bicarbonate labeling experiments (hydrogenotrophic methanogenesis), (3) manipulated experiments with the ad- dition of either molybdate (sulfate reducer inhibitor), 2- bromoethanesulfonate (methanogen inhibitor), or methanol (noncompetitive substrate, potential methanogenesis), and (4) the addition of 13C-labeled methanol (potential methy- lotrophic methanogenesis). After incubation with methanol, molecular analyses were conducted to identify key functional methanogenic groups during methylotrophic methanogene- sis. To also compare the magnitudes of SRZ methanogen- esis with methanogenesis below the sulfate reduction zone (> 30 cm b.s.f.), hydrogenotrophic methanogenesis was de- termined by 14C-bicarbonate radiotracer incubation in sam- ples collected in September 2013. SRZ methanogenesis changed seasonally in the up- per 30 cm b.s.f. with rates increasing from March (0.2 nmol cm−3 d−1) to November (1.3 nmol cm−3 d−1) 2013 and March (0.2 nmol cm−3 d−1) to September (0.4 nmol cm−3 d−1) 2014. Its magnitude and distribution appeared to be controlled by organic matter availability, Biogeosciences, 15, 137–157, 2018 https://doi.org/10.5194/bg-15-137-2018 © Author(s) 2018. This work is distributed under the Creative Commons Attribution 3.0 License. Biogeosciences, 15, 137–157, 2018 https://doi.org/10.5194/bg-15-137-2018 © Author(s) 2018. This work is distributed under the Creative Commons Attribution 3.0 License. 1 Introduction After water vapor and carbon dioxide, methane is the most abundant greenhouse gas in the atmosphere (e.g., Hartmann et al., 2013; Denman et al., 2007). Its atmospheric concen- tration has increased more than 150 % since preindustrial times, mainly through increased human activities such as fos- sil fuel usage and livestock breeding (Hartmann et al., 2013; Wuebbles and Hayhoe, 2002; Denman et al., 2007). Deter- mining the natural and anthropogenic sources of methane is one of the major goals for oceanic, terrestrial, and atmo- spheric scientists to be able to predict further impacts on the world’s climate. The ocean is considered to be a modest nat- ural source for atmospheric methane (Wuebbles and Hayhoe, 2002; Reeburgh, 2007; EPA, 2010). However, research is still sparse on the origin of the observed oceanic methane, which automatically leads to uncertainties in current ocean flux es- timations (Bange et al., 1994; Naqvi et al., 2010; Bakker et al., 2014). p Sulfate reduction is the dominant pathway of organic car- bon degradation in Eckernförde Bay sediments in the upper 30 cm b.s.f., followed by methanogenesis in deeper sediment layers where sulfate is depleted (≪30 cm b.s.f.; Whiticar, 2002; Treude et al., 2005a; Martens et al., 1998; Fig. 1). This methanogenesis below the sulfate–methane transition zone (SMTZ) can be intense and often leads to methane oversat- uration in the porewater below 50 cm of sediment depth, re- sulting in gas bubble formation (Abegg and Anderson, 1997; Whiticar, 2002; Thießen et al., 2006). Thus, methane is trans- ported from the methanogenic zone (> 30 cm b.s.f.) to the sur- face sediment by both molecular diffusion and advection via rising gas bubbles (Wever et al., 1998; Treude et al., 2005a). Although upward-diffusing methane is mostly retained by the anaerobic oxidation of methane (AOM; Treude et al., 2005a), a major part is reaching the sediment–water interface through gas bubble transport (Treude et al., 2005a; Jackson et al., 1998), resulting in a supersaturation of the water column with respect to atmospheric methane concentrations (Bange et al., 2010). The time series station Boknis Eck in the Eck- ernförde Bay is a known site of methane emissions into the Within the marine environment, the coastal areas (includ- ing estuaries and shelf regions) are considered the major source for atmospheric methane, contributing up to 75 % to the global ocean methane production (Bange et al., 1994). J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 138 In marine sediments, methanogenesis activity is mostly restricted to the sediment layers below sulfate reduction due to the successful competition of sulfate reducers with methanogens for the mutual substrates acetate and hydrogen (H2; Oremland and Polcin, 1982; Crill and Martens, 1986; Jørgensen, 2006). Methanogens produce methane mainly from using acetate (acetoclastic methanogenesis) or H2 and carbon dioxide (CO2; hydrogenotrophic methanogenesis). Competition with sulfate reducers can be relieved through the usage of noncompetitive substrates (e.g., methanol or methylated compounds, methylotrophic methanogenesis; Ci- cerone and Oremland, 1988; Oremland and Polcin, 1982). The coexistence of sulfate reduction and methanogenesis has been detected in a few studies from organic-rich sediments, e.g., salt-marsh sediments (Oremland et al., 1982; Buckley et al., 2008), coastal sediments (Holmer and Kristensen, 1994; Jørgensen and Parkes, 2010), or sediments in upwelling re- gions (Pimenov et al., 1993; Ferdelman et al., 1997; Maltby et al., 2016), indicating the importance of these environments for methanogenesis within the sulfate reduction zone (SRZ methanogenesis). So far, however, environmental controls of SRZ methanogenesis remain elusive. C / N, temperature, and oxygen in the water column, revealing higher rates in the warm, stratified, hypoxic seasons (September–November) compared to the colder, oxygenated seasons (March–June) of each year. The ma- jority of SRZ methanogenesis was likely driven by the usage of noncompetitive substrates (e.g., methanol and methylated compounds) to avoid competition with sulfate reducers, as was indicated by the 1000–3000-fold increase in potential methanogenesis activity observed after methanol addition. Accordingly, competitive hydrogenotrophic methanogenesis increased in the sediment only below the depth of sulfate penetration (> 30 cm b.s.f.). Members of the family Methanosarcinaceae, which are known for methylotrophic methanogenesis, were detected by PCR using Methanosarcinaceae-specific primers and are likely to be responsible for the observed SRZ methanogenesis. The present study indicates that SRZ methanogenesis is an important component of the benthic methane budget and car- bon cycling in Eckernförde Bay. Although its contributions to methane emissions from the sediment into the water col- umn are probably minor, SRZ methanogenesis could directly feed into methane oxidation above the sulfate–methane tran- sition zone. The coastal inlet Eckernförde Bay (southwestern Baltic Sea) is an excellent model environment to study seasonal and environmental controls of benthic SRZ methanogene- sis. Here, the muddy sediments are characterized by high organic loading and high sedimentation rates (Whiticar, 2002), which lead to anoxic conditions within the upper- most 0.1–0.2 cm b.s.f. (Preisler et al., 2007). J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone Seasonally hy- poxic (dissolved oxygen < 63 µM) and anoxic (dissolved oxygen = 0 µM) events in the bottom water of Eckernförde Bay (Lennartz et al., 2014; Steinle et al., 2017) provide ideal conditions for anaerobic processes at the sediment surface. Published by Copernicus Publications on behalf of the European Geosciences Union. Published by Copernicus Publications on behalf of the European Geosciences Union. www.biogeosciences.net/15/137/2018/ 2.1 Study site Samples were taken at the time series station Boknis Eck (BE; 54◦31.15 ′N, 10◦02.18 ′E; http://www.bokniseck.de) lo- cated at the entrance of Eckernförde Bay in the southwestern Baltic Sea with a water depth of about 28 m (map of sampling site can be found in Hansen et al., 1999). From mid-March until mid-September the water column is strongly stratified due to the inflow of saltier North Sea water and warmer and fresher surface water (Bange et al., 2011). Organic matter degradation in the deep layers causes pronounced hypoxia (March–September) or even anoxia (August–September; Smetacek, 1985; Smetacek et al., 1984). The source of or- ganic material is phytoplankton blooms that occur regularly in spring (February–March) and fall (September–November) and are followed by the pronounced sedimentation of organic matter (Bange et al., 2011). To a lesser extent, phytoplank- ton blooms and sedimentation are also observed during the summer months (July–August; Smetacek et al., 1984). Sed- iments at BE are generally classified as soft, fine-grained muds (< 40 µm) with a carbon content of 3 to 5 wt % (Balzer et al., 1986). The bulk of organic matter in Eckernförde Bay In the present study, we investigated sediments from within (< 30 cm b.s.f., on a seasonal basis) and below the sul- fate reduction zone (≪30 cm b.s.f., on one occasion) and the water column (on a seasonal basis) at the time series station Boknis Eck in Eckernförde Bay to validate the existence of SRZ methanogenesis and its potential contribution to ben- thic methane emissions. Water column parameters like oxy- gen, temperature, and salinity together with porewater geo- chemistry and benthic methanogenesis were measured over the course of 2 years. In addition to seasonal rate measure- ments, inhibition and stimulation experiments, stable isotope probing, and molecular analysis were carried out to find out if 1 Introduction The majority of coastal methane is produced during micro- bial methanogenesis in the sediment, with probably only a minor part originating from methane production within the water column (Bakker et al., 2014). However, knowledge on the magnitude, seasonality, and environmental controls of benthic methanogenesis is still limited. www.biogeosciences.net/15/137/2018/ Biogeosciences, 15, 137–157, 2018 J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 139 J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 139 Figure 1. Overview of processes relevant for benthic methane production, consumption, and emission in the Eckernförde Bay. The thickness of arrows for emissions and coupling between surface processes indicates the strength of methane supply. Note that this figure combines existing knowledge with results from the present study. See discussion for more details. Figure 1. Overview of processes relevant for benthic methane production, consumption, and emission in the Eckernförde Bay. The thickness of arrows for emissions and coupling between surface processes indicates the strength of methane supply. Note that this figure combines existing knowledge with results from the present study. See discussion for more details. Figure 1. Overview of processes relevant for benthic methane production, consumption, and emission in the Eckernförde Bay. The thickness of arrows for emissions and coupling between surface processes indicates the strength of methane supply. Note that this figure combines existing knowledge with results from the present study. See discussion for more details. atmosphere throughout the year due to this supersaturation of the water column (Bange et al., 2010). SRZ methanogenesis (1) is controlled by environmental pa- rameters, (2) shows seasonal variability, and/or (3) is based on noncompetitive substrates with a special focus on methy- lotrophic methanogens. The source for benthic and water column methane was seen in methanogenesis below the SMTZ (≪30 cm b.s.f.; Whiticar, 2002); however, the coexistence of sulfate re- duction and methanogenesis has been postulated (Whiticar, 2002; Treude et al., 2005a). Still, the magnitude and envi- ronmental controls of SRZ methanogenesis are poorly un- derstood, even though SRZ methanogenesis may make a measurable contribution to benthic methane emissions given the short diffusion distance to the sediment–water interface (Knittel and Boetius, 2009). The production of methane within the sulfate reduction zone of Eckernförde Bay sedi- ments could further explain the peaks in methane oxidation observed in top sediment layers, which was previously at- tributed to methane transported to the sediment surface via rising gas bubbles (Treude et al., 2005a). J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 140 sediments originates from marine plankton and macroalgal sources (Orsi et al., 1996), and its degradation leads to the production of free methane gas (Wever and Fiedler, 1995; Abegg and Anderson, 1997; Wever et al., 1998). The oxy- gen penetration depth is limited to the upper few millimeters when bottom waters are oxic (Preisler et al., 2007). Reduc- ing conditions within the sulfate reduction zone lead to a dark gray or black sediment color with a strong hydrogen sulfur odor in the upper meter of the sediment and a dark olive- green color in the deeper sediment layers (> 1 m; Abegg and Anderson, 1997). followed by storage at room temperature until further treat- ment. Concentrations of dissolved methane (CH4) were deter- mined by headspace gas chromatography as described in Bange et al. (2010). Calibration for CH4 was done by using a two-point calibration with known methane concentrations before the measurement of headspace gas samples, resulting in an error of < 5 %. Water samples for chlorophyll concentration were taken by transferring the complete water volume (from 25 m wa- ter of depth) from one water sampler into a 4.5 L Nalgene bottle, from which approximately 0.7–1 L (depending on the plankton content) were filtrated back in the GEOMAR laboratory using a GF/F filter (Whatman; 25 mm diameter, 8 µM pores size). Dissolved chlorophyll a concentrations were determined using the fluorometric method described by Welschmeyer (1994) with an error of < 10 %. 2.4 Sediment porewater geochemistry Porewater was extracted from sediment within 24 h after core retrieval using nitrogen (N2) pre-flushed rhizons (0.2 µm; Rhizosphere Research Products; Seeberg-Elverfeldt et al., 2005). In MUC cores, rhizons were inserted into the sedi- ment in 2 cm intervals through pre-drilled holes in the core liner. In the gravity core, rhizons were inserted into the sedi- ment in 30 cm intervals directly after retrieval. Extracted porewater from MUC and gravity cores was im- mediately analyzed for sulfide using standardized photomet- ric methods (Grasshoff et al., 1999). Sediment cores were taken with a miniature multi- corer (MUC; K.U.M. Kiel), holding four core liners (length = 60 cm, diameter = 10 cm) at once. The cores had an average length of ∼30 cm and were stored at 10 ◦C in a cold room (GEOMAR) until further processing (normally within 1–3 days after sampling). Sulfate concentrations were determined using ion chro- matography (Metrohm 761). Analytical precision was < 1 % based on repeated analysis of IAPSO seawater standards (di- lution series) with an absolute detection limit of 1 µM cor- responding to a detection limit of 30 µM for the undiluted sample. In September 2013, a gravity core was taken in addi- tion to the MUC cores. The gravity core was equipped with an inner plastic bag (polyethylene; diameter: 13 cm). Af- ter core recovery (330 cm total length), the polyethylene bag was cut open at 12 different sampling depths, result- ing in intervals of 30 cm, and sampled directly onboard for sediment porewater geochemistry (see Sect. 2.4), sediment methane (see Sect. 2.5), sediment solid-phase geochemistry (see Sect. 2.6), and microbial rate measurements for hy- drogenotrophic methanogenesis as described in Sect. 2.8. For analysis of dissolved inorganic carbon (DIC), 1.8 mL of porewater was transferred into a 2 mL glass vial, fixed with 10 µL saturated HgCL2 solution, and crimp sealed. DIC con- centration was determined as CO2 with a multi N/C 2100 analyzer (Analytik Jena) following the manufacturer instruc- tions. Therefore, the sample was acidified with phosphoric acid and the outgassing CO2 was measured. The detection limit was 20 µM with a precision of 2–3 %. 2.2 Water column and sediment sampling Sampling was done on a seasonal basis during the years 2013 and 2014. One-day field trips with either RV Alkor (cruise no. AL410), RV Littorina, or RV Polarfuchs were conducted in March, June, and September of each year. In 2013, additional sampling was conducted in November. In each sampling month, water profiles of temperature, salinity, and oxygen concentration (optical sensor RINKO III; detec- tion limit = 2 µM) were measured with a CTD (Hydro-Bios). In addition, water samples for methane concentration mea- surements were taken at 25 m of water depth with a Niskin bottle (4 L each) rosette attached to the CTD (Table 1). Com- plementary samples for water column chlorophyll were taken at 25 m of water depth with the CTD rosette within the same months during standardized monthly sampling cruises to Boknis Eck organized by GEOMAR. www.biogeosciences.net/15/137/2018/ Biogeosciences, 15, 137–157, 2018 2.3 Water column parameters In March 2013, June 2013, and March 2014, one MUC core was sliced in 1 cm intervals until 6 cm b.s.f. followed by 2 cm intervals until the end of the core. In the other sampling months, the MUC core was sliced in 1 cm intervals until 6 cm b.s.f. followed by 2 cm intervals until 10 cm b.s.f. and 5 cm intervals until the end of the core. In each sampling month, water samples for methane con- centration measurements were taken at 25 m of water depth in triplicates. Therefore, three 25 mL glass vials were filled bubble free directly after CTD rosette recovery and closed with butyl rubber stoppers. Biological activity in samples was stopped by adding saturated mercury chloride solution Per sediment depth (in MUC and gravity cores), 2 cm−3 of sediment were transferred into a 10 mL glass vial contain- Biogeosciences, 15, 137–157, 2018 www.biogeosciences.net/15/137/2018/ J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 141 J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone Table 1. Sampling months with bottom water (∼2 m above the seafloor) temperature (Temp.), dissolved oxygen (O2), and dissolved (CH4) concentration. Sampling month Date Instrument Temp. O2 CH4 Type of (◦C) (µM) (nM) analysis March 2013 13.03.2013 CTD 3 340 30 WC MUC All June 2013 27.06.2013 CTD 6 94 125 WC MUC All September 2013 25.09.2013 CTD 10 bdl 262∗ WC MUC All GC GC-All November 2013 08.11.2013 CTD 12 163 13 WC MUC All March 2014 13.03.2014 CTD 4 209 41∗ WC MUC All June 2014 08.06.2014 CTD 7 47 61 WC MUC All September 2014 17.09.2014 CTD 13 bdl 234 WC MUC All MUC: multicorer, GC: gravity corer, CTD: CTD rosette, bdl: below detection limit (5 µM), All: methane gas analysis, porewater analysis, sediment geochemistry, net methanogenesis analysis, hydrogenotrophic methanogenesis analysis, GC-All: analysis for gravity cores including methane gas analysis, porewater analysis, sediment geochemistry, hydrogenotrophic methanogenesis analysis, WC: water column analyses including methane analysis, chlorophyll analysis. ∗Concentrations from the regular monthly Boknis Eck sampling cruises on 24 September 2013 and 5 March 2014 (www.bokniseck.de). hs with bottom water (∼2 m above the seafloor) temperature (Temp.), dissolved oxygen (O2), Sampling month Date Instrument Temp. 2.7 Sediment methanogenesis ing 5 mL NaOH (2.5 %) for the determination of sediment methane concentration per volume of sediment. The vial was quickly closed with a butyl septum, crimp sealed, and shaken thoroughly. The vials were stored upside down at room tem- perature until measurement via gas chromatography. There- fore, 100 µL of headspace was removed from the gas vials and injected into a Shimadzu gas chromatograph (GC-2014) equipped with a packed Haysep-D column and a flame ion- ization detector. The column temperature was 80 ◦C and the helium flow was set to 12 mL min−1. CH4 concentrations were calibrated against CH4 standards (Scotty gases). The detection limit was 0.1 ppm with a precision of 2 %. 2.3 Water column parameters O2 CH4 Type of (◦C) (µM) (nM) analysis March 2013 13.03.2013 CTD 3 340 30 WC MUC All June 2013 27.06.2013 CTD 6 94 125 WC MUC All September 2013 25.09.2013 CTD 10 bdl 262∗ WC MUC All GC GC-All November 2013 08.11.2013 CTD 12 163 13 WC MUC All March 2014 13.03.2014 CTD 4 209 41∗ WC MUC All June 2014 08.06.2014 CTD 7 47 61 WC MUC All September 2014 17.09.2014 CTD 13 bdl 234 WC MUC All MUC: multicorer, GC: gravity corer, CTD: CTD rosette, bdl: below detection limit (5 µM), All: methane gas analysis, porewater analysis, sediment geochemistry, net methanogenesis analysis, hydrogenotrophic methanogenesis analysis, GC-All: analysis for gravity cores including methane gas analysis, porewater analysis, sediment geochemistry, hydrogenotrophic methanogenesis analysis, WC: water column analyses including methane analysis, chlorophyll analysis. ∗Concentrations from the regular monthly Boknis Eck sampling cruises on 24 September 2013 and 5 March 2014 (www.bokniseck.de). Table 1. Sampling months with bottom water (∼2 m above the seafloor) temperature (Temp.), dissolved oxygen (O2), and dissolved methane (CH4) concentration. Table 1. Sampling months with bottom water (∼2 m above the seafloor) temperature (Temp.), dissolved oxygen (O2), and dissolved methane (CH4) concentration. 2.6 Sediment solid-phase geochemistry Following the sampling for CH4, the same cores described under Sect. 2.5 were used for the determination of the sedi- ment solid-phase geochemistry, i.e., porosity, particulate or- ganic carbon (POC), and particulate organic nitrogen (PON). The sediment porosity of each sampled sediment section was determined by the weight difference of 5 cm−3 of wet sediment after freeze-drying for 24 h. Dried sediment sam- ples were then used for analysis of particulate organic carbon (POC) and particulate organic nitrogen (PON) with a Carlo Erba element analyzer (NA 1500). The detection limit for C and N analysis was < 0.1 dry weight percent (%) with a pre- cision of < 2 %. Following the sampling for CH4, the same cores described under Sect. 2.5 were used for the determination of the sedi- ment solid-phase geochemistry, i.e., porosity, particulate or- ganic carbon (POC), and particulate organic nitrogen (PON). 2.7.1 Methanogenesis in MUC cores In each sampling month, three MUC cores were sliced in 1 cm intervals until 6 cm b.s.f., in 2 cm intervals until 10 cm b.s.f., and in 5 cm intervals until the bottom of the core. Every sediment layer was transferred to a separate beaker and quickly homogenized before subsampling. The exposure time with air, i.e., oxygen, was kept to a minimum. Sedi- ment layers were then sampled for the determination of net methanogenesis (defined as the sum of total methane produc- tion and consumption, including all available methanogenic substrates in the sediment), hydrogenotrophic methanogen- esis (methanogenesis based on the substrates CO2 and H2), and potential methanogenesis (methanogenesis at ideal con- ditions, i.e., no lack of nutrients) as described in the follow- ing sections. Net methanogenesis Net methanogenesis was determined with sediment slurry experiments by measuring the headspace methane concen- tration over time. Per sediment layer, triplicates of 5 cm−3 of sediment were transferred into N2-flushed sterile glass vials (30 mL) and mixed with 5 mL of filtered bottom water. The slurry was repeatedly flushed with N2 to remove residual methane and to ensure complete anoxia. Slurries were incu- bated in the dark at in situ temperature, which varied for each sampling date (Table 1). Headspace samples (0.1 mL) were The sediment porosity of each sampled sediment section was determined by the weight difference of 5 cm−3 of wet sediment after freeze-drying for 24 h. Dried sediment sam- ples were then used for analysis of particulate organic carbon (POC) and particulate organic nitrogen (PON) with a Carlo Erba element analyzer (NA 1500). The detection limit for C and N analysis was < 0.1 dry weight percent (%) with a pre- cision of < 2 %. Hydrogenotrophic methanogenesis To determine if hydrogenotrophic methanogenesis, i.e., methanogenesis based on the competitive substrate H2, is present in the sulfate-reducing zone, radioactive sodium bi- carbonate (NaH14CO3) was added to the sediment. Per sediment layer, sediment was sampled in triplicates with glass tubes (5 mL) that were closed with butyl rubber stoppers on both ends according to Treude et al. (2005b). Through the stopper, NaH14CO3 (dissolved in water, injec- tion volume 6 µL, activity 222 kBq, specific activity = 1.85– 2.22 GBq mmol−1) was injected into each sample and in- cubated for 3 days in the dark at in situ temperature (Ta- ble 1). To stop bacterial activity, sediment was transferred into 50 mL glass vials filled with 20 mL of sodium hydrox- ide (2.5 % w/w), closed quickly with rubber stoppers, and shaken thoroughly. Five controls were produced from vari- ous sediment depths by injecting the radiotracer directly into the NaOH with sediment. Potential methylotrophic methanogenesis from methanol using stable isotope probing One additional experiment was conducted with sediments from September 2014 by adding 13C-labeled methanol to in- vestigate the production of 13C-labeled methane. Three cores were stored at 1 ◦C after the September 2014 cruise until further processing ∼3.5 months later. The low storage tem- perature together with the expected oxygen depletion in the enclosed supernatant water after the retrieval of the cores likely led to slowed anaerobic microbial activity during stor- age time and preserved the sediments for potential methano- genesis measurements. The production of 14C-methane was determined with the slightly modified method by Treude et al. (2005b) used for the determination of the anaerobic oxidation of methane. The method was identical, except no unlabeled methane was de- termined by using gas chromatography. Instead, DIC values were used to calculate hydrogenotrophic methane produc- tion. Sediment cores were sliced in 2 cm intervals and the up- per 0–2 cm b.s.f. sediment layer of all three cores was com- bined in a beaker and homogenized. Then, sediment slurries were prepared by mixing 5 cm−3 of sediment with 5 mL of artificial seawater medium in N2-flushed, sterile glass vials (30 mL). After this, methanol was added to the slurry with a final concentration of 10 mM (see also the previous para- graph about potential methanogenesis in manipulated exper- iments). Methanol was enriched with 13C-labeled methanol in a ratio of 1 : 1000 between 13C-labeled (99.9 % 13C) and non-labeled methanol mostly consisting of 12C (manufac- turer: Roth). In total, 54 vials were prepared for nine dif- ferent sampling time points during a total incubation time of 37 days. All vials were incubated at 13 ◦C (in situ tempera- ture in September 2014) in the dark. At each sampling point, six vials were stopped: one set of triplicates was used for headspace methane and carbon dioxide determination and a second set of triplicates was used for porewater analysis. J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 142 Molybdate was used as an enzymatic inhibitor for sulfate re- duction (Oremland and Capone, 1988) and BES was used as an inhibitor for methanogenic Archaea (Hoehler et al., 1994). Methanol is a known noncompetitive substrate, which is used by methanogens but not by sulfate reducers (Oremland and Polcin, 1982), and thus it is suitable to examine noncompet- itive methanogenesis. Treatments were incubated similar to net methanogenesis (see the previous paragraph about net methanogenesis) by incubating sediment slurries at the re- spective in situ temperature (Table 1) in the dark for a time period of 4 weeks. Headspace samples (0.1 mL) were taken every 3–5 days over a time period of 4 weeks and potential methanogenesis rates were determined by the linear increase in methane concentration over time (minimum of six time points). taken out every 3–4 days over a time period of 4 weeks and analyzed on a Shimadzu GC-2104 gas chromatograph (see Sect. 2.5). Net methanogenesis rates were determined by the linear increase in the methane concentration over time (min- imum of six time points; see also Fig. S1 in the Supplement). www.biogeosciences.net/15/137/2018/ Biogeosciences, 15, 137–157, 2018 J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 143 frozen at −20 ◦C. DNA was extracted from ∼500 mg of sediment using the FastDNA® SPIN Kit for Soil (Biomed- ical). The quantitative real-time polymerase chain reaction (qPCR) technique using TaqMan probes and TaqMan chem- istry (Life Technologies) was used for the detection of methanogens on a ViiA7 qPCR machine (Life Technolo- gies). Primer and probe sets as originally published by Yu et al. (2005) were applied to quantify the orders Methanobac- teriales, Methanosarcinales, and Methanomicrobiales along with the two families Methanosarcinaceae and Methanosae- taceae within the order Methanosarcinales. In addition, a uni- versal primer set for the detection of the domain Archaea was used (Yu et al., 2005). CO2) were calibrated against methane standards (Scotty gases). The detection limit was 0.1 ppm with a precision of 2 %. CO2) were calibrated against methane standards (Scotty gases). The detection limit was 0.1 ppm with a precision of 2 %. Analyses of the 13C / 12C ratios of methane and car- bon dioxide were conducted after headspace concentration measurements by using a continuous-flow combustion gas chromatograph (Trace Ultra; Thermo Scientific), which was coupled to an isotope ratio mass spectrometer (MAT253; Thermo Scientific). The isotope ratios of methane and car- bon dioxide given in the common delta notation (δ13C in permill) are reported relative to Vienna Pee Dee Belemnite (VPDB) standard. Isotope precision was ±0.5 ‰ when mea- suring near the detection limit of 10 ppm. For porewater analysis of methanol concentration and iso- tope composition, each sediment slurry of the triplicates was transferred into argon-flushed 15 mL centrifuge tubes and centrifuged for 6 min at 4500 rpm. Then 1 mL of filtered (0.2 µm) porewater was transferred into N2-flushed 2 mL glass vials for methanol analysis, crimp sealed, and immedi- ately frozen at −20 ◦C. Methanol concentrations and isotope composition were determined via high-performance liquid chromatography–ion ratio mass spectrometry (HPLC-IRMS; Thermo Fisher Scientific) at the MPI Marburg. The detection limit was 50 µM with a precision of 0.3 ‰. Absolute quantification of the 16S rDNA from the groups mentioned above was performed with standard dilution se- ries. The standard concentration reached from 108 to 101 copies per µL. Quantification of the standards and samples was performed in duplicates. 2.7.2 Methanogenesis in the gravity core Ex situ hydrogenotrophic methanogenesis was determined in a gravity core taken in September 2013. The pathway is thought to be the main methanogenic pathway in the sedi- ment below the SMTZ in Eckernförde Bay (Whiticar, 2002). Hydrogenotrophic methanogenesis was determined using ra- dioactive sodium bicarbonate (NaH14CO3). At every sam- pled sediment depth (12 depths in 30 cm intervals), tripli- cate glass tubes (5 mL) were inserted directly into the sedi- ment. Tubes were filled bubble free with sediment and closed with butyl rubber stoppers on both ends according to Treude et al. (2005). The methods following sampling were identi- cal to those described in the previous paragraph about hy- drogenotrophic methanogenesis. J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone Reaction was performed in a final volume of 12.5 µL containing 0.5 µL of each primer (10 pmol µL−1; MWG), 0.25 µL of the respective probe (10 pmol µL−1; Life Technologies), 4 µL of H2O (Roth), 6.25 µL of TaqMan Universal Master Mix II (Life Technolo- gies), and 1 µL of sample or standard. Cycling conditions started with an initial denaturation and activation step for 10 min at 95 ◦C followed by 45 cycles of 95 ◦C for 15 s, 56 ◦C for 30 s, and 60 ◦C for 60 s. Non-template controls were run in duplicates with water instead of DNA for all primer and probe sets and remained without any detectable signal after 45 cycles. 2.9 Statistical analysis To determine the possible environmental control parame- ters of SRZ methanogenesis, a principal component analysis (PCA) was applied according to the approach described in Gier et al. (2016). Prior to PCA, the dataset was transformed into ranks to ensure the same data dimensions. In total, two PCAs were conducted. The first PCA was used to test the relation of parameters in the surface sed- iment (integrated methanogenesis (0–5 cm, mmol m−2 d−1), POC content (average value from 0–5 cm b.s.f., wt %), C / N (average value from 0–5 cm b.s.f., molar) and the bottom wa- ter (25 m of water depth) oxygen (µM), temperature (◦C), salinity (PSU), chlorophyll (µg L−1), and methane (nM). The second PCA was applied on depth profiles of sediment SRZ methanogenesis (nmol cm−3 d−1), sediment depth (cm), sed- iment POC content (wt %), sediment C / N ratio (molar), and sampling month (one value per depth profile at a specific month, the later in the year the higher the value). Potential methanogenesis in manipulated experiments To examine the interaction between sulfate reduction and methanogenesis, inhibition and stimulation experiments were carried out. Therefore, every other sediment layer was sampled resulting in the following examined six sediment layers: 0–1, 2–3, 4–5, 6–8, 10–15, and 20–25 cm. From each layer, sediment slurries were prepared by mixing 5 mL of sediment in a 1 : 1 ratio with an adapted artificial seawater medium (salinity 24; Widdel and Bak, 1992) in N2-flushed, sterile glass vials before further manipulations. In total, four different treatments, each in triplicates, were prepared per depth: (1) with sulfate addition (17 mM), (2) with sulfate (17 mM) and molybdate (22 mM) addi- tion, (3) with sulfate (17 mM) and 2-bromoethanesulfonate (BES; 60 mM) addition, and (4) with sulfate (17 mM) and methanol (10 mM) addition. From here on, the following names are used to describe the different treatments, re- spectively: (1) control treatment, (2) molybdate treatment, (3) BES treatment, and (4) methanol treatment. Control treat- ments feature the natural sulfate concentrations occurring in sediments of the sulfate reduction zone at the sampling site. Headspace methane and carbon dioxide concentrations (volume 100 µL) were determined on a Shimadzu gas chro- matograph (GC-2014) equipped with a packed Haysep-D column, a flame ionization detector, and a methanizer. The methanizer (reduced nickel) reduces carbon dioxide with hydrogen to methane at a temperature of 400 ◦C. The col- umn temperature was 80 ◦C and the helium flow was set to 12 mL min−1. Methane concentrations (including reduced Biogeosciences, 15, 137–157, 2018 www.biogeosciences.net/15/137/2018/ www.biogeosciences.net/15/137/2018/ 2.8 Molecular analysis During the non-labeled methanol treatment of the 0– 1 cm b.s.f. horizon from the September 2014 sampling (see also the previous paragraph about potential methanogenesis in manipulated experiments), additional samples were pre- pared to detect and quantify the presence of methanogens in the sediment. Therefore, an additional 15 vials were pre- pared with the addition of methanol as described in the pre- vious paragraph about potential methanogenesis in manipu- lated experiments for five different time points (day 1 (= t0), day 8, day 16, day 22, and day 36) and stopped at each time point by transferring sediment from the triplicate slur- ries into whirl-paks (Nasco), which then were immediately For each PCA, biplots were produced to view data from different angles and to graphically determine a potential pos- itive, negative, or zero correlation between methanogenesis rates and the tested variables. www.biogeosciences.net/15/137/2018/ Biogeosciences, 15, 137–157, 2018 J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 144 eters measured in the water column and sediment in the Eckernförde Bay in each sampling month in the yea MG) and hydrogenotrophic (hydr.) methanogenesis rates are shown in triplicates with mean (solid line). , 15, 137–157, 2018 www.biogeosciences.net/15 Figure 2. Parameters measured in the water column and sediment in the Eckernförde Bay in each sampling month in the year 2013. Net methanogenesis (MG) and hydrogenotrophic (hydr.) methanogenesis rates are shown in triplicates with mean (solid line). www.biogeosciences.net/15/137/2018/ www.biogeosciences.net/15/137/2018/ Biogeosciences, 15, 137–157, 2018 3.1 Water column parameters In all sampling months, the sulfide concentration increased with sediment depth (Figs. 2 and 3). Similar to methane, sul- fide profiles revealed higher sulfide concentrations at a shal- lower sediment depth together with higher peak concentra- tions over the course of the sampled months in each sampling year. Accordingly, November 2013 (10.5 mM at 15 cm b.s.f.) and September 2014 (2.8 mM at 15 cm b.s.f.) revealed the highest sulfide concentrations. September 2014 was the only sampling month showing a pronounced decrease in sulfide concentration from 15 to 21 cm b.s.f. of over 50 %. From March 2013 to September 2014, the water column had pronounced temporal and spatial variability in temper- ature, salinity, and oxygen (Figs. 2 and 3). In 2013, the tem- perature of the upper water column increased from March (1 ◦C) to September (16 ◦C), but decreased again in Novem- ber (11 ◦C). The temperature of the lower water column in- creased from March 2013 (2 ◦C) to November 2013 (12 ◦C). In 2014, the lowest temperatures of the upper and lower wa- ter column were reached in March (4 ◦C). Warmer tempera- tures of the upper water column were observed in June and September (around 17 ◦C), while the lower water column peaked in September (13 ◦C). DIC concentrations increased with increasing sediment depth in all sampling months. Concomitant with the high- est sulfide concentrations, the highest DIC concentration was detected in November 2013 (26 mM at 27 cm b.s.f.). At the surface, DIC concentrations ranged between 2 and 3 mM in all sampling months. In June of both years, DIC concentra- tions were lowest at the deepest sampled depth compared to the other sampling months (16 mM in 2013, 13 mM in 2014). In all sampling months, POC profiles scattered around 5 ± 0.9 wt % with depth. Only in November 2013, June 2014, and September 2014 did POC content exceed 5 wt % in the upper 0–1 cm b.s.f. (5.9, 5.2, and 5.3 wt %, respectively) with the highest POC content in November 2013. Also in Novem- ber 2013, the surface C / N ratio (0–1 cm b.s.f.) of the partic- ulate organic matter was the lowest of all sampling months (8.6). In general, the C / N ratio increased with depth in both years with values around 9 at the surface and values around 10–11 at the deepest sampled sediment depths. 3 Results tions at a shallower sediment depth late in the year. The mag- nitudes of methane concentrations were similar in the respec- tive months of 2013 and 2014. 3.1 Water column parameters DIC concentrations increased with increasing sediment depth in all sampling months. Concomitant with the high- est sulfide concentrations, the highest DIC concentration was detected in November 2013 (26 mM at 27 cm b.s.f.). At the surface, DIC concentrations ranged between 2 and 3 mM in all sampling months. In June of both years, DIC concentra- tions were lowest at the deepest sampled depth compared to the other sampling months (16 mM in 2013, 13 mM in 2014). Salinity increased over time during 2013, showing the highest salinity of the upper and lower water column in November (18 and 23 PSU, respectively). In 2014, the salin- ity of the upper water column was highest in March and September (both 17 PSU) and lowest in June (13 PSU). The salinity of the lower water column increased from March 2014 (21 PSU) to September 2014 (25 PSU). In all sampling months, POC profiles scattered around 5 ± 0.9 wt % with depth. Only in November 2013, June 2014, and September 2014 did POC content exceed 5 wt % in the upper 0–1 cm b.s.f. (5.9, 5.2, and 5.3 wt %, respectively) with the highest POC content in November 2013. Also in Novem- ber 2013, the surface C / N ratio (0–1 cm b.s.f.) of the partic- ulate organic matter was the lowest of all sampling months (8.6). In general, the C / N ratio increased with depth in both years with values around 9 at the surface and values around 10–11 at the deepest sampled sediment depths. In both years, June and September showed the most pro- nounced vertical gradient of temperature and salinity, featur- ing a pycnocline at around ∼14 m of water depth. Summer stratification was also seen in the O2 profiles, which showed O2 depleted conditions (O2 < 150 µM) in the lower water column from June to September in both years, reaching concentrations below 1–2 µM (detection limit of CTD sensor) in September of both years (Figs. 2 and 3). The water column was completely ventilated, i.e., homog- enized, in March of both years with O2 concentrations of 300–400 µM down to the seafloor at about 28 m. 3.3 Sediment geochemistry in gravity cores Results from sediment porewater and solid-phase geochem- istry in the gravity core from September 2013 are shown in Fig. 4. Please note that the sediment depth of the grav- ity core was corrected by comparing the sulfate concentra- tions at 0 cm b.s.f. in the gravity core with the correspond- ing sulfate concentration and depth in the MUC core from September 2013 (Fig. 2). The soft surface sediment is often lost during the gravity coring procedure. Through this correc- tion, the topmost layer of the gravity core was set at a depth of 14 cm b.s.f. www.biogeosciences.net/15/137/2018/ 145 J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 3 Results 3.2 Sediment geochemistry in MUC cores Sediment porewater and solid-phase geochemistry results for the years 2013 and 2014 are shown in Figs. 2 and 3, respec- tively. Sulfate concentrations at the sediment surface ranged be- tween 15 and 20 mM. The concentration decreased with depth in all sampling months but was never fully depleted until the bottom of the core (18–29 cm b.s.f.; between 2 and 7 mM sulfate). November 2013 showed the strongest de- crease from ∼20 mM at the top to ∼2 mM at the bottom of the core (27 cm b.s.f.). Porewater sulfate concentration in the gravity core de- creased with depth (i.e., below 0.1 mM at 107 cm b.s.f.) and stayed below 0.1 mM until 324 cm b.s.f. Sulfate increased slightly (1.9 mM) at the bottom of the core (345 cm b.s.f.). In concert with sulfate, methane, sulfide, DIC, POC, and C / N profiles also showed distinct alteration in the profile at 345 cm b.s.f. (see below, Fig. 4). As fluid seepage has not been observed at the Boknis Eck station (Schlüter et al., 2000), these alterations could either indicate a change in sediment properties or result from a sampling artifact from the penetration of seawater through the core catcher into the Opposite to sulfate, the methane concentration increased with sediment depth in all sampling months (Figs. 2 and 3). Over the course of a year (i.e., March to November in 2013 and March to September in 2014), the maximum methane concentration increased, reaching the highest concentration in November 2013 (∼1 mM at 26 cm b.s.f.) and September 2014 (0.2 mM at 23 cm b.s.f.). Simultaneously, methane pro- files became steeper, revealing higher methane concentra- 3.4.1 Net methanogenesis Net methanogenesis activity (calculated by the linear in- crease of methane over time; see Fig. S1) was detected throughout the cores in all sampling months (Figs. 2 and 3). Activity measured in MUC cores increased over the course of the year in 2013 and 2014 (that is, March to November in 2013 and March to September in 2014) with lower rates mostly < 0.1 in March and higher rates > 0.2 nmol cm−3 d−1 in November 2013 and September 2014. In general, Novem- ber 2013 revealed the highest net methanogenesis rates (1.3 nmol cm−3 d−1 at 1–2 cm b.s.f.). Peak rates were de- tected at the sediment surface (0–1 cm b.s.f.) in all sam- pling months except for September 2013 when the maxi- mum rates were situated between 10 and 15 cm b.s.f. In addi- tion to the surface peaks, net methanogenesis showed sub- surface (= below 1 until 30 cm b.s.f.) maxima in all sam- pling months, but with alternating depths (between 10 and 25 cm b.s.f.). A comparison of the integrated net methanogenesis rates (0–25 cm b.s.f.) revealed the highest rates in September and November 2013 (0.09 and 0.08 mmol m−2 d−1, respectively) and the lowest rates in March 2014 (0.01 mmol m−2 d−1; Fig. 5). A trend of increasing areal net methanogenesis rates from March to September was observed in both years. J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 146 deepest sediment layer. The latter process is, however, not ex- pected to considerably affect sediment solid-phase properties (POC and C / N), and we therefore dismissed this hypothesis. The methane concentration increased steeply with depth, reaching a maximum of 4.8 mM at 76 cm b.s.f. The concen- tration stayed around 4.7 mM until 262 cm b.s.f. followed by a slight decrease until 324 cm b.s.f. (2.8 mM). From 324 to 345 cm b.s.f. methane increased again (3.4 mM). Figure 3. Parameters measured in the water column and sediment in the Eckernförde Bay in each sampling month in the year 2014. Net methanogenesis (MG) and hydrogenotrophic (hydr.) methano- genesis rates are shown in triplicates with mean (solid line). Both sulfide and DIC concentrations increased with depth, showing a maximum at 45 (∼5 mM) and 345 cm b.s.f. (∼1 mM), respectively. While sulfide decreased after 45 cm b.s.f. to a minimum of ∼300 µM at 324 cm b.s.f., it slightly increased again to ∼1 mM at 345 cm b.s.f. In ac- cordance, DIC concentrations showed a distinct decrease be- tween 324 and 345 cm b.s.f. (from 45 to 39 mM). While POC contents varied around 5 wt % throughout the core, the C / N ratio slightly increased with depth, revealing the lowest ratio at the surface (∼3) and the highest ratio at the bottom of the core (∼13). However, both POC and C / N showed a distinct increase from 324 to 345 cm b.s.f. www.biogeosciences.net/15/137/2018/ www.biogeosciences.net/15/137/2018/ Biogeosciences, 15, 137–157, 2018 J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 3.4.3 Potential methanogenesis in manipulated experiments Potential methanogenesis rates in manipulated experiments included either the addition of inhibitors (molybdate for the inhibition of sulfate reduction or BES for the inhibition of methanogenesis) or the addition of a noncompetitive sub- strate (methanol). Control treatments were run with neither the addition of inhibitors nor the addition of methanol. Controls. Potential methanogenesis activity in the control treatments was below 0.5 nmol cm−3 d−1 from March 2014 to September 2014 (Fig. 6). Only in November 2013 did con- trol rates exceed 0.5 nmol cm−3 d−1 below 6 cm b.s.f. While rates increased with depth in November 2013 and June 2014, they decreased with depth in the other two sampling months. Figure 5. Integrated net methanogenesis (MG) rates (determined by net methane production) and hydrogenotrophic MG rates (de- termined by radiotracer incubation) in the surface sediments (0– 25 cm b.s.f.) of Eckernförde Bay for different sampled time points. Molybdate. Peak potential methanogenesis rates in the molybdate treatments were found in the uppermost sedi- ment interval (0–1 cm b.s.f.) in almost every sampling month with rates being 3–30 times higher compared to the con- trol treatments (< 0.5 nmol cm−3 d−1). In November 2013, potential methanogenesis showed two maxima (0–1 and 10–15 cm b.s.f.). The highest measured rates were found in September 2014 (∼6 nmol cm−3 d−1) followed by Novem- ber 2013 (∼5 nmol cm−3 d−1). only between 0.01 and 0.05 nmol cm−3 d−1. In comparison, maximum hydrogenotrophic methanogenesis was up to 2 or- ders of magnitude lower compared to net methanogenesis. Only in March 2013 did both activities reach a similar range. Overall, hydrogenotrophic methanogenesis increased with depth in March, September, and November 2013 and in March, June, and September 2014. In June 2013, activity de- creased with depth, showing the highest rates in the upper 0–5 cm b.s.f. and the lowest at the deepest sampled depth. BES. Profiles of potential methanogenesis in the BES treatments were similar to the controls mostly in the lower range < 0.5 nmol cm−3 d−1. Only in November 2013 did rates exceed 0.5 nmol cm−3 d−1. Rates increased with depth in all sampling months, except for September 2014, when the highest rates were found at the sediment surface (0– 1 cm b.s.f.). Concomitant with integrated net methanogenesis, integrated hydrogenotrophic methanogenesis rates (0– 25 cm b.s.f.) were high in September 2013, with slightly higher rates in March 2013 (Fig. 5). J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 147 Figure 4. Parameters measured in the sediment gravity core taken in the Eckernförde Bay in September 2013. Hydrogenotrophic (hydr.) methanogenesis rates are shown in triplicates with mean (solid line). Figure 4. Parameters measured in the sediment gravity core taken in the Eckernförde Bay in September 2013. Hydrogenotrophic (hydr.) methanogenesis rates are shown in triplicates with mean (solid line). Figure 5. Integrated net methanogenesis (MG) rates (determined by net methane production) and hydrogenotrophic MG rates (de- termined by radiotracer incubation) in the surface sediments (0– 25 cm b.s.f.) of Eckernförde Bay for different sampled time points. 3.4.3 Potential methanogenesis in manipulated experiments The lowest areal rates of hydrogenotrophic methanogenesis were seen in June of both years. Methanol. In all sampling months, potential rates in the methanol treatments were 3 orders of magnitude higher com- pared to the control treatments (< 0.5 nmol cm−3 d−1). Ex- cept for November 2013, potential methanogenesis rates in the methanol treatments were highest in the upper 0– 5 cm b.s.f. and decreased with depth. In November 2013, the highest rates were detected at the deepest sampled depth (20– 25 cm b.s.f.). Hydrogenotrophic methanogenesis activity in the grav- ity core is shown in Fig. 4. The highest activity (∼0.7 nmol cm−3 d−1) was measured at 45 and 138 cm b.s.f. followed by a decrease with increasing sediment depth reaching 0.01 nmol cm−3 d−1 at the deepest sampled depth (345 cm b.s.f.). Biogeosciences, 15, 137–157, 2018 3.4.2 Hydrogenotrophic methanogenesis Hydrogenotrophic methanogenesis activity determined by 14C-bicarbonate incubations of MUC cores is shown in Figs. 2 and 3. In 2013, maximum activity ranged between 0.01 and 0.2 nmol cm−3 d−1, while in 2014 maxima ranged Figure 3. Parameters measured in the water column and sediment in the Eckernförde Bay in each sampling month in the year 2014. Net methanogenesis (MG) and hydrogenotrophic (hydr.) methano- genesis rates are shown in triplicates with mean (solid line). Biogeosciences, 15, 137–157, 2018 www.biogeosciences.net/15/137/2018/ J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 148 Figure 6. Potential methanogenesis rates versus sediment depth in sediment sampled in November 2013, March 2014, June 2014, and September 2014. Presented are four different types of incubations (treatments): control (blue symbols) describes the treatment with sediment plus artificial seawater containing natural salinity (24 PSU) and sulfate concentrations (17 mM), molybdate (green symbols) is the treatment with the addition of molybdate (22 mM), BES (purple symbols) is the treatment with 60 mM BES addition, and methanol (red symbols) is the treatment with the addition of 10 mM of methanol. Shown are triplicates per depth interval and the mean as a solid line. Please note the different x axis for the methanol treatment (red). Figure 6. Potential methanogenesis rates versus sediment depth in sediment sampled in November 2013, March 2014, June 2014, and September 2014. Presented are four different types of incubations (treatments): control (blue symbols) describes the treatment with sediment plus artificial seawater containing natural salinity (24 PSU) and sulfate concentrations (17 mM), molybdate (green symbols) is the treatment with the addition of molybdate (22 mM), BES (purple symbols) is the treatment with 60 mM BES addition, and methanol (red symbols) is the treatment with the addition of 10 mM of methanol. Shown are triplicates per depth interval and the mean as a solid line. Please note the different x axis for the methanol treatment (red). 3.4.4 Potential methanogenesis followed by 13C-methanol labeling Please note that the majority of CO2 was dissolved in the porewater, and thus the CO2 content in the headspace does not show the total CO2 abundance in the system. CO2 in the headspace was enriched with 13C during the first 2 weeks (from −16.2 to −7.3 ‰) but then stayed around −11 ‰ un- til the end of the incubation. Total methanol concentrations (labeled and unlabeled) in the sediment decreased sharply in the first 2 weeks from ∼8 mM at day 1 to 0.5 mM at day 13 (Fig. 7). At day 17, methanol was below the detection limit. In the first 2 weeks, residual methanol was enriched with 13C, reaching ∼200 ‰ at day 13. J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone in September 2014) over time in the treatment with the addition of methanol (10 mM) are shown above. Shown are triplicate values per measurement. DNA copies of Archaea, Methanosarcinales, and Methanosarcinaceae are shown below in duplicates per measurement. Please note the secondary y axis for Methanosarcinales and Methanosarcinaceae. More data are avail- able for methane (determined in the gas headspace) than from DNA samples (taken from the sediment) as sample volume for molecular analyzes was limited. Figure 8. Sediment methane concentrations (with sediment from the 0–1 cm b.s.f. in September 2014) over time in the treatment with the addition of methanol (10 mM) are shown above. Shown are triplicate values per measurement. DNA copies of Archaea, Methanosarcinales, and Methanosarcinaceae are shown below in duplicates per measurement. Please note the secondary y axis for Methanosarcinales and Methanosarcinaceae. More data are avail- able for methane (determined in the gas headspace) than from DNA samples (taken from the sediment) as sample volume for molecular analyzes was limited. Figure 8. Sediment methane concentrations (with sediment from the 0–1 cm b.s.f. in September 2014) over time in the treatment with the addition of methanol (10 mM) are shown above. Shown are triplicate values per measurement. DNA copies of Archaea, Methanosarcinales, and Methanosarcinaceae are shown below in duplicates per measurement. Please note the secondary y axis for Methanosarcinales and Methanosarcinaceae. More data are avail- able for methane (determined in the gas headspace) than from DNA samples (taken from the sediment) as sample volume for molecular analyzes was limited. Figure 8. Sediment methane concentrations (with sediment from the 0–1 cm b.s.f. in September 2014) over time in the treatment with the addition of methanol (10 mM) are shown above. Shown are triplicate values per measurement. DNA copies of Archaea, Methanosarcinales, and Methanosarcinaceae are shown below in duplicates per measurement. Please note the secondary y axis for Methanosarcinales and Methanosarcinaceae. More data are avail- able for methane (determined in the gas headspace) than from DNA samples (taken from the sediment) as sample volume for molecular analyzes was limited. Figure 7. Development of headspace gas content and isotope com- position of methane (CH4) and carbon dioxide (CO2) as well as porewater methanol (CH3OH) concentration and isotope composi- tion during the 13C-labeling experiment (with sediment from the 0–2 cm b.s.f. horizon in September 2014) with the addition of 13C- enriched methanol (13C:12C = 1:1000). J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone (a) Concentrations of pore- water methanol (CH3OH) and headspace content of methane (CH4) and carbon dioxide (CO2) over time. (b) Isotope composition of porewater CH3OH, headspace CH4, and headspace CO2 over time. Shown are means (from triplicates) with standard deviation. 3.6 Statistical analysis steep increase between day 13 and day 20 and ending in a stationary phase. The PCA of integrated SRZ methanogenesis (0–5 cm b.s.f.; Fig. 10) showed a positive correlation with bottom water temperature (Fig. 10a), bottom water salinity (Fig. 10a), bot- tom water methane (Fig. 10b), surface sediment POC con- tent (0–5 cm b.s.f.; Fig. 10c), and surface sediment C / N (0– 5 cm b.s.f.; Fig. 10b). A negative correlation was found with bottom water oxygen concentration (Fig. 10b). No correla- tion was found with bottom water chlorophyll. A similar increase was seen in the abundance of to- tal and methanogenic Archaea. Total Archaea abundances increased sharply in the second week of the incubation, reaching a maximum at day 16 (∼5000 × 106 copies g−1), and stayed around 3000 × 106–4000 × 106 copies g−1 over the course of the incubation. Similarly, methanogenic ar- chaea, namely the order Methanosarcinales and within this order the family Methanosarcinaceae, showed a sharp in- crease in the first 2 weeks as well with the highest abun- dances at day 16 (∼6 × 108 and ∼1 × 106 copies g−1, re- spectively). Until the end of the incubation, the abundances of Methanosarcinales and Methanosarcinaceae decreased to about one-third of their maximum abundances (∼2 × 108 and ∼0.4 × 106 copies g−1, respectively). The PCA of methanogenesis depth profiles showed pos- itive correlations with sediment depth (Fig. 11a) and C / N (Fig. 11b), and it showed negative correlations with POC (Fig. 11a). 3.5 Molecular analysis of benthic methanogens Over the same time period, the methane content in the headspace increased from 2 ppmv at day 1 to ∼66 000 ppmv at day 17 and stayed around that value until the end of the total incubation time (until day 37; Fig. 7). The carbon iso- topic signature of methane (δ13CCH4) showed a clear en- richment of the heavier isotope 13C (Table 3) from day 9 to 17 (no methane was detectable at day 1). After day 17, δ13CCH4 stayed around 13 ‰ until the end of the incuba- tion. The content of CO2 in the headspace increased from ∼8900 ppmv at day 1 to ∼29 000 ppmv at day 20 and stayed around 30 000 ppmv until the end of the incubation (Fig. 7). In September 2014, additional samples were run during the methanol treatment (see Sect. 2.7.) for the detection of ben- thic methanogens via qPCR. The qPCR results are shown in Fig. 8. For a better comparison, the microbial abundances are plotted together with the sediment methane concentrations from the methanol treatment, from which the rate calculation for the methanol-methanogenesis at 0–1 cm b.s.f. was done (shown in Fig. 6). Sediment methane concentrations increased over time, re- vealing a slow increase in the first ∼10 days followed by a Biogeosciences, 15, 137–157, 2018 www.biogeosciences.net/15/137/2018/ J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 149 149 J. Maltby et al.: Microbial methanogenesis in the sulfate reducing zone 149 Figure 7. Development of headspace gas content and isotope com- position of methane (CH4) and carbon dioxide (CO2) as well as porewater methanol (CH3OH) concentration and isotope composi- tion during the 13C-labeling experiment (with sediment from the 0–2 cm b.s.f. horizon in September 2014) with the addition of 13C- enriched methanol (13C:12C = 1:1000). (a) Concentrations of pore- water methanol (CH3OH) and headspace content of methane (CH4) and carbon dioxide (CO2) over time. (b) Isotope composition of porewater CH3OH, headspace CH4, and headspace CO2 over time. Shown are means (from triplicates) with standard deviation. Figure 8. Sediment methane concentrations (with sediment from the 0–1 cm b.s.f. in September 2014) over time in the treatment with the addition of methanol (10 mM) are shown above. Shown are triplicate values per measurement. DNA copies of Archaea, Methanosarcinales, and Methanosarcinaceae are shown below in duplicates per measurement. Please note the secondary y axis for Methanosarcinales and Methanosarcinaceae. More data are avail- able for methane (determined in the gas headspace) than from DNA samples (taken from the sediment) as sample volume for molecular analyzes was limited. 3.6 Statistical analysis Figure 7. Development of headspace gas content and isotope com- position of methane (CH4) and carbon dioxide (CO2) as well as porewater methanol (CH3OH) concentration and isotope composi- tion during the 13C-labeling experiment (with sediment from the 0–2 cm b.s.f. horizon in September 2014) with the addition of 13C- enriched methanol (13C:12C = 1:1000). (a) Concentrations of pore- water methanol (CH3OH) and headspace content of methane (CH4) and carbon dioxide (CO2) over time. (b) Isotope composition of porewater CH3OH, headspace CH4, and headspace CO2 over time. Shown are means (from triplicates) with standard deviation. Figure 8. Sediment methane concentrations (with sediment from the 0–1 cm b.s.f. in September 2014) over time in the treatment with the addition of methanol (10 mM) are shown above. Shown are triplicate values per measurement. DNA copies of Archaea, Methanosarcinales, and Methanosarcinaceae are shown below in duplicates per measurement. Please note the secondary y axis for Methanosarcinales and Methanosarcinaceae. More data are avail- able for methane (determined in the gas headspace) than from DNA samples (taken from the sediment) as sample volume for molecular analyzes was limited. Figure 8. Sediment methane concentrations (with sediment from the 0–1 cm b.s.f. www.biogeosciences.net/15/137/2018/ J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone Temporal development of integrated net surface methano- genesis (0–5 cm b.s.f.) in the sediment and chlorophyll (green) and methane concentrations (orange) in the bottom water (25 m). Methanogenesis (MG) rates and methane concentrations are shown in means (from triplicates) with standard deviation. at Boknis Eck. Even though sulfate reduction activity was not directly determined, the decrease in sulfate concentra- tions with a concomitant increase in sulfide within the up- per 30 cm b.s.f. clearly indicated its presence (Figs. 2 and 3). Several previous studies confirmed the high activity of sul- fate reduction in the surface sediment of Eckernförde Bay, revealing rates up to 100–10 000 nmol cm−3 d−1 in the upper 25 cm b.s.f. (Treude et al., 2005a; Bertics et al., 2013; Dale et al., 2013). The microbial fermentation of organic matter was probably high in the organic-rich sediments of Eckernförde Bay (POC contents of around 5 %; Figs. 2 and 3), providing high substrate availability and variety for methanogenesis. . The addition of methanol to sulfate-rich sediments in- creased methanogenesis rates by up to 3 orders of mag- nitude, confirming the potential of the methanogenic community to utilize noncompetitive substrates, espe- cially in the 0–5 cm b.s.f. sediment horizon (Fig. 6). At this sediment depth either the availability of non- competitive substrates, including methanol, was high- est (derived from fresh organic matter), or the usage of noncompetitive substrates was increased due to the high competitive situation as sulfate reduction is most active in the 0–5 cm b.s.f. layer (Treude et al., 2005a; Bertics et al., 2013). It should be noted that even though methanogenesis rates were calculated assuming a linear increase in methane concentration over the entire incu- bation to make a better comparison between different treatments, the methanol treatments generally showed a delayed response in methane development (Figs. 8, S2). We suggest that this delayed response was a reflec- tion of cell growth by methanogens utilizing the surplus methanol. We are therefore unable to decipher whether methanol plays a major role as a substrate in the Eck- ernförde Bay sediments compared to possible alterna- tives, as its concentration is relatively low in the natural setting (∼1 µM between 0 and 25 cm b.s.f., June 2014 sampling; Zhuang, unpublished data). It is conceivable that other noncompetitive substrates, such as methy- lated sulfides (e.g., dimethyl sulfide or methanethiol), are more relevant for the support of SRZ methanogene- sis. J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 150 . The addition of BES did not result in the inhibition of methanogenesis, indicating the presence of unconven- tional methanogenic groups using noncompetitive sub- strates (Fig. 7). The unsuccessful inhibition by BES can be explained by either incomplete inhibition or the fact that the methanogens were insensitive to BES (Hoehler et al., 1994; Smith and Mah, 1981; Santoro and Konisky, 1987). The BES concentration applied in the present study (60 mM) has been shown to result in the successful inhibition of methanogens in previ- ous studies (Hoehler et al., 1994). Therefore, the pres- ence of methanogens that are insensitive to BES is more likely. The insensitivity to BES in methanogens is ex- plained by heritable changes in BES permeability or the formation of BES-resistant enzymes (Smith and Mah, 1981; Santoro and Konisky, 1987). Such BES resis- tance was found in Methanosarcina mutants (Smith and Mah, 1981; Santoro and Konisky, 1987). This genus was successfully detected in our samples (for more de- tails see point 5) and is known for mediating the methy- lotrophic pathway (Keltjens and Vogels, 1993), support- ing our hypothesis on the utilization of noncompetitive substrates by methanogens. 3. The addition of BES did not result in the inhibition of methanogenesis, indicating the presence of unconven- tional methanogenic groups using noncompetitive sub- strates (Fig. 7). The unsuccessful inhibition by BES can be explained by either incomplete inhibition or the fact that the methanogens were insensitive to BES (Hoehler et al., 1994; Smith and Mah, 1981; Santoro and Konisky, 1987). The BES concentration applied in the present study (60 mM) has been shown to result in the successful inhibition of methanogens in previ- ous studies (Hoehler et al., 1994). Therefore, the pres- ence of methanogens that are insensitive to BES is more likely. The insensitivity to BES in methanogens is ex- plained by heritable changes in BES permeability or the formation of BES-resistant enzymes (Smith and Mah, 1981; Santoro and Konisky, 1987). Such BES resis- tance was found in Methanosarcina mutants (Smith and Mah, 1981; Santoro and Konisky, 1987). This genus was successfully detected in our samples (for more de- tails see point 5) and is known for mediating the methy- lotrophic pathway (Keltjens and Vogels, 1993), support- ing our hypothesis on the utilization of noncompetitive substrates by methanogens. Figure 9. 4.1 Methanogenesis in the sulfate-reducing zone On the basis of the results presented in Figs. 2 and 3, it is evident that methanogenesis and sulfate reduction were con- currently active in the sulfate reduction zone (0–30 cm b.s.f.) www.biogeosciences.net/15/137/2018/ Biogeosciences, 15, 137–157, 2018 150 J. Maltby et Figure 9. Temporal development of integrated net surface methano- genesis (0–5 cm b.s.f.) in the sediment and chlorophyll (green) and methane concentrations (orange) in the bottom water (25 m). Methanogenesis (MG) rates and methane concentrations are shown in means (from triplicates) with standard deviation. 150 J. Maltby et www.biogeosciences.net/15/137/2018/ J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 151 J. Maltby et al.: Microbial methanogenesis in the sulfate reducing zone 151 e 10. Principal component analysis (PCA) from three different angles of integrated surface methanogenesis (0–5 cm b.s.f.) and surface ulate organic carbon averaged over 0–5 cm b.s.f. (surface sediment POC), surface C / N ratio averaged over 0–5 cm b.s.f. (surface ent C / N), bottom water salinity, bottom water temperature (T ), bottom water methane (CH4), bottom water oxygen (O2), and bottom chlorophyll. Data were transformed into ranks before analysis. (a) Correlation biplot of principal components 1 and 2, (b) correlation of principal components 1 and 3, and (c) correlation biplot of principal components 2 and 3. Correlation biplots are shown in a imensional space with parameters shown as green lines and samples shown as black dots. Parameters pointing in the same direction sitively related; parameters pointing in the opposite direction are negatively related. Figure 10. Principal component analysis (PCA) from three different angles of integrated surface methanogenesis (0–5 cm b.s.f.) and surface particulate organic carbon averaged over 0–5 cm b.s.f. (surface sediment POC), surface C / N ratio averaged over 0–5 cm b.s.f. (surface sediment C / N), bottom water salinity, bottom water temperature (T ), bottom water methane (CH4), bottom water oxygen (O2), and bottom water chlorophyll. Data were transformed into ranks before analysis. (a) Correlation biplot of principal components 1 and 2, (b) correlation biplot of principal components 1 and 3, and (c) correlation biplot of principal components 2 and 3. Correlation biplots are shown in a multidimensional space with parameters shown as green lines and samples shown as black dots. Parameters pointing in the same direction are positively related; parameters pointing in the opposite direction are negatively related. 6. Stable isotope probing revealed highly 13C-enriched methane produced from 13C-labeled methanol, further confirming the potential of the methanogenic commu- nity to utilize noncompetitive substrates (Fig. 7). The production of both methane and CO2 from methanol has been shown previously in different strains of methy- 6. Stable isotope probing revealed highly 13C-enriched methane produced from 13C-labeled methanol, further confirming the potential of the methanogenic commu- nity to utilize noncompetitive substrates (Fig. 7). The production of both methane and CO2 from methanol has been shown previously in different strains of methy- ment (Fig. J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 8), confirming the presence of methanogens that utilize noncompetitive substrates in the natural environment (Boone et al., 1993; Fig. 8). The delay in the growth of Methanosarcinales moreover hints towards the predominant usage of noncompetitive substrates other than methanol (see also point 4). J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone The results of this study further identified methylotrophy to be a potentially important noncompetitive methanogenic pathway in the sulfate-reducing zone. The pathway utilizes alternative substrates, such as methanol, to bypass compe- tition with sulfate reducers for H2 and acetate. The poten- tial for methylotrophic methanogenesis within the sulfate- reducing zone was supported by the following observations. 1. Hydrogenotrophic methanogenesis was up to 2 orders of magnitude lower compared to net methanogenesis, resulting in insufficient rates to explain the observed net methanogenesis in the upper 0–30 cm b.s.f. (Figs. 2 and 3). This finding points towards the presence of alter- native methanogenic processes in the sulfate reduction zone, such as methylotrophic methanogenesis. 2. Methanogenesis increased when sulfate reduction was inhibited by molybdate, confirming the inhibitory effect of sulfate reduction on methanogenesis with competi- tive substrates (H2 and acetate; Oremland and Polcin, 1982; King et al., 1983; Fig. 6). Consequently, the usage of noncompetitive substrates was preferred in the sulfate reduction zone (especially in the upper 0–1 cm b.s.f.; Fig. 6). Accordingly, hydrogenotrophic methanogenesis increased at depths at which sulfate was depleted and thus the competitive situation was relieved (Fig. 4). 5. Methylotrophic methanogens of the order Methanosarcinales were detected in the methanol treat- 5. Methylotrophic methanogens of the order Methanosarcinales were detected in the methanol treat- www.biogeosciences.net/15/137/2018/ Biogeosciences, 15, 137–157, 2018 J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 152 Figure 11. Principal component analysis (PCA) from two different angles of net methanogenesis depth profiles and sampling month (Month), sediment depth, and depth profiles of particulate organic carbon (POC) and C / N ratio (C / N). Data were transformed into ranks before analysis. (a) Correlation biplot of principal compo- nents 1 and 2 and (b) correlation biplot of principal components 1 and 3. Correlation biplots are shown in a multidimensional space with parameters shown as green lines and samples shown as black dots. Parameters pointing in the same direction are positively re- lated; parameters pointing in the opposite direction are negatively related. lotrophic methanogens (Penger et al., 2012). The fast conversion of methanol to methane and CO2 (methanol was consumed completely in 17 days) hints towards the presence of methylotrophic methanogens (e.g., mem- bers of the family Methanosarcinaceae, which is known for the methylotrophic pathway; Keltjens and Vogels, 1993). Please note, however, that the storage of the cores (3.5 months) prior to sampling could have led to shifts in the microbial community and thus might not reflect the in situ conditions of the original microbial community in September 2014. The delay in methane production also seen in the stable isotope experiment was, however, only slightly different (methane devel- oped earlier between day 8 and 12; data not shown) from the non-labeled methanol treatment (between day 10 and 16; Fig. S2), which leads us to the assumption that the storage time at 1 ◦C did not dramatically affect the methanogen community. Similar to a previous study with arctic sediments, the addition of substrates had no stimulatory effect on the rate of methanogenesis or on the methanogen community structure at low tempera- tures (5 ◦C; Blake et al., 2015). 4.2.1 Temperature During the sampling period, bottom water temperatures in- creased over the course of the year from late winter (March, 3–4 ◦C) to autumn (November, 12 ◦C; Figs. 2 and 3). The PCA revealed a positive correlation between bottom wa- ter temperature and integrated SRZ methanogenesis (0– 5 cm b.s.f.). A temperature experiment conducted with sed- iment from ∼75 cm b.s.f. in September 2014 within a par- allel study revealed a mesophilic temperature optimum of methanogenesis (20 ◦C; data not shown). Whether methano- genesis in the sulfate reduction zone (0–30 cm) has the same physiology remains speculative. However, AOM organ- isms, which are closely related to methanogens (Knittel and Boetius, 2009), studied in the sulfate reduction zone from the same site were confirmed to have a mesophilic physi- ology, too (Treude et al., 2005a). The sum of these aspects leads us to the conceivable conclusion that SRZ methanogen- esis activity in the Eckernförde Bay is positively impacted by temperature increases. Such a correlation between ben- thic methanogenesis and temperature has been found in sev- eral previous studies from different environments (Sansone and Martens, 1981; Crill and Martens, 1983; Martens and Klump, 1984). 4.2 Environmental control of methanogenesis in the sulfate reduction zone Figure 11. Principal component analysis (PCA) from two different angles of net methanogenesis depth profiles and sampling month (Month), sediment depth, and depth profiles of particulate organic carbon (POC) and C / N ratio (C / N). Data were transformed into ranks before analysis. (a) Correlation biplot of principal compo- nents 1 and 2 and (b) correlation biplot of principal components 1 and 3. Correlation biplots are shown in a multidimensional space with parameters shown as green lines and samples shown as black dots. Parameters pointing in the same direction are positively re- lated; parameters pointing in the opposite direction are negatively related. SRZ methanogenesis in Eckernförde Bay sediments showed variations throughout the sampling period, which may be in- fluenced by variable environmental factors such as tempera- ture, salinity, oxygen, and organic carbon. In the following, we will discuss the potential impact of those factors on the magnitude and distribution of SRZ methanogenesis. www.biogeosciences.net/15/137/2018/ Biogeosciences, 15, 137–157, 2018 J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 4.2.5 Effect of POC and C / N ratio over 0–30 cm b.s.f. In the PCA for the sediment profiles from the sulfate reduc- tion zone (0–30 cm b.s.f.), POC showed a negative correla- tion with methanogenesis and sediment depth, while C / N ratio showed a positive correlation with methanogenesis and sediment depth (Fig. 11). Given that POC remained basi- cally unchanged over the top 30 cm b.s.f. with the exception of the topmost sediment layer, its negative correlation with methanogenesis is probably solely explained by the increase in methanogenesis with sediment depth and can therefore be excluded as a major controlling factor. As sulfate in this zone was likely never depleted to levels that critically limit sul- fate reduction (lowest concentration 1300 µM; compare with Treude et al., 2014), we do not expect a significant change in the competition between methanogens and sulfate reducers. It is therefore more likely that the progressive degradation of labile POC into dissolvable methanogenic substrates over depth and time had a positive impact on methanogenesis. The C / N ratio indicates such a trend as the labile fraction of POC decreased with depth. To determine the effect of POC concentration and C / N ra- tio (the latter as a negative indicator for the freshness of POC) on SRZ methanogenesis, two PCAs were conducted with (a) the focus on the upper 0–5 cm b.s.f., which is directly in- fluenced by freshly sedimented organic material from the wa- ter column (Fig. 10), and (b) the focus on the depth profiles throughout the sediment cores (up to 30 cm b.s.f.; Fig. 11). J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone a positive correlation between integrated SRZ methanogen- esis rates and bottom-near water methane concentrations (Fig. 10b) when viewed over all investigated months. How- ever, no correlation was found between bottom water chloro- phyll and integrated SRZ methanogenesis rates (Fig. 10). As seen in Fig. 9, bottom-near high chlorophyll concentra- tions did not coincide with high bottom-near methane con- centration in June–September 2014. We explain this result by a time lag between primary production in the water col- umn and the export of the produced organic material to the seafloor, which was probably even more delayed during strat- ification. Such a delay was observed in a previous study (Bange et al., 2010), revealing an enhanced water methane concentration close to the seafloor approximately 1 month after the chlorophyll maximum. The C / N ratio (averaged over 0–5 cm b.s.f.) also showed no correlation with integrated methanogenesis from the same depth layer (0–5 cm b.s.f.), which is surprising as we expected that a higher C / N ra- tio indicative of less labile organic carbon would have a negative effect on noncompetitive methanogenesis. However, methanogens are not able to directly use most of the labile or- ganic matter due to their inability to process large molecules (more than two C–C bondings; Zinder, 1993). Methanogens are dependent on other microbial groups to degrade large or- ganic compounds (e.g., amino acids) for them (Zinder, 1993). Because of this substrate speciation and dependence, a de- lay between the sedimentation of fresh, labile organic matter and the increase in methanogenesis can be expected, which would not be captured by the applied PCA. ter column stratification, which is often correlated with low O2 concentrations in the Eckernförde Bay (Fig. S3, Bange et al., 2011; Bertics et al., 2013). Methanogenesis is sensitive to O2 (Oremland, 1988; Zinder, 1993), and hence conditions might be more favorable during hypoxic or anoxic events, particularly in the sediment closest to the sediment–water in- terface, but potentially also in deeper sediment layers due to the absence of bioturbating and bioirrigating infauna (Dale et al., 2013; Bertics et al., 2013), which could introduce O2 beyond diffusive transport. Accordingly, the PCA revealed a negative correlation between O2 concentration close to the seafloor and SRZ methanogenesis. 4.2.3 Particulate organic carbon The supply of particulate organic carbon (POC) is one of the most important factors controlling benthic heterotrophic processes, as it determines substrate availability and variety (Jørgensen, 2006). In Eckernförde Bay, the organic mate- rial reaching the seafloor originates mainly from phytoplank- ton blooms in spring, summer, and autumn (Bange et al., 2011). It has been estimated that > 50 % in spring (February– March), < 25 % in summer (July–August), and > 75 % in au- tumn (September–October) of these blooms is reaching the seafloor (Smetacek et al., 1984), resulting in an overall high organic carbon content of the sediment (5 wt %), which leads to high benthic microbial degradation rates including sul- fate reduction and methanogenesis (Whiticar, 2002; Treude et al., 2005a; Bertics et al., 2013). Previous studies revealed that high organic matter availability can relieve competi- tion between sulfate reducers and methanogens in sulfate- containing marine sediments (Oremland et al., 1982; Holmer and Kristensen, 1994; Treude et al., 2009; Maltby et al., 2016). 4.2.5 Effect of POC and C / N ratio over 0–30 cm b.s.f. 4.2.2 Salinity and oxygen From March 2013 to November 2013 and from March 2014 to September 2014, salinity increased in the bottom-near wa- ter (25 m) from 19 to 23 and from 22 to 25 PSU (Figs. 2 and 3), respectively, due the pronounced summer stratifica- tion in the water column between saline North Sea water and less saline Baltic Sea water (Bange et al., 2011). The PCA detected a positive correlation between integrated SRZ methanogenesis (0–5 cm b.s.f.) and salinity in the bottom- near water (Fig. 10a). This correlation can hardly be ex- plained by salinity alone, as methanogens feature a broad salinity range from freshwater to hypersaline (Zinder, 1993). It is more likely that salinity serves as an indicator of wa- Biogeosciences, 15, 137–157, 2018 www.biogeosciences.net/15/137/2018/ 153 4.2.4 Effect of POC and C / N ratio in the upper 0–5 cm b.s.f. For the upper 0–5 cm b.s.f. in the sediment, a positive corre- lation was found between SRZ methanogenesis (integrated) and POC content (averaged; Fig. 10c), indicating that POC content is an important controlling factor for methanogen- esis in this layer. In support, the highest bottom-near wa- ter chlorophyll concentrations coincided with the highest bottom-near water methane concentrations and high inte- grated SRZ methanogenesis (0–5 cm b.s.f.) in September 2013, probably as a result of the sedimentation of the sum- mer phytoplankton bloom (Fig. 9). Indeed, the PCA revealed Biogeosciences, 15, 137–157, 2018 5 Summary The present study demonstrated that methanogenesis and sul- fate reduction were concurrently active within the sulfate- reducing zone in sediments at Boknis Eck (Eckernförde Bay, SW Baltic Sea). The observed methanogenesis was proba- bly based on noncompetitive substrates due to the competi- tion with sulfate reducers for the substrates H2 and acetate. Accordingly, members of the family Methanosarcinaceae, which are known for methylotrophic methanogenesis, were found in the sulfate reduction zone of the sediments and are likely to be responsible for the observed methanogene- sis with the potential use of noncompetitive substrates such as methanol, methylamines, or methylated sulfides. How much of the methane produced in the surface sed- iment is ultimately emitted into the water column depends on the rate of methane consumption, i.e., the aerobic and anaerobic oxidation of methane in the sediment (Knittel and Boetius, 2009; Fig. 1). In organic-rich sediments, such as in the present study, the oxygenated sediment layer is of- ten only millimeters thick due to the high O2 demand of mi- croorganisms during organic matter degradation (Jørgensen, 2006; Preisler et al., 2007). Thus, the anaerobic oxidation of methane (AOM) might play a more important role for methane consumption in the studied Eckernförde Bay sed- iments. In an earlier study from this site, AOM activity was detected throughout the top 0–25 cm b.s.f., which in- cluded zones that were well above the actual SMTZ (Treude et al., 2005a). But the authors concluded that methane oxidation was completely fueled by methanogenesis from below sulfate penetration, as integrated AOM rates (0.8– 1.5 mmol m−2 d−1) were in the same range as the predicted methane flux (0.66–1.88 mmol m−2 d−1) into the SMTZ. Potential environmental factors controlling SRZ methano- genesis are POC content, C / N ratio, oxygen, and tempera- ture, resulting in the highest methanogenesis activity during the warm, stratified, and hypoxic months after the late sum- mer phytoplankton blooms. This study provides new insights into the presence and seasonality of SRZ methanogenesis in coastal sediments and was able to demonstrate that the process could play an im- portant role for the methane budget and carbon cycling of Eckernförde Bay sediments, for example by directly fueling AOM above the SMTZ. Data availability. Research data for the present study can be accessed via the public data repository PANGEA (https://doi.org/10.1594/PANGAEA.873185, Maltby et al., 2017). 5 Summary Together with the dataset presented here we postulate that AOM above the SMTZ (0.8 mmol m−2 d−1; Treude et al., 2005a) could be partially or entirely fueled by SRZ methano- genesis. A similar close coupling between methane oxida- tion and methanogenesis in the absence of definite methane profiles was recently proposed from isotopic labeling exper- iments with sediments from the sulfate reduction zone of the nearby Aarhus Bay in Denmark (Xiao et al., 2017). It is therefore likely that such a cryptic methane cycling also occurs in the sulfate reduction zone of sediments in the Eck- ernförde Bay. If, in an extreme scenario, SRZ methanogen- esis represented the only methane source for AOM above the SMTZ, then maximum SRZ methanogenesis could be on www.biogeosciences.net/15/137/2018/ J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 154 the order of 1.6 mmol m−2 d−1 (1.5 mmol m−2 d−1 AOM + 0.09 mmol m−2 d−1 net SRZ methanogenesis). 4.3 Relevance of methanogenesis in the sulfate reduction zone of Eckernförde Bay sediments Even though the contribution of SRZ methanogenesis to AOM above the SMTZ remains speculative, it leads to the as- sumption that SRZ methanogenesis could play a much bigger role for benthic carbon cycling in the Eckernförde Bay than previously thought. Whether SRZ methanogenesis at Eckern- förde Bay has the potential for the direct emission of methane into the water column goes beyond the scope of this study and should be tested in the future. The time series station Boknis Eck in Eckernförde Bay is known for being a methane source to the atmosphere throughout the year due to supersaturated waters, which result from significant benthic methanogenesis and emis- sion (Bange et al., 2010). The benthic methane formation is thought to take place mainly in sediments below the SMTZ (Treude et al., 2005a; Whiticar, 2002). In the present study, we show that SRZ methanogenesis within the sulfate zone is present despite sulfate concen- trations > 1 mM, a limit above which methanogenesis has been thought to be negligible (Alperin et al., 1994; Hoehler et al., 1994; Burdige, 2006), and could thus contribute to benthic methane emissions. In support of this hypothesis, a high dissolved methane concentration in the water column occurred with concomitantly high SRZ methanogenesis ac- tivity (Fig. 9). However, whether the observed water col- umn methane originated from SRZ methanogenesis, from gas ebullition caused by methanogenesis below the SMTZ, or a mixture of both remains speculative. The Supplement related to this article is available online at https://doi.org/10.5194/bg-15-137-2018-supplement. Author contributions. JM and TT designed the experiments. JM carried out all experiments. HWB coordinated measurements of water column methane and chlorophyll. CRL and MAF conducted molecular analysis. MS coordinated 13C-isotope measurements. JM prepared the paper with contributions from all coauthors. Biogeosciences, 15, 137–157, 2018 www.biogeosciences.net/15/137/2018/ References Dale, A. W., Bertics, V. J., Treude, T., Sommer, S., and Wallmann, K.: Modeling benthic-pelagic nutrient exchange processes and porewater distributions in a seasonally hypoxic sediment: ev- idence for massive phosphate release by Beggiatoa?, Biogeo- sciences, 10, 629–651, https://doi.org/10.5194/bg-10-629-2013, 2013. Abegg, F. and Anderson, A. L.: The acoustic turbid layer in muddy sediments of Eckernfoerde Bay, Western Baltic?: methane con- centration, saturation and bubble characteristics, Mar. Geol., 137, 137–147, 1997. Alperin, M. J., Albert, D. B., and Martens, C. S.: Seasonal variations in production and consumption rates of dissolved organic carbon in an organic-rich coastal sediment, Geochim. Cosmochim. Ac., 58, 4909–4930, 1994. Denman, K. L., Brasseur, G., Chidthaisong, A., Ciais, P., Cox, P. M., Dickinson, R. E., Hauglustaine, D., Heinze, C., Holland, E., Jacob, D., Lohmann, U., Ramachandran, S., da Silva Dias, P. L., Wofsy, S. C., and Zhang, X.: Couplings Between Changes in the Climate System and Biogeochemistry, in: Climate Change 2007: The Physical Science Basis, Contribution of Wokring Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge, United Kingdom and New York, NY, USA, Cambridge University Press, 2007. Bakker, D. E., Bange, H. W., Gruber, N., Johannessen, T., Upstill- Goddard, R. C., Borges, A. V., Delille, B., Löscher, C. R., Naqvi, S. W. A., Omar, A. M., and Santana-Casiano, J. M.: Air-sea in- teractions of natural long-lived greenhouse gases (CO2, N2O, CH4) in a changing climate, in: Ocean-Atmosphere Interactions of Gases and Particles, edited by: Liss, P. S. and Johnson, M. T., Heidelberg: Springer-Verlag, 113–169, 2014. Balzer, W., Pollehne, F., and Erlenkeuser, H.: Cycling of Organic Carbon in a Marine Coastal System, in: Sediments and Water Interactions, edited by: Sly, P. G., New York, NY, Springer New York, 325–330, 1986. EPA: Methane and nitrous oxide emissions from natural sources, Washington, DC, USA, 2010. Ferdelman, T. G., Lee, C., Pantoja, S., Harder, J., Bebout, B. M., and Fossing, H.: Sulfate reduction and methanogenesis in a Thioploca-dominated sediment off the coast of Chile, Geochim. Cosmochim. Ac., 61, 3065–3079, 1997. Bange, H. W., Bartell, U. H., Rapsomanikis, S., and Andreae, M. O.: Methane in the Baltic and North Seas and a reassessment of the marine emissions of methane, Global Biogeochem. Cy., 8, 465–480, 1994. Gier, J., Sommer, S., Löscher, C. R., Dale, A. J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 155 Bange, H. W., Hansen, H. P., Malien, F., Laß, K., Karstensen, J., Petereit, C., Friedrichs, G., and Dale, A.: Boknis Eck Time Se- ries Station (SW Baltic Sea): Measurements from 1957 to 2010, LOICZ-Affiliated Activities, Inprint 20, 16–22, 2011. Competing interests. The authors declare that they have no conflict of interest. Bertics, V. J., Löscher, C. R., Salonen, I., Dale, A. W., Gier, J., Schmitz, R. A., and Treude, T.: Occurrence of benthic micro- bial nitrogen fixation coupled to sulfate reduction in the season- ally hypoxic Eckernförde Bay, Baltic Sea, Biogeosciences, 10, 1243–1258, https://doi.org/10.5194/bg-10-1243-2013, 2013. Acknowledgements. We thank the captain and crew of RV Alkor, RV Littorina, and RV Polarfuchs for field assistance. We thank Gabriele Schüssler, Fynn Wulff, Peggy Wefers, Asmus Pe- tersen, Maik Lange, and Florian Evers for field and laboratory assistance. For the geochemical analysis we want to thank Bet- tina Domeyer, Anke Bleyer, Ulrike Lomnitz, Regina Suhrberg, and Verena Thoenissen. We thank Frank Malien, Xiao Ma, Annette Kock, and Tina Baustian for the O2, CH4, and chlorophyll measurements from the regular monthly Boknis Eck sampling cruises. Further, we thank Ralf Conrad and Peter Claus at the MPI Marburg for the 13C-methanol measurements. This study received financial support through the Cluster of Excellence “The Future Ocean” funded by the German Research Foundation through the Sonderforschungsbereich (SFB) 754 and through a D-A-CH project funded by the Swiss National Science Foundation and the German Research Foundation (grant nos. 200021L_138057, 200020_159878/1). Further support was provided through the EU COST Action PERGAMON (ESSEM 0902), the BMBF project BioPara (grant no. 03SF0421B), and the EU H2020 program (Marie Curie grant NITROX # 704272 to CRL). Blake, L. I., Tveit, A., Øvreås, L., Head, I. M., and Gray, N. D.: Response of Methanogens in Arctic Sediments to Temperature and Methanogenic Substrate Availability, Planet. Space Sci., 10, 1–18, 2015. Boone, D. R., Whitman, W. B., and Rouvière, P.: Diversity and Tax- onomy of Methanogens, in: Methanogenesis, edited by: Ferry, J. G., Springer US, 35–81, 1993. Buckley, D. H., Baumgartner, L. K., and Visscher, P. T.: Vertical distribution of methane metabolism in microbial mats of the Great Sippewissett Salt Marsh, Environ. Microbiol., 10, 967– 977, 2008. Burdige, D. J.: Geochemistry of Marine Sediments, New Jersey, USA, Princeton University Press, 2006. Cicerone, R. J. and Oremland, R. S.: Biogeochemical aspects of at- mospheric methane, Global Biogeochem. Cy., 2, 299–327, 1988. Crill, P. J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone and Martens, C.: Spatial and temporal fluctuations of methane production in anoxic coastal marine sediments, Limnol. Oceanogr., 28, 1117–1130, 1983. Edited by: Sébastien Fontaine Reviewed by: two anonymous referees Crill, P. M. and Martens, C. S.: Methane production from bicar- bonate and acetate in an anoxic marine sediment, Geochim. Cos- mochim. Ac., 50, 2089–2097, 1986. www.biogeosciences.net/15/137/2018/ www.biogeosciences.net/15/137/2018/ J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone S., Marsh, L. M., and Polcin, S.: Methane produc- tion and simultanous sulfate reduction in anoxic, salt-marsh sed- iments, Nature, 286, 143–145, 1982. Jackson, D. R., Williams, K. L., Wever, T. F., Friedrichs, C. T., and Wright, L. D.: Sonar evidence for methane ebullition in Eckern- forde Bay, Cont. Shelf Res., 18, 1893–1915, 1998. Orsi, T. H., Werner, F., Milkert, D., Anderson, A. L., and Bryant, W. R.: Environmental overview of Eckernförde Bay, northern Ger- many, Geo-Mar. Lett., 16, 140–147, 1996. Jørgensen, B. B.: Bacteria and marine Biogeochemistry, in: Ma- rine Geochemistry, edited by: Schulz, H. D. and Zabel, M., Berlin/Heidelberg: Springer-Verlag, 173–207, 2006. Penger, J., Conrad, R., and Blaser, M.: Stable carbon isotope frac- tionation by methylotrophic methanogenic archaea, Appl. Envi- ron. Microb., 78, 7596–602, 2012. Jørgensen, B. B. and Parkes, R. J.: Role of sulfate reduction and methane production by organic carbon degradation in eutrophic fjord sediments (Limfjorden, Denmark), Limnol. Oceanogr., 55, 1338–1352, 2010. Pimenov, N., Davidova, I., Belyaev, S., Lein, A., and Ivanov, M.: Microbiological processes in marine sediments in the Zaire River Delta and the Benguela upwelling region, Geomicrobiol. J., 11, 157–174, 1993. Keltjens, J. T. and Vogels, G. D.: Conversion of methanol and methylamines to methane and carbon dioxide, in: Methanogene- sis: Ecology, Physiology, Biochemistry, and Genetics, edited by: Ferry, J. G., Chapman, and Hall, 253–303, 1993. Preisler, A., de Beer, D., Lichtschlag, A., Lavik, G., Boetius, A., and Jørgensen, B. B.: Biological and chemical sulfide oxidation in a Beggiatoa inhabited marine sediment, ISME J., 1, 341–353, 2007. King, G. M., Klug, M. J., and Lovley, D. R.: Metabolism of acetate, methanol, and methylated amines in intertidal sediments of lowes cove, maine, Appl. Environ. Microb., 45, 1848–1853, 1983. Reeburgh, W.: Oceanic methane biogeochemistry, Chemical Rev., 107, 486–513, 2007. Knittel, K. and Boetius, A.: Anaerobic oxidation of methane: progress with an unknown process, Annu. Rev. Microbiol., 63, 311–334, 2009. Sansone, F. J. and Martens, C. S.: Methane Production from Acetate and Associated Methane Fluxes from Anoxic Coastal Sediments, Science, 211, 707–709, 1981. Lennartz, S. T., Lehmann, A., Herrford, J., Malien, F., Hansen, H.- P., Biester, H., and Bange, H. W.: Long-term trends at the Bok- nis Eck time series station (Baltic Sea), 1957–2013: does cli- mate change counteract the decline in eutrophication?, Biogeo- sciences, 11, 6323–6339, https://doi.org/10.5194/bg-11-6323- 2014, 2014. Santoro, N. J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 156 for sediments dominated by sulfate reduction and methanogene- sis, Geochim. Cosmochim. Ac., 48, 1987–2004, 1984. for sediments dominated by sulfate reduction and methanogene- sis, Geochim. Cosmochim. Ac., 48, 1987–2004, 1984. Grasshoff, K., Ehrhardt, M., and Kremmling, K.: Methods of Sea- water Analysis, Weinheim, Verlag Chemie, 1999. Martens, C. S., Albert, D. B., and Alperin, M. J.: Biogeochemical processes controlling methane in gassy coastal sediments – Part 1. A model coupling organic matter flux to gas production, oxi- dation and transport, Cont. Shelf Res., 18, 14–15, 1998. Hansen, H.-P., Giesenhagen, H. C., and Behrends, G.: Seasonal and long-term control of bottom-water oxygen deficiency in a strati- fied shallow-water coastal system, ICES J. Mar. Sci., 56, 65–71, 1999. Naqvi, S. W. A., Bange, H. W., Farías, L., Monteiro, P. M. S., Scranton, M. I., and Zhang, J.: Marine hypoxia/anoxia as a source of CH4 and N2O, Biogeosciences, 7, 2159–2190, https://doi.org/10.5194/bg-7-2159-2010, 2010. Hartmann, D. L., Klein Tank, A. M. G., Rusticucci, M., Alexander, L. V., Brönnimann, S., Charabi, Y., Dentener, F. J., Dlugokencky, Hartmann, D. L., Klein Tank, A. M. G., Rusticucci, M., Alexander, L. V., Brönnimann, S., Charabi, Y., Dentener, F. J., Dlugokencky, D. R., Easterling, D. R., Kaplan, A., Soden, B. J., Thorne, P. W., Wild, M., and Zhai, P. M.: Observations: Atmosphere and Surface, in: Climate Change 2013: The pHysical Science Basis, Contribution Group I to the Fifth Assessment Report of the In- tergovernmental Panel on Climate Change, United Kingdom and New York, NY, USA, Cambridge University Press, 2013. Oremland, R. S.: Biogeochemistry of methanogenic bacteria, in: Bi- ology of Anaerobic Microorganisms, edited by: Zehnder, A. J. B., New York, J. Wiley, and Sons, 641–705, 1988. Oremland, R. S. and Capone, D. G.: Use of specific inhibitors in biogeochemistry and microbial ecology, in: Advances in Micro- bial Ecology, edited by: Marshall, K. C., Advances in Microbial Ecology, Boston, MA, Springer US, 285–383, 1988. Hoehler, T. M., Alperin, M. J., Albert, D. B., and Martens, C. S.: Field and laboratory studies of methane oxidation in an anoxic marine sediment: Evidence for a methanogen-sulfate reducer consortium, Global Biogeochem. Cy., 8, 451–463, 1994. Oremland, R. S. and Polcin, S.: Methanogenesis and Sulfate Reduc- tion?: Competitive and Noncompetitive Substrates in Estuarine Sediments, Appl. Environ. Microbiol., 44, 1270–1276, 1982. Holmer, M. and Kristensen, E.: Coexistence of sulfate reduction and methane production in an organic-rich sediment, Mar. Ecol.- Prog. Ser., 107, 177–184, 1994. Oremland, R. References W., Schmitz, R. A., and Treude, T.: Nitrogen fixation in sediments along a depth transect through the Peruvian oxygen minimum zone, Biogeosciences, 13, 4065–4080, https://doi.org/10.5194/bg-13- 4065-2016, 2016. Bange, H. W., Bergmann, K., Hansen, H. P., Kock, A., Koppe, R., Malien, F., and Ostrau, C.: Dissolved methane during hy- poxic events at the Boknis Eck time series station (Eckern- förde Bay, SW Baltic Sea), Biogeosciences, 7, 1279–1284, https://doi.org/10.5194/bg-7-1279-2010, 2010. Biogeosciences, 15, 137–157, 2018 www.biogeosciences.net/15/137/2018/ J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone 157 Welschmeyer, N. A.: Fluorometric analysis of chlorophyll a in the presence of chlorophyll b and pheopigments, Limnol. Oceanogr., 39, 1985–1992, 1994. Rapports et Proces-Verbaux des Reunions Conseil International pour l’Exploration de la Mer, 186, 126–135, 1984. Smith, M. R. and Mah, R. A.: 2-Bromoethanesulfonate: A selec- tive agent for isolating resistantMethanosarcina mutants, Curr. Microbiol., 6, 321–326, 1981. Wever, T. F. and Fiedler, H. M.: Variability of acoustic turbidity in Eckernförde Bay (southwest Baltic Sea) related to the annual temperature cycle, Mar. Geol., 125, 21–27, 1995. Steinle, L., Maltby, J., Treude, T., Kock, A., Bange, H. W., Eng- bersen, N., Zopfi, J., Lehmann, M. F., and Niemann, H.: Effects of low oxygen concentrations on aerobic methane oxidation in seasonally hypoxic coastal waters, Biogeosciences, 14, 1631– 1645, https://doi.org/10.5194/bg-14-1631-2017, 2017. Wever, T. F., Abegg, F., Fiedler, H. M., Fechner, G., and Stender, I. H.: Shallow gas in the muddy sediments of Eckernförde Bay, Germany, Cont. Shelf Res., 18, 1715–1739, 1998. Germany, Cont. Shelf Res., 18, 1715–1739, 1998. Whiticar, M. J.: Diagenetic relationships of methanogenesis, nutri- ents, acoustic turbidity, pockmarks and freshwater seepages in Eckernförde Bay, Mar. Geol., 182, 29–53, 2002. Thießen, O., Schmidt, M., Theilen, F., Schmitt, M., and Klein, G.: Methane formation and distribution of acoustic turbidity in organic-rich surface sediments in the Arkona Basin, Baltic Sea, Cont. Shelf Res., 26, 2469–2483, 2006. Widdel, F. and Bak, F.: Gram-Negative Mesophilic Sulfate- Reducing Bacteria, in: The Prokaryotes, edited by: Balows, A., Trüper, H. G., Dworkin, M., Harder, W., and Schleifer, K.-H., New York, NY, Springer New York, 3352–3378, 1992. Treude, T., Krause, S., Maltby, J., Dale, A. W., Coffin, R., and Ham- dan, L. J.: Sulfate reduction and methane oxidation activity be- low the sulfate-methane transition zone in Alaskan Beaufort Sea continental margin sediments: Implications for deep sulfur cy- cling, Geochim. Cosmochim. Ac., 144, 217–237, 2014. Wuebbles, D. J. and Hayhoe, K.: Atmospheric methane and global change, Earth-Sci. Rev., 57, 177–210, 2002. Xiao, K. Q., Beulig, F., Kjeldsen, K. U., Jørgensen, B. B., and Risgaard-Petersen, N.: Concurrent methane production and ox- idation in surface sediment from Aarhus Bay, Denmark, Front. Microbiol., 1–12, 2017. Treude, T., Krüger, M., Boetius, A., and Jørgensen, B. B.: En- vironmental control on anaerobic oxidation of methane in the gassy sediments of Eckernförde Bay (German Baltic), Limnol. Oceanogr., 50, 1771–1786, 2005a. J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone and Konisky, J.: Characterization of bromoethanesulfonate-resistant mutants of Methanococcus voltae: Evidence of a coenzyme M transport system, J. Bacte- riol., 169, 660–665, 1987. Schlüter, M., Sauter, E., Hansen, H.-P., and Suess, E.: Seasonal vari- ations of bioirrigation in coastal sediments: modelling of field data, Geochim. Cosmochim. Ac., 64, 821–834, 2000. Maltby, J., Sommer, S., Dale, A. W., and Treude, T.: Microbial methanogenesis in the sulfate-reducing zone of surface sedi- ments traversing the Peruvian margin, Biogeosciences, 13, 283– 299, https://doi.org/10.5194/bg-13-283-2016, 2016. Seeberg-Elverfeldt, J., Schluter, M., Feseker, T., and Kolling, M.: Rhizon sampling of porewaters near the sediment-water inter- face of aquatic systems, Limnol. Oceanogr.-Methods, 3, 361– 371, 2005. Maltby, J., Steinle, L., Löscher, C. R., Bange, H. W., Fischer, M. A., Schmidt, M., and Treude, T.: Sediment and water column param- eters measured at Boknis Eck (SW Baltic Sea) on a seasonal basis from 2013–2014, https://doi.org/10.1594/PANGAEA.873185, 2017. Smetacek, V.: The Annual Cycle of Kiel Bight Plankton: A Long- Term Analysis, Estuaries, 8, 145–157, 1985. Smetacek, V., von Bodungen, B., Knoppers, B., Peinert, R., Pollehne, F., Stegmann, P., and Zeitzschel, B.: Seasonal stages characterizing the annual cycle of an inshore pelagic system, Martens, C. S. and Klump, J. V.: Biogeochemical cycling in an organic-rich coastal marine basin 4. An organic carbon budget Biogeosciences, 15, 137–157, 2018 www.biogeosciences.net/15/137/2018/ J. Maltby et al.: Microbial methanogenesis in the sulfate-reducing zone Yu, Y., Lee, C., Kim, J., and Hwang, S.: Group-specific primer and probe sets to detect methanogenic communities using quantita- tive real-time polymerase chain reaction, Biotechnol. Bioeng., 89, 670–679, 2005. Treude, T., Niggemann, J., Kallmeyer, J., Wintersteller, P., Schubert, C. J., Boetius, A., and Jørgensen, B. B.: Anaerobic oxidation of methane and sulfate reduction along the Chilean continental mar- gin, Geochim. Cosmochim. Ac., 69, 2767–2779, 2005b. Zinder, S. H.: Physiological ecology of methanogens, in: Methano- genesis, edited by: Ferry, J. G., New York, NY: Chapman, and Hall, 128–206, 1993. Treude, T., Smith, C. R., Wenzhöfer, F., Carney, E., Bernardino, A. F., Hannides, A. K., Krgüer, M., and Boetius, A.: Biogeochem- istry of a deep-sea whale fall: Sulfate reduction, sulfide efflux and methanogenesis, Mar. Ecol.-Prog. Ser., 382, 1–21, 2009. Biogeosciences, 15, 137–157, 2018 www.biogeosciences.net/15/137/2018/
https://openalex.org/W2804810112
https://europepmc.org/articles/pmc5980967?pdf=render
English
null
Multimodal Light Microscopy Approaches to Reveal Structural and Functional Properties of Promyelocytic Leukemia Nuclear Bodies
Frontiers in oncology
2,018
cc-by
21,562
Multimodal Light Microscopy Approaches to Reveal Structural and Functional Properties of Promyelocytic Leukemia Nuclear Bodies Christian Hoischen1, Shamci Monajembashi1, Klaus Weisshart2 and Peter Hemmerich1* 1 Leibniz Institute on Aging Research, Jena, Germany, 2 Carl Zeiss Microscopy GmbH, Jena, Germany The promyelocytic leukemia (pml) gene product PML is a tumor suppressor localized mainly in the nucleus of mammalian cells. In the cell nucleus, PML seeds the formation of macromolecular multiprotein complexes, known as PML nuclear bodies (PML NBs). While PML NBs have been implicated in many cellular functions including cell cycle regulation, survival and apoptosis their role as signaling hubs along major genome main- tenance pathways emerged more clearly. However, despite extensive research over the past decades, the precise biochemical function of PML in these pathways is still elusive. It remains a big challenge to unify all the different previously suggested cellular functions of PML NBs into one mechanistic model. With the advent of genetically encoded fluores- cent proteins it became possible to trace protein function in living specimens. In parallel, a variety of fluorescence fluctuation microscopy (FFM) approaches have been developed which allow precise determination of the biophysical and interaction properties of cel- lular factors at the single molecule level in living cells. In this report, we summarize the current knowledge on PML nuclear bodies and describe several fluorescence imaging, manipulation, FFM, and super-resolution techniques suitable to analyze PML body assembly and function. These include fluorescence redistribution after photobleaching, fluorescence resonance energy transfer, fluorescence correlation spectroscopy, raster image correlation spectroscopy, ultraviolet laser microbeam-induced DNA damage, erythrocyte-mediated force application, and super-resolution microscopy approaches. Since most if not all of the microscopic equipment to perform these techniques may be available in an institutional or nearby facility, we hope to encourage more researches to exploit sophisticated imaging tools for their research in cancer biology. Keywords: live cell imaging, fluorescence fluctuation microscopy, super-resolution, promyelocytic leukemia, tumor suppressor, oncogene Citation: Hoischen C, Monajembashi S, Weisshart K and Hemmerich P (2018) Multimodal Light Microscopy Approaches to Reveal Structural and Functional Properties of Promyelocytic Leukemia Nuclear Bodies. Front. Oncol. 8:125. doi: 10.3389/fonc.2018.00125 Review Review published: 25 May 2018 doi: 10.3389/fonc.2018.00125 Elisa Ferrando-May, Universität Konstanz, Germany Reviewed by: Lothar Schermelleh, University of Oxford, United Kingdom Graham Dellaire, Dalhousie University, Canada Don C. Lamb, Ludwig-Maximilians-Universität München, Germany *Correspondence: Peter Hemmerich peter.hemmerich@leibniz-fli.de Specialty section: This article was submitted to Cancer Genetics, a section of the journal Frontiers in Oncology Received: 17 November 2017 Accepted: 05 April 2018 Published: 25 May 2018 Edited by: Edited by: Elisa Ferrando-May, Universität Konstanz, Germany PML AND PML NUCLEAR BODIES The pml gene product (PML) is a member of the tripartite motif (TRIM)-containing protein superfamily. In human cells, six nuclear PML isoforms (I–VI) are expressed. The various isoforms originate from alternative mRNA splicing of exons 7–9 while exons 1–6 are shared by all isoforms (Figure 1A) (21). This primary sequence complexity of PML protein expression allows for common as well as individual functional modalities among the isoforms (22). PML I is the longest isoform (882 amino acids), while PML VI (552 amino acids) is the shortest isoform in the cell nucleus. Similar to other members of the TRIM family, all nuclear PML protein isoforms contain a conserved TRIM/RBCC motif consisting of a RING domain, two B-box domains and a coiled-coil domain (RBCC) (Figure 1A) (23). A nuclear localiza- tion signal (NLS) mediates predominant nuclear localization of PML. All PML isoforms contain three well-characterized small ubiquitin-related modifier (SUMO) modification sites at position 65, 160, and 490 of the PML primary sequence (Figure 1A) (24). Generally, SUMO modification of proteins plays important roles in diverse cellular processes, including chromatin organization, transcription, DNA repair, macromolecular assembly, protein i A better understanding of the biophysical and biochemical mechanisms by which PML and/or the PML nuclear bodies participate in genome maintenance is expected to facilitate the development of therapeutic strategies for the treatment of PML- related diseases (19). Novel microscopy methods have become key tools for study- ing biological systems over the past decades. Deep insight with unprecedented spatial and time resolution has been obtained for many cellular factors as a result of the rapid development of optical microscopy, fluorescent probes, and new labeling tech- niques (20). Since most biochemical mechanisms on the cellular level are dynamic by nature and cannot be fully understood by simply measuring fixed structures it is desirable to investigate the molecule of interest in real time, in living cells, at single-molecule, nanometer, and nanosecond resolution. Is this feasible? We think the answer is yes and the purpose of this report is explaining why. Figure 1 | Promyelocytic leukemia (PML) protein isoforms. (A) Schematic depiction of the six nuclear PML isoforms (I to VI). Exons 1–6 are shared by all isoforms while their C-termini are individually different due to alternative splicing of exons 7–9. R, RING domain, B, B box; CC, coiled coil domain; NLS, nuclear localization sequence; SIM, SUMO-interacting motif; S, SUMOylation sites at arginine positions K65, K160, and K490. INTRODUCTION At the physiological level, PML has been functionally linked to anti-inflammatory and antiviral response pathways, metabolism, stem cell maintenance, and aging, while more mechanistically, PML’s role in tumor suppression is linked to control of the cell cycle, apoptosis/ senescence, cell migration, angiogensis, and the DNA damage response (9, 10). Since upon DNA damage PML NBs accumulate various DNA damage response factors and physically associate with damaged chromatin, they have also been suggested to play important roles in genome maintenance, probably by supporting specific aspects of DNA repair pathways (11–18). We set out here to summarize our view of PML nuclear body function and assembly, the current status of powerful imaging methods and describe in some detail how the new imaging tools work in deciphering structural and functional aspects of PML nuclear bodies. Many of these tools may be accessible at a near-by imaging facility of most laboratories. We therefore wish to encour- age those researchers in the fields of cancer biology to exploit the new methods more rigorously. Ultimately, the combination of classical biochemical approaches with dynamic methods and live cell imaging platforms may make it possible to fully elucidate the biophysical mechanisms underlying the structure, function, and networks of tumor suppressors and oncogenes, thus aiding the development of new therapeutic approaches. INTRODUCTION The promyelocytic leukemia (pml) gene is a target of the t(15;17) chromosomal translocation, which fuses pml reciprocally with retinoic acid receptor α (RARα) (1). PML protein is the major build- ing unit of the so-called PML nuclear bodies (PML NBs). PML NBs appear as nuclear dot-shaped structures that are interspersed between chromatin (2). PML NBs are heterogeneous and dynamic May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 1 Advanced Bioimaging of PML Bodies Hoischen et al. structures, ranging in size from 0.1 to 1.0 µm, and typically there are 5–30 bodies per nucleus, depending on the cell type, phase of cell cycle, and the cellular stress level (3–5). Overexpression of PML in cancer cell lines induces cell cycle arrest and apoptosis (6). PML knock-out mice develop a range of cancers including papillomas, carcinomas, and lymphomas after exposure to car- cinogens (7). Furthermore, loss of PML is a hallmark of human cancers from diverse tissues (8). Therefore, PML is regarded as a potent tumor suppressor in in vitro (biochemistry, cell culture experiments) and in vivo (model organisms). At the physiological level, PML has been functionally linked to anti-inflammatory and antiviral response pathways, metabolism, stem cell maintenance, and aging, while more mechanistically, PML’s role in tumor suppression is linked to control of the cell cycle, apoptosis/ senescence, cell migration, angiogensis, and the DNA damage response (9, 10). Since upon DNA damage PML NBs accumulate various DNA damage response factors and physically associate with damaged chromatin, they have also been suggested to play important roles in genome maintenance, probably by supporting specific aspects of DNA repair pathways (11–18). structures, ranging in size from 0.1 to 1.0 µm, and typically there are 5–30 bodies per nucleus, depending on the cell type, phase of cell cycle, and the cellular stress level (3–5). Overexpression of PML in cancer cell lines induces cell cycle arrest and apoptosis (6). PML knock-out mice develop a range of cancers including papillomas, carcinomas, and lymphomas after exposure to car- cinogens (7). Furthermore, loss of PML is a hallmark of human cancers from diverse tissues (8). Therefore, PML is regarded as a potent tumor suppressor in in vitro (biochemistry, cell culture experiments) and in vivo (model organisms). PML AND PML NUCLEAR BODIES Additional posttranslational modifications (PTMs) of PML include phosphorylation, acetylation, and ubiquitination, all of which may serve to fine-tune PML (nuclear body) function through multiple mechanisms (28). A common feature of TRIM/RBCC proteins is homo-multimerization which generates a variety of subcellular structures including ribbon-like structures, cytoplasmic or nucleopasmic filaments, as well as cytoplasmic or nucleoplasmic bodies (23). Indeed, all six nuclear PML isoforms, when ectopically overexpressed, individually form nuclear bodies even in the absence of endogenous PML (29), with some isoforms contributing not only to nuclear body morphology (27, 30) but also function (31–33). By immunofluorescence light microscopy, normal PML bod- ies display as spherical structures, ranging in size from 0.2 µm up to 1 µm (Figure 2A). By electron or super-resolution light microscopy, PML protein is concentrated in a ~100  nm thick shell in the periphery of the nuclear bodies with no chromatin or RNA inside them (34–37). The shell also contains SUMO isoforms and other PML body components, such as SP100 (Figure  2B) (35). This structural arrangement provokes the question on the nature and biological function of the inner core of a PML NB. Within the nuclear body shell, PML’s branched SUMO chains stabilize protein complexes as a “molecular glue” (see next section). In functionally specialized PML bodies, such as in alternative lengthening of telomeres-associated PML nuclear bodies (APBs) and in immunodeficiency, centromeric instability, and facial dysmorphy (ICF) syndrome cells, the inner core of PML bodies contains chromatin, namely telomeric DNA in APBs or Figure 2 | Structure and function of promyelocytic leukemia (PML) nuclear bodies. (A) Distribution of PML protein in a cell nucleus of a MRC-5 (primary human lung fibroblast) cell. The micrograph shows the immunofluorecence signal of an antibody directed to all PML isoforms (green, monoclonal antibody E-11, sc-377390, Santa Cruz Biotechnology, Heidelberg, Germany) along with DAPI fluorescence (red) of a mid-confocal section of the nucleus. Bar; 5 µm. (B) Structure of PML nuclear bodies. SUMOylated PML protein subunits are the building blocks of a shell-like structure in the periphery of the nuclear body. Additional PML body- interacting proteins may bind to PML, specifically to the C-termini of the various PML isoforms, to the poly-small ubiquitin-related modifier (poly-SUMO) chains or to SUMO-interaction motifs. PML nuclear bodies’ are in direct contact with chromatin fibers, which contribute to the bodies physical stability. See Figure 3 for more information on the assembly mechanism. PML AND PML NUCLEAR BODIES (B) PML protein expression in various cell lines. Western blot of whole cell lysates derived from MRC-5 (primary human lung fibroblasts), U2OS (Osteosarcoma-derived ALT cell line), and HEp-2 (human epithelial non-ALT cancer cell line) using a rabbit-anti-PML antibody (ABD-030, Jena Bioscience, Germany) at 1:500 dilution. Non-SUMOylated PML isoforms are detectable between 55 kDa and 110 kDa. Poly-SUMOylated PML isoforms are detected above 110–250 kDa. Figure 1 | Promyelocytic leukemia (PML) protein isoforms. (A) Schematic depiction of the six nuclear PML isoforms (I to VI). Exons 1–6 are shared by all isoforms while their C-termini are individually different due to alternative splicing of exons 7–9. R, RING domain, B, B box; CC, coiled coil domain; NLS, nuclear localization sequence; SIM, SUMO-interacting motif; S, SUMOylation sites at arginine positions K65, K160, and K490. (B) PML protein expression in various cell lines. Western blot of whole cell lysates derived from MRC-5 (primary human lung fibroblasts), U2OS (Osteosarcoma-derived ALT cell line), and HEp-2 (human epithelial non-ALT cancer cell line) using a rabbit-anti-PML antibody (ABD-030, Jena Bioscience, Germany) at 1:500 dilution. Non-SUMOylated PML isoforms are detectable between 55 kDa and 110 kDa. Poly-SUMOylated PML isoforms are detected above 110–250 kDa. May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 2 Advanced Bioimaging of PML Bodies Hoischen et al. homeostasis, trafficking, and signal transduction (25). In the case of PML, SUMO-2 and SUMO-3 can form heteropolymeric poly-SUMO chains (26). PML isoforms as well as their poly- SUMOylated variants can be easily detected by Western blotting (Figure  1B) (27). Additional posttranslational modifications (PTMs) of PML include phosphorylation, acetylation, and ubiquitination, all of which may serve to fine-tune PML (nuclear body) function through multiple mechanisms (28). A common feature of TRIM/RBCC proteins is homo-multimerization which generates a variety of subcellular structures including ribbon-like structures, cytoplasmic or nucleopasmic filaments, as well as cytoplasmic or nucleoplasmic bodies (23). Indeed, all six nuclear PML isoforms, when ectopically overexpressed, individually form nuclear bodies even in the absence of endogenous PML (29), with some isoforms contributing not only to nuclear body morphology (27, 30) but also function (31–33). homeostasis, trafficking, and signal transduction (25). In the case of PML, SUMO-2 and SUMO-3 can form heteropolymeric poly-SUMO chains (26). PML isoforms as well as their poly- SUMOylated variants can be easily detected by Western blotting (Figure  1B) (27). PML NUCLEAR BODY FUNCTION Systems biological analyses based on online repositories, most notably the Nuclear Protein Database1 (43) have predicted, that more than 150 nuclear proteins have the ability to interact with PML bodies (44, 45). The “Biological General Repository for Interaction Datasets” (BioGRID) lists 243 unique protein interactions.2 Resident factors of PML NBs include, beside all PML isoforms, SUMO paralogs, Daxx, and SP100 (46). Most other factors only transiently accumulate at PML bodies under specific stress conditions or in specialized PML bodies, such as APBs or the giant PML bodies in ICF cells (39). In addition to the telomeric chromatin and shelterin core components, APBs accumulate DNA recombination and repair factors such as the MRN complex, RAD (radiation sensitivity) family members, RPA and WRN (38, 47).h The functional diversity of transient PML NB components is likely the basis of the many different biological roles ascribed to these nuclear structures (Figure 2C) (5, 48). PML NBs have been functionally linked to apoptosis (49), nuclear proteolysis (50), senescence (51), stem cell renewal (52, 53), regulation of gene expression (54), tumor suppression (55), the DNA dam- age response (40, 41, 56), telomere elongation and stability (47, 57), epigenetic regulation (37, 58), and antiviral responses (59) (Figure  2C). Not surprisingly, functional annotation of PML nuclear body proteins show an enrichment of terms related to cell cycle control, cellular stress response, DNA repair, and protein modification processes (44). More globally, the various aspects of PML NB functions mainly point to their role in genome maintenance (18). The iterative nature of the multiple binding sites creates a multivalency, which has now been suggested to be responsible for the compartmentalization activity of PML NBs through the biophysical mechanism of phase-separation (67). Although only inferred as probable from GFP-SUMO/RFP-SIM phase- separation data obtained in vitro, the Banani et al. report suggests that that the polySUMO/polySIM interfaces in PML NBs may form phase-separated liquid droplet structures in living cells (68). Thus PML NBs belong to the family of viscous liquid, mem- brane less nuclear compartments, which may function as phase separating condensates equivalent to lipid droplets (69). PML AND PML NUCLEAR BODIES (C) Proposed functions of PML nuclear bodies. Probably more than 100 proteins permanently or transiently bind to PML NBs. According to these protein’s function, many different physiological roles as depicted have been proposed for PML NBs. Figure 2 | Structure and function of promyelocytic leukemia (PML) nuclear bodies. (A) Distribution of PML protein in a cell nucleus of a MRC-5 (primary human lung fibroblast) cell. The micrograph shows the immunofluorecence signal of an antibody directed to all PML isoforms (green, monoclonal antibody E-11, sc-377390, Santa Cruz Biotechnology, Heidelberg, Germany) along with DAPI fluorescence (red) of a mid-confocal section of the nucleus. Bar; 5 µm. (B) Structure of PML nuclear bodies. SUMOylated PML protein subunits are the building blocks of a shell-like structure in the periphery of the nuclear body. Additional PML body- interacting proteins may bind to PML, specifically to the C-termini of the various PML isoforms, to the poly-small ubiquitin-related modifier (poly-SUMO) chains or to SUMO-interaction motifs. PML nuclear bodies’ are in direct contact with chromatin fibers, which contribute to the bodies physical stability. See Figure 3 for more information on the assembly mechanism. (C) Proposed functions of PML nuclear bodies. Probably more than 100 proteins permanently or transiently bind to PML NBs. According to these protein’s function, many different physiological roles as depicted have been proposed for PML NBs. May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 3 Advanced Bioimaging of PML Bodies Hoischen et al. pericentric satellite heterochromatin of chromosome 1 in the giant PML bodies of ICF cells (38, 39).h reactions or complex formation between low-abundance nuclear factors, as was also suggested for other subnuclear structures such as Cajal bodies or nucleoli (62). More specifically, PML NBs may be SUMOylation hot spots. This hypothesis is driven by the observation that most components of the SUMOylation machinery concentrate in PML NBs (45). The number of PML NBs varies between 5 and 30 depend- ing on the cell-type, the cellular differentiation status, and the cell cycle. During interphase PML bodies are positionally stable through their physical and probably functional interplay with the surrounding chromatin (Figure 2B) (2). Yet, PML NBs are also dynamic structures that undergo significant changes in number, size, and position particularly in response to cellular stress (4). One example is fission of PML bodies into smaller bodies in early S phase (40, 41, 42). 1 http://npd.hgu.mrc.ac.uk/ (Accessed: November 17, 2017). 2 https://thebiogrid.org/111384/summary/homo-sapiens/pml.html (Accessed: November 17, 2017). PML AND PML NUCLEAR BODIES PML NBs may lose their structural integrity based on modifications or structural alterations in adjacent chromatin associated with DNA replication. PML NUCLEAR BODY ASSEMBLY The formation and structural integrity of PML NBs relies on at least five basic mechanistic principles: (i) oxidation-driven intermo- lecular disulfide cross-linking of PML, (ii) the self-oligomerizing properties of PML’s RBCC motif, (iii) the poly-SUMO chains on the three major target lysines, (iv) the non-covalent interac- tion of SUMO with SUMO interacting motifs (SIM) in nuclear body-associated factors, and (v) specific sequences in various PML protein isoforms (Figure 3). In the initial step of nuclear body assembly, oxidized PML monomers allow the formation of disulfide-crosslinked covalent multimers that self-organize into the NB outer shell (9, 63). Non-covalent homodimerization mediated by the RBCC domain may be similarly important for the early PML NB assembly step, since the isolated RING domain of PML very efficiently forms multimeres in vitro (64). Subsequently, UBC9-mediated poly-SUMOylation, SUMO/SIM interactions (9, 65) and addition of SUMO and/or SIM-containing binding partners create a mature PML body with a peripheral scaffold consisting of the six different PML isoforms, their SIM motifs and the poly-SUMO chains (Figure 3). Recently, it was demonstrated that certain regions in the C-terminal domains of specific PML isoforms are also important for NB assembly and function (32, 33). These findings add an additional layer of complexity in the structural and functional maintenance of PML NB integrity. The PML nuclear body scaffold offers a multitude of potential sites to which an assortment of PML-interacting, SIM-containing, and/ or SUMOylated partner proteins may bind transiently to a more or less extent. The varying residence times (Rts) of binding part- ners at PML NBs would be expected to depend on the number and strength of their individual interaction modules (66). This is in line with the presence of several SUMOylation sites and SIMs in major PML-NB components including PML, SP100, DAXX, HIPK2, UBC9, PIASy, and RNF4 (9). PML NUCLEAR BODY FUNCTION The biochemical environment within a phase-separating PML body is different from that in the surrounding nucleoplasm, and this difference could enable unique strategies for regulating nuclear response pathways, including (a) regulation of enzyme reaction kinetics (i.e., posttranslational modifications), (b) regulation of One hypothesis for the integration of all of these functions in a unifying concept is based on the idea that PML NBs provide a stable protein scaffold onto which binding partners associate for their efficient PTM or sequestration (Figure 2C) (28, 60, 61). Controlled accumulation at or release of specific nuclear factors from the nuclear bodies may enhance their functional interaction based on mass-law action, thereby fine-tuning signaling cascades through the nucleoplasm. This mechanism may enable chemical May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 4 Hoischen et al. Advanced Bioimaging of PML Bodies Figure 3 | Assembly of promyelocytic leukemia (PML) nuclear bodies. The assembly of PML nuclear bodies is initiated by oligomerization of non-SUMOylated PML monomers. Oligomerization occurs via weak non-covalent interactions through the RBCC motif and covalent di-sulfide bonds between cystein residues. The E2-small ubiquitin-related modifier (SUMO) ligase UBC9 then promotes (poly-)SUMOylation of the PML moieties which allows for multiple SUMO–SUMO interacting motifs (SIM) interaction possibilities to form larger aggregates. Binding partners carrying SIMs and or SUMO residues can bind to the preassembled aggregates to form a normal PML body based on self-organization. Figure 3 | Assembly of promyelocytic leukemia (PML) nuclear bodies. The assembly of PML nuclear bodies is initiated by oligomerization of non-SUMOylated PML monomers. Oligomerization occurs via weak non-covalent interactions through the RBCC motif and covalent di-sulfide bonds between cystein residues. The E2-small ubiquitin-related modifier (SUMO) ligase UBC9 then promotes (poly-)SUMOylation of the PML moieties which allows for multiple SUMO–SUMO interacting motifs (SIM) interaction possibilities to form larger aggregates. Binding partners carrying SIMs and or SUMO residues can bind to the preassembled aggregates to form a normal PML body based on self-organization. genesis itself, suggesting that tightly controlled PTMs are required for full maturation of functional PML bodies in early G1 (71). the specificity of biochemical reactions, (c) sequestration of mol- ecules, and (d) buffering cellular concentration of molecules (67). Cell cycle-dependent disassembly of PML NBs begins upon de-SUMOylation of PML at the onset of mitosis. PML NUCLEAR BODY FUNCTION The spherical shell structure of PML NBs breaks down and other NB compo- nents such as SUMO, SP100, and DAXX detach or are removed. During mitosis PML aggregates into so-called mitotic accumu- lations of PML protein (MAPPs) (40, 41). Interestingly, PML bodies form stable interactions with early endosomes throughout mitosis and the two compartments dissociate in the cytoplasm of newly divided daughter cells (70). When followed through the telophase/G1 transition, Chen et al. observed that GFP-tagged MAPPs become trapped in the newly formed nuclei but also that many PML NBs are formed de novo at different sites in daughter nuclei. This suggests that PML NBs can assemble from both, MAPPs as well as soluble PML monomers in G1 (71). At the M/ G1 border of the cell cycle, MAPPs also complex with FG repeat- containing peripheral components of the nuclear pore complex to become CyPNs (cytoplasmic assemblies of PML and nucleop- orins) (72). Within CyPNs, PML appears to be instrumental in a novel, nuclear pore-independent, mechanism of nucleoporin and nuclear cargo protein targeting to the reforming G1 cell nucleus (73). The recruitment of SP100 and DAXX into newly formed PML NBs occurs considerably (ca. 30 min) later than PML NB TUMOR SUPPRESSOR AND ONCOGENIC FUNCTIONS OF PML Beside the correlative connection between carcinogenesis and PML expression, there is plenty of experimental evidence for a direct tumor-suppressive role of PML. Several independent studies have demonstrated that overexpression of PML can slow down or block cell cycle progression in a variety of cancer cell lines (6, 81, 84). Likewise, in primary human or mouse fibroblasts overexpression of PML isoform IV induces a stable senescence- associated cell cycle arrest (85, 86). Further analyses of typical stress-response pathways revealed the involvement of the tumor suppressors pRb and p53 in PML overexpression-induced cellular senescence (86, 87). However, the molecular details of PML action along the pRB and/or p53 tumor suppressive pathways remain elusive. Besides in cellular senescence, PML has an essential functional role in apoptosis (49). This is based on initial observations on the first reported PML knock-out mouse model, where splenic lymphocytes and thymocytes from Pml−/− mice show barely half the capacity of wild-type cells to initiate apoptosis after ionizing radiation or after induction of the cytokine death-receptor pathway (88). As already pointed out, PML loss correlates with the progression of many cancers and in most cases low PML expression is associated with poor prognosis. The tumor suppressor function of PML NBs may be linked to their ability to accumulate many proteins involved in DNA dam- age response and repair pathways, which is believed to stabilize DNA repair complexes and enhance their activities (4, 13, 60). In support of this hypothesis, it was shown recently in a knock-in mouse model, that intact PML bodies are critical for DNA dam- age responses. Functional assays in mice expressing PML but lacking PML NBs showed impaired homologous recombination (HR) and non-homologous end-joining repair pathways, with Inter- and intracellular mechanisms of molecular communication may be better understood through direct visualization. In the past decades, advancements in imaging technologies have expanded our ability to access and analyze in living specimen the morphol- ogy of tissues and cellular components. These enabled analyses of fine-structural features at the nanoscale level, precise localization, and the dynamic interplay of single and macromolecular assem- blies that drive cell growth, the cell cycle, differentiation, and cell death (20–37). Super-resolution light microscopy delivered images with unprecedented sensitivity and clarity allowing the exploration of interactions between individual molecules with a distance resolution as low as 20  nm (94). PML IN TUMORIGENESIS So far, we have summarized some aspects of PML NB biology derived from microscopic, cell, and molecular biology approaches. Another branch of PML research has tackled questions on PML protein function by means of genetics. These approaches uncov- ered PML’s role in cancer biology. PML was originally identified as a potential gene of interest in tumorigenesis due to its associa- tion with acute promyelocytic leukemia (APL). APL is a rare but aggressive subtype of white blood cell cancer, characterized by an accumulation of promyelocytes in the bone marrow and periph- eral blood (74). The majority of APL patients are characterized by the t(15;17) chromosomal translocation that reciprocally joins the PML and retinoic acid receptor α (RARα) genes, resulting in bal- anced expression of PML-RARα and RARα-PML fusion proteins (1). While PML-RARα blocks differentiation of promyelocytes by suppressing the transcriptional function of RARα, PML-RARα disrupts the structure of PML nuclear bodies through formation of PML-RARα/PML heterodimers. This phenotype was observed in 99% of APL patients (75). Treatment of APL for many years was retinoic acid, arsenic trioxide or a combination of the two, May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 5 Advanced Bioimaging of PML Bodies Hoischen et al. which, fortunately, seemed to cure most APL patients. It is now known that the mechanism of this therapy involves targeting of the PML/RARα fusion protein to proteasomal degradation (76). Strikingly, drug treatment reverses the pathological microspeck- led PML distribution in the nucleus of APL cells toward the regular morphology of PML nuclear bodies (77). defective localization of Brca1 and Rad51 to sites of DNA damage (89). Thus, although the physiological function of PML and the nuclear bodies have not been thoroughly elucidated, their tumor- suppressive role by supporting DNA damage response pathways may be common to all of these potential functions (19, 89).h The lack of PML is not necessarily a tumor-promoting event. Functional analysis of the hematopoietic stem cell compartment in mice have uncovered that PML is required for leukemia initiating cell maintenance (90). The authors suggest a new therapeutic approach for eradication of cancer-initiating cells in leukemia through pharamacological inhibition of PML. This and other reports have lead to the suggestion that PML may act as both a tumor suppressor and an oncogene, depending on the cellular context (91). PML IN TUMORIGENESIS Along these lines it was also demonstrated that PML targeting impacts on breast cancer (BCa)-initiating cell function, and hence on cancer initiation and dissemination in BCa (92). Furthermore, in triple- negative breast cancer cell and mouse models PML promotes cell migration, invasion, and metastasis through binding to regulatory regions of HIF1A target genes (93). These initially unexpected findings clearly suggest a previously underestimated importance of PML in the maintenance of some tumors. Another link between cancer and PML became evident by comparing PML protein expression in normal and neoplastic human tissues. Such studies documented loss of PML expression in breast carcinoma (78), gastric cancer (79), small cell lung car- cinoma (80), and in invasive epithelial tumors (81). Furthermore, microarray analyses of PML mRNA expression showed complete loss of or strongly reduced PML transcript expression in many different human neoplasms, including colon, prostate, and breast adenocarcinomas, as well as in lung, CNS, germ cell, and non- Hodgkin’s tumors/lymphomas (8). The same study reported that PML protein is also frequently overexpressed in carcinomas of larynx and thyroid, epithelial thymomas, Kaposi’s sarcoma, and in Hodgkin cells, a tumor of cytokine-producing cells. The latter phenomenon may be attributable to strong upregulation of the PML gene after Interferon induction (82). Taken together, loss of expression in many (but not all) cancer types have suggested that PML works as a tumor suppressor (83). Frontiers in Oncology  |  www.frontiersin.org TUMOR SUPPRESSOR AND ONCOGENIC FUNCTIONS OF PML New fluorescence fluctuation microscopy (FFM) approaches provided the basis for determining the biophysical and interaction properties of single molecules in living cells (95, 96). Laser-based FFM analysis tools are outlined below but many more exist, all of which unfortunately cannot be covered by this overview, including single particle tracking (SPT), light sheet microscopy, total internal reflection microscopy just to name a few. To acquire the full picture of live cell laser-based imaging technologies, we refer to recent excel- lent reviews on these topics (20, 97–99). Altogether, a plethora of new live cell imaging techniques have been developed which even large research groups are unable to establish to a broad extent in their departments. To address this, dedicated advanced light microscopy imaging facilities are extremely helpful as their members are usually microscope experts (100). However, we believe that research laboratories are still reluctant in exploiting the full potential of microscopy facilities. We therefore provide an introductory overview on some imaging instrumentation which May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 6 Advanced Bioimaging of PML Bodies Hoischen et al. the creation of photobleached spots of fluorescent molecules in solution or in living cells by the application of a laser beam. By monitoring the redistribution of the fluorescent molecules from the unbleached volume, their diffusion or transport properties can be assessed (101). FRAP and related techniques such as point continuous photobleaching, fluorescence loss in photobleaching, inverse-FRAP, and photoactivation/conversion have been devel- oped in the past, each suitable to quantitatively assess specific biophysical properties of the molecule under investigation (97). However, the limitations and pitfalls of FRAP experiments, in particular when they are employed to extract biophysical param- eters also, have to be considered. Things to consider include the complete set-up of the FRAP experiment (103), knowledge on the bleach volume profile (104), as well as the potential phototoxic effects elicited by the bleaching laser beam (105). are covered by such facilities and provide specific examples in PML biology to encourage cancer cell biologists and biochemists to extend their experimental approaches toward the exciting new imaging technologies. Figure 4 | Fluorescence recovery after photobleaching (FRAP) to assess component exchange at promyelocytic leukemia (PML) nuclear bodies. (A) A typical FRAP experiment is shown. Two circular regions in the nucleus of a GFP-PML-V expressing U2OS cell were exposed to a short 488 nm laser bleach pulse and fluorescence redistribution was monitored over time. A third circled unbleached region at the bottom of this nucleus is shown as a positive control. One particular bleach spot is shown in a magnified view in the bottom panels. (B) Quantitation of FRAP experiments. After background subtraction, compensation for imaging-induced photobleaching and normalization, typical FRAP curves are obtained. FRAP curve A shows full recovery to prebleach fluorescence values indicating complete exchange of the GFP-tagged protein in the bleached spot within the observation time. In FRAP curve B, fluorescence recovery is not complete within observation time indicating an immobile fraction of molecules or a fraction with a very slow exchange rate. (C) FRAP curve fitting using exponential functions. FRAP curves for GFP-tagged PML-I (left) and PML-II (right) were fitted with one-component (red) or two-component (green) exponential functions. (D) Table showing the residence time (Rt) in minutes of GFP-tagged PML isoforms I to VI derived from fitting FRAP curves employing different mathematical models (See text for details). * numbers in red letters represent Rt values derived from one component modeling which failed to precisely fit to the measured FRAP curve as shown for GFP-PML-II in (C). FLUORESCENCE RECOVERY AFTER PHOTOBLEACHING (FRAP) Arguably, one of the most commonly used approaches to study dynamic cellular processes in living cells is FRAP (101). FRAP is able to access average dynamics of diffusing molecules within the observation volume. The original description of FRAP was coined continuous fluorescence microphotolysis, which itself has been established for more than three decades (102). When subjected to repeated cycles of excitation and emission, fluorescent mol- ecules eventually lose their ability to emit fluorescence, enabling f Figure 4A shows a typical FRAP experiment for GFP-tagged PML (isofom V) at nuclear bodies. Measuring the redistribution Figure 4 | Fluorescence recovery after photobleaching (FRAP) to assess component exchange at promyelocytic leukemia (PML) nuclear bodies. (A) A typical FRAP experiment is shown. Two circular regions in the nucleus of a GFP-PML-V expressing U2OS cell were exposed to a short 488 nm laser bleach pulse and fluorescence redistribution was monitored over time. A third circled unbleached region at the bottom of this nucleus is shown as a positive control. One particular bleach spot is shown in a magnified view in the bottom panels. (B) Quantitation of FRAP experiments. After background subtraction, compensation for imaging-induced photobleaching and normalization, typical FRAP curves are obtained. FRAP curve A shows full recovery to prebleach fluorescence values indicating complete exchange of the GFP-tagged protein in the bleached spot within the observation time. In FRAP curve B, fluorescence recovery is not complete within observation time indicating an immobile fraction of molecules or a fraction with a very slow exchange rate. (C) FRAP curve fitting using exponential functions. FRAP curves for GFP-tagged PML-I (left) and PML-II (right) were fitted with one-component (red) or two-component (green) exponential functions. (D) Table showing the residence time (Rt) in minutes of GFP-tagged PML isoforms I to VI derived from fitting FRAP curves employing different mathematical models (See text for details). * numbers in red letters represent Rt values derived from one component modeling which failed to precisely fit to the measured FRAP curve as shown for GFP-PML-II in (C). Figure 4 | Fluorescence recovery after photobleaching (FRAP) to assess component exchange at promyelocytic leukemia (PML) nuclear bodies. (A) A typical FRAP experiment is shown. Two circular regions in the nucleus of a GFP-PML-V expressing U2OS cell were exposed to a short 488 nm laser bleach pulse and fluorescence redistribution was monitored over time. FLUORESCENCE RECOVERY AFTER PHOTOBLEACHING (FRAP) A third circled unbleached region at the bottom of this nucleus is shown as a positive control. One particular bleach spot is shown in a magnified view in the bottom panels. (B) Quantitation of FRAP experiments. After background subtraction, compensation for imaging-induced photobleaching and normalization, typical FRAP curves are obtained. FRAP curve A shows full recovery to prebleach fluorescence values indicating complete exchange of the GFP-tagged protein in the bleached spot within the observation time. In FRAP curve B, fluorescence recovery is not complete within observation time indicating an immobile fraction of molecules or a fraction with a very slow exchange rate. (C) FRAP curve fitting using exponential functions. FRAP curves for GFP-tagged PML-I (left) and PML-II (right) were fitted with one-component (red) or two-component (green) exponential functions. (D) Table showing the residence time (Rt) in minutes of GFP-tagged PML isoforms I to VI derived from fitting FRAP curves employing different mathematical models (See text for details). * numbers in red letters represent Rt values derived from one component modeling which failed to precisely fit to the measured FRAP curve as shown for GFP-PML-II in (C). Figure 4 | Fluorescence recovery after photobleaching (FRAP) to assess component exchange at promyelocytic leukemia (PML) nuclear bodies. (A) A typical FRAP experiment is shown. Two circular regions in the nucleus of a GFP-PML-V expressing U2OS cell were exposed to a short 488 nm laser bleach pulse and fluorescence redistribution was monitored over time. A third circled unbleached region at the bottom of this nucleus is shown as a positive control. One particular bleach spot is shown in a magnified view in the bottom panels. (B) Quantitation of FRAP experiments. After background subtraction, compensation for imaging-induced photobleaching and normalization, typical FRAP curves are obtained. FRAP curve A shows full recovery to prebleach fluorescence values indicating complete exchange of the GFP-tagged protein in the bleached spot within the observation time. In FRAP curve B, fluorescence recovery is not complete within observation time indicating an immobile fraction of molecules or a fraction with a very slow exchange rate. (C) FRAP curve fitting using exponential functions. FRAP curves for GFP-tagged PML-I (left) and PML-II (right) were fitted with one-component (red) or two-component (green) exponential functions. (D) Table showing the residence time (Rt) in minutes of GFP-tagged PML isoforms I to VI derived from fitting FRAP curves employing different mathematical models (See text for details). FLUORESCENCE (CROSS) CORRELATION SPECTROSCOPY Fluorescence correlation spectroscopy (FCS) is an in  vivo method that analyses diffusing particles in a diffraction-limited illumination ellipsoid (114, 115). The FCS detection volume is created by a laser beam in a pinhole-adjustable confocal optical system focused through a high numerical aperture objective (Figure 5A). The FCS detection volume is defined by the point spread function of the objective and the confocal pinhole. The excitation laser beam determines how much of the detection volume is excited and the final observation volume is deter- mined by the overlap of excitation and detection volumes. For objectives with a high numerical aperture (i.e., NA = 1.4) the effective measuring volume is ~1 fl (116). Photons emitted from diffusing fluorescent particles are counted continuously over time through the same optics using sensitive avalanche photodiodes (APDs) or galliumarsenidephosphide (GaAsP) hybrid detectors at single molecule resolution (Figure 5A) (117). The fluorescence intensity fluctuations are recorded over time (Figure 5B). Particle concentration is reflected by the fluctuation amplitude, whereas the frequency gives information on the diffusion times of the fluorescent particles. For quantitative evaluation, the photon trace is correlated with a time-shifted replica of itself (autocor- relation) at different time values (Figure 5C). The amplitude of the autocorrelation curve is inversely proportional to the average number of fluorescent molecules in the confocal volume allow- ing determination of particle concentration (Figure 5C). A more detailed overview on the theory, history, and application of FCS can be found here: (118, 119).l g gi g To obtain a complete picture we collected the Rts of all PML isoforms after fitting to one- and two-component exponential functions (Figure  4D). This approach delivers the Rt of the protein under investigation (110). One-component exponential fits were successful for GFP-tagged PML-I and PML-V, while FRAP curves for the other isoforms could only be fitted with two-component exponential fits (Figure  4C and data not shown). For comparison, the table includes the data we previ- ously obtained by application of a binding-diffusion model based on more sophisticated differential equation modeling to analyze the FRAP curves (66). The table shows that the Rts of PML isoforms at nuclear bodies as deduced from one-component exponential fits, is convincingly close to those obtained from assuming a binding-diffusion model (Figure 4D) although the fits are not satisfactory for PML-II, -III, -IV, and -VI (values in red letters). In particular, the very long Rt of PML-V (~50 min) is confirmed. FLUORESCENCE RECOVERY AFTER PHOTOBLEACHING (FRAP) Today, many FRAP models of processes in the cell nucleus assume that the proteins undergo diffusion as well as binding/unbinding events at chromatin or other more static subnuclear structures such as nuclear bodies. Importantly, both diffusion and binding/unbinding events contribute to the spatial dynamics of nuclear proteins (109, 110). of fluorescence into the bleached region then yields the FRAP recovery curve (Figure  4B). During the observation time of the FRAP experiment, the fluorescence in the bleached region may return to the prebleach value (Figure 4B, curve A) or not (Figure 4B, curve B). Incomplete recovery even after long obser- vation (>1 h) has been observed for some chromatin-binding proteins, which suggests the presence of immobile or very slow exchanging populations of molecules (106, 107). FRAP data can be analyzed using mathematical models to yield kinetic parameters (108). Today, many FRAP models of processes in the cell nucleus assume that the proteins undergo diffusion as well as binding/unbinding events at chromatin or other more static subnuclear structures such as nuclear bodies. Importantly, both diffusion and binding/unbinding events contribute to the spatial dynamics of nuclear proteins (109, 110). In conclusion, Figure 4 suggests that different FRAP modeling approaches, despite subtle differences, arrive at overall similar Rts for PML isoforms at nuclear bodies. It should be noted however that these long Rts do not necessarily reflect the time in which one PML molecule stays bound to one and the same specific binding site. Long Rts may also originate from PML molecules under- going rapid binding and unbinding events at multiple adjacent binding sites (in our case at the nuclear body) without leaving the observation volume (110). If binding/unbinding events do not occur on well-separated time scales, the interaction parameters may not be readily extractable from the FRAP curves (111). A combination of different FFM approaches may be required for accurate determination of binding parameters (112). To assess binding/unbinding events at PML NBs at higher resolution, the tool kit should be extended to single particle tracking (SPT) since this approach is able to quantitatively describe several popula- tions of molecules with distinct binding properties (113). With respect to PML protein exchange at nuclear bodies it is safe to assume a binding-dominant behavior because of the very slow exchange rates as observed by FRAP (Figure 4A). FLUORESCENCE RECOVERY AFTER PHOTOBLEACHING (FRAP) Previously, the residence time (Rt) at nuclear bodies of all PML isoforms had been determined by FRAP using a binding-diffusion model based on differential equations (29, 66). It was therefore interesting to compare different modeling approaches. Figure 4C shows two examples of fitting FRAP data obtained for GFP-tagged PML isoforms I and II. Interestingly both, one- and two-exponential functions delivered good fits to the FRAP curve for GFP-PML-I but not for GFP-PML-II, where only a two-component exponen- tial function gave good fit results (Figure 4C). FLUORESCENCE RECOVERY AFTER PHOTOBLEACHING (FRAP) * numbers in red letters represent Rt values derived from one component modeling which failed to precisely fit to the measured FRAP curve as shown for GFP-PML-II in (C). Figure 4 | Fluorescence recovery after photobleaching (FRAP) to assess component exchange at promyelocytic leukemia (PML) nuclear bodies. (A) A typical FRAP experiment is shown. Two circular regions in the nucleus of a GFP-PML-V expressing U2OS cell were exposed to a short 488 nm laser bleach pulse and fluorescence redistribution was monitored over time. A third circled unbleached region at the bottom of this nucleus is shown as a positive control. One particular bleach spot is shown in a magnified view in the bottom panels. (B) Quantitation of FRAP experiments. After background subtraction, compensation for imaging-induced photobleaching and normalization, typical FRAP curves are obtained. FRAP curve A shows full recovery to prebleach fluorescence values indicating complete exchange of the GFP-tagged protein in the bleached spot within the observation time. In FRAP curve B, fluorescence recovery is not complete within observation time indicating an immobile fraction of molecules or a fraction with a very slow exchange rate. (C) FRAP curve fitting using exponential functions. FRAP curves for GFP-tagged PML-I (left) and PML-II (right) were fitted with one-component (red) or two-component (green) exponential functions. (D) Table showing the residence time (Rt) in minutes of GFP-tagged PML isoforms I to VI derived from fitting FRAP curves employing different mathematical models (See text for details). * numbers in red letters represent Rt values derived from one component modeling which failed to precisely fit to the measured FRAP curve as shown for GFP-PML-II in (C). May 2018  |  Volume 8  |  Article 125 7 Advanced Bioimaging of PML Bodies Hoischen et al. of fluorescence into the bleached region then yields the FRAP recovery curve (Figure  4B). During the observation time of the FRAP experiment, the fluorescence in the bleached region may return to the prebleach value (Figure 4B, curve A) or not (Figure 4B, curve B). Incomplete recovery even after long obser- vation (>1 h) has been observed for some chromatin-binding proteins, which suggests the presence of immobile or very slow exchanging populations of molecules (106, 107). FRAP data can be analyzed using mathematical models to yield kinetic parameters (108). FLUORESCENCE (CROSS) CORRELATION SPECTROSCOPY These statistical fluctuations are mathematically processed using an autocorrelation algorithm, from which biophysical parameters such as the particle concentration, the diffusion coefficient and complex formation properties can readily be assessed (C). (D) Confocal live cell image of a U2OS nucleus coexpressing EGFP-SP100 and mRFP-PML-III (bar: 5 µm). The FCCS laser beam (light-blue) can be positioned anywhere in the cell. (E) By fitting the measured FCS data points (solid lines) to appropriate diffusion models (dashed lines), one can extract from the reciprocal of the amplitude and the decay half-time value the number of particles in the detection volume (concentration) and the diffusion time, respectively. The cross-correlation (CC) result of EGFP-SP100 and mRFP-PML-III are also shown. (F) CC results in the nucleus of living cells for a GFP–RFP fusion protein (positive control, high CC), GFP and RFP as individual proteins (negative control, no CC) and the measurement performed in (D,E). Cross-correlation analysis between EGFP-SP100 and mRFP- PML-III revealed a small but significant amplitude above the value of 1.0 (Figure 5E, blue curve indicated with GFP-SP100 and RFP-PML), indicating the formation of complexes between these fusion proteins. To evaluate this observation, the CC was compared with values obtained for individually expressed GFP and RFP molecules (negative control) as well as a GFP-RFP fusion protein (positive control) (Figures  5E,F). Experiments with these fluorochromes determine the dynamic range of the FCCS set-up. The mathematical delineation of the CC values is described elsewhere (124). Analyzing EGFP and mRFP as single molecules in our system resulted in CC = 1.001, indicating 0% complex formation while for the mRFP-EGFP fusion protein we observed a CC amplitude of 1.029, corresponding to 45% complex formation. The CC value for EGFP-SP100 and mRFP-PML-III was CC = 1.010, indicating that in this cell nucleus ca. 13% of SP100 molecules reside in a complex with PML (Figures 5E,F). These analyses demonstrate that FCS and FCCS, although An example of FCCS measurements of PML body components is shown in Figure 5D. The image shows a live-cell confocal snap- shot of a U2OS cell nucleus transiently expressing EGFP-SP100 and mRFP-PML III. The FCS laser spot was parked at a position in the nucleoplasm where the fluorescence signals of the fusion proteins are extremely low (Figure 5D, blue arrow). EGFP and mRFP fluorescence fluctuation was then recorded over time (10  ×  10  s measurements) and the fluctuation data correlated for each fluorophore (Figure 5E). FLUORESCENCE (CROSS) CORRELATION SPECTROSCOPY This observation is fully consistent with the presence of a strong homo-dimerization domain we found in the unique C-terminus of PML isofom V (32). Obviously, this domain in PML-V confers additional binding strength toward PML bodies. Fitting with two-component exponential functions assumes the presence of two populations of molecules exchanging at PML bodies with different on/off rates. These functions provided per- fect fits for all PML isoforms (Figure 4C, green curves, and data not shown), and the Rts are shown in Figure 4D. Interestingly, the two-component fits deliver considerably large populations of PML isoforms IV (61%) and VI (66%) with a Rt of ~half an hour (Figure 4D). This suggests that a subfraction of these isoforms may contribute to the structural integrity of nuclear bodies through stable incorporation. In fluorescence cross-correlation spectroscopy (FCCS), two spectrally distinct fluorophores are measured in the same detection volume at the same time (Figures 5A,B, red and green lines) and correlated by cross-correlation (CC) (Figure 5C, blue curve). The amplitude of the CC curve is directly proportional to the degree of complex formation and/or direct interaction between the two fluorescent particles (120). A practical guide to set up FCS and FCCS experiments in living cells can be found here (121–123). May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 8 Advanced Bioimaging of PML Bodies Hoischen et al. Figure 5 | Fluorescence cross-correlation spectroscopy (FCCS) analysis of promyelocytic leukemia (PML) nuclear body components. (A) Schematic side view of a living cell with the FCS laser beam focused to a position within the nucleus. The objective creates a laser light-illuminated subfemtoliter measuring volume in which single fluorescent molecules are excited to emit photons. The photons are counted on an avalanche photodiode (APD) or a galliumarsenidphosphid (GaAsP) detector as a time series of fluorescence intensity (B). These statistical fluctuations are mathematically processed using an autocorrelation algorithm, from which biophysical parameters such as the particle concentration, the diffusion coefficient and complex formation properties can readily be assessed (C). (D) Confocal live cell image of a U2OS nucleus coexpressing EGFP-SP100 and mRFP-PML-III (bar: 5 µm). The FCCS laser beam (light-blue) can be positioned anywhere in the cell. FLUORESCENCE (CROSS) CORRELATION SPECTROSCOPY (E) By fitting the measured FCS data points (solid lines) to appropriate diffusion models (dashed lines), one can extract from the reciprocal of the amplitude and the decay half-time value the number of particles in the detection volume (concentration) and the diffusion time, respectively. The cross-correlation (CC) result of EGFP-SP100 and mRFP-PML-III are also shown. (F) CC results in the nucleus of living cells for a GFP–RFP fusion protein (positive control, high CC), GFP and RFP as individual proteins (negative control, no CC) and the measurement performed in (D,E). Figure 5 | Fluorescence cross-correlation spectroscopy (FCCS) analysis of promyelocytic leukemia (PML) nuclear body components. (A) Schematic side view of a living cell with the FCS laser beam focused to a position within the nucleus. The objective creates a laser light-illuminated subfemtoliter measuring volume in which single fluorescent molecules are excited to emit photons. The photons are counted on an avalanche photodiode (APD) or a galliumarsenidphosphid (GaAsP) detector as a time series of fluorescence intensity (B). These statistical fluctuations are mathematically processed using an autocorrelation algorithm, from which biophysical parameters such as the particle concentration, the diffusion coefficient and complex formation properties can readily be assessed (C). (D) Confocal live cell image of a U2OS nucleus coexpressing EGFP-SP100 and mRFP-PML-III (bar: 5 µm). The FCCS laser beam (light-blue) can be positioned anywhere in the cell. (E) By fitting the measured FCS data points (solid lines) to appropriate diffusion models (dashed lines), one can extract from the reciprocal of the amplitude and the decay half-time value the number of particles in the detection volume (concentration) and the diffusion time, respectively. The cross-correlation (CC) result of EGFP-SP100 and mRFP-PML-III are also shown. (F) CC results in the nucleus of living cells for a GFP–RFP fusion protein (positive control, high CC), GFP and RFP as individual proteins (negative control, no CC) and the measurement performed in (D,E). Figure 5 | Fluorescence cross-correlation spectroscopy (FCCS) analysis of promyelocytic leukemia (PML) nuclear body components. (A) Schematic side view of a living cell with the FCS laser beam focused to a position within the nucleus. The objective creates a laser light-illuminated subfemtoliter measuring volume in which single fluorescent molecules are excited to emit photons. The photons are counted on an avalanche photodiode (APD) or a galliumarsenidphosphid (GaAsP) detector as a time series of fluorescence intensity (B). FÖRSTER RESONANCE ENERGY TRANSFER (FRET) The FRET process is a dipole–dipole interaction in which an excited donor fluorophore transfers energy to an acceptor mol- ecule in nanometer vicinity without absorption and emission of a photon (128). FRET is therefore commonly employed to measure the spatial distance between two fluorophores in fixed as well as in living cells (129). The FRET efficiency depends on the distance between two adjacent fluorescent molecules. At the Förster radius distance between a FRET pair (typically around 5 nm), the FRET efficiency is 50% (130). This size regime is comparable to the size of many proteins, the distance within which proteins interact, and the distance between sites on multisubunit proteins. Therefore, FRET can deliver parameters on the distance between two distinct sites on a macromolecule, the distance between two fluorophore- tagged proteins, and hence if and how these two proteins interact (131). Basically five different FRET detection methods have been developed for light microscopy, including acceptor photobleach- ing, donor photobleaching, ratio imaging, sensitized emission, and fluorescence lifetime measurements (132). Raster image correlation spectroscopy thereby expands the accessible timescales of FCS as it can resolve dynamics in the range of microseconds to seconds with still a sufficient spatial resolution (125). Data in cells are most conveniently acquired as a time series stack by raster scanning of images of selected cell areas. Due to its broad dynamic access by analyzing the fluctua- tions between neighboring pixels in the x- and y-direction, nearly all diffusion processes that take place in cellular subregions can be studied (125). A major advantage of the RICS technology is that it can be used in principle on any commercial confocal micro- scope with analog detection (126). The software and application tutorials developed by the Enrico Gratton lab can be found as downloads here.3 l In the past, we have mainly used acceptor photobleach- ing FRET (abFRET) to analyze spatial proximities within chromatin-interacting complexes (133). In abFRET, the accep- tor chromophore is photobleached, thereby preventing FRET from the donor to the acceptor (Figure 7A). If the donor and acceptor were in sufficient proximity for energy transfer, pho- tobleaching the acceptor results in an observable increase in donor fluorescence (Figure 7B). The measurement of abFRET only generates positive values when the distance between the donor and acceptor (in our case EGFP and mRFP, respec- tively) is between 3 and 8 nm. FLUORESCENCE (CROSS) CORRELATION SPECTROSCOPY By fitting theoretical model functions to the measured autocorrelation curves, the diffusion coefficient and the concentration of the diffusing species can be extracted. In this particular cell nucleus (Figure  5D), the concentration of EGFP-SP100 and mRFP-PML-III was 8.0 nM and 2.5  nM, respectively, demonstrating the power of FCS to work at extremely low expression levels (Figure 5E). The diffu- sion coefficient in the nucleoplasm outside nuclear bodies for these PML body components had been determined previously (DSP100 = 1.23 µm2 s−1, DPML-III = 1.63 µm2 s−1) (66). May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 9 Advanced Bioimaging of PML Bodies Hoischen et al. technically somewhat more demanding than for example FRAP experiments, provide an extremely powerful tool to precisely extract biophysical and interaction data on diffusing molecules of interest in living cells. suggests incorporation of PML into larger complexes and/ or interaction with an immobile structure (i.e., chromatin), or both. RICS can also be performed on large (but not small) PML nuclear bodies (Figures  6J–M). The resulting diffusion map reveals very slow diffusion of GFP-PML-IV at or within PML NBs (Figure 6L), suggesting that binding events predominante PML molecule mobility at or in the nuclear body.h RASTER IMAGE CORRELATION SPECTROSCOPY (RICS) The examples shown illustrate the power of RICS to determine spatial maps of concentrations, aggregation, diffusion and bind- ing of mobile molecules in living cells using readily accessible instrumentation (125). Ideally, in the assessment of biophysical parameters of mobile molecules in living specimens, one wants to know the space- resolved behavior of single molecules in terms of their kinetics and interactions and without the disturbance of the equilibrium state, as occurs in FRAP. All of these parameters are provided by RICS (125). Data acquisition in RICS is quite simple as only a 2D confocal image or time series analysis is required. The scanning encodes dynamic information within a single image, which can then be extracted using RICS. The processing of the resulting images, however, is not trivial: RICS data are computed from the power spectrum of the spatial autocorrelation function that is obtained from the intensity images by 2D fast Fourier transfor- mation algorithms (125). 3 http://www.lfd.uci.edu/globals/ (Accessed: November 17, 2017). FÖRSTER RESONANCE ENERGY TRANSFER (FRET) An abFRET example is shown in Figure  7C, where EGFP-Sumo-1 (green) and mRFP-PML I (red) are coexpressed in living cells. Two PML bodies were selected for analysis and acceptor photobleaching performed in region 1 but not in region 2 which served as internal control for non-FRET effects (Figure 7C). For quantitation, FRET efficien- cies in bleached and unbleached regions are then plotted in a bar diagram (Figure 7D). The plot indicates that FRET between EGFP-SUMO-1 and mRFP-PML-I occurred in most of the cases (mean of FRET = 5.5%; black bars in Figure 7D), while the unbleached control spots show a FRET mean value of −1.4% (gray bars in Figure 7C). The FRET efficiency distribution is significantly different from that in control regions (p < 0.001, n = 88) (Figure 7D). Thus, Sumo-1 is in close proximity to PML To measure RICS we have used a Zeiss LSM710 which conveniently provides a built-in RICS module in the ZEN microscope software. Some examples of RICS measurements are shown in Figure 6. As a positive control, a confocal time series was acquired in a subregion of a U2OS cell expressing EGFP (Figure 6A). RICS analysis then delivers a spatial correlation of this region (Figure 6B). By fitting of the correlation data with a 3D-free diffusion model, a spatially resolved diffusion coefficient map is generated (Figure 6C). This map shows that EGFP diffuses throughout the cellular volume with variable diffusion coeffi- cients ranging between 5 µm2 s−1 and 50 µm2 s−1. The mean value for EGFP in the nucleus by RICS was 25 (± 5) μm2 s−1 (n = 12) consistent with FCS data (127). The RICS approach also delivers a map of the number of detected mobile molecules in the diffu- sion analysis (Figure 6D). RICS was then applied to a U2OS cell nucleus expressing EGFP-PML (isoform IV) (Figures  6E–M). Two subregions of the 2D confocal time stack were selected for RICS analysis. RICS analysis in the nucleoplasm (Figures 6F–I) showed that the diffusion coefficient of GFP-tagged PML-IV is about one order of magnitude smaller than that of GFP alone (Figure  6H), consistent with FCS measurements (66). This May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 10 Hoischen et al. Advanced Bioimaging of PML Bodies Figure 6 | Spatial mapping of promyelocytic leukemia (PML) protein mobility in the nucleus by raster image correlation spectroscopy (RICS). FÖRSTER RESONANCE ENERGY TRANSFER (FRET) (A–D) As an introductory example, RICS was performed in a U2OS cell expressing EGFP alone. (A) Shows a subregion of the cell containing nuclear (nuc.) and cytoplasmic (cyt.) parts. The nuclear outshape is indicated by a black dashed line. For RICS analysis, a time series of GFP fluorescence images was acquired by confocal microscopy. Thus, the fluorescence intensity of each pixel is collected and the spatial autocorrelation is obtained per image (B). The image stack serves to increase the SNR and to be able to remove immobile and slow molecules. This analysis generates spatial maps of the diffusion coefficient (C) and the number of free molecules which contributed to the assessment (D). Since the shape of the spatial autocorrelation image indicates mostly freely diffusing species, the RICS data were fitted with a one-component 3D-free diffusion model yielding diffusion coefficients for EGFP in the nucleus between 10 µm2 s−1 and 50 µm2 s−1 (C). RICS was then performed similarly in a EGFP-PML-I-expressing U2OS cell (E–M). In the nucleoplasm, the diffusion coefficient of EGFP-tagged PML-I ranged between 1 µm2 s−1 and 4 µm2 s−1 (H). RICS in a region containing a large PML NB (J) still delivered acceptable spatial autocorrelation quality (K). This approach revealed a diffusion coefficient of EGFP-PML-I in or at PML bodies which was one order of magnitude lower than in the nucleoplasm (L). Bars; 5 µm. Figure 6 | Spatial mapping of promyelocytic leukemia (PML) protein mobility in the nucleus by raster image correlation spectroscopy (RICS). (A–D) As an introductory example, RICS was performed in a U2OS cell expressing EGFP alone. (A) Shows a subregion of the cell containing nuclear (nuc.) and cytoplasmic (cyt.) parts. The nuclear outshape is indicated by a black dashed line. For RICS analysis, a time series of GFP fluorescence images was acquired by confocal microscopy. Thus, the fluorescence intensity of each pixel is collected and the spatial autocorrelation is obtained per image (B). The image stack serves to increase the SNR and to be able to remove immobile and slow molecules. This analysis generates spatial maps of the diffusion coefficient (C) and the number of free molecules which contributed to the assessment (D). FÖRSTER RESONANCE ENERGY TRANSFER (FRET) Since the shape of the spatial autocorrelation image indicates mostly freely diffusing species, the RICS data were fitted with a one-component 3D-free diffusion model yielding diffusion coefficients for EGFP in the nucleus between 10 µm2 s−1 and 50 µm2 s−1 (C). RICS was then performed similarly in a EGFP-PML-I-expressing U2OS cell (E–M). In the nucleoplasm, the diffusion coefficient of EGFP-tagged PML-I ranged between 1 µm2 s−1 and 4 µm2 s−1 (H). RICS in a region containing a large PML NB (J) still delivered acceptable spatial autocorrelation quality (K). This approach revealed a diffusion coefficient of EGFP-PML-I in or at PML bodies which was one order of magnitude lower than in the nucleoplasm (L). Bars; 5 µm. binding properties of repair factors at DNA lesions (138). Live cell imaging of DNA damage foci has been used to reveal the mobility of repair proteins, their assembly timing into repair sites, and the movement of damaged chromatin (139–141). DNA damage can be induced globally by ionizing radiation or radiomimetic drugs allowing for bulk analysis of the DNA damage response at multiple sites of DNA damage in the nucleus (142). Generation of single focal spots of DNA damage is instrumental to analyze single repair sites and became possible by targeted expression of endonucle- ases or microirradiation (143). Coupling of UV-A light-emitting lasers into confocal microscopes resulted in the development of laser-microirradiation technologies (Figure 8A) (144, 145). Laser lines in the visible range spectrum (405–514 nm) as well as mul- tiphoton excitation (>750 nm) have been implemented in such devices (146). The advantages and disadvantages of the different laser systems to study cellular responses to DNA damage has been assessed (147). By fine-tuning the microirradiation system it is possible to discriminate between induction of base lesions, sin- gle–strand and double-strand DNA breaks. Special UV-suitable lenses (i.e., quartz glass) must be used to avoid energy loss and destroying the lenses. Objectives with a high numerical aperture I at PML NBs which was expected because of the covalent con- jugation of SUMO-1 to PML in nuclear bodies (134). A similar abFRET approach has previously been used to document the functional interaction between the CHFR mitotic checkpoint protein and PML within PML NBs (135). FÖRSTER RESONANCE ENERGY TRANSFER (FRET) By expanding this abFRET approach, the individual spatial relationships between many PML NB components and probably even the degree of PML SUMOylation could now be determined to obtain a full picture of the molecular interaction landscape within PML NBs. This kind of approach proved successful in detecting the spatial inter-relationships within the large human kinetochore complex (136) as well as in smaller complexes such as the nucleosome (137). Thus, adding FRET techniques to the experimental tool kits in many laboratories would significantly increase the understanding of protein-protein interaction net- works in cancer biology. LASER MICROIRRADIATION (B) Time courses of the fluorescence intensity of donor and acceptor during abFRET. Bleaching of the acceptor results in a fluorescence intensity increases of the donor indicating FRET (arrow). (C) Cell nucleus showing the location of EGFP-Sumo-1 and mRFP-PML I in PML-bodies. Two of them, spot1 and spot2, were selected for fluorescence intensity analysis before and after acceptor- photobleaching (see enlargements below). At spot 1, the acceptor fluorophore mRFP was bleached (compare prebleach and postbleach), whereas spot 2 was not bleached and served as control. (D) The donor fluorescence intensity variation observed during acceptor-photobleaching was determined for 89 not bleached control PML-bodies (see spot 2) yielding Evar (gray bars) and for 89 acceptor-photobleaching PML bodies (see spot 1) yielding EFRET (black bars). The numbers of observed single cases (grouped into Evar or EFRET value ranges of 4%) are displayed versus the values of Evar and EFRET. should be employed to achieve diffraction-limited focusing and fine micromanipulation. A starting point to plan the application of microirradiation techniques can be found here: (148, 149).h NBS1 has detached from the irradiated area and the number of PML NBs returned to preirradiation levels (Figure 8B, 4 h). The repair process has most likely been successfully completed by that time although direct evidence for successful repair is lacking. All these observations are consistent with previously reported data (40, 41). When DNA damage becomes irreparable, repair foci become permanent, as demonstrated for damaged telomeres (151). PML bodies stay stably associated with such irreparable DNA breaks (152). This phenomenon is illustrated in Figure 8C, where a U2OS cell was microirradiated at multiple locations in the nucleus with a high UV-A laser dose (40 μJ pulse−1) and stained for PML and gH2AX 24 h after damage induction. Interestingly, UV-induced DNA damage foci that colocalize with PML NBs are positionally more stable than non-colocalizing (14), suggesting that PML NBs may function to support topographic stability of DNA repair foci within chromatin. The involvement of PML NBs in cellular DNA damage response/repair pathways became evident upon the demonstra- tion of their colocalization with experimentally induced DNA damage foci (12, 13, 56, 150). UV laser microirradiation was also used in the initial studies to analyze in more detail the behavior of PML NBs in the vicinity of DNA damage in live cells (40, 41). LASER MICROIRRADIATION Experimental induction of DNA damage foci in living cells became an ideal method to analyze in time and space the recruitment and May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 11 Advanced Bioimaging of PML Bodies Hoischen et al. Figure 7 | Complex formation assessment of promyelocytic leukemia (PML) body components by acceptor-photobleaching Förster resonance energy transfer (FRET). (A) Schematic explanation of acceptor-photobleaching Förster resonance energy transfer (abFRET). The energy donor EGFP and the energy acceptor mRFP are fused to proteins X and Y, which are sufficiently close (<10 nm) to each other to allow for FRET. Left side: the acceptor mRFP absorbs radiation-free energy from the exited donor EGFP resulting in decreased donor fluorescence intensity. Right side: acceptor mRFP is bleached and energy is no longer transferred from donor EGFP to acceptor mRFP resulting in an increase of donor fluorescence intensity. (B) Time courses of the fluorescence intensity of donor and acceptor during abFRET. Bleaching of the acceptor results in a fluorescence intensity increases of the donor indicating FRET (arrow). (C) Cell nucleus showing the location of EGFP-Sumo-1 and mRFP-PML I in PML-bodies. Two of them, spot1 and spot2, were selected for fluorescence intensity analysis before and after acceptor- photobleaching (see enlargements below). At spot 1, the acceptor fluorophore mRFP was bleached (compare prebleach and postbleach), whereas spot 2 was not bleached and served as control. (D) The donor fluorescence intensity variation observed during acceptor-photobleaching was determined for 89 not bleached control PML-bodies (see spot 2) yielding Evar (gray bars) and for 89 acceptor-photobleaching PML bodies (see spot 1) yielding EFRET (black bars). The numbers of observed single cases (grouped into Evar or EFRET value ranges of 4%) are displayed versus the values of Evar and EFRET. Figure 7 | Complex formation assessment of promyelocytic leukemia (PML) body components by acceptor-photobleaching Förster resonance energy transfer (FRET). (A) Schematic explanation of acceptor-photobleaching Förster resonance energy transfer (abFRET). The energy donor EGFP and the energy acceptor mRFP are fused to proteins X and Y, which are sufficiently close (<10 nm) to each other to allow for FRET. Left side: the acceptor mRFP absorbs radiation-free energy from the exited donor EGFP resulting in decreased donor fluorescence intensity. Right side: acceptor mRFP is bleached and energy is no longer transferred from donor EGFP to acceptor mRFP resulting in an increase of donor fluorescence intensity. Frontiers in Oncology  |  www.frontiersin.org LASER MICROIRRADIATION These studies revealed intriguing morphological changes of PML NBs near the damaged chromatin, including moving toward the breaks, coalescing, and loss of positional stability. A recapitulation of these observations is shown in Figure 8B. In this experiment, a short pulse of 350 nm UV light was focused into the nucleus of a U2OS cell expressing GFP-tagged NBS1 (A DNA damage sensor protein) (green) and mRFP-tagged PML (red). As expected, NBS1 accumulates focally at the microirradiated chromatin spot within minutes. Shortly after, new PML bodies appear at the periphery of the damage focus (30 min). After 4 h, Of course, these fascinating microscopic observations remain descriptive without supporting functional studies. Previously it was shown that depletion of PML indeed decreases the ability to May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 12 Advanced Bioimaging of PML Bodies Hoischen et al. Figure 8 | Behavior of promyelocytic leukemia (PML) bodies at UV-A microbeam induced DNA damage foci. (A) For laser damage induction, a pulsed 350 nm Nd:YLF (neodymium-doped yttrium lithium fluoride) UV-A laser (Spectra Physics) was coupled into a confocal laser scanning microscope (LSM 510) via the epifluorescence illumination path. The laser-microbeam is focused into the middle of the field of view by a 100×, NA 1.3 Plan Neofluar oil immersion objective (Zeiss). The Nd:YLF laser can be frequency-tripled delivering 20 ns duration pulses at 350 nm with user-defined energies from 1 µJ to 200 µJ at user defined repetition rates 1–1000 Hz. (B) A living U2OS cell expressing EGFP-tagged NBS1 and mRFP-tagged PML-IV was irradiated at a single defined spot with approx. 5 µJ of energy using the set-up described above (yellow arrow). Confocal stacks were acquired across the nucleus before and at indicated time points after the damage pulse. In (C), U2OS cells were microirradiated at multiple positions with high laser power (40 µJ per site). Twenty-four hours after DNA damage induction cells were fixed and stained to detect the DNA damage marker gH2AX (green) and endogenous PML (red). Scale bars, 5 µm. Figure 8 | Behavior of promyelocytic leukemia (PML) bodies at UV-A microbeam induced DNA damage foci. (A) For laser damage induction, a pulsed 350 nm Nd:YLF (neodymium-doped yttrium lithium fluoride) UV-A laser (Spectra Physics) was coupled into a confocal laser scanning microscope (LSM 510) via the epifluorescence illumination path. LASER MICROIRRADIATION The laser-microbeam is focused into the middle of the field of view by a 100×, NA 1.3 Plan Neofluar oil immersion objective (Zeiss). The Nd:YLF laser can be frequency-tripled delivering 20 ns duration pulses at 350 nm with user-defined energies from 1 µJ to 200 µJ at user defined repetition rates 1–1000 Hz. (B) A living U2OS cell expressing EGFP-tagged NBS1 and mRFP-tagged PML-IV was irradiated at a single defined spot with approx. 5 µJ of energy using the set-up described above (yellow arrow). Confocal stacks were acquired across the nucleus before and at indicated time points after the damage pulse. In (C), U2OS cells were microirradiated at multiple positions with high laser power (40 µJ per site). Twenty-four hours after DNA damage induction cells were fixed and stained to detect the DNA damage marker gH2AX (green) and endogenous PML (red). Scale bars, 5 µm. perform homologeous recombination (HR) repair (15, 16), and it should also be mentioned that permanent lack of PML induces genomic instability and increased susceptibility to cancer (11). Thus it would be now interesting to fine-dissect the molecular mechanisms by which the presence of a PML NB is supportive to DNA repair events at particular DNA damage foci. A straight- forward model would be a scaffold or platform function of the bodies for efficient biochemical repair activities nearby damaged chromatin. A combination of super-resolution techniques with live cell imaging after microirradiation is an attractive approach to further study this phenomenon. and multiple traps or as optical strecher (156–159). OTs are excellent nanotools with which manipulation in a living cell or a living organism is possible without perforating the cell membrane. Further information on OT technologies can be found in Ref. (160–162). Generally OTs are used either to trap biological objects directly with light or as indirect force trans- ducers to exert linear forces via trapped microbeads. In EMFA, polyethylenimine-coated erythrocytes are used instead of beads as the “force transmitting device” for axial force application on cells (Figure 9A) (161). Here, we used EMFA to recapitulate some of the published data on PML NB behavior after global nuclear stress. Previously it had been observed that PML NBs disintegrate into many small PML-containing structures during heat shock or exposure to Cadmium2+ ions, implying that these structures undergo a stress response to altered chromatin organization or topology (163, 164). LASER MICROIRRADIATION When EMFA is applied on living cells expressing GFP- tagged PML, force is applied on chromatin located just below the erythrocyte (Figure  9A). This physical pressure induces the appearance of PML-containing microstructures within the region of force application (Figure 9B). Eventually, such micro- structures fuse with each other to form larger structures, while the native PML NBs remain positionally stable (Figure 9B). This behavior of PML microstructures occurs on a minute scale and was interpreted as evidence for a supramolecular assembly/disas- sembly model in which PML NBs are not a uniform, homogene- ous polymer, but rather are composed of units or modules that are linked together as supramolecular assemblies (4, 41). This view is supported by super-resolution analyses of the PML NB archi- tecture which revealed distinct occupation rather than uniform distribution of various PML body components in a shell-like structure (35) (Figure 10). Rapid disassembly/reassembly cycles of PML nuclear bodies upon cellular stress may be instrumental in their function as damage sensors and in genome maintenance. Frontiers in Oncology  |  www.frontiersin.org OPTICAL TWEEZER (OT): ERYTHROCYTE- MEDIATED FORCE APPLICATION (EMFA) Immediately after switching on the laser the erythrocyte is pulled toward the focus due to the gradient force of the laser light, which causes a brief physical force onto the cell. The experimental setup used here consists of a continuous wave (cw) diode pumped Nd-YAG-laser (Spectra Physics) emitting at 1064 nm. The laser beam is coupled into an inverted confocal laser scanning microscope (LSM 510, Carl Zeiss Jena) and was focused via a high numerical aperture objective (100×, 1.30 NA) into the object plane. (B) U2OS cells expressing EGFP-tagged PML-IV were subjected to EMFA as shown in (A). In phase contrast (PhC) imaging, the position of the nucleus relative to erythrocytes can be monitored during the course of the experiment (upper panels). The behavior of PML nuclear bodies was monitored by confocal sectioning (middle panels, images show maximum intensity projections). The nuclear region of force application is shown as a magnified view in the bottom panels. Arrowheads indicate de novo formation of PML NBs. Scale bar, 5 µm. Figure 10 | Super-resolution imaging of promyelocytic leukemia (PML) nuclear bodies. (A) Principle of stimulated emission depletion (STED) microscopy. In STED, two lasers are focused through a high numerical aperture objective lens. The excitation laser (green) serves to excite the fluorophore of interest similar to confocal imaging. Excitation light pulses are immediately followed by a high energy red-shifted STED beam with circularly polarized light (red). The STED light de-excites the excited fluorescence except for a small central spot due to the donut-like shape of the STED beam. This results in a subdiffraction size illumination excitation beam which can be scanned across the sample with a confocal scanner to produce super-resolved images. (B–D) Example of 3-color STED imaging of PML NBs using a Leica STED microscope. Fixed U2OS cells were immunofluorescently labeled to detect SUMO, SP100, and PML with secondary antibodies coupled to STAR-635P (green), STAR-580 (red), and Atto-490LS (blue), respectively. All dyes were depleted using the 770 nm STED laser. (B) shows one confocal section in the center of the nucleus recorded in confocal mode. (C) shows the same focal section as in (B) but recorded with the depletion laser switched on followed by deconvolution of the fluorescence signals using Huygens software (STED/decon.). OPTICAL TWEEZER (OT): ERYTHROCYTE- MEDIATED FORCE APPLICATION (EMFA) (D) The DAPI signal was also acquired in the same focal section employing the HyVolution II mode of the Leica LSM (= confocal mode with the pinhole closed to 0.5 Airy units followed by deconvolution) (Confocal/decon.). (E) 3D-STORM imaging of a PML nuclear body in U2OS cells immunofluorescently labeled with an anti-PML antibody (Secondary antibody: Alexa-647N). (F) Super-resolution SIM imaging of a PML nuclear body in U2OS cells immunofluorescently labeled with an anti-PML antibody (Secondary antibody: Cy3). STORM and SIM imaging was performed using a Zeiss Elyra system. Figure 10 | Super-resolution imaging of promyelocytic leukemia (PML) nuclear bodies. (A) Principle of stimulated emission depletion (STED) microscopy. In STED, two lasers are focused through a high numerical aperture objective lens. The excitation laser (green) serves to excite the fluorophore of interest similar to confocal imaging. Excitation light pulses are immediately followed by a high energy red-shifted STED beam with circularly polarized light (red). The STED light de-excites the excited fluorescence except for a small central spot due to the donut-like shape of the STED beam. This results in a subdiffraction size illumination excitation beam which can be scanned across the sample with a confocal scanner to produce super-resolved images. (B–D) Example of 3-color STED imaging of PML NBs using a Leica STED microscope. Fixed U2OS cells were immunofluorescently labeled to detect SUMO, SP100, and PML with secondary antibodies coupled to STAR-635P (green), STAR-580 (red), and Atto-490LS (blue), respectively. All dyes were depleted using the 770 nm STED laser. (B) shows one confocal section in the center of the nucleus recorded in confocal mode. (C) shows the same focal section as in (B) but recorded with the depletion laser switched on followed by deconvolution of the fluorescence signals using Huygens software (STED/decon.). (D) The DAPI signal was also acquired in the same focal section employing the HyVolution II mode of the Leica LSM (= confocal mode with the pinhole closed to 0.5 Airy units followed by deconvolution) (Confocal/decon.). (E) 3D-STORM imaging of a PML nuclear body in U2OS cells immunofluorescently labeled with an anti-PML antibody (Secondary antibody: Alexa-647N). (F) Super-resolution SIM imaging of a PML nuclear body in U2OS cells immunofluorescently labeled with an anti-PML antibody (Secondary antibody: Cy3). STORM and SIM imaging was performed using a Zeiss Elyra system. OPTICAL TWEEZER (OT): ERYTHROCYTE- MEDIATED FORCE APPLICATION (EMFA) SUPER-RESOLUTION MICROSCOPY (SRM) The resolution of a light microscope is limited to about 200 nm by several SRM approaches have been established over past decade which improve resolution by a factor of 2–10, depending on the technique. Meanwhile, three main super-resolution technolo- Figure 9 | Optical tweezer (OT) as a tool to analyze PML nuclear body assembly. (A) Schematic depiction of erythrocyte-mediated force application (EMFA) based on OTs. Polyethylenimine coated erythrocytes attach unspecifically to the surfaces of the adherent target cells. Erythrocytes serve as very efficient “force transmitting devices” for axial force application on cells. The cell layer is moved into the region of the desired position in such a way that the laser focus (yellow ellipse) locates slightly below the erythrocyte. Immediately after switching on the laser the erythrocyte is pulled toward the focus due to the gradient force of the laser light, which causes a brief physical force onto the cell. The experimental setup used here consists of a continuous wave (cw) diode pumped Nd-YAG-laser (Spectra Physics) emitting at 1064 nm. The laser beam is coupled into an inverted confocal laser scanning microscope (LSM 510, Carl Zeiss Jena) and was focused via a high numerical aperture objective (100×, 1.30 NA) into the object plane. (B) U2OS cells expressing EGFP-tagged PML-IV were subjected to EMFA as shown in (A). In phase contrast (PhC) imaging, the position of the nucleus relative to erythrocytes can be monitored during the course of the experiment (upper panels). The behavior of PML nuclear bodies was monitored by confocal sectioning (middle panels, images show maximum intensity projections). The nuclear region of force application is shown as a magnified view in the bottom panels. Arrowheads indicate de novo formation of PML NBs. Scale bar, 5 µm. Figure 9 | Optical tweezer (OT) as a tool to analyze PML nuclear body assembly. (A) Schematic depiction of erythrocyte-mediated force application (EMFA) based on OTs. Polyethylenimine coated erythrocytes attach unspecifically to the surfaces of the adherent target cells. Erythrocytes serve as very efficient “force transmitting devices” for axial force application on cells. The cell layer is moved into the region of the desired position in such a way that the laser focus (yellow ellipse) locates slightly below the erythrocyte. OPTICAL TWEEZER (OT): ERYTHROCYTE- MEDIATED FORCE APPLICATION (EMFA) Since their introduction in 1986 by Ashkin et al. (153), OTs have developed rapidly over the past decades (154). OTs are today widely used tools in physics, chemistry, biological, and medical research (155). OTs are applicable to objects at nanometer up to several micrometer size ranges. The simplest form to use OTs is by focusing a laser beam using an objective lens of high numerical aperture (Figure 9A). As the rear pupil of the objective must be entirely illuminated, the diameter of the laser beam is expanded by telescope optics before directed to the microscope. Dielectric particles such as small biological objects near the focus will mainly experience two forces: radiation pressure in the direction of light propagation and gradient forces in the direction of the spatial light gradient. The balancing of both forces is required. The equilibrium position of particles in the focus is given if gradi- ent force dominates over the scattering force.h There are also several setup variants: conventional OT with standard Gaussian laser beam, non-Gaussian laser beams based on a Bessel beam or a Laguerre–Gaussian mode, dual beams, May 2018  |  Volume 8  |  Article 125 13 Advanced Bioimaging of PML Bodies Hoischen et al. Figure 10 | Super-resolution imaging of promyelocytic leukemia (PML) nuclear bodies. (A) Principle of stimulated emission depletion (STED) microscopy. In STED, two lasers are focused through a high numerical aperture objective lens. The excitation laser (green) serves to excite the fluorophore of interest similar to confocal imaging. Excitation light pulses are immediately followed by a high energy red-shifted STED beam with circularly polarized light (red). The STED light de-excites the excited fluorescence except for a small central spot due to the donut-like shape of the STED beam. This results in a subdiffraction size illumination excitation beam which can be scanned across the sample with a confocal scanner to produce super-resolved images. (B–D) Example of 3-color STED imaging of PML NBs using a Leica STED microscope. Fixed U2OS cells were immunofluorescently labeled to detect SUMO, SP100, and PML with secondary antibodies coupled to STAR-635P (green), STAR-580 (red), and Atto-490LS (blue), respectively. All dyes were depleted using the 770 nm STED laser. (B) shows one confocal section in the center of the nucleus recorded in confocal mode. OPTICAL TWEEZER (OT): ERYTHROCYTE- MEDIATED FORCE APPLICATION (EMFA) (C) shows the same focal section as in (B) but recorded with the depletion laser switched on followed by deconvolution of the fluorescence signals using Huygens software (STED/decon.). (D) The DAPI signal was also acquired in the same focal section employing the HyVolution II mode of the Leica LSM (= confocal mode with the pinhole closed to 0.5 Airy units followed by deconvolution) (Confocal/decon.). (E) 3D-STORM imaging of a PML nuclear body in U2OS cells immunofluorescently labeled with an anti-PML antibody (Secondary antibody: Alexa-647N). (F) Super-resolution SIM imaging of a PML nuclear body in U2OS cells immunofluorescently labeled with an anti-PML antibody (Secondary antibody: Cy3). STORM and SIM imaging was performed using a Zeiss Elyra system. Figure 9 | Optical tweezer (OT) as a tool to analyze PML nuclear body assembly. (A) Schematic depiction of erythrocyte-mediated force application (EMFA) based on OTs. Polyethylenimine coated erythrocytes attach unspecifically to the surfaces of the adherent target cells. Erythrocytes serve as very efficient “force transmitting devices” for axial force application on cells. The cell layer is moved into the region of the desired position in such a way that the laser focus (yellow ellipse) locates slightly below the erythrocyte. Immediately after switching on the laser the erythrocyte is pulled toward the focus due to the gradient force of the laser light, which causes a brief physical force onto the cell. The experimental setup used here consists of a continuous wave (cw) diode pumped Nd-YAG-laser (Spectra Physics) emitting at 1064 nm. The laser beam is coupled into an inverted confocal laser scanning microscope (LSM 510, Carl Zeiss Jena) and was focused via a high numerical aperture objective (100×, 1.30 NA) into the object plane. (B) U2OS cells expressing EGFP-tagged PML-IV were subjected to EMFA as shown in (A). In phase contrast (PhC) imaging, the position of the nucleus relative to erythrocytes can be monitored during the course of the experiment (upper panels). The behavior of PML nuclear bodies was monitored by confocal sectioning (middle panels, images show maximum intensity projections). The nuclear region of force application is shown as a magnified view in the bottom panels. Arrowheads indicate de novo formation of PML NBs. Scale bar, 5 µm. SUPER-RESOLUTION MICROSCOPY (SRM) several SRM approaches have been established over past decade which improve resolution by a factor of 2–10, depending on the technique. Meanwhile, three main super-resolution technolo- gies are commercially available, namely structured illumination microscopy (SIM), single molecule localization (SML), and stimulated emission depletion (STED) (94). The resolution of a light microscope is limited to about 200 nm by diffraction (165). The microscopic images of small cellular orga- nelles or nuclear bodies in this size range therefore appear blurred and their morphological details go undetected. Fortunately, May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 14 Advanced Bioimaging of PML Bodies Hoischen et al. Structured illumination microscopy is a versatile and the most gentle super-resolution approach which increases the resolution by up to twofold in lateral and axial direction (166, 167). This is achieved by illuminating the sample with a grid pattern. The pat- tern can for example be generated by laser light passing through a movable optical grating which is projected via the objective onto the sample (168). The interference of the pattern with sample structures allows access to high frequency or in other words high-resolution information that would be otherwise obscured in a normal wide field image. SIM requires at least 9 images (2D- SIM) or 15 images (3D-SIM) to be taken for each optical section, whereby the illumination pattern is phase shifted and rotated in order to access the high-resolution information by sophisticated algorithms (168). The advantage of SIM is that it is compatible with all fluorescent dyes, making even super-resolved multicolor live-cell imaging feasible (169).l subdiffraction-sized fluorescence spot in the center of the donut (179, 180) (Figure 10A). Interestingly, the first report on super- resolution light microscopy of PML nuclear bodies was not based on the three SRM methods described above but was realized with the so-called 4Pi microscope developed by Hell et al. (179). Four-Pi fluorescence laser-scanning microscopy studies revealed that during interphase PML NBs adopt a spherical organization characterized by the assembly of different PML body components into distinct, partially overlapping patches within a 50–100-nm thick shell (35). The spherical organization of PML NBs had been observed already before by electron microscopy (36, 48), but 4Pi allowed for simultaneous pair-wise detection of two PML body components. One example of STED nanoscopy on PML NBs is shown in Figures 10B–D. SUPER-RESOLUTION MICROSCOPY (SRM) The three major PML NB constituents SUMO, SP100 and PML were immunolabeled in U2OS cells with differ- ent fluorophores and imaged in confocal as well as in STED mode to visualize the improvement in optical resolution through STED (Figures 10B,C, respectively). As expected, STED reveals that these proteins decorate distinct, yet partially overlapping patches in the peripheral shell of the PML NB (Figure  10C). Super- imposition of the STED image with the DAPI pattern of the same confocal section confirms the absence of chromatin in the core of normal PML NBs (Figure 10D) (36). We also applied STORM and SIM imaging of PML in U2OS cells. STORM is similarly well suited to reveal the shell morphology of PML protein distribution (Figure 10E) while the resolution in SIM is, as expected, consider- ably lower than in STED or STORM (Figure 10F). However, since the laser load is much less, SIM would be better suited for live cell super-resolved imaging of PML nuclear body morphology, i.e., in the analyses of fission and fusion events of PML microstructures in stress conditions (Figure 9) or DNA at damage foci (Figure 8). In conclusion, this section shows that with commercially avail- able SRM microscopes the analysis of biomolecules can be lifted to a new optical dimension. In SML switching of molecules between two distinct fluores- cent states, normally an “on” and an “off” state is used to determine the exact position of a fluorescent molecule by determining the center of mass within the blurry fluorescent spot. The blinking is thereby adjusted to have at average only one molecule in its fluorescent state within the diffraction limited spot. The concept of blinking was realized using photoactivatable dyes, such as paGFP in photoactivated localization microscopy (PALM) and fluorescence PALM, or by using photoswitchable dye pairs (such as Cy3–Cy5 or EosFPs) as in stochastic optical reconstruction microscopy (STORM). Although PALM was established using fluorescence proteins, it was soon realized that any organic dye under appropriate reducing conditions can be brought to on and off switch cycles, a technology termed dSTORM (170). In PALM/STORM, a series of several thousand images from the blinking specimen are recorded and mathematically pro- cessed into high-resolution images reaching resolutions below 30 nm in the lateral direction (171, 172). SML approaches have the inherent disadvantage that typically (ten)thousands of frames need to be acquired to reconstruct a single super-resolved image. 4 http://www.eurobioimaging.eu/ (Accessed: January 12, 2018). 5 http://www.eurobioimaging.eu/global-bioimaging (Accessed: January 12, 2018). SUPER-RESOLUTION MICROSCOPY (SRM) The entailed low temporal resolution, extended exposure with high excitation power and associated phototoxicity render these methods less suitable for live cell imaging.l Frontiers in Oncology  |  www.frontiersin.org OUTLOOK We believe that many biochemical or molecular biology ori- ented research labs are still not aware of the multitude of new and exciting microscopic methods and their capabilities. The aim of this contribution was to present recent advances in bio- imaging in combination with selected application examples in PML nuclear body biology. Here we have illustrated the power of imaging methods and provide a guide to these techniques to make them more accessible to a larger number of labs involved in oncogene or tumor suppressor research. We have presented several experimental examples feasible in our imaging facil- ity, yet the number of additional techniques is much higher. Bioimaging facility networks have been established in several countries worldwide and these can be approached with specific imaging requests. A source for comprehensive bioimaging methodology is available Europe-wide4 and a global bioimaging network project may be realized in the near future.5 More recently developed fluctuation microscopy (SOFI, SIRF) approaches in part overcome these limitations at the expense of much lower resolution increase (173, 174). Nevertheless, live cell imaging using SML has been reported (175). Optical resolution in STED usually is well below 50 nm in fixed samples and ca. 70 nm in live-cell experiments (94). A more in depth explanation on the theory and on practical applications of SIM, SML, and STED can be found here: (176, 177). Possible practical limita- tions and compromises that must be considered when designing super-resolution experiments have been pointed out by Lambert and Waters (178). Stimulated emission depletion is based on the application of two laser beams in a confocal (point-scanning) set-up. The STED depletion laser is delivered into the optical path through a phase filter, which creates a donut-shaped beam on the confocal fluorescence spot by controlled de-excitation of the previously excited fluorophore (Figure  10A). The high intensity STED beam extinguishes the peripheral fluorescence signal, leaving a May 2018  |  Volume 8  |  Article 125 15 Advanced Bioimaging of PML Bodies Hoischen et al. in certain stem cell niches, these nuclear bodies could be imaged and functionally analyzed in various living spheroid or organoid stem cell systems using a combination of multicolor lightsheet and super-resolution approaches (187, 188). In the same experimental setting, laser-assisted ablation of single PML NB-expressing cells could help to identify PML-mediated mechanisms of stem cell plasticity (189). FUNDING This work was supported by grant HE 2484/3-1 to PH from the Deutsche Forschungsgemeinschaft. This work was supported by grant HE 2484/3-1 to PH from the Deutsche Forschungsgemeinschaft. OUTLOOK Seeing is believing and therefore we look forward to monitor PML nuclear body biochemistry through new imaging set-ups in real time in living cells in the future. Local, regional, national, and supranational imaging networks will continue to develop with the aim to provide access, service and training to state-of-the-art imaging technologies. Only such dedicated facility infrastructures and/or very specialized imaging research labs will be able to cope with the fast development of novel microscopy techniques. Although probably a demanding task, both, the facility members as well as basic research scientists are now in charge to synergistically work together to fully exploit the powerful imaging tools in the study of molecular and cellular mechanisms. AUTHOR CONTRIBUTIONS CH, SM, KW, and PH prepared the figures and wrote the text. ACKNOWLEDGMENTS We apologize to all authors who’s excellent articles in the field of PML body biology and microscopy techniques could not be cited in this contribution due to space limitations. We would like to thank the following colleagues for their time and effort in helping to establish the microscopy techniques described in our facility: Stephanie Weidtkamp-Peters, Lars Schmiedeberg, Almut Horch, Sandra Münch, Sandra Orthaus, Karolin Klement, Paulius Grigaravicius, Daniela Hellwig, Tobias Ulbricht, Volker Döring, Otto Greulich, Friedrich Haubensak, Eberhard Schmitt, Frank Große, and Stephan Diekmann. We would like to thank Debra Weih for proof-reading of the manuscript. More physiologically, it would be seminal to investigate PML NBs in their most physiological setting, the living model organism. A combination of confocal microscopy and/or nanoscopy with adaptive optics for better tissue penetration (185, 186) would enable monitoring of fluorescent PML NBs in living tissue such as skin or brain of GFP-PML knock-in mice under normal vs. stress condi- tions (irradiation, chemicals). Since PML has an established role AUTHOR NOTE We have also summarized the current knowledge on the potential functions and assembly of PML nuclear bodies. PML has been analyzed using wet-lab and genetic techniques on one hand and imaging methods on the other. With the new microscopy methods now at hand it will be exciting to see the two different approaches merging. For example, a combination of STED and FCS (STED-FCS) (181), should make it possible to assess biophysical and binding properties of PML-interacting partners within PML NBs. This would help (i) to understand the molecular/biochemical events occurring molecularly at PML NBs at sites of DNA damage and (ii) to better visualize/understand the proposed phase separation function of PML NBs (68). For exam- ple, single-molecule tracking at nanoscale resolution has recently been employed to demonstrate the liquid droplet nature of stress granules in the cell nucleus (182). As nanoscopy will become less phototoxic in the future (183), super-resolution imaging of APBs in living cells will shed more light on the mechanisms of DNA recombination events which occur in PML NBs during telomere elongation in ALT cancer cells (184). This contribution is dedicated to Jörg Langowski. REFERENCES 8. Gurrieri C, Capodieci P, Bernardi R, Scaglioni PP, Nafa K, Rush LJ, et  al. Loss of the tumor suppressor PML in human cancers of multiple histologic origins. J Natl Cancer Inst (2004) 96:269–79. doi:10.1093/jnci/ djh043 1. Melnick A, Licht JD. Deconstructing a disease: RARα, its fusion partners, and their roles in the pathogenesis of acute promyelocytic leukemia. Blood (1999) 93:3167–215. 1. Melnick A, Licht JD. Deconstructing a disease: RARα, its fusion partners, and their roles in the pathogenesis of acute promyelocytic leukemia. Blood (1999) 93:3167–215. 9. Sahin U, Ferhi O, Jeanne M, Benhenda S, Berthier C, Jollivet F, et al. Oxidative stress-induced assembly of PML nuclear bodies controls sumoylation of part- ner proteins. J Cell Biol (2014) 204(6):931–45. doi:10.1083/jcb.201305148 h 9. Sahin U, Ferhi O, Jeanne M, Benhenda S, Berthier C, Jollivet F, et al. Oxidative stress-induced assembly of PML nuclear bodies controls sumoylation of part- ner proteins. J Cell Biol (2014) 204(6):931–45. doi:10.1083/jcb.201305148 h 2. Eskiw CH, Dellaire G, Bazett-Jones DP. Chromatin contributes to structural integrity of promyelocytic leukemia bodies through a SUMO-1- independent mechanism. J Biol Chem (2004) 279:9577–85. doi:10.1074/jbc. M312580200 2. Eskiw CH, Dellaire G, Bazett-Jones DP. Chromatin contributes to structural integrity of promyelocytic leukemia bodies through a SUMO-1- independent mechanism. J Biol Chem (2004) 279:9577–85. doi:10.1074/jbc. M312580200 10. Guan D, Kao HY. The function, regulation and therapeutic implications of the tumor suppressor protein, PML. Cell Biosci (2015) 5:60. doi:10.1186/ s13578-015-0051-9 10. Guan D, Kao HY. The function, regulation and therapeutic implications of the tumor suppressor protein, PML. Cell Biosci (2015) 5:60. doi:10.1186/ s13578-015-0051-9 3. Hodges M, Tissot C, Howe K, Grimwade D, Freemont PS. Structure, organi- zation, and dynamics of promyelocytic leukemia protein nuclear bodies. Am J Hum Genet (1998) 63:297–304. doi:10.1086/301991 11. Zhong S, Hu P, Ye TZ, Stan R, Ellis NA, Pandolfi PP. A role for PML and the nuclear body in genomic stability. Oncogene (1999) 18:7941–7. doi:10.1038/ sj.onc.1203367 4. Dellaire G, Bazett-Jones DP. PML nuclear bodies: dynamic sensors of DNA damage and cellular stress. Bioessays (2004) 26:963–77. doi:10.1002/ bies.20089 i 4. Dellaire G, Bazett-Jones DP. PML nuclear bodies: dynamic sensors of DNA damage and cellular stress. Bioessays (2004) 26:963–77. doi:10.1002/ bies.20089 12. Carbone R, Pearson M, Minucci S, Pelicci PG. PML NBs associate with the hMre11 complex and p53 at sites of irradiation induced DNA damage. Oncogene (2002) 21(11):1633–40. doi:10.1038/sj.onc.1205227 5. Bernardi R, Pandolfi PP. REFERENCES PML body meets telomere: the begin- ning of an ALTernate ending? Nucleus (2012) 3:263–75. doi:10.4161/nucl.20326 h 26. Tatham MH, Jaffray E, Vaughan OA, Desterro JM, Botting CH, Naismith JH, et al. Polymeric chains of SUMO-2 and SUMO-3 are conjugated to protein substrates by SAE1/SAE2 and Ubc9. J Biol Chem (2001) 276:35368–74. doi:10.1074/jbc.M104214200 48. Lallemand-Breitenbach V, de Thé H. PML nuclear bodies. Cold Spring Harb Perspect Biol (2010) 2(5):a000661. doi:10.1101/cshperspect.a000661 i 49. Bernardi R, Papa A, Pandolfi PP. Regulation of apoptosis by PML and the PMLNBs. Oncogene (2008) 27:6299–631. doi:10.1038/onc.2008.305 27. Condemine W, Takahashi Y, Zhu J, Puvion-Dutilleul F, Guegan S, Janin A, et al. Characterization of endogenous humanpromyelocyticl eukemia iso- forms. Cancer Res (2006) 66:6192–8. doi:10.1158/0008-5472.CAN-05-3792 50. Lallemand-Breitenbach V, Zhu J, Puvion F, Koken M, Honorè N, Doubeikovsky A, et al. Role of promyelocytic leukemia (PML) sumolation in nuclear body formation, 11S proteasome recruitment, and As2O3-induced PML or PML/retinoic acid receptor alpha degradation. J Exp Med (2001) 193(12):1361–71. doi:10.1084/jem.193.12.1361 h 28. Schmitz ML, Grishina I. Regulation of the tumor suppressor PML by sequen- tial post-translational modifications. Front Oncol (2012) 2:204. doi:10.3389/ fonc.2012.00204 51. Ivanschitz L, De Thè H, Le Bras M. PML, SUMOylation, and senescence. Front Oncol (2013) 3:171. doi:10.3389/fonc.2013.00171 f 29. Brand P, Lenser T, Hemmerich P. Assembly dynamics of PML nuclear bodies in living cells. PMC Biophys (2010) 3:3. doi:10.1186/1757-5036-3-3 52. Salomoni P. Stemming out of a new PML era? Cell Death Differ (2009) 16(8):1083–92. doi:10.1038/cdd.2009.63 30. Beech SJ, Lethbridge KJ, Killick N, McGlincy N, Leppard KN. Isoforms of the promyelocytic leukemia protein differ in their effects on ND10 organization. Exp Cell Res (2005) 307:109–17. doi:10.1016/j.yexcr.2005.03.012 53. Zhou W, Bao S. PML-mediated signaling and its role in cancer stem cells. Oncogene (2014) 33(12):1475–84. doi:10.1038/onc.2013.111 ih 31. Cuchet D, Sykes A, Nicolas A, Orr A, Murray J, Sirma H, et al. PML isoforms I and II participate in PML-dependent restriction of HSV-1 replication. J Cell Sci (2011) 124:280–91. doi:10.1242/jcs.075390 54. Zhong S, Salomoni P, Pandolfi PP. The transcriptional role of PML and the nuclear body. Nat Cell Biol (2000) 2(5):E85–90. doi:10.1038/35010583 55. Hofmann TG, Will H. Body language: the function of PML nuclear bodies in apoptosis regulation. Cell Death Differ (2003) 10(12):1290–9. doi:10.1038/ sj.cdd.4401313 32. Geng Y, Monajembashi S, Shao A, Cui D, He W, Chen Z, et al. Contribution of the C-terminal regions of promyelocytic leukemia protein (PML) isoforms II and V to PML nuclear body formation. REFERENCES Structure, dynamics and functions of promyelo- cytic leukaemia nuclear bodies. Nat Rev Mol Cell Biol (2007) 8:1006–16. doi:10.1038/nrm2277 5. Bernardi R, Pandolfi PP. Structure, dynamics and functions of promyelo- cytic leukaemia nuclear bodies. Nat Rev Mol Cell Biol (2007) 8:1006–16. doi:10.1038/nrm2277 13. Bøe SO, Haave M, Jul-Larsen A, Grudic A, Bjerkvig R, Lønning PE. Promyelocytic leukemia nuclear bodies are predetermined processing sites for damaged DNA. J Cell Sci (2006) 119(Pt 16):3284–95. doi:10.1242/ jcs.03068 6. Mu ZM, Le XF, Vallian S, Glassman AB, Chang KS. Stable overexpression of PML alters regulation of cell cycle progression in HeLa cells. Carcinogenesis (1997) 18:2063–9. doi:10.1093/carcin/18.11.2063 14. Foltánková V, Matula P, Sorokin D, Kozubek S, Bártová E. Hybrid detectors improved time-lapse confocal microscopy of PML and 53BP1 nuclear body colocalization in DNA lesions. Microsc Microanal (2013) 19:360–9. doi:10.1017/S1431927612014353 7. Wang ZG, Delva L, Gaboli M, Rivi R, Giorgio M, Cordon-Cardo C, et al. Role of PML in cell growth and the retinoic acid pathway. Science (1998) 279:1547–51. doi:10.1126/science.279.5356.1547 May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 16 Hoischen et al. Advanced Bioimaging of PML Bodies 15. Boichuk S, Hu L, Makielski K, Pandolfi PP, Gjoerup OV. Functional connec- tion between Rad51 and PML in homology-directed repair. PLoS One (2011) 6(10):e25814. doi:10.1371/journal.pone.0025814 38. Yeager TR, Neumann AA, Englezou A, Huschtscha LI, Noble JR, Reddel RR. Telomerase-negative immortalized human cells contain a novel type of promyelocytic leukemia (PML) body. Cancer Res (1999) 59:4175–9. 16. Yeung PL, Denissova NG, Nasello C, Hakhverdyan Z, Chen JD, Brenneman MA. Promyelocytic leukemia nuclear bodies support a late step in DNA dou- ble-strand break repair by homologous recombination. J Cell Biochem (2012) 113:1787–99. doi:10.1002/jcb.24050 39. Luciani JJ, Depetris D, Usson Y, Metzler-Guillemain C, Mignon-Ravix C, Mitchell MJ, et al. PML nuclear bodies are highly organised DNA-protein structures with a function in heterochromatin remodelling at the G2 phase. J Cell Sci (2006) 119:2518–31. doi:10.1242/jcs.02965 17. Legartová S, Sehnalová P, Malyšková B, Küntziger T, Collas P, Cmarko D, et  al. Localized movement and levels of 53BP1 protein are changed by γ-irradiation in PML deficient cells. J Cell Biochem (2016) 117:2583–96. doi:10.1002/jcb.25551 40. Dellaire G, Eskiw CH, Dehghani H, Ching RW, Bazett-Jones DP. Mitotic accumulations of PML protein contribute to the re-establishment of PML nuclear bodies in G1. J Cell Sci (2006) 119(Pt 6):1034–42. doi:10.1242/ jcs.02817 41. REFERENCES Dellaire G, Ching RW, Ahmed K, Jalali F, Tse KC, Bristow RG, et  al. Promyelocytic leukemia nuclear bodies behave as DNA damage sensors whose response to DNA double-strand breaks is regulated by NBS1 and the kinases ATM, Chk2, and ATR. J Cell Biol (2006) 175:55–66. doi:10.1083/jcb.200604009 18. Chang HR, Munkhjargal A, Kim MJ, Park SY, Jung E, Ryu JH, et al. The functional roles of PML nuclear bodies in genome maintenance. Mutat Res (2017). doi:10.1016/j.mrfmmm.2017.05.002 j 19. Gamell C, Jan Paul P, Haupt Y, Haupt S. PML tumour suppression and beyond: therapeutic implications. FEBS Lett (2014) 588:2653–62. doi:10.1016/j. febslet.2014.02.007 42. Ching G, Dehghani RW, Ren HY, Bazett-Jones DP. The number of PML nuclear bodies increases in early S phase by a fission mechanism. J Cell Sci (2006) 119:1026–33. doi:10.1242/jcs.02816 h 20. Liu Z, Lavis LD, Betzig E. Imaging live-cell dynamics and structure at the single-molecule level. Mol Cell (2015) 58:644–59. doi:10.1016/j. molcel.2015.02.033 43. Dellaire G, Farrall R, Bickmore WA. The Nuclear Protein Database (NPD): sub-nuclear localisation and functional annotation of the nuclear proteome. Nucleic Acids Res (2003) 31:328–30. doi:10.1093/nar/gkg018 h 21. Jensen K, Shiels C, Freemont PS. PML protein isoforms and the RBCC/TRIM motif. Oncogene (2001) 20:7223–33. doi:10.1038/sj.onc.1204765 44. Mohamad N, Bodén M. The proteins of intra-nuclear bodies: a data-driven analysis of sequence, interaction and expression. BMC Syst Biol (2010) 4:44. doi:10.1186/1752-0509-4-44 22. Nisole S, Maroui MA, Mascle XH, Aubry M, Chelbi-Alix MK. Differential roles of PML isoforms. Front Oncol (2013) 3:1–17. doi:10.3389/fonc.2013.00125 h 23. Reymond A, Meroni G, Fantozzi A, Merla G, Cairo S, Luzi L, et al. The tripar- tite motif family identifies cell compartments. EMBO J (2001) 20:2140–51. doi:10.1093/emboj/20.9.2140 45. Van Damme E, Laukens K, Dang TH, Van Ostade X. A manually curated network of the PML nuclear body interactome reveals an important role for PML-NBs in SUMOylation dynamics. Int J Biol Sci (2010) 6:51–67. doi:10.7150/ijbs.6.51 24. Kamitani T, Kito K, Nguyen HP, Wada H, Fukuda-Kamitani T, Yeh ET. Identification of three major sentrinization sites in PML. J Biol Chem (1998) 273:26675–82. 46. Negorev D, Maul GG. Cellular proteins localized at and interacting within ND10/PML nuclear bodies/PODs suggest functions of a nuclear depot. Oncogene (2001) 20:7234–42. doi:10.1038/sj.onc.1204764 25. Flotho A, Melchior F. Sumoylation: a regulatory protein modification in health and disease. Annu Rev Biochem (2013) 82:357–85. doi:10.1146/ annurev-biochem-061909-093311 f 47. Chung I, Osterwald S, Deeg KI, Rippe K. REFERENCES J Biol Chem (2012) 287(36):30729–42. doi:10.1074/jbc.M112.374769 56. Varadaraj A, Dovey CL, Laredj L, Ferguson B, Alexander CE, Lubben N, et al. Evidence for the receipt of DNA damage stimuli by PML nuclear domains. J Pathol (2007) 211(4):471–80. doi:10.1002/path.2126 33. Li C, Peng Q, Wan X, Sun H, Tang J. C-terminal motifs in promyelocytic leukemia protein isoforms critically regulate PML nuclear body formation. J Cell Sci (2017) 130:3496–506. doi:10.1242/jcs.202879 57. Marchesini M, Matocci R, Tasselli L, Cambiaghi V, Orleth A, Furia L, et al. PML is required for telomere stability in non-neoplastic human cells. Oncogene (2016) 35:1811–21. doi:10.1038/onc.2015.246 h 34. de Thè G, Riviére M, Bernhard W. Examen au microscope e’lectronique de la tumeur VX2 du lapin domestique de´rive´e du papillome de Shope. Bull Cancer (1960) 47:570–84. h 58. Salomoni P. The PML-interacting protein DAXX: histone loading gets into the picture. Front Oncol (2013) 3:152. doi:10.3389/fonc.2013.00152 35. Lang M, Jegou T, Chung I, Richter K, Münch S, Udvarhelyi A, et al. Three- dimensional organization of promyelocytic leukemia nuclear bodies. J Cell Sci (2010) 123:392–400. doi:10.1242/jcs.053496 59. Tavalai N, Stamminger T. New insights into the role of the subnuclear struc- ture ND10 for viral infection. Biochim Biophys Acta (2008) 1783(11):2207–21. doi:10.1016/j.bbamcr.2008.08.004 j 36. Boisvert FM, Hendzel MJ, Bazett-Jones DP. Promyelocytic leukemia (PML) nuclear bodies are protein structures that do not accumulate RNA. J Cell Biol (2000) 148:283–92. doi:10.1083/jcb.148.2.283 60. Dellaire G, Bazett-Jones DP. Beyond repair foci: subnuclear domains and the cellular response to DNA damage. Cell Cycle (2007) 15:1864–72. doi:10.4161/ cc.6.15.4560 37. Torok D, Ching RW, Bazett-Jones DP. PML nuclear bodies as sites of epigen- etic regulation. Front Biosci (2009) 14:1325–36. doi:10.2741/3311 61. Borden KL, Culjkovic B. Perspectives in PML: a unifying framework for PML function. Front Biosci (Landmark Ed) (2009) 14:497–509. doi:10.2741/3258 May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 17 Hoischen et al. Advanced Bioimaging of PML Bodies 62. Rajendra TK, Praveen K, Matera AG. Genetic analysis of nuclear bodies: from nondeterministic chaos to deterministic order. Cold Spring Harb Symp Quant Biol (2010) 75:365–74. doi:10.1101/sqb.2010.75.043h 85. Bischof O, Kirsh O, Pearson M, Itahana K, Pelicci PG, Dejean A. Deconstructing PMLinduced premature senescence. EMBO J (2002) 21:3358–69. doi:10.1093/emboj/cdf341 63. Sahin U, Lallemand-Breitenbach V, de The H. PML nuclear bodies: regu- lation, function and therapeutic perspectives. J Pathol (2014) 234:289–91. doi:10.1002/path.4426 86. Mallette FA, Goumard S, Gaumont-Leclerc MF, Moiseeva O, Ferbeyre G. REFERENCES Chen YC, Kappel C, Beaudouin J, Eils R, Spector DL. Live cell dynamics of promyelocytic leukemia nuclear bodies upon entry into and exit from mitosis. Mol Biol Cell (2008) 19(7):3147–62. doi:10.1091/mbc.E08-01-0035 72. Jul-Larsen A, Grudic A, Bjerkvig R, Bøe SO. Cell cycle regulation and dynamics of cytoplasmic compartments containing the promyelocytic leu- kemia protein and nucleoporins. J Cell Sci (2009) 122:1201–10. doi:10.1242/ jcs.040840 94. Sahl SJ, Hell SW, Jakobs S. Fluorescence nanoscopy in cell biology. Nat Rev Mol Cell Biol (2017) 18:685–701. doi:10.1038/nrm.2017.71 l 95. Weidemann T, Mücksch J, Schwille P. Fluorescence fluctuation microscopy: a diversified arsenal of methods to investigate molecular dynamics inside cells. Curr Opin Struct Biol (2014) 28:69–76. doi:10.1016/j.sbi.2014.07.008 ll 73. Lång A, Eriksson J, Schink KO, Lång E, Blicher P, Połeć A, et al. Visualization of PML nuclear import complexes reveals FG-repeat nucleoporins at cargo retrieval sites. Nucleus (2017) 8:404–20. doi:10.1080/19491034.2017.1306161 96. Bag N, Wohland T. Imaging fluorescence fluctuation spectroscopy: new tools for quantitative bioimaging. Annu Rev Phys Chem (2014) 65:225–48. doi:10.1146/annurev-physchem-040513-103641 74. Hillestad LK. Acute promyelocytic leukemia. Acta Med Scand (1957) 159:189–94. doi:10.1111/j.0954-6820.1957.tb00124.x 97. Wachsmuth M, Conrad C, Bulkescher J, Koch B, Mahen R, Isokane M, et al. High-throughput fluorescence correlation spectroscopy enables analysis of proteome dynamics in living cells. Nat Biotechnol (2015) 33(4):384–9. doi:10.1038/nbt.3146 75. Goddard AD, Borrow J, Freemont PS, Solomon E. Characterization of a zinc finger gene disrupted by the t(15,17) in acute promyelocytic leukemia. Science (1991) 254:1371–4. doi:10.1126/science.1720570 76. de Thè H, Chen Z. Acute promyelocytic leukaemia: novel insights into the mechanisms of cure. Nat Rev Cancer (2010) 10:775–83. doi:10.1038/nrc2943 98. Thorn K. A quick guide to light microscopy in cell biology. Mol Biol Cell (2016) 27(2):219–22. doi:10.1091/mbc.E15-02-0088 77. Zhu J, Koken MHM, Quignon F, Chelbi-Alix MK, Degos L, Wang ZY, et al. Arsenic-induced PML targeting onto nuclear bodies: implications for the treatment of acute promyelocytic leukemia. Proc Natl Acad Sci U S A (1997) 94:3978–83. doi:10.1073/pnas.94.8.3978 99. Follain G, Mercier L, Osmani N, Harlepp S, Goetz JG. Seeing is believing – multi-scale spatio-temporal imaging towards in vivo cell biology. J Cell Sci (2017) 130(1):23–38. doi:10.1242/jcs.189001 100. Ferrando-May E, Hartmann H, Reymann J, Ansari N, Utz N, Fried HU, et al. Advanced light microscopy core facilities: balancing service, science and career. German BioImaging network. Microsc Res Tech (2016) 79(6):463–79. doi:10.1002/jemt.22648 78. Gambacorta M, Flenghi L, Fagioli M, Pileri S, Leoncini L, Bigerna B, et al. REFERENCES Human fibroblasts require the Rb family of tumor suppressors, but not p53, for PML-induced senescence. Oncogene (2004) 23:91–9. doi:10.1038/ sj.onc.1206886 64. Kentsis A, Gordon RE, Borden KL. Control of biochemical reactions through supramolecular RING domain self-assembly. Proc Natl Acad Sci U S A (2002) 99(24):15404–9. doi:10.1073/pnas.202608799 87. de Stanchina E, Querido E, Narita M, Davuluri RV, Pandolfi PP, Ferbeyre G, et al. PML is a direct p53 target that modulates p53 effector functions. Mol Cell (2004) 13:523–35. doi:10.1016/S1097-2765(04)00062-0 65. Matunis MJ, Zhang XD, Ellis NA. SUMO: the glue that binds. Dev Cell (2006) 11(5):596–7. doi:10.1016/j.devcel.2006.11.011 88. Wang ZG, Ruggero D, Ronchetti S, Zhong S, Gaboli M, Rivi R, et al. PML is essential for multiple apoptotic pathways. Nat Genet (1998) 20:266–72. doi:10.1038/3073 66. Weidtkamp-Peters S, Lenser T, Negorev D, Gerstner N, Hofmann TG, Schwanitz G, et al. Dynamics of component exchange at PMLnuclear bodies. J Cell Sci (2008) 121:2731–43. doi:10.1242/jcs.031922 89. Voisset E, Moravcsik E, Stratford EW, Jaye A, Palgrave CJ, Hills RK, et al. Pml nuclear body disruption cooperates in APL pathogenesis and impairs DNA damage repair pathways in mice. Blood (2018) 131:636–48. doi:10.1182/ blood-2017-07-794784 j 67. Banani SF, Lee HO, Hyman AA, Rosen MK. Biomolecular condensates: orga- nizers of cellular biochemistry. Nat Rev Mol Cell Biol (2017) 18(5):285–98. doi:10.1038/nrm.2017.7 68. Banani SF, Rice AM, Peeples WB, Lin Y, Jain S, Parker R, et al. Compositional control of phase-separated cellular bodies. Cell (2016) 166(3):651–63. doi:10.1016/j.cell.2016.06.010 90. Ito K, Bernardi R, Morotti A, Matsuoka S, Saglio G, Ikeda Y, et al. PML targeting eradicates quiescent leukaemia-initiating cells. Nature (2008) 453:1072–8. doi:10.1038/nature07016 69. Uversky VN. Intrinsically disordered proteins in overcrowded milieu: mem- brane-less organelles, phase separation, and intrinsic disorder. Curr Opin Struct Biol (2017) 44:18–30. doi:10.1016/j.sbi.2016.10.015 91. Mazza M, Pelicci PG. Is PML a tumor suppressor? Front Oncol (2013) 3:174. doi:10.3389/fonc.2013.00174 92. Martín-Martín N, Piva M, Urosevic J, Aldaz P, Sutherland JD, Fernández- Ruiz S, et al. Stratification and therapeutic potential of PML in metastatic breast cancer. Nat Commun (2016) 7:12595. doi:10.1038/ncomms12595 70. Palibrk V, Lång E, Lång A, Schink KO, Rowe AD, Bøe SO. Promyelocytic leukemia bodies tether to early endosomes during mitosis. Cell Cycle (2014) 13(11):1749–55. doi:10.4161/cc.28653 93. Ponente M, Campanini L, Cuttano R, Piunti A, Delledonne GA, Coltella N, et  al. PML promotes metastasis of triple-negative breast cancer through transcriptional regulation of HIF1A target genes. JCI Insight (2017) 2:e87380. doi:10.1172/jci.insight.87380 71. REFERENCES Ultrasensitive detection of single molecules by fluo- rescence correlation spectroscopy. Bioscience (1990) 3:180–3. 138. Karanam K, Loewer A, Lahav G. Dynamics of the DNA damage response: insights from live-cell imaging. Brief Funct Genomics (2013) 12(2):109–17. doi:10.1093/bfgp/els059 116. Rüttinger S, Buschmann V, Krämer B, Erdmann R, Macdonald R, Koberling F. Comparison and accuracy of methods to determine the confocal volume for quantitative fluorescence correlation spectroscopy. J Microsc (2008) 232:343–52. doi:10.1111/j.1365-2818.2008.02105.x 139. Essers J, Houtsmuller AB, van Veelen L, Paulusma C, Nigg AL, Pastink A, et al. Nuclear dynamics of RAD52 group homologous recombination pro- teins in response to DNA damage. EMBO J (2002) 21(8):2030–7. doi:10.1093/ emboj/21.8.2030 117. Becker W, Su B, Holub O, Weisshart K. FLIM and FCS detection in laser-scanning microscopes: increased efficiency by GaAsP hybrid detectors. Microsc Res Tech (2011) 74(9):804–11. doi:10.1002/jemt.20959 140. Bekker-Jensen S, Mailand N. Assembly and function of DNA double-strand break repair foci in mammalian cells. DNA Repair (Amst) (2010) 9(12):1219– 28. doi:10.1016/j.dnarep.2010.09.010 118. Elson EL. Fluorescence correlation spectroscopy: past, present, future. Biophys J (2011) 101(12):2855–70. doi:10.1016/j.bpj.2011.11.012 141. Lemaître C, Soutoglou E. DSB (Im)mobility and DNA repair compartmen- talization in mammalian cells. J Mol Biol (2015) 427(3):652–8. doi:10.1016/j. jmb.2014.11.014 119. Ries J, Schwille P. Fluorescence correlation spectroscopy. Bioessays (2012) 34(5):361–8. doi:10.1002/bies.201100111 120. Schwille P, Meyer-Almes FJ, Rigler R. Dual-color fluorescence cross-cor- relation spectroscopy for multicomponent diffusional analysis in solution. Biophys J (1997) 72(4):1878–86. doi:10.1016/S0006-3495(97)78833-7 h 142. Rothkamm K, Barnard S, Moquet J, Ellender M, Rana Z, Burdak-Rothkamm S. DNA damage foci: meaning and significance. Environ Mol Mutagen (2015) 56(6):491–504. doi:10.1002/em.21944 121. Thews E, Gerken M, Eckert R, Zäpfel J, Tietz C, Wrachtrup J. Cross talk free fluorescence cross correlation spectroscopy in live cells. Biophys J (2005) 89:2069–76. doi:10.1529/biophysj.104.057919 143. Polo SEP, Jackson SP. Dynamics of DNA damage response proteins at DNA breaks: a focus on protein modifications. Genes Dev (2011) 25(5):409–33. doi:10.1101/gad.2021311 122. Bacia K, Kim SA, Schwille P. Fluorescence cross-correlation spectroscopy in living cells. Nat Methods (2006) 3(2):83–9. doi:10.1038/nmeth822 144. Kim JS, Heale JT, Zeng W, Kong X, Krasieva TB, Ball AR Jr, et al. In situ analysis of DNA damage response and repair using laser microirradiation. Methods Cell Biol (2007) 82:377–407. doi:10.1016/S0091-679X(06)82013-3 123. Weidtkamp-Peters S, Weisshart K, Schmiedeberg L, Hemmerich P. Fluorescence correlation spectroscopy to assess the mobility of nuclear proteins. Methods Mol Biol (2009) 464:321–41. doi:10.1007/978-1-60327-461-6_18 145. Ferrando-May E, Tomas M, Blumhardt P, Stöckl M, Fuchs M, Leitenstorfer A. REFERENCES Heterogeneous nuclear expression of the promyelocytic leukemia (PML) protein in normal and neoplastic human tissues. Am J Pathol (1996) 149:2023–35. 101. Carrero G, McDonald D, Crawford E, de Vries G, Hendzel MJ. Using FRAP and mathematical modeling to determine the in  vivo kinetics of nuclear proteins. Methods (2003) 29:14–28. l 79. Lee HE, Jee CD, Kim MA, Lee HS, Lee YM, Lee BL, et al. Loss of promy- elocytic leukemia protein in human gastric cancers. Cancer Lett (2007) 247:103–9. doi:10.1016/j.canlet.2006.03.034 102. Peters R, Brünger A, Schulten K. Continuous fluorescence microphotolysis: a sensitive method for study of diffusion processes in single cells. Proc Natl Acad Sci U S A (1981) 78(2):962–6. doi:10.1073/pnas.78.2.962 80. Zhang P, Chin W, Chow LT, Chan AS, Yim AP, Leung SF, et al. Lack of expres- sion for the suppressor PML in human small cell lung carcinoma. Int J Cancer (2000) 85:599–605. doi:10.1002/(SICI)1097-0215(20000301)85:5<599:: AID-IJC1>3.0.CO;2-# 103. Mueller F, Mazza D, Stasevich TJ, McNally JG. FRAP and kinetic modeling in the analysis of nuclear protein dynamics: what do we really know? Curr Opin Cell Biol (2010) 22(3):403–11. doi:10.1016/j.ceb.2010.03.002 81. Koken MH, Linares-Cruz G, Quignon F, Viron A, Chelbi-Alix MK, Sobczak- Thépot J, et  al. The PML growthsuppressor has an altered expression in human oncogenesis. Oncogene (1995) 10:1315–24. h 104. Blumenthal D, Goldstien L, Edidin M, Gheber LA. Universal approach to FRAP analysis of arbitrary bleaching patterns. Sci Rep (2015) 5:11655. doi:10.1038/srep11655 82. Lavau C, Marchio A, Fagioli M, Jansen J, Falini B, Lebon P, et al. The acute promyelocytic leukaemia-associated PML gene is induced by interferon. Oncogene (1995) 11(5):871–6. 105. Dobrucki JW, Feret D, Noatynska A. Scattering of exciting light by live cells in fluorescence confocal imaging: phototoxic effects and relevance for FRAP studies. Biophys J (2007) 93:1778–86. doi:10.1529/biophysj.106. 096636 g 83. Salomoni P, Pandolfi PP. The role of PML in tumor suppression. Cell (2002) 108:165–70. doi:10.1016/S0092-8674(02)00626-8 84. Le XF, Yang P, Chang KS. Analysis of the growth and transformation sup- pressor domains of promyelocytic leukemia gene, PML. J Biol Chem (1996) 271:130–5. doi:10.1074/jbc.271.1.130 106. Hemmerich P, Schmiedeberg L, Diekmann S. Dynamic as well as stable protein interactions contribute to genome function and maintenance. Chromosome Res (2011) 19(1):131–51. doi:10.1007/s10577-010-9161-8 May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 18 Hoischen et al. Advanced Bioimaging of PML Bodies 107. van Royen ME, Zotter A, Ibrahim SM, Geverts B, Houtsmuller AB. REFERENCES Nuclear proteins: finding and binding target sites in chromatin. Chromosome Res (2011) 19(1):83–98. doi:10.1007/s10577-010-9172-5 130. Clegg RM. FRET tells us about proximities, distances, orientations and dynamic properties. J Biotechnol (2002) 82(3):177–9. doi:10.1016/ S1389-0352(01)00044-7 108. McNally JG. Quantitative FRAP in analysis of molecular binding dynamics in  vivo. Methods Cell Biol (2008) 85:329–51. doi:10.1016/ S0091-679X(08)85014-5 131. Jares-Erijman EA, Jovin TM. Imaging molecular interactions in living cells by FRET microscopy. Curr Opin Chem Biol (2006) 10(5):409–16. doi:10.1016/j. cbpa.2006.08.021 109. Beaudouin J, Mora-Bermúdez F, Klee T, Daigle N, Ellenberg J. Dissecting the contribution of diffusion and interactions to the mobility of nuclear proteins. Biophys J (2006) 90:1878–94. doi:10.1529/biophysj.105.071241 132. Padilla-Parra S, Tramier M. FRET microscopy in the living cell: different approaches, strengths and weaknesses. Bioessays (2012) 34(5):369–76. doi:10.1002/bies.201100086 133. Diekmann S, Hoischen C. Biomolecular dynamics and binding studies in the living cell. Phys Life Rev (2014) 11(1):1–30. doi:10.1016/j.plrev.2013. 11.011 110. Sprague BL, Pego RL, Stavreva DA, McNally JG. Analysis of binding reactions by fluorescence recovery after photobleaching. Biophys J (2004) 86:3473–95. doi:10.1529/biophysj.103.026765 111. Erdel F, Müller-Ott K, Baum M, Wachsmuth M, Rippe K. Dissecting chroma- tin interactions in living cells from protein mobility maps. Chromosome Res (2011) 19(1):99–115. doi:10.1007/s10577-010-9155-6 134. Müller S, Matunis MJ, Dejean A. Conjugation with the ubiquitin-related modifier SUMO-1 regulates the partitioning of PML within the nucleus. EMBO J (1998) 17(1):61–70. doi:10.1093/emboj/17.1.61 112. Baum M, Erdel F, Wachsmuth M, Rippe K. Retrieving the intracellular topol- ogy from multi-scale protein mobility mapping in living cells. Nat Commun (2014) 24(5):4494. doi:10.1038/ncomms5494 135. Daniels MJ, Marson A, Venkitaraman AR. PML bodies control the nuclear dynamics and function of the CHFR mitotic checkpoint protein. Nat Struct Mol Biol (2004) 11(11):1114–21. doi:10.1038/nsmb837 113. Gebhardt JC, Suter DM, Roy R, Zhao ZW, Chapman AR, Basu S, et al. Single- molecule imaging of transcription factor binding to DNA in live mammalian cells. Nat Methods (2013) 10(5):421–6. doi:10.1038/nmeth.2411 hl 136. Hellwig D, Hoischen C, Ulbricht T, Diekmann S. Acceptor-photobleaching FRET analysis of core kinetochore and NAC proteins in living human cells. Eur Biophys J (2009) 38(6):781–91. doi:10.1007/s00249-009-0498-x 114. Magde D, Elson E, Webb WW. Thermodynamic fluctuations in a reacting system – measurement by fluorescence correlation spectroscopy. Phys Rev Lett (1972) 29:705–8. doi:10.1103/PhysRevLett.29.705 l 137. Bui M, Dimitriadis EK, Hoischen C, An E, Quénet D, Giebe S, et al. Cell- cycle-dependent structural transitions in the human CENP-A nucleosome in vivo. Cell (2012) 150(2):317–26. doi:10.1016/j.cell.2012.05.035 115. Rigler R, Widengren J. REFERENCES Superresolution optical fluctuation imaging (SOFI). Adv Exp Med Biol (2012) 733:17–21. doi:10.1007/978-94-007-2555-3_2 152. Münch S, Weidtkamp-Peters S, Klement K, Grigaravicius P, Monajembashi S, Salomoni P, et  al. The tumor suppressor PML specifically accumulates at RPA/Rad51-containing DNA damage repair foci but is nonessential for DNA damage-induced fibroblast senescence. Mol Cell Biol (2014) 34:1733–46. doi:10.1128/MCB.01345-13 174. Gustafsson N, Culley S, Ashdown G, Owen DM, Pereira PM, Henriques R. Fast live-cell conventional fluorophore nanoscopy with ImageJ through super-resolution radialfluctuations. Nat Commun (2016) 7:12471. doi:10.1038/ncomms12471 175. Hess ST, Gould TJ, Gudheti MV, Maas SA, Mills KD, Zimmerberg J. Dynamic clustered distribution of hemagglutinin resolved at 40 nm in living cell mem- branes discriminates between raft theories. Proc Natl Acad Sci U S A (2007) 104:17370–5. doi:10.1073/pnas.0708066104 153. Ashkin A, Dziedzic JM, Bjorkholm JE, Chu S. Observation of a single-beam gradient force optical trap for dielectric paricles. Opt Lett (1986) 11:288–90. doi:10.1364/OL.11.000288 154. Greulich KO. Selected applications of laser scissors and tweezers and new applications in heart research. Methods Cell Biol (2008) 82:59–80. doi:10.1016/S0091-679X(06)82002-9 176. Blom H, Widengren J. Stimulated emission depletion microscopy. Chem Rev (2017) 117:7377–427. doi:10.1021/acs.chemrev.6b00653 155. Greulich KO, Pilarczyk G, Hoffmann A, Meyer Zu Hörste G, Schäfer B, Uhl V, et  al. Micromanipulation by laser microbeam and optical twee- zers: from plant cells to single molecules. J Microsc (2000) 198:182–7. doi:10.1046/j.1365-2818.2000.00698.x 177. Fornasiero EF, Opazo F. Super-resolution imaging for cell biologists: con- cepts, applications, current challenges and developments. Bioessays (2015) 37:436–51. doi:10.1002/bies.201400170 178. Lambert TJ, Waters JC. Navigating challenges in the application of superresolution microscopy. J Cell Biol (2017) 216:53–63. doi:10.1083/ jcb.201610011 156. MCGloin D, Dholakia K. Bessel beams: diffraction in a new light. Contemp Phys (2005) 46:15–28. doi:10.1080/0010751042000275259 157. Nie Z, Shi G, Li D, Zhang X, Wang Y, Song Y. Tight focusing of a radially polarized Laguerre–Bessel–Gaussian beam and its application to manipula- tion of two types of particles. Phys Lett A (2015) 379:857–63. doi:10.1016/j. physleta.2014.11.029 179. Hell SW, Stelzer EH, Lindek S, Cremer C. Confocal microscopy with an increased detection aperture: type-B 4Pi confocal microscopy. Opt Lett (1994) 19:222–32. doi:10.1364/OL.19.000222 f 180. Hell SW, Wichmann J. Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy. Opt Lett (1994) 19:780–2. doi:10.1364/OL.19.000780 158. Diekmann R, Wolfson DL, Spahn C, Heilemann M, Schuttpelz M, Huser T. Nanoscopy of bacterial cells immobilized by holographic optical tweezers. Nat Commun (2016) 7:13711–4. doi:10.1038/ncomms13711 181. REFERENCES Highlighting the DNA damage response with ultrashort laser pulses in the near infrared and kinetic modeling. Front Genet (2013) 16(4):135. doi:10.3389/fgene.2013.00135 124. Bacia K, Schwille P. A dynamic view of cellular processes by in vivo fluores- cence auto- and cross-correlation spectroscopy. Methods (2003) 29(1):74–85. doi:10.1016/S1046-2023(02)00291-8 146. Gassman NR, Wilson SH. Micro-irradiation tools to visualize base excision repair and single-strand break repair. DNA Repair (Amst) (2015) 31:52–63. doi:10.1016/j.dnarep.2015.05.001 125. Digman MA, Brown CM, Sengupta P, Wiseman PW, Horwitz AR, Gratton E. Measuring fast dynamics in solutions and cells with a laser scanning microscope. Biophys J (2005) 89(2):1317–27. doi:10.1529/biophysj.105. 062836 147. Kong X, Mohanty SK, Stephens J, Heale JT, Gomez-Godinez V, Shi LZ, et al. Comparative analysis of different laser systems to study cellular responses to DNA damage in mammalian cells. Nucleic Acids Res (2009) 37(9):68. doi:10.1093/nar/gkp221 126. Brown CM, Dalal RB, Hebert B, Digman MA, Horwitz AR, Gratton E. Raster image correlation spectroscopy (RICS) for measuring fast protein dynamics and concentrations with a commercial laser scanning confocal microscope. J Microsc (2008) 229:78–91. doi:10.1111/j.1365-2818.2007.01871.x 148. Holton NW, Andrews JF, Gassman NR. Application of laser micro-irradia- tion for examination of single and double strand break repair in mammalian cells. J Vis Exp (2017) (127). doi:10.3791/56265 127. Chen Y, Müller JD, Ruan Q, Gratton E. Molecular brightness characterization of EGFP in vivo by fluorescence fluctuation spectroscopy. Biophys J (2002) 82(1 Pt 1):133–44. doi:10.1016/S0006-3495(02)75380-0 149. Lukas C, Bartek J, Lukas J. Imaging of protein movement induced by chromosomal breakage: tiny ‘local’ lesions pose great ‘global’ challenges. Chromosoma (2005) 114(3):146–54. doi:10.1007/s00412-005-0011-y 128. Förster T. Zwischenmolekulare Energiewanderung und Fluoreszenz. Ann Phys (1948) 437:55–75. doi:10.1002/andp.19484370105 150. Bischof O, Kim SH, Irving J, Beresten S, Ellis NA, Campisi J. Regulation and localization of the Bloom syndrome protein in response to DNA damage. J Cell Biol (2001) 153(2):367–80. doi:10.1083/jcb.153.2.367 129. Sun Y, Rombola C, Jyothikumar V, Periasamy A. Förster resonance energy transfer microscopy and spectroscopy for localizing protein-protein interactions in living cells. Cytometry A (2013) 83(9):780–93. doi:10.1002/ cyto.a.22321 151. Fumagalli M, Rossiello F, Clerici M, Barozzi S, Cittaro D, Kaplunov JM, et  al. Telomeric DNA damage is irreparable and causes persistent DNA- May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 19 Hoischen et al. Advanced Bioimaging of PML Bodies damage-response activation. Nat Cell Biol (2012) 14(4):355–65. doi:10.1038/ ncb2466 173. Dertinger T, Colyer R, Vogel R, Heilemann M, Sauer M, Enderlein J, et al. REFERENCES Mueller V, Honigmann A, Ringemann C, Medda R, Schwarzmann G, Eggeling C. FCS in STED microscopy: studying the nanoscale of lipid membrane dynamics. Methods Enzymol (2013) 519:1–38. doi:10.1016/ B978-0-12-405539-1.00001-4 159. Guck J, Ananthakrishnan R, Mahmood H, Moon TJ, Cunningham CC, Käs J. The optical stretcher: a novel laser tool to micromanipulate cells. Biophys J (2001) 81:767–84. doi:10.1016/S0006-3495(01)75740-2 160. Greulich KO. Manipulation of cells with laser microbeam scissors and optical tweezers: a review. Rep Prog Phys (2017) 80(2):026601. doi:10.1088/1361-6633/80/2/026601 182. Niewidok B, Igaev M, Pereira da Graca A, Strassner A, Lenzen C, Richter CP, et  al. Single-molecule imaging reveals dynamic biphasic partition of RNA-binding proteins in stress granules. J Cell Biol (2018) 217(4):1303–18. doi:10.1083/jcb.201709007 161. Grigaravicius P, Greulich KO, Monajembashi S. Laser microbeams and optical tweezers in ageing research. Chemphyschem (2009) 10:79–85. doi:10.1002/cphc.200800725 183. Balzarotti F, Eilers Y, Gwosch KC, Gynnå AH, Westphal V, Stefani FD, et al. Nanometer resolution imaging and tracking of fluorescent molecules with minimal photon fluxes. Science (2017) 355:606–12. doi:10.1126/science. aak9913 162. Zhang H, Liu K-K. Optical tweezers for single cells. J R Soc Interface (2008) 5:671–90. doi:10.1098/rsif.2008.0052 163. Maul GG, Yu E, Ishov AM, Epstein AL. Nuclear domain 10 (ND10) associ- ated proteins are also present in nuclear bodies and redistribute to hundreds of nuclear sites after stress. J Cell Biochem (1995) 59:498–513. doi:10.1002/ jcb.240590410 184. Osterwald S, Deeg KI, Chung I, Parisotto D, Wörz S, Rohr K, et al. PML induces compaction, TRF2 depletion and DNA damage signaling at telomeres and promotes their alternative lengthening. J Cell Sci (2015) 128:1887–900. doi:10.1242/jcs.148296 164. Eskiw CH, Dellaire G, Mymryk JS, Bazett-Jones DP. Size, position and dynamic behavior of PML nuclear bodies following cell stress as a paradigm for supramolecular trafficking and assembly. J Cell Sci (2003) 116:4455–66. doi:10.1242/jcs.00758 185. Booth M, Andrade D, Burke D, Patton B, Zurauskas M. Aberrations and adaptive optics in super-resolution microscopy. Microscopy (Oxf) (2015) 64:251–61. doi:10.1093/jmicro/dfv033 186. Heine J, Reuss M, Harke B, D’Este E, Sahl SJ, Hell SW. Adaptive-illumination STED nanoscopy. Proc Natl Acad Sci U S A (2017) 114:9797–802. doi:10.1073/ pnas.1708304114 165. Abbe E. Beiträge zur Theorie des Mikroskops und der mikroskopischen Wahrnehmung. Arch für Mikroskopische Anat (1873) 9:413–8. doi:10.1007/ BF02956173 187. Valm AM, Cohen S, Legant WR, Melunis J, Hershberg U, Wait E, et  al. Applying systems-level spectral imaging and analysis to reveal the organelle interactome. Nature (2017) 546:162–7. doi:10.1038/nature22369 166. Gustafsson MG. REFERENCES Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy. J Microsc (2000) 198:82–7. doi:10.1046/j.1365-2818.2000.00710.x 188. Gustavsson AK, Petrov PN, Lee MY, Shechtman Y, Moerner WE. 3D single-molecule super-resolution microscopy with a tilted light sheet. Nat Commun (2018) 9:123. doi:10.1038/s41467-017-02563-4 167. Gustafsson MG, Shao L, Carlton PM, Wang CJ, Golubovskaya IN, Cande WZ, et  al. Three-dimensional resolution doubling in wide-field fluorescence microscopy by structured illumination. Biophys J (2008) 94:4957–70. doi:10.1529/biophysj.107.120345 189. Engelbrecht CJ, Greger K, Reynaud EG, Krzic U, Colombelli J, Stelzer EH. Three-dimensional laser microsurgery in light-sheet based microscopy (SPIM). Opt Express (2007) 15:6420–30. doi:10.1364/OE.15.006420 168. Heintzmann R, Huser T. Super-resolution structured illumination micros- copy. Chem Rev (2017) 117(23):13890–908. doi:10.1021/acs.chemrev.7b00218 169. Shao L, Kner P, Rego EH, Gustafsson MG. Super-resolution 3D microscopy of live whole cells using structured illumination. Nat Methods (2011) 8:1044–6. doi:10.1038/nmeth.1734 Conflict of Interest Statement: KW was employed by Carl Zeiss Microscopy GmbH (ZEISS Group, Carl-Zeiss-Promenade 1007745 Jena, Germany). All other authors declare no competing interests. 170. van de Linde S, Löschberger A, Klein T, Heidbreder M, Wolter S, Heilemann M, et al. Direct stochastic optical reconstruction microscopy with standard flu- orescent probes. Nat Protoc (2011) 6:991–1009. doi:10.1038/nprot.2011.336 Copyright © 2018 Hoischen, Monajembashi, Weisshart and Hemmerich. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. 171. Betzig E, Patterson GH, Sougrat R, Lindwasser OW, Olenych S, Bonifacino JS, et  al. Imaging intracellular fluorescent proteins at nanometer resolution. Science (2006) 313:1642–5. doi:10.1126/science.1127344 172. Hess ST, Girirajan TP, Mason MD. Ultra-high resolution imaging by fluores- cence photoactivation localization microscopy. Biophys J (2006) 91:4258–72. doi:10.1529/biophysj.106.091116 172. Hess ST, Girirajan TP, Mason MD. Ultra-high resolution imaging by fluores- cence photoactivation localization microscopy. Biophys J (2006) 91:4258–72. doi:10.1529/biophysj.106.091116 May 2018  |  Volume 8  |  Article 125 Frontiers in Oncology  |  www.frontiersin.org 20
https://openalex.org/W4361922351
https://figshare.com/articles/journal_contribution/Figure_S3_from_Whole-Exome_Sequencing_of_Metaplastic_Breast_Carcinoma_Indicates_Monoclonality_with_Associated_Ductal_Carcinoma_Component/22462722/1/files/39914025.pdf
Georgian
null
Figure S2 from Whole-Exome Sequencing of Metaplastic Breast Carcinoma Indicates Monoclonality with Associated Ductal Carcinoma Component
null
2,023
cc-by
374,580
● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● EGFR KMT2C KDM6A ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC A mod, r−squared: 0.79 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● EGFR KMT2C KDM6A ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC A mod, r−squared: 0.79 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC A low, r−squared: 0.8 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● EGFR KMT2C KDM6A ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC A mod, r−squared: 0.79 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 MC A low, r−squared: 0.8 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 MC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC A low, r−squared: 0.8 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC A dbSNP, r−squared: 0.8 IDC IDC IDC MC A low, r−squared: 0.8 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC A dbSNP, r−squared: 0.8 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC A modf, r−squared: 0.79 IDC IDC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC B low, r−squared: 0.84 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ERBB2 KMT2C ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC B mod, r−squared: 0.86 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ERBB2 KMT2C ● ● 00 0.25 0.50 0.75 1.00 MC B mod, r−squared: 0.86 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC B low, r−squared: 0.84 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●●●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.25 0.50 0.75 1.00 IDC 00 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC B low, r−squared: 0.84 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● 00 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●●●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC B dbSNP, r−squared: 0.79 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ERBB2 ● 0.00 0.25 0.50 0.00 0.25 0.50 0.75 1.00 MC B mod, r−squared: 0.86 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.00 0.25 0.50 0.75 MC B low, r−squared: 0.84 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC B modf, r−squared: 0.79 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 MC B dbSNP, r−squared: 0.79 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.00 0.25 0.50 0.75 1.00 MC B low, r−squared: 0.84 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●●●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC B dbSNP, r−squared: 0.79 IDC IDC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●●●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC B dbSNP, r−squared: 0.79 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.25 0.50 0.75 1.00 MC B modf, r−squared: 0.79 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●●●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC B dbSNP, r−squared: 0.79 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC B modf, r−squared: 0.79 IDC IDC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● TP53 BRCA1 KMT2C KDM6A ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC C mod, r−squared: 0.82 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC C low, r−squared: 0.81 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● TP53 BRCA1 KMT2C KDM6A ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC C mod, r−squared: 0.82 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 MC C low, r−squared: 0.81 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 MC IDC 1.00 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC C low, r−squared: 0.81 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC C dbSNP, r−squared: 0.8 IDC IDC IDC IDC MC C low, r−squared: 0.81 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC C dbSNP, r−squared: 0.8 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC C modf, r−squared: 0.78 IDC IDC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● TP53 NF1 KMT2C ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC D mod, r−squared: 0.73 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC D low, r−squared: 0.68 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● TP53 NF1 KMT2C ● ● ● 00 0.25 0.50 0.75 1.00 MC D mod, r−squared: 0.73 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC D low, r−squared: 0.68 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.25 0.50 0.75 1.00 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● TP53 NF1 KMT2C ● ● ● 00 0.25 0.50 0.75 1.00 MC D mod, r−squared: 0.73 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC D low, r−squared: 0.68 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● TP53 NF1 KMT2C ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC D mod, r−squared: 0.73 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 MC D low, r−squared: 0.68 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC D modf, r−squared: 0.72 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 MC D dbSNP, r−squared: 0.67 IDC ● ● ● ● ● ● ● 5 1.00 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC D low, r−squared: 0.68 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● 5 1.00 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC D dbSNP, r−squared: 0.67 IDC IDC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC D dbSNP, r−squared: 0.67 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 0.25 0.50 0.75 1.00 MC D modf, r−squared: 0.72 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC D dbSNP, r−squared: 0.67 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC D modf, r−squared: 0.72 IDC IDC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● BRCA1 SEPT9 MYC ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC E mod, r−squared: 0.88 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC E low, r−squared: 0.88 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● BRCA1 SEPT9 MYC ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC E mod, r−squared: 0.88 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC E low, r−squared: 0.88 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● BRCA1 SEPT9 MYC ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC E mod, r−squared: 0.88 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 MC E low, r−squared: 0.88 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC IDC ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 MC IDC 1.00 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC E low, r−squared: 0.88 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ●● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC E dbSNP, r−squared: 0.87 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.00 0.25 0.50 0.75 1.00 MC E low, r−squared: 0.88 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ●● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC E dbSNP, r−squared: 0.87 IDC IDC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.25 0.50 0.75 1.00 MC E modf, r−squared: 0.86 ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ●●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●●●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 00 0.00 0.25 0.50 0.75 1.00 MC E dbSNP, r−squared: 0.87 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC E modf, r−squared: 0.86 IDC ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC E dbSNP, r−squared: 0.87 IDC IDC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC F mod, r−squared: 0.74 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC F low r−squared: 0 82 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC F mod, r−squared: 0.74 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 MC F low, r−squared: 0.82 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.25 0.50 0.75 1.00 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● 0.25 0.50 0.75 1.00 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC F low, r−squared: 0.82 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC F dbSNP, r−squared: 0.79 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.00 0.25 0.50 0.75 1.00 MC F low, r−squared: 0.82 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC F dbSNP, r−squared: 0.79 IDC IDC IDC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC F modf, r−squared: 0.81 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.25 0.50 0.75 1.00 MC F modf, r−squared: 0.81 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC F dbSNP, r−squared: 0.79 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC F dbSNP, r−squared: 0.79 IDC IDC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ERBB2 BRCA1 PIK3CA MAP3K1 EGFR ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC G mod r squared: 0 75 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC G low r squared: 0 78 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ERBB2 BRCA1 PIK3CA MAP3K1 EGFR ● ● ● ● ● 00 0.25 0.50 0.75 1.00 MC G mod, r−squared: 0.75 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC G low, r−squared: 0.78 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.25 0.50 0.75 1.00 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC G low, r−squared: 0.78 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC G dbSNP, r−squared: 0.75 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● BRCA1 PIK3CA ● ● 0.00 0.25 0.50 0.00 0.25 0.50 0.75 1.00 MC G mod, r−squared: 0.75 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.00 0.25 0.50 0.75 MC G low, r−squared: 0.78 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC G modf, r−squared: 0.75 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 MC G dbSNP, r−squared: 0.75 IDC IDC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.00 0.25 0.50 0.75 1.00 MC G low, r−squared: 0.78 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC G dbSNP, r−squared: 0.75 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC G dbSNP, r−squared: 0.75 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC G modf, r−squared: 0.75 IDC IDC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● EGFR ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC H mod r−squared: 0 88 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC H low, r−squared: 0.86 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● EGFR ● 00 0.25 0.50 0.75 1.00 MC H mod, r−squared: 0.88 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC H low, r−squared: 0.86 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● EGFR ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC H mod, r−squared: 0.88 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC H low, r−squared: 0.86 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● EGFR ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC H mod, r−squared: 0.88 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 MC H low, r−squared: 0.86 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 MC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 MC H low, r−squared: 0.86 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC H dbSNP, r−squared: 0.85 IDC ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.00 0.25 0.50 0.75 1.00 MC H low, r−squared: 0.86 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC H dbSNP, r−squared: 0.85 IDC IDC IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.25 0.50 0.75 1.00 MC H modf, r−squared: 0.87 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC H dbSNP, r−squared: 0.85 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC H dbSNP, r−squared: 0.85 IDC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 MC H modf, r−squared: 0.87 IDC IDC IDC IDC
https://openalex.org/W3136935945
https://univoak.eu/islandora/object/islandora:119876/datastream/PDF/download/citation.pdf
English
null
Non-specific interactions of antibody-oligonucleotide conjugates with living cells
Scientific reports
2,021
cc-by
6,402
Non‑specific interactions of antibody‑oligonucleotide conjugates with living cells Victor Lehot1, Isabelle Kuhn1, Marc Nothisen1, Stéphane Erb2, Sergii Kolodych3, Sarah Cianférani2, Guilhem Chaubet1 & Alain Wagner1* OPEN Antibody-Oligonucleotide Conjugates (AOCs) represent an emerging class of functionalized antibodies that have already been used in a wide variety of applications. While the impact of dye and drug conjugation on antibodies’ ability to bind their target has been extensively studied, little is known about the effect caused by the conjugation of hydrophilic and charged payloads such as oligonucleotides on the functions of an antibody. Previous observations of non-specific interactions of nucleic acids with untargeted cells prompted us to further investigate their impact on AOC binding abilities and cell selectivity. We synthesized a series of single- and double-stranded AOCs, as well as a human serum albumin-oligonucleotide conjugate, and studied their interactions with both targeted and non-targeted living cells using a time-resolved analysis of ligand binding assay. Our results indicate that conjugation of single strand oligonucleotides to proteins induce consistent non-specific interactions with cell surfaces while double strand oligonucleotides have little or no effect, depending on the preparation method. Antibody-oligonucleotide conjugates (AOCs) have received increasing attention as an emerging class of chi- meric biomolecules. Combining the specific binding ability of antibodies with the vast structural and functional properties of oligonucleotides (ONs), these conjugates have found a wide variety of applications as imaging, detection and therapeutic ­agents1.i p g All of these functions primarily require the discrimination of the targeted cell type via specific binding of the AOC to its protein target. Reaching high efficacy in therapeutic applications thus requires, among other, both a high affinity for the targeted protein at the targeted cell surface and low interactions with the other, non- targeted, cells. g In a recent ­work2, we investigated the ability of AOC constructs (termed DNA-linked ADCs) to carry and deliver a small-molecule drug into a targeted cell in a selective fashion. To our surprise, we observed that while our DNA-linked ADC (based on the anti-HER2 monoclonal antibody trastuzumab) showed a similar toxicity profile on ­HER2+ cells to classical covalent conjugates, it also showed low but unexpected toxicity on the control ­HER2− cell line. We hypothesized that this toxicity was the result of a non-specific interaction of the conjugate with ­HER2− cells induced by the ON linker. This puzzling observation motivated us to further investigate the impact of ON conjugation on the cell binding properties of antibodies and proteins. www.nature.com/scientificreports www.nature.com/scientificreports 1Bio‑Functional Chemistry (UMR 7199), LabEx Medalis, University of Strasbourg, 74 Route du Rhin, 67400  Illkirch‑Graffenstaden, France. 2BioOrganicMass Spectrometry Laboratory (LSMBO), IPHC, University of Strasbourg, 25 rue Becquerel, 67087  Strasbourg, France. 3Syndivia SAS, ISIS, 8 allée Gaspard Monge, 67000 Strasbourg, France. *email: alwag@unistra.fr Scientific Reports | (2021) 11:5881 Non‑specific interactions of antibody‑oligonucleotide conjugates with living cells Victor Lehot1, Isabelle Kuhn1, Marc Nothisen1, Stéphane Erb2, Sergii Kolodych3, Sarah Cianférani2, Guilhem Chaubet1 & Alain Wagner1* OPEN p j g g p p p ONs, because of their hydrophilic nature and multiple negative charges, constitute a singular type of payload for which a few literature reports have highlighted non-specific interactions with cell membranes. In 1995, Walker et al.3 described the synthesis and in vitro cellular uptake of an anti-transferrin receptor antibody-antisense ON conjugate (the antisense ON being a single-stranded DNA) and observed non-specific cell association for both control IgG-ssON conjugate and free ON. The “non-specific” interactions of non-modified4 and dye-labelled5 ONs with cell membranes have also been reported. However, despite these early warnings, the effect of ON conjugation on antibody selectivity remains understudied.f j g y y To shed light on such potentially determinant effect, we compared the interactions of various protein-ON conjugates, unconjugated proteins and free ONs with live cells using a time-resolved analysis of ligand binding assay. This technique allows the study of interactions in real-time on non-treated, live cells in culture medium, and in the presence of serum, a situation resembling in vivo conditions. Importantly, it requires no washing step that could wash off compounds before their ­detection6, revealing weak interactions with fast dissociation rates. 1Bio‑Functional Chemistry (UMR 7199), LabEx Medalis, University of Strasbourg, 74 Route du Rhin, 67400  Illkirch‑Graffenstaden, France. 2BioOrganicMass Spectrometry Laboratory (LSMBO), IPHC, University of Strasbourg, 25 rue Becquerel, 67087  Strasbourg, France. 3Syndivia SAS, ISIS, 8 allée Gaspard Monge, 67000 Strasbourg, France. *email: alwag@unistra.fr | https://doi.org/10.1038/s41598-021-85352-w www.nature.com/scientificreports/ www.nature.com/scientificreports/ www.nature.com/scientificreports/ Figure 1. General scheme for the synthesis and labelling of Ab*-ssON conjugates. Figure 1. General scheme for the synthesis and labelling of Ab*-ssON conjugates. Figure 2. Association rate constants ­(ka) of unconjugated trastuzumab (T*), trastuzumab- single-stranded ON conjugate (T*-ssON) and free single stranded ON (ssON*) on SK-BR-3 ­(HER2+ cell line, red bars) and MDA-MB-231 ­(HER2− cell line, blue bars) measured using the time-resolved analysis of ligand binding assay (Fig. S3, S4, and S13). The symbol * indicates fluorescein labelling. Error bars indicate the standard error of the fitted parameter ­ka. Figure 2. Association rate constants ­(ka) of unconjugated trastuzumab (T*), trastuzumab- single-stranded ON conjugate (T*-ssON) and free single stranded ON (ssON*) on SK-BR-3 ­(HER2+ cell line, red bars) and MDA-MB-231 ­(HER2− cell line, blue bars) measured using the time-resolved analysis of ligand binding assay (Fig. S3, S4, and S13). The symbol * indicates fluorescein labelling. Error bars indicate the standard error of the fitted parameter ­ka. www.nature.com/scientificreports/ www.nature.com/scientificreports/ Figure 3. Association rate constants ­(ka) of unconjugated rituximab (R*), single stranded rituximab-ssON conjugate (R*-ssON), unconjugated HSA (HSA*), and single stranded HSA-ssON conjugate (HSA*-ssON) on SK-BR-3 ­(HER2+ cell line, red bars) and MDA-MB-231 ­(HER2− cell line, blue bars) measured using the time- resolved analysis of ligand binding assay (Fig. S7-10). The symbol * indicates fluorescein-labelling. Error bars indicate the standard error of the fitted parameter ­ka. Figure 3. Association rate constants ­(ka) of unconjugated rituximab (R*), single stranded rituximab-ssON conjugate (R*-ssON), unconjugated HSA (HSA*), and single stranded HSA-ssON conjugate (HSA*-ssON) on SK-BR-3 ­(HER2+ cell line, red bars) and MDA-MB-231 ­(HER2− cell line, blue bars) measured using the time- resolved analysis of ligand binding assay (Fig. S7-10). The symbol * indicates fluorescein-labelling. Error bars indicate the standard error of the fitted parameter ­ka. random conjugation of payloads, including ­dyes11 and small-molecule ­drugs12,13, to an antibody was reported to deteriorate its antigen affinity in some cases. It is noteworthy that ssON* showed an HER2-independant interaction with both cell lines, as evidenced by low but significant values of ­ka on both SK-BR-3 and MDA-MB-231 cell lines. The order of magnitude of these interactions falls in the same range as that of T*-ssON on ­HER2− cells, advocating for the fact that the latter was the result of ON-cell interactions. To validate this observation, we conjugated the same single-stranded 37mer ON to rituximab (R), an antibody targeting B-lymphocyte antigen CD20 (an antigen that is expressed by neither SK-BR-3 nor MDA-MB-231), and to HSA (Fig. 3). g As expected, both non-conjugated rituximab (R*) and HSA (HSA*) showed no interaction with either cell line. On the other hand, the corresponding ON conjugated R*-ssON and HSA*-ssON were shown to interact to an undeniable extent with both cell lines (Fig. 3), which is consistent with our previous observation that the conjugation of an ON to a protein induces an interaction with cells that is mediated by the ON moiety and not the protein. Interestingly, this effect was more pronounced with R*-ssON than HSA*-ssON, indicating that dif- ferent proteins might be impacted differently by ON conjugation. gf y y j g To gain further evidence, we performed a competition assay, where MDA-MB-231 cells, supposedly interact- ing with T*-ssON via non-specific interactions, were pre-incubated with a 100-fold excess of free 37mer ssON, relative to T*-ssON (Fig. S17). Results and discussion l d l Using a previously reported plug and play conjugation ­strategy7, we prepared several fluorescein-labelled proteins and protein-ON conjugates (see Fig. 1, 5, S1, S2 and Table S1 for syntheses and characterization of the conju- gates) with Degrees of Conjugation (DoC) in line with those of our previously-described DNA-linked ­ADCs2 (i.e. comprised between 2 and 3). We then evaluated the interaction profiles of these protein-ON conjugates with two cell lines, SK-BR-3 ­(HER2+) and MDA-MB-231 ­(HER2−), using time-resolved analysis of ligand binding ­assay8,9. As an HER2 targeting antibody, we used trastuzumab and as negative controls, we used the anti-CD20 antibody rituximab and Human Serum Albumin (HSA).i In the following figures, we will report association rate constant values ­ka ­(M−1 ­s−1), describing the rate of formation of complexes, i.e. the number of fluorescein-labelled compounds bound to cell membranes per sec- ond. Thus, high ­ka value will account for fast binding to cell surface, while low value will account for slow to no interaction. The values of ­ka in biological systems are typically comprised between 1.103 and 1.107 ­M−1 ­s−1. We chose to study this parameter to compare specific and non-specific interactions as it was previously shown to be largely insensitive to differences between binding ­patterns10.i f In a first set of experiments, we compared the association rate constants of anti-HER2 antibody trastuzumab (T*), trastuzumab-37mer ssON conjugate (T*-ssON), and single-stranded 37mer ssON (ssON*), on both cell lines (Fig. 2). In order to do so, cells were seeded on a cell dish and incubated with fluorescein-labelled com- pounds (the symbol * indicates fluorescein labelling). The fluorescence intensity was then measured over time and normalized against the background fluorescence of the plastic support (see Fig. S3 to S16). The signal increase was used to extract the association rate constant ­ka.i Unsurprisingly, trastuzumab displayed a high selectivity profile with an association rate constant ­ka of 23,800 ­M−1 ­s−1 on the ­HER2+ cell line, while no signal variation was detected for the ­HER2− cell line. T*-ssON showed a deteriorated selectivity profile with a reduced ­ka for ­HER2+ cells, but more importantly with the appearance of "non-specific" interactions with ­HER2− cells. Stochastic conjugation with lysine ­residues11,12 for T*-ssON might account for the lower ­ka with the ­HER2+ cell line as compared to unconjugated T*. Indeed, Scientific Reports | (2021) 11:5881 | https://doi.org/10.1038/s41598-021-85352-w www.nature.com/scientificreports/ g As expected, we found that the addition of free ssON to the medium almost completely prevented the further association of T*-ssON with MDA-MB-231, suggesting a shielding effect from the free ssON.l f We then evaluated the influence of the ONs’ length and hybridization on the association rate constant by comparing single and double stranded forms of non-coding and non-structured 20mers, 37mers and 74mers. In all cases, weak interactions with both cell lines were observed, with consistently higher values for single-stranded species (Fig. 4 and SI).t In the context of drug delivery applications of ­AOCs2,14–20, the ON component is often hybridized with its complementary strand in the form of double-stranded ONs (dsONs). As this could lead to weaker interactions with cell membranes, based on the results in Fig. 4, we set to prepare a dsON version of our trastuzumab conju- gate (T*-dsON) in order to evaluate the effect of such structural change. A first method to prepare this conjugate consists in the hybridization of a complementary ssON (cON) to the previously synthesized T-ssON. This is typically done by a brief incubation at 37 °C of the two partners, in order to prevent degradation of the antibody (method 1, Fig. 5). This approach is mostly employed for non-covalent ­conjugation21 between two molecules that had been separately conjugated with complementary ­ssONs2,20,22,23. The validity of this approach is sup- ported by the many examples of immunoassays (e.g. immuno-PCR24,25, proximity extension ­assay26,27, protein ­arrays28), which rely upon hybridization steps that proceed under similar conditions. A second method consists in hybridizing the two strands under classical conditions (i.e. by incubation at 95 °C) prior to the bioconjuga- tion step (method 2, Fig. 5). This method has been reported for the synthesis of antibody-siRNA conjugates from commercial chemically-modified duplexed ­siRNAs14,16. We produced T*-dsON conjugates with identical DoC values of 2.9 (determined by SDS-PAGE gel analysis; see Fig. S1) using both methods and compared their interaction rate constants to those of T*-ssON on both cell lines (Fig. 6). https://doi.org/10.1038/s41598-021-85352-w Scientific Reports | (2021) 11:5881 | www.nature.com/scientificreports/ Figure 4. Association rate constants ­(ka) of free 20mer, 37mer, and 74mer, single and double-stranded ONs (respectively ssON20*, ssON37*, ssON74*, and dsON20*, dsON37*, dsON74*) on SK-BR-3 ­(HER2+ cell line, red bars) and MDA-MB-231 ­(HER2− cell line, blue bars) measured using the time-resolved analysis of ligand binding assay (Fig. S11-16). The symbol * indicates fluorescein-labelling. www.nature.com/scientificreports/ Error bars indicate the standard error of the fitted parameter ­ka. Figure 4. Association rate constants ­(ka) of free 20mer, 37mer, and 74mer, single and double-stranded ONs (respectively ssON20*, ssON37*, ssON74*, and dsON20*, dsON37*, dsON74*) on SK-BR-3 ­(HER2+ cell line, red bars) and MDA-MB-231 ­(HER2− cell line, blue bars) measured using the time-resolved analysis of ligand binding assay (Fig. S11-16). The symbol * indicates fluorescein-labelling. Error bars indicate the standard error of the fitted parameter ­ka. Figure 5. General scheme for the synthesis and labelling of Ab*-dsON conjugates. Figure 5. General scheme for the synthesis and labelling of Ab*-dsON conjugates. For the T*-dsON conjugates prepared following the first method, switching from single to double-stranded ONs gave comparable non-specific interactions, and also resulted in a slight decrease in ­ka, notably on the ­HER2+ SK-BR-3 cell line. Interestingly, the conjugate prepared following the second method had similar ­ka with SK-BR-3 cells but did not display non-specific interactions with MDA-MB-231 cells. p y pi In the polymerase chain reaction (PCR), full hybridization of ONs is highly dependent on temperature, and the initial denaturation step is typically performed at 94 °C29. Incubation at 90–95 °C is thus commonly used for the hybridization of complementary ssONs into dsONs, as in the case of method 2 (Fig. 5). Performing the hybridization at lower temperature is useful when working with protein-ssON conjugates, since they are prone to undergo thermal denaturation, but it might not be sufficient to reach full hybridization (method 1, Fig. 5). This could account for the interaction profile of the T*-dsON conjugate prepared by method 1 which is halfway between that of the fully hybridized T*-dsON, prepared by method 2, and that of T*-ssON.h y y y The association of naked ONs with cells surface has now been studied for more than 50 years, with many cell- surface proteins proposed as ­receptors4. It has been documented that various types of ONs might bind to different receptors. As an example, toll-like receptors (TLRs), involved in the innate immune response, possess the ability to bind DNA molecules containing CpG motifs, dsRNAs as well as ­ssRNAs30. Cell-surface receptors of the scav- enger receptors family, such as stabilin, have been reported to bind and internalize phosphorothioate-modified ­oligodeoxynucleotides31, despite some conflicting results having been ­published32. Furthermore, proteins of the Scientific Reports | (2021) 11:5881 | https://doi.org/10.1038/s41598-021-85352-w www.nature.com/scientificreports/ Figure 6. Conclusion As AOCs are developing into powerful tools in various ­applications1, investigations to get a better understanding of their interactions with cell surfaces appear to be stimulating a renewed ­interest30. Our ­previous2 and present results show that ONs are a particular payload that may display weak but consistent interactions with cell sur- faces, which can impact the binding properties of antibodies upon conjugation. We demonstrate that both the nature of the ON, single strand vs double strand, as well as the method used to prepare the dsON AOC have a clear impact on the non-specific interaction of the resulting conjugates. This phenomenon is likely to disturb the in vitro and in vivo behavior of AOCs and influence their fate beyond what can be extrapolated from the knowledge of classical protein conjugates. As such, it appears that both ON structure and preparation method should be taken into consideration when developing antibody-oligonucleotide conjugates for imaging, detection or therapeutic application. www.nature.com/scientificreports/ Association rate constants ­(ka) of single and double stranded trastuzumab-ssON conjugate (T*-ssON and T*-dsON, respectively), and free single and double stranded ONs (ssON* and dsON*, respectively) on SK-BR-3 ­(HER2+ cell line, red bars) and MDA-MB-231 ­(HER2− cell line, blue bars) measured using the time- resolved analysis of ligand binding assay (Fig. S4-6). The symbol * indicates fluorescein-labelling. Regarding the T*-dsON conjugates modes of preparation, method 1 corresponds to the hybridization of the complementary ON strand with the T-ssON conjugate, while method 2 corresponds to the conjugation of a hybridized dsON to trastuzumab (see Fig. 5). Error bars indicate the standard error of the fitted parameter ­ka. Figure 6. Association rate constants ­(ka) of single and double stranded trastuzumab-ssON conjugate (T*-ssON and T*-dsON, respectively), and free single and double stranded ONs (ssON* and dsON*, respectively) on SK-BR-3 ­(HER2+ cell line, red bars) and MDA-MB-231 ­(HER2− cell line, blue bars) measured using the time- resolved analysis of ligand binding assay (Fig. S4-6). The symbol * indicates fluorescein-labelling. Regarding the T*-dsON conjugates modes of preparation, method 1 corresponds to the hybridization of the complementary ON strand with the T-ssON conjugate, while method 2 corresponds to the conjugation of a hybridized dsON to trastuzumab (see Fig. 5). Error bars indicate the standard error of the fitted parameter ­ka. systemic RNA interference defective protein 1 (SID1) transmembrane family, such as SIDT-1 and SIDT-2, have been shown to facilitate the uptake of ssRNA and dsRNA but not of ssDNA and ­dsDNA33–35. Our results show that, when conjugated to an antibody, ONs are not simple linkers nor spectator payloads. Based on the present work and this body of literature, our group is currently investigating further the mecha- nism by which these interactions between AOCs and cell membranes operate at the molecular level and can be controlled. www.nature.com/scientificreports/ Free oligonucleotides were hybridized by stirring a solution of the complementary strands at an equimolar ratio (100 µM) in DPBS 1 × at 95 °C for 5 mn, and then allowing the solution to come back to room temperature. The hybridized species were then purified from the non-hybridized ones using AKTA Pure System (isocratic elution with DPBS (1x, pH 7.4), 0.5 mL/min).h ) The double stranded AOCs were prepared by two methods (Fig. 5): The double stranded AOCs were prepared by two methods (Fig. 5): Method 1. T-ssON conjugate was mixed with an excess (4.5 equiv.) of complementary strand in DPBS 1x (pH 7.4), incubated at 37 °C for 30 min, and purified by gel filtration chromatography using AKTA Pure System (isocratic elution with DPBS (1x, pH 7.4), 0.5 mL/min) to yield T-dsON. Method 2. 5′-BCN-modified oligonucleotide (3 equiv., 2.06 nmole, 400 µM in DPBS 1x), and its complemen- tary strand (4.5 equiv., 3.09 nmole, 1 mM in DPBS 1x) were mixed and stirred at 95 °C for 5 min, and then allowed to slowly return to room temperature. The mixture was then added with 3 µL of DPBS 10x, and then with the above-described azido-modified trastuzumab (1 equiv., 100 µg, 4.3 mg/mL). After incubation at 25 °C for 24 h, the formed T-dsON37 conjugate was purified using AKTA Pure System (isocratic elution with DPBS (1x, pH 7.4), 0.5 mL/min). Conjugates’ characterization. Protein‑oligonucleotide conjugates concentration determination. The concentration of a protein in a given solution can usually be determined by measuring its absorption at 280 nm, and using Beer-Lambert’s law. ON’s absorbance at 280 nm thus makes it impossible to determine the concentra- tion of protein-oligonucleotide conjugates through absorption spectrophotometry measurement. g j g g y Protein-oligonucleotide conjugates’ concentration was then determined using Pierce BCA protein assay kit (ThermoFisher ref 23225), following the manufacturer’s protocol. This method allows quantification of the pro- tein moiety’s concentration, regardless of the presence of conjugated ONs. Concentrations were used to calculate the yields of conjugation (see Table S1). Protein‑oligonucleotide conjugates DoC distribution determination by SDS PAGE. SDS-PAGE was performed on 4–20% Mini-PROTEAN TGX Gel (Bio-Rad ref 4561094) following the manufacturer’s procedure. Proteins, or protein-oligonucleotide conjugates (24 µL, 0.2 mg/mL in DPBS 1x) were added with 8 µL of non-reducing Laemmli SDS sample buffer (Alfa Aesar), and heated at 95 °C for 5 mn. www.nature.com/scientificreports/ Oligonucleotide purification. The previously obtained precipitate was then dissolved with water (100 µL) and purified by HPLC (detection at 260 nm, mobile phase gradient A/B 9:1 to 6:4 in 30 mn). After lyophilization, the ON conjugate was dissolved in DPBS (1x, pH 7.4) and analyzed by absorption spectrophotometry (measured at 260 nm using a Nanodrop) to calculate the solution’s concentration using Beer-Lambert’s law. Oligonucleotide purification. The previously obtained precipitate was then dissolved with water (100 µL) and purified by HPLC (detection at 260 nm, mobile phase gradient A/B 9:1 to 6:4 in 30 mn). After lyophilization, the ON conjugate was dissolved in DPBS (1x, pH 7.4) and analyzed by absorption spectrophotometry (measured at 260 nm using a Nanodrop) to calculate the solution’s concentration using Beer-Lambert’s law. Protein azido‑functionalization. 4-azidobenzoyl fluoride (ABF, 2) was synthetized as previously ­described7. 2 (3 equiv., 10 mM in DMSO) was added to a solution of protein (1 equiv., 5 mg/mL, 100 µL in DPBS 1x, pH 7.4) and the reaction mixture was incubated at 25 °C for 30 min. The excess of reagents was then removed by gel fil- tration chromatography using Bio-spin P-30 Columns (Bio-Rad, Hercules, U.S.A.) pre-equilibrated with DPBS (1x, pH 7.4) to give a solution of protein-azide conjugates, which was used in the following step. Protein‑oligonucleotide conjugates synthesis. The previously obtained 5′-BCN-modified oligonucleotide (3 equiv., 0.5–1 mM in DPBS 1x) and 10 µL of DPBS 10 × were added to a solution of the protein-azide conjugate (1 equiv., 5.0 mg/mL, in 100 µL DPBS 1x, pH 7.4). The mixture was purged with argon and incubated for 24 h at 25 °C. The conjugates were purified by gel filtration chromatography using AKTA Pure System (isocratic elution with DPBS (1x, pH 7.4), 0.5 mL/min) to yield the protein-oligonucleotide conjugates. Fluorescein labelling. 5′-fluorescein labelled (56-FAM) oligonucleotides were purchased from IDT.f Fluorescein labelling. 5′-fluorescein labelled (56-FAM) oligonucleotides were purchased from IDT. Proteins were concentrated to 1–5 mg/mL on micro-concentrators (Vivaspin, 50 and 10 kD cutoff, for anti- bodies and HSA, respectively, Sartorius, Gottingen, Germany), and added with 20 equiv. of FITC (10 mM in DMSO). The mixture was then incubated at 25 °C overnight. The excess of FITC was then removed by gel filtra- tion chromatography using Bio-spin P-30 Columns (Bio-Rad, Hercules, U.S.A.) pre-equilibrated with DPBS 1x (pH 7.5) to give a solution of FITC-labelled proteins. Double stranded oligonucleotides and antibody‑oligonucleotide conjugates synthesis. Materials and methods All reagents were obtained from commercial sources and used without prior purifications. Amino-modified (5AmMC12) oligonucleotides were purchased from IDT. Protein-oligonucleotide conjugates were purified by gel filtration using ÄKTA Pure System (isocratic elution with DPBS 1x, pH 7.5, 0.5 mL/mn, column: Superdex 200 Increase 10/300 GL). The oligonucleotide species were purified using a Shimadzu HPLC system (pumps: LC 20-AD, detector: SPD 20-A, autosampler: SIL 20-A) using a XTerra MS C18 5 μM 4.6 × 150 mm column (Waters), with a flow rate of 1 mL/mn (Mobile phase: A triethylammonium acetate 50 mM in water, B triethylammonium acetate 50 mM in acetonitrile). Conjugates synthesis. Oligonucleotide functionalization. BCN-PEG6-PFP (1) was synthesized as previ- ously ­described7. In a 2 mL Eppendorf tube, 5′-amino-modified oligonucleotide (1 equiv., 50 µL, 1 mM in water) was combined with 1 (20 equiv., 50 µL, 20 mM in DMSO) and ­NaHCO3 (100 equiv., 5 µL, 1 M in water). The mixture was incubated at 25 °C overnight. The mixture was then diluted with water to a final volume of 300 µL and added with acetone (900 µL) and ­LiClO4 (20 µL, 3 M in water) in order to precipitate the oligonucleotide species. The sample was then centrifuged (15,000 G, 8 mn) and the supernatant was discarded. The precipitate was dissolved with water (300 µL) to repeat the precipitation and centrifugation procedure a second time. https://doi.org/10.1038/s41598-021-85352-w Scientific Reports | (2021) 11:5881 | www.nature.com/scientificreports/ Received: 16 July 2020; Accepted: 29 January 2021 www.nature.com/scientificreports/ We measured the interactions of fluorescein-labelled proteins and oligonucleotides with living cells in real-time using LigandTracer Green (Ridgeview intruments).h The Petri dish on which cells were grown (see above) was placed on the inclined rotating support of the instrument, with the Blue/Green detector placed on its upper part.hl First, a baseline signal was collected for 30 min. The fluorescein-labelled compound was then added in two steps at increasing concentrations (10 and 30 nM). Inclination of the Petri dish allows for the addition of the fluorescein-labelled compounds outside of the detection area. For each rotation of the Petri dish, the signal from the three areas containing cells (two spots for SK-BR-3, one for MDA-MB-231) and a background reference area (plastic) is recorded. Measurements last 30 s each, with 5 s in between each of them to allow the medium to sit in the lower part of the Petri dish. This results in three background-subtracted real-time binding curves, which represent the binding of the fluorescein-labelled compound to each cell-containing area.fi p gl p g For each concentration the incubation was performed until a sufficient curvature was obtained for the sub- sequent extraction of kinetic parameters. Dissociation of the ligand was recorded after replacing the incubation solution with 3 ml of fresh medium. Signals from cell and reference areas are recorded during every rotation, resulting in a background-subtracted binding curve. Binding traces were analyzed with the evaluation software TraceDrawer 1.8.1 (Ridgeview Instru- ments) in order to determine ­ka according to the Langmuir, or “one-to-one”, binding model. Competition assay. After collection of the baseline signal, 100 equiv. of unlabelled ssON37 (relative to the total added amount of T*-ssON) were added to the medium. After 30 mn, the time-resolved analysis of T*-ssON binding was performed as previously described (Fig. S17). Received: 16 July 2020; Accepted: 29 January 2021 www.nature.com/scientificreports/ www.nature.com/scientificreports/ Additionally, we analyzed the deglycosylated azido-modified trastuzumab intermediate by native mass spec- trometry (see figure S2). As observed in a previous ­work7, the mean DoC values obtained by integration of SDS-PAGE gel bands of the Ab-ssON conjugate (2.9) and native MS of the azido-modified intermediate (2.8) were closely correlated. Proteins and protein‑oligonucleotide conjugate degree of labelling (DoL) determination. After FITC-labelling, the fluorescein concentration of each protein and protein-ON conjugate was measured by absorption spectropho- tometry using NanoDrop’s “proteins and labels” mode.h y g p p The DoL of each compound was calculated using Eq. (2) (see Table S1). y g p p The DoL of each compound was calculated using Eq. (2) (see Table S1). (2) DoL = fluorescein concentration (M) Protein concentration (M) (2) For fluorescein-labelled proteins, the protein concentration was determined by absorption at 280 nm, while for fluorescein-labelled protein-ON conjugates, it was determined by BCA assay (see above). For fluorescein-labelled proteins, the protein concentration was determined by absorption at 280 nm, while for fluorescein-labelled protein-ON conjugates, it was determined by BCA assay (see above). Binding assays. Cell culture. Human breast adenocarcinoma cells SK-BR-3 (ATCC HTB-30) and MDA- MB-231 (ATCC HTB-26)) were grown in Dulbecco’s Modified Eagle’s Medium (DMEM) containing 4.5 g/L glucose (Sigma, St Louis, MO, USA). The medium was supplemented with 10% fetal bovine serum (Perbio, Brebieres, France), 2 mM L-Glutamine, 100 U/mL Penicillin and 100 µg/mL Streptomycin (Sigma). Cells were maintained in a 5% CO2 humidified atmosphere at 37 °C. i p SK-BR-3 cells overexpress HER2 protein, and MDA-MB-231 cells are used as negative controls. Th d b f h d ( d ) ll The day before the experiment on Ligand Tracer Green (Ridgeview Instruments), cells were seeded as 600 μL droplets with 8 × 105 cells/mL near the edge in 87 mm cell culture treated dishes (Greiner, Frickenhausen, Germany) and incubated at 37 °C overnight. Two droplets were prepared with SK-BR-3, one with MDA-MB-231, and one was left as a background reference (plastic). t g p Prior to kinetic measurements, the medium was carefully removed and 3 mL of fresh complete medium was added to the dish. Time‑resolved analysis of ligand binding assays. www.nature.com/scientificreports/ 10 µL of the resulting solutions were deposited, and the gel was run at constant voltage (200 V) for 35 mn using TRIS 0.25 M—Glycine 1.92 M—SDS 1% as a running buffer. Coomassie Blue staining was performed using InstantBlue solution, prior to visualization on GeneGenius bio-imaging system (Syngene).ht The lines’ intensities were determined using the Image Studio Lite 5.2 software (LI-COR Biosciences), and the DoC of each conjugate was calculated using the following formula (Eq. 1): (1) DoC =  k k × I(DoCk)  k I(DoCk) (1) where I(DoCk) is the line’s intensity of the conjugate with k conjugated oligonucleotides per antibody. https://doi.org/10.1038/s41598-021-85352-w https://doi.org/10.1038/s41598-021-85352-w https://doi.org/10.1038/s41598-021-85352-w Scientific Reports | (2021) 11:5881 | 1. Dovgan, I., Koniev, O., Kolodych, S. & Wagner, A. Antibody-oligonucleotide conjugates as therapeutic, imaging, and detection agents. Bioconjug. Chem. 30(10), 2483–2501. https​://doi.org/10.1021/acs.bioco​njche​m.9b003​06 (2019). 10(1), 1–9. https​://doi.org/10.1038/s4159​8-020-64518​-y (2020). 3. Walker, I., Irwin, W. J. & Akhtar, S. Improved cellular delivery of antisense oligonucleotides using transferrin receptor antibody- oligonucleotide conjugates. Pharm. Res. 12(10), 1548–1553. https​://doi.org/10.1023/A:10162​60110​049 (1995).h oligonucleotide conjugates. Pharm. Res. 12(10), 1548 1553. https​://doi.org/10.1023/A:10162​60110​049 (1995). 4. Bennett, R. M. As nature intended? The uptake of DNA and oligonucleotides by eukaryotic cells. Antisense Res. Dev. 3(3), 235–241. https​://doi.org/10.1089/ard.1993.3.235 (1993).hil www.nature.com/scientificreports/ www.nature.com/scientificreports/ 7. Dovgan, I. et al. Acyl fluorides: fast, efficient, and versatile lysine-based protein conjugation via plug-and-play strategy. Bioconjug. Chem. 28(5), 1452–1457. https​://doi.org/10.1021/acs.bioco​njche​m.7b001​41 (2017).fi 8. Björke, H. & Andersson, K. Measuring the affinity of a radioligand with its receptor using a rotating cell dish with in situ refer area. Appl. Radiat. Isot. Data Instrum. Methods Use Agric. Ind. Med. 64(1), 32–37. https​://doi.org/10.1016/j.aprad​iso.2005.06 (2006). (2006). 9. Björke, H. & Andersson, K. Automated, high-resolution cellular retention and uptake studies in vitro. Appl. Radiat. Isot. Data ( ) 9. Björke, H. & Andersson, K. Automated, high-resolution cellular retention and uptake studies in vitro. Appl. Radiat. Isot. Data Instrum. Methods Use Agric. Ind. Med. 64(8), 901–905. https​://doi.org/10.1016/j.aprad​iso.2006.03.002 (2006). g g j 0. Bondza, S. et al. Real-time characterization of antibody binding to receptors on living immune cells. Front. Immunol. 8, 455. https ://doi.org/10.3389/fimmu​.2017.00455​ (2017).hflfi gi 1. Szabó, Á. et al. The effect of fluorophore conjugation on antibody affinity and the photophysical properties of dyes. Biophys. J 114(3), 688–700. https​://doi.org/10.1016/j.bpj.2017.12.011 (2018). ( ) p g j pj ( ) 2. Buecheler, J. W., Winzer, M., Weber, C. & Gieseler, H. Alteration of physicochemical properties for antibody-drug conjugates and their impact on stability. J. Pharm. Sci. 109(1), 161–168. https​://doi.org/10.1016/j.xphs.2019.08.006 (2020). p y p g j p 13. Acchione, M., Kwon, H., Jochheim, C. M. & Atkins, W. M. Impact of linker and conjugation chemistry on antigen binding, Fc recep- tor binding and thermal stability of model antibody-drug conjugates. MAbs 4(3), 362–372. https​://doi.org/10.4161/mabs.19449​ (2012).h 4. Leng, Q., Woodle, M. C. & Mixson, A. J. Targeted Delivery of siRNA Therapeutics to Malignant Tumors https​://www.hinda​wi.com/ journ​als/jdd/2017/69712​97/ (accessed Mar 26, 2020). .https​://doi.org/10.1155/2017/69712​97. 5. Liu, T. et al. Selective delivery of doxorubicin to EGFR+ cancer cells by cetuximab-DNA conjugates. ChemBioChem 20(8), 1014– 1018. https​://doi.org/10.1002/cbic.20180​0685 (2019). p g 6. Cuellar, T. L. et al. Systematic evaluation of antibody-mediated SiRNA delivery using an industrial platform of THIOMAB-SiRNA conjugates. Nucleic Acids Res. 43(2), 1189–1203. https​://doi.org/10.1093/nar/gku13​62 (2015). j g g g 7. Liu, G. et al. Pretargeting CWR22 prostate tumor in mice with MORF-B723 antibody and radiolabeled CMORF. Eur. J. Nucl. Med Mol. Imaging 35(2), 272–280. https​://doi.org/10.1007/s0025​9-007-0606-z (2008). g g 35(2), 272–280. https​://doi.org/10.1007/s0025​9-007-0606-z (2008 g g p g 8. Liu, G. et al. A novel pretargeting method for measuring antibody internalization in tumor cells. Cancer Biother. Radiopharm 22(1), 33–39. https​://doi.org/10.1089/cbr.2006.339 (2007).h g 9. Verhoeven, M., Seimbille, Y. & Dalm, S. U. Therapeutic applications of pretargeting. www.nature.com/scientificreports/ Pharmaceutics https​://doi.org/10.3390/pharm aceut​ics11​09043​4 (2019). 0. Hsu, N.-S. et al. Development of a versatile and modular linker for antibody-drug conjugates based on oligonucleotide strand pairing. Bioconjug. Chem. 31(7), 1804–1811. https​://doi.org/10.1021/acs.bioco​njche​m.0c002​81 (2020). 1. Schreiber, C. L. & Smith, B. D. Molecular conjugation using non-covalent click chemistry. Nat. Rev. Chem. 3(6), 393–400. https​:// doi.org/10.1038/s4157​0-019-0095-1 (2019). g 2. Rosier, B. J. H. M. et al. Incorporation of native antibodies and fc-fusion proteins on DNA nanostructures via a modular conjuga- tion strategy. Chem. Commun. 53(53), 7393–7396. https​://doi.org/10.1039/C7CC0​4178K​ (2017).i 23. Kuijpers, W. H., Bos, E. S., Kaspersen, F. M., Veeneman, G. H. & van Boeckel, C. A. Specific recognition of antibody-oligonucleotide conjugates by radiolabeled antisense nucleotides: a novel approach for two-step radioimmunotherapy of cancer. Bioconjug. Chem. 4(1), 94–102. https​://doi.org/10.1021/bc000​19a01​3 (1993).ii ( ) p g ( ) 24. Kazane, S. A. et al. Site-Specific DNA-antibody conjugates for specific and sensitive immuno-PCR. Proc. Natl. Acad. Sci. 109(10), 3731–3736. https​://doi.org/10.1073/pnas.11206​82109​ (2012).i p g p 5. Li, G. et al. An activity-dependent proximity ligation platform for spatially resolved quantification of active enzymes in single cells Nat. Commun. 8(1), 1775. https​://doi.org/10.1038/s4146​7-017-01854​-0 (2017). p g 6. Leino, M. et al. Optimization of proximity-dependent initiation of hybridization chain reaction for improved performance. Mol Syst. Des. Eng. 4(5), 1058–1065. https​://doi.org/10.1039/C9ME0​0079H​ (2019). 26. Leino, M. et al. Optimization of proximity-dependent initiation of hybridization chain reacti Syst. Des. Eng. 4(5), 1058–1065. https​://doi.org/10.1039/C9ME0​0079H​ (2019). 27. Koos, B. et al. Proximity-dependent initiation of hybridization chain reaction. Nat. Commun. 6(1), 7294. https​://doi.org/10.1038/ ncomm​s8294​ (2015).fi 8. Niemeyer, C. M., Boldt, L., Ceyhan, B. & Blohm, D. DNA-directed immobilization: efficient, reversible, and site-selective surface binding of proteins by means of covalent DNA-streptavidin conjugates. Anal. Biochem. 268(1), 54–63. https​://doi.org/10.1006/ abio.1998.3017 (1999).i 28. Niemeyer, C. M., Boldt, L., Ceyhan, B. & Blohm, D. DNA-directed immobilization: efficient, reversible, and site-selective surface binding of proteins by means of covalent DNA-streptavidin conjugates. Anal. Biochem. 268(1), 54–63. https​://doi.org/10.1006/ abio.1998.3017 (1999). 29 Rychlik, W, Spencer, W J & Rhoads, R E Optimization of the annealing temperature for DNA amplification in vitro Nucleic g p y p j g p g abio.1998.3017 (1999). 29. Rychlik, W., Spencer, W. J. & Rhoads, R. E. Optimization of the annealing temperature for DNA amplification in vitro. Nucleic Acids Res 18(21) 6409–6412 https://doi org/10 1093/nar/18 21 6409 (1990) 29. Rychlik, W., Spencer, W. J. & Rhoads, R. E. Optimization of the annealing temperature for DNA amplification in vitro. Nu Acids Res. 18(21), 6409–6412. www.nature.com/scientificreports/ https​://doi.org/10.1093/nar/18.21.6409 (1990).fi ( ) p g ( ) 30. Juliano, R. L., Ming, X., Carver, K. & Laing, B. Cellular uptake and intracellular trafficking of oligonucleotides: implications for oligonucleotide pharmacology. Nucleic Acid Ther. 24(2), 101–113. https​://doi.org/10.1089/nat.2013.0463 (2014).ii p g 30. Juliano, R. L., Ming, X., Carver, K. & Laing, B. Cellular uptake and intracellular trafficking of oligonucleotides: implicatio fi oligonucleotide pharmacology. Nucleic Acid Ther. 24(2), 101–113. https​://doi.org/10.1089/nat.2013.0463 (2014). 31. Miller, C. M. et al. Stabilin-1 and Stabilin-2 are specific receptors for the cellular internalization of phosphorothioate 1. Miller, C. M. et al. Stabilin-1 and Stabilin-2 are specific receptors for the cellular internalization of phosphorothioate-modified antisense oligonucleotides (ASOs) in the liver. Nucleic Acids Res. 44(6), 2782–2794. https​://doi.org/10.1093/nar/gkw11​2 (2016). , pi p p p antisense oligonucleotides (ASOs) in the liver. Nucleic Acids Res. 44(6), 2782–2794. https​://doi.org/10.1093/nar/gkw11​2 (20 antisense oligonucleotides (ASOs) in the liver. Nucleic Acids Res. 44(6), 2782–2794. https​://doi.org/10.1093/nar/gkw11​2 (2016). 2. Butler, M. et al. Phosphorothioateoligodeoxynucleotides distribute similarly in class a scavenger receptor knockout and wild-type mice. J. Pharmacol. Exp. Ther. 292(2), 489–496 (2000). mice. J. Pharmacol. Exp. Ther. 292(2), 489–496 (2000). ph 33. Duxbury, M. S., Ashley, S. W. & Whang, E. E. RNA interference: a mammalian SID-1 homologue enhances SiRNA uptake and gene silencing efficacy in human cells. Biochem. Biophys. Res. Commun. 331(2), 459–463. https​://doi.org/10.1016/j.bbrc.2005.03.199 (2005). 34. Wolfrum, C. et al. Mechanisms and optimization of in vivo delivery of lipophilic SiRNAs. Nat. Biotechnol. 25(10), 1149–1 https​://doi.org/10.1038/nbt13​39 (2007). g 35. Takahashi, M. et al. SIDT2 mediates gymnosis, the uptake of naked single-stranded oligonucleotides into living cells. RNA 14(11), 1534–1543. https​://doi.org/10.1080/15476​286.2017.13026​41 (2017). References e e e ces 1. Dovgan, I., Koniev, O., Kolodych, S. & Wagner, A. Antibody-oligonucleotide conjugates as therapeutic, imaging, and detection agents. Bioconjug. Chem. 30(10), 2483–2501. https​://doi.org/10.1021/acs.bioco​njche​m.9b003​06 (2019). g j g p g 4. Bennett, R. M. As nature intended? The uptake of DNA and oligonucleotides by eukaryotic cells. Antisense Res. Dev. 3(3), 235–241. https​://doi.org/10.1089/ard.1993.3.235 (1993).hil g j g p g 4. Bennett, R. M. As nature intended? The uptake of DNA and oligonucleotides by eukaryotic cells. Antisense Res. Dev. 3(3), 235–241. https​://doi.org/10.1089/ard.1993.3.235 (1993).hil p g ( ) 5. Lu, T. et al. The non-specific binding of fluorescent-labeled MiRNAs on cell surface by hydrophobic interaction. PLoS ONE 11(3) e0149751. https​://doi.org/10.1371/journ​al.pone.01497​51 (2016).f p g j p ( ) 6. Bondza, S., Stenberg, J., Nestor, M., Andersson, K. & Björkelund, H. Conjugation effects on antibody-drug conjugates: evaluation of interaction kinetics in real time on living cells. Mol. Pharm. 11(11), 4154–4163. https​://doi.org/10.1021/mp500​379d (2014). p g j p ( ) 6. Bondza, S., Stenberg, J., Nestor, M., Andersson, K. & Björkelund, H. Conjugation effects on antibody-drug conjugates: evaluation of interaction kinetics in real time on living cells. Mol. Pharm. 11(11), 4154–4163. https​://doi.org/10.1021/mp500​379d (2014). p g j p ( ) 6. Bondza, S., Stenberg, J., Nestor, M., Andersson, K. & Björkelund, H. Conjugation effects on antibody-drug conjugates: evaluation of interaction kinetics in real time on living cells. Mol. Pharm. 11(11), 4154–4163. https​://doi.org/10.1021/mp500​379d (2014). https://doi.org/10.1038/s41598-021-85352-w Scientific Reports | (2021) 11:5881 | Acknowledgements g International Center for Frontier Research in Chemistry (icFRC), Region Alsace and the French Proteomic Infrastructure (ProFI; ANR-10-INBS-08-03) are acknowledged for their financial support. g nternational Center for Frontier Research in Chemistry (icFRC), Region Alsace and the French Proteomic nfrastructure (ProFI; ANR-10-INBS-08-03) are acknowledged for their financial support. Author contributions V.L. synthesized the conjugates, I.K. and M.N. performed the binding assays, S.E. performed the MS experi- ments, V.L. and A.W. wrote the manuscript, S.K., S.C., and G.C. contributed to the interpretation of results and revised the manuscript critically, S.C., and A.W. supervised the project. All authors reviewed the manuscript. www.nature.com/scientificreports/ www.nature.com/scientificreports/ org/10.1038/s4159​8-021-85352​-w. Correspondence and requests for materials should be addressed to A.W. Competing interests h 8 orts | (2021) 11:5881 | https://doi.org/10.1038/s41598-021-85352-w Additional information Supplementary Information The online version contains supplementary material available at https​://doi. Scientific Reports | (2021) 11:5881 | https://doi.org/10.1038/s41598-021-85352-w Reprints and permissions information is available at www.nature.com/reprints. Reprints and permissions information is available at www.nature.com/reprints. Publisher’s note  Springer Nature remains neutral with regard to jurisdictional claims in published maps and nstitutional affiliations. Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat​iveco​mmons​.org/licen​ses/by/4.0/. © The Author(s) 2021 https://doi.org/10.1038/s41598-021-85352-w Scientific Reports | (2021) 11:5881 |
https://openalex.org/W2768173523
https://discovery.ucl.ac.uk/id/eprint/10038756/1/Forster_fdx145.pdf
English
null
Public awareness and healthcare professional advice for obesity as a risk factor for cancer in the UK: a cross-sectional survey
Journal of public health
2,017
cc-by
5,931
ABSTRACT Background Overweight and obesity is the second biggest preventable cause of cancer after smoking, causing ~3.4 million deaths worldwide. This study provides current UK data on awareness of the link between obesity and cancer by socio-demographic factors, including BMI, and explores to what degree healthcare professionals provide weight management advice to patients. Methods Cross-sectional survey of 3293 adults completed an online survey in February/March 2016, weighted to be representative of the UK population aged 18+. Results Public awareness of the link between obesity and cancer is low (25.4% unprompted and 57.5% prompted). Higher levels of awareness existed for least deprived groups (P < 0.001), compared to more deprived groups. Most respondents had seen a healthcare practitioner in the past 12 months (91.6%) and 17.4% had received advice about their weight, although 48.4% of the sample were overweight/obese. Conclusion Cancer is not at the forefront of people’s minds when considering health conditions associated with overweight or obesity. Socio- economic disparities exist in health knowledge across the UK population, with adults from more affluent groups being most aware. Healthcare professionals are uniquely positioned to provide advice about weight, but opportunities for intervention are currently under-utilized in healthcare settings. Keywords cancer, obesity, socio-economic factors current overweight and obesity trends continue in the UK there could be an additional 670 000 cancer cases by 2035.7 Public awareness and healthcare professional advice for obesity as a risk factor for cancer in the UK: a cross-sectional survey 1Policy Research Centre for Cancer Prevention (PRCP), Cancer Research UK, Angel Building, 407 St. John Street, London EC1V 4AD, UK 2Centre for Research into Cancer Prevention and Screening, Level 7, Ninewells Hospital and Medical School, University of Dundee, Dundee DD1 9SY, UK 3Department of Behavioural Science and Health, UCL, Gower Street, London WC1E 6BT, UK 4Cancer Research UK, Angel Building, 407 St. John Street, London EC1V 4AD, UK 5University of Stirling, Stirling FK9 4LA, UK Add d L i H E il l i h @ k Address correspondence to Lucie Hooper, E-mail: lucie.hooper@cancer.org.uk © The Author 2017. Published by Oxford University Press on behalf of Faculty of Public Health. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. 1 Journal of Public Health | pp. 1–9 | doi:10.1093/pubmed/fdx145 Journal of Public Health | pp. 1–9 | doi:10.1093/pubmed/fdx145 Downloaded from https://academic.oup.com/jpubhealth/advance-article-abstract/doi/10.1093/pubmed/fdx145/4582914 by University College London user on 11 December 2017 Downloaded from https://academic.oup.com/jpubhealth/advance-article-abstract/doi/10.1093/pubmed/fdx145/4582914 by University College London user on 11 December 2017 ttps://academic.oup.com/jpubhealth/advance-article-abstract/doi/10.1093/pubmed/fdx145/4582914 lege London user 17 Address correspondence to Lucie Hooper, E-mail: lucie.hooper@cancer.org.uk © The Author 2017. Published by Oxford University Press on behalf of Faculty of Public Health. This is an Open Access article distributed under the terms of the Creative Commons Attribution L distribution, and reproduction in any medium, provided the original work is properly cited. Measures Questions included in the survey were informed by previous research conducted by Buykx et al.18 in Australia. Additional items were incorporated from other survey tools and adapted where necessary. Where no existing tools could be found, new questions were developed and tested for clarity, content and style of questions using Cancer Research UK’s patient panel group and health professionals from the Scottish Cancer Prevention Network. Key demographic information held by YouGov included gender, age and region lived, including nine English regions, Wales, Scotland and Northern Ireland. Socio-economic sta- tus (SES) was calculated by YouGov based on the National Readership Survey (NRS) system and grouped into four: AB (higher and intermediate managerial, administrative, profes- sional occupations), C1 (supervisory, clerical and junior managerial, administrative, professional occupations), C2 (skilled manual occupations), DE (semi-skilled and unskilled manual occupations, unemployed and lowest grade occupa- tions). BMI was calculated using self-reported height and weight: weight (kg)/(height (m2)). BMI categories were grouped: underweight (<18.5 kg/m2), normal weight (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2), obese (>30 kg/m2).19 Any cancer diagnosis was also recorded. Research into cancer risk awareness amongst the UK population has shown differences in understanding between groups based on factors such as socio-economic status and ethnicity.10–12 However, there are few studies that examine how differences in body mass index (BMI) are related to awareness of overweight and obesity as a risk factor for can- cer. In addition, few studies have examined cancer risk aware- ness and weight in the context of whether individuals have been given advice by healthcare professionals about the importance of maintaining a healthy weight. Previous research has suggested that overweight and obese adults are more likely to want to weigh less and attempt to lose weight after having received healthcare practitioner advice.13 Despite this, only a minority of patients report receiving advice on weight loss.13 Both patients and healthcare professionals have expressed frustrations with discussing advice regarding weight loss.14 Healthcare professionals may not be fully equipped15,16 to engage with patients about why weight is an important risk factor for a range of health conditions,17 including cancer. Cancer risk awareness was explored using an unprompted open-ended question: ‘Which, if any, health conditions do you think can result from being obese/ overweight?’; and a prompted question: ‘Which, if any, of the following health conditions do you think can result from being overweight/ obese?’ Prompted response options included diabetes, heart disease, stroke, cancer and arthritis. Measures Unprompted and prompted cancer awareness were both coded into dichotom- ous variables (aware of obesity as a risk factor for cancer versus not). Participants were provided with a list of thirteen cancer types and asked to select whether a person would be at increased risk of developing each cancer through being overweight or obese. ‘Yes’, ‘No’ and ‘Don’t know’ response options were provided. The four most prevalent cancer types in the UK associated with body weight were selected for analysis: breast (postmenopausal), kidney, bowel and womb. Responses were coded into two variables: ‘Yes’ if participants had selected the correct response, and ‘No’ if they incorrectly selected the cancer type. Don’t know responses were re-coded as ‘No’ responses. Given these gaps in the literature this study aimed to investigate: public knowledge of health conditions linked to overweight and obesity, particularly cancer and the factors that influence this; and to determine whether adults in the UK who access healthcare services had been given advice about their weight. Background Overweight and obesity is a contributor to diseases such as diabetes, coronary heart disease, stroke and cancer.1 In 2010 these conditions were estimated to have caused 3.4 million deaths and 4% of years of life lost worldwide.2 Latest data has found that 63% of the English3 and 67% of the Scottish adult population are overweight or obese.4 Lucie Hooper, MSc, Researcher Annie S. Anderson, PhD, Professor of Public Health Nutrition Jack Birch, Research Assistant Alice S. Forster, PhD, Senior Research Associate Gillian Rosenberg, PhD, Senior Researcher Linda Bauld, PhD, Chair in Behavioural Research for Cancer Prevention and Professor of Health Policy Jyotsna Vohra, PhD Head of Policy Research Centre for Cancer Prevention (PRCP) Lucie Hooper, MSc, Researcher Annie S. Anderson, PhD, Professor of Public Health Nutrition Jack Birch, Research Assistant Alice S. Forster, PhD, Senior Research Associate Gillian Rosenberg, PhD, Senior Researcher Linda Bauld, PhD, Chair in Behavioural Research for Cancer Prevention and Professor of Health Policy Jyotsna Vohra, PhD Head of Policy Research Centre for Cancer Prevention (PRCP) Obesity is associated with thirteen types of cancer,5 including breast (postmenopausal), kidney, bowel, and womb. In the UK 18 100 cancer cases are attributable to obesity, ~5% of all cancers.6 A recent study estimated that if JOURNAL OF PUBLIC HEALTH In the UK, few studies have explored public knowledge of the risks of obesity and associations with cancer. Reported levels of awareness have varied, perhaps due to differences in study design and recruitment approaches. One UK survey conducted in 2014 found that when asked an unprompted question only 10% of respondents recalled that being overweight is a risk factor for cancer.8 Latest WCRF data found 62% Britons to be aware of obesity as a risk fac- tor for cancer.9 Downloaded from https://academic.oup.com/jpubhealth/advance-article-abstract/doi/10.1093/pubmed/fdx145/4582914 by University College London user on 11 December 2017 Analysis y Data were analysed using IBM SPSS Version 23 and Statacorp Stata Statistical Software release 13. Weights were applied to age, gender, SES and region to ensure the results were representative of the population. Weighted results are presented here, unless otherwise specified. Univariable chi squared analysis was undertaken to explore the relationship between cancer awareness and socio-demographic factors and BMI. Age, SES, gender, BMI and the cancer diagnosis variables were then entered into a multivariable logistic regression model, with step-wise elimination of non- significant variables. Ordinal regression was carried out to explore factors associated with receiving healthcare practi- tioner advice. As we are interested in advice given to over- weight and obese people, the underweight BMI category was coded as missing for the regression analysis. Response cat- egories: advice to gain weight; other advice; not applicable; and don’t know/can’t remember responses were coded as missing for the analysis. Methods An online cross-sectional survey exploring knowledge of health risks associated with being overweight or obese was conducted in February 2016. A total of 3490 adults aged 18 and over were recruited by market research company, YouGov. The survey was weighted to be representative of the UK population. Geographically targeted over-samples of an additional 500 participants were obtained from Wales, Scotland and Northern Ireland to provide data relevant to these jurisdictions. There were 3293 complete responses to the survey (response rate = 94%). Participants were credited with 50 points (equivalent to 50p) to their YouGov account once the survey was completed. Respondents were asked, ‘In the past 12 months, has a doctor, nurse, or other healthcare professional given you advice about your weight?’. Response options included: ‘No’, ‘Yes, lose weight’, ‘Yes, gain weight’, ‘Yes, maintain current weight’, ‘Not applicable, have not seen a healthcare AWARENESS OF OBESITY AS A RISK FACTOR FOR CANCER IN THE UK AND HEALTHCARE PROFESSIONAL ADVICE 3 Table 1 Profile of sample population Unweighted sample (n = 3293) Weighted sample (n = 3292) n (%) n (%) Gender Male 1580 (48) 1604 (48.7) Female 1713 (52) 1689 (51.3) Age 18–39 1006 (30.5) 1202 (36.5) 40–59 1274 (38.7) 1126 (34.2) 60+ 1013 (30.8) 965 (29.3) Region of residence North East 89 (2.7) 135 (4.1) North West 234 (7.1) 362 (11) Yorkshire and the Humber 173 (5.3) 273 (8.3) East Midlands 145 (4.4) 237 (7.2) West Midlands 179 (5.4) 290 (8.8) East of England 206 (6.3) 306 (9.3) London 272 (8.3) 428 (13) South East 294 (8.9) 451 (13.7) South West 181 (5.5) 280 (8.5) Wales 503 (15.3) 158 (4.8) Scotland 513 (15.6) 280 (8.5) Northern Ireland 504 (15.3) 92 (2.8) Socio-economic status (SES) AB 913 (27.7) 724 (22) C1 1037 (31.5) 988 (30) C2 538 (16.3) 494 (15) DE 805 (24.4) 1087 (33) Body mass index (BMI) Underweight 75 (2.3) 85 (2.6) Normal weight 1244 (37.8) 1327 (40.3) Overweight 1015 (30.8) 944 (28.7) Obese 700 (21.3) 648 (19.7) Not calculated 259 (7.9) 290 (8.8) Cancer diagnosis Ever been diagnosed with cancer 151 (4.8) 145 (4.6) Never been diagnosed with cancer 3018 (95.2) 3009 (95.4) professional in the past 12 months’, ‘Don’t know/can’t remember’. Advice to gain weight, other advice, not applic- able and don’t know/can’t remember responses were coded as missing for the analysis. Downloaded from https://academic.oup.com/jpubhealth/advance-article-abstract/doi/10.1093/pubmed/fdx145/4582914 by University College London user on 11 December 2017 Univariate analysis the highest social grade (AB) showed greatest awareness compared to all other SES groups (C1 P = 0.11, OR = 0.77, C2 P < 0.001, OR = 0.573, DE P < 0.001, OR = 0.515) (Table 3). For the unprompted cancer awareness question, it was found that SES (30.1% AB versus 22% DE P < 0.001) and having ever had a cancer diagnosis were significant factors in cancer awareness (34.5% ever diagnosed versus 24.7% never diagnosed P = 0.008). Gender also had a small but significant association with awareness (26.9% females versus 23.8% males P = 0.041). Gender was an independent predictor for cancer type awareness for postmenopausal breast and kidney cancer with females (P < 0.001, OR = 0.746) and males (P = 0.022, OR = 1.177) more likely to be aware of body weight association, respectively. Those from the highest SES group (AB) were most likely to be aware of each cancer type, com- pared to all other groups (postmenopausal breast: C2 P = 0.006 OR = 1.436, DE P < 0.001, OR = 1.506; kidney: C1 P = 0.021, OR = 1.259, DE P < 0.001, OR = 1.634; bowel: DE P < 0.001 OR = 1.836; womb: C1 P = 0.040. OR = 1.291, C2 P = 0.012, OR = 1.469). Those aged 18–39 years old were most likely to know that kidney (40–59 P < 0.001, OR = 1.722, 60 + P < 0.001 OR = 1.759) and womb (40–59 P = 0.002, OR = 1.384, 60 + P < 0.001, OR = 1.757) cancers are associated with overweight and obesity compared to all other age groups (Table 3). Prompted awareness was significantly associated with SES and BMI. AB respondents were more likely to be aware of being overweight or obese as a risk factor for cancer than all of the other social grades (66.6 versus 50.6% P < 0.001). Respondents of normal weight were the most likely to be aware of overweight/obesity as a risk factor for cancer and respondents who were obese were the least likely to be aware (63.6 versus 52.3%, P < 0.001). Of the four cancer types examined, awareness of their association with overweight/obesity was greatest from the highest SES group (AB) across all cancer types (P < 0.001). Results A nationally representative sample of 3293 people from England, Wales, Scotland and Northern Ireland completed the survey. Of these, 51.3% were females and 48.7% were males. The proportion in each of the SES categories were: AB 22%; C1 30%; C2 15%, DE 33% (Table 1). Unprompted, only 25.4% of respondents listed cancer as a health condition that could result from being overweight or obese. When prompted with a list of potential health con- ditions, 57.5% selected cancer. Arthritis was the least selected health condition (50%) and diabetes was the most selected condition (93.6%). For cancer types known to be associated with overweight and obesity, knowledge was wide-ranging with responses ranging from 21.5% for womb cancer to 60.1% for bowel cancer. current weight; 1% to gain weight and the remaining 1% were given ‘other advice’. As the proportion of the sample given advice to gain weight or other advice was so small, they were excluded for the next stage of the analysis. The majority of the unweighted sample (52.1%) and just under half of the weighted sample (48.4%) were overweight or obese. Results examining the relationship between the weight of respondent and receipt of advice are outlined below. The vast majority of participants (3018/3293, 91.6%) had seen a seen a doctor, nurse or healthcare professional in a healthcare setting in the past 12 months and recalled whether or not they had received advice about their weight. Of these, 74.2% did not receive any advice and 17.4% had received some form of advice about their weight. Twelve percent had been told to lose weight; 4% to maintain their JOURNAL OF PUBLIC HEALTH Main finding of this study Awareness of being overweight or obese as a risk factor for cancer was generally low with only 25.4% of respondents listing cancer when asked an unprompted question. This shows that cancer is not at the forefront of people’s minds when considering health risks associated with body weight. When asked a prompted question, 57.5% of the sample recognized overweight/obesity as a risk factor for cancer; however, awareness of the association between overweight and diabetes was much greater (93.6%). In both instances, SES played a significant role with those from the highest SES group being more aware than the other SES groups. Univariate analysis People who were normal weight were most likely to know of the relationship between all cancer types and obesity (P < 0.001) apart from womb cancer (P = 0.065) Highest aware- ness was found among 18–39 year olds for kidney and womb cancers (P < 0.001) and there was greater awareness among females for postmenopausal breast cancer (34 versus 28.1%, P < 0.001) and males for kidney cancer (46.2 versus 42%, P = 0.008). Ordinal regression analysis for healthcare practitioner advice found all factors were significant apart from age and having previously received a cancer diagnosis. Normal weight respondents were significantly less likely to receive advice to lose weight, but were more likely to be told to maintain weight than overweight or obese respondents (P < 0.001 OR = 5.844) (Table 4). All demographics listed: age, gender, SES, including BMI and cancer diagnosis were significant factors in receiving advice to lose or maintain weight. Around twice as many people aged over 60 received advice to lose weight com- pared to 18–39 year olds (16.1 versus 7.8% P < 0.001). Obese and overweight respondents were significantly more likely to receive advice to lose weight than those who were normal weight (obese: 38.3% and overweight: 11.7% versus normal weight 2.3% P < 0.001). Downloaded from https://academic.oup.com/jpubhealth/advance-article-abstract/doi/10.1093/pubmed/fdx145/4582914 by University College London user on 11 December 2017 Multivariate analysis The logistic regression models for unprompted cancer awareness showed that the highest SES group (AB) were more likely to be aware of the links between overweight and cancer than those from the lowest two SES groups (C2 P < 0.001, OR = 0.532 and DE P < 0.001, OR = 0.638) as were males (compared to females) (P = 0.012, OR = 1.233). Having ever been diagnosed with cancer was also shown to be significant contributor to unprompted cancer awareness of obesity risk (P = 0.017, OR = 0.648) (Table 2). There were misconceptions about cancer types linked to overweight and obesity. Greater levels of awareness were found for cancers of the digestive system organs such as, bowel and kidney, but not for reproductive organs, such as womb or postmenopausal breast. The majority of respondents (91.6%) had seen a health- care practitioner in the past 12 months. However, only one in five respondents had been given any advice about their For prompted cancer awareness, the only factor inde- pendently associated with awareness was SES. Multivariate analysis Those from AWARENESS OF OBESITY AS A RISK FACTOR FOR CANCER IN THE UK AND HEALTHCARE PROFESSIONAL ADVICE 5 5 Table 2 Multivariate logistic regression results for unprompted and prompted awareness of the link between cancer and overweight/obesity Awareness of cancer (unprompted) Awareness of cancer (prompted) Yes (%) OR CI (95%) P-value Yes (%) OR CI (95%) P-value Overall (n = 3293) 25.4 – – – 57.5 – – – Gender Male (n = 1604) 23.8 – – – 58 – – – Female (n = 1690) 26.9 1.233 1.047–1.451 0.012 57 0.985 0.854–1.136 0.839 Age 18–39 (n = 1202) 26.4 – – – 59.4 – – – 40–59 (n = 1126) 25 0.983 0.809–1.195 0.866 56.4 0.945 0.796—1.122 0.519 60+ (n = 965) 24.8 0.951 0.772–1.171 0.636 56.4 0.953 0.794–1.143 0.603 Social grade AB (n = 724) 30.1 – – – 66.6 – – – C1 (n = 988) 28.8 0.927 0.746–1.151 0.491 60.5 0.77 0.631–0.941 0.011 C2 (n = 494) 19.2 0.532 0.402–0.705 <0.001 53.2 0.573 0.453–0.725 <0.001 DE (n = 1087) 22 0.638 0.512–0.795 <0.001 50.6 0.515 0.424–0.626 <0.001 BMI Underweight (n = 85) 26.2 – – – 58.3 – – – Normal Weight (n = 1327) 27.9 1.078 0.647–1.794 0.773 63.6 1.165 0.731–1.856 0.522 Overweight (n = 944) 25.5 0.977 0.581–1.642 0.931 58.1 0.937 0.583–1.503 0.786 Obese (648) 23.5 0.835 0.490–1.423 0.508 52.3 0.764 0.472–1.237 0.273 Diagnosed with cancer Ever been diagnosed with cancer (n = 137) 34.5 – – – 60.7 – – – Never been diagnosed with cancer (n = 2684) 24.7 0.648 0.454–0.924 0.017 56.8 0.88 0.624–1.241 0.467 Values highlighted in bold are P < 0.05. Table 2 Multivariate logistic regression results for unprompted and prompted awareness of the link between cancer and overweight/obesity ression results for unprompted and prompted awareness of the link between cancer and overweight/obesity weight and if advice was provided, it was focused on losing weight. It is positive that the group receiving advice to lose weight most often self-reported as being obese (38.3%) but this was not the case individuals who were overweight (11.7%). It is important that advice on weight is provided by health professionals to individuals who are overweight and therefore at higher risk of becoming obese. Multivariate analysis It is estimated that average weight gain in adulthood is around 400 g per annum and this may be greater with increasing age.20 weight and if advice was provided, it was focused on losing weight. It is positive that the group receiving advice to lose weight most often self-reported as being obese (38.3%) but this was not the case individuals who were overweight (11.7%). It is important that advice on weight is provided by health professionals to individuals who are overweight and therefore at higher risk of becoming obese. It is estimated that average weight gain in adulthood is around 400 g per annum and this may be greater with increasing age.20 significant impact on intention to change behaviour and lose weight.23 Healthcare settings are favourable environments for receiving weight loss advice13,24 and effecting behaviour change23,25,26 as well as raising cancer risk awareness.22 However, such opportunities are currently under-utilized.27 Downloaded from https://academic.oup.com/jpubhealth/advance-article-abstract/doi/10.1093/pubmed/fdx145/4582914 by University College London user on 11 December 2017 What the study adds This is the first study to explore factors associated with knowledge of obesity as a risk factor for cancer using both prompted and unprompted response options. Additionally, data on public awareness of the link between overweight/ obesity and cancer for the four most prevalent cancer types linked to overweight and obesity has been explored. Those from lower SES groups are more likely to be overweight or obese (64% males and 51% females in highest SES group compared to 67% males and 63% females in lowest SES group).28 Modelled projections show overweight and obesity trends will increase by 2035 (76% males and 69% females) and the gap between the highest and lowest income quintile is expected to widen further.7 This study lends support to the concept of providing targeted programmes for vulnerable populations. Whilst there is concern over health education ssocia t egression What is already known about this topic Although previous studies have collected data on aware- ness of obesity as a risk factor for cancer,8,9,11,12,21 there are limited data available for unprompted responses and particularly data exploring knowledge of risks related to specific cancer types. Limitations of this study in weight loss programmes.29 The data reported here show that there are public mis- conceptions of cancer types associated with overweight and obesity. These are of particular interest as in the UK breast cancer is one of the most prevalent cancers,30 yet there are poor levels of public awareness of its link to body weight. In addition, there has also been an increase in cancers of the womb that has been linked to increases in population obesity rates.31 The proportion of kidney cancer cases are also increasing and are projected to continue.30 It is therefore vital that population measures to halt and ultimately reduce rates for overweight and obese are implemented in the UK. This study reiterates similar data from earlier research13,27 exploring healthcare practitioner advice about body weight, therefore building the evidence base further in this area. The data has shown that whilst most of the population see a health practitioner, a small proportion are given any advice about their weight. As there is a real need to prevent people from becoming overweight or obese, attendance at health- care settings provide significant opportunities to advise peo- ple about their weight.13,23,25,26 However, these are currently being missed.27 There is a need for healthcare practitioners to be sufficiently equipped and trained to provide weight loss advice.15,16,32 Limitations include the sampling method which was an online survey where a panel was used to recruit participants and therefore a self-selected group. As with any cross-sectional survey, data cannot be collected over a period time to analyse behaviour change. When comparing the study data to Health Survey for England (HSE) data, the levels of obesity, as calcu- lated by self-reported BMI, are lower in this study than those seen in the latest HSE (2015) data (20 versus 27%).28 This could be due to 9% of participants not providing their weight and that the data was self-reported. HSE use an objective method of measuring weight and height at the time of collect- ing survey data and is therefore a more validated approach. A priority for future research should be to explore what kind of advice healthcare practitioners are giving to patients about their weight, whether these are in line with official guidance and what the barriers are to giving advice. The data reported here show that there are public mis- conceptions of cancer types associated with overweight and obesity. Limitations of this study These are of particular interest as in the UK breast cancer is one of the most prevalent cancers,30 yet there are poor levels of public awareness of its link to body weight. In addition, there has also been an increase in cancers of the womb that has been linked to increases in population obesity rates.31 The proportion of kidney cancer cases are also increasing and are projected to continue.30 It is therefore vital that population measures to halt and ultimately reduce rates for overweight and obese are implemented in the UK. This study reiterates similar data from earlier research13,27 exploring healthcare practitioner advice about body weight, therefore building the evidence base further in this area. The data has shown that whilst most of the population see a health practitioner, a small proportion are given any advice about their weight. As there is a real need to prevent people from becoming overweight or obese, attendance at health- care settings provide significant opportunities to advise peo- ple about their weight.13,23,25,26 However, these are currently being missed.27 There is a need for healthcare practitioners to be sufficiently equipped and trained to provide weight loss advice.15,16,32 Downloaded from https://academic.oup.com/jpubhealth/advance-article-abstract/doi/10.1093/pubmed/fdx145/4582914 by University College London user on 11 December 2017 What is already known about this topic Public awareness of disease risk is considered important as it has an influence on behavioural intentions.22 A recent study reported that 17% of overweight and 42% of obese people had received advice to lose weight from a healthcare practitioner.13 A 2013 literature review and meta- analysis of survey data found physician advice had a P-v – 7 0 – 5 0 5 <0 – 6 0 4 0 9 0 – 3 0 7 0 2 0 – 8 0 between overweight/obesity and four cancer types Kidney Bowel Womb alue Yes (%) OR CI P-value Yes (%) OR CI P-value Yes (%) OR CI 46.6 – – – 60.3 – – – 21.2 – – .001 42.0 1.177 1.024–1.354 0.022 59.9 0.983 0.844–1.146 0.828 21.8 0.995 0.832–1.18 53.1 – – – 62.6 – – – 25.5 – – 642 39.6 1.722 1.458–2.035 <0.001 58.1 1.077 0.894–1.297 0.437 20.7 1.384 1.123–1.70 329 38.8 1.759 1.476–2.096 <0.001 59.3 0.962 0.790–1.173 0.704 17.5 1.757 1.400–2.20 49.7 – – – 68.0 – – – 24.6 – – 340 46.5 1.259 1.035–1.531 0.021 61.5 1.227 0.992–1.517 0.059 19.9 1.291 1.012–1.64 .006 47.0 1.109 0.880–1.398 0.380 62.1 1.178 0.915–1.515 0.203 17.6 1.469 1.088–1.98 .001 37.4 1.634 1.348–1.981 <0.001 51.5 1.836 1.494–2.257 <0.001 22.8 1.044 0.826–1.31 47.1 – – – 48.2 – – – 12.9 – – .028 48.6 0.882 0.563–1.381 0.582 64.4 0.510 0.327–0.794 0.003 23.4 0.448 0.232–0.86 .026 47.7 0.849 0.538–1.341 0.484 62.3 0.563 0.359–0.882 0.012 21.5 0.461 0.237–0.89 477 36.9 1.263 0.792–2.014 0.326 56.2 0.694 0.439–1.097 0.118 19.9 0.510 0.260–1.00 40.0 – – – 55.9 – – – 19.3 – – 199 44.1 0.966 0.671–1.390 0.852 59.6 0.843 0.590–1.205 0.349 21.5 1.063 0.677–1.66 bmed/fdx145/4582914 66 0.671–1.39 2914 AWARENESS OF OBESITY AS A RISK FACTOR FOR CANCER IN THE UK AND HEALTHCARE PROFESSIONAL ADVICE 7 Table 4 Ordinal logistic regression results for receiving healthcare practitioner advice regarding weight No % Yes, lose weight % Yes, maintain weight % OR CI (95%) P value Overall (n = 2953) 82.8 13.2 4.1 – – – Gender (n = 2953) Male 80.8 14.6 4.6 0.735 0.591–0.914 0.006 Female 84.6 11.8 3.5 – – – Age (n = 2593) 18–39 89.2 7.8 3.1 1.904 1.416–2.558 0.939 40–59 79.5 16.5 3.9 1.139 0.886–1.464 0.381 60+ 78.5 16.1 5.4 – – – SES (n = 2593) AB 81.8 13.4 4.7 0.645 0.477–0.873 0.005 C1 82.5 12.3 5.3 0.576 0.432–0.768 <0.001 C2 80.1 15.8 4.1 0.63 0.452–0.877 0.006 DE 84.8 12.7 2.5 – – – BMI (n = 2646) Normal weight 92 2.3 5.7 5.844 4.435–7.701 <0.001 Overweight 83.4 11.7 4.9 3.158 2.444–4.082 <0.001 Obese 61.2 38.3 0.5 – – – Cancer diagnosis (n = 2821) Yes 77.4 13.1 9.5 0.784 0.497–1.236 0.295 No 82.9 13.3 4 – – – Values highlighted in bold are P < 0.05. What is already known about this topic Table 4 Ordinal logistic regression results for receiving healthcare practitioner advice regarding weight Values highlighted in bold are P < 0.05. increasing health inequalities this has not been demonstrated in weight loss programmes.29 Supplementary data Supplementary data are available at the Journal of Public Health online. 12 Robb K, Stubbings S, Ramirez A et al. Public awareness of cancer in Britain: a population-based survey of adults. Br J Cancer 2009;101: S18–23. 13 Jackson SE, Wardle J, Johnson F et al. The impact of a health pro- fessional recommendation on weight loss attempts in overweight and obese British adults: a cross-sectional analysis. BMJ Open 2013;3 (11):e003693. Contributors LH designed the study, analysed the data, interpreted the results and contributed to the article preparation. AS contributed to the study design and article preparation. JB contributed to analysing the data, results interpretation and contributed to the article preparation. AF contributed to analysing the data. GR, LB and JV contributed to the study design and article preparation. 14 McClinchy J, Dickinson A, Barron D et al. Practitioner and patient experiences of giving and receiving healthy eating advice. Br J Community Nurs 2013;18(10):498–504. 15 Puhringer PG, Olsen A, Climstein M et al. Current nutrition promo- tion, beliefs and barriers among cancer nurses in Australia and New Zealand. PeerJ 2015;3:e1396. 16 Williams K, Beeken RJ, Fisher A et al. Health professionals’ provi- sion of lifestyle advice in the oncology context in the United Kingdom. Eur J Cancer Care (Engl) 2015;24(4):522–30. Summary Only a quarter of adults in the UK are aware of cancer as a health condition associated with being overweight or obese. Differences in awareness exist between socio-economic groups and weight status, as those from more affluent groups have higher levels of awareness and generally lower BMI than those JOURNAL OF PUBLIC HEALTH 8 from the least affluent groups. Opportunities exist for health- care professionals to advise about weight loss, but these appear to be under-utilized—in this study only 38.3% of respondents who were obese were advised to lose weight. 9 World Cancer Research Fund. YouGov survey for World Cancer Day 2015. World Cancer Research Fund, 2015. 10 Buykx P, Li J, Gavens L et al. Public awareness of the link between alcohol and cancer in England in 2015: a population-based survey. BMC Public Health 2016;16(1):1194. 11 Marlow LAV, Robb KA, Simon AE et al. Awareness of cancer risk factors among ethnic minority groups in England. Public Health 2012;126(8):702–9. Funding This research was supported by funding from Cancer Research UK. 17 Mogre V, Wanaba P, Apala P et al. Self-reported receipt of health- care professional’s weight management counselling is associated with self-reported weight management behaviours of type 2 diabetes mellitus patients. SpringerPlus 2016;5:379. Downloaded from https://academic.oup.com/jpubhealth/advance-article-abstract/doi/10.1093/pubmed/fdx145/4582914 by University College London user on 11 December 2017 None. None. Conflicts of Interest 18 Buykx P LJ, Gavens L, Lovatt M et al. An Investigation of Public Knowledge of the Link Between Alcohol and Cancer. UK: University of Sheffield and Cancer Research, 2015. 27 Booth AO, Nowson CA. Patient recall of receiving lifestyle advice for overweight and hypertension from their General Practitioner. BMC Fam Pract 2010;11:8. 28 Health and Social Care Information Centre. Statistics on Obesity, Physical Activity and Diet, 2015. Downloaded from https://academic.oup.com/jpubhealth/advance-article-abstract/doi/10.1093/pubmed/fdx145/4582914 by University College London user on 11 December 2017 29 Bambra CL, Hillier FC, Cairns JM et al. How Effective are Interventions at Reducing Socioeconomic Inequalities in Obesity Among Children and Adults? Two Systematic Reviews. Southampton (UK): NIHR Journals Library, 2015. References 19 World Health Organization. BMI Classification World Health Organization, 2011. 1 World Health Organization. Global health risks: mortality and burden of disease attributable to selected major risks. World Health Organization, 2009. 20 Alcohol (Minimum Unit) Pricing Act 2012. http://www.legislation. gov.uk/asp/2012/4/pdfs/asp_20120004_en.pdf. 21 Ryan AM, Cushen S, Schellekens H et al. Poor awareness of risk fac- tors for cancer in Irish adults: results of a large survey and review of the literature. Oncologist 2015;20(4):372–8. 2 Ng M, Fleming T, Robinson M et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014;384(9945):766–81. 22 Anderson AS, Caswell S, Macleod M et al. Awareness of lifestyle and colorectal cancer risk: findings from the BeWEL Study. Biomed Res Int 2015;2015:871613. 3 Fuller E, Mindell J, Prior G et al. Health Survey for England 2015: Health, Social Care and Lifestyles, 2016. 23 Rose SA, Poynter PS, Anderson JW et al. Physician weight loss advice and patient weight loss behavior change: a literature review and meta-analysis of survey data. Int J Obes (Lond) 2013;37(1): 118–28. 4 Scottish Government. The Scottish Health Survey 2015, 2016. 5 Lauby-Secretan B, Scoccianti C, Loomis D et al. Body fatness and cancer-viewpoint of the IARC Working Group. N Engl J Med 2016; 375(8):794–8. 24 Epstein L, Ogden J. A qualitative study of GPs’ views of treating obesity. Br J Gen Pract 2005;55(519):750–4. 6 Parkin DM, Boyd L. 8. Cancers attributable to overweight and obes- ity in the UK in 2010. Br J Cancer 2011;105(Suppl 2):S34–7. 25 Aveyard P, Lewis A, Tearne S et al. Screening and brief intervention for obesity in primary care: a parallel, two-arm, randomised trial. Lancet 2016;388(10059):2492–2500. 7 Cancer Research UK, UK Health Forum. Tipping the scales: Why preventing obesity makes economic sense. Cancer Research UK & UK Health Forum, 2016. 26 Johns DJ, Hartmann-Boyce J, Jebb SA et al. Weight change among people randomized to minimal intervention control groups in weight loss trials. Obesity (Silver Spring) 2016;24(4):772–80. 8 Cancer Research UK. Cancer Awareness Measure (CAM) Key Findings Report: 2014 & Trends Analysis, 2016. Downloaded from https://academic.oup.com/jpubhealth/advance-article-abstract/doi/10.1093/pubmed/fdx145/4582914 by University College London user on 11 December 2017 AWARENESS OF OBESITY AS A RISK FACTOR FOR CANCER IN THE UK AND HEALTHCARE PROFESSIONAL ADVICE AWARENESS OF OBESITY AS A RISK FACTOR FOR CANCER IN THE UK AND HEALTHCARE PROFESSIONAL ADVICE 9 30 Smittenaar CR, Petersen KA, Stewart K et al. Cancer incidence and mor- tality projections in the UK until 2035. Br J Cancer 2016;115(9):1147–55. 31 Kitson SJ, Evans DG, Crosbie EJ. Identifying high-risk women for endometrial cancer prevention strategies: proposal of an endometrial cancer risk prediction model. Cancer Prev Res (Phila) 2017;10(1):1–13. 32 Klumbiene J, Petkeviciene J, Vaisvalavicius V et al. Advising over- weight persons about diet and physical activity in primary health care: Lithuanian health behaviour monitoring study. BMC Public Health 2006;6:30.
https://openalex.org/W4226106426
https://figshare.com/articles/journal_contribution/Thermo-mechanical_characteristics_and_reliability_of_die-attach_through_self-propagating_exothermic_reaction_bonding/16698022/1/files/30918712.pdf
English
null
Thermo-Mechanical Characteristics and Reliability of Die-Attach Through Self-Propagating Exothermic Reaction Bonding
IEEE transactions on components, packaging, and manufacturing technology
2,021
cc-by
8,993
All Rights Reserved All Rights Reserved PLEASE CITE THE PUBLISHED VERSION https://doi.org/10.1109/TCPMT.2021.3108017 PUBLISHER AM (Accepted Manuscript) PUBLISHER STATEMENT Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This item was submitted to Loughborough's Research Repository by the author. Items in Figshare are protected by copyright, with all rights reserved, unless otherwise indicated. Thermo-mechanical Characteristics and Reliability of Die-attach through Self-propagating Exothermic Reaction Bonding Yi Zhong, Stuart Robertson, Allan Liu, Zhaoxia Zhou and Changqing Liu, Senior Member, IEEE g, Stuart Robertson, Allan Liu, Zhaoxia Zhou and Changqing Liu, Senior Member, IEEE Shuibao Liang, Yi Zhong, Stuart Robertson, Allan Liu, Zhaoxia Zhou and Changqing Liu, Senior Shuibao Liang, Yi Zhong, Stuart Robertson, Allan Liu, Zhaoxia Zhou and Changqing L was significantly lower than the conventional solder reflow temperature ( > 200 °C). Abstract- Self-propagating exothermic reactions (SPER) provide intense localized heat sufficient for bonding metals or alloys with minimal heat excursion to the components, which shows great potential for the die attach in power electronics packaging. However, the reliability of such formed joints is yet to be fully understood owing to a wide range of defects involved in the instantaneous propagating reaction and heating/cooling. In this work, the finite element analysis is performed to understand the thermal transfer and mechanical responses of materials to the SPER bonding for the die attach of Si device onto direct bonded copper (DBC) substrate with Sn-3.0Ag-0.5Cu solder. The simulation has been validated using the temperature distribution in SPER bonding, which shows a good agreement with the actual measured results. Moreover, a systematic investigation on the mechanical responses due to thermal mismatch reveals their effects on the thermal stress of interfaces and bonding reliability.1 Many studies [4, 6] found the void formation at the bonded interface in the joints formed by SPER of nanofoils, these voids greatly undermine the performance and reliability of the interconnects. Voids could arise from the volume shrinkage due to the phase changes, which is related to the temperature changes of materials. Thus, the thermal transfer behaviour of materials is of vital importance to the optimization of SPER bonding process. Some studies [7, 8] simulated the temperature distribution as a result of thermal transfer through different materials during SPER bonding. However, their simulations consider neither the latent heat, nor temperature- dependent natures of the materials. Although there are lots of studies on the formation of voids in the solder joints formed by the conventional reflow process or transient liquid phase bonding process [9], the void formation in SPER bonding is yet to be understood. Index Terms—thermo-mechanical response, phase-change behaviour, residual stress, void, reliability, numerical simulation. Moreover, the difference in coefficients of thermal expansion (CTE) of the materials in SPER bonding induces the thermal stress and stress concentration. This work was supported by two EPSRC research grants (UK): (i) Underpinning Power Electronics 2017 – Heterogeneous Integration (HI) project (Grant No. EP/R004501/1), and (ii) Quasi-ambient bonding to enable cost-effective high temperature Pb-free solder interconnects (QAB) project (Grant No. EP/R032203/1). S. Liang, Y. Zhong, A. Liu and C. Liu are with the Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, U.K. (e-mail: c.liu@lboro.ac.uk). REPOSITORY RECORD Liang, Shuibao, Yi Zhong, Stuart Robertson, Allan Liu, Zhaoxia Zhou, and Changqing Liu. 2021. “Thermo- mechanical Characteristics and Reliability of Die-attach Through Self-propagating Exothermic Reaction Bonding”. Loughborough University. https://hdl.handle.net/2134/16698022.v1. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology le has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology IEEE y g g ( @ ) S. Robertson and Z. Zhou are with the Loughborough Materials Characterization Centre, Department of Materials, Loughborough University, Loughborough LE11 3TU, U.K. Thermo-mechanical Characteristics and Reliability of Die-attach through Self-propagating Exothermic Reaction Bonding The stress concentration can be potentially released as voids and cracks develop at the bonding interfaces. Owing to the extremely narrow melting region and heat-affected zone, it is almost impossible to physically quantify the stress/strain distributions during and after the SPER bonding process, let alone any further understanding of their influence on the reliability of the SPER bonded joints. Therefore, numerical approach through modelling presents a significant advantage in prediction of the stress/strain distribution. Kanetsuki et al. [10] proposed a stress balance model to explain the void and crack generation mechanisms during SPER bonding, but no validation was provided due to the unknown stress distribution. Our recent model [11] has included the thermo-mechanical behavior of the Sn/Cu interconnects during SPER bonding, but the fluid flow and viscoplastic behaviour of solder and their effects on the joint reliability were not considered. 2156-3950 (c) 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. Authorized licensed use limited to: LOUGHBOROUGH UNIVERSITY. Downloaded on September 29,2021 at 07:57:34 UTC from IEEE Xplore. Restrictions apply. I. INTRODUCTION Self-propagating exothermic reaction (SPER) of metallic multilayered foils can be used for bonding temperature- sensitive electronics components at low ambient temperatures, thanks to the highly concentrated local heat energy (~1300 J/g) and the self-propagating rate (0.01-30 m/s) [1-3]. The recent study [4] showed the potential of the Ni/Al nanofoil acting as a moving heat source to melt solder and form interconnection at low ambient temperatures, hence the minimal thermal impact on the adjacent components during bonding. For wide- bandgap (WBG), where die-attach in power devices is anticipated to operate at high power and temperature (likely exceeding 300 °C). However, bonding process for die-attach at a low ambient temperature is desirable in order to minimize deterioration of device caused by thermal excursion, thus achieve the enhanced performance and reliability. Wang et al. [5] attempted and successfully attached Si die onto Cu using the SPER process at 25 °C, where the ambient temperature In this study, the Si power device attached with Sn-3.0Ag- 0.5Cu (SAC) solder alloy onto direct bonded copper (DBC) substrate by SPER of Ni/Al nanofoil, is systematically investigated by considering heat transfer, fluid flow, and temperature-dependent elastic-plastic/plastic deformations of materials in SPER process. While the predicted temperature distribution during SPER bonding is verified by experimental work, we have also examined the mechanical behaviour of the bonded structures induced by thermal mismatch and its influence on the joint reliability. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology ournal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology IEEE II. METHODOLOGY s Q [ ], dn=x+0.5lf and lf is the length of the nanofoil, the propagating velocity v of the reaction is set as v=5.03 m/s, which is obtained from the estimation of the experimental results. The rectangular function term is defined as: The test vehicle of die-attach provided by Dynex Semiconductor Ltd and its configuration are shown in Fig. 1(a), where a Si die is attached to the DBC by SPER bonding with three interlayers (SAC/nanofoil/SAC) of a total thickness of 90 μm. I. INTRODUCTION The Ni/Al nanofoil (40 μm thick) was ignited with an electrical spark, and the SPER bonding was conducted under a pressure of 0.5MPa applied on the top of stacked structure at the ambient temperature. In the simulation, the thin metallization layers on both Si die and DBC substrate are not included; as such a two-dimensional model for FE analysis is shown in Fig. 1(b). Moreover, a K-type thermocouple was fixed at the Cu substrate 0.1 mm away from the solder/DBC interface during SPER bonding and the recorded temperature has been compared with the simulation results. The cross- sections of the bonded samples were prepared, and subsequently examined under a JEOL 7100F field emission gun scanning electron microscope (FEGSEM) to observe the microstructure and interfacial morphologies. 2 0 ( ) , 2 1 n n r n r d vt l rect d vt d vt l          (3) (3) where the reaction zone length 100μm. rl  During the SPER of Ni/Al nanofoil, the nanofoil can convert into Ni-Al metallics [8]. A variable p is used to present the state of the nanofoil, and p is determined by:     1 2 1 sin ( ) 2 . 2 0 n r n r n r d vt l p vt d l else d vt l             (4) (4) Fig. 1 Schematic diagram of a Si power module (a) and two-dimensional geometric model (b) used in numerical simulation. Then, the material properties of the nanofoil can be obtained by (1 ) , f rf uf M M M p p    where Mrf and Muf are the properties of reacted and unreacted nanofoils, respectively. In addition, the effect of phase change of SAC solder, i.e., melting and solidification, on thermal transfer can be described by the apparent heat capacity method. I. INTRODUCTION The heat capacity of the solder is written as: , , (1 ) , ps p s p l s l C C C L d dT            (5) (5) where ,p s C and , p l C are respectively the capacities of the solid solder and liquid solder,  is the percent volume occupied by liquid phase, the latent heat 61.03KJ/Kg s l L  [13]. Fig. 1 Schematic diagram of a Si power module (a) and two-dimensional geometric model (b) used in numerical simulation. The flow velocity (u) of the SAC solder during the SPER bonding is governed by the Navier-Stokes equation: A. Heat Transfer and Fluid Flow Once initiated, SPER of the Ni/Al nanofoil releases massive local heat, the temperature T in the interconnect obeys:     2 0 1 ( ) , s P T T t                  u u u u g F (6) (6) ( ) , p T C T k T q t              u (1) (1) where P, μ, α and g is the fluid pressure, melt viscosity, thermal expansivity and gravity acceleration, respectively. The last term Fs in Eq. (6) is used to damp the acceleration resulting from the momentum equation and thereby imitates solid behaviour [14], and it can be written as 2 3 (1 ) ( ), s n m      F u where m=105 and n=0.001. where p C , and k are respectively the specific heat capacity, density and thermal conductivity; the last term is the volumetric heat source. The ambient temperature is set to Tenv = 25 °C and the thermal boundary 0 ( ) env q h T T    is applied to the surfaces around the bonded structure, where h is the convective heat transfer coefficient. The value of h for the bottom surface of DBC is set to be 600 W/(m2·K), h=100 W/(m2·K) for the top surface of Si die, and h=25 W/(m2·K) for the rest surrounding boundaries, where the surface temperature and emissivity are assigned to be 25 °C and 0.5. 2156-3950 (c) 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. Authorized licensed use limited to: LOUGHBOROUGH UNIVERSITY. Downloaded on September 29,2021 at 07:57:34 UTC from IEEE Xplore. Restrictions apply. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final public Transactions on Components, Packaging and Manufacturing Technology C. Material properties C. Material properties C. Material properties Material properties are temperature-dependent during SPER bonding in the simulation. At the solid-liquid interface, the properties of SAC solder are the linear combination of the properties at its solid or liquid states. The properties of the other materials are provided in Table II [17-21]. The dynamic viscosity of the liquid SAC solder is given by μ=μ0exp(Eμ/RT), and μ0=4.58×10-4 Pa·s, Eμ=6.89×103 J/mol [22]. TABLE II MATERIALS’ PROPERTIES Properties Density (Kg m-3) Thermal conductivity (W m-1 K-1) Specific heat (J Kg-1 K-1) CTE (ppm K-1) Young’s modulus (GPa) Poisson’s ratio Yield strength (MPa) Cu 9062.2-0.39T 420-0.068T 342.764+0.13T 11.05+2.7×10-8T- 3.16×10-11T2 140.8-0.047T 0.33 222.4-0.35(T-273) AlN 3260 319a 1118.4+8. 17×10- 2T -3.65×107T-2 2.8a 310.2-0.0247Te- 533/T 0.23 – Nanofoil 5500 152 830 16.9 91.867-0.048(T- 273) 0.31 151.09-0.07(T-273) Reacted nanofoil 5900 60 640 13.2 193-0.04(T- 273) 0.31 543.16-0.126(T-273) Solder (S) 7202.783+2.72T -0.013T2 58a 229a 21.7a – – – Solder (L) 7452.9-0.662T 24b 249b 29.98+2.01×10-3T – – – Si 2330 148 712 2.6 130 0.278 – aThese values corresponding to the properties at the room temperature, temperature-dependent properties are assigned in the simulation. bThese values corresponding to the properties at the melting point, temperature-dependent properties are assigned in the simulation. aThese values corresponding to the properties at the room temperature, temperature-dependent properties are assigned in the simulati bThese values corresponding to the properties at the melting point, temperature-dependent properties are assigned in the simulation. 2156-3950 (c) 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. Authorized licensed use limited to: LOUGHBOROUGH UNIVERSITY. Downloaded on September 29,2021 at 07:57:34 UTC from IEEE Xplore. Restrictions apply. III. RESULTS AND DISCUSSION bonding are shown in Fig. 3. At t=0.005 ms, the SAC solder remains in its solid state as the temperature is lower than its melting point. At t=0.025 ms, the solder begins to melt and is likely to react with DBC substrate. At t=0.125 ms, the SAC melting region expands due to further temperature increase. From t=0.225 ms to t=0.25 ms, while the SAC solder in contact with the Si die still maintains molten state, the SAC solder in contact with the DBC may start to solidify as it has cooled to melting point or below. The time for SAC solder to solidify mainly depends on the thermal diffusivity of the adjacent materials. The higher thermal diffusivity of Cu (~1.11×10-4 m2/s) in comparison with Si (~8.8×10-5 m2/s) can accelerate the heat dissipation from the molten solder, resulting in a sooner solidification of the SAC solder near the DBC substrate. bonding are shown in Fig. 3. At t=0.005 ms, the SAC solder remains in its solid state as the temperature is lower than its melting point. At t=0.025 ms, the solder begins to melt and is likely to react with DBC substrate. At t=0.125 ms, the SAC melting region expands due to further temperature increase. From t=0.225 ms to t=0.25 ms, while the SAC solder in contact with the Si die still maintains molten state, the SAC solder in contact with the DBC may start to solidify as it has cooled to melting point or below. The time for SAC solder to solidify mainly depends on the thermal diffusivity of the adjacent materials. The higher thermal diffusivity of Cu (~1.11×10-4 m2/s) in comparison with Si (~8.8×10-5 m2/s) can accelerate the heat dissipation from the molten solder, resulting in a sooner solidification of the SAC solder near the DBC substrate. A. Temperature and Fluid Flow Velocity Distribution W is the strain energy density, and  T is the traction vector. g , p TABLE I PARAMETERS OF THE ANAND MODEL FOR SOLDER TABLE I PARAMETERS OF THE ANAND MODEL FOR SOLDER Properties Symbol Unit Value Deformation resistance sensitivity η – 0.07 Activation energy Q/R K 9400 Stress sensitivity m0 – 0.303 Stress multiplier ξ – 1.5 Pre-exponential factor A 1/s 4.1×106 Deformation resistance saturation coefficient s0 MPa 12.41 Deformation resistance initial value s MPa 13.79 Hardening sensitivity a – 1.3 Hardening coefficient h0 MPa 1378.95 B. Thermal Stress and J-integral Assuming zero displacement along y direction of the bottom surface of DBC and the left end of bottom surface is fixed, the CTE mismatch induced thermal stress ij  is governed by: =0. ij i  x  (7) The heat released from SPER of nanofoil layer is regarded as a moving heat source and it is expressed as: (7) (2) 1( , ) ( ), s n q x t Q rect vt d    1( , ) ( ), s n q x t Q rect vt d    This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final public Transactions on Components, Packaging and Manufacturing Technology ournal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology IEEE The plastic deformation of Cu is described by an isotropic hardening model , t d d E   where tE is the tangent modulus. The mechanical behaviour of the Ni/Al nanofoil is described by the perfectly plastic model, while the mechanical behaviour of SAC solder can be defined by the Anand model, and the parameters are listed in Table I [15]. The relief of stress and strain due to the melting of solder, Al and NiAl in nanofoil [8] should also be considered, thus an activation factor (~10-5) is introduced to scale the strain tensor sufficiently at melting region, in order to simulate their mechanical responses. The plastic deformation of Cu is described by an isotropic hardening model , t d d E   where tE is the tangent modulus. To evaluate the probability of crack propagation near the interfaces, a path independent line integral (i.e., J-integral) along a counterclockwise contour (Γ) surrounding a crack tip is calculated. B. Thermal Stress and J-integral The J-integral is defined as [16]: The mechanical behaviour of the Ni/Al nanofoil is described by the perfectly plastic model, while the mechanical behaviour of SAC solder can be defined by the Anand model, and the parameters are listed in Table I [15]. The relief of stress and strain due to the melting of solder, Al and NiAl in nanofoil [8] should also be considered, thus an activation factor (~10-5) is introduced to scale the strain tensor sufficiently at melting region, in order to simulate their mechanical responses. , di x i u J Wn T ds x              (8) (8) W is the strain energy density, and  T is the traction vector. W is the strain energy density, and  T is the traction vector. B. Mechanical Behaviour due to the CTE mismatch The mechanical response of materials to the thermal strain causes the increase of thermal stress in the power module during the SPER bonding process. As can be seen in Fig. 6, more heat accumulates in the Si power device, and the evolution of stress highly depends on the temperature distribution. The stress near the reaction front is relatively high because of the greater CTE mismatch induced strain due to the high temperature gradient, and the maximum von Mises stress can reach 510 MPa. As time proceeds from 0.2 to 0.4 ms (Fig. 6a & b), the maximum von Mises stresses in the solder region close to the Si/SAC interface reduced from 325.12 to 10.736 MPa, as compared to the values near the SAC/DBC interface from 371.14 to 215.64 MPa, respectively. The results also showed the mean values of von Mises stresses in the solder near the Si/SAC interface decresed from 3.12 to 0.18 MPa, whilst the mean values of von Mises stresses near the SAC/DBC interface increased from 20.48 and 34.568 MPa. The decrease in maxium stress of the solder is caused by the melting of the SAC solder, which leads to the stress relief in the regions. The greater stress in the solder close to the SAC/DBC interface implies the greater tendency of the mechanical failure to occur at the SAC/DBC interface. Fig. 3 Temperature distribution along the line X=−6.7×10-3 m during bonding Fig. 3 Temperature distribution along the line X=−6.7×10-3 m during b di Fig. 4 Comparison of experimentally measured and numerically computed temperature at the Cu substrate 0.1 mm from the solder/DBC interface during SPER bonding. Fig. 6 Von Mises stress in the power module during the SPER bonding at times: (a) t=0.2 ms; (b) t=0.4 ms. Fig. 4 Comparison of experimentally measured and numerically computed temperature at the Cu substrate 0.1 mm from the solder/DBC interface during SPER bonding. Fig. 6 Von Mises stress in the power module during the SPER bonding at times: (a) t=0.2 ms; (b) t=0.4 ms. Except for the temperature, the flow velocity of the molten solder can be critical to the melting of solder. The maximum velocity ~1.6 μm/s is likely to occur along the interfaces, particularly when reaching the stage of solidifying between the nanofoil and DBC substrate as seen at the bottom-left corners in Fig. 5 (a) and (b). A. Temperature and Fluid Flow Velocity Distribution p y When the nanofoil’s combustion is ignited with an electrical spark, intense heat is released from the propagating SPER and spontaneously transfers to the adjacent layers, resulting in the temperature increases. As shown in Fig. 2, only the temperature distribution near the front of the self-propagating reaction is exhibited due to the large aspect ratio of the considered interconnect structure (see Fig. 1). While the SPER proceeds, the highest temperature at the nanofoil can reach 1303 °C and 1307 °C at t=0.2 and t=0.4 ms, respectively. The green isotherm lines in Fig. 2 represent the contour of melting temperature of SAC alloy (Tm ~217 °C) in the adjacent of the nanofoil, marking the phase changes as the SPER propagates. Note that the temperature in the solder’s region is an important factor in determining its wetting behaviour and chemical reaction with the substrate, the temperature profiles along the line X=−6.7×10-3 m at different times during SPER To verify the simulation results of temperature distribution, the experiment with the same Si power module structure is also carried out to monitor the temperature at Cu substrate This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology e has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology ournal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology IEEE degree of thermal excursion at the DBC/SAC interface as indicated in Fig. 2(a). near the DBC/solder interface, and the temperature change during the SPER bonding can be seen in Fig. 4. By comparing the simulation results with the experimental data, the simulation results are in an excellent agreement with the experimental results. degree of thermal excursion at the DBC/SAC interface as indicated in Fig. 2(a). Fig. 2156-3950 (c) 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. Authorized licensed use limited to: LOUGHBOROUGH UNIVERSITY. Downloaded on September 29,2021 at 07:57:34 UTC from IEEE Xplore. Restrictions apply. A. Temperature and Fluid Flow Velocity Distribution 5 Magnitudes of flow velocity in the SAC solder during the SPER bonding at times: (a) t=0.1 ms; (b) t=0.2 ms. Fig. 5 Magnitudes of flow velocity in the SAC solder during the SPER bonding at times: (a) t=0.1 ms; (b) t=0.2 ms. Fig. 2 Temperature distribution in the power module during the SPER bonding at times: (a) t=0.2 ms; (b) t=0.4 ms (the green isotherm lines corresponding to the melting point of the SAC solder). Fig. 5 Magnitudes of flow velocity in the SAC solder during the SPER bonding at times: (a) t=0.1 ms; (b) t=0.2 ms. Fig. 2 Temperature distribution in the power module during the SPER bonding at times: (a) t=0.2 ms; (b) t=0.4 ms (the green isotherm lines corresponding to the melting point of the SAC solder). This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final public Transactions on Components, Packaging and Manufacturing Technology B. Mechanical Behaviour due to the CTE mismatch The maximum residual von Mises stresses in the solder region near the Si/SAC interface and SAC/DBC interface are 488.14 and 455.97 MPa respectively. These values are higher than the maximum residual stress (~245 MPa [23]) in the Sn-based solder interconnects formed by a conventional reflow process due to the higher temperature and constraint deformation in the narrow heat-affected zone of the SPER bonding. The residual stress is higher than the yield strength of the solder alloys (~ 30 MPa [24]), which can cause plastic deformation of the solder interconnects and promote the crack formation. Therefore, it would be more beneficial if the residual stresses may be minimized to enhance the mechanical integrity of SPER solder bonding structures. Fig. 7 Von Mises stress along the line X=−6.7×10-3 m during bonding. Fig. 8 presents the Von Mises stress and temperature at Si/SAC, SAC/Nanofoil, Nanofoil/SAC and SAC/DBC interfaces. Except for the SAC/DBC interface, an obvious stress relief phase at the other interfaces is present with a time- length of 0.5 ms (corresponding to the time-length of the temperature higher than the melting point of the solder in Fig. 8 (b)). This also implies that the stress relief hold time of solder near DBC is shorter than that near Si. The stress at SAC/DBC interface first increases rapidly and then gradually decreases. However, the stress at the other three interfaces increases sharply, but relaxes immediately due to the solder melting, followed by steadily rises due to the cooling with the accompanying solidification of the liquid solder. Fig. 9 The distribution of x-component (a) and y-component (b) of stress in the power module after SPER bonding. Fig. 9 The distribution of x-component (a) and y-component (b) of stress in the power module after SPER bonding. Note that the longitudinal residual stress along interface is important because it is a driving force for crack propagation [25]. Fig. 10(a) shows the high tensile longitudinal stress in the solder regions along the line X=−6.7×10-3 m after SPER bonding, against the compressive stress in the Si and DBC layers, which is likely to promote the formation of interfacial voids/cracks. It should be mentioned that susceptibility to void formation depends not only on the magnitude of the residual stresses but also the strength of the bonding interfaces. B. Mechanical Behaviour due to the CTE mismatch It is also found that the velocities of the molten solder at the reaction fronts and the solidification boundaries are generally higher than other regions. However, the velocities are relatively small in magnitude and the Rayleigh number is below the critical value, as such they are unlikely to have any apparent effect on heat convection in the soldering process. It is worth of noticing that the velocities at the DBC/SAC interface are greater than that at the Si/SAC interface, which is likely attributed to the higher The Von Mises stress along the line X=−6.7×10-3 m during SPER bonding is presented in Fig. 7. It is found that the stress concentration at the Si/SAC and SAC/DBC interface is high. At t=0.005 ms, the stress in the solder regions is ~90 MPa. As time increases to 0.025 ms, the stress rapidly decreases since the molten of solder. From t=0.125 ms to t=0.25 ms, the stress in the solder matrix is almost zero, the interfacial stress near Si layer decreases, but the interfacial stress near the DBC layer gradually increases. After 6×105 ms, the temperature of the Si power device cools down to the room temperature, the solidification of the solder results in the increase of the stress, and the inelastic deformation of materials continues to occur with the stress increasing. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology e has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final public Transactions on Components, Packaging and Manufacturing Technology ournal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology IEEE IEEE Fig. 7 Von Mises stress along the line X=−6.7×10-3 m during bonding. stresses in the solder region near the Si/SAC and SAC/DBC interface are 331.98 and 331.74 MPa respectively. B. Mechanical Behaviour due to the CTE mismatch In the solder region, the residual stress near the Si/SAC interface is higher than that near SAC/DBC interface, which can be attributed to the higher Young’s modulus of Si compared to Cu (see Table II). From the through-thickness residual stress distribution shown in Fig. 10(b), it is found that the residual stresses are mostly compressive along the vertical direction, which can reduce the possibility of delamination at the interfaces. Fig. 8 Von Mises stress (a) and temperature (b) of the points A, B, C and D respectively at Si/SAC, SAC/Nanofoil, Nanofoil/SAC and SAC/DBC interfaces during SPER bonding. Fig. 8 Von Mises stress (a) and temperature (b) of the points A, B, C and D respectively at Si/SAC, SAC/Nanofoil, Nanofoil/SAC and SAC/DBC interfaces during SPER bonding. interfaces. Fig. 10 Longitudinal stress (a) and through-thickness residual stress (b) distributions along the line X=−6.7×10-3 m after SPER bonding. C. Residual Stress Analysis After the bonding, i.e., the bonded structure cools down to room temperature, the inelastic deformation cannot be recovered, then the residual stress exists in the interconnects. Fig. 9 presents the distribution of the residual stresses along x (longitudinal) and y (through-thickness) directions. It is observed that the maximum longitudinal and through- thickness stresses are both located in the layer of nanofoil as expected. The x-component of residual stresses in the Si and DBC layers are predominantly compressive, evolving into tensile stress in the nanofoil and solder. Interestingly, the longitudinal residual stress is much higher than the through- thickness residual stress in the solder layer (see Fig. 9 (a) and (b)). The estimated average values of the residual von Mises Fig. 10 Longitudinal stress (a) and through-thickness residual stress (b) distributions along the line X=−6.7×10-3 m after SPER bonding. 2156-3950 (c) 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. Authorized licensed use limited to: LOUGHBOROUGH UNIVERSITY. Downloaded on September 29,2021 at 07:57:34 UTC from IEEE Xplore. Restrictions apply. D. Interfacial Reliability and J-integral HS , 3 x y z        (9) HS HS HS HS , , . x y z               (10) (9) (10) y Fig. 12 (a) Optical cross-sectional micrograph of a die-attach bond line; the cross-sectional SEM images of (b) the bonded structure, (c) Si/solder interface and (d) solder/DBC interface. Fig. 11 Hydrostatic stress distribution (a) and hydrostatic stress gradient magnitude (b) along the line X=−6.7×10-3 m after SPER bonding. Fig. 11 Hydrostatic stress distribution (a) and hydrostatic stress gradient magnitude (b) along the line X=−6.7×10-3 m after SPER bonding. Fig. 11 (a) shows the hydrostatic stress distribution along the line X=−6.7×10-3 m at room temperature after SPER bonding. It can be observed that the hydrostatic stresses in the solder and nanofoil are tensile, and they are compressive in other regions of the bonded structure. This suggests that there exists a sharp gradient of hydrostatic stress along the through- thickness direction of the power module, as can be plotted in Fig. 11(b). There are large hydrostatic stress gradients at the Si/SAC and SAC/DBC interfaces, and the stress gradient at the DBC/SAC interface is much steeper than that at the Si/SAC interface. Since the atomic flux is proportional to the negative of hydrostatic stress [26], high hydrostatic stress gradient at interfaces will drive the directional movement of vacancies, which will accumulate at the interfaces to potentially form the voids. Therefore, the stress gradients at the Si/SAC and SAC/DBC interfaces after bonding can become important factors affecting the possibility of void formation. Fig. 11 Hydrostatic stress distribution (a) and hydrostatic stress gradient magnitude (b) along the line X=−6.7×10-3 m after SPER bonding. Fig. 11 Hydrostatic stress distribution (a) and hydrostatic stress gradient magnitude (b) along the line X=−6.7×10-3 m after SPER bonding. Fig. 12 (a) Optical cross-sectional micrograph of a die-attach bond line; the cross-sectional SEM images of (b) the bonded structure, (c) Si/solder interface and (d) solder/DBC interface. Although it is found that the formation of voids was mainly attributed to volume shrinkage as well as the trapped air [28]; and the voids were observed at the interface of bonded structures prepared by Ni/Al nanofoil SPER bonding [4], the further details accounting for the void formation still remains unclear. From our experimental results shown in Fig. D. Interfacial Reliability and J-integral 12, many voids have been observed, especially near the DBC/SAC interface (Fig. 12(d)). However, the voids near the Si/SAC interface are relatively scarce, which is likely attributed to the combination of the prolonged melting, better interfacial wetting due to metalized surface on the die, and the lower hydrostatic stress gradient induced post SPER bonding (Fig. 11). Our simulation and analysis provided the supportive fundamental understanding on the void formation and its effect on the reliability of SPER solder interconnects for die attach, and further clarified the reason of that fracture occurred at the DBC/SAC interface which was observed in our experiment. Fig. 12 (a) Optical cross-sectional micrograph of a die-attach bond line; the cross-sectional SEM images of (b) the bonded structure, (c) Si/solder interface and (d) solder/DBC interface. Fig. 13 Time-dependence of J-integrals corresponding to the two cases of a crack respectively at Si/SAC and SAC/DBC interfaces during bonding. Fig. 13 Time-dependence of J-integrals corresponding to the two cases of a crack respectively at Si/SAC and SAC/DBC interfaces during bonding. The high thermal stress has a significant effect on the mechanical reliability of the interconnects, the J-integral can be used to evaluate the probability of crack propagation. In our study, the variations are calculated in J-integral of the crack tips during bonding, at the Si/DBC and SAC/DBC interfaces. For both cases, the thermo-mechanical behaviour during 2156-3950 (c) 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. Authorized licensed use limited to: LOUGHBOROUGH UNIVERSITY. Downloaded on September 29,2021 at 07:57:34 UTC from IEEE Xplore. Restrictions apply. D. Interfacial Reliability and J-integral Note that the non-negligible role of hydrostatic stress and its gradient in driving the vacancies to directionally diffuse This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology e has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publica Transactions on Components, Packaging and Manufacturing Technology ournal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology IEEE toward the void [26], and the additional atomic flux due to the stress can be expressed as HS ( ) , sJ cD KT     where c is the normalized atomic density, D is the atom diffusivity, Ω is the atomic volume. Thus, the hydrostatic stress gradient is usually taken as an indicator of void location. The hydrostatic stress and its gradient are defined as [26, 27]: SPER bonding is simulated followed by the calculation of J- integral based on the stress and strain distribution around the crack tips, yielding the J-integral curves shown in Fig. 13. It can be seen that the J-integral of the SAC/DBC interface is greater than that of the Si/SAC interface at the early stage of bonding, but J-integral of the SAC/DBC interface evolves with time and become smaller. At the early stage of the bonding, cracks at the SAC/DBC interface are more likely to propagate during the period of solder’s melting and solidification, while there is a higher risk of cracking at the Si/SAC interface at a later stage given the drastic increase of the J-integral, which would degrade the thermal cycling reliability of the interconnects. IV. CONCLUSIONS The hydrostatic stress gradient at SAC/DBC interface is found to be steeper at the early stage of the bonding, implying the likeliness of directional movement of vacancies and accumulation to potentially form the voids, which is confirmed through experimental validation. [12] T. Fiedler, I. V. Belova, S. Broxtermann, G. E. Murch, “A thermal analysis on self-propagating high temperature synthesis in joining technology,” Comput. Mater. Sci., vol. 53, no. 1, pp. 251–257, Feb. 2012. [13] C. D. Zou, Y. L. Gao, B. Yang, X. Z. Xia, Q. J. Zhai, C. Andersson, J. Liu, “Nanoparticles of the Lead-free Solder Alloy Sn-3.0Ag-0.5Cu with Large Melting Temperature Depression,” J. Electron. Mater., vol. 38, no. 2, pp. 351–355, Oct. 2008. (5) The high thermal stress has a significant effect on the mechanical reliability of the interconnects. The J-integral that can be used to evaluate the probability of crack propagation indicates that the J-integral of the SAC/DBC interface is greater than that of the SAC/Si interface at the early stage of bonding, but it evolves with time and become smaller. Cracks are more likely to initiate and propagate at the SAC/DBC interface during the initial SPER bonding stage. However, a higher risk of cracking at the SAC/Si interface at the later stage. [14] W. Sanhye, C. Dubois, I. Laroche, P. Pelletier, “Numerical modeling of the cooling cycle and associated thermal stresses in a melt explosive charge,” AICHE J., vol. 62, no. 10, pp. 3797–3811, May 2016. [15] B. Hu et al., “Failure and Reliability Analysis of a SiC Power Module Based on Stress Comparison to a Si Device,” IEEE Trans. Device Mater. Reliab., vol. 17, no. 4, pp. 727–737, Dec. 2017. [16] J. R. Rice, “A Path Independent Integral and the Approximate Analysis of Strain Concentration by Notches and Cracks,” J. Appl. Mech., vol. 35, no. 2, pp. 379–386, Jun. 1968. [17] R. J. Bruls, H. T. Hintzen, G. de With, R. Metselaar, “The temperature dependence of the Young’s modulus of MgSiN2, AlN and Si3N4,” J. Eur. Ceram. Soc., vol. 21, no. 3, pp. 263–268, Mar. 2001. IV. CONCLUSIONS In this study, the Si power device attached with Sn-3.0Ag- 0.5Cu solder onto DBC substrate by SPER of Ni/Al nanofoil is systematically investigated by numerical simulation. The emphasis is placed on the distribution characteristics of IEEE temperature, flow velocity and thermal stress. The effects of residual stress and hydrostatic stress on void formation and interfacial reliability are discussed, and the simulated results are verified by experiment. The main conclusions are summarized as follows: temperature, flow velocity and thermal stress. The effects of residual stress and hydrostatic stress on void formation and interfacial reliability are discussed, and the simulated results are verified by experiment. The main conclusions are summarized as follows: REFERENCES [1] P. Swaminathan, M. D. Grapes, K. Woll, S. C. Barron, D. A. LaVan, T. P. Weihs, “Studying exothermic reactions in the Ni-Al system at rapid heating rates using a nanocalorimeter,” J. Appl. Phys., vol. 113, no. 14, p. 143509, Apr. 2013. [2] K. Wang, K. Ruan, W. Hu, S. Wu, H. Wang, “Room temperature bonding of GaN on diamond wafers by using Mo/Au nano-layer for high-power semiconductor devices,” Scr. Mater., vol. 174, pp. 87–90, Jan. 2020. (1) During SPER bonding, the temperature of nanofoil combustion could reach 1307 °C. Results of temperature distribution from the simulation are in an excellent agreement with the experimental results. The intensive localized heat has caused the melting of adjacent SAC solder alloy, and the melting time of the adjacent solder near Si/SAC interface is longer than that near SAC/DBC interface due to the less effective heat dissipation through the Si compared to DBC. (1) During SPER bonding, the temperature of nanofoil combustion could reach 1307 °C. Results of temperature distribution from the simulation are in an excellent agreement with the experimental results. The intensive localized heat has caused the melting of adjacent SAC solder alloy, and the melting time of the adjacent solder near Si/SAC interface is longer than that near SAC/DBC interface due to the less effective heat dissipation through the Si compared to DBC. [3] Y. C. Liu, S. K. Lin, H. Zhang, S. Nagao, C. Chen, K. Suganuma, “Reactive wafer bonding with nanoscale Ag/Cu multilayers,” Scr. Mater., vol. 184, pp. 1–5, Jul. 2020. [4] W. Zhu, X. Wang, C. Liu, Z. Zhou, F. Wu, “Formation and homogenisation of Sn Cu interconnects by self-propagated exothermic reactive bonding,” Mater. Des., vol. 174, p. 107781, Jul. 2019. [5] X. Wang, M. IV. CONCLUSIONS Li, W. Zhu, “Formation and homogenization of Si interconnects by non-equilibrium self-propagating exothermic reaction,” J. Alloys Compd., vol. 817, p. 153210, Mar. 2020. (2) As the SPER bonding progresses, more heat accumulates in the nanofoil’s region of the power module, and evolution of stress highly depends on the temperature distribution across the entire bonded structure. The melting of the solder causes stress relief, which last shorter time in the solder near SAC/DBC interface than that near Si/SAC interface. [6] S. Kanetsuki, S. Miyake, T. Namazu, “Effect of free-standing Al/Ni exothermic film on thermal resistance of reactively bonded solder joint,” Sens. Mater., vol. 31, no. 3, pp. 729–741, Mar. 2019. [7] J. Wang, E. Besnoin, A. Duckham, S. J. Spey, M. E. Reiss, O. M. Knio, T. P. Weihs, “Joining of stainless-steel specimens with nanostructured Al/Ni foils,” J. Appl. Phys., vol. 95, pp. 248–256, Jan. 2004. [8] I. E. Gunduz, K. Fadenberger, M. Kokonou, C. Rebholz, C. C. Doumanidis, “Investigations on the self-propagating reactions of nickel and aluminum multilayered foils,” Appl. Phys. Lett., vol. 93, no. 13, pp. 134101, Sep. 2008. (3) After the bonding, higher residual stresses are induced near the Si/SAC interface than SAC/Cu interface. The residual stresses change from compressive to tensile along the longitudinal x-axis at the regions of nanofoil and solder can act as a driving force for crack propagation. The residual stress at Si/SAC interface is higher than that at SAC/DBC interface, which can be attributed to the higher Young’s modulus of Si compared to Cu on DBC. [9] O. Mokhtari, “A review: Formation of voids in solder joint during the transient liquid phase bonding process-Causes and solutions,” Microelectron. Reliab., vol. 98, pp. 95–105, Jul. 2019. [10] S. Kanetsuki, S. Miyake, T. Namazu, “Effect of free-standing Al/Ni exothermic film on thermal resistance of reactively bonded solder joint,” Sensors and Materials, vol. 31, no. 3, pp. 729–741, Mar. 2019. [11] S. Liang, Y. Zhong, S. Robertson, A. Liu, Z. Zhou, C. Liu, “Investigation of Thermo-mechanical and Phase-change Behavior in the Sn/Cu Interconnects during Self-Propagating Exothermic Reaction Bonding,” in Proc. IEEE 70th Electron. Compon. Technol. Conf., May 2020, pp. 269–275. (4) High hydrostatic stresses along the SAC/DBC and SAC/Si interface are inevitable during and after SPER bonding. 2156-3950 (c) 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. Authorized licensed use limited to: LOUGHBOROUGH UNIVERSITY. Downloaded on September 29,2021 at 07:57:34 UTC from IEEE Xplore. Restrictions apply. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final public Transactions on Components, Packaging and Manufacturing Technology ournal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology IV. CONCLUSIONS It is anticipated that the in-depth and comprehensive understanding of the thermo-mechanical behavior of the Si power module with SAC interconnects formed by SPER bonding in this study enables a step forward for the tangible application of SPER bonding in power electronics industry, and the results will assist the process optimization in connection with the residual stress and interfacial reliability. The thermal stress induced crack formation and propagation could be investigated by performing simulation using more powerful numerical model in the follow-up studies. [18] A. M. Hodge, D. C. Dunand, “Measurement and modeling of creep in open-cell NiAl foams,” Metall. Mater. Trans. A, vol. 34, no. 10, pp. 2353–2363, Oct. 2003. [19] J. Wang, E. Besnoin, O. M. Knio, T. P. Weihs, “Effects of physical properties of components on reactive nanolayer joining,” J. Appl. Phys., vol. 97, no. 11, p. 114307, Jun. 2005. [20] H. Kröncke, S. Figge, D. Hommel, B. M. Epelbaum, “Determination of the Temperature Dependent Thermal Expansion Coefficients of Bulk This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology ournal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology IEEE AlN by HRXRD,” Acta Phys. Pol., vol. 114, no. 5, pp. 1193–1200, Nov. 2008. AlN by HRXRD,” Acta Phys. Pol., vol. 114, no. 5, pp. 1193–1200, Nov. 2008. technical specialist in ion and electron microscopy at the Loughborough materials characterization center (LMCC). [21] C. H. Cho, “Characterization of Young’s modulus of silicon versus temperature using a ‘beam deflection’ method with a four-point bending fixture,” Curr. Appl. Phys., vol. 9, no. 2, pp. 538–545, Mar. 2009. Allan Liu received his B.E. degree from Coventry University, Coventry, U.K., in 2019. He is currently pursuing a Ph.D. degree with the Department of Mechanical Engineering, The University of Sheffield, Sheffield, U.K. [22] A. Yakymovych, H. Weber, I. Kaban, H. Ipser, “Dynamic viscosity of a liquid Sn-3.0Ag-0.5Cu alloy with Ni nanoparticles,” J. Mol. Liq., vol. 268, pp. 176–180, Oct. 2018. [23] C. S. Lau, M. Z. Abdullah, F. C. Ani, “Effect of Solder Joint Arrangements on BGA Lead-Free Reliability During Cooling Stage of Reflow Soldering Process,” IEEE Trans. Electron. Packag. Manuf., vol. 2, no. 12, pp. 2156-3950 (c) 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. Authorized licensed use limited to: LOUGHBOROUGH UNIVERSITY. Downloaded on September 29,2021 at 07:57:34 UTC from IEEE Xplore. Restrictions apply. IV. CONCLUSIONS 2098–2107, Dec. 2012s. In 2018, and from 2019 to 2020, he was a Research Assistant with the Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, U.K. [24] J. Fan, T. Shi, Z. Tang, B. Gong, J. Li, J. Huang, T. Li, “Low- Temperature Cu-Cu Bonding Process Based on the Sn-Cu Multilayer and Self-Propagating Reaction Joining,” J. Electron. Mater., vol. 48, no. 2, pp. 1310–1317, Dec. 2018. Zhaoxia Zhou received the B.Eng. and M.Eng. degrees from Harbin Institute of Technology, Harbin, China, in 1997, and Ph.D. degrees from Institute of Metal Research, Chinese Academy of Sciences and The University of Sheffield in 2010. She is a Research Fellow in materials characterization at Loughborough Materials Characterization Centre, Department of Materials, Loughborough University. One of her research areas is applying electron microscopy and X-ray related techniques to understand interfaces at heterogeneously integrated materials in electronics for optimized thermal, electrical and mechanical performance. Zhaoxia Zhou received the B.Eng. and M.Eng. degrees from Harbin Institute of Technology, Harbin, China, in 1997, and Ph.D. degrees from Institute of Metal Research, Chinese Academy of Sciences and The University of Sheffield in 2010. [25] T. Mukherjee, W. Zhang, T. DebRoy, “An improved prediction of residual stresses and distortion in additive manufacturing,” Comput. Mater. Sci., vol. 126, pp. 360–372, Jan. 2017. [26] Y. Liu, Thermal Stress Migration and Its Role in Electromigration of Microelectronics. In: Hetnarski R.B. (eds) Encyclopedia of Thermal Stresses, Springer, Dordrecht, 2014. [27] S. H. Rhee, Y. Du, P. S. Ho, “Thermal stress characteristics of Cu/oxide and Cu/low-k submicron interconnect structures,” J. Appl. Phys., vol. 93, no. 7, pp. 3926–3933, Apr. 2003. y She is a Research Fellow in materials characterization at Loughborough Materials Characterization Centre, Department of Materials, Loughborough University. One of her research areas is applying electron microscopy and X-ray related techniques to understand interfaces at heterogeneously integrated materials in electronics for optimized thermal, electrical and mechanical performance. [28] J. Fan, T. Shi, X. Tao, T. Zhou, J. Li, Z. Tang, G. Liao, X. Yu, “The Cu -Cu self-propagating reaction joining with different thickness of tin,” J. Alloys Compd., vol. 735, pp. 1189–1194, Feb. 2018. Shuibao Liang received the B.E. degree from Wuhan University of Science and Technology, Wuhan, China, in 2012, and the Ph.D. degree from South China University of Technology, Guangzhou, China, in 2019. Changqing Liu received his B.Eng. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final public Transactions on Components, Packaging and Manufacturing Technology This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCPMT.2021.3108017, IEEE Transactions on Components, Packaging and Manufacturing Technology IV. CONCLUSIONS degree in 1985 from the Nanjing University of Science and Technology, Nanjing, China, M.Sc. degree in 1988 from the Chinese Academy of Science, Beijing, China, and his Ph.D. degree in 1998 from Hull University, Hull, U.K. Changqing Liu received his B.Eng. degree in 1985 from the Nanjing University of Science and Technology, Nanjing, China, M.Sc. degree in 1988 from the Chinese Academy of Science, Beijing, China, and his Ph.D. degree in 1998 from Hull University, Hull, U.K. He is currently a Research Associate with the Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, U.K. Yi Zhong received the B.E. degree from Nanchang Hangkong University, Nanchang, China, in 2013, and the Ph.D. degree from Dalian University of Technology, Dalian, China, in 2018. From 2018 to 2020, he was a Research Associate with the Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, U.K. In 2020, He joined the Xiamen university, as an Assistant Professor. He was an Assistant Professor with the Institute of Metals Research, Chinese Academy of Science. From 1993, he secured an Overseas Research Scholarship and moved to the U.K. for his PhD study. In 1997, he joined Birmingham University, U.K., as a Post-Doctoral Research Fellow for 3 years. In 2000, he joined the Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, U.K., where he has been a Professor of electronics manufacture since 2011, after his appointments as a Lecturer in 2005, and a Senior Lecturer in 2007. He has authored over 242 academic papers. His current research interests include advanced materials and innovative manufacturing to enable 3-D multi- material heterogeneous embodiment, integration, and miniaturization of future generation multifunctional devices. Stuart Robertson received a M.Eng. and Ph.D. degrees from Loughborough University, Loughborough, U.K., in 2014 and 2018, respectively. Stuart Robertson received a M.Eng. and Ph.D. degrees from Loughborough University, Loughborough, U.K., in 2014 and 2018, respectively. From 2018 to 2020, he was a Research Associate with in the Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, U.K. He is currently a Dr. Liu is currently a Fellow of the Higher Education Academy, U.K., an IEEE Senior Member, and previously served as the Chair of the Interconnections Committee of ECTC (USA) and the Chair of Packaging Materials and Processes Committee of ICEPT (China).
https://openalex.org/W2759559981
https://ora.ox.ac.uk/objects/uuid:aa2c93bb-547b-4b4e-8d6d-46622e781c0d/files/m060c396352a78af0c76833c9b6b559e6
English
null
Deep Brain Stimulation, Authenticity and Value
Cambridge quarterly of healthcare ethics/CQ. Cambridge quarterly of healthcare ethics
2,017
cc-by
12,223
Cambridge Quarterly of Healthcare Ethics (2017), 26, 640–657. © Cambridge University Press 2017. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. doi:10.1017/S0963180117000147 640 org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Continuing the Conversation This work was supported by the Wellcome Trust [WT203195/Z/16/Z]; [WT104848/Z/14/Z]. nloaded from https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017 JONATHAN PUGH, HANNAH MASLEN, and JULIAN SAVULESCU Abstract: Deep brain stimulation has been of considerable interest to bioethicists, in large part because of the effects that the intervention can occasionally have on central features of the recipient’s personality. These effects raise questions regarding the philosophical concept of authenticity. In this article, we expand on our earlier work on the concept of authenticity in the context of deep brain stimulation by developing a diachronic, value-based account of authenticity. Our account draws on both existentialist and essentialist approaches to authenticity, and Laura Waddell Ekstrom’s coherentist approach to personal autonomy. In developing our account, we respond to Sven Nyholm and Elizabeth O’Neill’s synchronic approach to authenticity, and explain how the diachronic approach we defend can have practical utility, contrary to Alexandre Erler and Tony Hope’s criticism of autonomy-based approaches to authenticity. Having drawn a distinction between the authenticity of an indi- vidual’s traits and the authenticity of that person’s values, we consider how our conception of authenticity applies to the context of anorexia nervosa in comparison to other prominent accounts of authenticity. We conclude with some reflections on the prudential value of authenticity, and by highlighting how the language of authenticity can be invoked to justify covert forms of paternalism that run contrary to the value of individuality that seems to be at the heart of authenticity. Keywords: authenticity; deep brain stimulation; anorexia nervosa; autonomy; well-being m https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 m https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Cambridge Quarterly of Healthcare Ethics (2017), 26, 640–657. org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Deep Brain Stimulation, Authenticity and Value aspects of the self that are regarded as symptoms of the mental disorder as inau- thentic; however, other patients may hold precisely the opposite view.10 Moreover, the very aim of DBS in this context may be to try to evoke changes to some of the values, beliefs, or affective responses that might be deemed pathological, or to undergird the patient’s disorder. In earlier work, we have tried to address some of the issues pertaining to authenticity in the context of using DBS as an experimental treatment for anorexia nervosa.11 In this work, we defended a diachronic conception of authenticity, and a corresponding approach to its assessment, according to which patients are encouraged to reflect on changes to their moods and behavior both when “on” and “off” stimulation, to better determine whether the patient embraces them as authentic over time. This initial discussion has been fruitfully taken up and further advanced in an article by Sven Nyholm and Elizabeth O’Neill in this journal.12 Here, we hope to further advance this discussion by exploring the differences between our interpre- tations of authenticity in the context of using DBS in the treatment of psychiatric disorders. We will begin by briefly introducing the concept of authenticity, before summarizing some areas of seeming theoretical disagreement between our dia- chronic conception of authenticity, the synchronic approach endorsed by Nyholm and O’Neill, and the broadly essentialist “true self” view advocated by Erler and Hope. We will then consider the practical implications of these disagreements for understanding of the issues pertaining to authenticity in context of using DBS to treat anorexia nervosa. Keywords: authenticity; deep brain stimulation; anorexia nervosa; autonomy; well-being Deep brain stimulation (DBS) is a highly invasive neurosurgical procedure that has been shown to have profound therapeutic effects in the treatment of move- ment disorders. In addition to being routinely commissioned for Parkinson’s dis- ease and dystonia in the United Kingdom, DBS is currently being considered as an experimental intervention for a wide range of indications, including certain psy- chiatric disorders, such as anorexia nervosa and depression.1 The majority of patients who undergo DBS for Parkinson’s disease and dystonia experience positive treatment outcomes.2 However, even though it is routinely com- missioned for these indications, DBS can, in some cases, have unintended adverse side effects.3 In particular, a small number of patients have reported feelings of self- alienation following DBS treatment, and some have even seemingly undergone radi- cal changes in their personalities, becoming far more impulsive, and developing tastes and behaviors that they only exhibit under the influence of stimulation.4 Although comparatively rare, such cases have been of considerable interest to bioethicists, in large part because of the questions that they raise regarding the philosophical concept of authenticity5 (that is, the property of living in accordance with one’s “true self”), as well as questions related to inter alia, personal identity,6 and moral responsibility.7 Conversely however, other patients claim that DBS treatment has enhanced their abil- ity to live authentically, by virtue of removing the disease state that had previously inhibited their ability to live in accordance with their true selves.8 The issues related to authenticity are arguably more complicated when we consider the use of DBS in the treatment of psychiatric disorders.9 As Alexandre Erler and Tony Hope have observed, some of those with such disorders may view m https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Jonathan Pugh, Hannah Maslen, and Julian Savulescu not entail that this is the correct approach to the question of authenticity. First, it seems plausible that the true self could have negative valence, even if people do not assess their own true self (or the self of another) in this way. More significantly, however, some critics of this approach to authenticity have claimed that the idea that we have a hidden essential self that is waiting to be discovered is deeply prob- lematic, and most likely a fiction.17 Drawing on themes from existentialist philosophy, advocates of authenticity who dispute the notion of an essential self have claimed that authenticity should be construed as a form of self-creation. To live authentically, in strong versions of this view, is to choose the person that one wishes to become, unburdened by the dictates of a fixed essence. Through this approach, we can identify authentic elements of the individual’s self by identifying those elements that the individual reflectively endorses.18 The essentialist and existentialist conceptions have sometimes been understood as representing two poles on a continuum of theories of authenticity,19 and even as rival conceptions. For example, in their discussion, Erler and Hope argue that (1) existentialist conceptions of authenticity lack practical utility for those who wish to draw on the notion of authenticity to help guide their choices and commit- ments, and (2) that those with mental disorders often draw on an essentialist con- ception.20 For Hope and Erler, the purported lack of practical utility associated with the existentialist conception derives from the conceptual difficulty of how individuals may plausibly be said to authentically choose their own characteris- tics in the way that the existentialist approach seems to demand. We will elaborate on this criticism of the existentialist conception subsequently. p q y However, as we mentioned, critics similarly raise concerns about the essentialist conception of authenticity, in particular its seeming reliance on a hidden essential self. In view of the fact that each conception of authenticity has both apparent flaws and strengths, we may well feel attracted to both understandings.21 Rather than seeking to explain why one sort of conception is more convincing, a more plausible strategy may be to try and seek some common ground between the two. Introducing Authenticity As an initial starting point, we can say that to be authentic is to live in accordance with one’s “true self.” If such language of a “true self” is to be of any practical significance, then it seems that one must also accept that there can be elements of a person’s self more generally that are not part of the “true” self, but instead merely peripheral. To live inauthentically is to fail to live in accordance with the true ele- ments, even if one can be understood as living in accordance with these peripheral elements. The key question for a theory of authenticity is how we should identify those features of the self that are “true,” and those that are peripheral.13,14 p p As Nyholm and O’Neill also recognize, social psychology can give us a number of clues about how we do in fact seem to go about identifying these features. In a recent review, George Newman et al. point out that when an individual makes an assessment either about his or her own “true self” or another’s, that person tends to emphasize features that have positive valence, particularly if those features are moral features.15 Further, and interestingly for our purposes, research in this area also suggests that these sorts of positive features of the self tend to be understood in an essentialist fashion; that is, they are understood to constitute a “discrete, biologically based, immutable, informative, consistent” characteristic that is “deeply inherent within the person.”16 p We will refer to this as the essentialist conception of authenticity. According to this sort of view, to live authentically is to live in accordance with this deep essence; the path to authenticity on this account is one of self-discovery of this (usually positive) essence. However, the mere fact that social psychologists have shown that people tend to make judgements about authenticity in accordance with this model clearly does 641 org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Deep Brain Stimulation, Authenticity and Value 1) The true self permeates human thinking and so will affect how stakeholders interpret the results of DBS. 1) The true self permeates human thinking and so will affect how stakeholders interpret the results of DBS. 2) The true self is a synchronic notion that permits us to describe effects of DBS on the self that the diachronic concept of personal identity does not. p p y 3) The extent to which the true self is expressed can be a matter of degree.l 4) The degree to which persons feel their true self is expressed can be influenced by their modes of functioning, which can be affected by DBS. y g y 5) In some cases, radical transformation can make the true self more fully expressed. p 6) Which features are considered characteristic of a person’s true self depends, in an important sense, on which features he or she values.23 We agree with much of Nyholm’s and O’Neill’s assessment; however, we will raise some queries about the second and sixth features that they identify. At this point, however, we may observe that the other four features are clearly compatible with the dual-basis framework that we have just sketched. We take (1) to capture the idea that authenticity is often treated as a normative ideal, as something that we have reason (whether prudential, moral or autonomy based) to achieve; the same can also be said of both essentialist and existentialist elements of the dual- basis framework. Similarly, in accordance with (3) and (4), authenticity in either essentialist or existentialist terms may plausibly be said to admit of degree, and this can plausibly be affected by our modes of functioning, and thus by DBS. p y y g y Prima facie, feature (5) might seem problematic for the essentialist element of the dual-basis view. If living authentically is to live in accordance with the dispositions, talents, and personalities that one has (even if we do not make the strong claim that these features must be parts of an immutable essential self), how can radical change be compatible with authenticity? org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 This sort of thought has motivated much criticism of the use of various technologies to enhance human mood and cognition.24 However, the prospect of radical change need only threaten authenticity in this conception if we assume that a tenet of this conception is that one must accept the extant features of the self that one has thus far discovered. However, as Levy points out, this not a tenet of the essentialist view as it has historically been defended; self-discovery might tell us that we need to undergo radical change in order to live in accordance with our essence.25 For example, it is quite possible to have an essentialist understanding of the radical transformation of Ebenezer Scrooge in A Christmas Carol; according to such a reading, the purpose of Scrooge’s hauntings were to help him to discover that his miserly personality did not reflect who he was at a fundamental level. The potential points of disagreement between our understanding of authenticity and that which is endorsed by Nyholm and O’Neill pertain to their features (2) and (6). Although Nyholm and O’Neill do not invoke the terminology of essen- tialism or existentialism, we believe that these features of their understanding of authenticity seem to invite an existentialist interpretation of their view as we shall go on to explain and critique in the next section. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 This strategy becomes more plausible once we concede that one need not be committed to strong forms of essentialism or existentialism of the sort that we have caricatured here. Neil Levy captures this point as follows: Downloaded from https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:2 We can emphasize self-discovery without holding the empirically implausible notion that the self has a fixed essence; we can point to the fact that people do have dispositions and talents and personalities, which fit them better for some activities than for others . . . without committing ourselves to the claim that people are immutable, and even without denying that genuinely profound change is possible. We can emphasize self-creation without denying that change is difficult and always only partial. The ethics of self-creation and of self-discovery are better seen as outlooks on human life; conceptions of how we best live.22 Downloaded from https://www.cambridge.org/core. Universi We believe that Levy captures an important insight with this framework, which we will henceforth refer to as the dual-basis framework. We return to this framework of authenticity later. We believe that Levy captures an important insight with this framework, which we will henceforth refer to as the dual-basis framework. We return to this framework of authenticity later. At this point, however, it should be noted that Nyholm and O’Neill do not invoke the terminology of either self-creation or self-discovery in their discussion of authenticity in the context of DBS. Instead, they identify what they take to be six core features of the true self: 642 aded from https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0 contingent on the history of the agent’s traits or desires: authenticity can be assessed in an isolated time-slice. In understanding authenticity as a synchronic notion (as feature 2 stipulates), Nyholm and O’Neill draw a distinction between authenticity and narrative identity (as well as numerical identity). In contrast to numerical identity, narrative identity concerns the qualitative sense of identity that captures the continuity of a person’s character over time, a character grounded by an autobiographical self-narrative that incorporates the agent’s past traits, actions, and experiences.26 As authenticity is synchronic in Nyholm and O’Neill’s account, whether or not a person is authentic does not depend on whether that person exhibits the sort of continuity over time that narrative identity implies. p y y p In the context of DBS, Nyholm and O’Neill are therefore concerned that by focusing only on narrative identity, bioethicists might overlook the question of whether DBS has an important impact on the self here and now, independently of how the person relates to him- or herself in the past. They claim: “if a patient has experienced severe OCD over a long period of time, it might be more in keeping with her past narrative if she were to continue having obsessions and compul- sions. However, one might think instead that her real self would be better served if she could rid herself of that dominant narrative.” Claiming that authenticity is synchronic in this way has important implications for the question of how we should ascertain whether some feature of the self (e.g., a particular desire) is authentic, which is a key question for any theory of authenticity. More specifically, understanding authenticity as a synchronic notion seems to require abandoning the essentialist claim that to ascertain whether some feature of the self is authentic, we should appeal to other enduring, extant elements of the self. If authenticity is purely synchronic, why should these enduring elements have implications for authenticity in the here and now? p y Feature (6) offers some clues as to how Nyholm and O’Neill believe we should ascertain an agent’s authentic desires. On this approach, an individual’s true self may plausibly be construed as being constituted, and indeed grounded, by the agent’s values. Synchronicity, Diachronicity, and Value The central feature of Nyholm and O’Neill’s account of authenticity is synchronicity. In this context, synchronicity implies that the authenticity of a trait or desire is not 643 mbridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Jonathan Pugh, Hannah Maslen, and Julian Savulescu Deep Brain Stimulation, Authenticity and Value Erler and Hope think that this sort of conception is problematic because it lacks practical value for those who wish to draw on the notion of authenticity to help guide their choices and commitments. They write: “When a person is struggling with the question of what are her authentic desires (or other relevant psychological aspects of the self) it is not particularly helpful to be told that whatever she decides, as long as she commits herself wholeheartedly or has reflected carefully, will be authentic. The question of authenticity, from this perspective, precedes and informs which desires the person wishes to endorse or which decisions she makes.”28 p We take it that the point Erler and Hope are making here is that existentialist conceptions of authenticity such as Frankfurt and DeGrazia’s arguably put the cart before the horse. Such theories claim that to ascertain whether some element of the self is authentic, we broadly need to consider whether the agent would identify with it after reflection; however, if such reflection is to be a guide to authenticity, we surely need to know that the sort of reflection being conducted is itself authentic. f We will not be concerned here with the exegetical question of whether this is a fair criticism of DeGrazia’s conception of authenticity. We believe that it is possible to develop a dual-basis view of diachronic authenticity that builds on the idea of reflective endorsement but that avoids Erler and Hope’s criticism. At this point however, we may note that Erler and Hope’s criticism seems problematic for exis- tentialist authenticity conceived as a purely synchronic notion in the way that Nyholm and O’Neill outline. The reason for this is that if authenticity is a purely synchronic notion, then it is not clear what basis there could be for grounding the authenticity of elements of the agent’s self, including that agent’s present values, other than the values that the agent exhibits here and now; however, this is the very element of the self whose authenticity is under question. ownloaded from https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000 Deep Brain Stimulation, Authenticity and Value aded from https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0 However, in their discussion of this feature, they do not elaborate on their understanding of values in this context; rather, they focus on how third- party assessments of authenticity will be informed by the third party’s values. p y y y p y Although it is no doubt true that third-party assessments of authenticity will be informed by the third party’s values, we are more interested in the role that the individual’s values play in that person’s own sense of authenticity. However, without further elaboration on what it means for a person to value something, Nyholm and O’Neill’s appeal to the individual’s values seems to leave their understanding of authenticity open to the critique that Erler and Hope aim at existentialist accounts, briefly sketched previously. To see why, it is illuminating to first consider the main targets of Erler and Hope’s criticism. They aim their criti- cism at Harry Frankfurt’s wholeheartedness account (according to which an ele- ment of the self is authentic if endorsed wholeheartedly) and David DeGrazia’s autonomy-based account. According to this latter account, a self-creation project is authentic if it is both autonomous and honest. In turn, a self-creation project is autonomous if (1) the agent chooses it because that person prefers this project, (2) that person has this preference because he or she (at least dispositionally) identifies with and prefers to have it, and (3) this identification has not resulted primarily from influences that that person would, on careful reflection, consider alienating.27 644 m https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 mbridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Jonathan Pugh, Hannah Maslen, and Julian Savulescu their desire to x or to realize their desire to y, given their other coherent values and rational beliefs. If they deem it more valuable for them to realize x than y, then their preference to realize this desire may be incorporated as a cohering element of their true self.30 In developing this account, Ekstrom claims that cohering rationally endorsed elements of the self are good candidates for constituting the true self for three rea- sons. First, they are particularly long-lasting because they are well-supported with reasons. This is important because, as Ekstrom recognizes in her discussion: “a variety of beliefs and desires . . . come and go in us in a rather fleeting manner. But we expect our character to be more continuous than this – if not constant, then at least not in a state of perpetual fluctuation.”31 Second, cohering elements will be fully defensible against external challenge by virtue of their support from the coherent nexus in which they reside. Third, they will also be elements that the agent feels comfortable owning, by virtue of that same fact.32i Consider first the implications of this coherence approach to the relationship between narrative identity and authenticity. First, on the rationalist understand- ing that we have sketched, persons can clearly disvalue significant elements of their personal history. Accordingly, with respect to Nyholm and O’Neill’s OCD example, the mere fact that the person’s history has included experiencing the symptoms of OCD, does not tell us anything about the implications that treatment may have for authenticity. In order to ascertain this, we would need to know how the patient values his or her experience of these symptoms. For example, some successful academics might plausibly value their obsessiveness over details of their work; conversely, compulsive hand-washers may want desperately to be rid of their anxiety and compulsive behavior. y p To this point, it might be claimed that the coherence approach seems to be an account of authenticity that contrasts the concept with the notion of narrative identity, in so far as we claim that one can disvalue significant elements of one’s personal history. However, this understanding of authenticity departs from Nyholm and O’Neill’s synchronic understanding, in so far as an agent’s values are most plausibly understood in a diachronic sense. mbridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 We believe that this also helps to explain how a coherence approach to authenticity can avoid Erler and Hope’s criticism regarding practical utility, as we will now explain. A Dual-Basis View of Diachronic Authenticity To avoid Erler and Hope’s critique of existentialist approaches to authenticity, we believe that we need to appeal to diachronic values, and in doing so, incorporate some broadly essentialist elements to our account of authenticity. In light of Levy’s comments, however, we take this to be a strength rather than a weakness of our theory. Using the approach that we endorse, we may say that a person values x when that person believes that x is good, in the sense that that person understands him- or herself to have broadly prudential or autonomy-based reasons to pursue x; our values are thus responses to our beliefs about what is good for us or others. This is a rationalist approach to value.29 Although we can revise our beliefs about what is good for us, it would be indicative of irrationality (or reasons-irresponsiveness) if these beliefs were unduly capricious. We claim that the true self is best construed as being constituted by the cohering elements of the individual’s nexus of values and that individual’s rational beliefs. Here, we broadly follow a view of authenticity that is implicit within Laura Waddell Ekstrom’s coherence account of personal autonomy. Whereas Ekstrom develops a nuanced account of what it is for elements of the self to cohere, for our purposes here, a rough understanding will be sufficient. Roughly, we may say that these elements of the self cohere if they are mutually compatible. In the case of mutually incompatible elements of the self, such as, say, a desire to x and a desire to y, individual agents must decide whether it is more valuable for them to realize 645 Deep Brain Stimulation, Authenticity and Value However, we can also make sense of the importance of preexisting values without committing ourselves to this overtly essentialist interpretation, whereby Scrooge was really never a miser. According to a reading that is more in keeping with the existentialist approach, part of the reason that we might believe that Scrooge was living authentically after his radical change is that the ghosts who haunted him persuaded him to change his miserly ways by appealing to other values that he held, to show him that he had reasons to change his hitherto positive evalu- ation of “being miserly.” The ghosts showed him that he would die alone and despised if he continued his miserly ways. This strategy would only have been successful if Scrooge, as he appears to do, already placed disvalue on a life in which this occurred. Importantly, according to this interpretation, the change that Scrooge under- went cannot be completely wholesale if it is to be authentic. For Scrooge to believe that he has reasons to change his ways, there must be something in his conception of the good prior to his haunting through which he can understand why he has a reason to change; if not, it is not clear how the change could be intelligible to Scrooge. Using this approach, although we can undergo radical authentic change, we can only do so in a manner akin to rebuilding Neurath’s raft; that is, we can only intelligibly and justifiably change constituent parts of our true selves by appealing to other values that we hold. Although we may come to change many or even all of our values over time, such changes are only authentic if our decision to do so is made intelligible by some other reason implying value that we maintain over the course of that change.34 g It is important to remember that our character contains many elements, some often in conflict with others. Few people are purely virtuous or purely vicious; we are all conflicted, a mix of “light and dark.” Using the coherence approach, the true self is best understood as the set of cohering elements of the self that we understand ourselves to have most reason to preserve. Our choices about which elements of our characters to preserve as central elements of our selves amount to decisions to bring out certain aspects of our character, while downplaying others. The Practical Utility of a Diachronic Conception of Authenticity: Enduring Values and Intelligible Change To begin, it is important to note that the expectation that elements of the true self will be continuous and long-lasting is quite consistent with the possibility of one retain- ing authenticity despite undergoing a radical change in character (as Nyholm and O’Neill’s feature 5 suggests). Such change can be authentic if it is intelligible to the agent in the light of that agent’s preexisting values and commitments. To illustrate, consider again the example of Scrooge from A Christmas Carol. Previously, we explained that it is possible to give an essentialist reading of this example, according to which Scrooge may be understood to be authentic following his radical change, because the hauntings helped him to discover that his miserly personality did not reflect his essence. According to this reading, Scrooge’s change is intelligible to him by virtue of the preexisting deep value (of non-miserliness) that actually constituted his essence, or part of it, and which he comes to accept and recognize as his own.33 646 University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Jonathan Pugh, Hannah Maslen, and Julian Savulescu sufficient for establishing authenticity; we can still ask whether the rational evalu- ation itself is incorporated into the agent’s true self. This is the point that Erler and Hope’s critique of Frankfurt and DeGrazia’s account raises. However, the coherence approach can offer an answer to this question by investigating whether the rational evaluation is incorporated into a coherent character system, whose lineage can be traced back over a diachronic process of intelligible rational change. The crux of Erler and Hope’s criticism of existentialist accounts seems to be that if the language of authenticity is to be of practical value, there needs to be some sort of foundational essential self whose characteristics can plausibly undergird our judgements of authenticity. This has parallels with the approach that epis- temic foundationalists adopt in understanding the justification of knowledge; epistemic foundationalists claim that certain beliefs are basic, and that our other beliefs are epistemically dependent on these basic beliefs. Whereas epistemic foundationalists face difficulties in accounting for the items of basic knowledge, adopting a foundationalist approach to the self faces the analogous problem of stipulating the existence of a foundational, or basic, essential self. The coherence approach that we advocate also has a parallel in epistemology.35 Epistemic coher- entists do not claim that the justification of knowledge requires basic items of knowledge, but rather that our beliefs constitute knowledge in so far as they belong to a coherent system of mutual justification. Just as epistemic coherentists do not need to stipulate basic items of knowledge, those who adopt a coherence approach to authenticity do not need to stipulate the existence of an essential self. That said, although the coherence approach is existentialist in spirit, it also incorporates significant elements of the essentialist approach. We have already seen that Ekstrom stresses the long-lasting nature of elements of the cohering self, and the importance of this feature. A second point that Ekstrom does not acknowl- edge but that is apposite here is that we do not develop our values in a vacuum; our beliefs about what we have reasons to pursue are likely to be informed by fixed elements of our lived experience, including our awareness of our past expe- riences, and the set of traits and dispositions that we have, in part in virtue of our biology. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 The extent of our self-creation is thus limited: authentic change on this account is difficult and always only partial in the manner that Levy raises in his discussion of what we call the dual-basis framework. Our values and essential elements of our characters may thus be understood in a symbiotic fashion; it is through the lens of our evaluations, themselves developed in the light of our per- sonal history and our stable, long-lasting characteristics and traits, that we are able to understand which of our features we want to be incorporated into our under- standing of who we really are. Downloaded from https://www.cambridge.org/core. University Deep Brain Stimulation, Authenticity and Value In choosing his response to his haunting, Scrooge chose to emphasize the “light,” socially acceptable elements of his character system, and to downplay the “dark,” in rejecting his miserliness. j g The truth of essentialism is that we may have certain elements of our character that are more or less fixed. The truth of existentialism is that we may be able to choose which of these more or less fixed elements to bring to the fore, and which to downplay in developing our selves. One of the problems we face when thinking about authenticity in the context of mental disorder is that some “pathological” elements of the self seem to lack value, and do not seem worth preserving. Moreover, with some mental illness, there may be no stable coherent sense of self, and treatment may involve attempts to bring about a stable coherent self. y p g We will consider the application of our approach to authenticity to mental dis- order in greater detail subsequently. At this point, however, the discussion of the Scrooge example helps to explain why the coherence view is not susceptible to the criticism that Erler and Hope raise against DeGrazia’s existentialist conception of authenticity. The coherence approach can give practical guidance to those who wish to draw on the notion of authenticity to help guide their choices and commitments. It is true, with this approach, that simply establishing that the agent endorses some desire in accordance with a rational evaluation is not alone 647 Case One: Inauthentic Traits A 70-year-old man with advanced Parkinson’s disease underwent DBS of the subthalamic nucleus (STN). The patient developed hypersexuality as a side effect, insisting on sexual gratification from his partner. Once satisfied, the patient returns “back to his normal self,” and confronts the realization that he could not control his (unwanted) urges.36 g In this case, it appears that the DBS treatment generated inauthentic urges and related behavior (hypersexuality), but did not affect the patient’s values relating to those urges and behaviors. We can assume that, prior to the intervention, the patient’s values did not generate rational endorsement of hypersexual behavior, and the case report suggests that the patient continued to disvalue such behavior, which he now found himself engaging in following stimulation. This motivating urge was incongruous with the agent’s own nexus of values and beliefs. Downloaded from https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000 Deep Brain Stimulation, Authenticity and Value physique may come to value athletic activity and excellence more than an agent who substantially lacks athletic prowess. In relation to authenticity, we noted in the previous section that we do not develop our values in a vacuum, and that our values and essential elements of our characters may be understood in a symbiotic fashion. However, the relationship between our traits and our values is clearly not a determinate relationship. We can disvalue aspects of our character and behavior, and our values can generate and sustain rationally endorsed desires that motivate behavior that resists the influences of more basic drives and urges. Therefore, despite the inevitable interaction between traits and values, we will argue in this section that there is still an important distinction to draw between the authenticity of our more essential traits on the one hand, and the authenticity of our values on the other, with significant implications for how troubled we should be by the effects of a DBS intervention (or the effects of a psychiatric condition). The dual- basis framework, which acknowledges the essential nature of many of our traits, yet allows for authentic rejection or modification of these traits, supports this distinction. We will argue that we should be most concerned about DBS interventions that affect the authenticity of an agent’s values, especially where these values inform treatment decisions. Interventions that affect the authenticity of an agent’s traits, on the other hand, are only problematic in so far as the agent, all things consid- ered, (authentically) disvalues this influence. We now illustrate this distinction and its implications with two examples. Authenticity of Values versus Authenticity of Traits So far, our discussion has included a range of objects of authenticity: (1) the agent him or herself, (2) the agent’s traits and characteristics, and (4) the agent’s ratio- nally endorsed desires and values. To a certain extent, these are interrelated: we often (although not always) exhibit traits and behaviors that reveal our values: if an agent is consistently conscientious at work, this may be explained by the value that the person places on the ends of his or her toil, or on working hard per se. Conversely, our biological and psychological makeup is likely to have some influ- ence on our values: in general, an agent who is naturally gifted with an athletic 648 m https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Downloaded from https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://do g In case two, inauthentic values (or lack of authentic values) flowing from a sig- nificant increase in apathy would, we argue, provide a much stronger reason against continuing with the treatment, especially where the inauthentic values inform the treatment preferences of the patient. For example, if, as a result of increased apathy, the patient expressed a preference to continue with the treat- ment, because that patient did not care about the broader effects (including the increased apathy), then this treatment preference should be treated as much less instructive. This will especially be the case if the treatment preference is in tension with preferences expressed “off” stimulation. Consider also a case in which a patient develops hypersexuality under stimulation but does not regard this behavior as abnormal, and perhaps even endorses this change. In these cases, the normative significance of the inauthenticity of the patient’s values differs from the signifi- cance of the unpleasantness of exhibiting inauthentic traits. The patient, with the patient’s physician and family members, can evaluate the inauthentic traits resulting from DBS, whereas inauthentic values resulting from DBS affect the very grounds of the patient’s treatment decisions. p In the next section, we will turn to examining how the diachronic approach to assessing authenticity bears on the case of anorexia nervosa. 1) The authentic self is the well self and aspects of the self that are part of the mental disorder are inauthentic. Case Two: Inauthentic Values Apathy has been observed as a postoperative symptom of STN stimulation sur- gery. Apathy can be measured using the Frontal Systems Behavior Scale, which measures apathy using items such as “Has lost interest in things that used to be fun or important to him/her,” “Shows little emotion, is unconcerned and unrespon- sive,” and “Has difficulty starting an activity, lacks initiative, motivation.”37i A DBS treatment that resulted in a significant increase in a patient’s apathy might have a direct impact on the patient’s values; apathy can be characterized as a failure to be moved to express or act on one’s values. We suggest that a treatment 649 m https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Jonathan Pugh, Hannah Maslen, and Julian Savulescu that impacts on the patient’s values in this way is more problematic than a treat- ment that renders only (a number of) the patient’s traits inauthentic. In case one, the patient’s inauthentic hypersexual urges were clearly undesirable, not least for the patient himself. However, in this case, the patient was in a position to decide whether the benefits of the intervention (reduced PD symptoms) outweighed the cost of the inauthentic urges and associated behaviors. Therefore, even if the DBS treatment has an effect on the patient’s authenticity (as it pertains to that patient’s traits), this aspect of inauthenticity would only rule out continuing with the DBS treatment if, from the patient’s assessment of his or her best interests, the harms of the treatment outweighed the benefits. As we will explore, this example may be an instance in which authenticity (at least of traits) is less relevant than the question of what, overall, leads to the better life for the patient. However, although the incidence of inauthentic traits does not necessarily provide a decisive reason against continu- ing a DBS treatment, we do not suggest that inauthentic traits are irrelevant to treat- ment decisions. Further, inauthentic values have acute relevance, as we now argue.l org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Deep Brain Stimulation, Authenticity and Value 2) Psychological characteristics that result from taking medication are not authentic. 2) Psychological characteristics that result from taking medication are not authentic. 3) Mental disorder is part of a unified self; they see their disorder as an authentic part of who they are. 3) Mental disorder is part of a unified self; they see their disorder as an authentic part of who they are. p y 4) There are two selves, each equally authentic. 4) There are two selves, each equally authentic. 5) There is no issue of authenticity: the only consideration is what leads to the better (or best) life, and questions of authenticity are irrelevant to that question. 5) There is no issue of authenticity: the only consideration is what leads to the better (or best) life, and questions of authenticity are irrelevant to that question. However, we will argue that the prevalence of inner conflict in persons with mental disorders such as anorexia nervosa, and these different ways in which such indi- viduals draw on the concept of authenticity, do not speak decisively against adopt- ing a coherence approach to authenticity in this context. Indeed, as we suggested in our discussion, we are all conflicted to some degree.i The first thing to note is that, as a procedural account of authenticity, the coherence approach is compatible with either (1) or (3) being true of a particular individual. Some essentialist views of authenticity only advocate something like (1) as being true for all individuals with anorexia nervosa; for example, Jacinta Tan et al. have argued that the anorexic patient’s extreme positive evaluation of low weight is not authentic because it is a “pathological value.”’38 With this sort of approach, the authenticity of certain elements of the self can be determined by their substantive content; a strong desire to maintain an extremely low weight is necessarily inau- thentic because that desire is itself part of the pathology of anorexia nervosa. One benefit of this approach is that it provides an approach to authenticity that offers clear practical guidance to those with mental disorder. However, the problem with this approach is, as Erler and Hope observe, that many persons with mental disor- der claim something like (3); they believe that their “pathological values” are part of their authentic self. Authenticity and Anorexia Nervosa From the outset, it seems that the coherentist approach faces a significant diffi- culty. In many cases of psychiatric disorders, the condition itself can plausibly be understood to distort the patient’s values with implications for that patient’s cor- responding authenticity. Moreover, individuals with such disorders very rarely have a coherent sense of self, and are instead subject to feelings of extreme self- conflict. Erler and Hope stress this point, and suggest that these individuals draw upon the idea of authenticity to help find a way to resolve the conflict and give direction to self-development. In turn, they suggest that there are five alternative positions that individuals with mental disorders such as anorexia nervosa seem to endorse with respect to authenticity, as follows: Downloaded from https://www.cambridge.org/core. Univer 1) The authentic self is the well self and aspects of the self that are part of the mental disorder are inauthentic. 650 650 University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Jonathan Pugh, Hannah Maslen, and Julian Savulescu to tease out potential inconsistency and conflict. However, with this approach, particularly if such conflict does not exist, it is quite possible for an agent to authentically hold the values that are characteristic of anorexia nervosa as part of her self-conception, particularly in the case of chronic sufferers who may have shaped and developed a coherent character system over many years to accommo- date this “pathological” desire. Position (4) perhaps raises a deeper problem for the coherence approach; namely, that two cohering selves with radically different evaluative perspectives might plausibly reside in the same agent. Such an agent may thus lack stable values. Here, with the coherence approach, authenticity must partly be a matter of self- discovery, in so far as the agent must identify the distinct aspects of her coherent selves; however, it must also be a matter of self-creation, in so far as the agent must decide which of those selves to prioritize as her most authentic self. This is where the crux of the problem lies for the coherence approach in such cases: on what basis can the individual make this decision? The very values that she might appeal to in order to justify her decision are bound up in the very character systems that she may be choosing between. y g The coherence approach cannot offer an easy answer in such cases of inner con- flict; however, this is perhaps a fitting response to such hard cases. At least the coherence approach may allow third parties to offer some practical guidance about how the individual might go about making this decision, perhaps by draw- ing her attention to the strength of certain reasons, and the goods at stake in her decision. Furthermore, it is notable that such cases also raise significant issues for the essentialist perspective. Although the essentialist might claim that there is a right and wrong answer to the question “which of the two selves is the authentic one?” the essentialist still faces the epistemological question of how we should arrive at the correct answer to this question. Nyholm and O’Neill suggest that in this sort of case, we should assume that the value set that is widely endorsed by others is the authentic one. We will raise our doubts about this response at the end of this section. org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 The substantive approach resolves this conflict in favor of a view of authenticity that reflects (1), stipulating that pathological values cannot be held authentically. This strategy gives authority to the healthcare provider over the patient herself with regard to the question of the authenticity of the patient’s internal states. We have argued elsewhere that this strategy is problematic;39 however, it is important to be clear that the coherence approach does not similarly resolve the conflict in favor of a view of authenticity that instead reflects (3) simply by fiat. To simply say that what the patient herself “feels” or “believes” at a nonreflective level has unquestionable authority with regard to the authenticity of elements of her self would be problematic, given the high degree of inner conflict and vacillation that such patients experience with regard to this very issue. Rather, in cases in which these “pathological” values may plausibly be understood to have been incorpo- rated into the agent’s authentic self-understanding, this must be grounded by the coherence of those values with other long-standing cohering elements of the agent’s character system, elements that are rationally intelligible to that agent. Establishing that this is the case requires going deeper than simply asking what the patient herself believes or feels at a given moment. It may require investigating the reasons why she holds the desires she does, and how the values that undergird those desires relate to other values and beliefs that she holds. This strategy may help to elucidate whether these desires are grounded by the patient’s own rational endorsements, and whether they have any basis in reality. Moreover, it may serve 651 org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Deep Brain Stimulation, Authenticity and Value this is not to say that all directly induced psychological changes must be experi- enced as alienating with this approach. In cases in which the patient has consented to a direct intervention, the psychological change induced may be understood as intelligible to the patient in the light of the values that moved them to consent to treatment. For example, suppose a patient consents to undergo DBS for anorexia nervosa. If stimulation is successful in reducing her desire to maintain a low weight, the patient may understand this change in her evaluative stance as intel- ligible to her in light of her prior desire to change, even if the precise (direct) mech- anism by which the change occurred is not intelligible to her.41i this is not to say that all directly induced psychological changes must be experi- enced as alienating with this approach. In cases in which the patient has consented to a direct intervention, the psychological change induced may be understood as intelligible to the patient in the light of the values that moved them to consent to treatment. For example, suppose a patient consents to undergo DBS for anorexia nervosa. If stimulation is successful in reducing her desire to maintain a low weight, the patient may understand this change in her evaluative stance as intel- ligible to her in light of her prior desire to change, even if the precise (direct) mech- anism by which the change occurred is not intelligible to her.41i y g g The final position acknowledged by Erler and Hope, according to which “there is no issue of authenticity” is a position that is best understood as one regarding the value of authenticity and the role it should play in treatment decisions, rather than a position about the nature of authenticity per se. As such, the position is compatible with the coherence approach that we have outlined here, although it is perhaps in tension with the first feature of Nyholm and O’Neill’s claim that authenticity is treated as a normative ideal. To conclude we will offer some further reflections on the role that authenticity plays in well-being, and the reasons that those with mental disorder or their care team give for holding the view that authenticity is irrelevant to treatment decisions, or at least less relevant than the patient’s welfare. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Prior to doing so, we will first briefly consider the other positions identified by Erler and Hope. l y pi y p The coherence approach also provides a basis for position (2). Although authen- ticity is compatible with radical change with this approach, for such change to be authentic it must be rationally intelligible to the agent, as we explored in the previous section. Interventions that serve to directly induce psychological changes, such as psychoactive drugs or DBS, may in some cases result in feelings of alien- ation because they cause the patient to undergo changes that are unintelligible to that patient, in the light of the patient’s other values and beliefs. Depressed patients who takes Prozac may feel alienated from their elevated mood if the drug serves only to increase their positive affect without engaging with other elements of their character system that may play a role in their condition (such as apathy and feel- ings of worthlessness). This stands in contrast to indirect interventions that aim to evince changes in the patient’s mood by rationally engaging with the patient, for example, in talk therapy.40 Changes brought about via such interventions will more likely be intelligible to patients, in so far as they are brought about by changes that the patients themselves decided to make to their modes of thinking. Nonetheless, other patients on psychotherapeutics such as Prozac claim that it enables them to find their true self, presumably by creating intelligible changes, possibly rooted in primitive existing aspects of their own psychology. Therefore, 652 m https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 wnloaded from https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S096318011700 Jonathan Pugh, Hannah Maslen, and Julian Savulescu outlined here. Throughout the chapter, Mill defends the importance of developing one’s own character and living in accordance with it, stating that living in accor- dance with one’s own character is to be understood as living in accordance with the desires and impulses that express one’s “own nature as it has been developed and modified by his own culture.”44 i y Evidence from modern-day social psychology suggests that people tend to echo this Millian view in their understanding of the value of authenticity.45 This litera- ture suggests that people value authenticity because it plays a central role in “giving meaning to their lives.” Such an understanding of the value of authenticity fits neatly with Mill’s observation that: “If a person possesses any tolerable amount of common sense and experience, his own mode of laying out his existence is the best not because it is the best, but because it is his own mode.”46i With this in mind, consider now the justification that individuals offer in favor of position (5): Jams Hughes, one of the advocates of this position in the context of using medication for attention-deficit/hyperactivity disorder (ADHD) discussed by Erler and Hope, denies the importance of authenticity and claims instead that “The real question for me is whether the drug makes the taker happier and more able to accomplish life goals.”47 Hughes implicitly seems to endorse a theory of well-being that incorporates hedonistic elements (in so far as feeling happy is cen- tral to what matters to him) as well as elements of a desire-fulfilment approach to well-being (in so far as it is important that they are able to accomplish their life goals). In light of the previous discussion of the value of authenticity, this approach to well-being might seem impoverished if it is understood to eschew all reference to authenticity; for example, we might wonder to what extent accomplishing a goal increases well-being if it is not an expression of one’s own character. However, as distinguished, one can express one’s character by choosing between modes of living and experiences that are open to oneself (including those made open by biomedical intervention), even where some of these are less aligned to one’s more biologically immediate dispositions. Those who endorse position (5) might plausibly raise the complaint that even supporters of authenticity should concede that it is not the only prudential value. Authenticity and Well-Being Authenticity might plausibly be understood to have instrumental prudential value for well-being.42 This is perhaps most obvious in hedonistic accounts of well-being, according to which what would be best for someone is what would make that person’s life happiest. Authenticity is plausibly instrumental to well- being because it involves the experience of a particular kind of positive mental state (that of feeling authentic), or at least the absence of a negative mental state (that of alienation). However, although authenticity is often explicated in phenomenological terms, our positive evaluation of authenticity is not, it seems, wholly explicable in such terms. The reason for this is simply that authenticity need not be experienced as a pleasurable mental state, a point that Felicitas Kraemer also recognizes in her dis- cussion of authenticity and DBS;43 conversely, alienation need not be experienced as a negative mental state. In such cases, if we still value the experience of authen- ticity (and disvalue alienation), this cannot be explicated in purely hedonic terms. y ( ) p p y One way to capture the value of authenticity in such cases is to understand authenticity to be prudentially valuable as an end in itself, or to be a constitutive element of objective well-being. Using such an approach, our prudential reason to live authentically is not just that it will, on balance, lead to more pleasurable mental states (although it may); rather, we have a reason to live authentically for authenticity’s own sake. This view garners support from John Stuart Mill’s famous defense of individuality as one of the elements of well-being in Chapter 3 of On Liberty. Here, Mill writes that the man who cultivates his individuality becomes more valuable to himself, and achieves a “greater fullness of life about his own existence.” Whereas there is some debate about how best to construe Mill’s con- ception of individuality, some passages hint toward a reading that suggests that individuality for Mill comes close to the conception of authenticity that we have 653 Deep Brain Stimulation, Authenticity and Value This sort of view seems inimical to Mill’s championing of individuality against the forces of custom, and his derisory claim that “he who lets the world, or his own portion of it, choose his plan of life for him, has no need of any other fac- ulty than the ape-like one of imitation.”49 We do not deny that a case can be made y p y in favor of Nyholm and O’Neill’s claim; our point here is that it seems prima facie problematic to ascertain authenticity, a concept whose value is tied to individual meaning, by reference to the values of others. This is not merely a pedantic theoreti- cal foible. In light of the close relationship between authenticity and autonomy according to many approaches (including our own), the identification of authentic desires as those that are congruous with widely shared values raises the prospect that this strategy might in practice amount to dressing up considerations of benef- icence in the language of autonomy; this in turn, is a good recipe for paternalism, albeit via the back door. Deep Brain Stimulation, Authenticity and Value Deep Brain Stimulation, Authenticity and Value We recognize the appeal of this strategy in that it provides us with a clear action- guiding principle in cases of epistemic uncertainty. However, the previous reflec- tions suggest that more work needs to be done on explicating why the fact that a mind-set incorporating values that fall inside the range of widely endorsed values should be understood as the mind-set that is more expressive of the person’s true self. This sort of view seems inimical to Mill’s championing of individuality against the forces of custom, and his derisory claim that “he who lets the world, or his own portion of it, choose his plan of life for him, has no need of any other fac- ulty than the ape-like one of imitation.”49 We do not deny that a case can be made in favor of Nyholm and O’Neill’s claim; our point here is that it seems prima facie problematic to ascertain authenticity, a concept whose value is tied to individual meaning, by reference to the values of others. This is not merely a pedantic theoreti- cal foible. In light of the close relationship between authenticity and autonomy according to many approaches (including our own), the identification of authentic desires as those that are congruous with widely shared values raises the prospect that this strategy might in practice amount to dressing up considerations of benef- icence in the language of autonomy; this in turn, is a good recipe for paternalism, albeit via the back door. We recognize the appeal of this strategy in that it provides us with a clear action- guiding principle in cases of epistemic uncertainty. However, the previous reflec- tions suggest that more work needs to be done on explicating why the fact that a mind-set incorporating values that fall inside the range of widely endorsed values should be understood as the mind-set that is more expressive of the person’s true self. wnloaded from https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S096318011700 In cases of mental disorder, it may also be a prudential value that is incompatible with other plausible constituents of well-being, including, for example, the experience of positively valenced mental states. Considering the precise role of authenticity in well-being would take us far beyond the scope of this article. However, we believe that this brief reflection on this matter raises a concern about Nyholm and O’Neill’s preferred strategy when we face epistemic uncertainty regarding the authenticity of an individual with unstable values. In cases of such uncertainty in which we cannot rely on the patient’s own values, Nyholm and O’Neill suggest that we may instead need to take as our reference points widely endorsed values that are viewed as sensible or legitimate even by those who do not hold them: the commonly recognized range of what are regarded as val- ues about which there can be reasonable discussions and disagreements. If the values the patient has in one mind-set fall squarely outside of this range, whereas the values the patient has in a different mind-set fall inside of this range, then this might be taken to give us reason to suppose that the latter values are more expressive of the person’s true self than are the former.48 654 m https://www.cambridge.org/core. University of Oxford, on 17 Nov 2017 at 11:58:27, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Notes The issues pertaining to personal identity and moral responsibility might also be understood to be more complicated in the case of psychiatric disorders to the extent that such disorders can be understood to threaten personal identity and/or moral responsibility. However, we do not make a stand on this claim here. 9. The issues pertaining to personal identity and moral responsibility might also be understood to be more complicated in the case of psychiatric disorders to the extent that such disorders can be understood to threaten personal identity and/or moral responsibility. However, we do not make a stand on this claim here. 9. The issues pertaining to personal identity and moral responsibility might also be understood to be more complicated in the case of psychiatric disorders to the extent that such disorders can be understood to threaten personal identity and/or moral responsibility. However, we do not make a stand on this claim here. 10. See note 4, Kraemer 2013. 11. Maslen H, Pugh J, Savulescu J. The ethics of deep brain stimulation for the treatment of anorex nervosa. Neuroethics 2015;8(3):215–230; see note 15, Maslen et al. 2015. 12. See note 5, Nyholm, O’Neill 2015. 13. Marya Schetmann calls this the characterization question. See Schechtman M. The Constitution of Selves. Ithaca; London: Cornell University Press; 1996, 73. 13. Marya Schetmann calls this the characterization question. See Schechtman M. The Constitution of Selves. Ithaca; London: Cornell University Press; 1996, 73. 14. We note that the spatial metaphor of peripheral traits is suggestive of synchronicity: traits at differ- ent distances from the central self, instantiated at the same time. However, we do not intend to use this metaphor to illustrate anything substantive about the account of authenticity we will develop: peripheral traits might be better or alternatively understood as less frequently instantiated. 15. Newman GE, Bloom P, Knobe J. Value judgments and the true self. Personality and Social Psychology 2014;40(2):203–16. 16. See note 15, Strohminger et al. 17. See note 15, Strohminger et al.; DeGrazia D. Human Identity and Bioethics. Cambridge: Cambrid University Press; 2005, at 233–34. 18. In their discussion, Erler and Hope draw a tripartite distinction between what they term “authenticity as wholeheartedness,” “authenticity as autonomous and honest endorsement,” and “true-self- accounts.” The first two can be understood to be examples of what we call existentialist accounts, whereas the latter maps onto what we are terming essentialist accounts. Erler A, Hope T. Jonathan Pugh, Hannah Maslen, and Julian Savulescu Jonathan Pugh, Hannah Maslen, and Julian Savulescu Conclusion We have defended a coherentist approach to authenticity that draws on both exis- tentialist and essentialist themes. It grounds claims of authenticity by an appeal to the agent’s diachronic values, recognizing that such values, although not immu- table, are likely to be long-lasting and difficult to change. We believe that this diachronic approach is better placed to respond to Erler and Hope’s critique of existentialist approaches to authenticity than the synchronic approach outlined by Nyholm and O’Neill. Although the approach that we have defended denies the presence of a hidden essential coherent self that requires discovery, the coherentist approach can offer practical guidance to those who wish to invoke the language of authenticity in their practical deliberations. When considering whether some ele- ment of the self is authentic, we must consider not just whether the individual rationally endorses it, but also whether that evaluation is incorporated into a coherent character system, whose lineage can be traced back over a diachronic process of intelligible rational change. We have also drawn attention to the conflicting nature of character traits, and how authenticity may involve greater emphasis on some, and downplaying others. p p y g This account will not provide us with a “one- size-fits-all” answer to ques- tions of authenticity in mental disorder, or to questions regarding the implica- tions of DBS for authenticity; much will depend on how individual agents view their own condition in their self-conception and their other evaluations, and whether DBS is most aptly construed as effecting their traits or their values themselves. However, we take this flexibility to be a strength of our approach, in that it is able to adapt to the individual experiences of psychiatric disorders and treatment. If we are serious about protecting the value of indi- viduality that seems to be at the heart of authenticity, then we believe that there is good reason to be wary of less flexible approaches, in so far as they threaten to impose an objective conception of the good onto others in the name of their authenticity. 655 available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0963180117000147 Notes The funding information was not included in the print or original online version of this article. It has now been added as an acknowledgment footnote on page 640. A corrigendum has been published. The funding information was not included in the print or original online version of this article. It has now been added as an acknowledgment footnote on page 640. A corrigendum has been published. 1. Mayberg HS, Lozano AM, Voon V, McNeely HE, Seminowicz D, Hamani C. Deep brain stimulation for treatment-resistant depression. Neuron 2003;45(5):651–60; Lipsman N, Lozano AM. Targeting emotion circuits with deep brain stimulation in refractory anorexia nervosa. Neuropsychopharmacology 2014;39(1):250–51; Bari AA, Kon Kam King N, Lipsman N, Lozano AM. Deep brain stimulation for neuropsychiatric disorders. In: Tuszynski MH, ed. Translational Neuroscience. New York: Springer US;2016:499–516. 2. Rodriguez-Oroz MC, Obeso JA, Lang AE, Houeto JL, Pollak P, Rehncrona S. Bilateral deep brain stimulation in Parkinson’s disease: A multicentre study with 4 years follow-up. Brain 2005;128(10): 2240–49; Hu W, Stead M, Deep brain stimulation for dystonia. Translational Neurodegeneration 2014;3:2. 3. Clausen J. Ethical brain stimulation – neuroethics of deep brain stimulation in research and clinical practice. European Journal of Neuroscience 2010;32(7):1152–62. 4. Baylis F. ’I am who I am’: On the perceived threats to personal identity from deep brain stimulation. Neuroethics 2013;6(3):513–26; Kraemer F. Me, myself and my brain implant: Deep brain stimulation raises questions of personal authenticity and alienation. Neuroethics 2013;6(3):483–97; Lipsman N, Glannon W. Brain, mind and machine: What are the implications of deep brain stimulation for perceptions of personal identity, agency and free will? Bioethics 2013;27(9):465–70; Klaming L, Haselager P. Did my brain implant make me do it? Questions raised by DBS regarding psychologi- cal continuity, responsibility for action and mental competence, Neuroethics 2010;6(3):527–39. 5. See note 4, Kraemer 2013; Nyholm S, O’Neill E. Deep brain stimulation, continuity over time, and the true self. Cambridge Quarterly of Healthcare Ethics 2016;25(4):647–58; Maslen H, Pugh J, Savulescu J. Authenticity and the stimulated self: Neurosurgery for anorexia nervosa. AJOB Neuroscience 2015;6(4):69–71. 6. See note 4, Baylis 2013. 7. Sharp D, Wasserman D. Deep brain stimulation, historicism, and moral responsibility. Neuroethics 2016;9(2):173–85; see note 4, Klaming, Haselager 2010. 8. See note 4, Kraemer 2013. 9. Notes Mental disorder and the concept of authenticity. Philosophy, Psychiatry, & Psychology 2015;21(3):219–32. 19. Bublitz JC, Merkel R. Autonomy and authenticity of enhanced personality traits. Bioethi 2009;23(6):370. 656 Deep Brain Stimulation, Authenticity and Value 20. See note 18, Erler, Hope 2015. p 21. Parens E, Authenticity and ambivalen Hastings Center Report 2005;35(3):34–41 p 21. Parens E, Authenticity and ambivalence: Toward understanding the enhancement debate. The Hastings Center Report 2005;35(3):34–41. y Hastings Center Report 2005;35(3):34–41. g p ( ) 22. Levy N. Enhancing authenticity. Journal of Applied Philosophy 2011;28(3):312. 23. See note 5, Nyholm, O’Neill, 2016. 23. See note 5, Nyholm, O’Neill, 2016. 24. Elliott C. Better than Well : American Medicine Meets the American Dream. New York ,London W.W. Norton; 2003. Levy N. Enhancing authenticity. Journal of Applied Ph 25. Levy N. Enhancing authenticity. Journal of Applied Philosophy 2011;28(3):316. 26. Schechtman M. The Constitution of Selves. Ithaca; London: Cornell University Press; 1996. 26. Schechtman M. The Constitution of Selves. Ithaca; London: Cornell University Press; 1996. 27. See note 17, DeGrazia 2005, at 102. 28. See note 18, Erler, Hope 2015. p 29. For a detailed account of this rationalist approach see See Parfit D. On What Matters. Oxford: Oxford University Press; 2011. Part One. Oxford University Press; 2011. Part One. y 30. Ekstrom LW. A coherence theory of autonomy. Philosophy and Phenomenological Research 1993;53(3):599–616. 31. See note 30, Ekstrom 1993, at 607. 32. See note 30, Ekstrom 1993, at 608–9. 33. According to social psychology research, we may also observe that people would likely attribute authenticity to Scrooge by virtue of the fact that they regard his change in character as having posi- tive valence. See note 15, Strohminger et al. g 34. Robert Noggle also appeals to the idea of “Neurathian Autonomy” in Noggle R. The public con- ception of autonomy and critical self-reflection. Southern Journal of Philosophy 1997;35(4):510. However, he appeals to this sort of idea with regards to what he terms the core attitudes that undergird agential autonomy. See Noggle R. Autonomy and the paradox of self-creation. In: Taylor JS, ed. Personal Autonomy New Essays on Personal Autonomy and Its Role in Contemporary Moral Philosophy, Cambridge: Cambridge University Press; 2005. 35. See note 30, Ekstrom 1993, at 600. 36. Doshi P, Bhargava P. Hypersexuality following subthalamic nucleus stimulation for Parkinson’s disease. Neurology India 2008;56(4):474–76. 36. Doshi P, Bhargava P. Hypersexuality follo disease. Neurology India 2008;56(4):474–76. gy 37. Voon V, Kubu C, Krack P, Houeto JL, Tröster AI. Deep brain stimulation: Neuropsychological and neuropsychiatric issues. Movement Disorders 2006;21(Suppl 14):S305–327. p y pp 38. Tan J, Hope T, Stewart A, Fitzpatrick R. Deep Brain Stimulation, Authenticity and Value Competence to make treatment decisions in anorexia nervosa: Thinking processes and values. Philosophy, Psychiatry, & Psychology 2007;13(4):267–82. 39. See note 11, Maslen et al. 2015. 40. Focquaert F, Schermer M. Moral enhancement: Do means matter morally? Neuroethics 2015;8(2): 139–51. 41. See note 11, Maslen et al. 2015. 42. See note 18, Erler, Hope 2015. 43. See note 4, Kraemer 2013. 44. Mill JS. On Liberty. New Haven: Yale University Press; 2003, at 125 45. See note 15, Strohminger et al. 46. See note 41, Mill 2003, at 131. 47. Hughes J. Beyond “Real Boys” and Back to Parental Obligations. The American Journal of Bioethics 2005;5(3):61. 48. See note 5, Nyholm, O’Neill 2015. 48. See note 5, Nyholm, O’Neill 2015. 49. See note 41, Mill 2003, at 124. 657
https://openalex.org/W1791765324
https://link.springer.com/content/pdf/10.1007/s10198-015-0722-9.pdf
English
null
Exploring a new method for deriving the monetary value of a QALY
˜The œEuropean journal of health economics
2,015
cc-by
7,597
Eur J Health Econ (2016) 17:801–809 DOI 10.1007/s10198-015-0722-9 ORIGINAL PAPER Exploring a new method for deriving the monetary value of a QALY Carl Tilling1 • Marieke Krol2,3 • Arthur E. Attema3 • Aki Tsuchiya1,4 • John Brazier1 • Job van Exel3 • Werner Brouwer3 Received: 11 December 2014 / Accepted: 5 August 2015 / Published online: 20 August 2015  The Author(s) 2015. This article is published with open access at Springerlink.com 1 School of Health and Related Research, University of Sheffield, Sheffield, UK 2 Institute for Medical Technology Assessment, Erasmus University, Rotterdam, The Netherlands 3 Department of Health Policy and Management, Erasmus University, PO Box 1738, 3000 DR Rotterdam, The Netherlands & Arthur E. Attema attema@bmg.eur.nl 4 Department of Economics, University of Sheffield, Sheffield, UK JEL Classification I10 One intriguing question regarding the use of the out- comes of economic evaluations, typically taking the form of a ratio of incremental costs per QALY gained, is when to consider a technology to offer ‘value for money’ and hence to implement or fund it. That final judgment requires some threshold against which to evaluate the cost-per- QALY ratio. Different ideas regarding the nature and meaning of this threshold, and therefore the decision making context, exist [3–5]. It can represent either the amount a society is willing to pay for a QALY from private consumption or, in a fixed budget system, the opportunity cost of a QALY from displaced health care activities [6]. This paper, however, is concerned with the former inter- pretation, i.e. the societal value of a QALY. For either interpretation, introducing the technology can be deemed 1 School of Health and Related Research, University of Sheffield, Sheffield, UK 2 Institute for Medical Technology Assessment, Erasmus University, Rotterdam, The Netherlands 3 Department of Health Policy and Management, Erasmus University, PO Box 1738, 3000 DR Rotterdam, The Netherlands 4 Department of Economics, University of Sheffield, Sheffield, UK Introduction Abstract Several studies have sought to determine the monetary value of health gains expressed as quality adjusted life years (QALYs) gained, predominantly using willingness to pay approaches. However, willingness to pay has a number of recognized problems, most notably its insensitivity to scope. This paper presents an alternative approach to estimate the monetary value of a QALY, which is based on the time trade-off method. Moreover, it presents the results of an online study conducted in the Netherlands exploring the feasibility of this novel approach. The results seem promising, but also highlight a number of methodological problems with this approach, most notably nontrading and the elicitation of negative values. Additional research is necessary to try to overcome these problems and to determine the potential of this new approach. In light of increasing health care expenditure and the limited resources available, decision makers face the challenge of determining the appropriate allocation of these resources over health programs. To help determine an appropriate distribution, economic evaluations provide information on the costs and effects of health technologies. Within economic evaluations, health effects are typically expressed in quality adjusted life years (QALYs). The QALY is an outcome measure of health benefit that com- bines length of life with quality of life. Quality of life is typically expressed on a scale from zero to one, where zero represents a health state equivalent to being dead and one represents perfect health [1]. By expressing health out- comes on a common unit of measurement, outcomes can be compared across different health programs, which is helpful for making reimbursement decisions. Several countries use these economic evaluations to inform allo- cation decisions [2]. Keywords Time trade-off method  QALY  Willingness to pay JEL Classification I10 & Arthur E. Attema attema@bmg.eur.nl 3 Department of Health Policy and Management, Erasmus University, PO Box 1738, 3000 DR Rotterdam, The Netherlands 4 Department of Economics, University of Sheffield, Sheffield, UK 12 3 3 802 C. Tilling et al. cost-effective, i.e. welfare improving [3], only if the ratio of costs per QALY remains below the value of that QALY. be considered particularly problematic in the context of health care, where the emphasis is on accessibility and equity [30]. In WTP, personal income acts as a budget constraint. The approach of WTP thus allows the wealthy to state higher values for the goods/treatments they prefer than the poor, which (depending on the use of the results) could bias health care decisions. This has led some to argue that WTP is a valid method only if we accept that the current distribution of income is appropriate [22], although Donaldson [31] has argued that one can correct and adjust WTP towards any desired distribution. p Finding the societal value of a QALY is a delicate matter and by no means easy. Recently, two large studies aimed at finding the monetary value of the QALY (MVQ) have been conducted: the UK Social Value of a QALY (SVQ) project [7] and an international study involving nine European countries (EuroVaQ, [8, 9]). Both studies expe- rienced large difficulties related to the methodological approaches chosen. Like most other studies conducted to determine MVQ [10–18], these studies used a contingent valuation (CV) method to estimate the willingness to pay (WTP) for a health improvement (either life extension or quality of life improvement). However, CV has a number of recognised problems, most notably its insensitivity to scope [19], strategic behaviour [20], protest responses [21] and the restriction of personal income [22]. In the light of these issues with WTP, it seems useful to examine ways other than common WTP studies to obtain monetary valuations of health gains. This paper presents such an alternative approach1 based on a time trade-off (TTO) exercise of income with health held constant at perfect health, which can be used to estimate the MVQ. We present the methods and theory underlying this experi- mental approach and some results from an online feasi- bility study in the Netherlands. Insensitivity to scope (or scale) arises if respondents’ WTP does not change in response to the size of the out- come being valued. Methods TTO is a widely used choice-based method of health state preference elicitation. Buckingham and Devlin [32] have outlined how the TTO method can be interpreted in the theoretical context of Hicksian utility theory and hence comply with welfare economic principles in a similar fashion to WTP derived through CV. We designed a TTO exercise in which respondents trade off length of life (in a certain health state) and income. People are thus asked to indicate their indifference between living longer (in health state X) with a lower income and living shorter (in health state X) but with a higher income. From these trade-offs, the implicit monetary value placed on a QALY can be derived. This is explained in more detail below. Besides insensitivity to scope, a concern with WTP is the opportunity for strategic behaviour, depending on the payment vehicle (free-riding) [20, 29]. This may occur in two directions. Firstly, if respondents think they will actually have to pay the amount they reveal, they may underbid. Alternatively, if respondents do not believe they will actually have to pay their stated WTP amount, but they want to influence the provision of the good in question, they might overbid. There is limited available evidence regarding strategic behaviour in WTP studies in the health care field [20]. 1 Note that a new approach may suffer from (some of) the same limitations. & Arthur E. Attema attema@bmg.eur.nl Evidence of insensitivity to scope concerns economists because it contradicts the fundamen- tal principles of neo-classical theory since ‘more is better’ consumers should be prepared to sacrifice more money to obtain more of some good (albeit at a diminishing rate). From a practical perspective, if WTP does not vary with the size of the gain, any possible MVQ could be obtained by varying the size of the gains. Although some studies found evidence against insensitivity to scope [23–25], quite a few others found evidence in support of scope insensi- tivity [19, 26–28]. Data and questionnaire Two of these TTO exercises were relevant for this study, in which health is replaced by income so the trade-off becomes between longevity and income rather than longevity and health. The second question also asks respondents the decrease in longevity that would be required to compensate for an increase in income, but the reference point differs: The wording of the first question was as follows: TTO 1: Trading years to avoid an income loss in perfect health (equivalent variation of a loss) TTO 1: Trading years to avoid an income loss in perfect health (equivalent variation of a loss) TTO2: Trading years to achieve an income gain in perfect health (compensating variation of a gain) ‘‘You can live for 10 years in perfect health with (100 - Y) % of your current annual income for each year and then die or you can live for a shorter period of time in perfect health with your current annual income for each year and then die. How many years with your current income do you consider to be equally good as living 10 years with (100 - Y) % of your current income?’’ ‘‘You can live for 10 years in perfect health with your current annual income for each year and then die or you can live for a shorter period of time in perfect health with (100 ? Y) % of your current annual income for each year and then die. How many years with (100 ? Y) % of your current income do you consider to be equally good as living 10 years with your current income?’’ ‘‘I find living... years and... months with my current income equally good as 10 years with (100 - Y) % of my current income’’. ‘‘I find living... years and... months with (100 ? Y) % of my current income equally good as 10 years with my current income’’. The indifference curves representing the trade-off are shown in Fig. 1. The x-axis represents length of life and the y-axis represents income. Each indifference curve repre- sents a level of utility that can be achieved by different combinations of longevity and income, where Referring again to Fig. 1, the first option is to stay at point b on indifference curve U1 (10 years with current annual income). Data and questionnaire Data were gathered as part of a study seeking to determine whether respondents in TTO exercises consider the effects the states might have upon their income [33, 34]. Data were gathered through an online self-complete questionnaire administered in the Netherlands. Invitations were sent out to a subset of an existing panel of potential survey respondents in order to obtain a representative sample of 300 members of the Dutch general public. Respondents between the ages of 18 and 65 only were selected as questions about income were seen as being most relevant Another issue with WTP is the incidence of protest answers. For instance, people who indicate a WTP of zero may do so for several reasons, such as that they do not know their true WTP, they actually have a zero value for the good (real zeros), or they are protesting against the exercise or payment for the good or outliers [18, 21, 29]. In a contingent valuation survey of Dalmau-Matarrodona (aimed at determining the value of day case surgery as opposed to inpatient treatment) as much as 35 % of the respondents stated a zero WTP [21]. One-third of these were classified as protest zeros. An additional problem with WTP is the influence of ability to pay. This influence may 123 123 Exploring a new method for deriving the monetary value of a QALY 803 U2 [ U1 [ U0. The first option asks the respondent to consider a move from point b on indifference curve U1 (10 years in perfect health with current income) to point a on indifference curve U0 (10 years in perfect health with less than current income). The second option involves a move from point b to point c (X years in perfect health with current income), which is again on U0. The respondent must thus specify a decrease in longevity that is equivalent to a decrease in income, both of which causing a decrease in utility from U1 to U0. for people in this age bracket. The data collection was performed by an online market research company (Survey Sampling International; http://www.surveysampling.com). Following a number of background questions including age, sex, marital status and self-assessed health by means of a visual analogue scale (VAS), respondents were pre- sented with 14 different TTO exercises (see Tilling et al. [33] for more details). Data and questionnaire Note, in TTO2 the first option is on a higher indifference curve (U1) than in TTO1 (U0), because income is set at current annual income. An increase in income (to a value greater than current income) places the individual onto a higher indifference curve U2, at point d. The respondent must then specify a decrease in long- evity that returns them to their original indifference curve at point e on U1. Fig. 1 Equivalent income loss and compensating income gain (adapted from Buckingham and Devlin [32], p 1151) In other words, respondents have to consider an equiv- alent variation for a loss in TTO1. Equivalent variation is ‘the amount of money a consumer would pay to avert a price increase’ [35]. In TTO1, the consumer is faced with a fall in income of X %, which is essentially the same as an increase in prices. They are then asked how many years of life (rather than how much money) they would pay to avoid this ‘price increase’. Similarly, TTO2 can be viewed as asking a form of compensating variation. Compensating variation is ‘the amount of additional money a consumer requires to reach his initial level of utility after a change in prices [35]. For a drop in prices, the amount of additional money compensation will be negative. TTO2 corresponds essentially to a compensating variation that identifies the number of years payable that would let the individual Fig. 1 Equivalent income loss and compensating income gain (adapted from Buckingham and Devlin [32], p 1151) Fig. 1 Equivalent income loss and compensating income gain (adapted from Buckingham and Devlin [32], p 1151) 12 3 804 C. Tilling et al. maintain the initial level of utility after a drop in prices, or increase in income. Essentially these questions can be interpreted as a WTP and a WTA question, respectively. However, while standard WTP (WTA) questions ask peo- ple to trade money for an improvement (deterioration) in length of life or health, these questions asked people to trade length of life for an improvement in income. Respondents were thus paying in years of life. health and income. Relaxing this assumption would require us to estimate an indifference curve across a range of values, which is beyond the scope of this first empirical exploration of the method. Data and questionnaire The compensating gain data from TTO2 is analysed in a similar fashion to the equivalent loss data in TTO1. Con- sider a respondent who is indifferent between 10 years with their current income and 9 years with 120 % of their cur- rent income. Their income is, once again, €100,000 per year: Three income change levels (Y) were used: in version 1 of the questionnaire 20 % was used, in version 2 40 % and in version 3, 60 %. Respondents were randomised to one of the three income change levels, which they then received in both TTO1 and TTO2. Since the survey was administered in an online self-complete fashion there was no iterative process. Respondents were simply asked to state how many years with higher income, was equivalent to 10 years with lower income. All respondents first received TTO1, fol- lowed by TTO2. 10U PH ð Þ þ ¤1;000;000 ¼ 9U PH ð Þ þ ¤1;080;000 ð5Þ 10U PH ð Þ 9U PH ð Þ ¼ ¤1;080;000  ¤1;000;000 ð6Þ U PH ð Þ ¼ ¤80;000 ð7Þ 10U PH ð Þ þ ¤1;000;000 ¼ 9U PH ð Þ þ ¤1;080;000 ð5Þ 10U PH ð Þ 9U PH ð Þ ¼ ¤1;080;000  ¤1;000;000 ð6Þ U PH ð Þ ¼ ¤80;000 ð7Þ Analysis of responses Our responses can be interpreted and analysed only after assuming the form of the utility function of respondents over health and income. In the current paper, given its explorative nature, we assume a simple additive function W(.) over health (H) and income (Y): W H; Y ð Þ ¼ U H ð Þ þ Y ð1Þ ð1Þ W H; Y ð Þ ¼ U H ð Þ þ Y That is, individuals derive utility (U) from their health state H and have a linear utility function over income. This specification was used earlier by Eeckhoudt et al. [36]. The advantage of this function is that it becomes straightfor- ward to elicit a monetary value of the utility of perfect health. Moreover, an additive way of thinking when answering this task is cognitively less demanding and appears more plausible than a multiplicative way of thinking. Respondent income In order to determine the level of ‘‘current annual income’’ for each respondent, respondents were asked to choose the income bracket within which their monthly income fell within the background characteristics questions. For our analysis, these income brackets were converted into numerical values using the mid-point of each bracket [37]. For respondents in the lowest income bracket, an income of two-thirds of the upper limit of the bracket was used. For respondents in the highest income bracket, an income of 1.5 of the lower income limit of the bracket was assumed [37]. Results Data were available from 321 members of the Dutch general public. After exclusion of 80 ‘extreme non-traders’ the relevant sample size fell to 241. The sample consisted of slightly more males than females, and 41.5 % of the sample was not employed. Just under one-half of the sample had children, and less than one-half of the sample was married. The mean VAS score for own health was 0.75. The results of v2 tests showed that background characteristics did not differ significantly across the three versions of the questionnaire. Only employment differed slightly across the versions, with a smaller proportion of respondents in version 2 being in employment than in the other two versions. Regardless of whether non-trades are protest responses or a true reflection of lexicographic preferences, if an individual calculation method (i.e. calculate an MVQ for each individual and then compute the mean) is to be used, then non-traders must be excluded, because their answers would imply an infinite MVQ [38]. Therefore, we excluded all ‘extreme non-traders’ (i.e. respondents who did not trade across all 14 TTO questions of the ques- tionnaire). An alternative is to use an aggregate approach, where we divide the sum of the income differences by the sum of the life time reductions (‘ratio of means’) [38]. This can be compared to the disaggregate approach (‘mean of ratios’), where one divides the income differ- ence by the reduction of life time for each respondent. These approaches are likely to generate different results, especially because we have a lot of non-traders, who could be included in the aggregate approach but not in the disaggregate approach. The results from both approaches are presented. Even after excluding the ‘extreme non-traders’, a sub- stantial number of the respondents did not trade time in the compensating gain and/or equivalent loss questions. The proportion of non-traders in the equivalent loss questions decreased as the level of loss increased: 72 % were non- traders for 20 % loss, 54 % for 40 % loss and 45 % for 60 % loss. In the compensating gain questions the pro- portion of non-traders was fairly constant across the three income gain levels: 63 %, 65 % and 64 % were non-tra- ders for 20 %, 40 % and 60 % gain, respectively. Trading off life duration for income increases hence invokes a large degree of non-trading. Non-traders Some respondents did not trade any time in any of the TTO exercises. For these respondents, calculating an MVQ becomes problematic because the left hand side of Eq. (2) becomes 0, meaning that the equation would give an indeterminate value. If such responses occur and are a protest against the exercise, this poses questions about the feasibility of the exercise. If such responses are a mean- ingful statement of preference for a seemingly infinite preference for life over income then this does not mean the exercises are infeasible, but rather that the calculation method above is not capable of calculating a finite MVQ for such individuals based on these meaningful responses. A respondent with lexicographic preferences of this nature would not give up any length of life to increase their income. In the context of the equivalent variation for a loss question, the decrease in income facing the respondent (from current income to less than current income) does not decrease their utility; therefore, they stay on their initial indifference curve, implying their equivalent loss in long- evity is zero, because otherwise their utility would drop below this level. To see how the results from these questions can be used to derive an MVQ, imagine that a respondent facing TTO1 states that 9 years with normal annual income of €100,000 is equivalent to 10 years with 80 % of this income, so €80,000. Using prospective lifetime income values and assuming a zero discount rate, this point of indifference gives us the following information: 10U PH ð Þ þ ¤800;000 ¼ 9U PH ð Þ þ ¤900;000 ð2Þ 10U PH ð Þ 9U PH ð Þ ¼ ¤900;000  ¤800;000 ð3Þ U PH ð Þ ¼ ¤100;000 ð4Þ 10U PH ð Þ þ ¤800;000 ¼ 9U PH ð Þ þ ¤900;000 ð2Þ 10U PH ð Þ 9U PH ð Þ ¼ ¤900;000  ¤800;000 ð3Þ U PH ð Þ ¼ ¤100;000 ð4Þ ð4Þ where PH is perfect health. Results Table 1 shows the mean number of years respondents were willing to trade, in both the compensating gain and equivalent loss questions. Looking at the values including the non-traders, for two of the income change levels, respondents were willing to trade more years to avoid an income loss than they were to achieve an income gain. However, these differences were significant only for the 60 % income change level (at the 1 % level). The median values were 0 in all but one case, which was a product of the large numbers of non-traders. Mann–Whitney rank-sum tests were performed to compare the values for the dif- ferent income levels, both for equivalent loss and com- pensating gain values. Number of years traded was significantly different between 20 % and 40 % equivalent loss (5 % level) and between 20 % and 60 % equivalent loss (1 % level). For the equivalent loss questions the standard deviations generally increased as the level of loss increased, while no clear relationship was observed for the gain questions. Non-traders In reality, it is likely that the utility from a year in perfect health will be higher when combined with a higher amount of income, whereas we assume a constant marginal rate of substitution between 123 805 Exploring a new method for deriving the monetary value of a QALY It should be noted that non-trading in the equivalent variation for a loss or compensating variation for a gain question does not necessarily mean that the indifference curve is perfectly vertical; it just means that the curve is sufficiently steep that the utility gained from the increase in income is less than the amount of utility that would be lost through giving up the smallest amount of longevity pos- sible (the smallest unit of trade was 1 month). Furthermore, non-trading for a given income change level does not mean that the entire indifference curve is vertical (or sufficiently steep), it only determines the slope of the indifference curve between the two income points on the y axis that the respondent is being questioned on. Negative values Version 1: 20 % (n = 78) Version 2: 40 % (n = 80) Version 3: 60 % (n = 83) Loss Gain Loss Gain Loss Gain Number of years traded to either avoid an income loss or achieve an income gain Mean 0.99 1.47 1.81** 1.33 2.45 1.51*** SD 2.23 2.96 2.74 2.63 3.28 2.89 Median 0 0 0 0 1 0 ** Significant at 5 % level, *** significant at 1 % level Table 1 Number of years traded ** Significant at 5 % level, *** significant at 1 % level Table 2 Monetary value of the QALY (MVQ) values calculated at the individual level (excluding non-traders) V i 1 20 % V i 2 40 % V i 3 60 % ALY (MVQ) values calculated at the individual level (excluding non-traders) Table 2 Monetary value of the QALY (MVQ) values calculated at the individual level (excluding non-traders) Version 1: 20 % Version 2: 40 % Version 3: 60 % Loss Gain Loss Gain Loss Gain Number of respondents 22 29 37 28 46 30 Mean number of years traded 3.5 3.95 3.91 3.81 4.43 4.17 Mean annual income (€) 15,042 16,375 14,834 15,675 21,041 18,630 Number of negative responses (truncated to zero) 11 17 16 14 13 14 Value of a QALY (€) Mean 17,439 42,212 43,564 65,957 56,827 48,846 SD 44,561 166,650 13,8097 193,760 126,109 108,570 Median 0 0 0 1020 8673 10,994 Table 2 Monetary value of the QALY (MVQ) values calculated at the individual level (excluding non-traders) for the analysis) for the compensating gain questions than for the equivalent loss questions. In general, the mean MVQ values increased as the level of income change increased, 60 % income gain being the only exception. The monetary values for a QALY were higher for the gain questions than the loss questions, except in the case of the 60 % income change level. The mean values were con- sistently higher than the median values, implying that the data were skewed. In half of the cases the median was 0, caused by the large number of respondents who traded enough years to generate a negative MVQ value, which was then truncated to zero. As shown in Table 4, we tested whether weighted mean monetary valuesfor a QALY for both the disaggregate and the aggregate approach differed between respondents in different income brackets. Negative values One further problem of our approach is the potential gen- eration of negative MVQ values. For TTO1, if the per- centage of life years the respondent is prepared to give up is larger than the percentage income loss they are faced with, their MVQ will be negative. For example, if a respondent is faced with 20 % income loss and is willing to trade more than 2 years of life to avert this, her MVQ value will be negative (while if she trades exactly 2 years, her MVQ value will be zero). In other words, for the 20 % loss respondents, trading more than 2 years leads to a negative MVQ; for the 40 % (60 %) loss respondents, this holds for trades of more than 4(6) years. For TTO2 the relationship is not linear. For a 20 % (40 %, 60 %) gain in income, trades of more than 1.67 (2.86,3.75) years result in negative values. In the disaggregate approach, we truncated negative MVQ values at 0. In the aggregate approach we left the number of years traded unchanged. Table 2 shows the MVQ estimates calculated according to the disaggregate approach. As described, this approach excludes all non-traders, resulting in a much smaller sample for analysis. The mean MVQ values ranged from €17,439 to €65,957. A larger proportion of respondents gave negative MVQ values (which were truncated to zero 12 3 806 C. Tilling et al. Negative values We found no clear relationship between respondents’ income and mean QALY values. For the dis- aggregate approach, values were broadly similar across income levels, suggesting that the MVQ values generated by our method were not a function of respondent income. Exploring a new method for deriving the monetary value of a QALY It is also likely that respondents may not have been able to calculate exactly at which point their lifetime income in one prospect became lower than that in the other prospect. In that sense, applying this method in an interview elici- tation procedure, potentially using visual aids and provid- ing feedback to respondents whose answers imply negative WTP, could support the decision-making process of respondents. This may reduce the number of respondents trading ‘too many years’, yielding negative valuations, but not being aware of this implication. Since respondents are forced to consider giving up years of life from a finite 10-year survival, one could claim that the method introduced here forces respondents to trade-off income and health in a very direct way. Furthermore, the method makes strategic behaviour difficult as it is not obvious to the respondent how the results from the exercise will be used, although the results from this feasibility study do not allow us to specifically test this. Amongst the sample analysed (excluding 80 ‘extreme non-traders’), 60 % of responses in the equivalent loss and compensating gain questions were non-trades. This is considerably higher than the 35 % found in the study by Dalmau-Matarrodona [21] in the context of a WTP exercise. We have no means of determining what pro- portion of these trades revealed true lexicographic pref- erences and what proportion were protest responses. The high proportion of non-trades may also be related to the use of an online survey. Van Nooten et al. [39] found that numerous respondents opted not to trade in con- ventional TTO exercises in their online questionnaire. It may well be that trading off life time for income is considered in some way ‘unethical’ by respondents or a trade-off they are even less willing to make than trading off length and quality of life. This requires further investigation. The use of discrete choice experiments to elicit WTP could be a fruitful direction for future research in this respect. In this study respondents were told to imagine being in perfect health in both scenarios. In future work it may be preferable to tell respondents they would be in their own current state of health. Their current health could then be valued through either conventional TTO or VAS and the income changes obtained could be divided by the value of the respondents’ current health to give MVQ values. Exploring a new method for deriving the monetary value of a QALY 807 Table 4 Weighted mean QALY values for different income brackets Respondent income level (€) Weighted mean QALY value Disaggregate approach Less than 12,000 45,837 12,000–17,999 39,097 18,000–23,999 66,060 [24,000 43,240 Aggregate approach Less than 12,000 10,401 12,000–17,999 41,770 18,000–23,999 30,986 [24,000 30,137 Respondent income level (€) Weighted mean QALY value Generally, respondents in our new method gave up more years when faced with a larger income change level rather than a smaller income change, suggesting some sensitivity to scope. However, these differences were not always significant and never significant without the ‘non-traders’, due to the small numbers in the sample. Surprisingly, we did not find a clear relation between respondent income and MVQ. Maybe this is related to the relatively small sample size of our explorative study. Studies with larger sample sizes may be able to provide more insight into the rela- tionship between income and MVQ values generated with this new approach. Moreover, larger sample size would allow further investigation of sensitivity to scope in the TTO method in this context. A serious problem with the TTO-based approach, and one not encountered when using WTP, is the elicitation of negative MVQ values. It is not easy for respondents to see that they are making choices that imply negative valuation of health, which they may not support if they were shown the implication. This is where the proportion of health traded off exceeds that of the income change. However, in reality, it is plausible that individuals may wish to live for a shorter period of time with higher income than for a longer period of time with lower income, even though their total lifetime income may be lower. For instance, they may feel that the lower income is not enough to be able to sustain themselves and their significant others, so that they would rather live for a shorter time and with a lower total, but higher monthly, income. This also relates to the shape of the utility function assumed here. The additive, linear utility function may not adequately describe people’s actual preferences. In addition, the zero discounting assumption we used here may not hold. If respondents instead discount future income very steeply, a short lifes- pan with high yearly income will give more discounted utility than a long lifespan with a lower yearly income. Discussion and conclusions The aim of this study was not to present a definitive MVQ for the Netherlands, but rather to test the feasibility of an alternative method of eliciting an MVQ. The results from the small-scale online study suggest that the compensating gain and equivalent loss TTO exercises have potential, but a number of problems must be overcome before its use can be advocated more widely for purposes other than research. Table 3 shows the MVQ values calculated using aggregate values. The estimates ranged from €2805 to €49,437. Similar to the individual approach, the mean MVQ values increased as the level of income change increased. Except in the case of the 20 % income change level, the MVQ was higher for the gain questions than for the loss questions. Version 1: 20 % Version 2: 40 % Version 3: 60 % Loss Gain Loss Gain Loss Gain Number of respondents 78 78 80 80 83 83 Mean number of years traded 0.99 1.47 1.81 1.33 2.45 1.51 Mean annual income (€) 17,471 17,471 15,771 15,771 20,829 20,829 Value of a QALY (€) 17,824 2805 19,082 25,353 30,181 49,437 Table 3 MVQ values calculated at the aggregate level 12 123 Exploring a new method for deriving the monetary value of a QALY References Finally, because there is evidence of a lack of the con- stant proportional trade-off, the willingness to trade years (and thus the trade-off between income and length of life) may depend on the baseline length of life [42, 43]. More- over, answers to TTO questions may depend on real remaining life expectancy, which in turn depends on income. For this reason, it has been suggested to use real remaining life expectancy in TTO exercises as opposed to an arbitrary number of years of life (10 years in this study), at least for subjects where real life expectancy diverges from preset life expectancy [39, 44]. Future research may investigate this possibility further. 1. Weinstein, M.C., Stason, W.B.: Foundations of cost-effectiveness analysis for health and medical practices. N. Engl. J. Med. 296, 716–721 (1977) 2. NICE: Guide to the methods of technology appraisal. http://www. nice.org.uk/aboutnice/howwework/devnicetech/technologyapprai salprocessguides/guidetothemethodsoftechnologyappraisal.jsp (2008). Accessed 20 February 2014 3. Gravelle, H., Brouwer, W., Niessen, L., Postma, M., Rutten, F.: Discounting in economic evaluations: stepping forward towards optimal decision rules. Health Econ. 16(3), 307–317 (2007) 4. Claxton, K., Paulden, M., Gravelle, H., Brouwer, W., Culyer, A.J.: Discounting and decision making in the economic evalua- tion of health-care technologies. Health Econ. 20, 2–15 (2011) 5. Culyer, A., McCabe, C., Briggs, A., Claxton, K., Buxton, M., Akehurst, R., Sculpher, M., Brazier, J.: Searching for a threshold, not setting one: the role of the National Institute for Health and Clinical Excellence. J. Health Serv. Res. Policy 12, 56–58 (2007) At this moment, the aggregate approach seems to be preferred over the disaggregate approach. Even though it may include some responses of individuals who strategi- cally did not trade, the alternative (the disaggregate approach) left a small number of ‘trading’ respondents after excluding non-traders and truncating negative values to zero. The aggregate approach represents a movement away from standard welfare economics (societal welfare as the sum of individual welfare), but might be considered acceptable in an extra-welfarist framework, although fur- ther discussion remains warranted. Further research using face-to-face interviews is needed to try to determine whe- ther the non-trades are strategic or true indicators of pref- erence, and hence whether the calculation method needs to be able to accommodate them. 6. Exploring a new method for deriving the monetary value of a QALY This may reduce the number of hypothetical aspects and hence make the task more manageable for respondents who are 12 3 3 123 C. Tilling et al. 808 currently not in full health. However, this approach would entail further dependence upon the assumption of no interactions between health and income. This assumption, one of the impossibility theorem criteria set out by Dolan and Edlin [40], is not avoided in this study. The MVQ value elicited is determined essentially by the choice of income change level. A large-scale study would make it possible to obtain values for enough income change levels to estimate an indifference curve between health and income. MVQ values across a range of income change levels could then be estimated. If it is found that the utility of health depends on income and vice versa, this would suggest that an additive utility function is not descriptively valid. In that case, a multiplicative utility function over health and income would be a logical alternative [41]. feasible for respondents to answer. Still, the empirical exploration highlighted numerous important issues with the method, most notably the elicitation of ‘non-trades’ and negative values. Future research could address these issues, also looking at the shape of the utility function over income and health. An interview-based study that requires respondents to engage in an iterative process, and that can be supplemented by a visual aid, is required to determine whether this approach is valid and should be taken forward, also as an alternative for WTP valuations. Acknowledgments We would like to thank Jan van Busschbach, Paul McNamee, Phil Shackley and Richard Edlin who provided helpful feedback and comments on earlier versions of this paper. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://crea tivecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Another limitation of this study is that we used large income losses, which may be perceived to be unrealistic. Hence, future research may attempt to use more realistic scenarios in order to reduce the hypothetical nature of the data. However, care should be taken that the use of smaller losses does not result in differences becoming too small to be meaningful for the respondents. 123 References Abelson, P.: The value of life and health for public policy. Econ. Rec. 79, S2–S13 (2003) 30. Brouwer, W.B.F., Culyer, A.J., van Exel, N.J.A., Rutten, F.F.H.: Welfarism vs. extra-welfarism. J. Health Econ. 27, 325–338 (2008) 14. Johannesson, M., Meltzer, D.: Editorial: some reflections on cost- effectiveness analysis. Health Econ. 7, 1–7 (1998) 15. Gyrd-Hansen, D.: Willingness to pay for a QALY. Health Econ. 12, 1049–1060 (2003) 31. Donaldson, C.: Valuing the benefits of publicly-provided health care: does ‘ability to pay’ preclude the use of ‘willingness to pay’? Soc. Sci. Med. 49, 551–563 (1999) 16. Hirth, R.A., Chernew, M.E., Miller, E., Fendrick, A.M., Weissert, W.G.: Willingness to pay for a quality-adjusted life year. in search of a standard. Med. Decis. Mak. 20, 332–342 (2000) 32. Buckingham, K., Devlin, N.: A theoretical framework for TTO valuations of health. Health Econ. 15, 1149–1154 (2006) 17. Johannesson, M., Johansson, P.: Is the valuation of a QALY gained independent of age? Some empirical evidence. J. Health Econ. 16, 589–599 (1997) 33. Tilling, C., Krol, M., Tsuchiya, A., Brazier, J., van Exel, J., Brouwer, W.: Does the EQ-5D reflect lost earnings? Pharma- coeconomics 30, 47–61 (2012) 18. Helvoort-Postulart, D., Dirksen, C., Kessels, A., Engelshoven, J., Hunink, M.M.: A comparison between willingness to pay and willingness to give up time. Eur. J. Health Econ. 10, 81–91 (2009) 34. Tilling, C., Devlin, N., Tsuchiya, A., Buckingham, K.: Protocols for time tradeoff valuations of health states worse than dead: a literature review. Med. Decis. Mak. 30, 610–619 (2010) 35. Hicks, J.R.: Value and capital: an enquiry into some fundamental principles of economic theory. Clarendon, Oxford (1939) 19. Olsen, J.A., Donaldson, C., Pereira, J.: The insensitivity of willingness-to-pay to the size of the good: new evidence for health care. J. Econ. Psychol. 25, 445–460 (2004) 36. Eeckhoudt, L., Godfroid, P., Marchand, M.: Risque de sante´, me´decine pre´ventive et me´decine curative. Rev. d’Econ. Poli- tique 108, 321–337 (1998) 20. Hackl, F., Pruckner, G.J.: Warm glow, free-riding and vehicle neutrality in a health-related contingent valuation study. Health Econ. 14, 293–306 (2005) 37. Layard, R., Mayraz, G., Nickell, S.: The marginal utility of income. J. Public Econ. 92, 1846–1857 (2008) 21. Dalmau-Matarrodona, E.: Alternative approaches to obtain opti- mal bid values in contingent valuation studies and to model protest zeros. Estimating the determinants of individuals will- ingness to pay for home care services in day case surgery. Health Econ. 10, 101–118 (2001) 38. References Baker, R., Chilton, S., Donaldson, C., Jones-Lee, M., Lancsar, E., Mason, H., Metcalf, H., Pennington, M., Wildman, J.: Searchers vs surveyors in estimating the monetary value of a QALY: resolving a nasty dilemma for NICE. Health Econ. Policy Law 6, 435–447 (2011) 7. Donaldson, C., Baker, R., Mason, H., Jones-Lee, M.W., Lancsar, E., Wildman, J., Bateman, I., Loomes, G.C., Robinson, A., Sugden, R., Pinto Prades, J.L., Ryan, M., Shackley, P., Smith, R.: The social value of a QALY : raising the bar or barring the raise?. BMC Health Serv. Res. Vol. 11, arte no. 8 (2011) 8. Pennington, M., Baker, R., Brouwer, W., Mason, H., Hansen, D.G., Robinson, A., Donaldson, C., the EuroVaQ Team: Com- paring wtp values of different types of Qaly gain elicited from the general public. Health Econ. 24, 280–289 (2015) 9. Robinson, A., Gyrd-Hansen, D., Bacon, P., Baker, R., Penning- ton, M., Donaldson, C.: Estimating a WTP-based value of a QALY: the ‘chained’ approach. Soc. Sci. Med. 92, 92–104 (2013) In summary, the search for the monetary value of QALYs is ongoing, yet remains problematic. Here, we presented an alternative method for the elicitation of MVQ based on the TTO and a first empirical test found it to be 10. Bobinac, A., van Exel, N.J.A., Rutten, F.F.H., Brouwer, W.B.F.: Willingness to pay for a quality-adjusted life-year: the individual perspective. Value Health 13, 1046–1055 (2010) 123 123 Exploring a new method for deriving the monetary value of a QALY 809 27. Jones-Lee, M.W., Loomes, G.C., Philips, P.R.: Valuing the pre- vention of non-fatal road injuries: contingent valuation vs. stan- dard gambles. Oxf. Econ. Pap. 47, 676–695 (1995) 11. Bobinac, A., van Exel, J., Rutten, F.F.H., Brouwer, W.B.F.: Get more, pay more? An elaborate test of construct validity of will- ingness to pay per QALY estimates obtained through contingent valuation. J. Health Econ. 31, 158–168 (2012) 28. Smith, V.K., Desvousges, W.H.: An empirical analysis of the economic value of risk changes. J. Polit. Econ. 95, 89–114 (1987) 12. Johnson, F.R., Desvousges, W.H., Ruby, M.C., Stieb, D., De Civita, P.: Eliciting stated health preferences: an application to willingness to pay for longevity. Med. Decis. Mak. 18, S57–S67 (1998) 29. Fonta, W., Ichoku, H.E., Kabubo-Mariara, J.: The effect of pro- test zeros on estimates of willingness to pay in healthcare con- tingent valuation analysis. Appl. Health Econ. Health Policy 8, 225–237 (2010) 13. References Gyrd-Hansen, D., Kjær, T.: Disentangling WTP per QALY data: different analytical approaches, different answers. Health Econ. 21, 222–237 (2012) 39. van Nooten, F.E., Koolman, X., Brouwer, W.B.F.: The influence of subjective life expectancy on health state valuations using a 10 year TTO. Health Econ. 18, 549–558 (2009) 22. O’Brien, B., Drummond, M.: Statistical versus quantitative sig- nificance in the socioeconomic evaluation of medicines. Phar- macoeconomics 5, 389–398 (1994) 40. Dolan, P., Edlin, R.: Is it really possible to build a bridge between cost-benefit analysis and cost-effectiveness analysis? J. Health Econ. 21, 827–843 (2002) 23. Kartman, B., Andersson, F., Johannesson, M.: Willingness to pay for reductions in angina pectoris attacks. Med. Decis. Mak. 16, 248–253 (1996) 41. Levy, M., Nir, A.R.: The utility of health and wealth. J. Health Econ. 31, 379–392 (2012) 24. Kartman, B., Sta˚lhammar, N., Johannesson, M.: Valuation of health changes with the contingent valuation method: a test of scope and question order effects. Health Econ. 5, 531–541 (1996) 24. Kartman, B., Sta˚lhammar, N., Johannesson, M.: Valuation of health changes with the contingent valuation method: a test of scope and question order effects. Health Econ. 5, 531–541 (1996) 25. O’Conor, R.M., Johannesson, M., Hass, S.L., Kobelt-Nguyen, G.: Urge incontinence Pharmacoeconomics 14 531 539 (1998) 42. Attema, A.E., Brouwer, W.B.F.: On the (not so) constant pro- portional tradeoff in TTO. Qual. Life Res. 19, 489–497 (2010) 43. Bleichrodt, H., Pinto, J.L., Abella´n-Perpina´n, J.M.: A consistency test of the time trade-off. J. Health Econ. 22, 1037–1052 (2003) 25. O’Conor, R.M., Johannesson, M., Hass, S.L., Kobelt-Nguyen, G.: Urge incontinence. Pharmacoeconomics 14, 531–539 (1998) 44. Heintz, E., Krol, M., Levin, L.A.: The impact of patients sub- jective life expectancy on time trade-off valuations. Med. Decis. Mak. 33, 261–270 (2013) 26. Chestnut, L.G., Keller, L.R., Lambert, W.E., Rowe, R.D.: Mea- suring heart patients willingness to pay for changes in angina symptoms. Med. Decis. Mak. 16, 65–76 (1996) 123 123 12
https://openalex.org/W4391090740
https://www.medrxiv.org/content/medrxiv/early/2024/01/22/2024.01.21.24301506.full.pdf
English
null
DODGE: Automated point source bacterial outbreak detection using cumulative long term genomic surveillance
medRxiv (Cold Spring Harbor Laboratory)
2,024
cc-by
6,028
. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: edRxiv preprint DODGE: Automated point source bacterial outbreak detection using cumulative long term genomic surveillance. reprint reports new research that has not been certified by peer review and should not be used to guide clinical practice DODGE: Automated point source bacterial outbreak detection using cumulative long term genomic surveillance. DODGE: Automated point source bacterial outbreak detection using cumulative long term genomic surveillance. Michael Payne1, Dalong Hu1, Qinning Wang2, Geraldine Sullivan2, Rikki M Graham3, Irani U Rathnayake3, Amy V Jennison3, Vitali Sintchenko2,4, Ruiting Lan1,# Michael Payne1, Dalong Hu1, Qinning Wang2, Geraldine Sullivan2, Rikki M Graham3, Irani U Rathnayake3, Amy V Jennison3, Vitali Sintchenko2,4, Ruiting Lan1,# 1 School of Biotechnology and Biomolecular Sciences, University of New South Wales, New South Wales, Australia 2 Centre for Infectious Diseases and Microbiology - Public Health, Institute of Clinical Pathology and Medical Research - NSW Health Pathology, Westmead Hospital, New South Wales, Australia 3 Public Health Microbiology, Queensland Health Forensic and Scientific Services, Coopers Plains, Brisbane, Australia 2 Centre for Infectious Diseases and Microbiology - Public Health, Institute of Clinical Pathology and Medical Research - NSW Health Pathology, Westmead Hospital, New South Wales, Australia 3 Public Health Microbiology, Queensland Health Forensic and Scientific Services, Coopers Plains, Brisbane, Australia 4 Sydney Institute for Infectious Diseases, Sydney Medical School, University of Sydney, New South Wales, Australia 4 Sydney Institute for Infectious Diseases, Sydney Medical School, University of Sydney, New South Wales, Australia #correspondance: r.lan@unsw.edu.au . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: edRxiv preprint Abstract (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: edRxiv preprint Abstract Summary: The reliable and timely recognition of outbreaks is a key component of public health surveillance for foodborne diseases. Whole genome sequencing (WGS) offers high resolution typing of foodborne bacterial pathogens and facilitates the accurate detection of outbreaks. This detection relies on grouping WGS data into clusters at an appropriate genetic threshold, however, methods and tools for selecting and adjusting such thresholds according to the required resolution of surveillance and epidemiological context are lacking. Here we present DODGE (Dynamic Outbreak Detection for Genomic Epidemiology), an algorithm to dynamically select and compare these genetic thresholds. DODGE can analyse expanding datasets over time and clusters that are predicted to correspond to outbreaks (or ‘investigation clusters’) can be named with the established genomic nomenclature systems to facilitate integrated analysis across jurisdictions. DODGE was tested in two real-world genomic surveillance datasets of different duration, two months from Australia and nine years from the UK. In both cases only a minority of isolates were identified as investigation clusters. Two known outbreaks in the UK dataset were detected by DODGE and were recognised at an earlier timepoint than the outbreaks were reported. These findings demonstrated the potential of the DODGE approach to improve the effectiveness and timeliness of genomic surveillance for foodborne diseases and the effectiveness of the algorithm developed. Two known outbreaks in the UK dataset were detected by DODGE and were recognised at an earlier timepoint than the outbreaks were reported. These findings demonstrated the potential of the DODGE approach to improve the effectiveness and timeliness of genomic surveillance for foodborne diseases and the effectiveness of the algorithm developed. Availability and implementation: DODGE is freely available at Availability and implementation: DODGE is freely available at https://github.com/LanLab/dodge and can easily be installed using Conda. https://github.com/LanLab/dodge and can easily be installed using Conda. Supplementary information: Supplementary Tables, Results, Figure 1 and Figure 2 Supplementary information: Supplementary Tables, Results, Figure 1 and Figure 2 . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Introduction Foodborne pathogens are a major cause of morbidity globally with 550 million infections reported in 2010 (Kirk et al. 2015). Salmonella enterica is a common cause of these infections with 78 million cases per year with the two most common serovars being S. Typhimurium (STM) and S. Enteritidis (Hendriksen et al. 2011, Kirk et al. 2015). Once they reach the human population from agricultural and environmental reservoirs the control of these pathogens depends on the identification and elimination of outbreaks. Outbreaks are mostly caused by single strains that contaminate food and lead to many cases of disease over a short time span. The identification of an outbreak has therefore relied on identifying strains that share the same genetic or phenotypic makeup and have occurred over a short temporal window (Sabat et al. 2013). Whole genome sequencing (WGS) has offered new capacity to identify related clinical and food isolates at high resolution. Previous studies have demonstrated that isolates within an outbreak examined using WGS are often not genetically identical but are very closely related (Octavia et al. 2015). Therefore, there is a need to group isolates together using a genetic distance threshold. A single static genetic threshold is unlikely to be universally applicable due to differences in genetic diversity across bacterial populations and differences in the transmission pathways within the outbreak (Bekal et al. 2016, Gymoese et al. 2017, Leekitcharoenphon et al. 2014, Octavia et al. 2015, Phillips et al. 2016). We previously demonstrated the utility of a variable genetic threshold that depended on the local diversity of isolates over time and provided optimal sensitivity and specificity for outbreak detection (Payne et al. 2019). Whole genome sequencing (WGS) has offered new capacity to identify related clinical and food isolates at high resolution. Previous studies have demonstrated that isolates within an outbreak examined using WGS are often not genetically identical but are very closely related (Octavia et al. 2015). Therefore, there is a need to group isolates together using a genetic distance threshold. A single static genetic threshold is unlikely to be universally applicable due to differences in genetic diversity across bacterial populations and differences in the transmission pathways within the outbreak (Bekal et al. 2016, Gymoese et al. 2017, Leekitcharoenphon et al. 2014, Octavia et al. 2015, Phillips et al. 2016). DODGE inputs DODGE is primarily designed for use with cgMLST allele profiles and can accept this data directly downloaded from MGTdb or Enterobase (Kaur et al. 2022, Payne et al. 2020, Zhou et al. 2020). Temporal and nomenclature data (MGT STs or hierCC clusters) were extracted from metadata files that can be obtained from the corresponding databases. To facilitate ad hoc analyses using DODGE, SNP based inputs can also be used. Inputs using SNP analysis are vcf files and masked genomes produced by the program snippy (Seemann 2015). Introduction The method was tested on two STM genomic datasets, genome sequences from all STM isolates from a two-month period from two Australian states and over 9 years from the United Kingdom. Introduction We previously demonstrated the utility of a variable genetic threshold that depended on the local diversity of isolates over time and provided optimal sensitivity and specificity for outbreak detection (Payne et al. 2019). Therefore, there is a need for a method and software tool that can identify an outbreak using thresholds determined dynamically based on the population and evolutionary dynamics of the . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: edRxiv preprint pathogen. Public health genomic surveillance has become routine in many countries therefore any software solution must also be capable of identifying and tracking outbreaks over time in continuously expanding datasets. pathogen. Public health genomic surveillance has become routine in many countries therefore any software solution must also be capable of identifying and tracking outbreaks over time in continuously expanding datasets. In this study we present DODGE (Dynamic Outbreak Detection for Genomic Epidemiology), a method and tool to identify outbreaks with dynamic genetic thresholds selected using temporal thresholds that can accommodate expanding datasets from ongoing surveillance (software available from https://github.com/LanLab/dodge). This method utilises retrospective genomic surveillance data to define a background dataset which is then used to identify distinct, new clusters that subsequently appear. The method was tested on two STM genomic datasets, genome sequences from all STM isolates from a two-month period from two Australian states and over 9 years from the United Kingdom. In this study we present DODGE (Dynamic Outbreak Detection for Genomic Epidemiology), a method and tool to identify outbreaks with dynamic genetic thresholds selected using temporal thresholds that can accommodate expanding datasets from ongoing surveillance (software available from https://github.com/LanLab/dodge). This method utilises retrospective genomic surveillance data to define a background dataset which is then used to identify distinct, new clusters that subsequently appear. DODGE algorithm In order to identify genetic clusters of bacteria that are likely to correspond to point source outbreaks DODGE uses a temporal threshold to dynamically select the best genetic threshold for each cluster independently. The stages of the DODGE algorithm are as follows (Figure . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: edRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint 1A and B). Firstly, calculate pairwise distances between all isolates and perform single linkage clustering, clusters at each allowed thresholds are saved. Secondly, identify all genetic clusters at the maximum single linkage distance allowed (e.g., 5). For each cluster, if it is above the minimum size (e.g., 5 strains) check for the timespan of the collection times of isolates within the cluster. For clusters with timespans greater than the temporal threshold (e.g., 28 days) reduce the genetic threshold by one and check temporal threshold again. This is repeated until the timespan of the cluster is below the temporal threshold. This cluster is then stored as an investigation cluster which denotes a cluster that may warrant further examination using more detailed traditional epidemiological analysis. The minimum genetic threshold that retains the initial investigation cluster size is selected (e.g., if a cluster with threshold of 3 and 2 are identical threshold of 2 will be retained). For the temporal window to be effective in selecting genetic thresholds a set of background isolate data should also be included. This background dataset is composed of isolates collected before the start date of the main investigation and is processed by DODGE to identify existing genetic clusters without calling any for investigation. Any cluster that originated in this time period is treated as background and will not be reported. To track investigation clusters over time, each cluster is named based on the genomic identities of its constituent isolates and the genetic threshold used to identify it. The same process is used for hierCC progressing from larger to smaller threshold hierCC clusters. Because SNP based analyses have no standardised nomenclature, numerical investigation cluster names are assigned per analysis. The second part of the investigation cluster name is the genetic threshold chosen by DODGE so that the full name is “genomic identity:genetic threshold”. The same process is used for hierCC progressing from larger to smaller threshold hierCC clusters. Because SNP based analyses have no standardised nomenclature, numerical investigation cluster names are assigned per analysis. The second part of the investigation cluster name is the genetic threshold chosen by DODGE so that the full name is “genomic identity:genetic threshold”. DODGE algorithm For cgMLST data obtained from the MGTdb website each investigation cluster will be assigned an MGT ST. For data obtained from Enterobase a hierCC cluster name will be assigned (Zhou et al. 2021). The name is selected at the highest resolution level where greater than 70% of isolates in the cluster share the same ST (for MGT) or cluster (for hierCC). For example, in a cluster of 20 isolates, 20 (100%) have the same MGT6 ST, 17 (85%) the same MGT7 ST and 12 (60%) the same MGT8 ST, the MGT7 ST is then chosen as the investigation cluster name. . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: edRxiv preprint DODGE pipeline Most genomic analyses operate on a static set of isolates. However, pathogen surveillance occurs continuously, and the analyses must be able to absorb additional isolates on a regular basis. For this reason, the DODGE pipeline was designed to run the DODGE algorithm with any input dataset divided into segments (1 week or 1 month) and runs once for each segment (Figure 1C). For example, if a dataset contains 2 months of data and the time period was set to week based then the DODGE pipeline would run 1 background run on data sampled from prior to those 2 months and then 9 separate detection runs, one for each of the 9 weeks in the 2 months. The first run would identify clusters in the background dataset. Each subsequent detection run would include all previous investigation and non-investigation clusters (from previous weeks and background) and would identify if an investigation cluster was new, expanded or unchanged from one week to the next. In this way DODGE produces the same results from a large dataset over multiple years whether that data was added prospectively week by week or retrospectively in one run. Importantly investigation cluster names assigned by the DODGE algorithm are inherited across time periods to allow ongoing surveillance and tracking of the cluster. Additionally, once the cluster is identified as an investigation cluster, temporal thresholds used for cluster identification are no longer applied to allow long lived investigation clusters to be reported. The DODGE pipeline can also be run with a single static genetic threshold (bypassing the DODGE algorithm) if needed. Most genomic analyses operate on a static set of isolates. However, pathogen surveillance occurs continuously, and the analyses must be able to absorb additional isolates on a regular basis. For this reason, the DODGE pipeline was designed to run the DODGE algorithm with any input dataset divided into segments (1 week or 1 month) and runs once for each segment (Figure 1C). For example, if a dataset contains 2 months of data and the time period was set to week based then the DODGE pipeline would run 1 background run on data sampled from prior to those 2 months and then 9 separate detection runs, one for each of the 9 weeks in the 2 months. The first run would identify clusters in the background dataset. DODGE pipeline Each subsequent detection run would include all previous investigation and non-investigation clusters (from previous weeks and background) and would identify if an investigation cluster was new, . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint DODGE case study datasets and algorithm settings The Australian dataset includes genomic data for all STM isolates collected and sequenced at NSW and QLD public health laboratories in January and February 2017. All isolates in the STM MGTdb from Australia before 2017 were used as the background dataset. DODGE was run on this dataset with 5 isolate minimum cluster size and 28-day temporal threshold (ie, 5 cases in a 28 day window as signal of an outbreak) and an initial genetic threshold of five. For the UK dataset all STM isolates from the UK from 2014 to 2022 that had year and month metadata were extracted from the STM MGTdb database. DODGE was run using a 5 isolate minimum cluster size, 5 genetic distance maximum and a two month temporal window. agreement with MGT based clusters with a kohens kappa score of 0.91 (Supplementary Results). agreement with MGT based clusters with a kohens kappa score of 0.91 (Supplementary Results). Application of DODGE to two months of Australian surveillance data using MGT A total of 517 STM genomes from NSW and QLD sequenced in January and February 2017 were used to identify investigation clusters using DODGE (data available at https://github.com/LanLab/dodge/tree/main/examples/). Existing publicly available Australian isolates collected prior to 2017 were used as background data and included 1030 isolates over 26 years (Supplementary Table 1). Fourteen investigation clusters including 214 isolates (41.4%) were identified from the 2 months of surveillance (Figure 1D, Supplementary Figure 1, Supplementary Table 2). The average investigation cluster timespan was 29.3 days, average size was 15.3 isolates and average maximum pairwise distance was 4.7 allele differences. Of the 208 isolates in investigation clusters, 35 (16.8%) were collected before the cluster was identified as an investigation cluster, 77 (37.0%) were collected in the week the cluster was identified and 96 (46.2%) were collected after the identification. The Australian dataset was also run using SNP inputs and investigation clusters showed good . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: edRxiv preprint Application to UK data Publicly available STM genomic surveillance data from the United Kingdom between 2014 and 2022 was evaluated as it is the most complete large dataset that includes month and year metadata (n=13251, Supplementary Table 3). Isolates from 2014 and 2015 were used as background data (n=2912) and the remaining 7 years of isolates (n=10339) were used to detect investigation clusters. A total of 93 investigation clusters were identified (Supplementary Table 4, Supplementary Figure 2) containing 1727 isolates (16.70% of 7 year dataset). The average investigation cluster timespan was 9.19 months, average size was 19.38 isolates and average maximum pairwise distance was 3.75 allele differences. Of the 1727 investigation cluster isolates, 105 (6.1%) were collected before the corresponding cluster was identified as an investigation cluster, 719 (41.5%) were collected in the week the corresponding cluster was identified and 909 (52.4%) were collected after the identification. Two epidemiologically confirmed outbreaks were matched to publicly available representative genomic data within the UK dataset. The first was identified in April 2020 and caused 104 confirmed cases in the UK (European Centre for Disease Prevention and Control 2020). A representative from this cluster fell within the MGT9 ST22592:1 investigation cluster which contained 90 isolates and was assigned as an investigation cluster in February 2020. The second outbreak was reported in February 2022 and consisted of two distinct clusters which caused 102 and 7 epidemiologically linked cases in the UK, respectively (Larkin et al. 2022). Two representatives for Cluster 1 fell within the investigation cluster MGT7 . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: edRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint January 2022. Two representatives for Cluster 2 fell within investigation cluster MGT9 January 2022. Two representatives for Cluster 2 fell within investigation cluster MGT9 ST30910:3, which contained 7 isolates and was assigned as an investigation cluster March 2022. Discussion The identification of point source outbreaks using automated methods often rely on epidemiological data such as time, location and strain phenotype without considering detailed genetic relationships between isolates (Latash et al. 2020, Salmon et al. 2016, Zhang et al. 2021). The increased uptake of WGS for prospective public health surveillance of different bacterial pathogens has the potential to provide this genetic context. However, the identification and reporting of emerging outbreaks from large datasets requires significant time and expertise. A recent promising approach for outbreak threshold detection employs temporal metadata and evolutionary modelling to select optimal genetic clusters (Duval et al. 2023). However, it was tested on a small set of simulated data with addition of only one real- life outbreak . Another published method does allow for clusters to be named and tracked over time from large datasets but does not select or adjust thresholds nor identify potential outbreak clusters (Mixao et al. 2023). A third method can identify whether an isolate should be included in an existing outbreak but cannot detect those outbreaks initially (Radomski et al. 2019). DODGE is designed to identify a potential outbreak cluster by dynamically selecting the genetic threshold appropriate for the given investigation cluster using large, long term ongoing genomic surveillance datasets. This is achieved by identifying a genetic threshold for a given cluster that is stringent enough to exclude all isolates that occur more than a certain time in the past. In this way when sufficient background data is available, DODGE can adapt . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: edRxiv preprint to the diversity of different clades in a population to provide more accurate outbreak cluster detection. to the diversity of different clades in a population to provide more accurate outbreak cluster detection. Other key features of DODGE are the ability to analyse data in on-going surveillance while maintaining cluster identity through existing bacterial genomic nomenclature systems (MGT and hierCC). These nomenclature systems have been applied to all public global data for STM allowing investigation clusters to be placed in broader genomic context while also facilitating simple communication of outbreak types. Two investigation clusters from the UK dataset were matched with previously described outbreaks (European Centre for Disease Prevention and Control 2020; Larkin et al. 2022). In both cases representative isolates from the outbreaks were found within investigation clusters predicted by DODGE. These investigation clusters matched the size and timeframe reported for the outbreaks. Importantly, in both cases investigation clusters were identified prior to the date the cluster was originally reported (1 month earlier for MGT7 ST21164:4, 2 months earlier for MGT9 ST22592:1). This potential improvement in detection speed could allow more rapid responses to outbreaks, potentially reducing the overall number of outbreak cases. Additionally, in both the Australian and UK datasets, a significant proportion of isolates in investigation clusters were sampled after their respective investigation clusters were first detected (46.2% and 52.4%, respectively). These clusters represented likely community outbreaks and if they were investigated in a timely manner and preventative measures were implemented, the public health and societal burden of such clusters could be substantially reduced. DODGE provides a means to identify, name and track outbreak clusters using dynamic thresholds from prospective genomic surveillance datasets and can be incorporated within laboratory surveillance and analysis workflows. The program is publicly available . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: edRxiv preprint (https://github.com/LanLab/dodge) and could be used to accelerate the identification and control of point source outbreaks in any bacterial species where appropriate quality surveillance data is available. Acknowledgements This work was supported by The National Health and Medical Research Council: [Grant Number 1146938]. Number 1146938]. indicates the week in which the cluster was identified as an investigation cluster by the DODGE algorithm. indicates the week in which the cluster was identified as an investigation cluster by the DODGE algorithm. Figure legends Figure 1. The DODGE pipeline, algorithm and Australian dataset investigation clusters. A. Flowchart describing 6 stages of the DODGE algorithm. B. Example investigation cluster detection with the same 6 stages marked. Blue circles represent isolates, red numbered lines are genetic distances. At each genetic threshold isolates within the grey shaded area are the cluster being evaluated. C. High level schematic of the DODGE pipeline including the DODGE algorithm. Genetic data in the form of allele profiles (Enterobase or MGTdb) or SNPs (output by snippy) for isolates from a given temporal window (a week or month) are combined with previous time periods to generate a combined distance matrix. Distances between isolate pairs that are not in an optional input distance matrix (Blue arrow) are calculated and added. Clusters are identified using single linkage clustering from the distance matrix. These clusters are compared to existing investigation and non-investigation clusters from previous time periods (blue arrow) to identify expanded or unchanged investigation clusters. Remaining non investigation clusters are then used to identify novel investigation clusters using the DODGE algorithm detailed in B and C. Green boxes are input files, red outlined boxes are output files, blue arrows represent outputs from one time period used as inputs in the next. D. Investigation clusters identified from the Australian dataset over time. X axis is date of collection by week. Y axis is investigation cluster with MGT ST based ID. The area of circles is proportional to number of isolates in that investigation cluster in that week. Colour represents the genetic threshold used for that investigation cluster. Red outline . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: edRxiv preprint indicates the week in which the cluster was identified as an investigation cluster by the DODGE algorithm. References CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: edRxiv preprint Latash, J., Greene, S. K., Stavinsky, F., et al.; Salmonellosis Outbreak Detected by Automated Spatiotemporal Analysis - New York City, May-June 2019. MMWR Morb Mortal Wkly Rep 2020;69:815-19. https://doi.org/10.15585/mmwr.mm6926a2 Leekitcharoenphon, P., Nielsen, E. M., Kaas, R. S., et al.; Evaluation of whole genome sequencing for outbreak detection of Salmonella enterica. PLoS One 2014;9:e87991. https://doi.org/10.1371/journal.pone.0087991 Mixao, V., Pinto, M., Sobral, D., et al.; ReporTree: a surveillance-oriented tool to strengthen the linkage between pathogen genetic clusters and epidemiological data. Genome Med 2023;15:43. https://doi.org/10.1186/s13073-023-01196-1 Octavia, S., Wang, Q., Tanaka, M. M., et al.; Delineating community outbreaks of Salmonella enterica serovar Typhimurium by use of whole-genome sequencing: insights into genomic variability within an outbreak. J Clin Microbiol 2015;53:1063- 71. https://doi.org/10.1128/JCM.03235-14 p g Payne, M., Octavia, S., Luu, L. D. W., et al.; Enhancing genomics-based outbreak detection of endemic Salmonella enterica serovar Typhimurium using dynamic thresholds. Microb Genom 2019;7:https://doi.org/10.1099/mgen.0.000310 p g Payne, M., Octavia, S., Luu, L. D. W., et al.; Enhancing genomics-based outbreak detection of endemic Salmonella enterica serovar Typhimurium using dynamic thresholds. Microb Genom 2019;7:https://doi.org/10.1099/mgen.0.000310 Payne, M., Kaur, S., Wang, Q., et al.; Multilevel genome typing: genomics-guided scalable resolution typing of microbial pathogens. Euro Surveill 2020;25:https://doi.org/10.2807/1560-7917.ES.2020.25.20.1900519 Phillips, Anastasia, Sotomayor, Cristina, Wang, Qinning, et al.; Whole genome sequencing of Salmonella Typhimurium illuminates distinct outbreaks caused by an endemic multi-locus variable number tandem repeat analysis type in Australia, 2014. BMC microbiology 2016;16:211. https://doi.org/10.1186/s12866-016-0831-3 Radomski, N., Cadel-Six, S., Cherchame, E., et al.; A Simple and Robust Statistical Method to Define Genetic Relatedness of Samples Related to Outbreaks at the Genomic Scale - Application to Retrospective Salmonella Foodborne Outbreak Investigations. Front Microbiol 2019;10:2413. https://doi.org/10.3389/fmicb.2019.02413 Sabat, A. J., Budimir, A., Nashev, D., et al.; Overview of molecular typing methods for outbreak detection and epidemiological surveillance. Euro Surveill 2013;18:20380. https://doi.org/10.2807/ese.18.04.20380-en Salmon, M., Schumacher, D., Burmann, H., et al.; A system for automated outbreak detectio of communicable diseases in Germany. Euro Surveill 2016;21:https://doi.org/10.2807/1560-7917.ES.2016.21.13.30180 Salmon, M., Schumacher, D., Burmann, H., et al.; A system for automated outbreak detection of communicable diseases in Germany. Euro Surveill 2016;21:https://doi.org/10.2807/1560-7917.ES.2016.21.13.30180 Seemann, T. (2015), 'snippy: fast bacterial variant calling from NGS reads', (3.1 edn.; https://github.com/tseemann/snippy: GitHub). References Bekal, S., Berry, C., Reimer, A. R., et al.; Usefulness of High-Quality Core Genome Single- Nucleotide Variant Analysis for Subtyping the Highly Clonal and the Most Prevalent Salmonella enterica Serovar Heidelberg Clone in the Context of Outbreak Investigations. J Clin Microbiol 2016;54:289-95. https://doi.org/10.1128/JCM.02200- 15 Duval, A., Opatowski, L., and Brisse, S.; Defining genomic epidemiology thresholds for common-source bacterial outbreaks: a modelling study. Lancet Microbe 2023;4:e349- e57. https://doi.org/10.1016/S2666-5247(22)00380-9 European Centre for Disease Prevention and Control, European Food Safety Authority (2020), 'Multi-country outbreak of Salmonella Typhimurium and S. Anatum infections linked to Brazil nuts – 21 October 2020', EFSA Supporting Publications (17), 1944E. Gymoese, P., Sorensen, G., Litrup, E., et al.; Investigation of Outbreaks of Salmonella enterica Serovar Typhimurium and Its Monophasic Variants Using Whole-Genome Sequencing, Denmark. Emerg Infect Dis 2017;23:1631-39. https://doi.org/10.3201/eid2310.161248 Hendriksen, R. S., Vieira, A. R., Karlsmose, S., et al.; Global monitoring of Salmonella serovar distribution from the World Health Organization Global Foodborne Infections Network Country Data Bank: results of quality assured laboratories from 2001 to 2007. Foodborne Pathog Dis 2011;8:887-900. https://doi.org/10.1089/fpd.2010.0787 Kaur, S., Payne, M., Luo, L., et al.; MGTdb: a web service and database for studying the global and local genomic epidemiology of bacterial pathogens. Database (Oxford) 2022;2022:https://doi.org/10.1093/database/baac094 p g Kirk, M. D., Pires, S. M., Black, R. E., et al.; World Health Organization Estimates of the Global and Regional Disease Burden of 22 Foodborne Bacterial, Protozoal, and Viral Diseases, 2010: A Data Synthesis. PLoS Med 2015;12:e1001921. https://doi.org/10.1371/journal.pmed.1001921 Larkin, L., Pardos de la Gandara, M., Hoban, A., et al.; Investigation of an international outbreak of multidrug-resistant monophasic Salmonella Typhimurium associated with chocolate products, EU/EEA and United Kingdom, February to April 2022. Euro Surveill 2022;27:https://doi.org/10.2807/1560-7917.ES.2022.27.15.2200314 . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 22, 2024. ; https://doi.org/10.1101/2024.01.21.24301506 doi: medRxiv preprint . References Seemann, T. (2015), 'snippy: fast bacterial variant calling from NGS reads', (3.1 edn. https://github.com/tseemann/snippy: GitHub). Zhang, P., Cui, W., Wang, H., et al.; High-Efficiency Machine Learning Method for Identifying Foodborne Disease Outbreaks and Confounding Factors. Foodborne Pathog Dis 2021;18:590-98. https://doi.org/10.1089/fpd.2020.2913 Zhang, P., Cui, W., Wang, H., et al.; High-Efficiency Machine Learning Method for Identifying Foodborne Disease Outbreaks and Confounding Factors. Foodborne Pathog Dis 2021;18:590-98. https://doi.org/10.1089/fpd.2020.2913 p g p Zhou, Z., Charlesworth, J., and Achtman, M.; HierCC: a multi-level clustering scheme for population assignments based on core genome MLST. Bioinformatics 2021;37:3645- 46. https://doi.org/10.1093/bioinformatics/btab234 Zhou, Z., Charlesworth, J., and Achtman, M.; HierCC: a multi-level clustering scheme for population assignments based on core genome MLST. Bioinformatics 2021;37:3645- 46. https://doi.org/10.1093/bioinformatics/btab234 Zhou, Z., Alikhan, N. F., Mohamed, K., et al.; The EnteroBase user's guide, with case studies on Salmonella transmissions, Yersinia pestis phylogeny, and Escherichia core genomic diversity. Genome Res 2020;30:138-52. https://doi.org/10.1101/gr.251678.119 Zhou, Z., Alikhan, N. F., Mohamed, K., et al.; The EnteroBase user's guide, with case studies on Salmonella transmissions, Yersinia pestis phylogeny, and Escherichia core genomic diversity. Genome Res 2020;30:138-52. https://doi.org/10.1101/gr.251678.119
https://openalex.org/W2806620768
http://publications.lnu.edu.ua/journals/index.php/biology/article/download/554/560
Ukrainian
null
Ethological relations in the consortion
Bìologìčnì studìï
2,017
cc-by
2,035
Biol. Stud. 2017: 11(2); 137–140 • DOI: https://doi.org/10.30970/sbi.1102.556 www.http://publications.lnu.edu.ua/journals/index.php/biology УДК 574.4 ЕТОЛОГІЧНІ ЗВ’ЯЗКИ В КОНСОРЦІЇ УДК 574.4 Й. В. Царик Й. В. Царик Львівський національний університет імені Івана Франка вул. Грушевського, 4, Львів 79000, Україна e-mail: zoomus @franko.lviv.ua Львівський національний університет імені Івана Франка вул. Грушевського, 4, Львів 79000, Україна e-mail: zoomus @franko.lviv.ua Розглянуто подальший розвиток вчення про консорцію як загальнобіологіч­ не явище, котре характеризує взаємозв’язок живого й неживого в єдиній системі. Зокрема, звернуто увагу на потребу аналізу етологічних зв’язків між детермінан­ том консорції й консортами, які в системі консорції ще не вивчали. Етологічні зв’язки в основному проявляються на рівні гетеротрофно-детермінантних кон­ сорцій. Зроблено припущення, що носіями етологічних зв’язків є інформація, яка може проявлятися на рівні зорових, хімічних, температурних, вологих, мімічних тощо сигналів. Подано також деякі літературні фактичні дані щодо етологічних зв’язків між детермінантами й консортами. Завершується стаття фразою, що, можливо, консорцію доцільно розглядати як елементарну еволюційну одиницю еволюції екосистем. ISSN 1996-4536 (print) • ISSN 2311-0783 (on-line) • Біологічні Студії / Studia Biologica • 2017 • Том 11/№2 • С. 137–140 Ключові слова: консорція, зв’язки, етологія, детермінанти, консорти Це повідомлення доцільно розглядати як продовження праці, що була опублі­ кована нами в 2008 році і стосувалася ролі топічних та фабричних зв’язків у кон­ сорціях [10]. У ній ми акцентували увагу на тому, що дослідники консорцій в осно­ вному вивчають трофічні зв’язки між консортами і ядром консорції, рідше форетич­ ні – перенесення пилку, насіння, молоді тварин, а також фабричні, медіопатичні тощо. Згідно з уявленнями В.М. Беклемишева [1] та Е.М. Лавренка [4], консорція – це система різних систематичних груп організмів, які пов’язані між собою комплек­ сом зв’язків: трофічними, топічними, фабричними й форетичними. Як ми вже зга­ дували, з поля зору дослідників випали інші зв’язки, наприклад, етологічні (пове­ дінкові). Цей тип зв’язків, на нашу думку, найбільш яскраво виражений у гетеро­ трофно-детермінантних консорцій, у яких ядром є гетеротрофний організм [10, 11]. Неврахування етологічних зв’язків у гетеротрофно-детермінантних консорціях збіднює наше уявлення про особливості функціонування цих унікальних гетеро­ трофних екосистем, а відтак, твердження щодо ефективного управління ними, на­ приклад, ужитковими видами тварин є надто оптимістичним. Етологія, за визначенням класика цієї науки К.А. Лоренца [5], є біологічною дис­ ципліною, яка вивчає поведінку тварин у природних умовах, приділяє увагу аналізові генетично зумовлених інстинктів, навчанню тварин, їхнім розумовим здібностям, 4536 (print) • ISSN 2311-0783 (on-line) • Біологічні Студії / Studia Biologica • 2017 • Том 11/№2 • С. 137–140 138 Й. В. Царик а також еволюції. Ще раз звертаємо увагу на те, що спеціальних досліджень ето­ логічних зв’язків та їхньої ролі у функціонуванні консорцій в літературі ми поки що не знайшли. Відтак, для розкриття теми будемо послуговуватися літературними даними, які стосуються поведінки тварин, а також іншими загальнобіологічними фактами. Як приклад наводимо дані М.А. Голубця [3], подані у монографії “Екосис­ темологія”, щодо різноманіття консортів ондатри (Ondatra zibethicus L.) у Західно­ му Сибіру. а також еволюції. Ще раз звертаємо увагу на те, що спеціальних досліджень ето­ логічних зв’язків та їхньої ролі у функціонуванні консорцій в літературі ми поки що не знайшли. Відтак, для розкриття теми будемо послуговуватися літературними даними, які стосуються поведінки тварин, а також іншими загальнобіологічними фактами. Як приклад наводимо дані М.А. Голубця [3], подані у монографії “Екосис­ темологія”, щодо різноманіття консортів ондатри (Ondatra zibethicus L.) у Західно­ му Сибіру. у у Так, трофічними й топічними зв’язками ондатра пов’язана з 38 видами птахів, 26 – ссавців, 2 – плазунів і 2 – риб. На ондатру полюють 24 види хижаків, а на її тілі паразитують іксодові та гамазові кліщі, а також властиві ендопаразити (48 видів гельмінтів). ISSN 1996-4536 (print) • ISSN 2311-0783 (on-line) • Біологічні Студії / Studia Biologica • 2017 • Том 11/№2 • С. 137–140 Ключові слова: консорція, зв’язки, етологія, детермінанти, консорти Як бачимо з цих даних, основна увага дослідників була спрямована на дві форми зв’язків: трофічні й топічні. Що стосується фабричних і форетичних та етологічних, то таких даних немає. У той же час М.А. Голубець звертає увагу на такий цікавий взаємозв’язок між водяною полівкою (Arvicola terrestris L.) та онда­ трою. Так, чисельність особин ондатри (детермінант консорції) тісно корелює із чисельністю водяної полівки, яка є носієм спільного для обох видів збудника туля­ ремії – захворювання зовнішніх лімфатичних вузлів. Встановлено, що в період де­ пресії чисельність особин полівки різко зростає одночасно з чисельністю особин ондатри. Виявлено, що водяна полівка заселяє взимку “хатки” ондатри, в яких про­ тягом осені, зими й на початку весни інтенсивно розмножуються іксодові кліщі, що живляться кров’ю полівки. Весною, після заселення хаток ондатрою, кліщі поселя­ ються на її тілі та через укуси разом зі слиною передають збудник туляремії, який у подальшому призводить до смерті особин ондатри. Залишення ондатрою місця помешкання, яке може бути зумовлене зміною її поведінки, зокрема, внаслідок впливу хижих тварин: світлого тхора (Mustela eversmanni L.), лисиці (Vulpes vulpes L.), домашньої собаки (Canis familiaris L.), призведе до розриву зв’язків зі співмешканкою – водяною полівкою, а відтак і зниження рівня зараженості ондатри збудником туляремії, тобто зміна поведінки вплине на виживання її особин. Можна думати, що на консортивну організацію детермінантів гетеротрофних консорцій впливає також зміна їхньої поведінки, яка пов’язана із тісним співісну­ ванням з людиною (деякі пристосування птахів, ссавців) і пристосування до урба­ нізованого середовища. Це співіснування людини і тварин може призвести до того, що частина консортів, які притаманні конкретному виду тварин, випаде зі складу їхніх консорцій. Це, зокрема, можуть бути природні хижаки, але одночасно можуть з’явитися нові (зокрема, патогенні організми тощо). Це лише припущення, яке по­ требує фактичного підтвердження. Цікаві дані щодо впливу поведінки рудих лісових мурашок (Formica anquilonia L.) на риючих ссавців подають С.М. Пантелєєва, Т.І. Резнікова й О.Б. Сільнова [9]. Цими дослідниками встановлено, що окремі види полівок (Microtus sp.), а також звичайна бурозубка (Sorex araneus L.) уникають мурашників і фуражирних доріг мурашок. Для деяких видів ссавців фуражирні дороги є суттєвою перешкодою для вільного переміщення у просторі, це саме стосується і безхребетних, зокрема, ту­ рунів. Із цих даних можна зробити припущення, що поведінка лісових мурашок впливає на життєдіяльність дрібних ссавців. Не менш важливим питанням під час дослідження поведінкових зв’язків у кон­ сорції є таке: хто може бути “носієм” їхнього впливу? 4536 (print) • ISSN 2311-0783 (on-line) • Біологічні Студії / Studia Biologica • 2017 • Том 11/№2 • С. Ключові слова: консорція, зв’язки, етологія, детермінанти, консорти 137–140 139 ЕТОЛОГІЧНІ ЗВ’ЯЗКИ В КОНСОРЦІЇ На нашу думку, таким носієм може бути інформація, поняття якої у різних га­ лузях знань має багато трактувань. Усталеного розуміння поняття “інформація” немає. У нашому випадку інформація – це подразники, сигнали, знання тощо, які отримує споживач (індивідуум, група індивідуумів). Для інформації властива дис­ кретність, старіння. Інформація може бути зорова, тактильна, хімічна, звукова, ме­ ханічна тощо. М.П. Наумов [8] розробив теорію сигнального поля тварин, яка базу­ ється на даних про наслідки їхньої життєдіяльності. Цікаві фактичні дані щодо сиг­ нального поля тварин подає також О.В. Міхеєв [7]. Відомо, що “живе” як цілісне явище проявляється на трьох рівнях організації: індивідуумі, популяції й екосистемі [3]. Відтак інформаційне (сигнальне) поле тва­ рин може проявлятись на рівні індивідуума (індивідуальна консорція), популяції (популяційна консорція) й екосистеми (метаконсорція – система консорцій різних ієрархічних рівнів, які тісно пов’язані між собою й середовищем існування). Що стосується середовища (в першу чергу абіотичного), то воно володіє при­ таманною йому інформацією, наприклад, вологістю ґрунту, температурою, силою вітру, освітленням, вмістом забруднювачів, ступенем деградації порівняно з при­ родним тощо. Можна зробити припущення, що інформація середовища є тлом, на якому відбувається інтерференція інформацій, а джерелом для них слугують інди­ відууми, популяції та їхні комплекси. уу у На нашу думку, власне в контексті розвитку уявлення про інформаційну взає­ модію між особинами різних систематичних груп у консорції і доцільно розглядати етологічні зв’язки, які їй притаманні. Тобто етологічні зв’язки між ядром і його кон­ сортами можуть відбуватися на рівні сигналів (хімічних, звукових, зорових, міміч­ них тощо). Прикладом таких інформаційно-етологічних зв’язків можуть бути взаємозв’язки між птахами, які розшукують гнізда диких бджіл, і ссавцями – капським медоїдом [2]. В етології достатньо детально розглядається таке явище як ритулізація і кому­ нікація. Якщо ритулізація – це обмін інформацією між особинами одного виду, на­ приклад, у зграї вовків, яка полює на здобич, наприклад, на оленя (детермінант консорції), то комунікація – обмін інформацією між особинами різних видів (тобто консортами й детермінантом консорції). Таким прикладом може бути демонстра­ ція різних плям денними й нічними метеликами у разі наближення їхніх хижаків (птахів), а також мімікрія [6]. Безумовно, фактичний матеріал, який міститься в цій статті, є фрагментарним і не дає цілісного уявлення про роль поведінкових зв’язків у гетеротрофно детермі­ нантних консорціях. Необхідні спеціальні дослідження цього типу взаємовідносин як між консортами, так і між детермінантом консорцій. Особливо ці дослідження потрібні тепер, у час суттєвих кліматичних змін і ан­ тропогенної трансформації середовища. ISSN 1996-4536 (print) • ISSN 2311-0783 (on-line) • Біологічні Студії / Studia Biologica • 2017 • Том 11/№2 • С. 137–140 Ключові слова: консорція, зв’язки, етологія, детермінанти, консорти Studia Biologica, 2016; 10(2): 195–202. Ключові слова: консорція, зв’язки, етологія, детермінанти, консорти На основі теперішніх уявлень про консорцію можна стверджувати, що вона як цілісна система забезпечується такими зв’язками: трофічними, топічними, фа­ бричними, форетичними, медіопатичними (зміна середовища) й етологічними. Два останні зв’язки є найменш вивченими. Ще один аспект, на який доцільно звернути увагу: хто може бути елементарною одиницею еволюції екосистем? Ми вважаємо, що це консорція. 6 (print) • ISSN 2311-0783 (on-line) • Біологічні Студії / Studia Biologica • 2017 • Том 11/№2 • С. 137–140 ISSN 1996-4536 (print) • ISSN 2311-0783 (on-line) • Біологічні Студії / Studia Biologica • 2017 • Том 11/№2 • С. 137–140 140 Й. В. Царик 1. Beklemishev V.N. About the classification of biogeocoenological (symphysiological) rela­ tions. Bull. MOIP. Biol. Series, 1951; 65(2): 3–30 (In Russian). 2. Begon M., Harper J., Townsend C. Ecology: Individuals, Populations and Communities. Moscow: Mir, 1989: 668 p. , p 3. Holubets M.A. Ecosystemology. Lviv: Polly Co. Ltd., 2000. 316 p. (In Ukrainian). 3. Holubets M.A. Ecosystemology. Lviv: Polly Co. Ltd., 2000. 316 p. (In Ukrainian). 4. Lavrenko E.M. The main mechanisms of plant communities and the ways of their study. Field Phytosociology M ; L : AS of USSR Publishing House 1959 Vol 1: 13–75 (In Russian) 4. Lavrenko E.M. The main mechanisms of plant communities and the ways of their study. Field Phytosociology. M.; L.: AS of USSR Publishing House, 1959. Vol. 1: 13–75. (In Russian). Phytosociology. M.; L.: AS of USSR Publishing House, 1959. Vol. 1: 13–75. (In Russian). 5. Lorenz K. King Solomon’s Ring. Moscow: Znaniye, 1980: 240 p. 5. Lorenz K. King Solomon’s Ring. Moscow: Znaniye, 1980: 240 p. cFarland D. Animal Behavior: Psychobiology, Ethology and Evolution. Moscow: Mir, 88: 520 p.ii 7. Mikheyev A.V. The classification of mammal signs as signal elements of information field. Eco­logy and nature conservation problems of the technogenic region. Donetsk: DonNU, 2009; 1: 115–123. (In Russian).ii 8. Naumov N.P. Signal (biological) fields and their significance for animals. Zhurn. Obshch. Biol, 1973; 34(6): 808–817. (In Russian). 9. Panteleeva S.N., Reznikova Zh. I., Sinkova O.B. Spatio-ethological aspects of interactions between small mammals and wood ants. Zhurn. Obshch. Biol, 1973; 34(6): 808–817. (In Russian). ) 10. Tsaryk J.V., Tsaryk I.J. Topic and fabric consortive relations, and their role in the biodiversity conservation. Studia Biologica, 2008; 2(1): 71–77. (In Ukrainian). 11. Sachok O.S., Tsaryk I.J. The role of insects in pollination and dissemination of some plant species in high mountains of the Ukrainian Carpathians. ISSN 1996-4536 (print) • ISSN 2311-0783 (on-line) • Біологічні Студії / Studia Biologica • 2017 • Том 11/№2 • С. 137–140 ETHOLOGICAL RELATIONS IN THE CONSORTION y Ivan Franko National University of Lviv, 4, Hrushevskyi St., Lviv 79005, Ukraine e-mail: zoomus@franko.lviv.ua Further development of the study about the consortion as a biological phenomenon that characterizes interrelations between the biotic and abiotic components within a single system is reviewed. In particular, an attention is drawn to the necessity of analy­ sis of the ethological relations between the consortion determinant and its consorts that haven’t been studied under this point of view yet. The ethological relations are displayed mainly on the level of heterotrophic consortions. An assumption is made that the infor­ mation as the carrier of ethological relations can be displayed on the level of visual, chemical, thermal, mimic signals etc. Some literary data about the ethological relations between the determinant and its consorts are presented. Summing up the consortion is supposed to be the possible elementary unit of ecosystem evolution. Keywords: consortion, relations, ethology, determinants, consorts Одержано: 31.08.2017 Одержано: 31.08.2017 ISSN 1996-4536 (print) • ISSN 2311-0783 (on-line) • Біологічні Студії / Studia Biologica • 2017 • Том 11/№2 • С. 137–140
https://openalex.org/W4308998153
https://www.intechopen.com/citation-pdf-url/84676
English
null
Medicinal Potential of Camel Milk Lactoferrin
IntechOpen eBooks
2,023
cc-by
8,635
Abstract Camel milk is a rich source of protein with well-recognized medicinal properties to treat various diseases. The objective of this work is to understand the role of camel milk lactoferrin in immunomodulation and in disease treatment. It has been found that camel milk lactoferrin is a very suitable nutraceutical agent by virtue of its bioac- tivity, immuno-compatibility, and safety. It can be used for the treatment of infec- tious, metabolic, and neurodegenerative diseases, besides cancer. It is a cost-effective biomolecule that also has high relative abundance and bioavailability. Keywords: camel milk, lactoferrin, medicinal potential, commercial significance, immunomodulatory, anti-microbial, anti-cancer Chapter Medicinal Potential of Camel Milk Lactoferrin Neelam Mahala, Aastha Mittal and Uma S. Dubey 2.1 Medicinal properties of camel milk Naturally occurring bioactive compounds have contributed effectively to cancer therapeutics, paving a way for better disease management. Camel milk is one such dietary food with immense nutritional and medicinal value. Like human and bovine milk, camel milk also contains numerous proteins such as immunoglobulins, alpha- lactalbumin, lactoperoxidase, casein, lysozyme, lactoferrin, amylase, etc. The major proteins present in camel milk along with their clinical significance have been depicted in Table 1. It forms a high nutritional source with low cholesterol, low sugar, high min- erals (sodium, potassium, iron, copper, zinc, and magnesium), high vitamins (vitamin C, B2, A, and E), and high concentrations of insulin compared to the ruminant milk [20–22]. Moreover, very recently camel milk casein-derived nanoparticles have been used as carriers for the delivery of sorafenib in hepatocarcinoma cells [23]. 1. Introduction The medicinal properties of camel milk have long been recognized, especially in middle eastern countries. Camel Milk is a rich source of active proteins, especially enzymes that have several biological activities including antibacterial, antiviral, immunological, and antioxidant properties. Camel milk has been used to treat many diseases such as Hepatitis, Allergy, Liver, and kidney function, Diarrhea, and Diabetes. Moreover, camel milk has no allergenic properties and can be consumed by lactase-deficient people. Like human milk, camel milk has a high content of lactoferrin and α-lactalbumin but lacks β-lactoglobulin [1]. It differs from cow milk as it has lower fat, cholesterol, and lactose levels, besides this, there is an absence of beta-lactoglobu- lin and beta-casein. Beta casein is the allergenic component that is present in cow milk but absent in camel milk. Also, it has very low levels of lactose making it consumable by lactase deficient people [2]. It has been noted that despite the lack of refrigeration, camel’s milk remains unspoiled for several days. This may be due to the antibacterial activity of certain proteins contained in camel’s milk [3]. Furthermore, camel milk proteins are generally pH hydrolysis resistant and thermostable. Lactoferrin is well recognized as an adjunct to anti-cancer standard therapy by virtue of its immunomod- ulatory activity. It also exhibits immuno-compatibility, bioavailability, safety, relative abundance, and low-cost effectiveness. Moreover, the oral route of administration makes it very easy to be given to patients and it is usually well-tolerated [4]. Numerous studies on camel lactoferrin reported that it has anti-bacterial, anti-fungal, anti-viral, anti-inflammatory, antioxidant, and anti-tumor properties. Camel milk lactoferrin is a molecule that not only boosts the immune system but also acts against cancer. The 1 Current Issues and Advances in the Dairy Industry objective of this work is to understand the role of camel milk lactoferrin in immuno- modulation and in disease treatment [5]. objective of this work is to understand the role of camel milk lactoferrin in immuno- modulation and in disease treatment [5]. 2. Camel milk Camel milk has been found to be a healthier option for people with diabetes and those with food allergies. Several studies on camel milk have found its positive impact on autism, diabetes, liver disease, jaundice, and even cancer. Camel milk is high in vitamin C, many minerals, and immunoglobulins, which boost the immune system. It is not only a very nutritious dairy beverage but it also innately includes probiotics. Camel milk helps enhance gastrointestinal health besides improving systemic immu- nity. The drink has a low-fat content (only 2 to 3%, compared to cow milk) and thus is likely to attract more attention of health-aware consumers. In various Middle East countries and an Africa, it is used as a suitable supplement to feed undernourished children because it’s similarity with human breast milk [6]. 2.2 Commercial value of camel Milk Bedouins (nomadic Arab people) and many other desert communities of the world to face their harsh living conditions. g The dairy market in India reached a value of 13,174 billion INR in 2021. In the coming times, International market analysis research and consulting (IMARC) group expects the market to reach 30,840 billion INR by 2027. This would amount to a compound annual growth rate (CAGR) of 14.98% during the time interval 2022–2027. Actually, despite its availability, India has been late in entering the market scenario. Only in the end of 2016 did the Food Safety and Standard Authority of India (FSSAI) decide the standards for commercialization of camel milk. Notably, while government dairy cooperatives have been slow to respond, some entrepreneurs, interestingly, even from the Raika community of Rajasthan, have taken multiple dynamic initiatives. India’s first camel milk brand Aadvik Foods is set to disrupt the dairy and organic milk products market. This New Delhi-based company started its journey in 2016 with just one liter of camel milk. Today, it is procuring around 10,000 liters a month, having sold over 2 lakhs liters over the last three-and-half years. 2.2 Commercial value of camel Milk Latest reports suggest that the global camel dairy market reached 2.3 billion US$ in 2020. A total of 2.9 million tons of camel milk production has been recorded annually worldwide [24]. Camel dairy market is expected to reach USD 10.07 billion by 2027 growing at a growth rate of 8.0% in the forecast period 2020 to 2027. g g g p Camel milk is traditionally consumed in either a raw form or in a fermented form. But to cater with preferences of urban populations now manufacturers have stated the production of novel camel milk based food products such as flavored beverages, sweets, chocolates and Ice creams. These products are becoming increas- ingly popular in nations such as UAE, Saudi Arabia,, Kazakhstan, Algeria, Australia, Morocco, Egypt and India. Its increasing demand has resulted in a wide opportunity for product innovation and generation of new markets. Camel milk products are relatively more expensive than other cattle dairy food items due to its high produc- tion costs. In spite of being low in fat, camel milk has a relatively high content of unsaturated fatty acids, which are beneficial for us. It’s suitable for lactose-intolerant people. Camel milk is actually considered a super food because of its high mineral and vitamin content. Moreover, its benefits for joint pain and diabetes has also been well documented. It’s no wonder then that it’s for long been consumed by the 2 S. No Clinical condition Therapeutic molecules in camel milk Reference 1 Diabetes Insulin-like molecule [7] 2 Allergy Low levels of β-Casein & lack of β-lactoglobulin [8] 3 Liver and kidney function Alanine aminotransferase and aspartate aminotransferase [9] 4 Slimming properties Low protein content and reasonable cholesterol content [10] 5 Antitumor activity Lactoferrin, Lysozyme, Lactoperoxidase [11, 12] 6 Nutritional supplements Unsaturated fatty acids [13] 7 Easy assimilation in Lactase deficient patients L-lactate [14] 8 Bone formation High level of calcium [15] 9 Diarrhea High levels of sodium and potassium [16] 10 Immuno enhancer and antimicrobial activity Peptidoglycan recognition protein (PRP) [17] 11 Antibacterial and antiviral activity N-acetyl-glucosaminidase (NAGase) [18] 12 Confers special passive immunity Heavy chain antibodies (HCAb) or variable heavy antibodies (VHH) or nanobodies [19] Table 1. Application of camel milk molecules in treatment of various diseases. [14] Bedouins (nomadic Arab people) and many other desert communities of the world to face their harsh living conditions. 3. Clinical relevance of lactoferrin Lactoferrin is a versatile molecule that has been molded by natural selection to be amongst the first line of defense in mammals [25]. As the second most abundant protein 3 Current Issues and Advances in the Dairy Industry in colostrum, it is responsible for conferring immunity on newborns within the first few weeks of life [26]. Lactoferrin is involved in various physiological functions such as regulating homeostasis and cell proliferation, besides being a very potent antimicrobial agent. It has antibacterial, antifungal, antiviral, antioxidant, immunomodulatory, and anticancer activities [25, 27–29]. During infection and inflammation processes, the lac- toferrin concentration increases through the recruitment of neutrophils. The important properties of lactoferrin have been depicted in the flow diagram in Figure 1. Lactoferrin, the natural protein, is proving to be a highly promising bio-drug as an antimicrobial, immunomodulatory, and anticancer agent. According to Cragg et al., over 50% of the drugs in clinical trials for anticancer activity are isolated from natural sources or their ingredients. Several drugs currently used in chemotherapy are isolated from plant species and food sources [30, 31] Lactoferrin is a multi-functional protein with many beneficial properties. It is now recognized as a functional food for several products with commercial and clinical applications [32]. It is widely distributed in all biological fluids and is also expressed by immune cells, which release it under stimulation by pathogens. p y y p g The primary function of lactoferrin has been recognized to be in the modulation of the immune responses, besides iron transport, storage, and chelation. Lactoferrin activates immune cells and enhances their proliferation and differentiation. Its poten- tial to perform multiple activities is often attributed to its capacity to bind iron and interact with diverse molecular and cellular components of hosts and pathogens. The multiple functions ascribed to lactoferrin can either be dependent or independent of lactoferrin’s iron-binding ability [33]. Furthermore, it is noteworthy that lactoferrin concentrations are locally elevated in inflammatory disorders such as neurodegenera- tive diseases, autoimmune diseases (e.g., arthritis), and allergic inflammation. Figure 1. g Bioactivity of lactoferrin. g Bioactivity of lactoferrin. In addition to this, researchers have shown that in a murine model of diethyl nitrosamine-induced hepatocarcinogenesis, bovine milk lactoferrin significantly down-regulated the activity of liver antioxidant enzymes such as glutathione peroxi- dase, superoxide dismutase and catalase. It also increased the concentration of hepatic glutathione. Furthermore, bovine lactoferrin promoted the decrease of serum inflam- matory markers and ameliorated in hepatic histological structures in a significant manner [41]. Furthermore, the applications of lactoferrin have been highlighted in Table 2. Other than the direct modulation of the immune response, lactoferrin strategically acts as a potent anti-inflammatory agent by scavenging ROS. Pro-oxidant agents can both promote DNA damage and induce as well as sustain inflammatory disorders. Inflammation itself drastically contributes to cancer development. Lactoferrin can maintain the physiological balance of ROS levels by direct binding of free iron, one of the principal actors involved in ROS production. It can also act as a regulator of key antioxidant enzymes, thus protecting the host from ROS-mediated cell and tissue dam- age in an overall manner [51]. g The protective character of lactoferrin against cancer has been demonstrated, on numerous occasions, including its impact on chemically induced tumors, in laboratory rodents. Lactoferrin has even been reported to inhibit the development of experimental metastases in mice [52–54]. Lactoferrin-mediated inhibition of tumor growth might be related to apoptosis of these cells, induced by the activation of the Fas signaling pathway. Nevertheless, the exact mechanism of this function has not been discovered so far [55]. 3.1 Lactoferrin as an Immuno-modulator Lactoferrin is a cell-secreted mediator that bridges innate and adaptive immune responses. For immune-modulatory functions, it interacts with specific receptors of the target cells (either epithelial cells or cells of the immune system) It also can bind to bacterial cell wall LPS. Lactoferrin modulates the activation, proliferation, maturation, differentiation, and migration of immune cells. The functional modulations take place in the T and B cells, neutrophils, monocytes/macrophages, and dendritic cells belong- ing to the antigen-presenting class of cells. It acts via two mechanisms of intracellular signal transduction, i.e., nuclear factor kappa B and MAP kinase [34–36]. Furthermore, it affects the mechanisms of the innate response, by influencing the activation of the complement system, increasing the NK cell activity, increasing the phagocytic ability of monocytes, and by enhancing their cytotoxicity [37]. There are lactoferrin receptors on many immune cells, so lactoferrin directly affects how these cells function. Its action increases levels of cytokines such as tumor necrosis factor (TNF-alpha), interleukin 8 (IL-8), and Nitric Oxide production besides limiting pathogenic growth [37, 38]. Lactoferrin modulates innate and adaptive immune response because of its abil- ity to bind LPS and CD-14. It also interferes with the formation of the CD14–LPS complex. This results in the attenuation of the LPS/CD-14/TLR-4, a signaling pathway involved in the pathogenesis of sepsis. Lactoferrin may stimulate the immune system by binding to CD-14 and then activating the TLR-4-mediated pathway while prevent- ing overexpression of LPS-induced inflammation [39]. Lactoferrin, which functions as a natural iron scavenger and a modulator of signaling pathways, leads to the negative feedback of the inflammatory response. This is also shown by a decrease in the produc- tion of reactive oxygen species and various pro-inflammatory cytokines [40]. 4 Medicinal Potential of Camel Milk Lactoferrin DOI: http://dx.doi.org/10.5772/intechopen.108316 Figure 1. Bioactivity of lactoferrin. Medicinal Potential of Camel Milk Lactoferrin DOI: http://dx.doi.org/10.5772/intechopen.108316 Medicinal Potential of Camel Milk Lactoferrin DOI: http://dx.doi.org/10.5772/intechopen.108316 Medicinal Potential of Camel Milk Lactoferrin DOI: http://dx.doi.org/10.5772/intechopen.108316 Figure 1. Bioactivity of lactoferrin. 3.2 Camel milk lactoferrin as an antimicrobial, anticancer, and immunomodulatory agent Lactoferrin is a highly conserved molecule. It possesses high degree of sequence homology and exerts multiple identical functions across mammalian species. Its 5 Current Issues and Advances in the Dairy Industry S. No Applications Additional Information References 1 Antihypertensive activity Obtained from lactoferrin- derived peptides [42] 2 Protection from anemia Serves as an iron-containing protein useful for treatment [43] 3 Bone regeneration Beneficial effect [44, 45] 4 Prevention of metabolic diseases Eg. Obesity and diabetes [46] 5 Acts as drug nanocarriers Emphasis on tumor-targeted drug delivery. [47] 6 Protection from Neurodegenerative diseases Markedly increased expression upregulation in brain cells [48] 7 Anti-inflammatory effect By inhibition of the formation of hydroxyl free radicals. [49] 8 DNA damage prevention Prevention of tumor formation in the central nervous system [50] 9 Activates the p53 tumor suppressor gene (TSG) Suppression of tumor formation [50] 10 Natural substitute for Antibiotics Antimicrobial activity: Also, a promising candidate to help break the vicious cycle of antibiotic resistance [49] 11 Natural food preservative Antimicrobial activity [49] Table 2. Applications of lactoferrin. ability to act as an antibacterial, antifungal, antiviral and antiparasitic, anti-inflam- matory and immunomodulatory agent is shared amongst most mammalian species and has already been discussed [56–58]. More specifically, it inhibits growth of Escherichia coli, Klebsiella pneumonia, Clostridium, Helicobacter pylori, Staphylococcus aureus, Candida albicans, etc. According to studies, the most therapeutic effects of camel milk are due to lactoferrin and immunoglobulins. Redwan & Tabll, 2007 reported that lactoferrin of camel milk has anti-viral activity and inhibits the virus entry into the cells. The camel milk lactoferrin stops HCV entry and replication in infected HepG2 cells two times higher than lactoferrin in human, bovine, and sheep milk. Generally, camel milk lactoferrin may directly interact with viral molecules or receptors (heparan sulfate) on the cell surface and prevent the virus’s attachment to the host cells and thus hinder infection. The virucidal mechanism of camel milk lactoferrin depends on its alpha-helical structure and cationic nature [59]. The antiviral effects of lactoferrin from camel milk have been demonstrated against many viruses. The mode of action behind this activity is the neutralization of virus particles and inhi- bition of their replication. Camel milk lactoferrin also has anti-pathogenic activity against human immunodeficiency virus, hepatitis B and C, cytomegalovirus as well as herpes simplex virus-1 infection. 3.2 Camel milk lactoferrin as an antimicrobial, anticancer, and immunomodulatory agent Not only this, but camel lactoferrin’s immunomodulatory role is exemplified by the fact that it modulates the activation and maturation of various immune cells such as neutrophils, macrophages, and lymphocytes [60]. 6 Medicinal Potential of Camel Milk Lactoferrin DOI: http://dx.doi.org/10.5772/intechopen.108316 Medicinal Potential of Camel Milk Lactoferrin DOI: http://dx.doi.org/10.5772/intechopen.108316 An earlier study on camel milk lactoferrin has demonstrated the ability to inhibit the growth of colon cancer cells line HCT-116. Camel milk lactoferrin exerted antioxidant activity through scavenging NO and the DPPH free radical. It has shown the capability to furnish reducing power as evident by total antioxidant assays. Camel milk lactoferrin also inhibited DNA damage most likely through binding catalytic iron [5]. g y Camel milk lactoferrin exhibits an anti-inflammatory activity against IL-1β induced activation of osteoarthritis associated chondrocytes in humans by blocking the NF- kappa B mediated signaling. Furthermore it inhibited cyclooxygenase-2 expression and PGE2 production in stimulated osteoarthritis chondrocytes. N. Rasheed et al., 2016 have reported that camel lactoferrin has cartilage protective and anti-arthritic activity. This novel mode of action of camel milk lactoferrin is very important in understanding the mechanisms behind its anti-inflammatory or anti-arthritic effects [61]. The above studies on lactoferrin derived from camel milk highlight the clinical relevance. 3.3 Anticancer potential of lactoferrin from other mammalian species Human and Bovine lactoferrin has been suggested to be able to act in tumor prevention and treatment [62, 63]. The lactoferrin preventive effect has been demon- strated in several animal models bearing different types of malignancies, including lung, tongue, esophagus, liver, and colorectal tumors [64–67]. Whereas lactoferrin treatment, was found to be effective in inhibiting growth, metastasis, and tumor- associated angiogenesis [63, 68, 69]. g g Bovine lactoferrin prevents development of chemically induced tumors. This effect has been confirmed in studies conducted on laboratory rodents. Based on in vivo stud- ies, oral administration of lactoferrin to rodents significantly decreased the chemically induced carcinogenesis in various organs such as breast, esophagus, tongue, lung, liver, colon, and bladder. It also hindered angiogenesis and decreased the incidence of metastases in experimental mice [67]. Furthermore, the combined administration of Lactoferrin and temozolomide enhances the effect of chemotherapy both in vitro and in vivo [55] Similarly, humans suffering from lung cancer undergoing chemotherapy had increased immune system response after taking human lactoferrin post-treatment [70]. Lactoferrin from a bovine source is a promising candidate as an anticancer agent [71] Although bovine milk contains lactoferrin, the human form has been found to be far more potent. Animal studies with mice or rats have shown beneficial effects of bovine lactoferrin ingestion as it can inhibit carcinogen–induced tumors in the colon, esophagus, lung, tongue, bladder, and liver [72]. The anticancer effect of lactoferrin has been extensively studied, and it has been observed that in the presence of Lactoferrin, cancer cells suffer significant damage. It is known to cause cell cycle arrest, damage to the cytoskeleton, and induction of apoptosis, in addition to decreasing cell migration [63, 73]. It decreased the viability and growth of breast cancer cell lines (HS578T and T47D). It also stopped cancer cell growth during the cell cycle and disrupted the cancer cell membrane [74]. Bovine lactoferrin efficiently inhibited the growth of breast cancer cells, suggesting that it has a potential to act as an anti-cancer agent against breast cancer [63, 75]. Lactoferrin helps to prevent the growth of cancer cells and shrinks the cancer cells. It is also known for its inhibitory action on cancer cell proliferation and its anti-inflammatory as well as antioxidant abilities against them [75]. Lactoferrin 7 Current Issues and Advances in the Dairy Industry expression levels are decreased in colorectal cancer as compared with normal tissue. 3.3 Anticancer potential of lactoferrin from other mammalian species Lactoferrin knockout mice demonstrated a great susceptibility to inflammation- induced colorectal dysplasia. Treatment of knockout mice with lactoferrin post- chemotherapy accelerated the reconstitution of the immune system, reducing the chances for infection, following chemotherapy treatment. Additionally, lactoferrin is significantly downregulated in specimens of nasopharyngeal carcinoma (NPC) and is negatively associated with tumor progression, metastasis, and prognosis of patients with NPC [76]. p Lactoferrin was shown to have preventive effects against gastrointestinal cancers, such as cancer of the colon, stomach, liver, and pancreas, and against metastasis of such neoplasms [77, 78]. Xu et al. (2010) demonstrated that bovine lactoferrin induces apoptosis in stomach cancer, thereby suppressing it [79]. Oral administration of lactoferrin decreased the occurrence of colon cancer by 83%. The number of adeno- carcinoma cells in the gut of rats was reduced after the ingestion of lactoferrin. g g Lactoferrin-mediated inhibition of tumor growth might be related to apoptosis of these cells, induced by the activation of the Fas signaling pathway [55]. It has been suggested that the treatment of lactoferrin knockout mice with lactoferrin (post-che- motherapy) accelerated the reconstitution of the immune system. This also reduced the chances of infection following chemotherapy treatment [76]. Lactoferrin can scavenge free iron in fluids and inflamed and infected sites, suppressing free radical- mediated damage and decreasing the availability of the metal to pathogens and cancer cells. Also, lactoferrin hinders migration in a model of human glioblastoma by revert- ing an epithelial-to-mesenchymal transition-like process [4, 32]. 3.5 Lactoferrin assimilation in vivo Lactoferrin shows high bioavailability after oral administration, high selectivity toward cancer cells, and a wide range of molecular targets controlling tumor prolifera- tion, survival, migration, invasion, and metastasis. Notably, lactoferrin may either promote or inhibit cell proliferation and migration depending on whether its target cell is normal or cancerous. Significantly, its administration is well tolerated and does not exhibit any significant side effects. Furthermore, lactoferrin may prevent cancer development and growth by enhancing the adaptive immune response. Oral adminis- tration of lactoferrin has also led to promising improvement in the immune responses of antiretroviral therapy in naıve children suffering from HIV [86]. Oral administra- tion of lactoferrin decreased the occurrence of colon cancer by 83%, while the quantity of adenocarcinoma cells was reduced in the gut of rats after ingestion of Lactoferrin, ameliorating tongue cancer. Of particular interest is the notion that even its oral administration may be effec- tive. This is different from many other therapeutic proteins, which typically require other invasive routes of administration [87]. Oral administration of bovine lactoferrin prevents carcinogenesis in the colon and other organs in rats. It also inhibits lung metastasis in mice. It might be mediating its anti-carcinogenesis effects is by increas- ing expression of relevant cytokines and inducing subsequent activation of immune cells [67]. It interacts with a wide range of molecular targets controlling tumor proliferation, survival, migration, invasion, and metastasis. It may be noted that lac- toferrin can promote or inhibit cell proliferation and migration depending on whether it acts upon normal or cancerous cells, respectively. Moreover, lactoferrin can prevent the development or inhibit cancer growth by boosting adaptive immune response. Most importantly, lactoferrin administration is highly tolerated and does not present significant adverse effects. g Oral administration of lactoferrin is the most widely adopted method of its deliv- ery into the human body. This still possesses some challenges that must be addressed before reaping the highest benefit from its intake. Since the functional domains of lactoferrin are highly dependent on its unique 3D structural conformation, the gastro- intestinal breakdown of lactoferrin may cause undesirable loss of some of its func- tional properties. The important receptors of lactoferrin are located at the intestinal mucosa and lymphatic tissue cells in the gut [88–91]. 3.4 Lactoferrin in COVID-19 treatment Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection has recently become a primary global health concern, leading to the urgent development of therapeutic agents for its prevention and treatment. Iron overload is understood to have an important role in the pathogenesis of COVID-19. Actually some features (such as inflammation hyperferritinemia, hypercoagulation, and immune dysfunc- tion) manifested a in COVID-19, are linked to iron overload. The presence of free iron, resulting from iron overload and dysregulation, is very highly reactive and toxic due to its reactive oxygen species (ROS) generation potential. The ROS produced react with very important cellular biomolecules and induce their subsequent damage. Nucleic acids, proteins as well as membranous and cellular lipids are effected by the highly activate inflammatory processes which may be either acute or chronic. The linkage of inflammation with multiple clinical conditions, such as cancer is well understood [80]. Lactoferrin has exhibited unique immunomodulatory, anti-inflammatory, and broad- spectrum antiviral activity indicating its potential for the cure of COVID-19 cases and prevention of its devastating effects on multiple target organs [81, 82]. Lactoferrin could counteract the coronavirus infection and inflammation, acting either as a natu- ral barrier of respiratory and intestinal mucosa or reverting the iron disorders related to the viral colonization. Iron-catalyzed lipid damage is understood to exerts a direct effect on ferroptosis, the newly discovered cell death mechanism. Unlike programmed cell death (PCD), ferroptosis not only leads to amplified cell death but is also associ- ated with inflammation. Iron chelators are generally recognized as safe and have been shown to protect patients in diseases characterized by iron overload. Research work also suggests that iron chelators exhibit antimicrobial activities. It is suggested that the naturally occurring iron chelators, such as lactoferrin, exert anti-inflammatory 8 Medicinal Potential of Camel Milk Lactoferrin DOI: http://dx.doi.org/10.5772/intechopen.108316 as well as immunomodulatory effects. It binds to some of the same receptors used by coronaviruses and hence blocks its entry into host cells. Iron chelators may actually be of a very high therapeutic value during the present scenario of the ongoing COVID-19 pandemic [80]. Therefore, the use of lactoferrin may be of value in the prevention and management of COVID-19. The use of lactoferrin appears to be a promising approach to treating COVID-19, but further investigations are required to verify its antiviral activity in vitro and in vivo [83–85]. 3.5 Lactoferrin assimilation in vivo Hence, the delivery of lactofer- rin through oral administration requires that it is protected so that it passes through the stomach and is delivered to the absorption sites in a functionally active form. But the most important thing is to note that the digestive tract in infants and newborns is not mature enough (e.g., the intragastric pH and the gastric emptying rate are higher than in adults), and lactoferrin would not be completely digested under these condi- tions. This hypothesis has been confirmed by measuring the unhydrolyzed lactofer- rin in fecal extracts of babies [92, 93]. Nevertheless, the degradation of lactoferrin during the gastrointestinal tract could also be beneficial. It has been reported that 9 Current Issues and Advances in the Dairy Industry strong antibacterial peptides such as lactoferricin and lactoferrampin are produced by its pepsin hydrolysis [94, 95]. This further benefits the utilization of lactoferrin in high value food products such as infant formula, nutritional supplements, and other formulations that aim at delivering lactoferrin through oral administration. A commonly accepted method to protect lactoferrin during digestion is microen- capsulation. In this method, a protective matrix is created around the lactoferrin core. Food grade proteins (e.g., bovine serum albumin, β- lactoglobulin) and polysaccha- rides (e.g., pectin, carrageenan, sodium alginate, gum Arabic) are commonly used as the shell materials. This core-shell structure excellently protects lactoferrin from the harsh environment prevailing in the human digestive system. The microencapsulation also helps achieve targeted and controlled release of lactoferrin by simply using shell materials with suitable properties. p p Based on in vivo studies, oral administration of lactoferrin to rodents significantly decreased the chemically induced carcinogenesis in various organs such as the breast, esophagus, tongue, lung, liver, colon, bladder, and hindered angiogenesis [78]. During the past two decades, many animal and human studies have proved that orally administered Lactoferrin exerts many beneficial effects on the health of animals and humans [75]. p p Based on in vivo studies, oral administration of lactoferrin to rodents significantly decreased the chemically induced carcinogenesis in various organs such as the breast, esophagus, tongue, lung, liver, colon, bladder, and hindered angiogenesis [78]. 4. Conclusion Lactoferrin, a multifunctional ingredient amply found in camel milk. It has numerous applications as a natural antimicrobial food additive and pharmaceutical agent. Camel milk lactoferrin has unique antimicrobial, antioxidant, anti-infective and anti-cancer activity. It can be used as a natural alternative to chemical antibiotics. Camel milk also been suggested for weight management. Lactoferrin from the milk of different indigenous species is being increasingly used as a specialty ingredient in the dairy industry. Lactoferrin can be used for biopreservation of foods such as milk, meat, fresh-cut fruits and vegetables, and their products to increase shelf life, control diseases and enhance public health. Indeed, our feeling is that camel milk lactoferrin can be used in synergy with both, conventional therapies and recent advancements allowing many therapeutic agents with potential side effect to be administered at lower, more sustainable doses. 3.6 Lactoferrin industries in the world Human and bovine lactoferrin is generally recognized as a safe substance (GRAS) by the Food and Drug Administration (FDA, USA). Some pharmaceutical industries (e.g., Morinaga Milk Industry Co LTD Venture LLC, Ventria Bioscience, AusBioMed, Biopharming, Max Biocare, etc.) are into commercialization of human and bovine Lactoferrin related products such as nutraceuticals and vitamin supplements for pedi- atric use. Also are being produced baby foods, beverages, and a cell growth promoting adjuncts for better child development. According to Global Market Insights Inc. report, the global lactoferrin powder revenue size was US$195 million (€164 m) in 2020, which is set to surpass US$315 million (€364.1 m) by 2027 and is expected to register over 7.7% CAGR between 2021 and 2027. Owing to the anti-inflammatory attribute of lactoferrin its market is likely to surpass 70 Million USD by 2027. Its antiviral efficacy is being increasingly recognized during the COVID-19 pandemic. Furthermore, its immunomodulatory and anti-inflammatory capability is expected to raise product demand in an unprec- edented manner from the pharmaceutical sector. It is estimated that the lactoferrin industry from the pharmaceutical application would actually exceed 53.78 Million USD by 2027. The global Lactoferrin Market is anticipated to attain substantial growth by the end of the forecast period (2021–2025). Lactoferrin has also been used in different products, such as probiotics, supplemental tablets, cosmetics, and as a natural solubilizer of iron in food. It is also used in the treatment of diverse carcinomas, severe sepsis, and diabetic foot ulcers. Numerous attributes of lactoferrin, such as its iron absorption ability, antibacterial, anti-inflammatory, antioxidant, and immunity-boosting capabilities, are likely to pro- vide promising opportunities for the lactoferrin industry. The ability of lactoferrin to prevent biofilm formation helps inhibiting the growth of bacteria. This can lead to an enhanced product demand owing to its therapeutic applications. The higher suscepti- bility of infections in infants and newborns due to an underdeveloped immune system can be supplemented by the lactoferrin industry. Growing demand for lactoferrin from physical fitness and sports nutrition application is likely to drive the growth of 10 Medicinal Potential of Camel Milk Lactoferrin DOI: http://dx.doi.org/10.5772/intechopen.108316 f f DOI: http://dx.doi.org/10.5772/intechopen.108316 lactoferrin capsules during the forecast period. Increasing instances of digestive and gastric disorders should boost the demand for lactoferrin as an anti-inflammatory ingredient. Acknowledgements The authors would like to acknowledge the Birla Institute of Technology and Science, Pilani (BITS Pilani), Pilani Campus, Rajasthan for the infrastructure sup- port. NM would like to thank the Department of Science and Technology (DST), India for the Innovation in Science Pursuit for Inspired Research [INSPIRE] fellow- ship [DST/INSPIRE Fellowship/2016/IF160137]. Conflict of interest The authors declare no conflict of interest. Author details Neelam Mahala, Aastha Mittal and Uma S. Dubey* Neelam Mahala, Aastha Mittal and Uma S. Dubey* Department of Biological Sciences, Birla Institute of Technology of Science (BITS), Pilani, Rajasthan, India y Department of Biological Sciences, Birla Institute of Technology of Science (BITS), Pilani, Rajasthan, India *Address all correspondence to: uma@pilani.bits-pilani.ac.in © 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 11 Current Issues and Advances in the Dairy Industry References [1] El-Hatmi H, Girardet JM, Gaillard JL, et al. Characterisation of whey proteins of camel (Camelus dromedarius) milk and colostrum. Small Ruminant Research. 2007;70:267-271 to the nutrition of cow milk allergic children? Small Ruminant Research. 2009;82:1-6 [9] Hamad EM, Abdel-Rahi EA, Romeih EA. Beneficial effect of camel Milk on liver and kidneys function in diabetic Sprague-Dawley rats. International Journal of Dairy Science. 2011;6:190-197 [9] Hamad EM, Abdel-Rahi EA, Romeih EA. Beneficial effect of camel Milk on liver and kidneys function in diabetic Sprague-Dawley rats. International Journal of Dairy Science. 2011;6:190-197 [2] Ebrahim F, Fellah A, Eldarhobi S, et al. Purification of lactoferrin from camel colostrum and protein profiles of camel and bovine Milk. Alexendar Journal of Veterinary Science. 2019;60:67 [10] Faye B, Bengoumi M, Al-Masaud A, et al. Comparative milk and serum cholesterol content in dairy cow and camel. Journal of King Saudi University Science. 2015;27:168-175 [3] El-F Fakharany EM, Tabll A, Abd A, et al. Potential activity of camel milk- amylase and lactoferrin against Hepatitis C virus infectivity in Hepg2 and lymphocytes. 2008;8:101-109 [11] Agamy ES, Ruppanner R, Ismail A, et al. Antibacterial and antiviral activity of camel milk protective proteins. Journal of Dairy Research. 1992;59:169-175 [11] Agamy ES, Ruppanner R, Ismail A, et al. Antibacterial and antiviral activity of camel milk protective proteins. Journal of Dairy Research. 1992;59:169-175 [11] Agamy ES, Ruppanner R, Ismail A, et al. Antibacterial and antiviral activity of camel milk protective proteins. Journal of Dairy Research. 1992;59:169-175 [4] Cutone A, Colella B, Pagliaro A, et al. Native and iron-saturated bovine lactoferrin differently hinder migration in a model of human glioblastoma by reverting epithelial-to-mesenchymal transition-like process and inhibiting interleukin-6/STAT3 axis. Cellular Signalling. 2020;65:109461 [12] Konuspayeva G, Faye B, Loiseau G, et al. Lactoferrin and immunoglobulin contents in camel’s milk (Camelus bactrianus, campus dromedarius, and hybrids) from Kazakhstan. Journal of Dairy Science. 2007;90:38-46 [5] Habib HM, Ibrahim WH, Schneider- Stock R, et al. Camel milk lactoferrin reduces the proliferation of colorectal cancer cells and exerts antioxidant and DNA damage inhibitory activities. Food Chemistry. 2013;141:148-152 [13] Konuspayeva G, Faye B, Loiseau G. et al, The composition of camel milk: A meta-analysis of the literature data. Journal of Food Composition and Analysis. 2009;22(2):95-101. DOI: 10.1016/j.jfca.2008.09.008 [13] Konuspayeva G, Faye B, Loiseau G. et al, The composition of camel milk: A meta-analysis of the literature data. Journal of Food Composition and Analysis. 2009;22(2):95-101. [8] El-Agamy EI, Nawar M, Shamsia SM, et al. Are camel milk proteins convenient [23] Mittal A, Mahala N, Krishna KV, et al. Calcium chloride linked camel milk derived casein nanoparticles for the delivery of sorafenib in hepatocarcinoma cells. BIOCELL. 2021;46(1):127-136 References DOI: 10.1016/j.jfca.2008.09.008 [6] Dubey U, Lal M, Mittal A, et al. Therapeutic potential of camel Milk. Emirates Journal of Food Agriculture. 2016;28:164 [14] Kaskous S. Importance of camel milk for human health. Emirates Journal of Food Agriculture. 2016;28:158-163 [7] Agrawal RP, Tantia P, Jain S, et al. Camel milk: A possible boon for type 1 diabetic patients. Cellular and Molecular Biology. 2013;59:99-107 [15] Davicco MJ, Barlet JP, Davicco MJ, et al. Influence of 1α-hydroxycholecalciferol on calcium and phosphorus concentration in camel milk. Journal of Dairy Research. 1994;61:567-571 [8] El-Agamy EI, Nawar M, Shamsia SM, et al. Are camel milk proteins convenient [8] El-Agamy EI, Nawar M, Shamsia SM, et al. Are camel milk proteins convenient 12 Medicinal Potential of Camel Milk Lactoferrin DOI: http://dx.doi.org/10.5772/intechopen.108316 of camel milk proteins: A review. Journal of Dairy Research. 2016;83:422-429 [25] Siqueiros-Cendón T, Arévalo- Gallegos S, Iglesias-Figueroa BF, et al. Immunomodulatory effects of lactoferrin. Acta Pharmacologica Sinica. 2014;35:557-566 of camel milk proteins: A review. Journal of Dairy Research. 2016;83:422-429 [16] Yagil DVM. Camel milk and its unique anti-diarrheal Properties. 15, http://www.crohnscanada.org, [Accessed May 26, 2022] [16] Yagil DVM. Camel milk and its unique anti-diarrheal Properties. 15, http://www.crohnscanada.org, [Accessed May 26, 2022] [25] Siqueiros-Cendón T, Arévalo- Gallegos S, Iglesias-Figueroa BF, et al. Immunomodulatory effects of lactoferrin. Acta Pharmacologica Sinica. 2014;35:557-566 [17] EI el A, R R, A I et al. Antibacterial and antiviral activity of camel milk protective proteins. The Journal of Dairy Research. 1992;59:169-175 [26] Turin CG, Ochoa TJ. The role of maternal breast Milk in preventing infantile Diarrhea in the developing world. Current Tropical Medical Report. 2014;1:97-105 [18] Galali Y, Al-Dmoor HM. Journal of family medicine and disease prevention miraculous properties of camel Milk and perspective of modern science. Journal of Family Medicine and Disease Prevention. 2019;5:95 [18] Galali Y, Al-Dmoor HM. Journal of family medicine and disease prevention miraculous properties of camel Milk and perspective of modern science. Journal of Family Medicine and Disease Prevention. 2019;5:95 [27] Baker EN, Baker HM. Molecular structure, binding properties and dynamics of lactoferrin. Cellular and Molecular Life Sciences. 2005;62:2531-2539 [19] Muyldermans S. Nanobodies: Natural single-domain antibodies. Annual Review of Biochemistry. 2013;82:775-797 [28] Kanyshkova TG, Buneva VN, Nevinsky GA. Lactoferrin and its biological functions. Biochemistry (Mosc). 2001;66:1-7 [20] Korashy HM, el Gendy MAM, Alhaider AA, et al. Camel milk modulates the expression of aryl hydrocarbon receptor-regulated genes, Cyp1a1, Nqo1, and Gsta1, in murine hepatoma Hepa 1c1c7 cells. References Journal of Biomedicine Biotechnology. 2012:782642 [20] Korashy HM, el Gendy MAM, Alhaider AA, et al. Camel milk modulates the expression of aryl hydrocarbon receptor-regulated genes, Cyp1a1, Nqo1, and Gsta1, in murine hepatoma Hepa 1c1c7 cells. Journal of Biomedicine Biotechnology. 2012:782642 [29] Lönnerdal B, Iyer S. Lactoferrin: Molecular structure and biological function. Annual Review of Nutrition. 1995;15:93-110 [21] Haddadin MSY, Gammoh SI, Robinson RK. Seasonal variations in the chemical composition of camel milk in Jordan. The Journal of Dairy Research. 2008;75:8-12 [21] Haddadin MSY, Gammoh SI, Robinson RK. Seasonal variations in the chemical composition of camel milk in Jordan. The Journal of Dairy Research. 2008;75:8-12 [30] Cragg GM, Schepartz SA, Suffness M, et al. The taxol supply crisis. New NCI policies for handling the large-scale production of novel natural product anticancer and anti-HIV agents. Journal of Natural Products. 1993;56:1657-1668 [22] Alhaider AA, Abdel Gader AGM, Almeshaal N, et al. Camel milk inhibits inflammatory angiogenesis via downregulation of proangiogenic and proinflammatory cytokines in mice. APMIS. 2014;122:599-607 [31] Samarghandian S, Shabestari MM. DNA fragmentation and apoptosis induced by safranal in human prostate cancer cell line. Indian Journal of Urology. 2013;29:177-183 [23] Mittal A, Mahala N, Krishna KV, et al. Calcium chloride linked camel milk derived casein nanoparticles for the delivery of sorafenib in hepatocarcinoma cells. BIOCELL. 2021;46(1):127-136 [32] Adlerova L, Bartoskova A, Faldyna M. Lactoferrin: A review. Veterinary Medicine (Praha). 2008;53:457-468 [32] Adlerova L, Bartoskova A, Faldyna M. Lactoferrin: A review. Veterinary Medicine (Praha). 2008;53:457-468 [33] Rosa L, Cutone A, Lepanto MS, et al. Lactoferrin: A natural glycoprotein [33] Rosa L, Cutone A, Lepanto MS, et al. Lactoferrin: A natural glycoprotein [33] Rosa L, Cutone A, Lepanto MS, et al. Lactoferrin: A natural glycoprotein [24] Hailu Y, Hansen EB, Seifu E, et al. Functional and technological properties 13 Current Issues and Advances in the Dairy Industry involved in iron and inflammatory homeostasis. International Journal of Molecular Science. 2017;18:22 involved in iron and inflammatory homeostasis. International Journal of Molecular Science. 2017;18:22 protein concentrate and lactoferrin in diethylnitrosamine-treated male albino mice. Environmental Toxicology. 2019;34:1025-1033 [34] Dashper SG, Pan Y, Veith PD, et al. Lactoferrin inhibits Porphyromonas gingivalis proteinases and has sustained biofilm inhibitory activity. Antimicrobial Agents and Chemotherapy. 2012;56:1548 [34] Dashper SG, Pan Y, Veith PD, et al. Lactoferrin inhibits Porphyromonas gingivalis proteinases and has sustained biofilm inhibitory activity. Antimicrobial Agents and Chemotherapy. 2012;56:1548 [42] Fernández-Musoles R, Castelló- Ruiz M, Arce C, et al. References Antihypertensive mechanism of lactoferrin-derived peptides: Angiotensin receptor blocking effect. Journal of Agricultural and Food Chemistry. 2014;62:173-181 [42] Fernández-Musoles R, Castelló- Ruiz M, Arce C, et al. Antihypertensive mechanism of lactoferrin-derived peptides: Angiotensin receptor blocking effect. Journal of Agricultural and Food Chemistry. 2014;62:173-181 [35] Gibbons JA, Kanwar JR, Kanwar RK. Iron-free and iron-saturated bovine lactoferrin inhibit survivin expression and differentially modulate apoptosis in breast cancer. BMC Cancer. 2015;15:1-16 [43] Artym J, Zimecki M, Kruzel ML. Lactoferrin for prevention and treatment of anemia and inflammation in pregnant women: A comprehensive review. Biomedicines. 2021;9 [43] Artym J, Zimecki M, Kruzel ML. Lactoferrin for prevention and treatment of anemia and inflammation in pregnant women: A comprehensive review. Biomedicines. 2021;9 [36] Kawai K, Shimazaki K, Higuchi H, et al. Antibacterial activity of bovine lactoferrin hydrolysate against mastitis pathogens and its effect on superoxide production of bovine neutrophils. Zoonoses and Public Health. 2007;54:160-164 [44] Li W, Zhu S, Hu J. Bone regeneration is promoted by orally administered bovine lactoferrin in a rabbit tibial distraction osteogenesis model. Clinical Orthopaedics and Related Research. 2015;473:2383-2393 [44] Li W, Zhu S, Hu J. Bone regeneration is promoted by orally administered bovine lactoferrin in a rabbit tibial distraction osteogenesis model. Clinical Orthopaedics and Related Research. 2015;473:2383-2393 [45] Gao R, Watson M, Callon KE, et al. Local application of lactoferrin promotes bone regeneration in a rat critical-sized calvarial defect model as demonstrated by micro-CT and histological analysis. Journal of Tissue Engineering and Regenerative Medicine. 2018;12:e620-e626 [45] Gao R, Watson M, Callon KE, et al. Local application of lactoferrin promotes bone regeneration in a rat critical-sized calvarial defect model as demonstrated by micro-CT and histological analysis. Journal of Tissue Engineering and Regenerative Medicine. 2018;12:e620-e626 [37] Actor J, Hwang S-A, Kruzel M. Lactoferrin as a natural immune modulator. Current Pharmaceutical Design. 2009;15:1956-1973 [37] Actor J, Hwang S-A, Kruzel M. Lactoferrin as a natural immune modulator. Current Pharmaceutical Design. 2009;15:1956-1973 [38] Majka G, Więcek G, Śróttek M, et al. The impact of lactoferrin with different levels of metal saturation on the intestinal epithelial barrier function and mucosal inflammation. Biometals. 2016;29:1019 [46] Sun J, Ren F, Xiong L, et al. Bovine lactoferrin suppresses high-fat diet induced obesity and modulates gut microbiota in C57BL/6J mice. Journal of Functional Foods. 2016;22:189-200 [39] Lu YC, Yeh WC, Ohashi PS. LPS/ TLR4 signal transduction pathway. Cytokine. 2008;42:145-151 [47] Elzoghby AO, Abdelmoneem MA, Hassanin IA, et al. References Lactoferrin, a multi-functional glycoprotein: Active therapeutic, drug nanocarrier & targeting ligand. Biomaterials. 2020;263 [47] Elzoghby AO, Abdelmoneem MA, Hassanin IA, et al. Lactoferrin, a multi-functional glycoprotein: Active therapeutic, drug nanocarrier & targeting ligand. Biomaterials. 2020;263 [40] Kruzel ML, Bacsi A, Choudhury B, et al. Lactoferrin decreases pollen antigen-induced allergic airway inflammation in a murine model of asthma. Immunology. 2006;119:159-166 [48] Li YQ , Guo C. A review on lactoferrin and central nervous system diseases. Cell. 2021;10 [41] Mohammed MM, Ramadan G, Zoheiry MK, et al. Antihepatocarcinogenic activity of whey [49] Kell DB, Heyden EL, Pretorius E. The biology of lactoferrin, an Iron-binding [49] Kell DB, Heyden EL, Pretorius E. The biology of lactoferrin, an Iron-binding 14 Medicinal Potential of Camel Milk Lactoferrin DOI: http://dx.doi.org/10.5772/intechopen.108316 protein that can help defend against viruses and Bacteria. Frontiers in Immunology. 2020;11:1221 protein that can help defend against viruses and Bacteria. Frontiers in Immunology. 2020;11:1221 [50] Pan S, Weng H, Hu G, et al. Lactoferrin may inhibit the development of cancer via its immunostimulatory and immunomodulatory activities (review). International Journal of Oncology. 2021;59:1-11 [58] Valenti P, Antonini G. Lactoferrin: An important host defence against microbial and viral attack. Cellular and Molecular Life Sciences. 2005;62:2576-2587 [50] Pan S, Weng H, Hu G, et al. Lactoferrin may inhibit the development of cancer via its immunostimulatory and immunomodulatory activities (review). International Journal of Oncology. 2021;59:1-11 [50] Pan S, Weng H, Hu G, et al. Lactoferrin may inhibit the development of cancer via its immunostimulatory and immunomodulatory activities (review). International Journal of Oncology. 2021;59:1-11 [59] Redwan ERM, Tabll A. Camel lactoferrin markedly inhibits hepatitis C virus genotype 4 infection of human peripheral blood leukocytes. Journal of Immunoassay & Immunochemistry. 2007;28:267-277 [59] Redwan ERM, Tabll A. Camel lactoferrin markedly inhibits hepatitis C virus genotype 4 infection of human peripheral blood leukocytes. Journal of Immunoassay & Immunochemistry. 2007;28:267-277 [51] Kruzel ML, Zimecki M, Actor JK. Lactoferrin in a context of inflammation- induced pathology. Frontiers in Immunology. 2017;8:1438 [60] Rasheed Z. Medicinal values of bioactive constituents of camel milk: A concise report. International Journal of Health Science (Qassim). 2017;11:1 [52] Wolf JS, Li D, Taylor RJ, et al. Lactoferrin inhibits growth of malignant tumors of the head and neck. ORL: Journal for Otorhinolaryngology and Its Related Specialties. 2003;65:245-249 [61] Rasheed N, Alghasham A, Rasheed Z. [65] Sugihara Y, Zuo X, Takata T, et al. Inhibition of DMH-DSS-induced colorectal cancer by liposomal bovine lactoferrin in rats. Oncology Letters. 2017;14:5688-5694 [65] Sugihara Y, Zuo X, Takata T, et al. Inhibition of DMH-DSS-induced colorectal cancer by liposomal bovine lactoferrin in rats. Oncology Letters. 2017;14:5688-5694 [60] Rasheed Z. Medicinal values of bioactive constituents of camel milk: A concise report. International Journal of Health Science (Qassim). 2017;11:1 References Lactoferrin from Camelus dromedarius inhibits nuclear transcription factor-kappa B activation, Cyclooxygenase-2 expression and prostaglandin E2 production in stimulated human chondrocytes, 2016 [53] Bezault J, Bhimani R, Wiprovnick J, et al. Human lactoferrin inhibits growth of solid tumors and development of experimental metastases in mice. AACR, 1994. https://cancerres.aacrjournals. org/content/54/9/2310.short. [Accessed March 5, 2022] [62] Tsuda H, Kozu T, Iinuma G, et al. Cancer prevention by bovine lactoferrin: From animal studies to human trial. Biometals. 2010;23:399-409 [62] Tsuda H, Kozu T, Iinuma G, et al. Cancer prevention by bovine lactoferrin: From animal studies to human trial. Biometals. 2010;23:399-409 [54] Wang WP, Iigo M, Sato J, et al. Activation of intestinal mucosal immunity in tumor-bearing mice by lactoferrin. Japanese Journal of Cancer Research. 2000;91:1022-1027 [54] Wang WP, Iigo M, Sato J, et al. Activation of intestinal mucosal immunity in tumor-bearing mice by lactoferrin. Japanese Journal of Cancer Research. 2000;91:1022-1027 [63] Zhang Y, Lima CF, Rodrigues LR. Anticancer effects of lactoferrin: Underlying mechanisms and future trends in cancer therapy. Nutrition Reviews. 2014;72:763-773 [55] Fujita KI, Matsuda E, Sekine K, et al. Lactoferrin enhances Fas expression and apoptosis in the colon mucosa of azoxymethane-treated rats. Carcinogenesis. 2004;25:1961-1966 [64] Hegazy RR, Mansour DF, Salama AA, et al. Regulation of PKB/Akt- pathway in the chemopreventive effect of lactoferrin against diethylnitrosamine- induced hepatocarcinogenesis in rats. Pharmacological Reports. 2019;71:879-891 [56] Puddu P, Latorre D, Carollo M, et al. Bovine lactoferrin counteracts toll-like receptor mediated activation signals in antigen presenting cells. PLoS One. 2011;6:22504 [65] Sugihara Y, Zuo X, Takata T, et al. Inhibition of DMH-DSS-induced colorectal cancer by liposomal bovine lactoferrin in rats. Oncology Letters. 2017;14:5688-5694 [57] Puddu P, Valenti P, Gessani S. Immunomodulatory effects of lactoferrin on antigen presenting cells. Biochimie. 2009;91:11-18 15 Current Issues and Advances in the Dairy Industry Modulation of xenobiotic-metabolizing enzymes and redox status during chemoprevention of hamster buccal carcinogenesis by bovine lactoferrin. Nutrition. 2006;22:940-946 Modulation of xenobiotic-metabolizing enzymes and redox status during chemoprevention of hamster buccal carcinogenesis by bovine lactoferrin. Nutrition. 2006;22:940-946 [66] Tanaka T, Kawabata K, Kohno H, et al. Chemopreventive effect of bovine lactoferrin on 4-nitroquinoline 1-oxide- induced tongue carcinogenesis in male F344 rats. Japanese Journal of Cancer Research. 2000;91:25-33 [66] Tanaka T, Kawabata K, Kohno H, et al. Chemopreventive effect of bovine lactoferrin on 4-nitroquinoline 1-oxide- induced tongue carcinogenesis in male F344 rats. Japanese Journal of Cancer Research. 2000;91:25-33 [75] Duarte DC, Nicolau A, Teixeira JA, et al. [82] Berlutti F, Pantanella F, Natalizi T, et al. Antiviral properties of lactoferrin--a natural immunity molecule. Molecules. 2011;16:6992-7012 References The effect of bovine milk lactoferrin on human breast cancer cell lines. Journal of Dairy Science. 2011;94:66-76 [67] Ushida Y, Sekine K, Kuhara T, et al. Possible Chemopreventive effects of bovine lactoferrin on Esophagus and lung carcinogenesis in the rat. Japanese Journal of Cancer Research. 1999;90:262-267 [76] Ye Q , Zheng Y, Fan S, et al. Lactoferrin deficiency promotes colitis- associated colorectal dysplasia in mice. PLoS One. 2014;9 [76] Ye Q , Zheng Y, Fan S, et al. Lactoferrin deficiency promotes colitis- associated colorectal dysplasia in mice. PLoS One. 2014;9 [68] Shimamura M, Yamamoto Y, Ashino H, et al. Bovine lactoferrin inhibits tumor-induced angiogenesis. International Journal of Cancer. 2004;111:111-116 [77] Tsuda H, Sekine K, Fujita KI, et al. Cancer prevention by bovine lactoferrin and underlying mechanisms--a review of experimental and clinical studies. Biochemistry and Cell Biology. 2002;80:131-136 [69] Gibbons JA, Kanwar RK, Kanwar JR. Lactoferrin and cancer in different cancer models. Frontiers in Bioscience- Scholar. 2011;3:1080-1088 [78] Iigo M, Alexander DB, Long N, et al. Anticarcinogenesis pathways activated by bovine lactoferrin in the murine small intestine. Biochimie. 2009;91:86-101 [70] Madan RA, Tsang K-Y, Bilusic M, et al. Effect of talactoferrin alfa on the immune system in adults with non- small cell lung cancer. The Oncologist. 2013;18:821-822 [79] Xu XX, Jiang HR, Li HB, et al. Apoptosis of stomach cancer cell SGC- 7901 and regulation of Akt signaling way induced by bovine lactoferrin. Journal of Dairy Science. 2010;93:2344-2350 [71] Kanwar JR, Roy K, Patel Y, et al. Multifunctional iron bound lactoferrin and nanomedicinal approaches to enhance its bioactive functions. Molecules. 2015;20:9703-9731 [80] Habib HM, Ibrahim S, Zaim A, et al. The role of iron in the pathogenesis of COVID-19 and possible treatment with lactoferrin and other iron chelators. Biomedicine and Pharmacotherapy. 2021;136:11228 [72] Kozu T, Iinuma G, Ohashi Y, et al. Effect of orally administered bovine lactoferrin on the growth of adenomatous colorectal polyps in a randomized, placebo-controlled clinical trial. Cancer Prevention Research. 2009;2:975-983 [81] Legrand D, Elass E, Carpentier M, et al. Lactoferrin: A modulator of immune and inflammatory responses. Cellular and Molecular Life Sciences. 2005;62:2549-2559 [81] Legrand D, Elass E, Carpentier M, et al. Lactoferrin: A modulator of immune and inflammatory responses. Cellular and Molecular Life Sciences. 2005;62:2549-2559 [73] de Mejia EG, Dia VP. The role of nutraceutical proteins and peptides in apoptosis, angiogenesis, and metastasis of cancer cells. Cancer and Metastasis Reviews. References 2010;29:511-528 [82] Berlutti F, Pantanella F, Natalizi T, et al. Antiviral properties of lactoferrin--a natural immunity molecule. Molecules. 2011;16:6992-7012 [82] Berlutti F, Pantanella F, Natalizi T, et al. Antiviral properties of lactoferrin--a natural immunity molecule. Molecules. 2011;16:6992-7012 [74] Chandra Mohan KVP, Kumaraguruparan R, Prathiba D, et al. 16 Medicinal Potential of Camel Milk Lactoferrin DOI: http://dx.doi.org/10.5772/intechopen.108316 [83] Salaris C, Scarpa M, Elli M, et al. Protective effects of lactoferrin against SARS-CoV-2 infection in vitro. Nutrients. 2021;13:328 [83] Salaris C, Scarpa M, Elli M, et al. Protective effects of lactoferrin against SARS-CoV-2 infection in vitro. Nutrients. 2021;13:328 [91] Jiang R, Lopez V, Kelleher SL, et al. Apo- and holo-lactoferrin are both internalized by lactoferrin receptor via clathrin-mediated endocytosis but differentially affect ERK-signaling and cell proliferation in Caco-2 cells. Journal of Cellular Physiology. 2011;226:3022-3031 [84] Wang Y, Wang P, Wang H, et al. Lactoferrin for the treatment of COVID-19 (review). Experimental and Therapeutic Medicine. 2020;20:1-1 [92] Gisbert JP, McNicholl AG, Gomollon F. Questions and answers on the role of fecal lactoferrin as a biological marker in inflammatory bowel disease. Inflammatory Bowel Diseases. 2009;15:1746-1754 [85] Morniroli D, Consales A, Crippa BL, et al. The antiviral properties of human milk: A multitude of defence tools from mother nature. Nutrients. 2021;13:694 [86] Zuccotti GV, Vigano A, Borelli M, et al. Modulation of innate and adaptive immunity by lactoferrin in human immunodeficiency virus (HIV)-infected, antiretroviral therapy-naïve children. International Journal of Antimicrobial Agents. 2007;29:353-355 [93] Spik G, Coddeville B, Mazurier J, et al. Primary and three-dimensional structure of lactotransferrin (lactoferrin) glycans. Advances in Experimental Medicine and Biology. 1994;357:21-32 [94] Lizzi AR, Carnicelli V, Clarkson MM, et al. Bovine lactoferrin and its tryptic peptides: Antibacterial activity against different species. Applied Biochemistry and Microbiology. 2016;52:435-440 [87] Leader B, Baca QJ, Golan DE. Protein therapeutics: A summary and pharmacological classification. Nature Reviews Drug Discovery. 2007;7:21-39 [87] Leader B, Baca QJ, Golan DE. Protein therapeutics: A summary and pharmacological classification. Nature Reviews Drug Discovery. 2007;7:21-39 [88] Yao X, Bunt C, Cornish J, et al. Oral delivery of bovine lactoferrin using pectin- and chitosan-modified liposomes and solid lipid particles: Improvement of stability of lactoferrin. Chemical Biology & Drug Design. 2015;86:466-475 [95] Bellamy W, Takase M, Yamauchi K, et al. Identification of the bactericidal domain of lactoferrin. Biochimica et Biophysica Acta. 1992;1121:130-136 [89] Yamano E, Miyauchi M, Furusyo H, et al. Inhibitory effects of orally administrated liposomal bovine lactoferrin on the LPS-induced osteoclastogenesis. References Laboratory Investigation. 2010;90:1236-1246 [90] Takeuchi T, Jyonotsuka T, Kamemori N, Kawano G, Shimizu H, Ando K et al. Enteric-formulated lactoferrin was more effectively transported into blood circulation from gastrointestinal tract in adult rats. Experimental Physiology. 2006;91:139-145 17
https://openalex.org/W4229503185
https://zenodo.org/records/2301186/files/article.pdf
German
null
Saturnring
Astronomische Nachrichten
1,921
public-domain
993
Der Saturnring im Februar 1921. Das Verschwindgn und Wiedererscheinen des Saturn- ringes im Febr. d. J. ist hier am 6 0 cm-Refraktor bei bester Luft rnit aller Sorgfalt verfolgt worden, und wenn auch keine Messungen der Lange der Ringprojektion vorliegen, so lassen doch die beiden weiter unten angefiihrten Schatzungen der Ansenlange nicht den geringsten Zweifel daran aufkommen, dafl hier in der Zeit zwischen dem 21. und 25. Febr. auch niyht die Spur eines neuen AuDenringes zu sehen war. hinweisen, und eine direkte Beobachtung der Erscheinung zu erhoffen war, was allerdings nicht eingetreten ist. Um das Abwarten giinstigsten Luftzustandes nicht ganz unfruchtbar zu gestalten, habe ich die Zwischenzeit rnit photometrischen hlessungen der Trabanten ausgefuJlt. Dabei ist Saturn dauernd links und rechts aus dem Gesichtsfelde gebracht worden, wobei dann die Ansen und schwacheren Trabanten besonders deutlich hervortraten. Bei der Aufmerksamkeit, mit der Sa- turn hier letzthin stundenlang am GroDen Refraktor verfolgt und nachgesehen worden ist, ware mir auch die geringste Aufhellung in der A4nsenfortsetzung nicht entgangen. Am 2 3 . Febr. nahm Dr. Baade, am 24. Febr. Prof. Schorr an den Beobachtungen teil. Am 2 2 . Febr. 8h m. 2: Gr. war der Ring bereits als iiberaus diinne aber scharfe Linie zu erkennen rnit allen Einzelheiten der folgenden Tage. Selbst die scheinbare Keulenform der Ansen, die durch die verschiedene Hellig- keit der Lichtlinie hervorgerufen wird, war merkwiirdiger. weise bereits deutlich sichtbar. Ich schatzte jede Anse = 0.6 5 des Saturndurchmessers, was eine Lange der Lichtlinie von 44" ergibt, in genauer Ubereinstimmung rnit der Ephemeride. Helle Piinktchen im Ring sind auch hier beobachtet worden, haben sich aber nach einigen Stunden als Trabanten [Ence- ladus, Dione) identifizieren lassen. Merkwiirdigerweise erwahnt Herr Meyermunn in seinen Beobachtungen rnit keinem Wort die Trabantenstellung, die fur die Wahrnehmung einer SO zarten Erscheinung doch von groi3er Bedeutung ist, Febr. 2 2 stand westlich Tethys in einem Abstande, der dem Radius des iMeyermannschen R i q e s entspricht, und mu0 recht gestort haben. Febr. 2 3 konnen Rhea im Westen, Tethys und Dione im Osten den Eindruck hervorgerufen haben, und Febr. 24 standen Tethys, Dione und Rhea dem alten Ring so nahe, daO die neue Anse direkt uber diese Monde hinweggegangen sein muDte. Bemerkt sei noch, dafl auch' die in Gottingen beobachtete helle Projek- tion aer Ringlinie auf Saturn hier vergeblich gesucht worden ist. 509 3 509 3 509 3 74 7 3 schaften einer solchen Flache werden die Unsicherheiten der Bestimmung herabdrucken und zu anderen Werten fiihren. Der GroDenordnung nach werden obige Daten jedoch bereits der Wirklichkeit nahe kommen. man die Dichte der Korper wie die des Saturn zu 0.66 an, so ware die Masse des AuDenringes i/34000 der Saturnmasse. Die Annahme einer den wirklichen Verhaltnissen naher kommen- den Verteilung in der Ringflache und der Anzahl der Korper sowie die bessere Beriicksichtigung der photometrischen Eigen- B. Meyermann. Der Saturnring im Februar 1921. Es liegt offenbar eine Verwechselung rnit der schmalen Aquatorialzone des Planeten vor, was nicht besonders auf- fallt, da diese in den kritischen Tagen nur siidlich von dem schwarzen Schattenstrich eine betrachtlichere Helligkeit zejgte. In den Abendstunden des 23. Febr. war die Keulen- form der Ansen bereits sehr deutlich ausgesprochen. Ihre Lange wurde zu je 0.6 bis 0.65 des Saturndurchmessers ge- schatzt, was wiederum vollkommen zum normalen Ring pafit. An diesem Tage ist besonders nach einer Fortsetzung der Ansen gesucht worden, und ich glaubte tatsachlich im Osten eine kaum I" lange auOerst diinne scharf abschneidende Fort- setzung zu bemerken. Es war aber nur eine durch Mimas hervorgerufene Tauschung, ahnlich der Tropfenerscheinung bei Planeten- und Trabantendurchgangen. Eine nicht alltagliche Beobachtung sei noch an dieser Stelle erwahnt. Febr. 2 5 fand eine sehr enge Konjunktion von Tethys und Dione statt. I zh 36mo m. 2. Gr., vielleioht schon I"' friiher, waren die beiden Monde bei 400facher Vergroflerung nicht mehr zu trennen. Die Loslosung erfolgte 1 2 ~ 38m5. Im Augenblicke der Konjunktion glich das Ge- samtlicht der Trabanten vollkommen der Rhea, was rnit den vorangehenden photometrischen Messungen nur dann im Ein- klang steht, wenn man eine Teilbedeckung annimmt. Das be- obachtete Gesamtlicht war zwar nur um o?; geringer als das berechnete, doch ist dieser Unterschied recht gut verburgt. Der 24. und 2 5 . Febr. boten an den Ringen auDer -einer Verstarkung der Ansen nichts bemerkenswertes. Auf die Erscheinung von Lichtpunkten, Knoten u. s. w. ist sorg- faltig geachtet worden. In den besten Momenten erschien die Linie vollig gleichmaDig, iiberall gleich dunn, aber mit einem Helligkeitsmaxiinuni dort, wo auch der geoffnete Ring ein solches zeigt. Die bekannten Knoten in den Ansen treten also nur dann auf, wenn wir die Ringprojektion von der unbeleuchteten Seite sehen. Die standige Verfolgung der Lichtlinie erfolgte hier aus dem Grunde, weil die Schatten- anomalien bei geoffnetem Ring auf einen Ebenenunterschied des auDeren und inneren Ringes am Rande der Cassinispalte K. Gra8 Bergedorf, 1 9 2 1 MLrz 12. Bergedorf, 1 9 2 1 MLrz 12. Bergedorf, 1 9 2 1 MLrz 12. K. Gra8 Wien, Uraniasternwarte, I g z I MIrz 13. lich - was ich zur Rechtfertigung dieser meiner Meldung hervorheben mochte - uberraschte, fiir eine Tauschung und legte ihr derart wenig Gewicht bei, daO ich sie nicht einmal im Notizbuch vermerkte. Ich kann deshalb das Datum der Beobachtung nicht mit Sicherheit angeben. In unserem Achtzoller hatte ich in den Tagen urn den 2 2 . Februar auch einmal den Eindruck, den Herr B. Meyernzunn in AN 5090 wiedergegeben. Eine feine mattrot- goldene Linie zog sich weit iiber den Rand des eigentlichen Ringes hinaus. So vie1 ich mich erinnere, war dies blofl auf einer Seite des Saturn zu sehen, auf der einige Monde standen. Ich hielt die Erscheinung, so sehr sie mich eigent- lich - was ich zur Rechtfertigung dieser meiner Meldung hervorheben mochte - uberraschte, fiir eine Tauschung und legte ihr derart wenig Gewicht bei, daO ich sie nicht einmal im Notizbuch vermerkte. Ich kann deshalb das Datum der Beobachtung nicht mit Sicherheit angeben. Wien, Uraniasternwarte, I g z I MIrz 13. 0. Thomas.
https://openalex.org/W4293053105
https://egusphere.copernicus.org/preprints/2022/egusphere-2022-130/egusphere-2022-130.pdf
English
null
Reply on RC2
null
2,022
cc-by
28,469
Abstract. Tsunamis caused by large volcanic eruptions and flanks collapsing into the sea are major hazards for nearby coastal regions. They often occur with little precursory activity, and are thus challenging to detect in a timely manner. This makes the pre- 15 emptive identification of volcanoes prone to causing tsunamis particularly important, as it allows for better hazard assessment and denser monitoring in these areas. Here, we present a catalogue of potentially tsunamigenic volcanoes in Southeast Asia and rank these volcanoes by their tsunami hazard. The ranking is based on a Multicriteria Decision Analysis (MCDA) composed of five individually weighted factors impacting flank stability and tsunami hazard. The data is sourced from geological databases, remote sensing data, historical volcano induced tsunami records and our topographic analyses, 20 mainly considering the eruptive and tsunami history, elevation relative to the distance from the sea, flank steepness, hydrothermal alteration as well as vegetation coverage. Out of 131 analysed volcanoes, we found 19 with particularly high tsunamigenic hazard potential in Indonesia (Anak Krakatau, Batu Tara, Iliwerung, Gamalama, Sangeang Api, Karangetang, Sirung, Wetar, Nila, Ruang, Serua) and Papua New Guinea (Kadovar, Ritter Island, Rabaul, Manam, Langila, Ulawun, Bam), but also in the Philippines (Didicas). While some of these volcanoes, such as Anak Krakatau, are well-known for their 25 deadly tsunamis, many others on this list are lesser known and monitored. We further performed tsunami travel time modelling on these high-hazard volcanoes, which indicates that future events could affect large coastal areas in a short time. This highlights the importance of individual tsunami hazard assessment for these volcanoes, dedicated volcanological monitoring, and the need for increased preparedness on the potentially affected coasts. Tsunamis caused by large volcanic eruptions and flanks collapsing into the sea are major hazards for nearby coastal regions. They often occur with little precursory activity, and are thus challenging to detect in a timely manner. This makes the pre- 15 emptive identification of volcanoes prone to causing tsunamis particularly important, as it allows for better hazard assessment and denser monitoring in these areas. Here, we present a catalogue of potentially tsunamigenic volcanoes in Southeast Asia and rank these volcanoes by their tsunami hazard. The ranking is based on a Multicriteria Decision Analysis (MCDA) composed of five individually weighted factors impacting flank stability and tsunami hazard. Correspondence to: Edgar U. Zorn (zorn@gfz-potsdam.de) Correspondence to: Edgar U. Zorn (zorn@gfz-potsdam.de) Identification and ranking of volcanic tsunami hazard sources in Southeast Asia Edgar U. Zorn1, Aiym Orynbaikyzy2, Simon Plank2, Andrey Babeyko1, Herlan Darmawan3, Ismail Fata Robbany2, Thomas R. Walter1 5 1German Research Centre for Geosciences GFZ, Telegrafenberg, 14473 Potsdam, Germany 2German Aerospace Center DLR, Münchenerstr. 20, 82234 Wessling, Germany 3Geophysics Study Program, Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Mada, Sekip Utara, Bulaksumur, Yogyakarta, Indonesia 10 Correspondence to: Edgar U. Zorn (zorn@gfz-potsdam.de) 1German Research Centre for Geosciences GFZ, Telegrafenberg, 14473 Potsdam, Germany 2German Aerospace Center DLR, Münchenerstr. 20, 82234 Wessling, Germany 3Geophysics Study Program, Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Bulaksumur, Yogyakarta, Indonesia 1German Research Centre for Geosciences GFZ, Telegrafenberg, 14473 Potsdam, Germany 2German Aerospace Center DLR, Münchenerstr. 20, 82234 Wessling, Germany 3Geophysics Study Program, Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Bulaksumur, Yogyakarta, Indonesia 10 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. 1 Introduction 30 While the mechanisms of this tsunami are not fully understood yet, reports suggest the interaction of acoustic and water gravity waves as a possible explanation (Somerville et al., 2022). This may be similar to airwaves attributed to tsunamis produced by Taal volcano, Philippines, in 1911 and 1965 (Paris et al., 2014 and references therein). These and many further examples emphasise that such potentially catastrophic tsunamis occur frequently and may pose a Hunga Haʻapai volcano near Tonga caused a tsunami affecting the entire Pacific Ocean, which travelled faster towards the 45 coasts than was expected. While the mechanisms of this tsunami are not fully understood yet, reports suggest the interaction of acoustic and water gravity waves as a possible explanation (Somerville et al., 2022). This may be similar to airwaves attributed to tsunamis produced by Taal volcano, Philippines, in 1911 and 1965 (Paris et al., 2014 and references therein). These and many further examples emphasise that such potentially catastrophic tsunamis occur frequently and may pose a th t f t l i h d d f kil t f th 50 severe threat for coastal regions even hundreds of kilometres away from the source. 50 As historical databases reveal, the details of the tsunami triggering source are often a subject of debate. Even for the largest and deadliest volcanogenic tsunami, at Krakatau in 1883, discussed processes include caldera collapse, pyroclastic flows into the sea, sector collapse, explosion, or combinations thereof (e.g., Yokoyama, 1981; Francis, 1985; Nomanbhoy and Satake, 1995; Maeno et al., 2006). This highlights that there are multiple ways in which a volcano can cause a tsunami, which are As historical databases reveal, the details of the tsunami triggering source are often a subject of debate. Even for the largest and deadliest volcanogenic tsunami, at Krakatau in 1883, discussed processes include caldera collapse, pyroclastic flows into the sea, sector collapse, explosion, or combinations thereof (e.g., Yokoyama, 1981; Francis, 1985; Nomanbhoy and Satake, 1995; Maeno et al., 2006). This highlights that there are multiple ways in which a volcano can cause a tsunami, which are considered a secondary volcanic hazard and result from eruptions or sector collapses of volcanic edifices (McGuire, 2006; 55 Paris, 2015). 1 Introduction 30 This may be similar to airwaves attributed to tsunamis produced by Taal volcano, Philippines, in 1911 and 1965 (Paris et al., 2014 and references therein). These and many further examples emphasise that such potentially catastrophic tsunamis occur frequently and may pose a severe threat for coastal regions even hundreds of kilometres away from the source. 50 Tsunamis are among the deadliest hazards affecting coastal regions around the world. While most tsunamis are caused by tectonic earthquakes, tsunamis induced by volcanic sources account for ~6% of global tsunamis (NGDC, 2021). As a result, volcanic tsunamis are far less researched, but have resulted in many deadly events that were often unexpected and hit shores without warning. This is because volcanic tsunamis are low-probability, high-impact and hardly predictable black swan events, causing some 26% of all volcano induced fatalities since 1800 (Brown et al., 2017). Due to the very high density of 35 active volcanoes near coastlines, Southeast (SE) Asia is one of the most prominent regions in the world for volcano induced tsunami events. The most well-known example is Krakatau volcano, Indonesia, where a tsunami caused by a major eruption in 1883 had an estimated death toll of ~36,000 people (Hamzah et al., 2000; Brown et al., 2017). In 2018, another tsunami by the same volcano killed 437 people due to the instability of its regrown volcano flank, which caused a sector collapse into events, causing some 26% of all volcano induced fatalities since 1800 (Brown et al., 2017). Due to the very high density of 35 active volcanoes near coastlines, Southeast (SE) Asia is one of the most prominent regions in the world for volcano induced tsunami events. The most well-known example is Krakatau volcano, Indonesia, where a tsunami caused by a major eruption in 1883 had an estimated death toll of ~36,000 people (Hamzah et al., 2000; Brown et al., 2017). In 2018, another tsunami by the same volcano killed 437 people due to the instability of its regrown volcano flank, which caused a sector collapse into events, causing some 26% of all volcano induced fatalities since 1800 (Brown et al., 2017). Due to the very high density of 35 active volcanoes near coastlines, Southeast (SE) Asia is one of the most prominent regions in the world for volcano induced tsunami events. 1 Introduction 30 The most well-known example is Krakatau volcano, Indonesia, where a tsunami caused by a major eruption in 1883 had an estimated death toll of ~36,000 people (Hamzah et al., 2000; Brown et al., 2017). In 2018, another tsunami by the same volcano killed 437 people due to the instability of its regrown volcano flank, which caused a sector collapse into the sea (Walter et al., 2019; Darmawan et al., 2020; Omira and Ramalho, 2020). In 1888, Ritter Island in Papua New Guinea 40 experienced a similar catastrophic collapse, resulting in a tsunami with a death toll exceeding several hundred people (Ward and Day, 2003). Even without flank or edifice instability, volcanic eruptions can still cause deadly tsunamis by the expulsion of pyroclastic density currents (PDCs) into the sea. Such events repeatedly occurred at Awu volcano, Indonesia, in 1856, 1892 and 1913 with a cumulative ~4,500 fatalities (Hidayat et al., 2020). The recent explosive eruption of the Hunga Tonga- the sea (Walter et al., 2019; Darmawan et al., 2020; Omira and Ramalho, 2020). In 1888, Ritter Island in Papua New Guinea 40 experienced a similar catastrophic collapse, resulting in a tsunami with a death toll exceeding several hundred people (Ward and Day, 2003). Even without flank or edifice instability, volcanic eruptions can still cause deadly tsunamis by the expulsion of pyroclastic density currents (PDCs) into the sea. Such events repeatedly occurred at Awu volcano, Indonesia, in 1856, 1892 and 1913 with a cumulative ~4,500 fatalities (Hidayat et al., 2020). The recent explosive eruption of the Hunga Tonga- the sea (Walter et al., 2019; Darmawan et al., 2020; Omira and Ramalho, 2020). In 1888, Ritter Island in Papua New Guinea 40 experienced a similar catastrophic collapse, resulting in a tsunami with a death toll exceeding several hundred people (Ward and Day, 2003). Even without flank or edifice instability, volcanic eruptions can still cause deadly tsunamis by the expulsion of pyroclastic density currents (PDCs) into the sea. Such events repeatedly occurred at Awu volcano, Indonesia, in 1856, 1892 and 1913 with a cumulative ~4,500 fatalities (Hidayat et al., 2020). The recent explosive eruption of the Hunga Tonga- Hunga Haʻapai volcano near Tonga caused a tsunami affecting the entire Pacific Ocean, which travelled faster towards the 45 coasts than was expected. 1 Introduction 30 Tsunamis are among the deadliest hazards affecting coastal regions around the world. While most tsunamis are caused by tectonic earthquakes, tsunamis induced by volcanic sources account for ~6% of global tsunamis (NGDC, 2021). As a result, volcanic tsunamis are far less researched, but have resulted in many deadly events that were often unexpected and hit shores without warning. This is because volcanic tsunamis are low-probability, high-impact and hardly predictable black swan Tsunamis are among the deadliest hazards affecting coastal regions around the world. While most tsunamis are caused by tectonic earthquakes, tsunamis induced by volcanic sources account for ~6% of global tsunamis (NGDC, 2021). As a result, volcanic tsunamis are far less researched, but have resulted in many deadly events that were often unexpected and hit shores without warning. This is because volcanic tsunamis are low-probability, high-impact and hardly predictable black swan events, causing some 26% of all volcano induced fatalities since 1800 (Brown et al., 2017). Due to the very high density of 35 active volcanoes near coastlines, Southeast (SE) Asia is one of the most prominent regions in the world for volcano induced tsunami events. The most well-known example is Krakatau volcano, Indonesia, where a tsunami caused by a major eruption in 1883 had an estimated death toll of ~36,000 people (Hamzah et al., 2000; Brown et al., 2017). In 2018, another tsunami by the same volcano killed 437 people due to the instability of its regrown volcano flank, which caused a sector collapse into the sea (Walter et al., 2019; Darmawan et al., 2020; Omira and Ramalho, 2020). In 1888, Ritter Island in Papua New Guinea 40 experienced a similar catastrophic collapse, resulting in a tsunami with a death toll exceeding several hundred people (Ward and Day, 2003). Even without flank or edifice instability, volcanic eruptions can still cause deadly tsunamis by the expulsion of pyroclastic density currents (PDCs) into the sea. Such events repeatedly occurred at Awu volcano, Indonesia, in 1856, 1892 and 1913 with a cumulative ~4,500 fatalities (Hidayat et al., 2020). The recent explosive eruption of the Hunga Tonga- Hunga Haʻapai volcano near Tonga caused a tsunami affecting the entire Pacific Ocean, which travelled faster towards the 45 coasts than was expected. While the mechanisms of this tsunami are not fully understood yet, reports suggest the interaction of acoustic and water gravity waves as a possible explanation (Somerville et al., 2022). Abstract. The data is sourced from geological databases, remote sensing data, historical volcano induced tsunami records and our topographic analyses, 20 mainly considering the eruptive and tsunami history, elevation relative to the distance from the sea, flank steepness, hydrothermal alteration as well as vegetation coverage. Out of 131 analysed volcanoes, we found 19 with particularly high tsunamigenic hazard potential in Indonesia (Anak Krakatau, Batu Tara, Iliwerung, Gamalama, Sangeang Api, Karangetang, Sirung, Wetar, Nila, Ruang, Serua) and Papua New Guinea (Kadovar, Ritter Island, Rabaul, Manam, Langila, Ulawun, Bam), but also in the Philippines (Didicas). While some of these volcanoes, such as Anak Krakatau, are well-known for their 25 deadly tsunamis, many others on this list are lesser known and monitored. We further performed tsunami travel time modelling on these high-hazard volcanoes, which indicates that future events could affect large coastal areas in a short time. This highlights the importance of individual tsunami hazard assessment for these volcanoes, dedicated volcanological monitoring, and the need for increased preparedness on the potentially affected coasts. Bam), but also in the Philippines (Didicas). While some of these volcanoes, such as Anak Krakatau, are well-known for their 25 deadly tsunamis, many others on this list are lesser known and monitored. We further performed tsunami travel time modelling on these high-hazard volcanoes, which indicates that future events could affect large coastal areas in a short time. This highlights the importance of individual tsunami hazard assessment for these volcanoes, dedicated volcanological monitoring, and the need for increased preparedness on the potentially affected coasts. Bam), but also in the Philippines (Didicas). While some of these volcanoes, such as Anak Krakatau, are well-known for their 25 deadly tsunamis, many others on this list are lesser known and monitored. We further performed tsunami travel time modelling on these high-hazard volcanoes, which indicates that future events could affect large coastal areas in a short time. This highlights the importance of individual tsunami hazard assessment for these volcanoes, dedicated volcanological monitoring, and the need for increased preparedness on the potentially affected coasts. 1 We create a comprehensive catalogue of potentially tsunamigenic volcanoes and further use this data to correctly interpret the moderate-sized seismic energy as a tsunamigenic event (Annunziato et al., 2019). To compensate 75 for this blind spot and improve local preparedness, a comprehensive understanding of the tsunami hazards posed by volcanic sources is required to identify the most likely individual volcanoes to produce such an event. Here, we present an in-depth analysis of the tsunami hazards by volcanoes in the Southeast Asian seas, including Indonesia, Papua New Guinea, the Philippines, and India. We create a comprehensive catalogue of potentially tsunamigenic volcanoes and further use this data to create a point-based ranking and identify the most likely candidates for sourcing potentially catastrophic tsunamis in the 80 future. to create a point-based ranking and identify the most likely candidates for sourcing potentially catastrophic tsunamis in the 80 future. 1 Introduction 30 Specifically, eruptions are known to generate tsunamis through large PDCs resulting from column or lava dome collapses entering the sea (Carey et al., 2000; Watts and Waythomas, 2003), through phreatic explosions when lava interacts with seawater (Smith and Shepherd, 1993; Belousov et al., 2000), and through the collapse of a lava delta when large amounts of lava construct unstable new land in the sea (Poland and Orr, 2014; Di Traglia et al., 2018). The formation of a considered a secondary volcanic hazard and result from eruptions or sector collapses of volcanic edifices (McGuire, 2006; 55 Paris, 2015). Specifically, eruptions are known to generate tsunamis through large PDCs resulting from column or lava dome collapses entering the sea (Carey et al., 2000; Watts and Waythomas, 2003), through phreatic explosions when lava interacts with seawater (Smith and Shepherd, 1993; Belousov et al., 2000), and through the collapse of a lava delta when large amounts of lava construct unstable new land in the sea (Poland and Orr, 2014; Di Traglia et al., 2018). The formation of a caldera during particularly large eruptions is also known to generate tsunamis as large parts of the volcanic edifice are 60 moving or collapsing (Maeno et al., 2006). On the other hand, a landslide or sector collapse (or lateral collapse) and resulting debris avalanche from a volcanic edifice may also occur in association with volcanic activity, i.e., flank instability triggered caldera during particularly large eruptions is also known to generate tsunamis as large parts of the volcanic edifice are 60 moving or collapsing (Maeno et al., 2006). On the other hand, a landslide or sector collapse (or lateral collapse) and resulting debris avalanche from a volcanic edifice may also occur in association with volcanic activity, i.e., flank instability triggered 2 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. through the intrusion of cryptodomes or dykes, earthquakes, explosions or loading of the flank with eruptive products (Lipman and Mullineaux, 1981; Siebert, 1984; Murray and Voight, 1996; McGuire, 2006; Romero et al., 2021). Flank instability can also be gravitationally driven without current volcanic unrest or eruptive activity through a deep-seated and 65 slow-moving décollement (van Wyk De Vries and Borgia, 1996) and may be seen as a precursory stage of a catastrophic flank collapse. Hydrothermal alteration may further facilitate gravitational instability by altering the chemical and structural composition of the volcanic flanks or basement (van Wyk De Vries and Borgia, 1996; Heap et al., 2013; Heap et al., 2021). However, the interrelation between gravitational and magmatic flank instability are still poorly understood and may strongly 65 depend on the local geologic setting and structural architecture of the volcano (Poland et al., 2017). 70 The inherent problem of volcanogenic tsunamis is the lack of warning time and quick response options because these tsunamis are not recognized by the early warning systems designed to detect tectonic earthquake events via seismic monitoring (Hanka et al., 2010; Lauterjung et al., 2010) and scenario-based modelling (Harig et al., 2020). This shortcoming also affected the 2018 tsunami originating from Anak Krakatau, where a warning system was in operation, but not designed depend on the local geologic setting and structural architecture of the volcano (Poland et al., 2017). 70 The inherent problem of volcanogenic tsunamis is the lack of warning time and quick response options because these tsunamis are not recognized by the early warning systems designed to detect tectonic earthquake events via seismic monitoring (Hanka et al., 2010; Lauterjung et al., 2010) and scenario-based modelling (Harig et al., 2020). This shortcoming also affected the 2018 tsunami originating from Anak Krakatau, where a warning system was in operation, but not designed to correctly interpret the moderate-sized seismic energy as a tsunamigenic event (Annunziato et al., 2019). To compensate 75 for this blind spot and improve local preparedness, a comprehensive understanding of the tsunami hazards posed by volcanic sources is required to identify the most likely individual volcanoes to produce such an event. Here, we present an in-depth analysis of the tsunami hazards by volcanoes in the Southeast Asian seas, including Indonesia, Papua New Guinea, the Philippines, and India. 2.1 Morphological evaluation and catalogue For creating the catalogue we considered all active volcanoes in the SE-Asian region (Fig. 1), here including India, For creating the catalogue we considered all active volcanoes in the SE-Asian region ( Indonesia, Papua New Guinea, and the Philippines, that were listed in the Global Volcanism Program (GVP) database 85 (Global Volcanism Program, 2013) with a maximum distance of 20 km to the sea (with one exception: Peuet Sague, which has an uncertain historical tsunami associated it). Volcanoes further inland were not considered as mass movements from eruptions or flank/sector collapses are unlikely to exceed such a distance, although in some circumstances this may still be possible (Kieffer, 1981; Yoshida et al., 2012). Indonesia, Papua New Guinea, and the Philippines, that were listed in the Global Volcanism Program (GVP) database 85 (Global Volcanism Program, 2013) with a maximum distance of 20 km to the sea (with one exception: Peuet Sague, which has an uncertain historical tsunami associated it). Volcanoes further inland were not considered as mass movements from eruptions or flank/sector collapses are unlikely to exceed such a distance, although in some circumstances this may still be possible (Kieffer, 1981; Yoshida et al., 2012). 90 3 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Figure 1: The overview map of all active volcanoes located in the SE-Asian region. Considered for our catalogue (in colour) are all subaerial volcanoes in Indonesia, India, Papua New Guinea and the Philippines at least 20 km away from the nearest coastline. The colour corresponds to the country where a volcano is located. In total, there are 214 active volcanoes between the four countries and 131 of them are considered in our catalogue. Base map data source: © OpenStreetMap contributors 5 2022. Distributed under the Open Data Commons Open Database License (ODbL) v1.0. Figure 1: The overview map of all active volcanoes located in the SE Asian region Considered for our catalogue (in colour) Figure 1: The overview map of all active volcanoes located in the SE-Asian region. Considered for our catalogue (in colour) are all subaerial volcanoes in Indonesia, India, Papua New Guinea and the Philippines at least 20 km away from the nearest coastline. The colour corresponds to the country where a volcano is located. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. volcanoes. NETVOLC initiates with a starting location (usually the volcano summit) and a pixel range to draw the edifice boundary by iteratively looking for the minimum profile convexity. This is based on the assumption that volcanic edifices are bound by concave breaks in their slopes. Then, MORVOLC allowed us to use that boundary (and an optional crater outline, manually added) to collect data such as maximum elevation, slope steepness, or edifice volume for further evaluation. For most volcanoes in our catalogue this approach worked very well. For some volcanoes (28/131 cases or 110 ~21%), however, we had to delineate the edifice boundary manually as the automatic NETVOLC approach would produce no or visibly wrong boundaries. This is due to the more complex morphology of some volcanoes, which does not allow for a clear delineation of concave slope breaks. 110 The final catalogue (see supplementary material) includes (1) the coordinates of the vol The final catalogue (see supplementary material) includes (1) the coordinates of the volcano, (2) the volcano type, (3) its activity status as the last eruption year, (4) how many tsunamis it has historically sourced, (5) its height and distance from 115 the sea (as a ratio) as well as (6) the maximum average slope angle, (7) the possible collapse azimuth range (flanks facing the sea) and (8) the most likely azimuth for tsunamis (manually selected base on slope steepness or location relative to the sea), (9) the edifice volume, and (10) a summary of other hazardous features (see below). activity status as the last eruption year, (4) how many tsunamis it has historically sourced, (5) its height and distance from 115 the sea (as a ratio) as well as (6) the maximum average slope angle, (7) the possible collapse azimuth range (flanks facing the sea) and (8) the most likely azimuth for tsunamis (manually selected base on slope steepness or location relative to the sea), (9) the edifice volume, and (10) a summary of other hazardous features (see below). 2.1 Morphological evaluation and catalogue In total, there are 214 active volcanoes between the four countries and 131 of them are considered in our catalogue. Base map data source: © OpenStreetMap contributors 95 2022. Distributed under the Open Data Commons Open Database License (ODbL) v1.0. Figure 1: The overview map of all active volcanoes located in the SE-Asian region. Considered for our catalogue (in colour) are all subaerial volcanoes in Indonesia, India, Papua New Guinea and the Philippines at least 20 km away from the nearest coastline. The colour corresponds to the country where a volcano is located. In total, there are 214 active volcanoes between the four countries and 131 of them are considered in our catalogue. Base map data source: © OpenStreetMap contributors 95 2022. Distributed under the Open Data Commons Open Database License (ODbL) v1.0. The catalogue contains a total of 131 volcanoes, colour-coded according to the country in Fig. 1. The information on the individual volcanoes was collected from databases, including the GVP (Global Volcanism Program, 2013) and the Global Historical Tsunami Database (NGDC 2021) scientific literature optical remote sensing data from Sentinel 2 satellites 100 The catalogue contains a total of 131 volcanoes, colour-coded according to the country in Fig. 1. The information on the individual volcanoes was collected from databases, including the GVP (Global Volcanism Program, 2013) and the Global individual volcanoes was collected from databases, including the GVP (Global Volcanism Program, 2013) and the Global Historical Tsunami Database (NGDC, 2021), scientific literature, optical remote sensing data from Sentinel-2 satellites 100 accessed via Sentinel Playground (ESA, 2022), as well as our own measurements using the Copernicus digital elevation model (DEM) (Airbus, 2020). Copernicus DEM is based on the previously available DEMs such as ASTER, SRTM90, SRTM30, SRTM30plus, GMTED2010, TerraSAR-X Radargrammetric DEM, and ALOS World 3D-30m. Historical Tsunami Database (NGDC, 2021), scientific literature, optical remote sensing data from Sentinel-2 satellites 100 accessed via Sentinel Playground (ESA, 2022), as well as our own measurements using the Copernicus digital elevation model (DEM) (Airbus, 2020). Copernicus DEM is based on the previously available DEMs such as ASTER, SRTM90, SRTM30, SRTM30plus, GMTED2010, TerraSAR-X Radargrammetric DEM, and ALOS World 3D-30m. We started by extracting morphometric data from the Copernicus DEMs using the NETVOLC (Euillades et al., 2013) and MORVOLC (Grosse et al., 2009; Grosse et al., 2012) codes and automatically delineated the edifice boundary of the 105 4 2.2 The volcanic tsunami-hazard ranking 120 One key challenge in creating a meaningful ranking of the tsunami hazard posed by many individual volcanoes is the application of consistent criteria to allow for strong comparability. Since volcanoes have a large variety of shapes, morphologies and styles of activity, this is not a trivial task. We therefore only considered the data representing all volcanoes under the same conditions and we used as many objectively measurable criteria as possible to minimise human subjectivity and inconsistency. Here, we decided on a Multicriteria Decision Analysis (MCDA), which is a method frequently used to aid 125 in prioritising and decision-making for complex and multifaceted problems across many scientific disciplines. For example, in medical sciences evaluating the impact of drugs (Nutt et al., 2010), in Earth sciences assisting in the management of nuclear waste disposal sites (Morton et al., 2009), or in hazard evaluations of flood-prone sites (Fernández and Lutz, 2010; Rahmati et al., 2016; Toosi et al., 2019). Our MCDA system uses weighted point scores based on five major factors to and inconsistency. Here, we decided on a Multicriteria Decision Analysis (MCDA), which is a method frequently used to aid 125 in prioritising and decision-making for complex and multifaceted problems across many scientific disciplines. For example, in medical sciences evaluating the impact of drugs (Nutt et al., 2010), in Earth sciences assisting in the management of nuclear waste disposal sites (Morton et al., 2009), or in hazard evaluations of flood-prone sites (Fernández and Lutz, 2010; Rahmati et al., 2016; Toosi et al., 2019). Our MCDA system uses weighted point scores based on five major factors to influence our final ranking. These factors were assigned (i) factor points based on their likelihood to contribute to the 130 volcano's tsunami hazard, and (ii) factor weights based on how much the factor contributes to the volcano's tsunami hazard. By adding these weighed factor points to a final score we could rank the tsunami-hazard from the individual volcanoes: 𝑆𝑐𝑜𝑟𝑒= 𝐹1 ∙𝑊1 + 𝐹1 ∙𝑊1 + … + 𝐹𝑛∙𝑊𝑛 (1) 𝑆𝑐𝑜𝑟𝑒= 𝐹1 ∙𝑊1 + 𝐹1 ∙𝑊1 + … + 𝐹𝑛∙𝑊𝑛 (1) (1) 𝑆𝑐𝑜𝑟𝑒= 𝐹1 ∙𝑊1 + 𝐹1 ∙𝑊1 + … + 𝐹𝑛∙𝑊𝑛 (1) where F represents the individual factor points from 0-100 (100 representing the highest tsunami-hazard) and W represents the factor weight as a percentage (the total of all factor weights adding up to 100%). https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. full 100 points could not always be reached, but the point systems were designed to scale well between 0 and 100. This results in a final score that also has points between 0-100 and makes our ranking easier to comprehend and visualise. We consider the following five factors and point systems for the ranking: i) H/D-Ratio: This is the height H of the volcanic edifice (i.e., the maximum elevation of the peak) as a fraction of the distance from that point to the sea D. To measure the height of volcano edifice, we used the 30 m 140 Copernicus DEM GLO-30 (Airbus, 2020), which is considered the most reliable choice among the freely available and global DEMs (Guth and Geoffroy, 2021). Only for Anak Krakatau no post-collapse DEM was available, so we used a downsampled photogrammetric DEM previously published by Darmawan et al. (2020). We selected the maximum elevation of the edifice (extracted using the MORVOLC-code) and from that location measured the minimum distance to the shoreline using OpenStreetMap land polygons 145 (OpenStreetMap, 2022). This parameter is highly relevant to the tsunami hazard of a volcano. Firstly, because a volcano with higher elevation can produce larger collapses and allow for more potential energy in mass movements, both from flank/sector/dome collapses and PDCs directed towards the sea. Secondly, if the mass movement source is closer to the sea it is more likely to actually reach it and produce a tsunami. The resulting values ranged from 0.02 to 0.89, so in order to convert the factor to the 0-100 point scale, the values were 150 multiplied by 100. The only exception is Ritter Island, Papua New Guinea, which achieved a ratio of 1.77 due to the remnant collapse scar, which drops steeply towards the sea. We simplified this by assigning a maximum of 100 points. i) 140 140 ii) Volcanic activity: Frequent eruptive activity can exert strain on the flanks of a volcano as the volcano deforms, inflates and deflates as a result of pressurisation or the movement of intrusions. Additionally, erupted lava or tephra can quickly pile up and over steepen flanks, while constant high seismic activity can act as a trigger to mass movements. 2.2 The volcanic tsunami-hazard ranking 120 Due to the specific nature of some factors, the 135 5 5 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. volcanoes experienced historical unrest episodes but no eruption, they were assigned 20 points. For volcanoes where Holocene eruptions are presumed or considered likely, we assigned 10 points and 0 points were assigned for volcanoes that are presumed to be extinct. 170 iii) Tsunamigenic history: Some volcanoes have an increased tendency to produce tsunamis, either through frequent large eruptions or inherently unstable flanks. Here, we counted the number of tsunamis known from historic records sourced from the Global Historical Tsunami Database (NGDC, 2021) and relevant review papers (Hamzah et al., 2000; Paris et al., 2014; Mutaqin et al., 2019; Hidayat et al., 2020). Our compilation is 175 shown in table 1. We further considered signs of previous edifice instability that include collapse scars (amphitheatres) and known submarine debris avalanche deposits. We assigned 10 points for every known historical tsunami, 10 for a collapse scar or submarine deposit and 20 if the volcano has multiple scars or submarine deposits. iv) Slope angle: The steeper an edifice is the less stable it becomes. Typically, the angle of repose for natural 180 volcanic rocks lies between 30-40° and edifices exceeding this angle may experience gravitational instability. Here, we measured the maximum average slope angle that is part of the MORVOLC output, meaning the steepest part of the edifice calculated as the average slope value of the 50 m elevation interval of the edifice with the highest mean average slope, see Grosse et al. (2009). However, we limited the output to only those flanks facing towards the sea and excluded slopes facing inland. For the factor points, we doubled the steepness 185 value in degrees, so a 50° slope would equal the maximum of 100 points. We also note that this factor is a major distinction from the H/D-ratio since it considers real measured local steepness. This may differ strongly from the H/D-Ratio, e.g., if the volcano is very steep, but the summit is located far from the sea. Hazardous Features: This factor is deliberately designed to encompass a broad collection of features impacting the likelihood of a tsunami-generating event at the volcanoes. These features cannot be easily quantified and have to be arbitrarily evaluated by a human and are easily missed or misinterpreted. This means a volcano with a high activity level is far more likely to experience a sector/flank/dome collapse or produce pyroclastic flows compared to a quiescent one. While the exact mechanisms and timescales are generally not well understood, it is known that many volcanic systems have extended periods or cycles of quiescence or low eruptive frequency, followed by more frequent eruptions (e.g., Crisci et al., 1991; Gertisser and Keller, 2003; Turner, 2008). This suggests that a volcano that recently erupted is more likely to become more active or erupt again in the near-future compared to ones that have been quiet for a long time. Considering all above, we based our factor points on the time since the last known eruption of the volcano, with the data sourced from the GVP (Global Volcanism Program, 2013). However, due to the different timescales of eruptive cycles and the decreasing certainty of historic records, we decided to apply a non-linear point scale. Any volcano that erupted since the beginning of 2020 received a full 100 points. Every year before 2020 resulted in one point deduction and from the year 2000 only every decade is worth one point less, but to a minimum of 20 points as long as the volcano erupted within the Holocene. Similarly, if these 6 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. breached craters. Similarly, calderas signal that one or many large eruptions have occurred at this volcano and were also given 15 points. Finally, a larger volcanic edifice may have multiple secondary edifices and vents, adding further potential source locations to volcanogenic tsunamis. We thus added 15 points if one or more secondary peaks/vents were found. 205 − Vegetation: Dense vegetation and plant roots can significantly enhance a flank's stability and make a flank/sector collapse less likely (Gonzalez-Ollauri and Mickovski, 2017). Contrary, a flank’s stability may significantly decrease due to the vegetation loss after major eruptions (Korup et al., 2019). Here, we visually inspected the volcano flanks using Sentinel-2 data (10 m spatial resolution). We gave no points if the volcano flanks were densely vegetated, 5 points if the volcano had vegetation free portions (most commonly, this is near the crater as a result of recent eruptions), and 15 points if at least one flank between summit and sea was free of vegetation. 210 − Hydrothermal alteration: Fumarole systems and weathering may significantly alter the rocks of a volcano flank, changing their appearance, composition and strength. Most commonly, hydrothermal alteration can weaken the rocks and promote failure or close permeable fluid paths and induce phreatic explosions (Heap and Violay, 2021). Thus, we attempted to identify areas of localised alteration, by visually inspecting the volcano flanks using Sentinel-2 data. We specifically looked for characteristic bright spots indicative of alteration minerals and localised vegetation loss (outside the main crater). If these were identified, we added 10 points. − Hydrothermal alteration: Fumarole systems and weathering may significantly alter the rocks of a volcano flank, changing their appearance, composition and strength. Most commonly, hydrothermal alteration can weaken the rocks and promote failure or close permeable fluid paths and induce phreatic explosions (Heap and Violay, 2021). Thus, we attempted to identify areas of localised alteration, by visually inspecting the volcano flanks using Sentinel-2 data. We specifically looked for characteristic bright spots indicative of alteration minerals and localised vegetation loss (outside the main crater). If these were identified, we added 10 points. − Topography between an edifice and the sea: Within 20 km of the shore, the volcano's flank may not directly face the sea. While past events at St. Thus, in order to minimise user bias and avoid unrealistic points, all listed features below were combined into one factor. The data was collected by visually examining the Copernicus DEM GLO-30 (Airbus, 2020) as well as optical satellite imagery from Sentinel-2 satellites accessed via Sentinel Playground (ESA, 2022). The considered features include: − Underwater extent: Whether a volcano and its flanks are submerged in the sea plays a very important role when assessing tsunami hazards as an edifice failure or an erupting vent may be located partially or fully underwater. We assigned 10 points if the edifice is partially submerged (so at least part of the edifice outline used in the NETVOLC and MORVOLC codes reaches into the sea) and 20 points if the edifice is fully in the water and all flanks reach into the sea 200 − Morphological features: Breached craters highlight a volcano's tendency to experience partial instability and provide an easy path for eruption products to reach the sea. We assigned 15 points to volcanoes with − Morphological features: Breached craters highlight a volcano's tendency to experience partial instability and provide an easy path for eruption products to reach the sea. We assigned 15 points to volcanoes with 7 Helens, USA, 1980 (Fisher, 1990) and Merapi, Indonesia, 2010 (Cronin et al., 2013) have shown that sector collapses or PDCs can overcome significant topography, it is less likely to reach the sea in such circumstances. To account for that, we added 30 points if we found no major topographic obstacle between the summit of the edifice towards the sea, thus adding more points to volcanoes close to the coast. − Topography between an edifice and the sea: Within 20 km of the shore, the volcano's flank may not directly face the sea. While past events at St. Helens, USA, 1980 (Fisher, 1990) and Merapi, Indonesia, 2010 (Cronin et al., 2013) have shown that sector collapses or PDCs can overcome significant topography, it is less likely to reach the sea in such circumstances. To account for that, we added 30 points if we found no major topographic obstacle between the summit of the edifice towards the sea, thus adding more points 225 to volcanoes close to the coast. For the chosen factor weights we decided to favour morphometry and eruptive activity over the others. Morphometry, here meaning H/D-ratio and slope angle, measure both the feasibility of gravitational mass movements (flank collapses or PDCs) reaching the sea, as well as quantify oversteepening of individual flanks. Eruptive activity is also favoured as tsunamis do 230 not only occur by flank collapse but also through PDCs or explosions. Additionally, unrest or eruptions may also act as a trigger for gravitational failures. In turn, we decided to weigh the Hazardous Features less since these are not quantitatively determined and more prone to human subjectivity and misjudgement. Consequently, the final factor weights used were the H/D-ratio (20%) and the slope angle (20%) as morphometry factors, then volcanic activity (30%), tsunamigenic history (20%), and hazardous features (10%). An example how the score was calculated is provided in Fig. 2. 235 For the chosen factor weights we decided to favour morphometry and eruptive activity over the others. Morphometry, here meaning H/D-ratio and slope angle, measure both the feasibility of gravitational mass movements (flank collapses or PDCs) reaching the sea, as well as quantify oversteepening of individual flanks. Eruptive activity is also favoured as tsunamis do 230 not only occur by flank collapse but also through PDCs or explosions. Additionally, unrest or eruptions may also act as a trigger for gravitational failures. In turn, we decided to weigh the Hazardous Features less since these are not quantitatively determined and more prone to human subjectivity and misjudgement. Consequently, the final factor weights used were the H/D-ratio (20%) and the slope angle (20%) as morphometry factors, then volcanic activity (30%), tsunamigenic history For the chosen factor weights we decided to favour morphometry and eruptive activity over the others. Morphometry, here meaning H/D-ratio and slope angle, measure both the feasibility of gravitational mass movements (flank collapses or PDCs) reaching the sea, as well as quantify oversteepening of individual flanks. Eruptive activity is also favoured as tsunamis do 230 not only occur by flank collapse but also through PDCs or explosions. Additionally, unrest or eruptions may also act as a trigger for gravitational failures. In turn, we decided to weigh the Hazardous Features less since these are not quantitatively determined and more prone to human subjectivity and misjudgement. Consequently, the final factor weights used were the H/D-ratio (20%) and the slope angle (20%) as morphometry factors, then volcanic activity (30%), tsunamigenic history (20%), and hazardous features (10%). An example how the score was calculated is provided in Fig. 2. 235 8 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Figure 2: Exemplary calculation of the ranking score using Nila volcano, Indonesia. a) is a false colour image from Sentinel-2 from bands 8 (NIR), 4 (red), and 3 (green). This highlights vegetated areas as red, but leaves barren areas grey. Here, Nila Island is densely vegetated, except for the southeast slope, which appears to be unvegetated due to ongoing hydrothermal alteration. b) is a hillshade DEM 240 from Copernicus GLO30 and c) is a summary of our MCDA score calculation using data marked in a) and b) as well as the GVP and Global Historical Tsunami databases. Figure 2: Exemplary calculation of the ranking score using Nila volcano, Indonesia. a) is a false colour image from Sentinel-2 from bands 8 (NIR), 4 (red), and 3 (green). This highlights vegetated areas as red, but leaves barren areas grey. Here, Nila Island is densely vegetated, except for the southeast slope, which appears to be unvegetated due to ongoing hydrothermal alteration. b) is a hillshade DEM 240 from Copernicus GLO30 and c) is a summary of our MCDA score calculation using data marked in a) and b) as well as the GVP and Global Historical Tsunami databases. Figure 2: Exemplary calculation of the ranking score using Nila volcano, Indonesia. a) is a false colour image from Sentinel-2 from bands 8 (NIR), 4 (red), and 3 (green). This highlights vegetated areas as red, but leaves barren areas grey. Here, Nila Island is densely vegetated, except for the southeast slope, which appears to be unvegetated due to ongoing hydrothermal alteration. b) is a hillshade DEM 240 from Copernicus GLO30 and c) is a summary of our MCDA score calculation using data marked in a) and b) as well as the GVP and Global Historical Tsunami databases. We further tested how robust our ranking is with respect to used factor weights. This is done to confirm that the highest 245 scoring volcanoes still retain their high score even when the weighing is significantly different, which can confirm that these volcanoes really pose the highest tsunami hazard despite possible human error or misjudgement. The test was carried out by 9 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. changing the five factor weights, increasing one factor to 60% and all others are set to 10%. The procedure was repeated for all five factor weights, so that every single factor was once set as the strongest influence. We then counted how many times the volcanoes would be placed within the top 5, 10, 15, and 20 spots on the ranking. For example, if a volcano is always in 250 the top 5, no matter how the factor weights change, then it is 5 times in the top 5, 10, 15, and 20 each, giving it the maximum count of 20. However, if the volcano is once in the top 10, twice in the top 15 and four times in the top 20 it receives a count of 7. The resulting compilation was used to judge whether our ranking can generally identify the highest scoring and most hazardous volcanoes well. 255 Volcano Country Year Deaths Cause References Agung Indonesia 1963 3, 5 Awu Indonesia 1856 3000 Pyroclastic flows 1, 2, 3, 4, 5 Awu Indonesia 1892 1532 Pyroclastic surges? 1, 2, 3, 4, 5 Awu Indonesia 1913 Pyroclastic surges? 4 Banua Wuhu Indonesia 1889 Underwater explosion? 2, 3, 4 Banua Wuhu Indonesia 1918 Underwater explosion 2, 3, 4 Banua Wuhu Indonesia 1919 Underwater explosion 2, 3, 4 Gamalama Indonesia 1608 <50 2, 3, 4, 5 Gamalama Indonesia 1771 3 Gamalama Indonesia 1772 35 4 Gamalama Indonesia 1840 2, 3, 4 Gamalama Indonesia 1871 1 Gamkonora Indonesia 1673 Earthquake/ Landslide 5 Gamkonora Indonesia 1673 2, 3, 5 changing the five factor weights, increasing one factor to 60% and all others are set to 10%. The procedure was repeated for all five factor weights, so that every single factor was once set as the strongest influence. We then counted how many times the volcanoes would be placed within the top 5, 10, 15, and 20 spots on the ranking. For example, if a volcano is always in 250 the top 5, no matter how the factor weights change, then it is 5 times in the top 5, 10, 15, and 20 each, giving it the maximum count of 20. However, if the volcano is once in the top 10, twice in the top 15 and four times in the top 20 it receives a count of 7. The resulting compilation was used to judge whether our ranking can generally identify the highest scoring and most hazardous volcanoes well. Volcano Country Year Deaths Cause References Agung Indonesia 1963 3, 5 Awu Indonesia 1856 3000 Pyroclastic flows 1, 2, 3, 4, 5 Awu Indonesia 1892 1532 Pyroclastic surges? 1, 2, 3, 4, 5 Awu Indonesia 1913 Pyroclastic surges? 4 Banua Wuhu Indonesia 1889 Underwater explosion? 2, 3, 4 Banua Wuhu Indonesia 1918 Underwater explosion 2, 3, 4 Banua Wuhu Indonesia 1919 Underwater explosion 2, 3, 4 Gamalama Indonesia 1608 <50 2, 3, 4, 5 Gamalama Indonesia 1771 3 Gamalama Indonesia 1772 35 4 Gamalama Indonesia 1840 2, 3, 4 Gamalama Indonesia 1871 1 Gamkonora Indonesia 1673 Earthquake/ Landslide 5 Gamkonora Indonesia 1673 2, 3, 5 10 Iliwerung Indonesia 1973 Underwater explosions? 2 Iliwerung Indonesia 1979 >539 Landslide 2, 3, 4 Iliwerung Indonesia 1983 Underwater explosion 2, 4, 5 Krakatau Indonesia 416 <1000 3, 4, 5 Krakatau Indonesia 1883 34417 Pyroclastic flows 1, 2, 3, 5 Krakatau Indonesia 1883 Landslide? 2, 5 Krakatau Indonesia 1884 Underwater explosion? 2, 3, 4 Krakatau Indonesia 1928 Underwater explosion 1, 2, 3, 4, 5 Krakatau Indonesia 1930 Underwater explosion 2, 3, 4, 5 Krakatau Indonesia 1981 Landslide? 2, 3 Krakatau Indonesia 2018 437 Landslide 4 Makian Indonesia 1550 2 Peuet Sague Indonesia 1837 3 Rokatenda/Paluweh Indonesia 1927 226 Underwater explosion? 1, 4 Rokatenda/Paluweh Indonesia 1928 98 Landslide 1, 2, 3, 4 Ruang Indonesia 1871 >400 Lava dome collapse 2, 3, 5 Ruang Indonesia 1889 1 Soputan Indonesia 1845 118 Earthquake? 2, 3 Tambora Indonesia 1815 <1000 Pyroclastic flows 1, 2, 3, 4, 5 Teon/Serawerna Indonesia 1659 Pyroclastic flows? 2, 3, 4, 5 Unknown Volcano Indonesia 1773 5 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Iliwerung Indonesia 1973 Underwater explosions? 2 Iliwerung Indonesia 1979 >539 Landslide 2, 3, 4 Iliwerung Indonesia 1983 Underwater explosion 2, 4, 5 Krakatau Indonesia 416 <1000 3, 4, 5 Krakatau Indonesia 1883 34417 Pyroclastic flows 1, 2, 3, 5 Krakatau Indonesia 1883 Landslide? 2, 5 Krakatau Indonesia 1884 Underwater explosion? 2, 3, 4 Krakatau Indonesia 1928 Underwater explosion 1, 2, 3, 4, 5 Krakatau Indonesia 1930 Underwater explosion 2, 3, 4, 5 Krakatau Indonesia 1981 Landslide? 2, 3 Krakatau Indonesia 2018 437 Landslide 4 Makian Indonesia 1550 2 Peuet Sague Indonesia 1837 3 Rokatenda/Paluweh Indonesia 1927 226 Underwater explosion? 1, 4 Rokatenda/Paluweh Indonesia 1928 98 Landslide 1, 2, 3, 4 Ruang Indonesia 1871 >400 Lava dome collapse 2, 3, 5 Ruang Indonesia 1889 1 Soputan Indonesia 1845 118 Earthquake? 2, 3 Tambora Indonesia 1815 <1000 Pyroclastic flows 1, 2, 3, 4, 5 Teon/Serawerna Indonesia 1659 Pyroclastic flows? 2, 3, 4, 5 Unknown Volcano Indonesia 1773 5 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. 1973 Underwater explosions? 2 1979 >539 Landslide 2, 3, 4 1983 Underwater explosion 2, 4, 5 416 <1000 3, 4, 5 1883 34417 Pyroclastic flows 1, 2, 3, 5 1883 Landslide? 2, 5 1884 Underwater explosion? 2, 3, 4 1928 Underwater explosion 1, 2, 3, 4, 5 1930 Underwater explosion 2, 3, 4, 5 1981 Landslide? 2, 3 2018 437 Landslide 4 1550 2 1837 3 1927 226 Underwater explosion? 1, 4 1928 98 Landslide 1, 2, 3, 4 1871 >400 Lava dome collapse 2, 3, 5 1889 1 1845 118 Earthquake? 2, 3 1815 <1000 Pyroclastic flows 1, 2, 3, 4, 5 1659 Pyroclastic flows? 2, 3, 4, 5 1773 5 Iliwerung Indonesia Iliwerung Indonesia Iliwerung Indonesia Krakatau Indonesia Krakatau Indonesia Krakatau Indonesia Krakatau Indonesia Krakatau Indonesia Krakatau Indonesia Krakatau Indonesia Krakatau Indonesia Makian Indonesia Peuet Sague Indonesia Rokatenda/Paluweh Indonesia Rokatenda/Paluweh Indonesia Ruang Indonesia Ruang Indonesia Soputan Indonesia Tambora Indonesia Teon/Serawerna Indonesia Unknown Volcano Indonesia 1973 Underwater explosions? 2 1979 >539 Landslide 2, 3, 4 1983 Underwater explosion 2, 4, 5 416 <1000 3, 4, 5 1883 34417 Pyroclastic flows 1, 2, 3, 5 1883 Landslide? 2, 5 1884 Underwater explosion? 2, 3, 4 1928 Underwater explosion 1, 2, 3, 4, 5 1930 Underwater explosion 2, 3, 4, 5 1981 Landslide? 2, 3 2018 437 Landslide 4 1550 2 1837 3 1927 226 Underwater explosion? 1, 4 1928 98 Landslide 1, 2, 3, 4 1871 >400 Lava dome collapse 2, 3, 5 1889 1 1845 118 Earthquake? 2, 3 1815 <1000 Pyroclastic flows 1, 2, 3, 4, 5 1659 Pyroclastic flows? 2, 3, 4, 5 1773 5 11 12 Unknown Volcano Indonesia 1878 5 Unknown Volcano Indonesia 1883 Pyroclastic flows? 3 Unknown Volcano Indonesia 1892 5 Unknown Volcano Indonesia 1918 5 Unknown Volcano Indonesia 1919 5 Kadovar Papua New Guinea 2018 Lava dome collapse 5 Long Island Papua New Guinea 1660 Pyroclastic flows? 2, 5 Rabaul Papua New Guinea 1878 Earthquake 2 Rabaul Papua New Guinea 1937 <50 Pyroclastic flows/ Explosions 2, 5 Rabaul Papua New Guinea 1994 Pyroclastic flows 2, 5 Ritter Island Papua New Guinea 1888 <3000 Landslide 2 Ritter Island Papua New Guinea 1972 Underwater explosions? 2, 5 Ritter Island Papua New Guinea 1974 Landslide? 2, 5 Ritter Island Papua New Guinea 2007 Landslides? 2 Unknown Volcano Papua New Guinea 1857 Earthquake 2 Unknown Volcano Papua New Guinea 1953 5 Bulusan? Philippines 1933 9 2, 5 Camiguin Philippines 1871 Pyroclastic flows? 2, 5 Didicas Philippines 1969 3 Underwater explosions? 2, 5 Taal Philippines 1716 Underwater explosions 2, 5 Taal Philippines 1749 Pyroclatic flows? 2, 5 12 Taal Philippines 1754 12 Pyroclatic flows 2, 5 Taal Philippines 1911 >50 Pyroclastic surges/ Air waves? 2, 5 Taal Philippines 1965 355 Air waves? 2, 5 Table1: Compiled list of historic Tsunami events in the Southeast Asia region. References are 1: Hamzah et al. (2000); 2: Paris et al. (2014); 3: Mutaqin et al. (2019); 4: Hidayat et al. (2020); 5: NGDC (2021). https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Table1: Compiled list of historic Tsunami events in the Southeast Asia region. References are 1: Hamzah et al. (2000); 2: Paris et al. (2014); 3: Mutaqin et al. (2019); 4: Hidayat et al. (2020); 5: NGDC (2021). Table1: Compiled list of historic Tsunami events in the Southeast Asia region. References are 1: Hamzah et al. (2000); 2: Paris et al. (2014); 3: Mutaqin et al. (2019); 4: Hidayat et al. (2020); 5: NGDC (2021). 2.3 Ranking assumptions and limitations 260 However, as the rules with which 270 points are given are kept strictly the same for all volcanoes, we retain the comparability of our results, allowing a meaningful identification of the most hazardous volcanoes for tsunami generation. This is despite the individual score by itself having little meaning in terms of hard data, such as expected tsunami event frequency, possible wave heights, or impacts on shorelines and population. Similarly, we can thus not adequately assess the risk to shores and population in the traditional sense. 275 It is important to emphasise that the point system used in our MCDA is based on arbitrary point scales, assigned to be 265 cover the range of values used to build the ranking score. Any evaluation of this type will inherently involve arbitrari chosen scores that have to consider and weigh the many multifaceted factors that contribute to volcano flank instability an the hazards of generating a tsunami. This also means that the factor points and weights are based on our subjecti judgement by how important we think these factors are. Naturally, this leaves a lot of room for arguments on how the poin and weights could be assigned differently, which may significantly change the final score. However, as the rules with whi 270 points are given are kept strictly the same for all volcanoes, we retain the comparability of our results, allowing a meaningf identification of the most hazardous volcanoes for tsunami generation. This is despite the individual score by itself havin little meaning in terms of hard data, such as expected tsunami event frequency, possible wave heights, or impacts shorelines and population. Similarly, we can thus not adequately assess the risk to shores and population in the tradition sense. 275 Another important consideration is that we cannot consider all factors that are known or suspected to impact t tsunamigenic potential of a volcano. The most noteworthy ones are (1) ongoing flank deformations (e.g., through dy intrusions or slow décollement movement), which can destabilise parts of the edifice, and (2) absence of bathymetric da covering the underwater geometry of the volcanoes. Because the lack of high quality and accessible data for all volcano makes meaningful comparison of the impact of these factors on the tsunami hazard impossible, we could only consider the 280 factors by proxy. 2.3 Ranking assumptions and limitations 260 There are many factors influencing the tsunami hazard posed by volcanoes and not all of them can be quantitatively evaluated. Furthermore, even for the ones which can be evaluated, certain assumptions have to be made in order to create a comparable baseline to judge all volcanoes on an equal basis. Here we address some of the issues with the data used in our ranking approach: It is important to emphasise that the point system used in our MCDA is based on arbitrary point scales, assigned to best 265 cover the range of values used to build the ranking score. Any evaluation of this type will inherently involve arbitrarily chosen scores that have to consider and weigh the many multifaceted factors that contribute to volcano flank instability and the hazards of generating a tsunami. This also means that the factor points and weights are based on our subjective judgement by how important we think these factors are. Naturally, this leaves a lot of room for arguments on how the points It is important to emphasise that the point system used in our MCDA is based on arbitrary point scales, assigned to best 265 cover the range of values used to build the ranking score. Any evaluation of this type will inherently involve arbitrarily chosen scores that have to consider and weigh the many multifaceted factors that contribute to volcano flank instability and the hazards of generating a tsunami. This also means that the factor points and weights are based on our subjective judgement by how important we think these factors are. Naturally, this leaves a lot of room for arguments on how the points It is important to emphasise that the point system used in our MCDA is based on arbitrary point scales, assigned to best 265 cover the range of values used to build the ranking score. Any evaluation of this type will inherently involve arbitrarily chosen scores that have to consider and weigh the many multifaceted factors that contribute to volcano flank instability and the hazards of generating a tsunami. This also means that the factor points and weights are based on our subjective judgement by how important we think these factors are. Naturally, this leaves a lot of room for arguments on how the points and weights could be assigned differently, which may significantly change the final score. 2.3 Ranking assumptions and limitations 260 For instance, eruptive activity of a volcano increases the likelihood of ongoing deformation and thus it and weights could be assigned differently, which may significantly change the final score. However, as the rules with which 270 points are given are kept strictly the same for all volcanoes, we retain the comparability of our results, allowing a meaningful identification of the most hazardous volcanoes for tsunami generation. This is despite the individual score by itself having little meaning in terms of hard data, such as expected tsunami event frequency, possible wave heights, or impacts on shorelines and population. Similarly, we can thus not adequately assess the risk to shores and population in the traditional sense. 275 Another important consideration is that we cannot consider all factors that are known or suspected to impact the tsunamigenic potential of a volcano. The most noteworthy ones are (1) ongoing flank deformations (e.g., through dyke intrusions or slow décollement movement), which can destabilise parts of the edifice, and (2) absence of bathymetric data covering the underwater geometry of the volcanoes. Because the lack of high quality and accessible data for all volcanoes Another important consideration is that we cannot consider all factors that are known or suspected to impact the tsunamigenic potential of a volcano. The most noteworthy ones are (1) ongoing flank deformations (e.g., through dyke intrusions or slow décollement movement), which can destabilise parts of the edifice, and (2) absence of bathymetric data covering the underwater geometry of the volcanoes. Because the lack of high quality and accessible data for all volcanoes makes meaningful comparison of the impact of these factors on the tsunami hazard impossible, we could only consider these 280 factors by proxy. For instance, eruptive activity of a volcano increases the likelihood of ongoing deformation and thus it is makes meaningful comparison of the impact of these factors on the tsunami hazard impossible, we could only consider these 280 factors by proxy. For instance, eruptive activity of a volcano increases the likelihood of ongoing deformation and thus it is 13 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. indirectly tied to the activity factor points. However, not all erupting volcanoes are likely to experience significant deformation and, on the other hand, there may be significant deformation without an eruption (e.g., due to the intrusion of magma underground). For the underwater geometry, our analysis is simplified to whether the volcano is partially or fully in the water, thus counting towards the hazardous features factor points. But it neglects potential steep underwater flanks, 285 which also means that some potentially hazardous submarine volcanoes had to be excluded from our catalogue as they had no subaerial edifice to examine. Here, these are Banua Wuhu, Indonesia, and Hankow Reef, Papua New Guinea. Future studies could take these missing factors into account properly and warrant their own point scores, provided that data quality, regularity, and availability of surveys improve. indirectly tied to the activity factor points. However, not all erupting volcanoes are likely to experience significant deformation and, on the other hand, there may be significant deformation without an eruption (e.g., due to the intrusion of magma underground). For the underwater geometry, our analysis is simplified to whether the volcano is partially or fully in the water, thus counting towards the hazardous features factor points. But it neglects potential steep underwater flanks, 285 which also means that some potentially hazardous submarine volcanoes had to be excluded from our catalogue as they had no subaerial edifice to examine. Here, these are Banua Wuhu, Indonesia, and Hankow Reef, Papua New Guinea. Future studies could take these missing factors into account properly and warrant their own point scores, provided that data quality, regularity, and availability of surveys improve. Data based on historic observations is often flawed as they were not always systematically recorded. This includes historical 290 tsunamis, flank collapses, and eruptions. The problem is facilitated the further the events lie back in time, and many events may be missed or wrongly interpreted because they were either not understood properly or simply not noticed or remembered. For instance, some volcanoes have unknown eruption dates and thus received a relatively low rating, even when it is quite likely that its last eruption happened only decades ago. One example is Balbi volcano, Papua New Guinea, which likely erupted around the early 1800s, but this is unconfirmed (Global Volcanism Program, 2013). This creates a 295 slight bias towards volcanoes that are well-known and researched, whereas volcanoes with less scientific attention may receive lower ratings. Thus, our analyses may be prone to missing or incorrectly recorded events. For tsunamis, we tried to minimise this bias by incorporating data from multiple databases and studies (Hamzah et al., 2000; Paris et al., 2014; Mutaqin et al., 2019; Hidayat et al., 2020; NGDC, 2021). Surprisingly, no study had the exact same tsunami events listed and some were only found in certain reviews. Our compilation thus likely marks the most comprehensive list of historic 300 tsunamis in SE-Asia to date, however, there are likely some further events that were missed or not recorded. which likely erupted around the early 1800s, but this is unconfirmed (Global Volcanism Program, 2013). This creates a 295 slight bias towards volcanoes that are well-known and researched, whereas volcanoes with less scientific attention may receive lower ratings. Thus, our analyses may be prone to missing or incorrectly recorded events. For tsunamis, we tried to minimise this bias by incorporating data from multiple databases and studies (Hamzah et al., 2000; Paris et al., 2014; Mutaqin et al., 2019; Hidayat et al., 2020; NGDC, 2021). Surprisingly, no study had the exact same tsunami events listed which likely erupted around the early 1800s, but this is unconfirmed (Global Volcanism Program, 2013). This creates a 295 slight bias towards volcanoes that are well-known and researched, whereas volcanoes with less scientific attention may receive lower ratings. Thus, our analyses may be prone to missing or incorrectly recorded events. For tsunamis, we tried to minimise this bias by incorporating data from multiple databases and studies (Hamzah et al., 2000; Paris et al., 2014; Mutaqin et al., 2019; Hidayat et al., 2020; NGDC, 2021). Surprisingly, no study had the exact same tsunami events listed and some were only found in certain reviews. Our compilation thus likely marks the most comprehensive list of historic 300 tsunamis in SE-Asia to date, however, there are likely some further events that were missed or not recorded. For evidence of edifice instability the problem is similar. Many collapse scars related to such instability or lateral blasts can be obscured by the regrowth of the volcano and are thus easy to miss. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. While we consider gravitational instability of volcanic edifices by measuring the slope steepness, additional factors can play an important role that could not be considered here as they are unknown for most volcanoes. These are mainly the lithological properties of the flank and the rock mass strength (Watters et al., 2000). Furthermore, the nature of the volcanic 315 flanks deposits and their state of consolidation is likely to play a role on how resistant they are to oversteepening and destabilisation. For instance, one factor that is speculated to have contributed to the 2018 Anak Krakatau flank collapse is that it consisted of loose unconsolidated pyroclastics covered with lavas (Grilli et al., 2019), which likely contributed to the instability. While we consider gravitational instability of volcanic edifices by measuring the slope steepness, additional factors can play an important role that could not be considered here as they are unknown for most volcanoes. These are mainly the lithological properties of the flank and the rock mass strength (Watters et al., 2000). Furthermore, the nature of the volcanic 315 flanks deposits and their state of consolidation is likely to play a role on how resistant they are to oversteepening and destabilisation. For instance, one factor that is speculated to have contributed to the 2018 Anak Krakatau flank collapse is that it consisted of loose unconsolidated pyroclastics covered with lavas (Grilli et al., 2019), which likely contributed to the instability. On the other hand, gradual erosion and destabilisation due to hydrothermally weakened rocks (Darmawan et al., 2022) may produce scars that are very similar to collapse scars and consequently very challenging to distinguish using satellite data. Finally, submarine debris avalanche deposits which are 305 evidence for past edifice failures that reached the sea are poorly studied since the required bathymetry data is rarely acquired. Here, Silver et al. (2009) was specifically investigating volcanic debris avalanches for most volcanoes in Papua New Guinea, so this region can be considered reasonably well covered. However, no similar studies exist for Indonesia or the Philippines, making some oversights likely. due to hydrothermally weakened rocks (Darmawan et al., 2022) may produce scars that are very similar to collapse scars and consequently very challenging to distinguish using satellite data. Finally, submarine debris avalanche deposits which are 305 evidence for past edifice failures that reached the sea are poorly studied since the required bathymetry data is rarely acquired. Here, Silver et al. (2009) was specifically investigating volcanic debris avalanches for most volcanoes in Papua New Guinea, so this region can be considered reasonably well covered. However, no similar studies exist for Indonesia or the Philippines, making some oversights likely. When analysing the vegetation cover of the volcanoes using the Sentinel-2 satellite images we found that the vegetation is 310 subject to seasonal changes. Mainly this encompasses vegetation colour changes due to dry or rainy periods. Since our analysis is kept rather simple and qualitative rather than quantitative, this effect is unlikely to impact our results. When analysing the vegetation cover of the volcanoes using the Sentinel-2 satellite images we found that the vegetation is 310 subject to seasonal changes. Mainly this encompasses vegetation colour changes due to dry or rainy periods. Since our analysis is kept rather simple and qualitative rather than quantitative, this effect is unlikely to impact our results. 14 3.1 Volcano catalogue and ranking Using the factor points and weights described in section 2.2, we ranked the volcanoes in our catalogue by their tsunami hazard. An overview is presented in Fig. 3 and a list of the 40 highest-scoring volcanoes is shown in table 2. A complete, more detailed, and interactive version of this list with individual entries relating to how the points were counted can be found in the supplementary material. The points range from 76 (Batu Tara, Indonesia), representing the highest tsunami hazard, to 325 13 (Baluan, Papua New Guinea), representing the lowest tsunami hazard. Using these results, we grouped the volcanoes into high, medium, and low tsunami hazard categories based on their relative score. High hazard is assigned for volcanoes having more than 55 points (~14% of the volcanoes in the catalogue), medium hazard is assigned to volcanoes with scores between 40 and 55 points (~36% of the volcanoes in the catalogue) and low hazard category is assigned to volcanoes with less than in the supplementary material. The points range from 76 (Batu Tara, Indonesia), representing the highest tsunami hazard, to 325 13 (Baluan, Papua New Guinea), representing the lowest tsunami hazard. Using these results, we grouped the volcanoes into high, medium, and low tsunami hazard categories based on their relative score. High hazard is assigned for volcanoes having more than 55 points (~14% of the volcanoes in the catalogue), medium hazard is assigned to volcanoes with scores between 40 and 55 points (~36% of the volcanoes in the catalogue) and low hazard category is assigned to volcanoes with less than in the supplementary material. The points range from 76 (Batu Tara, Indonesia), representing the highest tsunami hazard, to 325 13 (Baluan, Papua New Guinea), representing the lowest tsunami hazard. Using these results, we grouped the volcanoes into high, medium, and low tsunami hazard categories based on their relative score. High hazard is assigned for volcanoes having more than 55 points (~14% of the volcanoes in the catalogue), medium hazard is assigned to volcanoes with scores between 40 and 55 points (~36% of the volcanoes in the catalogue) and low hazard category is assigned to volcanoes with less than 40 points (~49% of volcanoes in the catalogue). 3.1 Volcano catalogue and ranking Volcanoes like Anak Krakatau, Indonesia, and Ritter Island, Papua New 330 Guinea are among the highest tsunami hazard volcanoes in our ranking, which is little surprise considering both their history of powerful eruptions and catastrophic tsunamis (Paris et al., 2014). However, we also identify high high-hazard volcanoes that are not as prominently considered for their tsunamigenic potential, but received similarly high scores. In Indonesia these include Batu Tara, Gamalama, Iliwerung, Karangetang, Nila, Sangeang Api, Wetar, Sirung, Serua and Ruang. For Papua 40 points (~49% of volcanoes in the catalogue). Volcanoes like Anak Krakatau, Indonesia, and Ritter Island, Papua New 330 Guinea are among the highest tsunami hazard volcanoes in our ranking, which is little surprise considering both their history of powerful eruptions and catastrophic tsunamis (Paris et al., 2014). However, we also identify high high-hazard volcanoes that are not as prominently considered for their tsunamigenic potential, but received similarly high scores. In Indonesia these include Batu Tara, Gamalama, Iliwerung, Karangetang, Nila, Sangeang Api, Wetar, Sirung, Serua and Ruang. For Papua New Guinea we identify Kadovar, Rabaul, Ritter Island, Manam, Bam, Langila and Ulawun as volcanoes with high tsunami 335 hazard. For the Philippines, only Didicas is classified as a high tsunami hazard volcano. New Guinea we identify Kadovar, Rabaul, Ritter Island, Manam, Bam, Langila and Ulawun as volcanoes with high tsunami 335 hazard. For the Philippines, only Didicas is classified as a high tsunami hazard volcano. 15 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Figure 3: Maps of the volcanoes in the catalogue with their corresponding ranking score and the resulting hazard category. Figure 3: Maps of the volcanoes in the catalogue with their corresponding ranking score and the resulting hazard category. For a detailed overview of tsunami hazard scores for all volcanoes in the catalogue, see table 2. Base map data source: © 0 OpenStreetMap contributors 2022. Distributed under the Open Data Commons Open Database License (ODbL) v1.0. Figure 3: Maps of the volcanoes in the catalogue with their corresponding ranking score Figure 3: Maps of the volcanoes in the catalogue with their corresponding ranking score and the resulting hazard category. Figure 3: Maps of the volcanoes in the catalogue with their corresponding ranking score and the resulting hazard category. 3.1 Volcano catalogue and ranking For a detailed overview of tsunami hazard scores for all volcanoes in the catalogue, see table 2. Base map data source: © 40 OpenStreetMap contributors 2022. Distributed under the Open Data Commons Open Database License (ODbL) v1.0. For a detailed overview of tsunami hazard scores for all volcanoes in the catalogue, see table 2. Base map data source: © 340 OpenStreetMap contributors 2022. Distributed under the Open Data Commons Open Database License (ODbL) v1.0. For a detailed overview of tsunami hazard scores for all volcanoes in the catalogue, see table 2. Base map data source: © 340 OpenStreetMap contributors 2022. Distributed under the Open Data Commons Open Database License (ODbL) v1.0. 16 Volcano Country Points: H/D-Ratio Points: Volcanic Activity Points: Tsunamigenic History Points: Slope Angle Points: Hazardous Features Total weighted Score Batu Tara Indonesia 83 95 20 100 65 76 Anak Krakatau (pre-2018) Indonesia 52 100 80 60 80 76 Kadovar Papua New Guinea 79 100 20 74 80 72 Ritter Island Papua New Guinea 100 87 60 39 65 72 Iliwerung Indonesia 45 100 40 70 70 68 Anak Indonesia 21 100 90 36 80 67 16 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. 3.1 Volcano catalogue and ranking Krakatau Gamalama Indonesia 40 98 50 63 70 67 Rabaul Papua New Guinea 62 94 30 67 70 67 Manam Papua New Guinea 41 100 20 76 90 66 Didicas Philippines 89 78 10 73 65 64 Sangeang Api Indonesia 36 100 20 67 70 61 Karangetang Indonesia 49 100 0 72 70 61 Langila Papua New Guinea 29 100 20 65 75 60 Sirung Indonesia 47 95 0 62 85 59 Ulawun Papua New Guinea 25 100 20 68 60 59 Wetar Indonesia 86 50 10 86 65 58 Nila Indonesia 50 77 0 67 95 56 Ruang Indonesia 45 82 20 64 55 56 Bam Papua New Guinea 50 76 20 68 55 56 Serua/ Legatala Indonesia 70 73 0 67 65 56 Lewotolok Indonesia 40 100 0 56 55 55 Agung Indonesia 25 99 10 65 50 55 Paluweh/ Rokatenda Indonesia 32 93 20 49 65 55 Barren Island India 33 100 0 48 80 54 Teon/ Serawerna Indonesia 51 71 20 63 60 54 Rinjani Indonesia 20 96 0 67 75 54 Iya Indonesia 49 77 10 64 60 54 Banda Api Indonesia 52 79 0 62 70 54 Gamkonora Indonesia 33 87 20 53 60 53 c⃝Author(s) 2022. CC BY 4.0 License. 17 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Karkar/ Uluman Papua New Guinea 26 94 10 49 80 53 Awu Indonesia 24 84 40 48 55 53 Taal Philippines 2 100 50 21 75 52 Soputan Indonesia 10 100 20 53 50 52 Mayon Philippines 25 99 0 64 35 51 Makian Indonesia 36 79 10 57 65 51 Biliran Philippines 32 74 20 70 40 51 Camiguin Philippines 30 76 10 63 65 50 Bagana Papua New Guinea 12 100 0 70 35 50 Babuyan Claro Philippines 32 73 20 43 90 50 Table 2: List of the 40 highest scoring volcanoes in our catalogue and their respective MC Table 2: List of the 40 highest scoring volcanoes in our catalogue and their respective MCDA ranking of the relative tsunami hazard, showing individual factor points and the final score. The factor weights for the total score are H/D-ratio 345 (20%), volcanic activity (30%), tsunamigenic history (20%), slope angle (20%), and hazardous features (10%). For the full catalogue and ranking table see the supplementary material. 3.1 Volcano catalogue and ranking g g g p g tsunami hazard, showing individual factor points and the final score. The factor weights for the total score are H/D-ratio 345 (20%), volcanic activity (30%), tsunamigenic history (20%), slope angle (20%), and hazardous features (10%). For the full catalogue and ranking table see the supplementary material. The results of the ranking robustness testing are summarised in Fig. 4, showing that the higher scoring volcanoes in our ranking generally still score high and are independent of the factor weight, which adds confidence to our results. The only 350 notable exceptions here are at the transitions between low and medium hazard categories (e.g., Hiri, Indonesia, or Tolokiwa, Papua New Guinea) in Fig 4a and 4b, which is indicating that these volcanoes are likely more sensitive to individual weights and, thus, less robustly ranked. The lower the volcanoes are ranked, the less robust the ranking order becomes, which is likely due to a higher number of volcanoes with similar scores. g g g g g g ranking generally still score high and are independent of the factor weight, which adds confidence to our results. The only 350 notable exceptions here are at the transitions between low and medium hazard categories (e.g., Hiri, Indonesia, or Tolokiwa, Papua New Guinea) in Fig 4a and 4b, which is indicating that these volcanoes are likely more sensitive to individual weights and, thus, less robustly ranked. The lower the volcanoes are ranked, the less robust the ranking order becomes, which is likely due to a higher number of volcanoes with similar scores. 355 18 Figure 4: Robustness test of the factor weights used in the ranking. This counts the number of times a volcano made it into the top 5, 10, 15 and 20 places in the ranking with different individual weights. This is displayed per countries a) Indonesia, b) Papua New Guinea and c) Philippines. It generally shows that the volcanoes we classed as high, medium and low hazard are well generally sorted in the order we classed them in, despite different factor weights and with only few exceptions. This 60 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Figure 4: Robustness test of the factor weights used in the ranking. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. shows that changing the factor weights may slightly change the order in which the volcanoes are ranked, but our analysis is generally classifying higher hazard volcanoes correctly, confirming the robustness of our ranking. shows that changing the factor weights may slightly change the order in which the volcanoes are ranked, but our analysis is generally classifying higher hazard volcanoes correctly, confirming the robustness of our ranking. 3.1 Volcano catalogue and ranking This counts the number of times a volcano made it into the top 5, 10, 15 and 20 places in the ranking with different individual weights. This is displayed per countries a) Indonesia, b) Papua New Guinea and c) Philippines. It generally shows that the volcanoes we classed as high, medium and low hazard are well generally sorted in the order we classed them in, despite different factor weights and with only few exceptions. This the top 5, 10, 15 and 20 places in the ranking with different individual weights. This is displayed per countries a) Indonesia, b) Papua New Guinea and c) Philippines. It generally shows that the volcanoes we classed as high, medium and low hazard are well generally sorted in the order we classed them in, despite different factor weights and with only few exceptions. This 360 are well generally sorted in the order we classed them in, despite different factor weights and with only few exceptions. This 360 360 19 3.2 Volcano distribution and tsunami causes Most of the high and medium tsunami hazard volcanoes are located in Indonesia, which by itself is not surprising since 365 Indonesia also has the most volcanoes in our catalogue (~46%). However, the relative amount of these volcanoes in those categories is significantly higher (Fig. 5), suggesting that Indonesia has an over-proportionally high number of hazardous volcanoes. This is further evident in the low tsunami hazard category, which are dominantly from Papua New Guinea (Fig. 5). Volcanoes of the Philippines are only underrepresented in the high tsunami hazard category, but this may be due to the lower number of overall volcanoes. 370 Most of the high and medium tsunami hazard volcanoes are located in Indonesia, which by itself is not surprising since 365 Indonesia also has the most volcanoes in our catalogue (~46%). However, the relative amount of these volcanoes in those categories is significantly higher (Fig. 5), suggesting that Indonesia has an over-proportionally high number of hazardous volcanoes. This is further evident in the low tsunami hazard category, which are dominantly from Papua New Guinea (Fig. 5). Volcanoes of the Philippines are only underrepresented in the high tsunami hazard category, but this may be due to the lower number of overall volcanoes. 370 Figure 5: Tsunamigenic hazard from individual volcanoes by country. Shown are (a) all considered volcanoes and their hazard categories according to our ranking, then their respective distribution between the countries for (b) high hazard, (c) medium hazard, and (d) low hazard volcanoes. We find a disproportionately large number of high and medium hazard 375 375 20 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. category volcanoes located in Indonesia (~64% and ~59%, respectively), which is much larger than expected since Indonesian volcanoes make up only ~46% of all volcanoes in our catalogue. Contrary, the Philippines have a lower share of high-hazard volcanoes (~4% only one volcano), but make up 18% of all volcanoes in our catalogues. Papua New Guinean volcanoes make up ~35% of the catalogue, so they can be considered underrepresented in the medium hazard category and overrepresented in the low hazard category. 380 category volcanoes located in Indonesia (~64% and ~59%, respectively), which is much larger than expected since Indonesian volcanoes make up only ~46% of all volcanoes in our catalogue. Contrary, the Philippines have a lower share of high-hazard volcanoes (~4% only one volcano), but make up 18% of all volcanoes in our catalogues. Papua New Guinean volcanoes make up ~35% of the catalogue, so they can be considered underrepresented in the medium hazard category and overrepresented in the low hazard category. 380 380 Our review of historical tsunamis in Southeast Asia contains 61 distinct events (Table 1) and shows that the majority of the historical volcanogenic tsunamis still have an unknown or uncertain cause (Fig. 6). However, we can still extract that the most known or suspected causes were explosions (21%), followed by mass movements like pyroclastic flows (19%) and historical volcanogenic tsunamis still have an unknown or uncertain cause (Fig. 6). However, we can still extract that the most known or suspected causes were explosions (21%), followed by mass movements like pyroclastic flows (19%) and landslides (14%). Volcanic earthquakes rarely cause tsunamis by themselves since volcanic quakes are usually much weaker 385 compared to tectonic events and lava dome growth is a rather specific eruption style and thus less frequent in producing tsunamis (here only 2 cases). Some cascading events also occurred involving multiple causes (here 3 cases), which were once an earthquake and a landslide, and twice an explosion and pyroclastic flow. It is noteworthy that most known cases of volcanogenic tsunamis are produced by pyroclastic flows and explosions, both of which are commonly associated with strong eruptive activity. Gravitational failures such as landslides or lava dome collapses occur less frequently, but do not 390 il i i i landslides (14%). https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. attributed to explosions, whereas earthquakes and lava domes rarely produce tsunamis. For the purpose of this figure, air waves were grouped with explosions as they also require a strong explosion. attributed to explosions, whereas earthquakes and lava domes rarely produce tsunamis. For the purpose of this figure, air waves were grouped with explosions as they also require a strong explosion. Volcanic earthquakes rarely cause tsunamis by themselves since volcanic quakes are usually much weaker 385 compared to tectonic events and lava dome growth is a rather specific eruption style and thus less frequent in producing tsunamis (here only 2 cases). Some cascading events also occurred involving multiple causes (here 3 cases), which were once an earthquake and a landslide, and twice an explosion and pyroclastic flow. It is noteworthy that most known cases of volcanogenic tsunamis are produced by pyroclastic flows and explosions, both of which are commonly associated with landslides (14%). Volcanic earthquakes rarely cause tsunamis by themselves since volcanic quakes are usually much weaker 385 compared to tectonic events and lava dome growth is a rather specific eruption style and thus less frequent in producing tsunamis (here only 2 cases). Some cascading events also occurred involving multiple causes (here 3 cases), which were once an earthquake and a landslide, and twice an explosion and pyroclastic flow. It is noteworthy that most known cases of volcanogenic tsunamis are produced by pyroclastic flows and explosions, both of which are commonly associated with strong eruptive activity. Gravitational failures such as landslides or lava dome collapses occur less frequently, but do not 390 necessarily require ongoing eruptions. strong eruptive activity. Gravitational failures such as landslides or lava dome collapses occur less frequently, but do not 390 necessarily require ongoing eruptions. Figure 6: The historical causes of volcanogenic tsunamis in SE-Asia sourced from table 1, uncertain causes are marked transparent. A third of all cases is caused by mass movements (pyroclastic flows and landslides) and about a fifth is 395 Figure 6: The historical causes of volcanogenic tsunamis in SE-Asia sourced from table 1, uncertain causes are marked transparent. A third of all cases is caused by mass movements (pyroclastic flows and landslides) and about a fifth is 395 Figure 6: The historical causes of volcanogenic tsunamis in SE-Asia sourced from table 1, uncertain causes are marked transparent. A third of all cases is caused by mass movements (pyroclastic flows and landslides) and about a fifth is 395 21 4.1 Evaluating scores and ranking through recent tsunami events However, the 2018 flank collapse indeed 410 lowered the score, which is reasonable since the main volcanic edifice has yet to rebuild after the collapse. Further tsunamis through further collapses, explosions or pyroclastic flows are still potential tsunami causes that may occur at Anak Krakatau in the near future. For Kadovar, the changes were different. While the 2018 eruption produced a new vent and formed a littoral lava dome (Plank et al., 2019), the overall topography of the island did not change significantly. Here, the tsunami was not generated as 415 a result of a major flank collapse but rather due to a collapse of the littoral dome and smaller parts of the southern flank (Plank et al., 2019). However, before the eruption, Kadovar had no known historic eruptions, although it is possible that one occurred in 1700, but this is unconfirmed (Llanes et al., 2009; Global Volcanism Program, 2013). In 1976 the island residents were briefly evacuated due to strong fumarolic activity and fears of an eruption, which ultimately did not occur (Plank et al., 2019), the overall topography of the island did not change significantly. Here, the tsunami was not generated as 415 a result of a major flank collapse but rather due to a collapse of the littoral dome and smaller parts of the southern flank (Plank et al., 2019). However, before the eruption, Kadovar had no known historic eruptions, although it is possible that one occurred in 1700, but this is unconfirmed (Llanes et al., 2009; Global Volcanism Program, 2013). In 1976 the island residents were briefly evacuated due to strong fumarolic activity and fears of an eruption, which ultimately did not occur (Llanes et al., 2009). Thus, before its 2018 eruption, the island could only be considered to have historic unrest, which 420 lowered the score significantly. The score was 45 points before the 2018 tsunami, meaning Kadovar would still have been identified as a volcano with an elevated hazard (medium category) before the eruption. However, given its high eruptive activity now, the score has increased strongly. If the unconfirmed eruption in 1700 is included, the hazard score would be significantly higher at 54 points, just outside the high hazard category. This highlights that a better constrained volcanic (Llanes et al., 2009). Thus, before its 2018 eruption, the island could only be considered to have historic unrest, which 420 lowered the score significantly. 4.1 Evaluating scores and ranking through recent tsunami events In recent years, both Anak Krakatau, Indonesia, and Kadovar, Papua New Guinea, produced tsunamis, with good-quality 400 topographic data available and their circumstances being well known (Plank et al., 2019; Walter et al., 2019). One important aspect when judging the usefulness of our ranking is its ability to correctly identify volcanoes that are most likely to produce tsunamis in the future. We tested this by comparing the scores of both volcanoes as it is now compared to how it was before the event. The morphology of Anak Krakatau has changed quite significantly following the 2018 flank collapse (Darmawan p gy g q g y g p ( et al., 2020). The island is reduced in size and became lower in elevation, which consequently reduced the H/D-ratio factor 405 points. However, it now has a crater that is open to the sea and it still has a history of many tsunamis and regular recent eruptions, thus only changing the score slightly from 76 points before the collapse to 67 points after (Table 2). Consequently, Anak Krakatau was the highest hazard volcano before its collapse and tsunami occurred, confirming that our approach would have correctly identified the volcano as a threat. Now, after the collapse, it is still among the highest scoring volcanoes, et al., 2020). The island is reduced in size and became lower in elevation, which consequently reduced the H/D-ratio factor 405 points. However, it now has a crater that is open to the sea and it still has a history of many tsunamis and regular recent eruptions, thus only changing the score slightly from 76 points before the collapse to 67 points after (Table 2). Consequently, Anak Krakatau was the highest hazard volcano before its collapse and tsunami occurred, confirming that our approach would have correctly identified the volcano as a threat. Now, after the collapse, it is still among the highest scoring volcanoes, meaning the recent 2018 tsunami and the event changed little in its overall status. However, the 2018 flank collapse indeed 410 lowered the score, which is reasonable since the main volcanic edifice has yet to rebuild after the collapse. Further tsunamis through further collapses, explosions or pyroclastic flows are still potential tsunami causes that may occur at Anak Krakatau in the near future. meaning the recent 2018 tsunami and the event changed little in its overall status. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. facing flank and the littoral lava dome are still in place and may pose a large tsunami hazard in the future, especially if the eruptive activity continues. From both these cases we can conclude that our ranking system is able to identify haz From both these cases we can conclude that our ranking system is able to identify hazardous volcanoes reasonably well before a tsunami occurs. While individual volcano scores may change significantly over time due to eruptions or 430 morphological changes, the applied multi-categorized approach has worked well for both Anak Krakatau and Kadovar. However, these cases also emphasise that particular attention should be devoted to coastal volcanoes with unclear eruptive histories, especially when they become active after decades or centuries of no activity. 4.1 Evaluating scores and ranking through recent tsunami events The score was 45 points before the 2018 tsunami, meaning Kadovar would still have been identified as a volcano with an elevated hazard (medium category) before the eruption. However, given its high eruptive activity now, the score has increased strongly. If the unconfirmed eruption in 1700 is included, the hazard score would be significantly higher at 54 points, just outside the high hazard category. This highlights that a better constrained volcanic (Llanes et al., 2009). Thus, before its 2018 eruption, the island could only be considered to have historic unrest, which 420 lowered the score significantly. The score was 45 points before the 2018 tsunami, meaning Kadovar would still have been identified as a volcano with an elevated hazard (medium category) before the eruption. However, given its high eruptive activity now, the score has increased strongly. If the unconfirmed eruption in 1700 is included, the hazard score would be significantly higher at 54 points, just outside the high hazard category. This highlights that a better constrained volcanic history on some volcanoes can significantly improve the meaningfulness of this ranking. Now, after the 2018 tsunami, 425 Kadovar scores 72 points, making it the third highest tsunami hazard in SE-Asia based on our ranking. Both the steep south- history on some volcanoes can significantly improve the meaningfulness of this ranking. Now, after the 2018 tsunami, 425 Kadovar scores 72 points, making it the third highest tsunami hazard in SE-Asia based on our ranking. Both the steep south- 22 4.2 Future tsunami hazards in SE-Asia To allow for a more detailed look at future tsunami hazards in SE-Asia we summarised in which locations a high 435 concentration of hazardous volcanoes is located. This was done by performing a weighted point density calculation, highlighting areas where many tsunamigenic volcanoes are located closely together, with their impact multiplied by the hazards score (Fig. 7). The result shows that the area with the highest volcanogenic tsunami hazard is located around the Indonesian Lesser Sunda Islands, particularly between East Nusa Tenggara and the Alor archipelago, at the Molucca Sea coast between northern Sulawesi and Halmahera, and at the southern Bismarck Sea in Papua New Guinea. Further elevated 440 hazard areas can be found within the Indonesian Banda Sea, the Philippine Luzon Strait, the central Philippine Islands, and along the southern Solomon Sea coast of Papua New Guinea. These areas can thus be considered to be the most important to prioritise for tsunami monitoring, modelling and forecasting. coast between northern Sulawesi and Halmahera, and at the southern Bismarck Sea in Papua New Guinea. Further elevated 440 hazard areas can be found within the Indonesian Banda Sea, the Philippine Luzon Strait, the central Philippine Islands, and along the southern Solomon Sea coast of Papua New Guinea. These areas can thus be considered to be the most important to prioritise for tsunami monitoring, modelling and forecasting. coast between northern Sulawesi and Halmahera, and at the southern Bismarck Sea in Papua New Guinea. Further elevated 440 hazard areas can be found within the Indonesian Banda Sea, the Philippine Luzon Strait, the central Philippine Islands, and along the southern Solomon Sea coast of Papua New Guinea. These areas can thus be considered to be the most important to prioritise for tsunami monitoring, modelling and forecasting. 23 23 445 Figure 7: Heat map resulting from weighted point density calculation using the hazard score. Shown are the most likely source areas of volcanogenic tsunamis, with a higher density meaning the area is closer to many tsunamigenic volcanoes. This does not represent the travel distance or wave heights of a potential tsunami, which may affect more distal coasts, but only highlights the most likely source regions of a tsunami. Base map data source: © OpenStreetMap contributors 2022. Distributed under the Open Data Commons Open Database License (ODbL) v1.0. 450 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. 5 https://doi.org/10.5194/egusphere-2022-130 Preprint. 4.2 Future tsunami hazards in SE-Asia Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Figure 7: Heat map resulting from weighted point density calculation using the hazard score. Shown are the most likely source areas of volcanogenic tsunamis, with a higher density meaning the area is closer to many tsunamigenic volcanoes. This does not represent the travel distance or wave heights of a potential tsunami, which may affect more distal coasts, but only highlights the most likely source regions of a tsunami. Base map data source: © OpenStreetMap contributors 2022. Distributed under the Open Data Commons Open Database License (ODbL) v1.0. 450 Figure 7: Heat map resulting from weighted point density calculation using the hazard score. Shown are the most likely source areas of volcanogenic tsunamis, with a higher density meaning the area is closer to many tsunamigenic volcanoes. This does not represent the travel distance or wave heights of a potential tsunami, which may affect more distal coasts, but only highlights the most likely source regions of a tsunami. Base map data source: © OpenStreetMap contributors 2022. Distributed under the Open Data Commons Open Database License (ODbL) v1.0. 450 To account for the potential spatial impact of volcanogenic tsunamis, we extend our tsunami hazard evaluation by assessing the total length of a coastline affected within one and two hours of tsunami propagation for the volcanoes categorised as high hazard in our ranking (except Didicas). For that, we compute tsunami travel times (TTT) from point sources centred at each volcano position using the SRM30+ bathymetry (Becker et al., 2009) resampled to 1 arc minute resolution and the numerical algorithm as proposed by Marchuk (2008). Fig. 8 shows tsunami propagation fronts after 1 hour of wave propagation. Table 455 3, in turn, lists the total lengths of the coastlines affected after 1 and 2 hours of propagation, respectively. Detailed tsunami travel time plots for the individual volcanoes can be found in the supplementary figures 1, 2 and 3. It is important to note that this type of simulation only includes the travel time of the tsunami, but not other important characteristics such as wave amplitude. algorithm as proposed by Marchuk (2008). Fig. 8 shows tsunami propagation fronts after 1 hour of wave propagation. Table 455 3, in turn, lists the total lengths of the coastlines affected after 1 and 2 hours of propagation, respectively. The results show the potentially wide reach of volcanogenic tsunamis in both Indonesia and Papua New Guinea (Fig. 8), but 465 it also reveals surprising differences. Anak Krakatau is only projected to affect ~1600 km of coastline within one hour (Table 1) and the area is restricted mostly within the Sunda Strait coast and parts of southern Java and Sumatra. This is nearly 4.2 Future tsunami hazards in SE-Asia Detailed tsunami travel time plots for the individual volcanoes can be found in the supplementary figures 1, 2 and 3. It is important to note that this type of simulation only includes the travel time of the tsunami, but not other important characteristics such as wave amplitude. 460 24 Volcano Coastline 1h in km Coastline 2h in km Anak Krakatau 1621 3969 Batu Tara 7322 25511 Kadovar 3078 10195 Ritter Island 3933 13370 Gamalama 6069 27900 Rabaul 5007 16380 Manam 2720 9061 Iliwerung 5974 21244 Sangeang Api 5451 18112 Karangetang 5819 24147 Langila 3955 13174 Sirung 5866 22289 Ulawun 2521 11527 Wetar 8512 27519 Nila 6117 23948 Ruang 6019 24998 Bam 2841 9012 Serua 6498 23998 Table 3: The affected coastline of a tsunami originating from high hazard volcanoes extracted using the tsunami travel time modelling We note that Anak Krakatau where the most prominent event in recent years occurred in 2018 affects the lowest https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Volcano Coastline 1h in km Coastline 2h in km Anak Krakatau 1621 3969 Batu Tara 7322 25511 Kadovar 3078 10195 Ritter Island 3933 13370 Gamalama 6069 27900 Rabaul 5007 16380 Manam 2720 9061 Iliwerung 5974 21244 Sangeang Api 5451 18112 Karangetang 5819 24147 Langila 3955 13174 Sirung 5866 22289 Ulawun 2521 11527 Wetar 8512 27519 Nila 6117 23948 Ruang 6019 24998 Bam 2841 9012 Serua 6498 23998 Table 3: The affected coastline of a tsunami orig modelling. We note that Anak Krakatau, where th Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Table 3: The affected coastline of a tsunami originating from high hazard volcanoes extracted using the tsunami travel time modelling. We note that Anak Krakatau, where the most prominent event in recent years occurred in 2018, affects the lowest length of coastline. This highlights that similar events at other locations can have much more widespread impacts. Table 3: The affected coastline of a tsunami originating from high hazard volcanoes extracted using the tsunami travel time modelling. We note that Anak Krakatau, where the most prominent event in recent years occurred in 2018, affects the lowest length of coastline. This highlights that similar events at other locations can have much more widespread impacts. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. consistent with the 2018 tsunami, where the impacts were only within the Sunda Strait (e.g., Paris et al., 2020). All other volcanoes may produce tsunamis affecting a lot more coasts (Table 3). Batu Tara, which is now the highest scoring volcano in our catalogue, is projected to affect a coastline of ~7300 km, almost 5 times as much as Anak Krakatau within the same 470 time. The longest total affected coastline of ~8500 km (after 1 hour of propagation) is calculated for Wetar, covering almost the entire Banda Sea. Tsunamis from the northern volcanoes in Indonesia are shown to potentially reach up to the Philippines as well as cover large parts of northern Sulawesi and Halmahera and almost all volcanoes in Papua New Guinea (with the exception of Rabaul) reach through most of the Bismarck Sea. consistent with the 2018 tsunami, where the impacts were only within the Sunda Strait (e.g., Paris et al., 2020). All other volcanoes may produce tsunamis affecting a lot more coasts (Table 3). Batu Tara, which is now the highest scoring volcano in our catalogue, is projected to affect a coastline of ~7300 km, almost 5 times as much as Anak Krakatau within the same 470 time. The longest total affected coastline of ~8500 km (after 1 hour of propagation) is calculated for Wetar, covering almost the entire Banda Sea. Tsunamis from the northern volcanoes in Indonesia are shown to potentially reach up to the Philippines as well as cover large parts of northern Sulawesi and Halmahera and almost all volcanoes in Papua New Guinea (with the exception of Rabaul) reach through most of the Bismarck Sea. in our catalogue, is projected to affect a coastline of ~7300 km, almost 5 times as much as Anak Krakatau within the same 470 time. The longest total affected coastline of ~8500 km (after 1 hour of propagation) is calculated for Wetar, covering almost the entire Banda Sea. Tsunamis from the northern volcanoes in Indonesia are shown to potentially reach up to the Philippines as well as cover large parts of northern Sulawesi and Halmahera and almost all volcanoes in Papua New Guinea (with the exception of Rabaul) reach through most of the Bismarck Sea. 4.2 Future tsunami hazards in SE-Asia The results show the potentially wide reach of volcanogenic tsunamis in both Indonesia and Papua New Guinea (Fig. 8), but 465 it also reveals surprising differences. Anak Krakatau is only projected to affect ~1600 km of coastline within one hour (Table 1) and the area is restricted mostly within the Sunda Strait coast and parts of southern Java and Sumatra. This is nearly The results show the potentially wide reach of volcanogenic tsunamis in both Indonesia and Papua New Guinea (Fig. 8), but 465 it also reveals surprising differences. Anak Krakatau is only projected to affect ~1600 km of coastline within one hour (Table 1) and the area is restricted mostly within the Sunda Strait coast and parts of southern Java and Sumatra. This is nearly 25 Despite demonstrating the potential to affect large coastal areas, our modelling does not inform how severe a tsunami from a 475 volcanic source could actually turn out. In fact, tsunami travel time modelling neither accounts for source magnitude, nor for energy transfer. Full source process simulation coupled to modelling of the full wave propagation is needed to assess the magnitude of the coastal impact. In particular, the models are expected to strongly depend on the mechanism triggering the tsunami, i.e., a landslide, PDC or explosion, as well as the magnitude of the event. For example, in landslide or sector Despite demonstrating the potential to affect large coastal areas, our modelling does not inform how severe a tsunami from a 475 volcanic source could actually turn out. In fact, tsunami travel time modelling neither accounts for source magnitude, nor for energy transfer. Full source process simulation coupled to modelling of the full wave propagation is needed to assess the magnitude of the coastal impact. In particular, the models are expected to strongly depend on the mechanism triggering the tsunami, i.e., a landslide, PDC or explosion, as well as the magnitude of the event. For example, in landslide or sector collapse events, the largest runups and the most severe impacts are expected to be largest in the near-field of the volcano, but 480 may still be significant in the far-field (Harris et al., 2012; Grilli et al., 2021). Furthermore, the recent Hunga Tonga-Hunga Haʻapai eruption has shown that large eruptions are capable of generating meteotsunamis travelling long distances without significant loss of amplitude. This particular tsunami also travelled faster than initially expected (Somerville et al., 2022). To compensate for these knowledge gaps, full physics-based source and propagation modelling, especially if they are coupled to collapse events, the largest runups and the most severe impacts are expected to be largest in the near-field of the volcano, but 480 may still be significant in the far-field (Harris et al., 2012; Grilli et al., 2021). Furthermore, the recent Hunga Tonga-Hunga Haʻapai eruption has shown that large eruptions are capable of generating meteotsunamis travelling long distances without significant loss of amplitude. This particular tsunami also travelled faster than initially expected (Somerville et al., 2022). 4.3 Tsunami source volcanoes Looking at individual volcanoes, our catalogue and ranking have identified a large number of potentially hazardous ones regarding the production of tsunamis. In the high hazard category are the Indonesian volcanoes Anak Krakatau, Batu Tara, Gamalama, Iliwerung, Sangeang Api, Karangetang, Sirung, Wetar, Nila, Ruang and Serua. In Papua New Guinea high risk volcanoes include Kadovar, Ritter Island, Rabaul, Manam, Langila, Ulawun and Bam. In the Philippines there is only one 500 high risk volcano - Didicas. Below, we briefly elaborate on the aspects that contribute to the high score of these volcanoes, speculate on the nature of future tsunamis that can be expected from them, and assess which particular volcanoes should be prioritised for tsunami monitoring and forecasting Anak Krakatau and Kadovar have been discussed in the previous section Looking at individual volcanoes, our catalogue and ranking have identified a large number of potentially hazardous ones regarding the production of tsunamis. In the high hazard category are the Indonesian volcanoes Anak Krakatau, Batu Tara, Gamalama, Iliwerung, Sangeang Api, Karangetang, Sirung, Wetar, Nila, Ruang and Serua. In Papua New Guinea high risk Gamalama, Iliwerung, Sangeang Api, Karangetang, Sirung, Wetar, Nila, Ruang and Serua. In Papua New Guinea high risk volcanoes include Kadovar, Ritter Island, Rabaul, Manam, Langila, Ulawun and Bam. In the Philippines there is only one 500 high risk volcano - Didicas. Below, we briefly elaborate on the aspects that contribute to the high score of these volcanoes, speculate on the nature of future tsunamis that can be expected from them, and assess which particular volcanoes should be prioritised for tsunami monitoring and forecasting. Anak Krakatau and Kadovar have been discussed in the previous section. volcanoes include Kadovar, Ritter Island, Rabaul, Manam, Langila, Ulawun and Bam. In the Philippines there is only one 500 high risk volcano - Didicas. Below, we briefly elaborate on the aspects that contribute to the high score of these volcanoes, speculate on the nature of future tsunamis that can be expected from them, and assess which particular volcanoes should be prioritised for tsunami monitoring and forecasting. Anak Krakatau and Kadovar have been discussed in the previous section. 4.3 Tsunami source volcanoes Batu Tara: This lone and small volcanic island is located north of the Lesser Sunda Islands and positioned centrally Batu Tara: This lone and small volcanic island is located north of the Lesser Sunda Islands and positioned centrally Batu Tara: This lone and small volcanic island is located north of the Lesser Sunda Islands and positioned centrally between the Flores- and Banda Sea. The island is exceptionally steep with the eastern flank measuring an incline of about 50 505 degrees. The morphology here is strikingly reminiscent of the Sciara del Fuoco at Stromboli, Italy. Despite its relatively small size, the Island also has an elevation of 753 m, making it 2.5 times higher than Anak Krakatau before its collapse. While no historical tsunamis are known from this volcano, the dissected morphology and apparent amphitheatre remnants suggest that multiple collapses have occurred during Batu Tara's geological history. It is also a recently active Island with the between the Flores- and Banda Sea. The island is exceptionally steep with the eastern flank measuring an incline of about 50 505 degrees. The morphology here is strikingly reminiscent of the Sciara del Fuoco at Stromboli, Italy. Despite its relatively small size, the Island also has an elevation of 753 m, making it 2.5 times higher than Anak Krakatau before its collapse. While no historical tsunamis are known from this volcano, the dissected morphology and apparent amphitheatre remnants suggest that multiple collapses have occurred during Batu Tara's geological history. It is also a recently active Island with the last activity being in 2015, consisting mostly of strombolian and vulcanian eruptions, but also pyroclastic flows and rockfalls 510 were reported to reach the sea (Global Volcanism Program, 2013). All these factors suggest that this volcano is a particularly large tsunami hazard, and the tsunamis could be generated both by catastrophic and smaller sector collapses due to gravitational instability of the oversteepened flanks as well as eruptive activity with large explosions and pyroclastic flows, which have a direct and steep path towards the sea. Travel-time modelling of a potential tsunami at this location is estimated last activity being in 2015, consisting mostly of strombolian and vulcanian eruptions, but also pyroclastic flows and rockfalls 510 were reported to reach the sea (Global Volcanism Program, 2013). https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. 495 4.3 Tsunami source volcanoes 4.3 Tsunami source volcanoes All these factors suggest that this volcano is a particularly large tsunami hazard, and the tsunamis could be generated both by catastrophic and smaller sector collapses due to gravitational instability of the oversteepened flanks as well as eruptive activity with large explosions and pyroclastic flows, which have a direct and steep path towards the sea. Travel-time modelling of a potential tsunami at this location is estimated to affect all lesser Sunda Islands, most of the Banda Sea, the north of Timor as well as the southern parts of Sulawesi and 515 Buru within an hour (Fig. 8). Since this volcano is a lot less known compared to islands like Anak Krakatau, future monitoring efforts and tsunami risk modelling should make Batu Tara a high priority target. to affect all lesser Sunda Islands, most of the Banda Sea, the north of Timor as well as the southern parts of Sulawesi and 515 Buru within an hour (Fig. 8). Since this volcano is a lot less known compared to islands like Anak Krakatau, future monitoring efforts and tsunami risk modelling should make Batu Tara a high priority target. to affect all lesser Sunda Islands, most of the Banda Sea, the north of Timor as well as the southern parts of Sulawesi and 515 Buru within an hour (Fig. 8). Since this volcano is a lot less known compared to islands like Anak Krakatau, future monitoring efforts and tsunami risk modelling should make Batu Tara a high priority target. Iliwerung: The small cone is situated at the southern coast of Lembata Island, where it forms a complex of vents and lava domes, including some submarine ones. The main subaerial cone is located above a steep flank, providing a direct path Iliwerung: The small cone is situated at the southern coast of Lembata Island, where it forms a complex of vents and lava domes, including some submarine ones. The main subaerial cone is located above a steep flank, providing a direct path domes, including some submarine ones. The main subaerial cone is located above a steep flank, providing a direct path towards the sea. The volcano is also known for frequent eruptions with the last one being submarine in 2021 (Global 520 Volcanism Program, 2013), and has three recorded historical tsunamis in 1973, 1979, and 1983 (Table 1), as well as signs of a past sector collapse in its morphology. To compensate for these knowledge gaps, full physics-based source and propagation modelling, especially if they are coupled to collapse events, the largest runups and the most severe impacts are expected to be largest in the near-field of the volcano, but 480 may still be significant in the far-field (Harris et al., 2012; Grilli et al., 2021). Furthermore, the recent Hunga Tonga-Hunga Haʻapai eruption has shown that large eruptions are capable of generating meteotsunamis travelling long distances without significant loss of amplitude. This particular tsunami also travelled faster than initially expected (Somerville et al., 2022). To compensate for these knowledge gaps, full physics-based source and propagation modelling, especially if they are coupled to the population density information along the coasts, may become the most useful tool to improve our understanding of the 485 risk posed by volcanogenic tsunamis. So far, published models almost exclusively consider Anak Krakatau (e.g., Grilli et al., 2019; Heidarzadeh et al., 2020; Mulia et al., 2020; Omira and Ramalho, 2020; Paris et al., 2020), whereas the risk posed by the other high-hazard volcanoes in our catalogue is largely unknown, emphasising the need for future investigations and modelling efforts. the population density information along the coasts, may become the most useful tool to improve our understanding of the 485 risk posed by volcanogenic tsunamis. So far, published models almost exclusively consider Anak Krakatau (e.g., Grilli et al., 2019; Heidarzadeh et al., 2020; Mulia et al., 2020; Omira and Ramalho, 2020; Paris et al., 2020), whereas the risk posed by the other high-hazard volcanoes in our catalogue is largely unknown, emphasising the need for future investigations and modelling efforts. 490 26 26 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. gure 8: Travel-distance plots of tsunamis originating at a high-hazard volcano after 60 minutes in a) Indonesia and pua New Guinea. How much coastline is affected by each volcano is summarised in table 3. Base map data source Figure 8: Travel-distance plots of tsunamis originating at a high-hazard volcano after 60 minutes in a) Indonesia and b) Papua New Guinea. How much coastline is affected by each volcano is summarised in table 3. Base map data source: © OpenStreetMap contributors 2022. Distributed under the Open Data Commons Open Database License (ODbL) v1.0. 27 Since most of the volcano's flanks are not exceptionally steep, 530 the most likely causes for tsunamis are far-reaching pyroclastic flows or eruptions on the lower flanks, however, partial collapses from the steeper summit region should also be considered. While Ternate is the largest populated area affected, it should be noted that a potential tsunami could also affect the other nearby islands as well as the western coast of Halmahera, the eastern coast of North-Sulawesi as well as the Islands Taliabu and Mangole. 530 Sirung: Similar to Iliwerung, Sirung forms a peninsula towards the south of the Lesser Sunda Islands. It is located on Pantar 535 Island and forms a multifaceted complex including a large caldera, a steep stratocone and lava domes. Recent eruptions have been dominantly phreatic, although the morphology suggests that multiple eruptive styles are possible, including potential large caldera-forming eruptions. While these are less likely to occur, the resultant pyroclastic flows would need to travel less than 3 km downhill to reach the sea. As with Iliwerung, a potential tsunami would rapidly affect all Lesser Sunda Islands and the north coast of Timor 540 Sirung: Similar to Iliwerung, Sirung forms a peninsula towards the south of the Lesser Sunda Islands. It is located on Pantar 535 Island and forms a multifaceted complex including a large caldera, a steep stratocone and lava domes. Recent eruptions have been dominantly phreatic, although the morphology suggests that multiple eruptive styles are possible, including potential large caldera-forming eruptions. While these are less likely to occur, the resultant pyroclastic flows would need to travel less than 3 km downhill to reach the sea. As with Iliwerung, a potential tsunami would rapidly affect all Lesser Sunda Islands and the north coast of Timor. 540 Ritter Island: After its catastrophic sector collapse and tsunami in 1888 much of the island's subaerial edifice remains destroyed, leaving only an elongated ridge as a remnant scar. While this may exaggerate the morphological metrics applied to our ranking (the island largely consists of a west-facing scar), the volcano has still produced multiple tsunamis after the large collapse, which occurred in 1972, 1974 and 2007. 4.3 Tsunami source volcanoes Considering all above, Iliwerung is one of the highest ranking volcanoes in our catalogue. All known mechanisms of volcanogenic tsunami generation may be relevant here, especially large submarine or coastal explosions, pyroclastic flows and flank or lava dome collapses. A potential tsunami would likely affect all Lesser Sunda Islands and well as Timor in a short amount of time (Fig. 8). 525 towards the sea. The volcano is also known for frequent eruptions with the last one being submarine in 2021 (Global 520 Volcanism Program, 2013), and has three recorded historical tsunamis in 1973, 1979, and 1983 (Table 1), as well as signs of a past sector collapse in its morphology. Considering all above, Iliwerung is one of the highest ranking volcanoes in our catalogue. All known mechanisms of volcanogenic tsunami generation may be relevant here, especially large submarine or coastal explosions, pyroclastic flows and flank or lava dome collapses. A potential tsunami would likely affect all Lesser Sunda Islands and well as Timor in a short amount of time (Fig. 8). 525 28 This demonstrates the volcano's continued potential to produce tsunamis, both by explosions and sector failures of the subaerial or submarine edifice, but also a scenario similar to the 545 Ritter Island: After its catastrophic sector collapse and tsunami in 1888 much of the island's subaerial edifice remains destroyed, leaving only an elongated ridge as a remnant scar. While this may exaggerate the morphological metrics applied to our ranking (the island largely consists of a west-facing scar), the volcano has still produced multiple tsunamis after the large collapse, which occurred in 1972, 1974 and 2007. This demonstrates the volcano's continued potential to produce tsunamis, both by explosions and sector failures of the subaerial or submarine edifice, but also a scenario similar to the 545 recent Hunga Tonga-Hunga Haʻapai eruption (Somerville et al., 2022) should be considered since both these volcanoes have their main vents located in shallow waters. tsunamis, both by explosions and sector failures of the subaerial or submarine edifice, but also a scenario similar to the 545 recent Hunga Tonga-Hunga Haʻapai eruption (Somerville et al., 2022) should be considered since both these volcanoes have their main vents located in shallow waters. Rabaul: The large 8 by 14 km Rabaul caldera forms a bay south of the Gazelle Peninsula in the northeast of New Britain. Here, it is questionable how well our morphological criteria for the ranking represent the tsunami hazard as the subaerial Rabaul: The large 8 by 14 km Rabaul caldera forms a bay south of the Gazelle Peninsula in the northeast of New Britain. Here, it is questionable how well our morphological criteria for the ranking represent the tsunami hazard as the subaerial edifice is limited to the Tavurvur and Vulcan cones, which are on opposite ends of the submerged caldera. We chose 550 Tavurvur since it was the site of Rabauls most recent eruption in 2014. On the other hand, the volcano's tsunamigenic potential has been demonstrated in 1878, 1937 and 1994, where all tsunamis occurred in conjunction with significant explosive eruptions. Since the caldera is mostly submerged, tsunamis may be generated not only by pyroclastic flows and edifice collapses at the two main cones, but also underwater or coastal explosions. Even otherwise less significant phreatic edifice is limited to the Tavurvur and Vulcan cones, which are on opposite ends of the submerged caldera. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Gamalama: The volcano forms a large, nearly circular island in the north of Indonesia as part of the Maluku Islands at the Molucca Sea. It has the city Ternate on its eastern flank, which has approximately 205,000 inhabitants, making it the largest and most densely populated city in the province and an important economic centre. Since the volcano is very frequently active with its last eruption in 2018, it has both a history of deadly eruptions such as in 1775 and 2011 (Hidayat et al., 2020) Gamalama: The volcano forms a large, nearly circular island in the north of Indonesia as part of the Maluku Islands at the Molucca Sea. It has the city Ternate on its eastern flank, which has approximately 205,000 inhabitants, making it the largest and most densely populated city in the province and an important economic centre. Since the volcano is very frequently active with its last eruption in 2018, it has both a history of deadly eruptions such as in 1775 and 2011 (Hidayat et al., 2020) as well as tsunamis in 1608, 1771, 1772 and 1840 (Table 1). Since most of the volcano's flanks are not exceptionally steep, 530 the most likely causes for tsunamis are far-reaching pyroclastic flows or eruptions on the lower flanks, however, partial collapses from the steeper summit region should also be considered. While Ternate is the largest populated area affected, it should be noted that a potential tsunami could also affect the other nearby islands as well as the western coast of Halmahera, the eastern coast of North-Sulawesi as well as the Islands Taliabu and Mangole. as well as tsunamis in 1608, 1771, 1772 and 1840 (Table 1). Since most of the volcano's flanks are not exceptionally steep, 530 the most likely causes for tsunamis are far-reaching pyroclastic flows or eruptions on the lower flanks, however, partial collapses from the steeper summit region should also be considered. While Ternate is the largest populated area affected, it should be noted that a potential tsunami could also affect the other nearby islands as well as the western coast of Halmahera, the eastern coast of North-Sulawesi as well as the Islands Taliabu and Mangole. as well as tsunamis in 1608, 1771, 1772 and 1840 (Table 1). Currently, Karangetang and Manam have ongoing eruptions at the time of writing and Sangeang Api had its last in 2020. While the lower flanks are mostly forested with gentle slopes, the summit regions are very steep and barren due to the constant activity. Manam and Sangeang Api are also heavily dissected, suggesting multiple partial edifice failures have occurred in their geological history. 570 Despite this, no historical tsunamis are known from any of these volcanoes, but gravitational mass movements like pyroclastic flows from large explosions or lava dome collapses as well as landslides from edifice failures have direct downhill paths into the sea in multiple directions, but would need to travel between 3 and 7 km. This makes a scenario in which a tsunami is generated only likely for larger eruptions. But as Anak Krakatau demonstrated, significant sector failures may also occur without significant eruptions (Williams et al., 2019). 575 Karangetang, Sangeang Api and Manam: These three volcanoes all form larger, near circular volcanic islands (diameters 565 between 8-15 km), with Karangetang connecting to the southern part of Siau Island. They are among the most active volcanoes on this list, having regular and dominantly explosive eruptions of varying intensity. Currently, Karangetang and Manam have ongoing eruptions at the time of writing and Sangeang Api had its last in 2020. While the lower flanks are mostly forested with gentle slopes, the summit regions are very steep and barren due to the constant activity. Manam and Sangeang Api are also heavily dissected, suggesting multiple partial edifice failures have occurred in their geological history. 570 Despite this, no historical tsunamis are known from any of these volcanoes, but gravitational mass movements like pyroclastic flows from large explosions or lava dome collapses as well as landslides from edifice failures have direct downhill paths into the sea in multiple directions, but would need to travel between 3 and 7 km. This makes a scenario in which a tsunami is generated only likely for larger eruptions. But as Anak Krakatau demonstrated, significant sector failures may also occur without significant eruptions (Williams et al., 2019). 575 Sangeang Api are also heavily dissected, suggesting multiple partial edifice failures have occurred in their geological history. We chose 550 Tavurvur since it was the site of Rabauls most recent eruption in 2014. On the other hand, the volcano's tsunamigenic potential has been demonstrated in 1878, 1937 and 1994, where all tsunamis occurred in conjunction with significant explosive eruptions. Since the caldera is mostly submerged, tsunamis may be generated not only by pyroclastic flows and edifice collapses at the two main cones, but also underwater or coastal explosions. Even otherwise less significant phreatic eruptions around the hot springs adjacent to Tavurvur may be considered here. A tsunami would affect the city of Rabaul 555 directly inside the bay, but may also spread to the northern coast of New Britain, the western coast of New Ireland and the Duke of York Island. eruptions around the hot springs adjacent to Tavurvur may be considered here. A tsunami would affect the city of Rabaul 555 directly inside the bay, but may also spread to the northern coast of New Britain, the western coast of New Ireland and the Duke of York Island. eruptions around the hot springs adjacent to Tavurvur may be considered here. A tsunami would affect the city of Rabaul 555 directly inside the bay, but may also spread to the northern coast of New Britain, the western coast of New Ireland and the Duke of York Island. 29 570 Despite this, no historical tsunamis are known from any of these volcanoes, but gravitational mass movements like pyroclastic flows from large explosions or lava dome collapses as well as landslides from edifice failures have direct downhill paths into the sea in multiple directions, but would need to travel between 3 and 7 km. This makes a scenario in which a tsunami is generated only likely for larger eruptions. But as Anak Krakatau demonstrated, significant sector failures may also occur without significant eruptions (Williams et al., 2019). 575 Ruang, Serua, Nila, Wetar and Bam: The volcanoes grouped here are the smaller volcanic Islands (diameters under 5 km). Naturally, these are primed for tsunami generation as their flanks are small and steep, with eruptions occurring close to the sea, however, most of these volcanoes are not as frequently active compared to the larger islands Karangetang, Sangeang Api and Manam. Their last eruption ranges from decades (Ruang, Nila, Wetar, Bam) to a century ago (Serua) and - with the Ruang, Serua, Nila, Wetar and Bam: The volcanoes grouped here are the smaller volcanic Islands (diameters under 5 km). Naturally, these are primed for tsunami generation as their flanks are small and steep, with eruptions occurring close to the sea, however, most of these volcanoes are not as frequently active compared to the larger islands Karangetang, Sangeang Api and Manam. Their last eruption ranges from decades (Ruang, Nila, Wetar, Bam) to a century ago (Serua) and - with the Api and Manam. Their last eruption ranges from decades (Ruang, Nila, Wetar, Bam) to a century ago (Serua) and - with the exception of Ruang in 1871 and 1889 - none of them have associated historical tsunamis. On the other hand, all islands show 580 signs of past edifice collapses, which is confirmed for Bam through submarine debris avalanche deposits (Silver et al., 2009), which underlines their tsunamigenic potential. Ongoing hydrothermal alteration is also visible on the flanks of Wetar, Nila and Serua, potentially weakening their flanks. For the consideration of future tsunami hazards posed by these volcanoes, especially since these smaller islands with little to no habitation are less studied, it is important to have adequate monitoring exception of Ruang in 1871 and 1889 - none of them have associated historical tsunamis. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Didicas: Lava dome extrusion from volcano formed a small island in 1952 in the Luzon Strait in the north of the Philippines. Multiple repeated eruptions are known from this volcano since 1773, which were mostly submarine, although some islands Multiple repeated eruptions are known from this volcano since 1773, which were mostly submarine, although some islands were formed and destroyed prior to the current island. The last eruptive episode ended in 1978, but had produced a tsunami 560 in 1969. Due to the small size of the young island, future activity has the potential to cause tsunamis by full or partial failure of the edifice, underwater explosions and lava dome collapses, should further domes grow. A tsunami from this location is likely to affect the Babuyan and Batanes Islands as well as the northern coast of Luzon. We note that Didicas was not used for the tsunami travel time simulations. were formed and destroyed prior to the current island. The last eruptive episode ended in 1978, but had produced a tsunami 560 in 1969. Due to the small size of the young island, future activity has the potential to cause tsunamis by full or partial failure of the edifice, underwater explosions and lava dome collapses, should further domes grow. A tsunami from this location is likely to affect the Babuyan and Batanes Islands as well as the northern coast of Luzon. We note that Didicas was not used for the tsunami travel time simulations. Karangetang, Sangeang Api and Manam: These three volcanoes all form larger, near circular volcanic islands (diameters 565 between 8-15 km), with Karangetang connecting to the southern part of Siau Island. They are among the most active volcanoes on this list, having regular and dominantly explosive eruptions of varying intensity. Currently, Karangetang and Manam have ongoing eruptions at the time of writing and Sangeang Api had its last in 2020. While the lower flanks are mostly forested with gentle slopes, the summit regions are very steep and barren due to the constant activity. Manam and Karangetang, Sangeang Api and Manam: These three volcanoes all form larger, near circular volcanic islands (diameters 565 between 8-15 km), with Karangetang connecting to the southern part of Siau Island. They are among the most active volcanoes on this list, having regular and dominantly explosive eruptions of varying intensity. The latest eruption at Paluweh occurred between October 2012 and August 2013 in which an effusive- explosive eruption produced PDCs that caused 5 fatalities, however, fortunately the pyroclastic materials did not trigger 600 tsunami (Primulyana et al., 2017). An eruption at Taal is currently ongoing at the time of writing, highlighting the relevance of these volcanoes. Similarly, there are a number of small volcanic islands that did not score as high because they are not as active, meaning their last eruption occurred decades to centuries ago. For Indonesia, these are Teon, Manuk, Wurlali, and Banda Api. Here, the situation is comparable to Kadovar before it erupted in 2018, the islands could become a significant tsunami hazard if new eruptive activity resumes. 605 On the other hand, all islands show 580 signs of past edifice collapses, which is confirmed for Bam through submarine debris avalanche deposits (Silver et al., 2009), which underlines their tsunamigenic potential. Ongoing hydrothermal alteration is also visible on the flanks of Wetar, Nila and Serua, potentially weakening their flanks. For the consideration of future tsunami hazards posed by these volcanoes, especially since these smaller islands with little to no habitation are less studied, it is important to have adequate monitoring in place as renewed eruptive activity would make these volcanoes particularly likely tsunami sources. Partial flank failures 585 similar to Anak Krakatau in 2018, both subaerial and submarine are likely causes, but explosions and pyroclastic flows are also possible. in place as renewed eruptive activity would make these volcanoes particularly likely tsunami sources. Partial flank failures 585 similar to Anak Krakatau in 2018, both subaerial and submarine are likely causes, but explosions and pyroclastic flows are also possible. Langila and Ulawun: The two Papua New Guinean volcanoes Langila and Ulawun are large and steep stratovolcanoes, very similar to large volcanic Islands such as Karangetang, both in terms of morphology and activity (frequent explosive 30 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. eruptions in recent years) as well as no known historical tsunamis. One major difference is that both are located on land and 590 have only parts of their flanks facing the sea, west to northeast for Langila and only northwest for Ulawun. This also makes coastal flank eruptions less likely and the main tsunami hazard stems from far-reaching pyroclastic flows (up to 9.5 km for Ulawun) or major edifice failures (both volcanoes have signs of past collapses). eruptions in recent years) as well as no known historical tsunamis. One major difference is that both are located on land and 590 have only parts of their flanks facing the sea, west to northeast for Langila and only northwest for Ulawun. This also makes coastal flank eruptions less likely and the main tsunami hazard stems from far-reaching pyroclastic flows (up to 9.5 km for Ulawun) or major edifice failures (both volcanoes have signs of past collapses). Other relevant volcanoes: This final paragraph briefly highlights some volcanoes that were not classified into the high Other relevant volcanoes: This final paragraph briefly highlights some volcanoes that we Other relevant volcanoes: This final paragraph briefly highlights some volcanoes that were not classified into the high hazard category, but should nonetheless be considered for tsunami assessments. The Indonesian volcanoes Awu and 595 Paluweh (or Rokatenda) and the Philippine volcano Taal do not have as tall and steep edifices as some other volcanoes on this list and thus received a lower score. However, all have a history of producing tsunamis with hundreds to thousands of fatalities as a result of their eruptions (Table 1). Provided that eruptions resume it is likely that such a scenario can happen again in the future. The latest eruption at Paluweh occurred between October 2012 and August 2013 in which an effusive- hazard category, but should nonetheless be considered for tsunami assessments. The Indonesian volcanoes Awu and 595 Paluweh (or Rokatenda) and the Philippine volcano Taal do not have as tall and steep edifices as some other volcanoes on this list and thus received a lower score. However, all have a history of producing tsunamis with hundreds to thousands of fatalities as a result of their eruptions (Table 1). Provided that eruptions resume it is likely that such a scenario can happen again in the future. 6 Acknowledgements The authors acknowledge the financial support by the Federal Ministry of Education and Research of Germany in the framework of the TSUNAMI_RISK project (project numbers 03G0906A and 03G0906B), which is a part of the funding initiative CLIENT-II. We further acknowledge the past contributions by GITEWS, on which this projects builds upon 620 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. 7 Author contributions EZ conceptualised and wrote the manuscript. Figures were prepared by EZ and AO. EZ also performed the analyses and evaluations of the individual volcanoes. EZ, AO, SP, TW and IR jointly developed the point score system. Tsunami-travel- time modelling was performed by AB and photogrammetric data for Anak Krakatau was provided by HD. All authors contributed to the writing and editing of the manuscript. 8 Competing interests The authors declare no competing interests. 5 Conclusions Based on our MCDA analysis considering 131 volcanoes in SE-Asia we identify 19 that pose a high tsunami hazard and another 48 with moderate tsunami hazard. We find that the Indonesian Lesser Sunda Islands and northern Molucca Sea as well as the southern Bismarck Sea in Papua New Guinea are areas with a high number of hazardous volcanoes and may thus another 48 with moderate tsunami hazard. We find that the Indonesian Lesser Sunda Islands and northern Molucca Sea as well as the southern Bismarck Sea in Papua New Guinea are areas with a high number of hazardous volcanoes and may thus be particularly prone to tsunamis sources by volcanoes. Many of these volcanoes such as Batu Tara, Indonesia, are not 610 commonly considered for this type of hazard. We therefore emphasise the need to reconsider the current state of monitoring and risk assessment in these areas. Since tsunami warning systems are mostly not designed to detect volcanogenic tsunamis, our results highlight the importance of a reassessment of the current network and additional suitable equipment on the ground and through earth observation satellites. Due to the inherently short warning times of these events, we also recommended increased pre-emptive measures on a local level, such as increased public education programs for coastal 615 communities and the marking evacuation routes along populated coasts. be particularly prone to tsunamis sources by volcanoes. Many of these volcanoes such as Batu Tara, Indonesia, are not 610 commonly considered for this type of hazard. We therefore emphasise the need to reconsider the current state of monitoring and risk assessment in these areas. Since tsunami warning systems are mostly not designed to detect volcanogenic tsunamis, our results highlight the importance of a reassessment of the current network and additional suitable equipment on the ground and through earth observation satellites. Due to the inherently short warning times of these events, we also 610 recommended increased pre-emptive measures on a local level, such as increased public education programs for coastal 615 communities and the marking evacuation routes along populated coasts. recommended increased pre-emptive measures on a local level, such as increased public education programs for coastal 615 communities and the marking evacuation routes along populated coasts. 31 9 References Airbus, 2020. Copernicus DEM Validation Report (v2.1), https://spacedata.copernicus.eu/documents/20126/0/GEO1988- CopernicusDEM-SPE-002_ProductHandbook_I1.00.pdf. Airbus, 2020. Copernicus DEM Validation Report (v2.1), https://spacedata.copernicus.eu/documents/20126/0/GEO1988- CopernicusDEM-SPE-002_ProductHandbook_I1.00.pdf. 630 Annunziato, A., Prasetya, G. and Husrin, S., 2019. Anak Krakatau volcano emergency tsunami early warning system. Science of Tsunami Hazards, 38(2). Becker, J.J., Sandwell, D.T., Smith, W.H.F., Braud, J., Binder, B., Depner, J., Fabre, D., Factor, J., Ingalls, S., Kim, S.H., Ladner, R., Marks, K., Nelson, S., Pharaoh, A., Trimmer, R., Von Rosenberg, J., Wallace, G. and Weatherall, P., 2009. Global Bathymetry and Elevation Data at 30 Arc Seconds Resolution: SRTM30_PLUS. Marine Geodesy, 635 32(4): 355-371. DOI: 10.1080/01490410903297766 Belousov, A., Voight, B., Belousova, M. and Muravyev, Y., 2000. Tsunamis Generated by Subaquatic Volcanic Explosions: Unique Data from 1996 Eruption in Karymskoye Lake, Kamchatka, Russia. pure and applied geophysics, 157(6): 1135-1143. DOI: 10.1007/s000240050021 , p p ( ), p p p CopernicusDEM-SPE-002_ProductHandbook_I1.00.pdf. 630 Annunziato, A., Prasetya, G. and Husrin, S., 2019. Anak Krakatau volcano emergency tsunami early warning system. Science of Tsunami Hazards, 38(2). Becker, J.J., Sandwell, D.T., Smith, W.H.F., Braud, J., Binder, B., Depner, J., Fabre, D., Factor, J., Ingalls, S., Kim, S.H., Ladner, R., Marks, K., Nelson, S., Pharaoh, A., Trimmer, R., Von Rosenberg, J., Wallace, G. and Weatherall, P., 2009. Global Bathymetry and Elevation Data at 30 Arc Seconds Resolution: SRTM30_PLUS. Marine Geodesy, 635 32(4): 355-371. DOI: 10.1080/01490410903297766 Belousov, A., Voight, B., Belousova, M. and Muravyev, Y., 2000. Tsunamis Generated by Subaquatic Volcanic Explosions: Unique Data from 1996 Eruption in Karymskoye Lake, Kamchatka, Russia. pure and applied geophysics, 157(6): 1135-1143. DOI: 10.1007/s000240050021 Annunziato, A., Prasetya, G. and Husrin, S., 2019. Anak Krakatau volcano emergency tsunami early warning system. Science of Tsunami Hazards, 38(2). Annunziato, A., Prasetya, G. and Husrin, S., 2019. Anak Krakatau volcano emergency tsunami early warning system. Science of Tsunami Hazards, 38(2). 2009. Global Bathymetry and Elevation Data at 30 Arc Seconds Resolution: SRTM30_PLUS. Marine Geodesy, 32(4): 355-371. DOI: 10.1080/01490410903297766 Belousov, A., Voight, B., Belousova, M. and Muravyev, Y., 2000. Tsunamis Generated by Subaquatic Volcanic Explosions: Unique Data from 1996 Eruption in Karymskoye Lake, Kamchatka, Russia. pure and applied geophysics, 157(6): 1135-1143. DOI: 10.1007/s000240050021 Brown, S.K., Jenkins, S.F., Sparks, R.S.J., Odbert, H. and Auker, M.R., 2017. Volcanic fatalities database: analysis of 640 volcanic threat with distance and victim classification. Journal of Applied Volcanology, 6(1): 15. DOI: 10.1186/s13617-017-0067-4 32 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Carey, S., Sigurdsson, H., Mandeville, C. and Bronto, S., 2000. Volcanic hazards from pyroclastic flow discharge into the sea: Examples from the 1883 eruption of Krakatau, Indonesia. In: F.W. McCoy and G. Heiken (Editors), Volcanic Hazards and Disasters in Human Antiquity. Geological Society of America, pp. 0. DOI: 10.1130/0-8137-2345-0.1 Crisci, G.M., De Rosa, R., Esperança, S., Mazzuoli, R. and Sonnino, M., 1991. Temporal evolution of a three component system: the island of Lipari (Aeolian Arc, southern Italy). Bulletin of Volcanology, 53(3): 207-221. DOI: 10.1007/BF00301231 645 Cronin, S.J., Lube, G., Dayudi, D.S., Sumarti, S., Subrandiyo, S. and Surono, 2013. Insights into the October–November 2010 Gunung Merapi eruption (Central Java, Indonesia) from the stratigraphy, volume and characteristics of its 0 pyroclastic deposits. Journal of Volcanology and Geothermal Research, 261: 244-259. DOI: 10.1016/j.jvolgeores.2013.01.005 650 Darmawan, H., Mutaqin, B.W., Harijoko, A., Wibowo, H.E., Haerani, N., Surmayadi, M., Jati, R. and Asriningrum, W., 2020. Topography and structural changes of Anak Krakatau due to the December 2018 catastrophic events. The Indonesian Journal of Geography, 52(3): 402-410. DOI: 10.22146/ijg.53740 655 Darmawan, H., Troll, V.R., Walter, T.R., Deegan, F.M., Geiger, H., Heap, M.J., Seraphine, N., Harris, C., Humaida, H. and Müller, D., 2022. Hidden mechanical weaknesses within lava domes provided by buried high-porosity hydrothermal alteration zones. Scientific Reports, 12(1): 3202. DOI: 10.1038/s41598-022-06765-9 Di Traglia, F., Nolesini, T., Solari, L., Ciampalini, A., Frodella, W., Steri, D., Allotta, B., Rindi, A., Marini, L., Monni, N., Galardi, E. and Casagli, N., 2018. Lava delta deformation as a proxy for submarine slope instability. Earth and Planetary Science Letters, 488: 46-58. DOI: 10.1016/j.epsl.2018.01.038 660 ESA, 2022. Copernicus Sentinel-2 data. Retrieved from Sentinel Playground accessed on 21st September 2021, https://apps.sentinel-hub.com/sentinel-playground. https://apps.sentinel hub.com/sentinel playground. Euillades, L.D., Grosse, P. and Euillades, P.A., 2013. NETVOLC: An algorithm for automatic delimitation of volcano edifice boundaries using DEMs. Computers & Geosciences, 56: 151-160. DOI: 10.1016/j.cageo.2013.03.011 665 Fernández, D.S. and Lutz, M.A., 2010. Urban flood hazard zoning in Tucumán Province, Argentina, using GIS and multicriteria decision analysis. Engineering Geology, 111(1): 90-98. DOI: 10.1016/j.enggeo.2009.12.006 Fisher, R.V., 1990. Transport and deposition of a pyroclastic surge across an area of high relief: The 18 May 1980 eruption of Mount St. Helens, Washington. GSA Bulletin, 102(8): 1038-1054. DOI: 10.1130/0016- 7606(1990)102<1038:TADOAP>2.3.CO;2 670 Francis, P.W., 1985. The origin of the 1883 Krakatau tsunamis. Journal of Volcanology and Geothermal Research, 25(3): 349-363. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Global Volcanism Program, 2013. Volcanoes of the World, v. 4.10.6 (24 Mar 2020). Venzke, E. Smithsonian Institution. DOI: 10.5479/si.GVP.VOTW4-2013 DOI: 10.5479/si.GVP.VOTW4-2013 Gonzalez-Ollauri, A. and Mickovski, S.B., 2017. Hydrological effect of vegetation against rainfall-induced landslides. Journal of Hydrology, 549: 374-387. DOI: 10.1016/j.jhydrol.2017.04.014 Gonzalez-Ollauri, A. and Mickovski, S.B., 2017. Hydrological effect of vegetation against rainfall-induced landslides. Journal of Hydrology, 549: 374-387. DOI: 10.1016/j.jhydrol.2017.04.014 680 Grilli, S.T., Tappin, D.R., Carey, S., Watt, S.F.L., Ward, S.N., Grilli, A.R., Engwell, S.L., Zhang, C., Kirby, J.T., 680 Schambach, L. and Muin, M., 2019. Modelling of the tsunami from the December 22, 2018 lateral collapse of Anak Krakatau volcano in the Sunda Straits, Indonesia. Scientific Reports, 9(1): 11946. DOI: 10.1038/s41598-019- 48327-6 Grilli, S.T., Zhang, C., Kirby, J.T., Grilli, A.R., Tappin, D.R., Watt, S.F.L., Hunt, J.E., Novellin Grilli, S.T., Zhang, C., Kirby, J.T., Grilli, A.R., Tappin, D.R., Watt, S.F.L., Hunt, J.E., Novellino, A., Engwell, S., Nurshal, Grilli, S.T., Zhang, C., Kirby, J.T., Grilli, A.R., Tappin, D.R., Watt, S.F.L., Hunt, J.E., Novellino, A., Engwell, S., Nurshal, M.E.M., Abdurrachman, M., Cassidy, M., Madden-Nadeau, A.L. and Day, S., 2021. Modeling of the Dec. 22nd 685 2018 Anak Krakatau volcano lateral collapse and tsunami based on recent field surveys: Comparison with observed tsunami impact. Marine Geology, 440: 106566. DOI: 10.1016/j.margeo.2021.106566 M.E.M., Abdurrachman, M., Cassidy, M., Madden-Nadeau, A.L. and Day, S., 2021. Modeling of the Dec. 22nd 685 2018 Anak Krakatau volcano lateral collapse and tsunami based on recent field surveys: Comparison with observed tsunami impact. Marine Geology, 440: 106566. DOI: 10.1016/j.margeo.2021.106566 Grosse, P., van Wyk de Vries, B., Petrinovic, I.A., Euillades, P.A. and Alvarado, G.E., 2009. Morphometry and evolution of arc volcanoes Geology 37(7): 651-654 DOI: 10 1130/G25734A 1 Grosse, P., van Wyk de Vries, B., Petrinovic, I.A., Euillades, P.A. and Alvarado, G.E., 2009. Morphometry and evolution of arc volcanoes. Geology, 37(7): 651-654. DOI: 10.1130/G25734A.1 Grosse, P., van Wyk de Vries, B., Euillades, P.A., Kervyn, M. and Petrinovic, I.A., 2012. Systematic morphometric 690 characterization of volcanic edifices using digital elevation models. Geomorphology, 136(1): 114-131. DOI: 10.1016/j.geomorph.2011.06.001 Grosse, P., van Wyk de Vries, B., Euillades, P.A., Kervyn, M. and Petrinovic, I.A., 2012. Systematic morphometric 690 characterization of volcanic edifices using digital elevation models. Geomorphology, 136(1): 114-131. DOI: 10.1016/j.geomorph.2011.06.001 Guth, P.L. and Geoffroy, T.M., 2021. LiDAR point cloud and ICESat-2 evaluation of 1 second global digital elevation models: Copernicus wins. DOI: 10.1016/0377-0273(85)90021-6 Gertisser, R. and Keller, J., 2003. Temporal variations in magma composition at Merapi Volcano (Central Java, Indonesia): magmatic cycles during the past 2000 years of explosive activity. Journal of Volcanology and Geothermal Research, 123(1): 1-23. DOI: 10.1016/S0377-0273(03)00025-8 675 Euillades, L.D., Grosse, P. and Euillades, P.A., 2013. NETVOLC: An algorithm for automatic delimitation of volcano edifice boundaries using DEMs. Computers & Geosciences, 56: 151-160. DOI: 10.1016/j.cageo.2013.03.011 5 Fernández, D.S. and Lutz, M.A., 2010. Urban flood hazard zoning in Tucumán Province, Argentina, using GIS and multicriteria decision analysis. Engineering Geology, 111(1): 90-98. DOI: 10.1016/j.enggeo.2009.12.006 Fisher, R.V., 1990. Transport and deposition of a pyroclastic surge across an area of high relief: The 18 May 1980 eruption of Mount St. Helens, Washington. GSA Bulletin, 102(8): 1038-1054. DOI: 10.1130/0016- 7606(1990)102<1038:TADOAP>2.3.CO;2 0 Francis, P.W., 1985. The origin of the 1883 Krakatau tsunamis. Journal of Volcanology and Geothermal Research, 25(3): 665 rancis, P.W., 1985. The origin of the 1883 Krakatau tsunamis. Journal of Volcanology and Geothermal Research, 25(3): 349-363. DOI: 10.1016/0377-0273(85)90021-6 Gertisser, R. and Keller, J., 2003. Temporal variations in magma composition at Merapi Volcano (Central Java, Indonesia): magmatic cycles during the past 2000 years of explosive activity. Journal of Volcanology and Geothermal Research, 123(1): 1-23. DOI: 10.1016/S0377-0273(03)00025-8 675 33 Transactions in GIS, 25(5): 2245-2261. DOI: 10.1111/tgis.12825 Guth, P.L. and Geoffroy, T.M., 2021. LiDAR point cloud and ICESat-2 evaluation of 1 second global digital elevation models: Copernicus wins. Transactions in GIS, 25(5): 2245-2261. DOI: 10.1111/tgis.12825 Hamzah, L., Puspito, N.T. and Imamura, F., 2000. Tsunami Catalog and Zones in Indonesia. Journal of Natural Disaster 695 Science, 22(1): 25-43. DOI: 10.2328/jnds.22.25 Hamzah, L., Puspito, N.T. and Imamura, F., 2000. Tsunami Catalog and Zones in Indonesia. Journal of Natural Disaster 695 Science, 22(1): 25-43. DOI: 10.2328/jnds.22.25 Hanka, W., Saul, J., Weber, B., Becker, J., Harjadi, P., Fauzi and Group, G.S., 2010. Real-time earthquake monitoring for tsunami warning in the Indian Ocean and beyond. Nat. Hazards Earth Syst. Sci., 10(12): 2611-2622. DOI: 10.5194/nhess-10-2611-2010 Harig, S., Immerz, A., Weniza, Griffin, J., Weber, B., Babeyko, A., Rakowsky, N., Hartanto, D., Nurokhim, A., Handayani, 700 T. and Weber, R., 2020. The Tsunami Scenario Database of the Indonesia Tsunami Early Warning System (InaTEWS): Evolution of the Coverage and the Involved Modeling Approaches. Pure and Applied Geophysics, 177(3): 1379-1401. DOI: 10.1007/s00024-019-02305-1 Harris, J.C., Grilli, S.T., Abadie, S. and Bakhsh, T.T., 2012. Near- And Far-field Tsunami Hazard From the Potential Flank Collapse of the Cumbre Vieja Volcano, The Twenty-second International Offshore and Polar Engineering 705 Conference, pp. ISOPE-I-12-515. Heap, M.J., Mollo, S., Vinciguerra, S., Lavallée, Y., Hess, K.U., Dingwell, D.B., Baud, P. and Iezzi, G., 2013. Thermal weakening of the carbonate basement under Mt. Etna volcano (Italy): Implications for volcano instability. Journal of Volcanology and Geothermal Research, 250: 42-60. DOI: 10.1016/j.jvolgeores.2012.10.004 Harig, S., Immerz, A., Weniza, Griffin, J., Weber, B., Babeyko, A., Rakowsky, N., Hartanto, D., Nurokhim, A., Handayani, 700 T. and Weber, R., 2020. The Tsunami Scenario Database of the Indonesia Tsunami Early Warning System (InaTEWS): Evolution of the Coverage and the Involved Modeling Approaches. Pure and Applied Geophysics, 177(3): 1379-1401. DOI: 10.1007/s00024-019-02305-1 T. and Weber, R., 2020. The Tsunami Scenario Database of the Indonesia Tsunami Early Warning System (InaTEWS): Evolution of the Coverage and the Involved Modeling Approaches. Pure and Applied Geophysics, 177(3): 1379-1401. DOI: 10.1007/s00024-019-02305-1 Harris, J.C., Grilli, S.T., Abadie, S. and Bakhsh, T.T., 2012. Near- And Far-field Tsunami Hazard From the Potential Flank Collapse of the Cumbre Vieja Volcano, The Twenty-second International Offshore and Polar Engineering 705 Conference, pp. ISOPE-I-12-515. Heap, M.J., Mollo, S., Vinciguerra, S., Lavallée, Y., Hess, K.U., Dingwell, D.B., Baud, P. and Iezzi, G., 2013. Thermal weakening of the carbonate basement under Mt. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Heap, M.J., Baumann, T.S., Rosas-Carbajal, M., Komorowski, J.C., Gilg, H.A., Villeneuve, M., Moretti, R., Baud, P., 710 Carbillet, L., Harnett, C. and Reuschlé, T., 2021. Alteration-Induced Volcano Instability at La Soufrière de Guadeloupe (Eastern Caribbean). Journal of Geophysical Research: Solid Earth, 126(8): e2021JB022514. DOI: 10.1029/2021JB022514 Heap, M.J., Baumann, T.S., Rosas Carbajal, M., Komorowski, J.C., Gilg, H.A., Villeneuve, M., Moretti, R., Baud, P., 710 Carbillet, L., Harnett, C. and Reuschlé, T., 2021. Alteration-Induced Volcano Instability at La Soufrière de Guadeloupe (Eastern Caribbean). Journal of Geophysical Research: Solid Earth, 126(8): e2021JB022514. DOI: 10.1029/2021JB022514 Heap, M.J. and Violay, M.E.S., 2021. The mechanical behaviour and failure modes of volcanic rocks: a review. Bulletin of Volcanology, 83(5): 33. DOI: 10.1007/s00445-021-01447-2 715 Heidarzadeh, M., Ishibe, T., Sandanbata, O., Muhari, A. and Wijanarto, A.B., 2020. Numerical modeling of the subaerial landslide source of the 22 December 2018 Anak Krakatoa volcanic tsunami, Indonesia. Ocean Engineering, 195: 106733. DOI: 10.1016/j.oceaneng.2019.106733 Hidayat, A., Marfai, M.A. and Hadmoko, D.S., 2020. Eruption on Indonesia’s volcanic islands: a review of potential hazards, fatalities, and management. IOP Conference Series: Earth and Environmental Science, 485(1): 012061. 720 DOI: 10.1088/1755-1315/485/1/012061 Kieffer, S.W., 1981. Blast dynamics at Mount St Helens on 18 May 1980. Nature, 291(5816): 568-570. DOI: 10.1038/291568a0 K O S id J d M h C H 2019 I d l d lid ti it f t d hill l f ll i t t Carbillet, L., Harnett, C. and Reuschlé, T., 2021. Alteration-Induced Volcano Instability at La Soufrière de Guadeloupe (Eastern Caribbean). Journal of Geophysical Research: Solid Earth, 126(8): e2021JB022514. DOI: 10.1029/2021JB022514 Heap, M.J. and Violay, M.E.S., 2021. The mechanical behaviour and failure modes of volcanic rocks: a review. Bulletin of Volcanology, 83(5): 33. DOI: 10.1007/s00445-021-01447-2 715 Heidarzadeh, M., Ishibe, T., Sandanbata, O., Muhari, A. and Wijanarto, A.B., 2020. Numerical modeling of the subaerial landslide source of the 22 December 2018 Anak Krakatoa volcanic tsunami, Indonesia. Ocean Engineering, 195: Heap, M.J. and Violay, M.E.S., 2021. The mechanical behaviour and failure modes of volcanic rocks: a review. Bulletin of Volcanology, 83(5): 33. DOI: 10.1007/s00445-021-01447-2 715 Heidarzadeh, M., Ishibe, T., Sandanbata, O., Muhari, A. and Wijanarto, A.B., 2020. Numerical modeling of the subaerial landslide source of the 22 December 2018 Anak Krakatoa volcanic tsunami, Indonesia. Ocean Engineering, 195: 106733. Etna volcano (Italy): Implications for volcano instability. Journal Harris, J.C., Grilli, S.T., Abadie, S. and Bakhsh, T.T., 2012. Near- And Far-field Tsunami Hazard From the Potential Flank Collapse of the Cumbre Vieja Volcano, The Twenty-second International Offshore and Polar Engineering 705 Conference, pp. ISOPE-I-12-515. 705 Heap, M.J., Mollo, S., Vinciguerra, S., Lavallée, Y., Hess, K.U., Dingwell, D.B., Baud, P. and Iezzi, G., 2013. Thermal weakening of the carbonate basement under Mt. Etna volcano (Italy): Implications for volcano instability. Journal of Volcanology and Geothermal Research, 250: 42-60. DOI: 10.1016/j.jvolgeores.2012.10.004 34 DOI: 10.1016/j.oceaneng.2019.106733 Hidayat, A., Marfai, M.A. and Hadmoko, D.S., 2020. Eruption on Indonesia’s volcanic islands: a review of potential hazards, fatalities, and management. IOP Conference Series: Earth and Environmental Science, 485(1): 012061. 0 DOI: 10.1088/1755-1315/485/1/012061 720 Kieffer, S.W., 1981. Blast dynamics at Mount St Helens on 18 May 1980. Nature, 291(5816): 568-570. DOI: 10.1038/291568a0 Korup, O., Seidemann, J. and Mohr, C.H., 2019. Increased landslide activity on forested hillslopes following two recent volcanic eruptions in Chile. Nature Geoscience, 12(4): 284-289. DOI: 10.1038/s41561-019-0315-9 25 volcanic eruptions in Chile. Nature Geoscience, 12(4): 284-289. DOI: 10.1038/s41561-019-0315-9 725 Lauterjung, J., Münch, U. and Rudloff, A., 2010. The challenge of installing a tsunami early warning system in the vicinity of the Sunda Arc, Indonesia. Nat. Hazards Earth Syst. Sci., 10(4): 641-646. DOI: 10.5194/nhess-10-641-2010 Lipman, P.W. and Mullineaux, D.R., 1981. The 1980 eruptions of Mount St. Helens, Washington. 1250. DOI: 10.3133/pp1250 Llanes, P., Silver, E., Day, S. and Hoffman, G., 2009. Interactions between a transform fault and arc volcanism in the 730 Bismarck Sea, Papua New Guinea. Geochemistry, Geophysics, Geosystems, 10(6). DOI: 10.1029/2009GC002430 Maeno, F., Imamura, F. and Taniguchi, H., 2006. Numerical simulation of tsunamis generated by caldera collapse during the 7.3 ka Kikai eruption, Kyushu, Japan. Earth, Planets and Space, 58(8): 1013-1024. DOI: 10.1186/BF03352606 Marchuk, A.G., 2008. Minimizing computational errors of tsunami wave-ray and travel time. Science of Tsunami Hazards, 27(4): 12-24. 735 McGuire, W.J., 2006. Lateral collapse and tsunamigenic potential of marine volcanoes. Geological Society, London, Special Publications, 269(1): 121. DOI: 10.1144/GSL.SP.2006.269.01.08 Morton, A., Airoldi, M. and Phillips, L.D., 2009. Nuclear Risk Management on Stage: A Decision Analysis Perspective on the UK's Committee on Radioactive Waste Management. Risk Analysis, 29(5): 764-779. DOI: 10.1111/j.1539- 6924.2008.01192.x 740 Mulia, I.E., Watada, S., Ho, T.C., Satake, K., Wang, Y. and Aditiya, A., 2020. Simulation of the 2018 Tsunami Due to the Flank Failure of Anak Krakatau Volcano and Implication for Future Observing Systems. Geophysical Research Letters, 47(14): e2020GL087334. DOI: 10.1029/2020GL087334 McGuire, W.J., 2006. Lateral collapse and tsunamigenic potential of marine volcanoes. Geological Society, London, Special Publications, 269(1): 121. DOI: 10.1144/GSL.SP.2006.269.01.08 McGuire, W.J., 2006. Lateral collapse and tsunamigenic potential of marine volcanoes. Geological Society, London, Special Publications, 269(1): 121. DOI: 10.1144/GSL.SP.2006.269.01.08 Morton, A., Airoldi, M. and Phillips, L.D., 2009. Nuclear Risk Management on Stage: A Decision Analysis Perspective on the UK's Committee on Radioactive Waste Management. Risk Analysis, 29(5): 764-779. DOI: 10.1111/j.1539- 6924.2008.01192.x 740 Mulia, I.E., Watada, S., Ho, T.C., Satake, K., Wang, Y. and Aditiya, A., 2020. Simulation of the 2018 Tsunami Due to the Flank Failure of Anak Krakatau Volcano and Implication for Future Observing Systems Geophysical Research Morton, A., Airoldi, M. and Phillips, L.D., 2009. Nuclear Risk Management on Stage: A Decision Analysis Perspective on the UK's Committee on Radioactive Waste Management. Risk Analysis, 29(5): 764-779. DOI: 10.1111/j.1539- 6924.2008.01192.x 740 Mulia, I.E., Watada, S., Ho, T.C., Satake, K., Wang, Y. and Aditiya, A., 2020. Simulation of the 2018 Tsunami Due to the Flank Failure of Anak Krakatau Volcano and Implication for Future Observing Systems. Geophysical Research Letters, 47(14): e2020GL087334. DOI: 10.1029/2020GL087334 Mulia, I.E., Watada, S., Ho, T.C., Satake, K., Wang, Y. and Aditiya, A., 2020. Simulation of the 2018 Tsunami Due to the Flank Failure of Anak Krakatau Volcano and Implication for Future Observing Systems. Geophysical Research Letters, 47(14): e2020GL087334. DOI: 10.1029/2020GL087334 35 Generation mechanism of tsunamis from the 1883 Krakatau Eruption. Geophysical Research Letters, 22(4): 509-512. DOI: 10.1029/94GL03219 Nutt, D.J., King, L.A. and Phillips, L.D., 2010. Drug harms in the UK: a multicriteria decision analysis. The Lancet, 376(9752): 1558-1565. DOI: 10.1016/S0140-6736(10)61462-6 Omira, R. and Ramalho, I., 2020. Evidence-Calibrated Numerical Model of December 22, 2018, Anak Krakatau Flank 755 Collapse and Tsunami. Pure and Applied Geophysics, 177(7): 3059-3071. DOI: 10.1007/s00024-020-02532-x OpenStreetMap, 2022. OSM Land polygons, https://www.openstreetmap.org/. Omira, R. and Ramalho, I., 2020. Evidence-Calibrated Numerical Model of December 22, 2018, Anak Krakatau Flank 755 Collapse and Tsunami. Pure and Applied Geophysics, 177(7): 3059-3071. DOI: 10.1007/s00024-020-02532-x OpenStreetMap, 2022. OSM Land polygons, https://www.openstreetmap.org/. Paris, A., Heinrich, P., Paris, R. and Abadie, S., 2020. The December 22, 2018 Anak Krakatau, Indonesia, Landslide and Tsunami: Preliminary Modeling Results. Pure and Applied Geophysics, 177(2): 571-590. DOI: 10.1007/s00024- 019-02394-y 760 Paris, R., Switzer, A.D., Belousova, M., Belousov, A., Ontowirjo, B., Whelley, P.L. and Ulvrova, M., 2014. Volcanic tsunami: a review of source mechanisms, past events and hazards in Southeast Asia (Indonesia, Philippines, Papua New Guinea). Natural Hazards, 70(1): 447-470. DOI: 10.1007/s11069-013-0822-8 Paris, R., 2015. Source mechanisms of volcanic tsunamis. Philosophical Transactions of the Royal Society A: Mathematical, Ph i l d E i i S i 373(2053) 20140380 DOI 10 1098/ t 2014 0380 765 Omira, R. and Ramalho, I., 2020. Evidence-Calibrated Numerical Model of December 22, 2018, Anak Krakatau Flank 755 Collapse and Tsunami. Pure and Applied Geophysics, 177(7): 3059-3071. DOI: 10.1007/s00024-020-02532-x OpenStreetMap, 2022. OSM Land polygons, https://www.openstreetmap.org/. Paris, A., Heinrich, P., Paris, R. and Abadie, S., 2020. The December 22, 2018 Anak Krakatau, Indonesia, Landslide and Tsunami: Preliminary Modeling Results. Pure and Applied Geophysics, 177(2): 571-590. DOI: 10.1007/s00024- 019-02394-y 760 Paris R Switzer A D Belousova M Belousov A Ontowirjo B Whelley P L and Ulvrova M 2014 Volcanic Paris, R., Switzer, A.D., Belousova, M., Belousov, A., Ontowirjo, B., Whelley, P.L. and Ulvrova, M., 2014. Volcanic tsunami: a review of source mechanisms, past events and hazards in Southeast Asia (Indonesia, Philippines, Papua New Guinea). Natural Hazards, 70(1): 447-470. DOI: 10.1007/s11069-013-0822-8 Paris, R., 2015. Source mechanisms of volcanic tsunamis. Philosophical Transactions of the Roy Paris, R., 2015. Source mechanisms of volcanic tsunamis. Philosophical Transactions of the Royal Society A: Mathematical, Paris, R., 2015. Source mechanisms of volcanic tsunamis. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 373(2053): 20140380. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Murray, J.B. and Voight, B., 1996. Slope stability and eruption prediction on the eastern flank of Mount Etna. Geological Society, London, Special Publications, 110(1): 111. DOI: 10.1144/GSL.SP.1996.110.01.08 Mutaqin, B.W., Lavigne, F., Hadmoko, D.S. and Ngalawani, M.N., 2019. Volcanic Eruption-Induced Tsunami in Indonesia: A Review. IOP Conference Series: Earth and Environmental Science, 256: 012023. DOI: 10.1088/1755- 1315/256/1/012023 NGDC, 2021. National Geophysical Data Center / World Data Service: NCEI/WDS Global Historical Tsunami Database, Murray, J.B. and Voight, B., 1996. Slope stability and eruption prediction on the eastern flank of Mount Etna. Geological Society, London, Special Publications, 110(1): 111. DOI: 10.1144/GSL.SP.1996.110.01.08 Murray, J.B. and Voight, B., 1996. Slope stability and eruption prediction on the eastern flank of Mount Etna. Geological Society, London, Special Publications, 110(1): 111. DOI: 10.1144/GSL.SP.1996.110.01.08 Murray, J.B. and Voight, B., 1996. Slope stability and eruption prediction on the eastern flank of Mount Etna. Geological Society, London, Special Publications, 110(1): 111. DOI: 10.1144/GSL.SP.1996.110.01.08 45 Mutaqin, B.W., Lavigne, F., Hadmoko, D.S. and Ngalawani, M.N., 2019. Volcanic Eruption-Induced Tsunami in Indonesia: A Review. IOP Conference Series: Earth and Environmental Science, 256: 012023. DOI: 10.1088/1755- 1315/256/1/012023 745 Mutaqin, B.W., Lavigne, F., Hadmoko, D.S. and Ngalawani, M.N., 2019. Volcanic Eruption-Induced Tsunami in Indonesia: A Review. IOP Conference Series: Earth and Environmental Science, 256: 012023. DOI: 10.1088/1755- 1315/256/1/012023 NGDC, 2021. National Geophysical Data Center / World Data Service: NCEI/WDS Global NGDC, 2021. National Geophysical Data Center / World Data Service: NCEI/WDS Global Historical Tsunami Database, NGDC, 2021. National Geophysical Data Center / World Data Service: NCEI/WDS Global Historical Tsunami Database, NOAA National Centers for Environmental Information. DOI: 10.7289/V5PN93H7 0 NOAA National Centers for Environmental Information. DOI: 10.7289/V5PN93H7 750 Nomanbhoy, N. and Satake, K., 1995. Generation mechanism of tsunamis from the 1883 Krakatau Eruption. Geophysical Research Letters, 22(4): 509-512. DOI: 10.1029/94GL03219 Nutt, D.J., King, L.A. and Phillips, L.D., 2010. Drug harms in the UK: a multicriteria decision analysis. The Lancet, 376(9752): 1558-1565. DOI: 10.1016/S0140-6736(10)61462-6 NOAA National Centers for Environmental Information. DOI: 10.7289/V5PN93H7 750 Nomanbhoy, N. and Satake, K., 1995. Generation mechanism of tsunamis from the 1883 Krakatau Eruption. Geophysical Research Letters, 22(4): 509-512. DOI: 10.1029/94GL03219 N tt D J Ki L A d Philli L D 2010 D h i th UK lti it i d i i l i Th L t Nomanbhoy, N. and Satake, K., 1995. Flood hazard zoning in Yasooj region, Iran, using GIS and multi-criteria decision analysis. Geomatics, Natural Hazards and Risk, 7(3): 1000-1017. DOI: 10.1080/19475705.2015.1045043 Rahmati, O., Zeinivand, H. and Besharat, M., 2016. Flood hazard zoning in Yasooj region, Iran, using GIS and multi-criteria decision analysis. Geomatics, Natural Hazards and Risk, 7(3): 1000-1017. DOI: 10.1080/19475705.2015.1045043 Romero, J.E., Polacci, M., Watt, S., Kitamura, S., Tormey, D., Sielfeld, G., Arzilli, F., La Spina, G., Franco, L., Burton, M. and Polanco, E., 2021. Volcanic Lateral Collapse Processes in Mafic Arc Edifices: A Review of Their Driving Processes, Types and Consequences. Frontiers in Earth Science, 9. DOI: 10.3389/feart.2021.639825 780 Siebert, L., 1984. Large volcanic debris avalanches: Characteristics of source areas, deposits, and associated eruptions. Journal of Volcanology and Geothermal Research, 22(3): 163-197. DOI: 10.1016/0377-0273(84)90002-7 Siebert, L., 1984. Large volcanic debris avalanches: Characteristics of source areas, deposits, and associated eruptions. Journal of Volcanology and Geothermal Research, 22(3): 163-197. DOI: 10.1016/0377-0273(84)90002-7 Silver, E., Day, S., Ward, S., Hoffmann, G., Llanes, P., Driscoll, N., Appelgate, B. and Saunders, S., 2009. Volcano collapse and tsunami generation in the Bismarck Volcanic Arc, Papua New Guinea. Journal of Volcanology and Geothermal 5 Research, 186(3): 210-222. DOI: 10.1016/j.jvolgeores.2009.06.013 Smith, M.S. and Shepherd, J.B., 1993. Preliminary investigations of the tsunami hazard of Kick'em Jenny submarine volcano. Natural Hazards, 7(3): 257-277. DOI: 10.1007/BF00662650 Somerville, P., Blong, R. and Gissing, A., 2022. Hunga Tonga-Hunga Ha'apai Eruption 15th of January 2022, Risk Frontiers Briefing Note 460. 90 Toosi, A.S., Calbimonte, G.H., Nouri, H. and Alaghmand, S., 2019. River basin-scale flood hazard assessment using a modified multi-criteria decision analysis approach: A case study. Journal of Hydrology, 574: 660-671. DOI: 10.1016/j.jhydrol.2019.04.072 Turner, M.B., 2008. Eruption cycles and magmatic processes at a reawakening volcano, Mt. Taranaki, New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Earth Science at 795 Massey University, Palmerston North, New Zealand. Doctoral Thesis, Massey University. van Wyk De Vries, B. and Borgia, A., 1996. The role of basement in volcano deformation. Geological Society, London, Special Publications, 110(1): 95. DOI: 10.1144/GSL.SP.1996.110.01.07 Walter, T.R., Haghshenas Haghighi, M., Schneider, F.M., Coppola, D., Motagh, M., Saul, J., Babeyko, A., Dahm, T., Troll, Walter, T.R., Haghshenas Haghighi, M., Schneider, F.M., Coppola, D., Motagh, M., Saul, J., Ba 800 V.R., Tilmann, F., Heimann, S., Valade, S., Triyono, R., Khomarudin, R., Kartadinata, N., Laiolo, M., Massimetti, 800 F. and Gaebler, P., 2019. DOI: 10.1098/rsta.2014.0380 765 Physical and Engineering Sciences, 373(2053): 20140380. DOI: 10.1098/rsta.2014.0380 765 Plank, S., Walter, T.R., Martinis, S. and Cesca, S., 2019. Growth and collapse of a littoral lava dome during the 2018/19 eruption of Kadovar Volcano, Papua New Guinea, analyzed by multi-sensor satellite imagery. Journal of Volcanology and Geothermal Research, 388: 106704. DOI: 10.1016/j.jvolgeores.2019.106704 Poland, M.P. and Orr, T.R., 2014. Identifying hazards associated with lava deltas. Bulletin of Volcanology, 76(12): 880. Plank, S., Walter, T.R., Martinis, S. and Cesca, S., 2019. Growth and collapse of a littoral lava dome during the 2018/19 eruption of Kadovar Volcano, Papua New Guinea, analyzed by multi-sensor satellite imagery. Journal of Volcanology and Geothermal Research, 388: 106704. DOI: 10.1016/j.jvolgeores.2019.106704 Poland, M.P. and Orr, T.R., 2014. Identifying hazards associated with lava deltas. Bulletin of Volcanology, 76(12): 880. DOI: 10.1007/s00445-014-0880-0 70 Poland, M.P., Peltier, A., Bonforte, A. and Puglisi, G., 2017. The spectrum of persistent volcanic flank instability: A review and proposed framework based on Kīlauea, Piton de la Fournaise, and Etna. Journal of Volcanology and Geothermal Research, 339: 63-80. DOI: 10.1016/j.jvolgeores.2017.05.004 DOI: 10.1007/s00445-014-0880-0 770 Poland, M.P., Peltier, A., Bonforte, A. and Puglisi, G., 2017. The spectrum of persistent volcanic flank instability: A review and proposed framework based on Kīlauea, Piton de la Fournaise, and Etna. Journal of Volcanology and Geothermal Research, 339: 63-80. DOI: 10.1016/j.jvolgeores.2017.05.004 Primulyana, S., Bani, P. and Harris, A., 2017. The effusive-explosive transitions at Rokatenda 2012–2013: unloading by extrusion of degassed magma with lateral gas flow. Bulletin of Volcanology, 79(2): 22. DOI: 10.1007/s00445-017- 775 1104-1 Primulyana, S., Bani, P. and Harris, A., 2017. The effusive-explosive transitions at Rokatenda 2012–2013: unloading by extrusion of degassed magma with lateral gas flow. Bulletin of Volcanology, 79(2): 22. DOI: 10.1007/s00445-017- 5 1104-1 775 36 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Rahmati, O., Zeinivand, H. and Besharat, M., 2016. Flood hazard zoning in Yasooj region, Iran, using GIS and multi-crite decision analysis. Geomatics, Natural Hazards and Risk, 7(3): 1000-1017. DOI: 10.1080/19475705.2015.1045043 Romero, J.E., Polacci, M., Watt, S., Kitamura, S., Tormey, D., Sielfeld, G., Arzilli, F., La Spina, G., Franco, L., Burton, M and Polanco, E., 2021. Volcanic Lateral Collapse Processes in Mafic Arc Edifices: A Review of Their Drivi 780 Processes, Types and Consequences. Frontiers in Earth Science, 9. DOI: 10.3389/feart.2021.639825 Siebert, L., 1984. Large volcanic debris avalanches: Characteristics of source areas, deposits, and associated eruption Journal of Volcanology and Geothermal Research, 22(3): 163-197. DOI: 10.1016/0377-0273(84)90002-7 Silver, E., Day, S., Ward, S., Hoffmann, G., Llanes, P., Driscoll, N., Appelgate, B. and Saunders, S., 2009. Volcano collap and tsunami generation in the Bismarck Volcanic Arc, Papua New Guinea. Journal of Volcanology and Geotherm 785 Research, 186(3): 210-222. DOI: 10.1016/j.jvolgeores.2009.06.013 Smith, M.S. and Shepherd, J.B., 1993. Preliminary investigations of the tsunami hazard of Kick'em Jenny submari volcano. Natural Hazards, 7(3): 257-277. DOI: 10.1007/BF00662650 Somerville, P., Blong, R. and Gissing, A., 2022. Hunga Tonga-Hunga Ha'apai Eruption 15th of January 2022, Risk Frontie Briefing Note 460. 790 Toosi, A.S., Calbimonte, G.H., Nouri, H. and Alaghmand, S., 2019. River basin-scale flood hazard assessment using modified multi-criteria decision analysis approach: A case study. Journal of Hydrology, 574: 660-671. DO 10.1016/j.jhydrol.2019.04.072 Turner, M.B., 2008. Eruption cycles and magmatic processes at a reawakening volcano, Mt. Taranaki, New Zealand thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Earth Science 795 Massey University, Palmerston North, New Zealand. Doctoral Thesis, Massey University. van Wyk De Vries, B. and Borgia, A., 1996. The role of basement in volcano deformation. Geological Society, Londo Special Publications, 110(1): 95. DOI: 10.1144/GSL.SP.1996.110.01.07 Walter, T.R., Haghshenas Haghighi, M., Schneider, F.M., Coppola, D., Motagh, M., Saul, J., Babeyko, A., Dahm, T., Tro V.R., Tilmann, F., Heimann, S., Valade, S., Triyono, R., Khomarudin, R., Kartadinata, N., Laiolo, M., Massime 800 F. and Gaebler, P., 2019. Complex hazard cascade culminating in the Anak Krakatau sector collapse. Natu Communications, 10(1): 4339. DOI: 10.1038/s41467-019-12284-5 Ward, S.N. and Day, S., 2003. Ritter Island Volcano—lateral collapse and the tsunami of 1888. Geophysical Journ International, 154(3): 891-902. DOI: 10.1046/j.1365-246X.2003.02016.x Rahmati, O., Zeinivand, H. and Besharat, M., 2016. Complex hazard cascade culminating in the Anak Krakatau sector collapse. Nature Communications, 10(1): 4339. DOI: 10.1038/s41467-019-12284-5 Ward, S.N. and Day, S., 2003. Ritter Island Volcano—lateral collapse and the tsunami of 1888. Geophysical Journal International, 154(3): 891-902. DOI: 10.1046/j.1365-246X.2003.02016.x V.R., Tilmann, F., Heimann, S., Valade, S., Triyono, R., Khomarudin, R., Kartadinata, N., Laiolo, M., Massimetti, 800 F. and Gaebler, P., 2019. Complex hazard cascade culminating in the Anak Krakatau sector collapse. Nature Communications, 10(1): 4339. DOI: 10.1038/s41467-019-12284-5 Ward, S.N. and Day, S., 2003. Ritter Island Volcano—lateral collapse and the tsunami of 1888. Geophysical Journal International, 154(3): 891-902. DOI: 10.1046/j.1365-246X.2003.02016.x Watters, R.J., Zimbelman, D.R., Bowman, S.D. and Crowley, J.K., 2000. Rock Mass Strength Assessment and Significance 805 to Edifice Stability, Mount Rainier and Mount Hood, Cascade Range Volcanoes. pure and applied geophysics, 157(6): 957-976. DOI: 10.1007/s000240050012 Watters, R.J., Zimbelman, D.R., Bowman, S.D. and Crowley, J.K., 2000. Rock Mass Strength Assessment and Significance 805 to Edifice Stability, Mount Rainier and Mount Hood, Cascade Range Volcanoes. pure and applied geophysics, 157(6): 957-976. DOI: 10.1007/s000240050012 Watts, P. and Waythomas, C.F., 2003. Theoretical analysis of tsunami generation by pyroclastic flows. Journal of Geophysical Research: Solid Earth, 108(B12). DOI: 10.1029/2002JB002265 Watters, R.J., Zimbelman, D.R., Bowman, S.D. and Crowley, J.K., 2000. Rock Mass Strength Assessment and Significance 805 to Edifice Stability, Mount Rainier and Mount Hood, Cascade Range Volcanoes. pure and applied geophysics, 157(6): 957-976. DOI: 10.1007/s000240050012 157(6): 957-976. DOI: 10.1007/s000240050012 Watts, P. and Waythomas, C.F., 2003. Theoretical analysis of tsunami generation by pyroclastic flows. Journal of Geophysical Research: Solid Earth, 108(B12). DOI: 10.1029/2002JB002265 Watts, P. and Waythomas, C.F., 2003. Theoretical analysis of tsunami generation by pyroclastic flows. Journal of Geophysical Research: Solid Earth, 108(B12). DOI: 10.1029/2002JB002265 37 37 Williams, R., Rowley, P. and Garthwaite, M.C., 2019. Reconstructing the Anak Krakatau flank collapse that caused the 810 December 2018 Indonesian tsunami. Geology, 47(10): 973-976. DOI: 10.1130/G46517.1 Yokoyama, I., 1981. A geophysical interpretation of the 1883 Krakatau eruption. Journal of Volcanology and Geothermal Research, 9(4): 359-378. DOI: 10.1016/0377-0273(81)90044-5 Yoshida, H., Sugai, T. and Ohmori, H., 2012. Size–distance relationships for hummocks on volcanic rockslide-debris avalanche deposits in Japan. Geomorphology, 136(1): 76-87. DOI: 10.1016/j.geomorph.2011.04.044 815 https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. https://doi.org/10.5194/egusphere-2022-130 Preprint. Discussion started: 4 April 2022 c⃝Author(s) 2022. CC BY 4.0 License. Williams, R., Rowley, P. and Garthwaite, M.C., 2019. Reconstructing the Anak Krakatau flank collapse that caused the 810 December 2018 Indonesian tsunami. Geology, 47(10): 973-976. DOI: 10.1130/G46517.1 Yokoyama, I., 1981. A geophysical interpretation of the 1883 Krakatau eruption. Journal of Volcanology and Geothermal Research, 9(4): 359-378. DOI: 10.1016/0377-0273(81)90044-5 Yoshida, H., Sugai, T. and Ohmori, H., 2012. Size–distance relationships for hummocks on volcanic rockslide-debris avalanche deposits in Japan. Geomorphology, 136(1): 76-87. DOI: 10.1016/j.geomorph.2011.04.044 815 Williams, R., Rowley, P. and Garthwaite, M.C., 2019. Reconstructing the Anak Krakatau flank collapse that caused the 10 December 2018 Indonesian tsunami. Geology, 47(10): 973-976. DOI: 10.1130/G46517.1 Williams, R., Rowley, P. and Garthwaite, M.C., 2019. Reconstructing the Anak Krakatau flank collapse that caused the 810 December 2018 Indonesian tsunami. Geology, 47(10): 973-976. DOI: 10.1130/G46517.1 Yokoyama, I., 1981. A geophysical interpretation of the 1883 Krakatau eruption. Journal of Volcanology and Geothermal Research, 9(4): 359-378. DOI: 10.1016/0377-0273(81)90044-5 Yoshida, H., Sugai, T. and Ohmori, H., 2012. Size–distance relationships for hummocks on volcanic rockslide-debris avalanche deposits in Japan. Geomorphology, 136(1): 76-87. DOI: 10.1016/j.geomorph.2011.04.044 815 Yokoyama, I., 1981. A geophysical interpretation of the 1883 Krakatau eruption. Journal of Volcanology and Geothermal Research, 9(4): 359-378. DOI: 10.1016/0377-0273(81)90044-5 Yoshida, H., Sugai, T. and Ohmori, H., 2012. Size–distance relationships for hummocks on volcanic rockslide-debris avalanche deposits in Japan. Geomorphology, 136(1): 76-87. DOI: 10.1016/j.geomorph.2011.04.044 15 Yoshida, H., Sugai, T. and Ohmori, H., 2012. Size–distance relationships for hummocks on volcanic rockslide-debris avalanche deposits in Japan. Geomorphology, 136(1): 76-87. DOI: 10.1016/j.geomorph.2011.04.044 815 815 38 38
https://openalex.org/W2802628226
https://research.monash.edu/files/289712005/253588639_oa.pdf
English
null
Benzoxaborole treatment perturbs S-adenosyl-L-methionine metabolism in Trypanosoma brucei
PLoS neglected tropical diseases
2,018
cc-by
13,354
RESEARCH ARTICLE OPEN ACCESS OPEN ACCESS Citation: Steketee PC, Vincent IM, Achcar F, Giordani F, Kim D-H, Creek DJ, et al. (2018) Benzoxaborole treatment perturbs S-adenosyl-L- methionine metabolism in Trypanosoma brucei. PLoS Negl Trop Dis 12(5): e0006450. https://doi. org/10.1371/journal.pntd.0006450 Editor: Timothy G. Geary, McGill University, CANADA Citation: Steketee PC, Vincent IM, Achcar F, Giordani F, Kim D-H, Creek DJ, et al. (2018) Benzoxaborole treatment perturbs S-adenosyl-L- methionine metabolism in Trypanosoma brucei. PLoS Negl Trop Dis 12(5): e0006450. https://doi. org/10.1371/journal.pntd.0006450 Benzoxaborole treatment perturbs S- adenosyl-L-methionine metabolism in Trypanosoma brucei Pieter C. Steketee1¤, Isabel M. Vincent1, Fiona Achcar1, Federica Giordani1, Dong- Hyun Kim2, Darren J. Creek3, Yvonne Freund4, Robert Jacobs4, Kevin Rattigan1, David Horn5, Mark C. Field5, Annette MacLeod1, Michael P. Barrett1* Pieter C. Steketee1¤, Isabel M. Vincent1, Fiona Achcar1, Federica Giordani1, Dong- Hyun Kim2, Darren J. Creek3, Yvonne Freund4, Robert Jacobs4, Kevin Rattigan1, David Horn5, Mark C. Field5, Annette MacLeod1, Michael P. Barrett1* 1 Wellcome Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom, 2 Centre for Analytical Bioscience, Division of Molecular and Cellular Sciences, School of Pharmacy, The University of Nottingham, Nottingham, United Kingdom, 3 Department of Biochemistry and Molecular Biology, Drug Delivery Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia, 4 Anacor Pharmaceuticals, Inc., Palo Alto, California, United States of America, 5 Wellcome Centre for Anti-Infectives Research, School of Life Sciences, University of Dundee, Dundee, United Kingdom a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 ¤ Current address: The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, United Kingdom * michael.barrett@glasgow.ac.uk Introduction The monoflagellate protozoan parasite Trypanosoma brucei is the causative agent of Human Afri- can trypanosomiasis (HAT), and is one of three species that cause Nagana in livestock [1]. HAT is prevalent in sub-Saharan Africa and is responsible for a significant socio-economic burden. The majority of HAT cases are caused by T. b. gambiense, in West Africa, with the remaining cases attributed to T. b. rhodesiense, in the east [2]. Cases have decreased in recent years from 38,000 in 1998 to fewer than 3,000 in 2015 [3], leading to the gambiense form of the disease being targeted by the WHO for elimination [4]. The disease is characterised by an early stage infection of the mammalian bloodstream and other tissues, followed by a late stage where the parasite penetrates the blood-brain barrier to proliferate within the central nervous system [1, 5]. Current therapeutics against HAT are inadequate, and in some cases, highly toxic, leading to fatal side effects—including a reactive encephalopathy in significant numbers of patient treated with melarsoprol [6]. There is evidence of resistance to these drugs in the field [7] and current therapeutics frequently target only one T. brucei subspecies, or either early- or late- stage HAT [8]. Thus, there is a desperate need for novel and improved therapeutics to combat HAT. An emerging class of boron-containing compounds known as benzoxaboroles have shown promise as therapies against a wide range of diseases including, but not limited to those caused by, viral [9], fungal [10], bacterial [11, 12] and parasitic [13] infections and inflammation [14]. These compounds have been reported to act as inhibitors of kinases [15], tRNA synthetases [16, 17], CPSF3 [18, 19], phosphodiesterases [20, 21], and carbonic anhydrases [22]. The benzoxaborole AN5568 (SCYX-7158) was previously identified as a potent trypanocide from a library screen of benzoxaborole 6-carboxamides [23]. In vivo analysis in murine models showed brain exposure was high, with a maximum serum concentration (Cmax) of 10 μg/mL and AUC0-24 hr higher than 100 μgh/mL, indicating favourable pharmacokinetics for a stage 2 HAT therapeutic [24]. Importantly, the compound can be administered orally and CNS con- centrations are maintained above minimum inhibitory concentration (MIC) for at least 20 hours, sufficient for a twice daily dose [24]. The same study observed a 100% cure rate after a regimen lasting 3 days or more, clearing both T. b. gambiense and T. b. rhodesiense infections [24]. Metabolomic response to AN5568 treatment in T. brucei study design, data collection and analysis, decision to publish, or preparation of the manuscript. study design, data collection and analysis, decision to publish, or preparation of the manuscript. Abstract The parasitic protozoan Trypanosoma brucei causes Human African Trypanosomiasis and Nagana in other mammals. These diseases present a major socio-economic burden to large areas of sub-Saharan Africa. Current therapies involve complex and toxic regimens, which can lead to fatal side-effects. In addition, there is emerging evidence for drug resis- tance. AN5568 (SCYX-7158) is a novel benzoxaborole class compound that has been selected as a lead compound for the treatment of HAT, and has demonstrated effective clearance of both early and late stage trypanosomiasis in vivo. The compound is currently awaiting phase III clinical trials and could lead to a novel oral therapeutic for the treatment of HAT. However, the mode of action of AN5568 in T. brucei is unknown. This study aimed to investigate the mode of action of AN5568 against T. brucei, using a combination of molecu- lar and metabolomics-based approaches.Treatment of blood-stage trypanosomes with AN5568 led to significant perturbations in parasite metabolism. In particular, elevated levels of metabolites involved in the metabolism of S-adenosyl-L-methionine, an essential methyl group donor, were found. Further comparative metabolomic analyses using an S-adenosyl- L-methionine-dependent methyltransferase inhibitor, sinefungin, showed the presence of several striking metabolic phenotypes common to both treatments. Furthermore, several metabolic changes in AN5568 treated parasites resemble those invoked in cells treated with a strong reducing agent, dithiothreitol, suggesting redox imbalances could be involved in the killing mechanism. Editor: Timothy G. Geary, McGill University, CANADA Received: December 1, 2017 Accepted: April 15, 2018 Published: May 14, 2018 Copyright: © 2018 Steketee et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright: © 2018 Steketee et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Funding: This work was funded by a Wellcome Trust (www.wellcome.ac.uk) PhD studentship awarded to PCS (096980/Z/11/Z), a core grant to the Wellcome Centre for Molecular Parasitology (104111/Z/14/Z) and a Medical Research Council (www.mrc.ac.uk) grant awarded to MPB, DH & MCF (MR/K008749/1). The funders had no role in 1 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Author summary Competing interests: We have read the journal’s policy and the authors of this manuscript have the following competing interests: Until January 2017, YF and RJ were employed by Anacor Pharmaceuticals, Inc., and involved in the development of the compound discussed. Human African Trypanosomiasis (HAT) is a neglected tropical disease affecting mostly rural communities of sub-Saharan Africa. New drugs for this parasitic disease have been slow to develop, but one new class of drug, the benzoxaboroles, has proven to be highly effective in preclinical models and holds promise for on-going clinical trials. The lead compound in this class is AN5568, also known as SCYX-7158. Here, we study the effects of AN5568 on intracellular metabolism of the parasite and show changes to pathways involved in S-adenosyl-methionine metabolism. Further work shows similarities between this drug and sinefungin, an inhibitor of methyltransferases and dithiothreitol, an endo- plasmic reticulum stress inducer. These phenotypes provide new clues to the mechanism of action of this compound. In vitro activity of AN5568 Efficacy of AN5568 was determined in both bloodstream form (BSF) and procyclic form (PCF) parasites of the Lister 427 strain, by calculating the half maximal effective concentration (EC50) (Table 1). In BSFs, mean EC50 was 193 ± 48 nM, whilst in contrast, the EC50 in PCF parasites was almost 10-fold higher. This suggests some difference in benzoxaborole targeting of the two developmental forms. Further analyses on other trypanosomatids were carried out (Table 1). The EC50 in Trypa- nosoma congolense, a closely-related trypanosome species of veterinary importance, was 509 ± 18 nM. In contrast, the promastigote stage of Leishmania mexicana, one of the trypano- somatid species responsible for Leishmaniasis, exhibited an EC50 of 37.7 ± 3.6 μM, almost 200-fold and 25-fold higher than in T. b. brucei BSF and PCF respectively (Table 1). Metabolomic response to AN5568 treatment in T. brucei AN5568, aside from one recent study where proteins potentially binding the drug were identi- fied through a chemoproteomics analysis and mutations in selected resistant lines were identi- fied [25]. Indeed, few MoAs have been resolved to date for preclinical benzoxaboroles [16]. Firstly, the anti-fungal Tavaborole, which targets the leucyl-tRNA synthetase, and more recently, an antimalarial that targets the cleavage and polyadenylation specificity factor subunit 3 (CPSF3) [19]. In addition, Crisaborole, a novel compound developed for the treatment of mild to moderate atopic dermatitis, was shown to inhibit phosphodiesterase 4 (PDE4) [21]. An understanding of AN5568 MoA is crucial to enable the identification of the specific drug target, development of further lead compounds, to assist in the choice of partner drugs in combination therapies and to elucidate potential mechanisms of resistance. Metabolomics, the study of all small molecules, or metabolites, in a given system, offers the possibility of direct drug target identification when drugs inhibit specific enzymes [26, 27]. In an ideal setting, drug inhibition of metabolic enzymes will result in elevated levels of the enzyme’s substrate, with a corresponding reduction in the product [26–28]. In this study, we utilised a liquid chromatography-mass spectrometry (LC-MS) platform, with the aim of eluci- dating the MoA of AN5568, using the lab-adapted Lister 427 strain of T. b. brucei. Liquid-chro- matography mass spectrometry analysis showed significant perturbations in methionine metabolism in drug-treated cells. Further investigation showed that the benzoxaborole is sig- nificantly antagonised in the presence of sinefungin, a non-specific methyltransferase inhibi- tor. In addition, parasites treated with sinefungin and the endoplasmic reticulum stress inducer dithiothreitol (DTT) both bear similar metabolic phenotypes to those observed follow- ing treatment with AN5568. Introduction The compound started Phase II/III clinical trials in the last quarter of 2016. In summary, AN5568 presents an exciting new therapeutic for the treatment of both early- and late-stage HAT. Whilst the pharmacokinetic parameters of the benzoxaborole are well understood, little work has been carried out with regard to understanding the mode of action (MoA) of PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 2 / 24 Metabolomic response to AN5568 treatment in T. brucei Fig 1. Metabolic changes associated with AN5568 treatment. A) A volcano plot showing the global metabolic changes associated with AN5568 treatment. Numbers at red dots correspond to the following metabolites that were significantly increased 1) S-adenosyl-L-methionine (m/z: 398.1374, RT: 18.02 min, 7.67-fold), 2) 1,2-Dihydroxy-5-(methylthio)pent-1-en-3-one (m/z: 162.0350, RT: 17.24 min, 46.33-fold), 3) 5’-methylthioadenosine (m/z: 297.0896, RT: 7.75 min, 6.17-fold), 4) N6-acetyl-L-lysine (m/z: 188.1162, RT: 14.70 min, 2.83-fold), 5) adenine (m/z: 135.0546, RT: 7.71 min, 12.55-fold), 6) 4-hydroxy- 4-methylglutamate (m/z: 177.0637, RT: 15.3 min, 3.46-fold), 7) N6,N6,N6-trimethyl-L-lysine (m/z: 188.1524, RT: 23.54 min, 7.40-fold), 8) cyclic ADP-ribose (m/z: 541.0608, RT: 16.90 min, 43.78-fold), 9) aminoacetone (m/z: 73.0528, RT: 7.67 min, 12.06-fold), 10) 8-amino-7-oxononanoate (m/z: 187.1208, RT: 13.75 min, 8.43-fold). Numbers at blue dots correspond to the following metabolites that were significantly decreased: 1) [PC(14:0)] 1-tetradecanoyl-sn-glycero- 3-phosphocholine (m/z: 467.3014, RT: 4.75 min, 0.35-fold), 2) sn-glycerol 3-phosphate (m/z: 172.0136, RT: 16.44 min, 0.40-fold), 3) D-glucosamine Fig 1. Metabolic changes associated with AN5568 treatment. A) A volcano plot showing the global metabolic changes associated with AN5568 treatment. Numbers at red dots correspond to the following metabolites that were significantly increased 1) S-adenosyl-L-methionine (m/z: 398.1374, RT: 18.02 min, 7.67-fold), 2) 1,2-Dihydroxy-5-(methylthio)pent-1-en-3-one (m/z: 162.0350, RT: 17.24 min, 46.33-fold), 3) 5’-methylthioadenosine (m/z: 297.0896, RT: 7.75 min, 6.17-fold), 4) N6-acetyl-L-lysine (m/z: 188.1162, RT: 14.70 min, 2.83-fold), 5) adenine (m/z: 135.0546, RT: 7.71 min, 12.55-fold), 6) 4-hydroxy- 4-methylglutamate (m/z: 177.0637, RT: 15.3 min, 3.46-fold), 7) N6,N6,N6-trimethyl-L-lysine (m/z: 188.1524, RT: 23.54 min, 7.40-fold), 8) cyclic ADP-ribose (m/z: 541.0608, RT: 16.90 min, 43.78-fold), 9) aminoacetone (m/z: 73.0528, RT: 7.67 min, 12.06-fold), 10) 8-amino-7-oxononanoate (m/z: 187.1208, RT: 13.75 min, 8.43-fold). Numbers at blue dots correspond to the following metabolites that were significantly decreased: 1) [PC(14:0)] 1-tetradecanoyl-sn-glycero- 3-phosphocholine (m/z: 467.3014, RT: 4.75 min, 0.35-fold), 2) sn-glycerol 3-phosphate (m/z: 172.0136, RT: 16.44 min, 0.40-fold), 3) D-glucosamine 6-phosphate (m/z: 259.0457, RT: 17.68 min, 0.47-fold), 4) 2-deoxy-D-ribose 5-phosphate (m/z: 214.0242, RT: 16.45 min, 0.39-fold), 5) Asp-Asp-Cys-Pro (peptide) (m/z: 448.1256, RT: 17.64 min, 0.22-fold). These metabolites all have p-values of <0.05. B) Plots of individual metabolites perturbed after AN5568 treatment. There was an enrichment in metabolites involved in L-methionine metabolism. WT; wild type untreated, AN5568; wildtype treated for six hours at 10x EC50. C) A schematic to show the metabolites involved in methyltransferase reactions. Red ‘x’ indicates the typical S-adenosyl-L-methionine-dependent methyltransferase reaction potentially affected by the benzoxaborole. https://doi.org/10.1371/journal.pntd.0006450.g001 AN5568 provokes profound changes in S-adenosyl-L-methionine levels in T. b. brucei Metabolomics analysis, using LC-MS, was carried out on T. b. brucei treated with AN5568 for six hours at a concentration of 1.9 μM (10-fold EC50). This time point was chosen as metabolic Table 1. EC50 concentrations calculated by alamar Blue for several trypanosomatids. Organism EC50 T. b. brucei–BSF 193 ± 48 nM T. b. brucei–PCF 1,500 ± 90 nM T. congolense–BSF 509 ± 18 nM L. mexicana—promastigote 37.7 ± 3.6 μM https://doi.org/10.1371/journal.pntd.0006450.t001 Table 1. EC50 concentrations calculated by alamar Blue for several trypanosomatids. Organism EC50 T. b. brucei–BSF 193 ± 48 nM T. b. brucei–PCF 1,500 ± 90 nM T. congolense–BSF 509 ± 18 nM L. mexicana—promastigote 37.7 ± 3.6 μM https://doi.org/10.1371/journal.pntd.0006450.t001 Table 1. EC50 concentrations calculated by alamar Blue for several trypanosomatids. Organism EC50 T. b. brucei–BSF 193 ± 48 nM T. b. brucei–PCF 1,500 ± 90 nM T. congolense–BSF 509 ± 18 nM L. mexicana—promastigote 37.7 ± 3.6 μM https://doi.org/10.1371/journal.pntd.0006450.t001 Table 1. EC50 concentrations calculated by alamar Blue for several trypanosomatids PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 3 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 3 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Metabolomic response to AN5568 treatment in T. brucei Following treatment, we observed an enrichment in metabolites involved in methionine metabolism (Fig 1), suggesting methyltransferases (MTase) as potential targets. The most sig- nificant of these changes were in the levels of S-adenosyl-L-methionine (AdoMet) (m/z: 398.1374, retention time (RT): 18.01 min, 7.67-fold, P = 0.0096) and 5’-methylthioadenosine (5’-MTA) (m/z: 297.0838, RT: 7.75 min, 6.17-fold, P = 4.61×10−6) (Fig 1). The levels of ade- nine, a purine nucleobase that is also formed as a byproduct of AdoMet degradation, were also increased (m/z: 135.0546, RT: 7.71 min, 12.55-fold, P = 0.0045) (Fig 1). The intermediate decarboxylated AdoMet (dcAdoMet), a key aminopropyl donor used in polyamine biosynthe- sis was not detected by LC-MS. These metabolites are all associated with the degradation of methionine, in addition to the recycling of this amino acid, which occurs in a cyclic metabolic pathway known as the Yang cycle, methionine salvage, or the 5’-methylthioadenosine (MTA) cycle [29, 30]. This pathway is crucial in maintaining a source of methyl groups for methyltransferase reactions as well as other processes such as polyamine biosynthesis [31]. It is currently unknown whether the com- plete Yang cycle is functional in T. brucei, although it is thought the parasite relies on uptake of exogenous L-methionine, rather than recycling the amino acid [32]. Nevertheless, metabolo- mics data were searched for further metabolites involved in the MTA cycle. Interestingly, one peak was putatively identified as 1,2-dihydro-5-(methylthio)pent-1-en-3-one (Fig 1A, red metabolite #2), which was significantly increased in AN5568-treated cells. This metabolite plays a role in the regeneration of L-methionine through 2-oxo-4-methylthiobutanoate (KMTB) [33]. The metabolomics data were further mined for 2-oxo-4-methylthiobutanoate, and a mass consistent with this metabolite appeared to decrease post-treatment (S1 Table). Whilst AdoMet was increased after AN5568 treatment, there was no corresponding decrease in levels of S-adenosyl-L-homocysteine (AdoHcy), the by-product of methylation reactions (Fig 1). Whilst there was no explanation for this observation, it is likely that homeo- static processes are at play. Indeed, the activity of S-adenosyl-L-homocysteine hydrolase (SAHH), the enzyme that catalyses the breakdown of AdoHcy into L-homocysteine and aden- osine, is strictly regulated in other organisms [34]. L-homocysteine similarly remained unchanged in the treated sample group. Importantly, two peaks corresponding to AN5568 were found, one for the parent ion and one for the boron-10 isotope (S1 Table). Most other changes observed after AN5568-treatment were in metabolites involved in amino acid metabolism (S1 Table), including increases in keto-arginine, modified lysines (mono-, di- and tri-methyl-L-lysine and acetyl-L-lysine) and aminoacetone as well as decreases in L-aspartate, L-proline, D-glucosamine 6-phosphate, L-carnitine and O-acetyl-L- carnitine (S1 Table). https://doi.org/10.1371/journal.pntd.0006450.g001 alterations occur much quicker than those of the genome or transcriptome. In addition, toxic compounds can lead to widespread metabolic perturbation, which would mask the effects of specific target inhibition as explained above. In this experiment, a total of 840 peaks were ten- tatively identified and considered as metabolites (Fig 1). Of these, 50 were significantly altered after drug treatment (Log2 fold-change = <-1, >1, P<0.05 [t-test]). These included a range of metabolites involved in carbohydrate metabolism and lipid metabolism, but mostly amino acid metabolism (S1 Table). PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 4 / 24 AN5568 provokes similar changes in procyclic T. b. brucei metabolism Plots of individual metabolites perturbed after AN5568 treatment. WT; wild-type untreated, AN5568; wildtype treated for eight hours at 15 μM (10x EC50). https://doi org/10 1371/journal pntd 0006450 g002 Fig 2. Metabolic changes in PCF T. b. brucei after AN5568 treatment. Plots of individual metabolites perturbed after AN5568 treatment. WT; wild-type untreated, AN5568; wildtype treated for eight hours at 15 μM (10x EC50). https://doi.org/10.1371/journal.pntd.0006450.g002 AN5568 provokes similar changes in procyclic T. b. brucei metabolism PCF Lister 427 cells were exposed to 15 μM (10x EC50) AN5568 to investigate whether benzox- aborole treatment induced similar changes in the metabolism of PCF cells to those observed in BSF cells (Fig 2). Important to note was the higher concentration of AN5568 in PCF cultures and a longer duration of drug exposure of 8 hours. The metabolic changes in PCF cells were found to be similar to those in BSF cells, indicating that the molecular mechanisms of drug action might also occur in the PCF stage. Once again, the most significant changes involved L-methionine and AdoMet metabolism (Fig 2). AdoMet (m/z: 398.1386, RT: 13.88 min) and 5’-MTA (m/z: 297.0898, RT: 7.69 min) were both highly increased after drug treatment. In addition, mono-, di- and tri-methylated lysines were again observed at high abundance. Finally, PCF cells also underwent changes in glycoprotein metabolism, as indicated by increased levels of UDP-glucose (Fig 2). 5 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Fig 2. Metabolic changes in PCF T. b. brucei after AN5568 treatment. Plots of individual metabolites perturbed after AN5568 treatment. WT; wild-type untreated, AN5568; wildtype treated for eight hours at 15 μM (10x EC50). Metabolomic response to AN5568 treatment in T. brucei Metabolomic response to AN5568 treatment in T. brucei Comparative analysis of AN5568 activity to Sinefungin, a non-specific methyltransferase inhibitor To investigate the hypothesis that MTases are targeted by AN5568, we compared the metabo- lomes of T. b. brucei cells treated with the non-specific AdoMet-dependent MTase inhibitor Fig 2. Metabolic changes in PCF T. b. brucei after AN5568 treatment. Plots of individual metabolites perturbed after AN5568 treatment. WT; wild-type untreated, AN5568; wildtype treated for eight hours at 15 μM (10x EC50). https://doi.org/10.1371/journal.pntd.0006450.g002 Comparative analysis of AN5568 activity to Sinefungin, a non-specific methyltransferase inhibitor T i i h h h i h MT d b AN5568 d h b Fig 2. Metabolic changes in PCF T. b. brucei after AN5568 treatment. Plots of individual metabolites perturbed after AN5568 treatment. WT; wild-type untreated, AN5568; wildtype treated for eight hours at 15 μM (10x EC50). https://doi.org/10.1371/journal.pntd.0006450.g002 Fig 2. Metabolic changes in PCF T. b. brucei after AN5568 treatment. Plots of individual metabolites perturbed after AN5568 treatment. WT; wild-type untreated, AN5568; wildtype treated for eight hours at 15 μM (10x EC50). https://doi org/10 1371/journal pntd 0006450 g002 Fig 2. Metabolic changes in PCF T. b. brucei after AN5568 treatment. Metabolomic response to AN5568 treatment in T. brucei To determine whether AN5568 and sinefungin target similar pathways in vitro, isobolo- gram experiments were conducted. Firstly, EC50 concentrations were calculated to be 193 nM and 1 nM for AN5568 and sinefungin respectively. Subsequently, a fixed ratio isobologram, as outlined previously by Fivelman and colleagues [37], was carried out to observe whether the effect of using the two compounds simultaneously was greater (synergism) or less than (antag- onism) the sum of the two compounds used separately. For each ratio (outlined in the meth- ods), the fractional inhibitory concentration (FIC) was calculated by dividing the EC50 of one drug in combination with the other, by the EC50 of that drug used alone. The sum of FIC was calculated by adding the FIC for one drug to that of the other for each ratio. Synergism can be defined as a mean FIC <0.5, whilst antagonism is likely occurring when FIC>1. Anything in between suggests the compounds do not interact. A scatter plot of FIC values showed higher FICs when the compounds were used in combi- nation (Fig 3A). The mean total fractional inhibitory concentration (SFIC) for AN5568 and sinefungin was calculated to be 1.21, suggesting slight antagonism between the two compounds. Metabolomics experiments were subsequently carried out, and a principal component anal- ysis (PCA) plot of three sample groups, wild-type, AN5568-treated and sinefungin-treated, revealed an association between the two drug-treated sample groups, which separated from the wild-type group (Fig 3B). Whilst the wild-type samples separated, both drug-treated A scatter plot of FIC values showed higher FICs when the compounds were used in combi- nation (Fig 3A). The mean total fractional inhibitory concentration (SFIC) for AN5568 and sinefungin was calculated to be 1.21, suggesting slight antagonism between the two compounds. A scatter plot of FIC values showed higher FICs when the compounds were used in combi- nation (Fig 3A). The mean total fractional inhibitory concentration (SFIC) for AN5568 and sinefungin was calculated to be 1.21, suggesting slight antagonism between the two compounds. Metabolomics experiments were subsequently carried out, and a principal component anal- ysis (PCA) plot of three sample groups, wild-type, AN5568-treated and sinefungin-treated, Metabolomics experiments were subsequently carried out, and a principal component anal ysis (PCA) plot of three sample groups, wild-type, AN5568-treated and sinefungin-treated, revealed an association between the two drug-treated sample groups, which separated from the wild-type group (Fig 3B). Comparative analysis of AN5568 activity to Sinefungin, a non-specific methyltransferase inhibitor To investigate the hypothesis that MTases are targeted by AN5568, we compared the metabo- lomes of T. b. brucei cells treated with the non-specific AdoMet-dependent MTase inhibitor sinefungin, to those of benzoxaborole-treated cells. Sinefungin is an AdoMet analogue con- taining an aminomethylene group in place of the methylated sulfonium group that typically acts as the methyl donor. It competes with AdoMet for MTase-binding and thereby inhibits AdoMet-dependent MTases in a non-selective manner [35, 36]. 6 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Metabolomic response to AN5568 treatment in T. brucei samples overlapped, thereby suggesting similarities between the two sample groups. Indeed, the main metabolic perturbations observed in AN5568-treated cells were also apparent in cells treated with sinefungin (Fig 3C, S1 Table). Most notably, increases in AdoMet and 5’-MTA were reproducible in both treatment groups. In addition, sinefungin-treated cells also exhib- ited increased abundance of mono-, di- and tri-methylated lysines, as well as adenine, all of which mirrored the metabolic changes in AN5568-treated cells. Interestingly, AdoHcy remained unchanged after sinefungin treatment (Fig 3C), suggesting that methyltransferase inhibition does not lead to decreased levels of AdoHcy that might be expected from inhibition of this class of enzymes. This might be due to downstream metabolite regulation of AdoHcy-hydrolase as previously mentioned [34]. There were also marked contrasts between AN5568- and sinefungin-treated cells. For example, AN5568-treated cells clearly exhibited changes in the trypanothione biosynthesis pathway, whilst these changes did not occur after sinefungin treatment (Fig 3D). Distribution of carbon originating from L-methionine in the T. b. brucei metabolome is not altered after AN5568 treatment To investigate whether any alterations in methylation patterns could be observed across the metabolic network, we carried out further LC-MS utilising Creek’s Minimal Medium (CMM) [38]. Adding 100% [U-13C]-L-methionine to CMM allowed the observation of the dissemina- tion of the isotope-labelled carbon atoms to be observed. As previously, cells were treated with 10× EC50 AN5568, and incubated for 6 hours under normal in vitro conditions. A total of 25 peaks containing 13C isotopes were detected (17 in negative mode, 8 in positive mode). Whilst the previously observed changes in methionine metabolism were reproducible, no changes in carbon distribution were observed between AN5568-treated and untreated cells (Fig 4). As expected, metabolic changes were consistent with previous experiments but intracellular L-methionine was not 100% labelled, suggesting that uptake is relatively slow. Hasne and col- leagues previously showed L-methionine uptake to be transporter mediated, and in BSF T. b. brucei the transporter exhibits a Vmax of 28.8 ± 0.1 nmol/min/108 cells [32]. Interestingly, whilst only small amounts of AdoMet and 5’-MTA were detected in untreated samples, they showed almost 100% labelling (Fig 4A), suggesting these metabolites all originate from L-methionine. In contrast, these metabolites were only ~75% labelled in drug-treated samples, suggesting they might be recycled, or the build-up initiates very quickly after drug treatment. AdoHcy was also detected, with four 13C labels, as predicted. In addition, L- cystathionine possessed four 13C labels, and was found to increase, as seen previously (Fig 4A). y p p y g Whilst arginine methylation was not observed in wild-type or drug-treated samples, meth- ylated lysines that were seen to increase in previous experiments did show stable isotope labels (S1 Fig), demonstrating that the carbon atoms in the methyl groups originated from L-methio- nine. Lysine methylation has been shown to be involved in the degradation pathway of this amino acid, which is ultimately converted to L-carnitine [39]. However, in neither sample group was L-carnitine found to exhibit 13C labelling (S1 Fig), indicating a separate source of this metabolite in T. b. brucei. Indeed, it was previously shown that the parasite has a high rate of L-carnitine uptake from serum [40]. Whilst the wild-type samples separated, both drug-treated Fig 3. Comparative analyses of T. b. brucei treated with AN5568 and sinefungin, a non-specific methyltransferase inhibitor. A) A fixed-ratio isobologram analysis was conducted using sinefungin and AN5568. B) Comparative metabolomics analysis was carried out to assess any common metabolic alterations between sinefungin- and AN5568-treated cells. A principal component analysis (PCA) plot of the 3 sample group was generated. C) Individual metabolites were compared in terms of their fold change over a control group. D) AN5568 treatment leads to increase abundance in components of the trypanothione biosynthesis pathway, whilst sinefungin treatment does not. https://doi.org/10.1371/journal.pntd.0006450.g003 Fig 3. Comparative analyses of T. b. brucei treated with AN5568 and sinefungin, a non-specific methyltransferase inhibitor. A) A fixed-ratio isobologram analysis was conducted using sinefungin and AN5568. B) Comparative metabolomics analysis was carried out to assess any common metabolic alterations between sinefungin- and AN5568-treated cells. A principal component analysis (PCA) plot of the 3 sample group was generated. C) Individual metabolites were compared in terms of their fold change over a control group. D) AN5568 treatment leads to increased abundance in components of the trypanothione biosynthesis pathway, whilst sinefungin treatment does not. https://doi.org/10.1371/journal.pntd.0006450.g003 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 7 / 24 Fig 3. Comparative analyses of T. b. brucei treated with AN5568 and sinefungin, a non-specific methyltransferase inhibitor. A) A fixed-ratio isobologram analysis was conducted using sinefungin and AN5568. B) Comparative metabolomics analysis was carried out to assess any common metabolic alterations between sinefungin- and AN5568-treated cells. A principal component analysis (PCA) plot of the 3 sample group was generated. C) Individual metabolites were compared in terms of their fold change over a control group. D) AN5568 treatment leads to increased abundance in components of the trypanothione biosynthesis pathway, whilst sinefungin treatment does not. https://doi.org/10.1371/journal.pntd.0006450.g003 7 / 24 Metabolomic response to AN5568 treatment in T. brucei in the production of glycosylphosphatidylinositol (GPI) anchors that attach the variant surface glycoproteins (VSG) to the trypanosome cell surface. To determine whether VSG biosynthesis was affected by AN5568 treatment, Western blots were generated using the Lister 427 line, which expresses VSG221 [41]. Firstly, lysates from cells treated with 10× EC50 AN5568 for 6 hours were probed with an αVSG221 antibody, and subsequently an α-enolase control (Fig 5B). No change in VSG221 expression was observed, although there appeared to be reduced expression of the endogenous control. Indeed, further analysis of the metabolomics data showed decreased levels of both the substrate and product (2-phospho-D-glycerate and phos- phoenolpyruvate respectively) of this enzyme, for reasons we could not ascertain (S1 Table). A further blot was generated using VSG cross-reacting determinant antibodies (VSG XR) (Fig 5C) [42]. For this experiment, cell lysates were separated into membrane and soluble frac- tions. Again, no changes were observed between the control and drug-treated samples, sug- gesting VSG biosynthesis is not impaired on a protein level. in the production of glycosylphosphatidylinositol (GPI) anchors that attach the variant surface glycoproteins (VSG) to the trypanosome cell surface. To determine whether VSG biosynthesis was affected by AN5568 treatment, Western blots were generated using the Lister 427 line, which expresses VSG221 [41]. Firstly, lysates from cells treated with 10× EC50 AN5568 for 6 hours were probed with an αVSG221 antibody, and subsequently an α-enolase control (Fig 5B). No change in VSG221 expression was observed, although there appeared to be reduced expression of the endogenous control. Indeed, further analysis of the metabolomics data showed decreased levels of both the substrate and product (2-phospho-D-glycerate and phos- phoenolpyruvate respectively) of this enzyme, for reasons we could not ascertain (S1 Table). A further blot was generated using VSG cross-reacting determinant antibodies (VSG XR) (Fig 5C) [42]. For this experiment, cell lysates were separated into membrane and soluble frac- tions. Again, no changes were observed between the control and drug-treated samples, sug- gesting VSG biosynthesis is not impaired on a protein level. AN5568 treatment affects glycoprotein metabolism, but does not lead to impaired VSG synthesis Several metabolites putatively identified as components of glycoprotein metabolism were ele- vated in benzoxaborole-treated cells. These included GDP-mannose, N-acetyl-D-glucosamine and UDP-glucose (or UDP-galactose) (Fig 5A). These metabolites are important components 8 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Comparing metabolic phenotypes of AN5568 treatment and ER stress Comparing metabolic phenotypes of AN5568 treatment and ER stress A major target for AdoMet donated methyl groups in T. b. brucei is the spliced leader cap RNA structure that is spliced to all mature messenger RNAs in these cells. Recent publications Fig 4. Tracing 13C distribution in AN5568-treated cells incubated with 13C-U-L-methionine. Cells were incubated with 200 μM [U-13C]-L-methionine for 6 hours. In addition, one sample group was incubated with 1.9 μM (10× EC50) AN5568. Metabolites involved in L-methionine metabolism detected in this experiment were overlaid onto metabolic maps. In cases where 13C isotopes were detected, graphs incorporating the percentage labelling are shown. The methionine salvage pathway (Yang cycle) is shown. Fig 4. Tracing 13C distribution in AN5568-treated cells incubated with 13C-U-L-methionine. Cells were incubated with 200 μM [U-13C]-L-methionine for 6 hours. In addition, one sample group was incubated with 1.9 μM (10× EC50) AN5568. Metabolites involved in L-methionine metabolism detected in this experiment were overlaid onto metabolic maps. In cases where 13C isotopes were detected, graphs incorporating the percentage labelling are shown. The methionine salvage pathway (Yang cycle) is shown. https://doi.org/10.1371/journal.pntd.0006450.g004 https://doi.org/10.1371/journal.pntd.0006450.g004 9 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Metabolomic response to AN5568 treatment in T. brucei Fig 5. VSG biosynthesis in AN5568-treated cells. A) Three metabolites, all known to be involved in glycoprotein biosynthesis, were found to be at higher levels in AN5568-treated cells. B) Western blots carried out on protein lysates taken from AN5568-treated cells at a 6-hour time-point showed no significant changes in VSG expression at this time- point. When the contrast of the resulting blot was increased, an extra band was seen in the 2× EC50-treated sample. C) In addition to VSG expression, blots were probed with a VSG cross-reacting determinant (VSG XR) antibody. For this experiment, protein lysates were fractionated to isolate the membrane fraction and separate it from the soluble fraction. Most of the cellular GPI is found in the membrane, and no changes in expression could be seen in cells treated with 10× EC50 for 6 hours. WT; untreated wild-type cells, AN5568; wild-type cells treated with AN5568 for 6 hours at 10× EC50. htt //d i /10 1371/j l td 0006450 005 Fig 5. VSG biosynthesis in AN5568-treated cells. A) Three metabolites, all known to be involved in glycoprotein biosynthesis, were found to be at higher levels in AN5568-treated cells. Comparing metabolic phenotypes of AN5568 treatment and ER stress B) Western blots carried out on protein lysates taken from AN5568-treated cells at a 6-hour time-point showed no significant changes in VSG expression at this time- point. When the contrast of the resulting blot was increased, an extra band was seen in the 2× EC50-treated sample. C) In addition to VSG expression, blots were probed with a VSG cross-reacting determinant (VSG XR) antibody. For this experiment, protein lysates were fractionated to isolate the membrane fraction and separate it from the soluble fraction. Most of the cellular GPI is found in the membrane, and no changes in expression could be seen in cells treated with 10× EC50 for 6 hours. WT; untreated wild-type cells, AN5568; wild-type cells treated with AN5568 for 6 hours at 10× EC50. https://doi.org/10.1371/journal.pntd.0006450.g005 have highlighted the presence of a unique ER stress response pathway in trypanosomatids [43– 45]. In response to unfolding proteins, and to ER stress inducers such as dithiothreitol (DTT), a programmed cell death known as the spliced leader silencing (SLS) pathway is activated, leading to programmed inhibition of spliced leader trans-splicing, as well as a reduction in total RNA, increased cytoplasmic Ca2+ and DNA fragmentation [43]. Presumably, this would also result in significant loss of RNA methylation. We therefore sought to compare the meta- bolomic profiles of DTT and AN5568 treated cells in an LC-MS experiment, in order to deter- mine whether the AdoMet signature was a specific response to the benzoxaborole treatment, or a non-specific stress response (Fig 6). No changes were observed in AdoMet (m/z: 398.1381, RT: 13.72 min, 2.53-fold, P = 0.230) and adenine (m/z: 135.0545, RT: 9.48 min, 1.37-fold, P = 0.190), after DTT-treatment (Fig 6A). Furthermore, 5’-MTA (m/z: 297.0889, RT: 6.70 min, 0.54-fold, P = 0.034) was decreased, com- pared to wild-type control, not increased as observed in AN5568 treatment. DTT treatment also led to metabolic changes in stress responses such as the trypanothione biosynthesis pathway (Fig 6B). Modified lysines were increased, in a similar fashion to AN5568 treatment. In particular, there was increased abundance of N6-acetyl-L-lysine (m/z: 188.1162, RT: 11.62 min, 4.26-fold, P = 0.0021), N6-methyl-L-lysine (m/z: 160.1211, RT: 18.99 min, 2.80-fold, P = 0.0004) and N6,N6,N6-trimethyl-L-lysine (m/z: 188.1528, RT: 18.09 min, 1.62-fold, P = 0.013) (Fig 6C), suggesting these changes are not unique to AN5568 treatment, 10 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Metabolomic response to AN5568 treatment in T. Comparing metabolic phenotypes of AN5568 treatment and ER stress brucei Fig 6. Comparing metabolic profiles of DTT and AN5568 treated cells. A heatmap was generated to highlight similarities and differences in metabolism after treatment with the ER stress inducer dithiothreitol (DTT) and AN5568. A) AdoMet metabolism was unaffected by DTT-treatment. B) Components of the oxidative stress response pathway were altered after both treatments. In particular, DTT treatment led to a significant decrease in trypanothione disulphide. C) Both DTT and AN5568 treatment result in increased levels of modified lysines and arginines, suggesting these are part of a conserved trypanosomatid stress response. WT; wild-type untreated, AN5568; wild-type cells treated with AN5568 for 6 hours at 10× EC50, DTT; wild-type cells treated with DTT for 6 hours at 10× EC50. Fig 6. Comparing metabolic profiles of DTT and AN5568 treated cells. A heatmap was generated to highlight similarities and differences in metabolism after treatment with the ER stress inducer dithiothreitol (DTT) and AN5568. A) AdoMet metabolism was unaffected by DTT-treatment. B) Components of the oxidative stress response pathway were altered after both treatments. In particular, DTT treatment led to a significant decrease in trypanothione disulphide. C) Both DTT and AN5568 treatment result in increased levels of modified lysines and arginines, suggesting these are part of a conserved trypanosomatid stress response. WT; wild-type untreated, AN5568; wild-type cells treated with AN5568 for 6 hours at 10× EC50, DTT; wild-type cells treated with DTT for 6 hours at 10× EC50. Fig 6. Comparing metabolic profiles of DTT and AN5568 treated cells. A heatmap was generated to highlight similarities and differences in metabolism after treatment with the ER stress inducer dithiothreitol (DTT) and AN5568. A) AdoMet metabolism was unaffected by DTT-treatment. B) Components of the oxidative stress response pathway were altered after both treatments. In particular, DTT treatment led to a significant decrease in trypanothione disulphide. C) Both DTT and AN5568 treatment result in increased levels of modified lysines and arginines, suggesting these are part of a conserved trypanosomatid stress response. WT; wild-type untreated, AN5568; wild-type cells treated with AN5568 for 6 hours at 10× EC50, DTT; wild-type cells treated with DTT for 6 hours at 10× EC50. but potential indicators of metabolic responses to stress. Further similarities were also found in keto-arginine (S2 Table). but potential indicators of metabolic responses to stress. Further similarities were also found in keto-arginine (S2 Table). In silico analysis of the T. brucei methyltransferome Bioinformatics analysis of the entire kinase complement in the Tri-Tryps (T. brucei, T. cruzi and Leishmania spp.) has greatly aided the identification of novel therapeutic targets, and driven research into this class of enzymes [46]. Methyltransferases (MTases) are a different class of highly specialised enzymes involved in the methylation of a large variety of substrates, which carry equal potential as therapeutic targets. However, the T. brucei methyltransferase complement has not been studied in great detail, with only ~25 experimentally characterised. Indeed, only two large-scale MTase studies have previously been reported [47, 48]. Given the metabolomics data generated, we sought to apply this in silico approach to characterise the T. brucei “methyltransferome” (MTome), with the aim of identifying potential AN5568 targets. Using a combination of interpro and pfam [49–51], a total of 143 genes containing MTase domains were identified (Fig 7), the majority of which contained additional conserved domains involved in substrate binding, transmembrane domains and localisation signalling PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 11 / 24 Metabolomic response to AN5568 treatment in T. brucei Fig 7. The T. brucei “methyltransferome”. A) A stylised tree depicting the entire methyltransferase complement of T. brucei, clustered based on domain class as designated by Schubert and colleagues [52]. The arrangements of genes and branch lengths carry no significance as methyltransferases are highly diverse, making generation of a phylogenetic tree challenging. Gene IDs in bold italics have been previously characterised. Abbreviations: TM: Tetrapyrrole methylase. B) Number of members in each class of methyltransferase. Enzymes containing Rossmann-like folds and SET domains are numerous compared to the remaining classes. C) Methyltransferases grouped by the substrate they methylate. The majority of MTases studied include spliced leader RNA MTases and protein arginine MTases. SET domain-containing proteins are likely lysine MTases. https://doi.org/10.1371/journal.pntd.0006450.g007 Fig 7. The T. brucei “methyltransferome”. A) A stylised tree depicting the entire methyltransferase complement of T. brucei, clustered based on domain class as designated by Schubert and colleagues [52]. The arrangements of genes and branch lengths carry no significance as methyltransferases are highly diverse, making generation of a phylogenetic tree challenging. Gene IDs in bold italics have been previously characterised. Abbreviations: TM: Tetrapyrrole methylase. B) Number of members in each class of methyltransferase. Enzymes containing Rossmann-like folds and SET domains are numerous compared to the remaining classes. C) Methyltransferases grouped by the substrate they methylate. Metabolomic response to AN5568 treatment in T. brucei domains (S3 Table). This list was categorised based on major folds present in the MTase domains, similar to the methodology used in the Wlodarski and Petrossian & Clarke studies [47, 48]. The majority of MTases (87/143) were found to exhibit Rossman-like folds. Most of the experimentally characterised methyltransferases are present in this group, including arginine methyltransferases, DOT methyltransferases and proteins involved in spliced leader methyla- tion (Fig 7A). Furthermore, this group contains lipid MTases as well as rRNA and tRNA MTases, most of which remain uncharacterised. Another group with many representatives are proteins containing the conserved SET domain (Fig 7A & 7B). These 33 genes are likely to be involved in protein lysine methylation, in particular methylation of histones [53]. This group is far larger than expected (The S. cerevi- siae genome encodes 12 SET domain MTases [47]), and could be indicative of the parasite’s need to alter global gene expression throughout the varying life cycle stages. Further work is required to confirm whether these proteins are true MTases. Indeed, none of the T. b. brucei SET domain MTases have been experimentally characterised, yet proteins of this class have been identified as therapeutic targets in cancer, and other protozoan parasites such as Plasmo- dium [54], and could present an interesting group of trypanocidal candidate targets. Like the S. cerevisiae MTome, the T. brucei genome also contains genes for other MTase family members, including SPOUT domain MTases (8 genes), tetrapyrrole methylases (2 genes), a DNA/RNA-binding 3-helical bundle MTase (1 gene) a thymidylate synthase (1 gene) a homocysteine MTases (1 gene), isoprenylcysteine carboxyl MTase (1 gene) and a TYW3 MTase (1 gene) (Fig 7). Finally, whilst not genuine methyltransferases, we chose to include the 8 predicted radical SAM enzyme family. These proteins typically cleave AdoMet to generate a 5’-deoxyadenosyl 5’-radical [55]. We attempted to overexpress several of the genes identified in the MTome screen based on their essentiality in an RNAi screen [56] (Gene IDs: Tb927.10.3080, Tb927.10.7560, Tb927.10/ 7850, Tb927.5.2050, Tb927.8.5040 and Tb927.6.2270). Whilst overexpression of some MTases was achievable, their overexpression did not alter parasite sensitivity to AN5568, although in the case of Tb927.8.5040 and Tb927.10.7850, resistance against sinefungin was noted (S2 Fig). In silico analysis of the T. brucei methyltransferome The majority of MTases studied include spliced leader RNA MTases and protein arginine MTases. SET domain-containing proteins are likely lysine MTases. PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 12 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Microscopy analysis of AN5568 treated BSF cells Morphological changes occurring during AN5568 treatment of T. b. brucei were investigated using fluorescence microscopy. The nuclear and kinetoplastid DNA were stained using DAPI, whilst Mitotracker was used to visualise the mitochondrion (Fig 8). Time-course experiments were carried out on BSF T. b. brucei using a single dose of AN5568 at 2× EC50 (380 nM). Wild- type controls were supplemented with an equal volume of DMSO. No significant changes in morphology were observed 6 hours post-treatment (Fig 8A). However, by 12 hours, most cells exhibited a rounded shape indicating adverse responses to the compound (Fig 8A). In addition, DAPI staining revealed several nucleolar spots visible after 12 and 24 hours, which could indicate a mitotic block. Interestingly, Mitotracker staining showed that rather than a long, single, elongated mitochondrion typical of BSF T. brucei, the organelle appeared patchy and swollen (Fig 8A). After 24 hours of 2× EC50 treatment, the aforementioned phenotypes were far more pronounced and cells were rounded, with multiple flagella and lack of flagellar extension. Furthermore, DAPI highlighted the presence of multiple DNA-compartments. To test whether AN5568 treatment affected T. b. brucei cell cycle and/or nuclear and kineto- plast replication, NK analysis was conducted (Fig 8B). Percentages were calculated for cells containing 1 of each organelle (1N1K); 1 nucleus and 2 kinetoplasts (1N2K); two of each 13 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Metabolomic response to AN5568 treatment in T. brucei Fig 8. Effect of AN5568 treatment on T. b. brucei cell division and morphology. T. b. brucei cells were incubated with 2× EC50 concentration of AN5568 and cells were isolated for analysis by microscopy at specific time points. A) After 6 hours of drug exposure, cells appeared normal under both direct light and DAPI, whilst mitochondria were swollen. This phenotype was exaggerated by 12-hours post-treatment. After 24 hours, DAPI staining indicated a buil Metabolomic response to AN5568 treatment in T. bruc Fig 8 Effect of AN5568 treatment on T b brucei cell division and morphology T b brucei cells were incubated Fig 8. Effect of AN5568 treatment on T. b. brucei cell division and morphology. T. b. brucei cells were incubated with 2× EC50 concentration of AN5568 and cells were isolated for analysis by microscopy at specific time points. A) After 6 hours of drug exposure, cells appeared normal under both direct light and DAPI, whilst mitochondria were swollen. Discussion The benzoxaborole AN5568 (SCYX-7158) is a promising lead compound for treatment of HAT, an infectious disease caused by T. brucei subspecies. Whilst the drug is currently await- ing phase III clinical trials, the MoA is as-of-yet unknown. We sought to use a metabolomics- based approach to reveal the metabolic perturbations induced by AN5568 in the lab-adapted Lister 427 strain of T. b. brucei. AN5568 treatment induced 50 significant metabolic perturbations in BSF trypanosomes, with most identified as components of amino acid metabolism. In particular, there was an enrichment of metabolites involved in L-methionine and AdoMet metabolism, leading us to hypothesize that an MTase could be targeted. Indeed, AN5568 exhibits antagonism with sine- fungin, a competitive AdoMet-dependent MTase inhibitor. Further mass spectrometry analyses were undertaken to compare metabolic profiles of sine- fungin, a known methyltransferase inhibitor and AN5568-treated parasites. These experiments identified AdoMet and 5’-MTA as key players in methyltransferase inhibition. Stable isotope-labelled [U-13C]-L-methionine was introduced to in vitro culture, in an attempt to resolve the aforementioned metabolic changes. However, to our surprise, fewer than 20 metabolites were found to incorporate carbon from L-methionine. This suggests that a) L-methionine is not an essential source of carbon in terms of small molecule metabolism, and b) carbon in methylation reactions is mainly transferred to larger molecules that could not be detected by LC-MS, probably proteins. Furthermore, the absence of labelled methyl-argi- nine in either untreated controls or drug-treated cells was surprising, and suggests that argi- nine methylation is either a slower process than, for example, lysine methylation, or the methyl groups used to methylate arginine do not originate from L-methionine or indeed AdoMet. In addition, these processes could occur in different subcellular localisations or compartments. Interestingly, the metabolic profile of DTT treated cells bore some similarities to those treated with AN5568, suggesting that T. b. brucei activates the conserved SLS pathway in response to the benzoxaboroles, although DTT may also impair cellular redox balance and induce other stresses in common with AN5568. These experiments were performed in order to see whether the loss of trans-splicing associated with the SLS pathway might lead to accu- mulation of AdoMet and related metabolites too, although it did not. Several findings presented here are in agreement with a previous study of AN5568 MoA in T. b. brucei [25]. Most notably, inhibition of cytokinesis was observed in both studies [25] (Fig 8). Metabolomic response to AN5568 treatment in T. brucei up of DNA-containing compartments in a significant number of cells, suggesting a cytokinetic defect. Scale bar represents 5 μm. B) Cell cycle analysis was carried out by counting the numbers of nuclei and kinetoplasts in AN5568-treated cells. Drug-treated cells were compared to a DMSO control at 6, 12 and 24 hour time-points, as indicated by the horizontal lines. up of DNA-containing compartments in a significant number of cells, suggesting a cytokinetic defect. Scale bar represents 5 μm. B) Cell cycle analysis was carried out by counting the numbers of nuclei and kinetoplasts in AN5568-treated cells. Drug-treated cells were compared to a DMSO control at 6, 12 and 24 hour time-points, as indicated by the horizontal lines. https://doi org/10 1371/journal pntd 0006450 g008 https://doi.org/10.1371/journal.pntd.0006450.g008 organelle (2N2K); 2 nuclei and 1 kinetoplast (2N1K), which suggests a defect in kinetoplast replication; and finally, cells containing more than 2 of each organelle (MNMK). The NK results mirrored the morphology analyses, and parasites exhibited no significant changes in nuclear and kinetoplast number after 6 hours. However, by 12 hours, almost 20% of cells contained 2 kinetoplasts and 2 nuclei, almost double the percentage of untreated para- sites (Fig 8B). PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Microscopy analysis of AN5568 treated BSF cells This phenotype was exaggerated by 12-hours post-treatment. After 24 hours, DAPI staining indicated a build- PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 14 / 24 T. b. brucei in vitro culture For BSF culture, the Lister 427 strain was used and maintained at 37˚C, 5% CO2. Cells were cul- tured in HMI-9, supplemented with 10% foetal bovine serum (FBS). For [U-13C]-L-methionine experiments, Creek’s Minimal Media was used [38], and isotope labelled metabolites were added upon initiation of time-course experiments. Procyclic form culture also utilised Lister 427 (also identified as 29–13). PCFs were cultured in SDM-79 (Gibco, Cat#: 07490916N) [58], supplemented with 10% FBS and 7.5 μg/mL hemin. PCF cell density was maintained between 5 × 105 cells/mL and 1 × 107 cells/mL and grown at 27˚C. For overexpression of methyltransferases, BSF T. brucei Lister 427 were transfected with methyltransferase open reading frames inserted into the pURAN vector. Transfection was car- ried out as previously described [56]. Drug sensitivity in successfully transfected cell line was tested by alamar blue. Metabolomic response to AN5568 treatment in T. brucei corresponding to the AdoMet decarboxylase (AdoMetDC) array. However, if AdoMetDC was the benzoxaborole target, treatment would hypothetically lead to reduced levels of 5’-MTA which was not seen (Fig 1). Based on the data presented here, it seems that AN5568 has a significant effect on methio- nine metabolism, and induces a stress response similar to the spliced leader silencing pathway. However, we have not been able to assign these effects directly to a specific enzyme or particu- lar methyltransferase reaction. This study also presents, to our knowledge, the first collection of all predicted MTases in the T. brucei genome. Using previous studies of H. sapiens [48] and S. cerevisiae [47] as a guide, as well as publicly available pfam annotations from TriTrypDB [57], a dataset was generated based on MTase class and fold. MTases are highly diverse and uniquely specific depending on their biological function, and many are essential in protein synthesis, regulation of gene expression, spliced leader methylation, and regulation of the cell cycle. They therefore present a protein family of therapeutic interest. One interesting finding in this regard is the large number of SET domain MTases which are predicted lysine methylators, predicted in the T. brucei genome. It is likely that many of these enzymes play crucial roles in histone modulation and maintenance of gene expression throughout the extremely diverse life cycle stages of the parasite. The dataset requires further refinement and expansion to include T. cruzi and Leishmania spp. Furthermore, the majority of these proteins remain uncharacterised experimentally. We hope this dataset will inspire fur- ther work on a group of proteins that in other settings, such as cancer biology, has recently generated intense interest. Although we now reveal metabolomics changes to trypanosomes treated with AN5568 we cannot attribute a mode of action to the drug from this data, in common with the other high throughput analysis on proteins that bind the drug and genetic differences in parasites selected for resistance [18]. However, the results outlined here suggest that AN5568 action is not in a catabolic or anabolic pathway, similar to other members of the benzoxaborole family [15, 16, 19, 21]. Further studies, for example, seeking genome scale over-expression libraries will be required to definitively find the cellular target of the drug. Discussion However, many drugs affect the ability of T. b. brucei to divide, and it is therefore not indic- ative of a particular mode of action for this compound. Interestingly, in the context of these data, Jones and colleagues found genomic deletions in one resistant cell line in a region PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 15 / 24 Isobologram assays To investigate drug-drug interactions, isobologram analyses were carried out using a fixed- ratio protocol previously described [37]. This assay uses the same principles as an alamar blue assay to test for cell viability over a range of drug concentrations but testing two drugs simultaneously. For both drugs, the top concentrations used were chosen for the EC50 to fall near the mid- point of a 12-part two-fold dilution series. We typically started with 16× EC50 and fixed ratio solutions of drugs were made as follows: 10:0, 9:1, 8:2, 7:3, 6:4, 5:5, 4:6, 3:7, 2:8, 1:9, 0:10. These stocks were then added to the first column of 3 solid white flat-bottomed 96-well plates in duplicate. The compounds were then serially diluted 1:1 with the final well of each row left blank as a negative control. Finally, cells were added at a final concentration of 2 × 104 cells/ mL. Plates were then incubated for 48 hours and alamar blue reagent added as described above. The plates were read after another 24 hour incubation on a BMG FLUOstar OPTIMA microplate reader (BMG Labtech GmbH, Germany) as described above. For each fixed ratio, an EC50 value was generated for either drug. These values were then used to obtain fractional inhibitory concentration (FICs) indices, which are defined as the EC50 values of drug in combination, divided by the EC50 values of those drugs acting alone [61]. The isobologram was then generated by plotting the FICs of one drug against the other. g g used to obtain fractional inhibitory concentration (FICs) indices, which are defined as the EC50 values of drug in combination, divided by the EC50 values of those drugs acting alone [61]. The isobologram was then generated by plotting the FICs of one drug against the other. The overall mean SFIC was calculated for each combination by adding the values of each individual FIC of either drug, and a mean SFIC value was used to assess whether the drug interactions were synergistic, indifferent or antagonistic. The overall mean SFIC was calculated for each combination by adding the values of each individual FIC of either drug, and a mean SFIC value was used to assess whether the drug interactions were synergistic, indifferent or antagonistic. Metabolomic response to AN5568 treatment in T. brucei plus (Sigma). Density was maintained between 5 × 104 and 2 × 106 cells/mL and cultured were incubated at 34˚C, 5% CO2. Leishmania mexicana promastigotes were cultured in a modified Minimum Eagle’s medium, termed HOMEM, supplemented with 10% FBS and 1% penicillin/streptomycin [59]. Cultures were maintained at 25˚C. Alamar blue assays To obtain in vitro EC50 values for specific compounds targeting T. b. brucei, the alamar blue assay was applied in 96-well plates (adapted from [60]). Compounds were added starting with the highest concentration (typically 100 μM) and serially diluted 1:2 over either 23 wells, leav- ing one negative control. Subsequently, BSF T. b. brucei cells were added at a final density of 2 × 104 cells/mL. Plates were incubated at 37˚C, 5% CO2 and 20 μL of alamar blue reagent (resazurin sodium salt, 0.49 mM in 1× PBS, pH 7.4) was added to each well after 48 hours. Reduction of the alamar blue reagent was measured as a function of cell viability on a BMG FLUOstar OPTIMA microplate reader (BMG Labtech GmbH, Germany) with λexcitation = 544 nm and λemission = 590 nm. The raw values were plotted against the log value of each concen- tration of drug or compound, and EC50 values were calculated using a non-linear sigmoidal dose-response curve. Each assay was performed in duplicate, and the final EC50 values pre- sented represent a mean of three or four independent experiments. For PCF parasites, plates were incubated for 72 hours prior to addition of alamar blue reagent, and then incubated for another 48 hours. When BSF T. congolense were assayed, the BSF T. b. brucei protocol was used, with an initial density of 2.5 × 105 cells/mL. Further parasite in vitro culture T. congolense bloodstream form, strain IL3000, were cultured in TcBSF3 a recently developed culture medium. Cultures were supplemented with 20% goat serum (Gibco) and 5% serum 16 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Metabolomic response to AN5568 treatment in T. brucei independently. In experiments involving stable isotope labelling, three replicates were used and isotope-labelled compounds ([U-13C]-L-methionine, enrichment 99%, Cambridge Iso- tope Laboratory Inc., cat: CLM-893-H-0.1) were added at the moment the time course was ini- tiated. After quenching, samples were centrifuged for 10 minutes at 1,500 × g, 4˚C, and all experimental steps hereafter were done on ice to keep the samples cold. Subsequently, 5 μL supernatant was transferred to an Eppendorf containing 200 μL extraction solvent (Appendix D), and the rest removed. Cells were re-suspended in the remaining supernatant and trans- ferred to an Eppendorf so that they could be centrifuged at 1,500 × g for another 5 minutes. Remaining supernatant was carefully removed, and the cells re-suspended in 200 μL extraction solvent. All samples, including a blank and fresh medium control, were then left in a shaker at 4˚C for one hour. Subsequently, samples were spun down at 16,060 × g for 10 minutes, and the supernatant was transferred to a 2 mL screw-top tube. From each sample, 10 μL was trans- ferred to an empty tube to produce a quality control sample. Finally, air in the tubes was dis- placed with argon gas to prevent oxidation of metabolites, and samples were stored at -80˚C until they were analysed by liquid chromatography-mass spectrometry. All mass spectrometry of metabolite samples was carried out by Glasgow Polyomics. Meta- bolomics samples were separated by hydrophilic interaction liquid chromatography (HPLC) using a ZIC-pHILIC (polymer-based HPLC) column (Merck). Two solvents were used in the column. Solvent A was 20 mM ammonium carbonate in H2O and solvent B was 100% acetoni- trile. Mass detection was carried out using an Exactive Orbitrap mass spectrometer (Thermo). The mass spectrometer was run in positive and negative mode with an injection volume of 10 μL and a flow rate of 100 μL/minute. Metabolomics, LC-MS & data analysis Samples for metabolomics analysis were acquired by rapidly quenching 8 × 107 cells in log phase in a dry-ice/ethanol bath, to ~4˚C. For each sample group, four replicates were grown 17 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Computational methods Graphical representation of data was created using the Graphpad Prism software (v6.0, GraphPad Software, www.graphpad.com), R [65] or Inkscape. Statistical analyses were carried out using Gra- phpad Prism, SPSS, Microsoft Excel and R. Further computational analysis was carried out using R. Analysis of microscopy images, as well as processing of blots, was carried out using Fiji [64]. Software, www.graphpad.com), R [65] or Inkscape. Statistical analyses were carried out using Gra phpad Prism, SPSS, Microsoft Excel and R. Further computational analysis was carried out using R. Analysis of microscopy images, as well as processing of blots, was carried out using Fiji [64]. Raw data produced by the mass spectrometer were converted to the mzXML format using msconvert [66]. This step also split the polarity of the data. Files were then converted to peakML files with XCMS, which uses the Centwave function to pick peaks, converting every individual file to the peakML output. Raw data produced by the mass spectrometer were converted to the mzXML format using msconvert [66]. This step also split the polarity of the data. Files were then converted to peakML files with XCMS, which uses the Centwave function to pick peaks, converting every individual file to the peakML output. Metabolite identification was done using Ideom [67, 68]. Where targeted metabolomics using stable isotopes labelling was carried out, mzMatch-ISO [69] was used for metabolite identification, and all hits were then confirmed using Ideom. Putatively identified metabolites were also analysed using the Metacyc [70] and Kegg [71] databases. Further metabolomics fig- ures, including heat maps and PCA plots, were either created using Metaboanalyst [72], Microsoft Excel, R or GraphPad Prism. Metabolomic response to AN5568 treatment in T. brucei To measure the distance between nucleus and kinetoplast, images were obtained from DAPI-stained samples and these imported into the Fiji software [64]. Distances were measured after the scale was set using the “measure” tool. For each sample group, 30 measurements were taken from three independent microscopy experiments. S3 Table. Genes containing MTase domains identified in T. b. brucei. (XLSX) S1 Fig. Tracing 13C distribution in AN5568-treated cells: Lysine metabolism. Methylated lysine contains methyl groups originating from L-methionine. Whilst lysine methylation has been shown to be involved in the generation of L-carnitine, no 13C-labeled L-carnitine was detected in wild-type or AN5568-treated cells. S1 Fig. Tracing 13C distribution in AN5568-treated cells: Lysine metabolism. Methylated lysine contains methyl groups originating from L-methionine. Whilst lysine methylation has been shown to be involved in the generation of L-carnitine, no 13C-labeled L-carnitine was detected in wild-type or AN5568-treated cells. (TIFF) S2 Fig. AN5568 and sinefungin sensitivity in methyltransferase overexpression lines. Six T. brucei overexpression lines were generated and their sensitivity to both AN5568 and sinefun- gin was tested. Whilst no methyltransferase conferred resistance to AN5568 when overex- pressed, two overexpressors did show a moderate increase in sinefungin resistance ( = P<0.05, Student’s t-test). (TIFF) S2 Fig. AN5568 and sinefungin sensitivity in methyltransferase overexpression lines. Six T. brucei overexpression lines were generated and their sensitivity to both AN5568 and sinefun- gin was tested. Whilst no methyltransferase conferred resistance to AN5568 when overex- pressed, two overexpressors did show a moderate increase in sinefungin resistance ( = P<0.05, Student’s t-test). (TIFF) S2 Fig. AN5568 and sinefungin sensitivity in methyltransferase overexpression lines. Six T. brucei overexpression lines were generated and their sensitivity to both AN5568 and sinefun- gin was tested. Whilst no methyltransferase conferred resistance to AN5568 when overex- pressed, two overexpressors did show a moderate increase in sinefungin resistance ( = P<0.05, Student’s t-test). (TIFF) S2 Table. Metabolomics dataset for AN5568 and DTT treatment of T. b. brucei Lister 427. (XLSX) S3 Table. Genes containing MTase domains identified in T. b. brucei. (XLSX) S1 Table. Metabolomics dataset for AN5568 and sinefungin treatment of T. b. brucei Lister 427. (XLSX) S1 Table. Metabolomics dataset for AN5568 and sinefungin treatment of T. b. brucei Lister 427. (XLSX) Preparation of slides & microscopy Mitochondria were stained using Mitotracker Red (Invitrogen) prior to fixation and mount- ing. To achieve this, cells (typically 1 mL at 5 x 105 cells/mL) were incubated for 5 minutes at 37˚C, 5% CO2, with a final concentration of 100 nM Mitotracker. Upon completion, cells were centrifuged for 5 minutes at 1,500 × g and washed twice in fresh medium before cells were fixed. Trypanosomes were grown to mid-log phase before control and treatment cultures were started at a density of 2 × 105 cells/mL. For each time-point, at least 3 mL culture was centri- fuged at 1,500 × g, washed twice with sterile 1× PBS, and finally re-suspended in 500 μL PBS. Samples were fixed by adding a final concentration of 2% formaldehyde, and incubated for 15 minutes at room temperature. Subsequent to a wash with PBS, cells were transferred onto a poly-L-lysine-coated slide, and left to air-dry in a safety cabinet. Dried slides were rehydrated and washed in PBS, and a counterstain consisting of 1× PBS with 3 μM 4,6-diamidino-2-phe- nylindole (DAPI) was applied to the slide, before mounting with a coverslip that was sealed with clear nail varnish. Slides were analysed with a Zeiss axioscope (Scope.A1, Zeiss). To ascertain whether compounds affected the T. b. brucei cell cycle, cells were prepared for microscopy analysis as described above. Cells were then counterstained with DAPI and classified according to the numbers of nuclei and kinetoplasts they had, as a direct correlation to phases of the cell cycle, as described in several publications [62, 63]. Cells in G1 phase have one nucleus and one kinetoplast (1N1K). Kinetoplast replication (S-phase) then initiates (1N2K) prior to nuclear division (2N2K). Finally, completion of the cell cycle leads to two cells in G1 phase. To analyse any potential changes in cell cycle, >300 cells were counted in multiple samples and the number of cells in different cell cycle stages, as well as those in 2N1K and MNMK (‘M’ defined as ‘multiple’ organelles) phase, were calculated as percentages of the total number of counted cells. 18 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Acknowledgments The authors thank Glasgow Polyomics for technical assistance with metabolomics experi- ments, and Wellcome Centre for Molecular Parasitology Imaging for assistance with microscopy. 19 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Metabolomic response to AN5568 treatment in T. brucei Conceptualization: Pieter C. Steketee, Isabel M. Vincent, Fiona Achcar, Federica Giordani, Darren J. Creek, Michael P. Barrett. Data curation: Pieter C. Steketee, Fiona Achcar, Dong-Hyun Kim. Formal analysis: Pieter C. Steketee, Fiona Achcar, Dong-Hyun Kim. Funding acquisition: Annette MacLeod, Michael P. Barrett. Funding acquisition: Annette MacLeod, Michael P. Barrett. Investigation: Pieter C. Steketee, Fiona Achcar, Federica Giordani, Kevin Rattigan. Methodology: Pieter C. Steketee, Isabel M. Vincent, Fiona Achcar, Federica Giordani, Dong- Hyun Kim, Darren J. Creek, Kevin Rattigan, Michael P. Barrett. Project administration: Pieter C. Steketee, Annette MacLeod, Michael P. Barrett. Resources: Yvonne Freund, Robert Jacobs, Annette MacLeod, Michael P. Barrett. Software: Dong-Hyun Kim, Darren J. Creek. Supervision: Annette MacLeod, Michael P. Barrett. Validation: Pieter C. Steketee, Annette MacLeod, Michael P. Barrett. Visualization: Pieter C. Steketee. Writing – original draft: Pieter C. Steketee, Isabel M. Vincent. Writing – review & editing: Pieter C. Steketee, Isabel M. Vincent, Yvonne Freund, Robert Jacobs, David Horn, Mark C. Field, Annette MacLeod, Michael P. Barrett. Metabolomic response to AN5568 treatment in T. brucei Antimicrobial agents and chemotherapy. 2013; 57(5):2401–4. https://doi.org/10.1128/AAC.02580-12 PMID: 23459482 Antimicrobial agents and chemotherapy. 2013; 57(5):2401–4. https://doi.org/10.1128/AAC.02580-12 PMID: 23459482 12. Hernandez V, Crepin T, Palencia A, Cusack S, Akama T, Baker SJ, et al. Discovery of a novel class of boron-based antibacterials with activity against gram-negative bacteria. Antimicrobial agents and che- motherapy. 2013; 57(3):1394–403. https://doi.org/10.1128/AAC.02058-12 PMID: 23295920 13. Zhang YK, Plattner JJ, Easom EE, Zhou Y, Akama T, Bu W, et al. Discovery of an orally bioavailable isoxazoline benzoxaborole (AN8030) as a long acting animal ectoparasiticide. Bioorganic & medicinal chemistry letters. 2015; 25(23):5589–93. 14. Akama T, Virtucio C, Dong C, Kimura R, Zhang YK, Nieman JA, et al. Structure-activity relationships of 6-(aminomethylphenoxy)-benzoxaborole derivatives as anti-inflammatory agent. Bioorganic & medici- nal chemistry letters. 2013; 23(6):1680–3. 15. Akama T, Dong C, Virtucio C, Sullivan D, Zhou Y, Zhang YK, et al. Linking phenotype to kinase: identifi- cation of a novel benzoxaborole hinge-binding motif for kinase inhibition and development of high- potency rho kinase inhibitors. The Journal of pharmacology and experimental therapeutics. 2013; 347 (3):615–25. https://doi.org/10.1124/jpet.113.207662 PMID: 24049062 16. Rock FL, Mao W, Yaremchuk A, Tukalo M, Crepin T, Zhou H, et al. An antifungal agent inhibits an ami- noacyl-tRNA synthetase by trapping tRNA in the editing site. Science. 2007; 316(5832):1759–61. https://doi.org/10.1126/science.1142189 PMID: 17588934 17. Palencia A, Liu RJ, Lukarska M, Gut J, Bougdour A, Touquet B, et al. Cryptosporidium and Toxoplasma Parasites Are Inhibited by a Benzoxaborole Targeting Leucyl-tRNA Synthetase. Antimicrobial agents and chemotherapy. 2016; 60(10):5817–27. https://doi.org/10.1128/AAC.00873-16 PMID: 27431220 18. Palencia A, Bougdour A, Brenier-Pinchart MP, Touquet B, Bertini RL, Sensi C, et al. Targeting Toxo- plasma gondii CPSF3 as a new approach to control toxoplasmosis. EMBO molecular medicine. 2017; 9 (3):385–94. https://doi.org/10.15252/emmm.201607370 PMID: 28148555 19. Sonoiki E, Ng CL, Lee MC, Guo D, Zhang YK, Zhou Y, et al. A potent antimalarial benzoxaborole targets a Plasmodium falciparum cleavage and polyadenylation specificity factor homologue. Nature communi- cations. 2017; 8:14574. https://doi.org/10.1038/ncomms14574 PMID: 28262680 20. Long T, Rojo-Arreola L, Shi D, El-Sakkary N, Jarnagin K, Rock F, et al. Phenotypic, chemical and func- tional characterization of cyclic nucleotide phosphodiesterase 4 (PDE4) as a potential anthelmintic drug target. PLoS neglected tropical diseases. 2017; 11(7):e0005680. https://doi.org/10.1371/journal.pntd. 0005680 PMID: 28704396 21. Jarnagin K, Chanda S, Coronado D, Ciaravino V, Zane LT, Guttman-Yassky E, et al. References 1. Lejon V, Bentivoglio M, Franco JR. Human African trypanosomiasis. Handbook of clinical neurology. 2013; 114:169–81. https://doi.org/10.1016/B978-0-444-53490-3.00011-X PMID: 23829907 2. Koffi M, De Meeus T, Bucheton B, Solano P, Camara M, Kaba D, et al. Population genetics of Trypano- soma brucei gambiense, the agent of sleeping sickness in Western Africa. Proceedings of the National Academy of Sciences of the United States of America. 2009; 106(1):209–14. https://doi.org/10.1073/ pnas.0811080106 PMID: 19106297 3. WHO. Global Health Observatory data repository: Human African Trypanosomiasis 2015 [cited 2016 11th January,]. Available from: http://apps.who.int/gho/data/node.main.A1635. 4. WHO. London Declaration on Neglected Tropical Diseases. Ending the neglect and reaching 2020 goals. 2012 [cited 2017 04/06]. Available from: http://unitingtocombatntds.org/resource/london- declaration. 5. Masocha W, Rottenberg ME, Kristensson K. Migration of African trypanosomes across the blood-brain barrier. Physiology & behavior. 2007; 92(1–2):110–4. 6. Pepin J, Milord F. The treatment of human African trypanosomiasis. Advances in parasitology. 1994; 33:1–47. PMID: 8122565 7. Barrett MP, Vincent IM, Burchmore RJ, Kazibwe AJ, Matovu E. Drug resistance in human African try- panosomiasis. Future microbiology. 2011; 6(9):1037–47. https://doi.org/10.2217/fmb.11.88 PMID: 21958143 8. Barrett MP, Croft SL. Management of trypanosomiasis and leishmaniasis. British medical bulletin. 2012; 104:175–96. https://doi.org/10.1093/bmb/lds031 PMID: 23137768 9. Mahalingam A, Geonnotti AR, Balzarini J, Kiser PF. Activity and safety of synthetic lectins based on benzoboroxole-functionalized polymers for inhibition of HIV entry. Molecular pharmaceutics. 2011; 8 (6):2465–75. https://doi.org/10.1021/mp2002957 PMID: 21879735 10. Markham A. Tavaborole: first global approval. Drugs. 2014; 74(13):1555–8. https://doi.org/10.1007/ s40265-014-0276-7 PMID: 25118637 11. Goldstein EJ, Citron DM, Tyrrell KL, Merriam CV. Comparative in vitro activities of GSK2251052, a novel boron-containing leucyl-tRNA synthetase inhibitor, against 916 anaerobic organisms. PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 20 / 24 Metabolomic response to AN5568 treatment in T. brucei 30. Trackman PC, Abeles RH. Methionine synthesis from 5’-S-Methylthioadenosine. Resolution of enzyme activities and identification of 1-phospho-5-S methylthioribulose. The Journal of biological chemistry. 1983; 258(11):6717–20. PMID: 6853500 31. Sauter M, Moffatt B, Saechao MC, Hell R, Wirtz M. Methionine salvage and S-adenosylmethionine: essential links between sulfur, ethylene and polyamine biosynthesis. The Biochemical journal. 2013; 451(2):145–54. https://doi.org/10.1042/BJ20121744 PMID: 23535167 32. Hasne MP, Barrett MP. Transport of methionine in Trypanosoma brucei brucei. Molecular and biochem- ical parasitology. 2000; 111(2):299–307. PMID: 11163438 33. Backlund PS Jr., Chang CP, Smith RA. Identification of 2-keto-4-methylthiobutyrate as an intermediate compound in methionine synthesis from 5’-methylthioadenosine. The Journal of biological chemistry. 1982; 257(8):4196–202. PMID: 7068632 34. Wang Y, Kavran JM, Chen Z, Karukurichi KR, Leahy DJ, Cole PA. Regulation of S-adenosylhomocys- teine hydrolase by lysine acetylation. The Journal of biological chemistry. 2014; 289(45):31361–72. https://doi.org/10.1074/jbc.M114.597153 PMID: 25248746 35. Devkota K, Lohse B, Liu Q, Wang MW, Staerk D, Berthelsen J, et al. Analogues of the Natural Product Sinefungin as Inhibitors of EHMT1 and EHMT2. ACS medicinal chemistry letters. 2014; 5(4):293–7. https://doi.org/10.1021/ml4002503 PMID: 24900829 36. Vedel M, Lawrence F, Robert-Gero M, Lederer E. The antifungal antibiotic sinefungin as a very active inhibitor of methyltransferases and of the transformation of chick embryo fibroblasts by Rous sarcoma virus. Biochemical and biophysical research communications. 1978; 85(1):371–6. PMID: 217377 37. Fivelman QL, Adagu IS, Warhurst DC. Modified fixed-ratio isobologram method for studying in vitro interactions between atovaquone and proguanil or dihydroartemisinin against drug-resistant strains of Plasmodium falciparum. Antimicrobial agents and chemotherapy. 2004; 48(11):4097–102. https://doi. org/10.1128/AAC.48.11.4097-4102.2004 PMID: 15504827 38. Creek DJ, Nijagal B, Kim DH, Rojas F, Matthews KR, Barrett MP. Metabolomics guides rational devel- opment of a simplified cell culture medium for drug screening against Trypanosoma brucei. Antimicro- bial agents and chemotherapy. 2013; 57(6):2768–79. https://doi.org/10.1128/AAC.00044-13 PMID: 23571546 39. Hoppel CL, Cox RA, Novak RF. N6-Trimethyl-lysine metabolism. 3-Hydroxy-N6-trimethyl-lysine and carnitine biosynthesis. The Biochemical journal. 1980; 188(2):509–19. PMID: 6772168 40. Gilbert RJ, Klein RA, Johnson P. Bromoacetyl-L-carnitine: biochemical and antitrypanosomal actions against Trypanosoma brucei brucei. Biochemical pharmacology. 1983; 32(22):3447–51. PMID: 6651867 41. Lamont GS, Tucker RS, Cross GA. Analysis of antigen switching rates in Trypanosoma brucei. Parasi- tology. 1986; 92 (Pt 2):355–67. 42. Glover L, Alsford S, Horn D. DNA break site at fragile subtelomeres determines probability and mecha- nism of antigenic variation in African trypanosomes. PLoS Pathog. 2013; 9(3):e1003260. https://doi. org/10.1371/journal.ppat.1003260 PMID: 23555264 43. Crisaborole Topi- cal Ointment, 2%: A Nonsteroidal, Topical, Anti-Inflammatory Phosphodiesterase 4 Inhibitor in Clinical Development for the Treatment of Atopic Dermatitis. Journal of drugs in dermatology: JDD. 2016; 15 (4):390–6. PMID: 27050693 22. Alterio V, Cadoni R, Esposito D, Vullo D, Fiore AD, Monti SM, et al. Benzoxaborole as a new chemotype for carbonic anhydrase inhibition. Chemical communications. 2016; 52(80):11983–6. https://doi.org/10. 1039/c6cc06399c PMID: 27722534 23. Nare B, Wring S, Bacchi C, Beaudet B, Bowling T, Brun R, et al. Discovery of novel orally bioavailable oxaborole 6-carboxamides that demonstrate cure in a murine model of late-stage central nervous sys- tem african trypanosomiasis. Antimicrobial agents and chemotherapy. 2010; 54(10):4379–88. https:// doi.org/10.1128/AAC.00498-10 PMID: 20660666 24. Jacobs RT, Nare B, Wring SA, Orr MD, Chen D, Sligar JM, et al. SCYX-7158, an orally-active benzoxa- borole for the treatment of stage 2 human African trypanosomiasis. PLoS neglected tropical diseases. 2011; 5(6):e1151. https://doi.org/10.1371/journal.pntd.0001151 PMID: 21738803 25. Jones DC, Foth BJ, Urbaniak MD, Patterson S, Ong HB, Berriman M, et al. Genomic and Proteomic Studies on the Mode of Action of Oxaboroles against the African Trypanosome. PLoS neglected tropical diseases. 2015; 9(12):e0004299. https://doi.org/10.1371/journal.pntd.0004299 PMID: 26684831 26. Vincent IM, Creek DJ, Burgess K, Woods DJ, Burchmore RJ, Barrett MP. Untargeted metabolomics reveals a lack of synergy between nifurtimox and eflornithine against Trypanosoma brucei. PLoS neglected tropical diseases. 2012; 6(5):e1618. https://doi.org/10.1371/journal.pntd.0001618 PMID: 22563508 27. Vincent IM, Ehmann DE, Mills SD, Perros M, Barrett MP. Untargeted Metabolomics To Ascertain Antibi- otic Modes of Action. Antimicrobial agents and chemotherapy. 2016; 60(4):2281–91. https://doi.org/10. 1128/AAC.02109-15 PMID: 26833150 28. Trochine A, Creek DJ, Faral-Tello P, Barrett MP, Robello C. Benznidazole biotransformation and multi- ple targets in Trypanosoma cruzi revealed by metabolomics. PLoS neglected tropical diseases. 2014; 8 (5):e2844. https://doi.org/10.1371/journal.pntd.0002844 PMID: 24853684 29. Marchitto KS, Ferro AJ. The metabolism of 5’-methylthioadenosine and 5-methylthioribose 1-phosphate in Saccharomyces cerevisiae. Journal of general microbiology. 1985; 131(9):2153–64. https://doi.org/ 10.1099/00221287-131-9-2153 PMID: 3906034 21 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Metabolomic response to AN5568 treatment in T. brucei 50. Jones P, Binns D, Chang HY, Fraser M, Li W, McAnulla C, et al. InterProScan 5: genome-scale protein function classification. Bioinformatics. 2014; 30(9):1236–40. https://doi.org/10.1093/bioinformatics/ btu031 PMID: 24451626 51. Letunic I, Doerks T, Bork P. SMART: recent updates, new developments and status in 2015. Nucleic acids research. 2015; 43(Database issue):D257–60. https://doi.org/10.1093/nar/gku949 PMID: 25300481 52. Schubert HL, Blumenthal RM, Cheng X. Many paths to methyltransfer: a chronicle of convergence. Trends in biochemical sciences. 2003; 28(6):329–35. https://doi.org/10.1016/S0968-0004(03)00090-2 PMID: 12826405 53. Qian C, Zhou MM. SET domain protein lysine methyltransferases: Structure, specificity and catalysis. Cellular and molecular life sciences: CMLS. 2006; 63(23):2755–63. https://doi.org/10.1007/s00018- 006-6274-5 PMID: 17013555 54. Morera L, Lubbert M, Jung M. Targeting histone methyltransferases and demethylases in clinical trials for cancer therapy. Clinical epigenetics. 2016; 8:57. https://doi.org/10.1186/s13148-016-0223-4 PMID: 27222667 55. Bauerle MR, Schwalm EL, Booker SJ. Mechanistic diversity of radical S-adenosylmethionine (SAM)- dependent methylation. The Journal of biological chemistry. 2015; 290(7):3995–4002. https://doi.org/ 10.1074/jbc.R114.607044 PMID: 25477520 56. Alsford S, Turner DJ, Obado SO, Sanchez-Flores A, Glover L, Berriman M, et al. High-throughput phe- notyping using parallel sequencing of RNA interference targets in the African trypanosome. Genome research. 2011; 21(6):915–24. https://doi.org/10.1101/gr.115089.110 PMID: 21363968 57. Aslett M, Aurrecoechea C, Berriman M, Brestelli J, Brunk BP, Carrington M, et al. TriTrypDB: a func- tional genomic resource for the Trypanosomatidae. Nucleic acids research. 2010; 38(Database issue): D457–62. https://doi.org/10.1093/nar/gkp851 PMID: 19843604 58. Brun R, Schonenberger. Cultivation and in vitro cloning or procyclic culture forms of Trypanosoma bru- cei in a semi-defined medium. Short communication. Acta tropica. 1979; 36(3):289–92. PMID: 43092 59. Berens RL, Brun R, Krassner SM. A simple monophasic medium for axenic culture of hemoflagellates. The Journal of parasitology. 1976; 62(3):360–5. PMID: 778371 60. Raz B, Iten M, Grether-Buhler Y, Kaminsky R, Brun R. The Alamar Blue assay to determine drug sensi- tivity of African trypanosomes (T.b. rhodesiense and T.b. gambiense) in vitro. Acta tropica. 1997; 68 (2):139–47. PMID: 9386789 61. Hall MJ, Middleton RF, Westmacott D. The fractional inhibitory concentration (FIC) index as a measure of synergy. The Journal of antimicrobial chemotherapy. 1983; 11(5):427–33. PMID: 6874629 62. Woodward R, Gull K. Timing of nuclear and kinetoplast DNA replication and early morphological events in the cell cycle of Trypanosoma brucei. Journal of cell science. 1990; 95 (Pt 1):49–57. 63. McKean PG. Coordination of cell cycle and cytokinesis in Trypanosoma brucei. Current opinion in microbiology. 2003; 6(6):600–7. Goldshmidt H, Matas D, Kabi A, Carmi S, Hope R, Michaeli S. Persistent ER stress induces the spliced leader RNA silencing pathway (SLS), leading to programmed cell death in Trypanosoma brucei. PLoS Pathog. 2010; 6(1):e1000731. https://doi.org/10.1371/journal.ppat.1000731 PMID: 20107599 44. Michaeli S. Spliced leader RNA silencing (SLS)—a programmed cell death pathway in Trypanosoma brucei that is induced upon ER stress. Parasit Vectors. 2012; 5:107. https://doi.org/10.1186/1756-3305- 5-107 PMID: 22650251 45. Field MC, Sergeenko T, Wang YN, Bohm S, Carrington M. Chaperone requirements for biosynthesis of the trypanosome variant surface glycoprotein. PloS one. 2010; 5(1):e8468. https://doi.org/10.1371/ journal.pone.0008468 PMID: 20052285 46. Parsons M, Worthey EA, Ward PN, Mottram JC. Comparative analysis of the kinomes of three patho- genic trypanosomatids: Leishmania major, Trypanosoma brucei and Trypanosoma cruzi. BMC geno- mics. 2005; 6:127. https://doi.org/10.1186/1471-2164-6-127 PMID: 16164760 47. Wlodarski T, Kutner J, Towpik J, Knizewski L, Rychlewski L, Kudlicki A, et al. Comprehensive structural and substrate specificity classification of the Saccharomyces cerevisiae methyltransferome. PloS one. 2011; 6(8):e23168. https://doi.org/10.1371/journal.pone.0023168 PMID: 21858014 48. Petrossian TC, Clarke SG. Uncovering the human methyltransferasome. Molecular & cellular proteo- mics: MCP. 2011; 10(1):M110 000976. 49. Finn RD, Bateman A, Clements J, Coggill P, Eberhardt RY, Eddy SR, et al. Pfam: the protein families database. Nucleic acids research. 2014; 42(Database issue):D222–30. https://doi.org/10.1093/nar/ gkt1223 PMID: 24288371 22 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 71. Okuda S, Yamada T, Hamajima M, Itoh M, Katayama T, Bork P, et al. KEGG Atlas mapping for global analysis of metabolic pathways. Nucleic acids research. 2008; 36(Web Server issue):W423–6. https:// doi.org/10.1093/nar/gkn282 PMID: 18477636 72. Xia J, Sinelnikov IV, Han B, Wishart DS. MetaboAnalyst 3.0—making metabolomics more meaningful. Nucleic acids research. 2015; 43(W1):W251–7. https://doi.org/10.1093/nar/gkv380 PMID: 25897128 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Metabolomic response to AN5568 treatment in T. brucei PMID: 14662356 64. Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, et al. Fiji: an open-source platform for biological-image analysis. Nature methods. 2012; 9(7):676–82. https://doi.org/10.1038/ nmeth.2019 PMID: 22743772 65. Team RC. R: A language and environment for statistical computing 2017 [cited 2017 04/06]. Available from: https://www.R-project.org/. 66. Chambers MC, Maclean B, Burke R, Amodei D, Ruderman DL, Neumann S, et al. A cross-platform toolkit for mass spectrometry and proteomics. Nature biotechnology. 2012; 30(10):918–20. https://doi. org/10.1038/nbt.2377 PMID: 23051804 67. Creek DJ, Jankevics A, Burgess KE, Breitling R, Barrett MP. IDEOM: an Excel interface for analysis of LC-MS-based metabolomics data. Bioinformatics. 2012; 28(7):1048–9. https://doi.org/10.1093/ bioinformatics/bts069 PMID: 22308147 68. Scheltema RA, Jankevics A, Jansen RC, Swertz MA, Breitling R. PeakML/mzMatch: a file format, Java library, R library, and tool-chain for mass spectrometry data analysis. Analytical chemistry. 2011; 83 (7):2786–93. https://doi.org/10.1021/ac2000994 PMID: 21401061 69. Chokkathukalam A, Jankevics A, Creek DJ, Achcar F, Barrett MP, Breitling R. mzMatch-ISO: an R tool for the annotation and relative quantification of isotope-labelled mass spectrometry data. Bioinformat- ics. 2013; 29(2):281–3. https://doi.org/10.1093/bioinformatics/bts674 PMID: 23162054 70. Caspi R, Billington R, Ferrer L, Foerster H, Fulcher CA, Keseler IM, et al. The MetaCyc database of met- abolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic acids research. 2016; 44(D1):D471–80. https://doi.org/10.1093/nar/gkv1164 PMID: 26527732 23 / 24 PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0006450 May 14, 2018 Metabolomic response to AN5568 treatment in T. brucei Metabolomic response to AN5568 treatment in T. brucei 24 / 24
https://openalex.org/W2909255723
https://rojournal.elpub.ru/jour/article/download/80/81
Russian
null
Functional Model of the Skull with Movable Articulations Designed for Training Practice on Cranial Tissues for Osteopathic Physicians
Rossijskij osteopatičeskij žurnal
2,017
cc-by
5,717
© Д. Е. Мохов, Ю. И. Коваль, А. В. Чащин, 2017 © Д. Е. Мохов, Ю. И. Коваль, А. В. Чащин, 2017 УДК 615.471.03.616-073.96 D. Mokhov 1, 2, Y. Koval 3, A. Chashchin 1 1 North-Western State Medical University n. a. I. I. Mechnikov, 41, Kirochnaya street, St. Petersburg, 191015, phone: +7 812 303-50-00, e-mail: rectorat@szgmu.ru 2 Saint Petersburg State University, Institute of Osteopathy, 7/9, Universitetskaya embankment, St. Petersburg, 199034, phone: +7 812 328-20-00, e-mail: spbu@spbu.ru 3 Clinic of Valentina Dudnik, 43, Svetlanovskaya avenue, St. Petersburg, 194223, phone: +7 921 784-67-36, e-mail: yurakovalspbgmu@mail.ru Abstract The article describes a new model of a skull with movable articulations designed for practical use. The model provides an imitation of bone mobility in the sutural region of the interosseous joints. It appears as a skull simulator, designed to develop the skills of palpation of cranial tissues. The model composition and characteristics refl ecting the possibilities of using are presented in the description. Keywords: model of the skull, osteopathy, еруsutures of interosseous joints, palpation of cranial tissues, imitators of mobility of bone simulators in the sutures, control of period, duty cycle and amplitude of displacement of bone simulators Д. Е. Мохов 1, 2, Ю. И. Коваль 3, А. В. Чащин 1 1 Северо-Западный государственный медицинский университет им. И. И. Мечникова, 191015, Санкт-Петербург, ул. Кирочная, д. 41, тел.: 8 812 303-50-00, e-mail: rectorat@szgmu.ru 2 Санкт-Петербургский государственный университет, Институт остеопатии, 199034, Санкт-Петербург, Университетская наб., д. 7/9, тел.: 8 812 328-20-00, e-mail: spbu@spbu.ru 3 «Клиника Валентины Дудник», 194223, Санкт-Петербург, Светлановский пр., д. 43, тел.: 8 921 784-67-36, e-mail: yurakovalspbgmu@mail.ru 1 Северо-Западный государственный медицинский университет им. И. И. Мечникова, 191015, Санкт-Петербург, ул. Кирочная, д. 41, тел.: 8 812 303-50-00, e-mail: rectorat@szgmu.ru 2 Санкт-Петербургский государственный университет, Институт остеопатии, 199034, Санкт-Петербург, Университетская наб., д. 7/9, тел.: 8 812 328-20-00, e-mail: spbu@spbu.ru 3 «Клиника Валентины Дудник», 194223, Санкт-Петербург, Светлановский пр., д. 43, тел.: 8 921 784-67-36, e-mail: yurakovalspbgmu@mail.ru Функциональная модель черепа с подвижно-суставным сочленением костей для обучения практической работе врачей-остеопатов на краниальных тканях Д. Е. Мохов 1, 2, Ю. И. Коваль 3, А. В. Чащин 1 Functional Model of the Skull with Movable Articulations Designed for Training Practice on Cranial Tissues for Osteopathic Physicians D. Mokhov 1, 2, Y. Koval 3, A. Chashchin 1 Реферат В статье описана новая для практического применения действующая модель черепа с подвижно-суставным сочленением костей. Модель обеспечивает имитацию подвижности костей в области швов межкостных соч- ленений. Она представляется как симулятор черепа для обучения навыкам пальпации краниальных тканей. Модель черепа с подвижно-суставным сочленением костей удобна для эксплуатации в учебных учреждениях, для научно-исследовательских работ, а также для диагностики и терапии заболеваний. Ключевые слова: модель черепа, остеопатия, швы межкостных сочленений, пальпация краниальных тканей, имитаторы подвижности симуляторов костей в швах, управление периодом, скважностью и амплитудой сме- щения симуляторов костей Положение в развитии моделей черепа Среди методов диагностического обследования организма и терапевтических воздействий в практике остеопатии широко используют техники, основанные на пальпации краниальных 20 Оригинальные статьи тканей. В частности, при пальпации анализируют состояние суставной подвижности костей черепа и проявление ритмически повторяемых смещений костей относительно друг друга. Применение приёмов пальпации в остеопатической медицине основано на известных фактах о подвижности суставов в сочленении костей черепа, которые в этих участках (швах) проявляются в виде рит- мически повторяемых смещений костей относительно друг друга. Используя при обследовании специальные приёмы пальпации определённых участков краниальных тканей, врач-остеопат на качественном уровне анализирует функциональное выполнение относительного смещения костей черепа. Цель этих обследований — выявление ситуаций, связанных с возможными огра- ничениями движений, определение и устранение таких причин. Так, в условно нормальном со- стоянии пациента в участках швов межкостных сочленений должны проявляться повторяемые и выраженные по амплитуде и в соответствии с краниосакральным ритмом обратимые смещения костей относительно друг друга. При ограничивающих нарушениях проявляется изменение харак- теристик смещения — амплитуды и частоты. тканей. В частности, при пальпации анализируют состояние суставной подвижности костей черепа и проявление ритмически повторяемых смещений костей относительно друг друга. Применение приёмов пальпации в остеопатической медицине основано на известных фактах о подвижности суставов в сочленении костей черепа, которые в этих участках (швах) проявляются в виде рит- мически повторяемых смещений костей относительно друг друга. Используя при обследовании специальные приёмы пальпации определённых участков краниальных тканей, врач-остеопат на качественном уровне анализирует функциональное выполнение относительного смещения костей черепа. Цель этих обследований — выявление ситуаций, связанных с возможными огра- ничениями движений, определение и устранение таких причин. Так, в условно нормальном со- стоянии пациента в участках швов межкостных сочленений должны проявляться повторяемые и выраженные по амплитуде и в соответствии с краниосакральным ритмом обратимые смещения костей относительно друг друга. При ограничивающих нарушениях проявляется изменение харак- теристик смещения — амплитуды и частоты. Механизм проявления в тканях краниосакральной системы ритмических движений хорошо из- вестен и имеет теоретическое объяснение. Например, в работе [4] их происхождение связывается с функционированием пяти компонентов: головного и спинного мозга, с движением цереброспи- нальной жидкости, мембраны реципрокного натяжения, костно-суставного механизма и кранио- сакральным взаимодействием. При этом движения связаны с соответствующими изменениями состояния мембраны реципрокного натяжения и с объемными изменениями наполнения сосу- дистой системы черепа. Положение в развитии моделей черепа Несмотря на то, что диапазон смещения костей черепа при движении не- значительный (для справки: максимальный размах движения костей черепа здорового человека в области швов, выявленный при исследованиях, не превышает 1–1,5 мм), они чрезвычайно значимы для поддержания в нормальном состоянии процессов в организме и, в конечном счете, состояния здоровья. Это связано с тем, что, как и в других суставных участках тела, в области швов межкостных сочленений имеется развитая система сосудов, соединительной ткани и мно- жественные нервные окончания. Отсутствие ритмически повторяемых смещений или их слабое проявление может свидетельствовать об ограничении движений и, соответственно, о возможных патологических изменениях в организме. При обследовании общепринято анализировать ха- рактер смещения костей с учётом отмеченных проявлений. Это позволяет, используя пальпацию краниальных тканей, вместе с возможностью на качественном уровне оценивать состояние су- ставного аппарата костей черепа, по этим косвенным данным анализировать состояние орга- низма в целом. Результат обследования определяют такие характеристики, как амплитуда, ритмич- ность проявления смещений и подвижность костей в швах межкостных сочленений. Возможности обучения врачей-остеопатов на симуляторах черепа В медицинских учебных заведениях для изучения строения черепной коробки в целом и отдельных её костей используют разные наглядные пособия: рисунки соответствующих костей и участков их со- единения, манекены черепа и симуляторы отдельных костей, анатомические препараты. Например, в качестве учебных пособий для специализации в области остеопатической ме- дицины немецкая фирма «Erler zimmer» производит разборные модели черепа. Конструкция симу- лятора черепа представляется в собранном виде и выполнена на основе китайского патента [2]. В ней используют симуляторы соответствующих костей. Сборку общей конструкции черепной ко- робки, составленной из симуляторов костей черепа, производят с использованием встроенных магнитов. За счёт силы притяжения магнитов образуется их соединение в сборной конструкции симулятора черепной коробки. Производимая фирмой «Erler zimmer» модель представляет собой симулятор черепа среднего европейского взрослого человека. В конструкции симуляторов костей имеются анатомически правильные срезы, позволяющие образовывать оптимальные соединения межкостных сочленений (швы). Они выполнены с учетом срезов и пивотов (стержневых точек 21 Д. Е. Мохов, Ю. И. Коваль, А. В. Чащин швов). При этом основное достоинство модели — простота и наглядность сборки и разборки симу- лятора черепа. Кроме того, каждая из костей (групп костей) выполнена в своей цветовой гамме. швов). При этом основное достоинство модели — простота и наглядность сборки и разборки симу- лятора черепа. Кроме того, каждая из костей (групп костей) выполнена в своей цветовой гамме. Однако эта конструкция модели черепа является статичной и не позволяет на ней симулировать функциональную костно-суставную подвижность. В результате, не моделируется проявление ритми- чески повторяемых смещений костей относительно друг друга. Соответственно, смещение костей не визуализируется. На собранной модели не наблюдается, а при пальпации в области швов меж- костных сочленений не ощущается смещение костей в участках их сочленения. По этой причине при обучении и практической подготовке врачей-остеопатов невозможно проводить тренирующие упражнения с пальпациями и анализировать при этом ритмически повторяющееся смещение костей в участках сочленения. На практике же врачу-остеопату важно приобрести навыки пальпации на дей- ствующей модели с учётом динамического взаимодействия составляющих её тканей и подвижного состояния суставного сочленения костей. По причине статичности также невозможно в научно-ис- следовательской работе изучать механизм проявления костно-суставной подвижности черепа. В работе [1] даётся решение вопроса создания модели, в которой образуется движение костей черепа в системе межкостных сочленений на уровне швов. При этом модель предназначена для тренировок остеопатическим техникам пальпации краниальных тканей в участках швов меж- костных сочленений. Тренировки на модели важны для получения у тренирующегося ощущений, возникающих в результате подвижности и смещения симуляторов костей в швах межкостных сочле- нений. Возможности обучения врачей-остеопатов на симуляторах черепа По ощущениям, получаемым при пальпации краниальных тканей, врач-остеопат анализирует характер изменения амплитуды, силу и ритм повторяющихся смещений костей относительно друг друга. Это имеет значение для исследования состояния подвижности суставного аппарата костей черепа и для приобретения врачами-остеопатами навыков работы. Для симуляции смещения симу- ляторов костей в швах в модели используют имитаторы подвижности, исполненные в виде активно действующих механизмов, передающих движение симуляторам костей. В качестве исполнительных механизмов имитаторов подвижности в модели используют электрически управляемые пьезодви- гатели, механически связанные с участками имитации швов межкостных сочленений. Однако при использовании модели такой конструкции не симулируется проявление механи- ческих воздействий на кости, производимых со стороны краниальных тканей, расположенных в пространстве внутри черепной коробки, или создаваемых за счёт пальпирующих воздействий. Фактически же, к источникам двигательной активности относятся именно эти факторы, и, по сути, они и приводят к смещению костей в швах межкостных сочленений. В организме к таким тканям относится, прежде всего, мембрана реципрокного натяжения (dura mater). При этом её двига- тельная активность передается в виде направленно силового действия одновременно на все кости черепа, что в модели [1] также не учитывается. Отмеченные особенности показывают, что модель не позволяет моделировать состояния, вызванные возможными патологическими изменениями в краниальных тканях. Примерами таких нарушений могут явиться случаи, когда проявляются ограничения движению тканей, причина которых связана с изменением характера смещений костей в швах, например с ограничением смещений, или полным отсутствием, или вследствие патологии в тканях, расположенных в пространстве внутри черепной коробки. Кроме того, несмотря на то, что в участках швов межкостных сочленений с помощью модели [1] и симулируется смещение костей черепа, применение для этого активно действующих электроме- ханизмов в качестве имитаторов подвижности неадекватно по отношению к главной причине про- явления двигательной активности и циклически повторяемых смещений костей. Физиологическая причина проявления ритмически повторяемых смещений костей относительно друг друга в швах межкостных сочленений не связана со структурами, сходными с активно дей- ствующими электромеханизмами и отвечающими за производимые тканями движения, в част- ности со структурами, подобными пьезодвигателям. Поэтому в швах межкостных сочленений на модели черепа только обеспечивается создание подвижного состояния, а это является лишь прибли- 22 Оригинальные статьи жением к действительному положению. На самом же деле, на смещение костей черепа основное действие оказывает движение краниальных тканей, расположенных в полости черепной коробки. К ним, в частности, относятся двигательная активность твёрдой мозговой оболочки (или мембраны реципрокного натяжения, или dura mater) на уровне II, III и IV желудочков и движение тканей го- ловного мозга. Возможности обучения врачей-остеопатов на симуляторах черепа На смещение костей также влияет уровень заполнения соответствующих структур тканей спинномозговой жидкостью и, кроме того, объёмные изменения в наполнении кровеносных сосудов артериальной и венозной кровью. При этом результирующее действие проявляется в швах межкостных сочленений в виде подвижного состояния и смещения костей черепа. Кроме того, для обеспечения подвижности суставного сочленения симуляторов костей в швах межкостных сочле- нений, в патенте [1] не учитывается, что существенное влияние на характер их смещения в швах обусловлено особенностью структуры пивотов. Механизм действия пивотов приводит к особому, поворотному характеру движения соседних костей относительно друг друга. Это связано с особым расположением соседних костей в швах межкостных сочленений. К примеру, в венечном, лямб- довидном, затылочно-височном, клиновидно-височном швах пространственная ориентация костей относительно друг друга меняется. Так, расположение костей при рассмотрении с одной стороны на соответствующий пивот отмечается следующее: одна из костей расположена поверх соседней кости, а в продолжении сочленения этих костей — наоборот, она расположена снизу. Модель [1] также не позволяет выполнять методики пальпации краниальных тканей, располо- женных в объёме пространства в области черепной коробки, а это важный аспект практической работы врачей-остеопатов с пациентами. К примеру, пальпацию в этой зоне производят не только с ди- агностической, но и терапевтической целью. Поэтому для более качественной тренировки на модели черепа требуется учитывать действие мембраны реципрокного натяжения на смещение костей, так как состояние её натяжения и двигательная активность механически передаются и влияют одновре- менно на все кости черепа. Это влияние проявляется в виде взаимного смещения костей в разных швах межкостных сочленений. Внесение возможности пальпации тканей, расположенных в объёме пространства внутри симулятора черепной коробки, для тренировочной работы на модели черепа рас- ширило бы функциональные возможности модели. Следует учитывать также, что при контакте с телом пациента врач-остеопат собирает и анализирует информацию о возможных ограничениях, функцио- нально препятствующих выполнению циклически повторяемых смещений костей черепа в участках швов межкостных сочленений. Косвенно он также анализирует состояние внутричерепных структур (например таких, как серп мозговой, тенториум мозжечка, серп мозжечка, III и IV желудочки). В этом анализе, как косвенные, используют характеристики, определяющие смещение и подвижность костей в швах межкостных сочленений, — амплитуду, силу и ритм производимых смещений костей в швах. Таким образом, без учёта особенностей сочленения соседних костей черепа друг с другом и их взаимодействия с краниальными тканями, расположенными внутри черепной коробки, на модели черепа сложно организовать управляемые тренировки навыкам пальпации или научно- исследовательскую работу, направленную на изучение проявлений механизма костно-суставной подвижности сочленений. Возможности обучения врачей-остеопатов на симуляторах черепа Поэтому для учебно-практической подготовки врача-остеопата и иссле- довательской работы важно использовать модель черепа, в которой учитываются взаимодействие и состояние основных составляющих, отвечающих за смещение костей в швах. К числу таких составляющих относятся объемные изменения жидкостного наполнения внутрисосудистого про- странства краниальных тканей, механическое взаимодействие костей с мембраной реципрокного натяжения и механическое взаимодействие соседних костей на уровне швов межкостных сочле- нений, где при диагностике важно выявлять причины возможных ограничений движения. Цель и решение задачи конструирования модели черепа Целью построения модели черепа в настоящей работе является расширение его функциональных возможностей. В первую очередь, это относится к созданию возможности симулировать смещение 23 Д. Е. Мохов, Ю. И. Коваль, А. В. Чащин соседних симуляторов костей в участках на уровне швов межкостных сочленений, а также к симу- ляции их механического взаимодействия со структурами тканей, расположенными внутри полости симулятора черепной коробки, например с мембраной реципрокного натяжения, механически приво- дящей в движение симуляторы костей, и к их смещению в швах. Так реализуется возможность исполь- зовать симулятор черепа при тренировках пальпации врачом-остеопатом. Другая цель расширения функциональных возможностей — это создание удобной настройки для осуществления условий, симу- лирующих ограничение подвижности в швах межкостных сочленений и взаимодействие с мембраной реципрокного натяжения. Ещё одна цель — обеспечение возможности пальпации структур тканей, расположенных во внутричерепной полости и механически действующих на смещение костей черепа в участках швов межкостных сочленений. И наконец, расширение функциональных возможностей модели нацелено на создание возможности проведения научных исследований, позволяющих анали- зировать проявление смещений в разных швах межкостных сочленений, связанных с ограничением подвижности в них и с изменением условий смещения симуляторов костей в швах. Для этого в устройство модели черепа были внесены составляющие элементы, обеспечи- вающие механическое действие на симуляторы костей со стороны тканей, симулирующих за- полнение объёма пространства симулятора черепной коробки. Они предназначены, чтобы ока- зывать влияние на смещение симуляторов костей в швах. При этом было учтено, что в сочленении определённых соседних костей имеются пивоты, а именно изменяется порядок наложения одной кости на другую. На одном участке сочленения в швах одна из костей покрывает другую, а за этим участком, — наоборот, другая покрывает первую. Кроме того, в модель черепа дополнительно внесены устройства, позволяющие симулировать ограничивающее (препятствующее, или блоки- рующее) действие на смещение костей в швах. Была также предусмотрена адекватно доступная возможность пальпации структур симуляторов краниальных тканей, расположенных в объёме про- странства симулятора черепной коробки. Целью пальпации тканей, расположенных в объеме пространства симулятора внутри черепной коробки, при таком построении модели является проведение врачом-остеопатом практических тренировок именно в этой области, с использованием при этом качественных критериев и оценки изменений частоты и амплитуды циклически повторяемых движений и сил действия, переда- ваемых структурами тканей. Конструкция модели черепа с подвижно-суставным сочленением костей На рис. 1 представлена схема модели черепа с подвижно-суставным сочленением костей, ис- пользованная при решении поставленной задачи. Схема составлена из симуляторов костей, об- разующих симулятор черепной коробки со швами межкостных сочленений. В ней имеется блок Блок управления, регистрации, обработки и представления информации Симулятор черепной коробки Блок симуляторов костей черепа Швы межкостных сочленений Блок имитатора подвижности Блок преобразования электрических сигналов Рис. 1. Схема модели черепа с подвижно-суставным сочленением костей Блок управления, регистрации, обработки и представления информации Швы межкостных сочленений Блок симуляторов костей черепа Блок преобразования электрических сигналов Рис. 1. Схема модели черепа с подвижно-суставным сочленением костей Рис. 1. Схема модели черепа с подвижно-суставным сочленением костей 24 Оригинальные статьи имитатора подвижности, связанный через преобразователь электрических сигналов с блоком управления, регистрации, обработки и представления информации. имитатора подвижности, связанный через преобразователь электрических сигналов с блоком управления, регистрации, обработки и представления информации. Блок имитатора подвижности состоит из пневмоблока, соединённого с расположенной в объеме пространства симулятора черепной коробки пневмокамерой. Пневмокамера механически, по- средством деталей крепления из состава связующих элементов имитатора межтканевых соеди- нений, связана с симуляторами костей. В такой конструкции модели черепа симулятор черепной коробки составлен из номенклатуры симуляторов костей, которые, соответственно, образуют швы межкостных сочленений и предна- значены для тренировки методическим приёмам пальпации или для научных исследований фе- номена суставной подвижности костей черепа. При этом могут быть образованы разные конфигу- рации симуляторов черепной коробки. Например, включение в состав мозговой части симулятора черепной коробки симуляторов двух теменных, двух височных костей, одной лобной кости, одной затылочной и одной клино- видной костей в участках их сочленения образует, соответственно, венечный, лямбдовидный, сагиттальный, два чешуйчатых, два теменно-сосцевидных, два затылочно-височных, два клино- видно-теменных, два клиновидно-лобных и два клиновидно-височных шва и сфенобазилярный синхондроз. Или другой пример: с включением симуляторов костей лицевого черепа — симуля- торов решетчатой кости, двух симуляторов костей верхней челюсти, двух симуляторов скуловых костей, в сочленении образующих, соответственно, клиновидно-решетчатые, лобно-решет- чатые, решетчато-верхнечелюстные, лобно-верхнечелюстные, скуловерхнечелюстные, сре- динный нёбный, клиновидно-скуловые, лобно-скуловые и скуловерхнечелюстные швы. В общей сборке эти симуляторы костей и швы образуют симулятор черепной коробки, предназначенный для тренировок пальпации в участках названных швов межкостных сочленений или для экс- периментальных исследований. Конструкция модели черепа с подвижно-суставным сочленением костей При выборе симуляторов костей, необходимых в построении конструкции симулятора черепной коробки, может использоваться, например, комплект симуля- торов из числа производимых немецкой фирмой «Erler zimmer»: левая и правая теменная кость; затылочная кость; височные кости; клиновидная кость; лобная кость; решетчатая кость; сошник; левая и правая небная кость; левая и правая нижние носовые раковины; левая и правая верхняя челюсть с зубами; левая и правая слезная кость; носовая кость; левая и правая ску- ловая кость; нижняя челюсть с зубами. Важной особенностью симуляторов костей фирмы «Erler zimmer» является наличие в них анато- мически правильных срезов и пивотов. В собранной конструкции симулятора черепной коробки это имеет принципиальное значение с точки зрения характеристик, определяющих направление смещений симуляторов костей в образовавшихся швах межкостных сочленений. Именно в соот- ветствии с исполнением срезов и пивотов в модели черепа определяется направление поворотно- осевого смещения и амплитуда смещения костей в швах. Блоком имитатора подвижности создаются условия, при которых происходит смещение симу- ляторов костей в швах межкостных сочленений. В блок имитатора подвижности входят имитатор межтканевых соединений и связей, пневмоблок и пневмокамера с упруго растяжимой стенкой. Имитатор межтканевых соединений и связей обеспечивает образование соединения друг с другом симуляторов костей черепа и создание при этом между ними механической связи и си- лового взаимодействия, а также создание взаимодействия симуляторов костей с краниальными тканями, расположенными в объеме пространства симулятора черепной коробки. Детали ими- татора межтканевых соединений и связей используют при сборке симулятора черепа для её укре- пления, а также для обеспечения моделью черепа функциональной подвижности в суставах во время тренировок пальпации. Функционально подвижное состояние составляющих модели обе- спечивается, в частности, именно за счёт деталей крепления имитатора межтканевых соединений и связей. К числу таких деталей относятся крепежные детали и материал, придающие участкам 25 Д. Е. Мохов, Ю. И. Коваль, А. В. Чащин межкостных сочленений имитацию свойства суставной подвижности или ограничивающие сме- щение соседних симуляторов костей в швах межкостных сочленений. межкостных сочленений имитацию свойства суставной подвижности или ограничивающие сме- щение соседних симуляторов костей в швах межкостных сочленений. В процессе сборки симулятора черепной коробки на суставные поверхности участков соч- ленения соседних симуляторов костей наносится упруго-эластичный материал, герметик типа MAKROFLEX AX104, с модулем упругости при 100 % удлинении = 0,35МРа (ISO 8339), или другой подобный материал. Назначение герметика в симуляторе черепной коробки состоит, с одной стороны, в образовании швов межкостных сочленений, механически объединяющих между собой симуляторы костей. С другой стороны, упруго-эластичные свойства герметика создают возмож- ность выполнения упругих возвратно-поступательных смещений симуляторов костей относительно друг друга. Конструкция модели черепа с подвижно-суставным сочленением костей После сборки герметик сохраняет устойчивую форму и свои упругоэластичные свойства, обеспечивая смещение симуляторов костей в суставах межкостных сочленений. Среди других деталей имитатора межтканевых соединений и связей используются неэла- стичные, нерастяжимые нити из лески марки «Shimano» диаметром 0,45 мм. Они образуют меха- ническое соединение, посредством которого передаётся силовое действие на симуляторы костей и происходит их взаимодействие. Это приводит к взаимному смещению симуляторов костей в швах. Кроме того, нити обеспечивают симуляцию механической связи симуляторов костей черепа с имитаторами краниальных тканей, расположенных в объёме пространства симулятора черепной коробки. Нити соединяют друг с другом симуляторы теменных костей, симуляторы лобной и теменной костей, симуляторы височных и затылочной костей. Они закрепляются на симуляторах костей во внутреннем объеме пространства симулятора черепной коробки. Образующиеся между симуляторами костей механические связи обеспечивают передачу силового действия одних симу- ляторов костей на другие. В результате, происходит их смещение в швах межкостных сочленений. При этом соответствующие симуляторы костей приводятся в движение за счёт натяжения нитей и за счёт движения симуляторов краниальных тканей, расположенных в объеме пространства си- мулятора черепной коробки. На рис. 2 схематично представлен симулятор черепной коробки с отметками симуляторов ос- новных костей и точек прохождения связующих нитей крепления межкостных сочленений. Рис 2 Симулятор черепной коробки с отметками симуляторов основных костей Рис. 2. Симулятор черепной коробки с отметками симуляторов основных костей и точек прохождения связующих нитей крепления межкостных сочленений (вид сбоку) Рис. 2. Симулятор черепной коробки с отметками симуляторов основных костей и точек прохождения связующих нитей крепления межкостных сочленений (вид сбоку) Рис. 2. Симулятор черепной коробки с отметками симуляторов основных костей и точек прохождения связующих нитей крепления межкостных сочленений (вид сбоку) 26 Оригинальные статьи Имитатор межтканевых соединений и связей дополнительно включает имитатор ограничения подвижности и смещения симуляторов костей в швах. Посредством него симулизуется огра- ничение подвижности костей в швах межкостных сочленений. Имитатор ограничения подвиж- ности и смещения располагается в участке соответствующего шва межкостного сочленения, венечного, лямбдовидного, сагиттального, чешуйчатого, теменно-сосцевидного, затылочно-ви- сочного, клиновидно-теменного, клиновидно-лобного, клиновидно-височного шва или сфеноба- зилярного синхондроза. Имитатор ограничения подвижности и смещения костей в швах устанав- ливается изнутри имитатора черепной коробки в виде скрепляющей шов склейки, например при помощи медицинского пластыря. Собранная с использованием имитатора ограничения подвиж- ности и смещения костей конструкция симулятора черепной коробки позволяет симулировать патологии, вызванные ограничением в каком-либо из швов подвижности и смещения костей, и при пальпации анализировать при этом относительное смещение между симуляторами костей в других швах межкостных сочленений. Конструкция модели черепа с подвижно-суставным сочленением костей Вариант же с использованием микропроцессорного кон- троллера предпочтителен для индивидуальных занятий и тренировок врачей-остеопатов. для исследовательских целей феномена суставной подвижности краниальных тканей и отработки методик их практического применения. Вариант же с использованием микропроцессорного кон- троллера предпочтителен для индивидуальных занятий и тренировок врачей-остеопатов. Блок управления, регистрации, обработки и представления информации обеспечивает режим автоматического управления функционированием пневмоблока, при котором давление в пневмо- камере создаётся полностью в автоматическом режиме. Он формирует управляющие сигналы и, в частности, сигналы включения и выключения питания микрокомпрессора и пневмореле, обе- спечивая задание в соответствии с протоколом тренировки закона изменения давления в пневмо- камере. В этом режиме блок управления, регистрации, обработки и представления информации, например персональный компьютер, используется для регистрации, запоминания и отображения на экране монитора изменений сигнала давления в пневмокамере. Блок управления, реги- страции, обработки и представления информации может быть выполнен с возможностью пред- ставления визуализированных данных, пересчитанных из данных о сигналах, полученных от пре- образователя давления. Блок управления, регистрации, обработки и представления информации также включает пульт дистанционного управления. Работа с устройством производится в циклах повышения и последующего снижения давления в пневмокамере. Соответственно, меняется натяжение стенки пневмокамеры, приводящее к из- менению натяжения неупругих связующих нитей крепления имитатора межтканевых соединений и связей. Как следствие, во время тренировочных пальпаций это приводит к смещению симу- ляторов костей в швах межкостных сочленений и проявлению осевого поворотного смещения вследствие использования в конструкции симуляторов костей структуры пивотов. Собранная из симуляторов костей предлагаемая модель черепа с подвижно-суставным соч- ленением костей применялась по назначению, а именно в качестве действующего пособия при обучении методики пальпации краниальных тканей врачей-остеопатов для получения у них ощущений подвижности и смещения симуляторов костей в швах межкостных сочленений и при- обретения опыта при анализе результатов пальпирующих обследований. Для научных исследо- ваний также анализировались движения краниальных тканей при симуляции препятствующего действия подвижности и смещения в одном из швов и его влияние на смещение симуляторов костей в других швах межкостных сочленений. Ниже приведены примеры применения дей- ствующей модели черепа. Пример 1. Применение модели черепа для моделирования подвижности костей в швах меж- костных сочленений и получения при этом при пальпации на симуляторе черепной коробки ощу- щений смещения соседних симуляторов костей, и в частности в соответствии со строением соч- ленений в виде пивотов. Конструкция модели черепа с подвижно-суставным сочленением костей Таким образом, конструкция симулятора черепа снабжена передаточным механизмом взаи- модействия, производимого посредством механической связи между симуляторами костей и их связи с симуляторами тканей, расположенных в объёме пространства симулятора черепной ко- робки. При этом крепёжные детали и материал имитатора подвижности представляются как со- ставляющие имитатора межтканевых соединений в объёме пространства симулятора черепной коробки. В целом же блок имитатора подвижности обеспечивает функциональную подвижность си- муляторов костей в участках швов межкостных сочленений, а имитатор ограничения подвижности и смещения симуляторов костей в швах обеспечивает имитацию нарушения при исполнении ме- ханизма суставной подвижности и смещения относительно друг друга симуляторов костей. Пневмокамера, входящая в блок имитатора подвижности, предназначена при тренировках для создания и передачи посредством её упруго растяжимой стенки силового поля действия одновре- менно на все структуры тканей, расположенных в объеме пространства симулятора черепной ко- робки, и, соответственно, на все симуляторы костей. Силовое действие на кости проявляется во вза- имном смещении симуляторов костей в участках швов межкостных сочленений. Оно образуется за счёт давления воздуха, действующего на упругорастяжимую стенку пневмокамеры, и за счёт изме- нения заполняемого в ней объёма воздуха. Создаваемая давлением воздуха в пневмокамере сила, действующая на её стенку, передаётся в объеме пространства симулятора черепной коробки на систему нитей имитатора межтканевых соединений и связей межкраниальных тканей, укреплённых на симуляторах костей. Размер пневмокамеры выбирается с учётом размеров симуляторов костей и образуемого симулятора черепной коробки. Посредством упругорастяжимой стенки пневмо- камеры давление от неё передаётся на систему симуляторов костей и краниальных тканей, распо- ложенных в полости симулятора черепной коробки. Стенкой превмокамеры также воспринимаются внешние механические воздействия, вызванные движением симуляторов костей. Пневмоблок в составе имитатора подвижности производит циклы создания изменений дав- ления воздуха в пневмокамере. Это осуществляется при наполнении от пневмоблока воздухом воздушной полости пневмокамеры и нагнетания в ней избыточного давления, по уровню и про- должительности времени в пределах, задаваемых устройством управления, регистрации, обра- ботки и представления информации. При этом пневмоблок является источником избыточного дав- ления, и он функционирует автоматически по командам от блока управления. В качестве блока управления, регистрации, обработки и представления информации могут ис- пользоваться различные варианты. К примеру, могут применяться устройства, построенные на основе персонального компьютера, или решения с использованием микропроцессорного кон- троллера. Применение персонального компьютера, в частности, позволяет преподавателю, сле- дящему за работой обучающихся врачей-остеопатов, оперативно менять программы тренировки и отслеживать работу тренирующихся. Компьютеризированный вариант также предпочтителен 27 Д. Е. Мохов, Ю. И. Коваль, А. В. Чащин для исследовательских целей феномена суставной подвижности краниальных тканей и отработки методик их практического применения. Конструкция модели черепа с подвижно-суставным сочленением костей Исходно перед включением в работу электропневматических устройств предлагаемой модели черепа учебным планом были определены для тренировочной пальпации симуляторы двух теменных костей, двух височных костей, одной лобной кости, соединённой с ко- стями лицевого черепа, одной затылочной, одной клиновидной костей, а также венечный шов, лямбдовидный, сагиттальный швы, два чешуйчатых шва, два теменно-сосцевидных шва, два затылочно-височных шва, два клиновидно-теменных шва, два клиновидно-лобных шва, два кли- новидно-височных шва и сфенобазилярный синхондроз. Для этого симулятор черепной коробки комплектовался из блока симуляторов костей соответствующими основными костями — двумя теменными, двумя височными костями, одной лобной костью, соединённой с костями лицевого черепа, одной затылочной и одной клиновидной костями. В конструкции строения симуляторов костей имелись предусмотренные для межкостных сочленений соответствующие пивоты. Была поставлена задача при разных уровнях изменения давления в пневмокамере, зада- ваемых в пределах 14–75 мм рт. ст., пальпировать симуляторы венечного, лямбдовидного, сагит- тального, двух чешуйчатых, двух теменно-сосцевидных, двух затылочно-височных, двух клиновидно- теменных, двух клиновидно-лобных, двух клиновидно-височных швов межкостных сочленений 28 Оригинальные статьи и симулятор сфенобазилярного синхондроза. При этом необходимо было на качественном уровне, по ощущениям анализировать изменение амплитуды и частоты повторения смещений относи- тельно друг друга соседних симуляторов костей. и симулятор сфенобазилярного синхондроза. При этом необходимо было на качественном уровне, по ощущениям анализировать изменение амплитуды и частоты повторения смещений относи- тельно друг друга соседних симуляторов костей. В исходном состоянии, до включения питающего напряжения и подачи сигналов управления от блока управления, давление воздуха в пневмокамере равно атмосферному давлению. В этом состоянии остаётся пока не задействованным механизм натяжения связующих нитей крепления, входящих в состав имитатора межтканевых соединений и связей и образующих механическую связь симуляторов костей со стенкой пневмокамеры. В венечном, лямбдовидном, сагиттальном, двух чешуйчатых, двух теменно-сосцевидных, двух затылочно-височных, двух клиновидно-те- менных, двух клиновидно-лобных, двух клиновидно-височных швах и сфенобазилярном синхон- дрозе соседних симуляторов двух теменных, двух височных костей и одной лобной кости, соеди- нённой с костями лицевого черепа, одной затылочной, одной клиновидной костями, смещений костей в швах не происходит. Соответственно, при пальпации этих участков не ощущается сме- щений относительно друг друга симуляторов костей. Согласно плану тренирующего занятия, на микропроцессорном контроллере, используемом в качестве блока управления, устанавливали нижний и верхний пределы диапазона изменения давления в пневмокамере. Также были уста- новлены временны′ е параметры — скорость повышения и понижения давления в пневмокамере и продолжительность времени тренировки. В частности, задавали диапазоны изменения давления в пределах 14–75 мм рт. ст., скорость повышения в пневмокамере давления от 8 до 75 мм рт. ст. за 15 с, скорость понижения давления от 75 до 8 мм рт. Конструкция модели черепа с подвижно-суставным сочленением костей ст. за 15 с и продолжительность времени тренировки, включающей один цикл повышения-понижения давления с минимальной частотой один раз в 30 с. Начало тренировки отсчитывали с момента подачи от блока управления на блок имитатора подвижности команды включения. При этом автоматически включался пневмоблок, пневмо- камера наполнялась воздухом, в ней нагнетался воздух выше атмосферного давления. По мере повышения давления в пневмокамере, её наполнение воздухом возрастало, увеличивались габа- ритные размеры пневмокамеры, её стенка приобретала упругость, натягивались связующие нити крепления имитатора, входящие в состав межтканевых соединений и связей, образовывалось неупругое механическое взаимодействие связующих нитей крепления со стенкой пневмокамеры. Абсолютное значение давления в пневмокамере отображалось на цифровом индикаторе блока управления. В момент достижения заданного верхнего предела давления 75 мм рт. ст. автомати- чески выключался пневмоблок. Из пневмокамеры стравливался воздух и снижалось давление, что наблюдалось на цифровых индикаторах блока. В момент достижения заданного нижнего предела давления 8 мм рт. ст. снова включался пневмоблок. Вновь происходило наполнение воздухом пневмокамеры и повышение в ней избыточного давления. Таким же образом происходили после- дующие циклы повышения и снижения давления в пневмокамере, вплоть до момента достижения заданного времени окончания тренировки. По соответствующей команде завершения тренировки выключался пневмоблок, пневмосистема приходила в исходное состояние. В циклах повышения с последующим понижением давления в пневмокамере во время тренировочных пальпаций это приводило к смещению симуляторов костей в швах межкостных сочленений. Врачи-остеопаты при пальпации отмечали ощущаемое смещение симуляторов костей в швах. Визуально также от- мечались соответствующие изменения в венечном, лямбдовидном, сагиттальном швах, в двух чешуйчатых, двух теменно-сосцевидных, двух затылочно-височных, двух клиновидно-теменных, двух клиновидно-лобных, двух клиновидно-височных швах и сфенобазилярном синхондрозе. При установлении других параметров изменения давления в пневмокамере, выбираемых из предус- мотренного диапазона в пределах 8–75 мм рт. ст. за 15 с, и скорости понижения давления от 75 до 8 мм рт. ст. за 15 с при тренировках также подтверждалась возможность приобретения навыка ощущения изменений. 29 Д. Е. Мохов, Ю. И. Коваль, А. В. Чащин Пример 2. Моделирование изменений физиологической подвижности симуляторов костей при ограничении подвижности в подвижно-суставном сочленении одного из швов. Имитатор ограни- чения движения в швах выполнен в виде шовной склейки изнутри черепной коробки упругоэла- стичным герметиком или клеем, например в участке пивота левого затылочно-височного шва. Так как ограничение в одном из швов оказывает влияние на смещение симуляторов костей во всех швах симулятора черепной коробки, то тренирующемуся предлагалось на основе ощущения этих изменений при смещении симуляторов костей выявить имитируемый таким образом патоло- гичный участок. Заключение Примеры тренировок врачей-остеопатов с использованием модели черепа с подвижно-су- ставным сочленением костей показывают их эффективность. Роль преподавателя при тренировке пальпации сводится к указанию выбора параметров, воспроизводимых при тренировках: частоты повторения, амплитуды производимых смещений соседних симуляторов костей черепа и скорости изменения этих смещений в швах межкостных сочленений. Преподаватель также контролирует работу симулятора и правильность пальпации, уточняет у тренирующихся получаемые ощущения при разных значениях амплитуды и частоты смещения симуляторов костей в швах межкостных сочленений. По результатам тренировки определяют готовность врачей-остеопатов к самостоя- тельной работе. р Предлагаемая модель черепа удобна для эксплуатации в учебных учреждениях, при исполь- зовании в научно-исследовательских лабораториях для изучения феномена подвижно-суставного сочленения костей черепа в участках швов, а также для диагностики и терапии заболеваний. Конструкция модели черепа с подвижно-суставным сочленением костей В ходе испытаний, в зависимости от имевшегося опыта у врача-остеопата, результат трени- ровочной пальпации удавался с разным успехом. Однако после нескольких тренировок приоб- ретался навык, в котором однозначно определялась причина нарушения смещения симуляторов костей в швах межкостных сочленений, связанная с включением имитатора ограничения дви- жения, причём при разном расположении имитатора ограничения движения вдоль линий швов межкостных сочленений. Более детальное описание работы устройства при имитации разных ситуаций в остеопати- ческой практике представлены в работе [3]. Мохов Д. Е., Коваль Ю. И., Чащин А. В. Функциональная модель черепа с подвижно-суставным сочленением костей для обучения практической работе врачей-остеопатов на краниальных тканях // Рос. остеопат. журн. 2017. № 1–2 (36–37). С. 20–30. Литература 1. Бучнов А. Д., Матвиенко В. В., Сергеев И. Н., Егорова И. А. Тренажер для обучения и развития навыков пальпации: Патент на изобретение Ru2561902, приоритет от 13.01.2014. [Buchnov A. D., Matvienko V. V., Sergeev I. N., Egorova I. A. The simulator for training and development of skills of palpation. Patent for invention Ru2561902, priority from 13.01.2014] (rus.) Matvienko V. V., Sergeev I. N., Egorova I. A. The simulator for training and development of skills of palpation. ntion Ru2561902, priority from 13.01.2014] (rus.) p y ] ( ) 2. Модель черепа: Патент CN203465885 на полезную модель, приоритет от 22.09 2013. [Model of a skull: Patent CN203465885 for utility model, priority from 22.09 2013] (rus.) 3. Мохов Д. Е., Коваль Ю. И. Модель черепа с подвижно-суставным сочленением костей: Заявка № 2016109558 от 16.03.2016 в Патентном ведомстве РФ Роспатент. [Mokhov D., Koval Y. Model of a skull with a movable-articulate joint of bones: Application № 2016109558 of March 16, 2016 in the Patent Offi ce of the Russian Federation Rospatent] (rus.) Мохов Д. Е., Коваль Ю. И., Чащин А. В. Функциональная модель черепа с подвижно-суставным сочленением костей для обучения практической работе врачей-остеопатов на краниальных тканях // Рос. остеопат. журн. 2017. № 1–2 (36–37). С. 20–30. 30
https://openalex.org/W4290379624
https://hal.science/hal-01963928/document
English
null
Estimating true species richness and the degree of hierarchical structuring of species abundances in eight frog communities from the North-Western Ghats of India.
HAL (Le Centre pour la Communication Scientifique Directe)
2,018
cc-by
13,958
Estimating true species richness and the degree of hierarchical structuring of species abundances in eight frog communities from the North-Western Ghats of India Jean Béguinot To cite this version: Jean Béguinot. Estimating true species richness and the degree of hierarchical structuring of species abundances in eight frog communities from the North-Western Ghats of India.. International Journal of Environment and Climate Change, 2018, 8 (2), pp.118-137. ￿10.9734/IJECC/2018/42067￿. ￿hal- 01963928￿ HAL Id: hal-01963928 Submitted on 21 Dec 2018 L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, whether they are pub- lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. International Journal of Environment and Climate Change 8(2): 118-137, 2018; Article no.IJECC.2018.009 Previously known as British Journal of Environment & Climate Change ISSN: 2231–4784 Estimating True Species Richness and the Degree of Hierarchical Structuring of Species Abundances in Eight Frog Communities from the North-Western Ghats of India Jean Béguinot1* 1Biogéosciences, UMR 6282, CNRS, Université Bourgogne Franche-Comté, 6, Boulevard Gabriel, 21000 Dijon, France. Author’s contribution The sole author designed, analyzed and interpreted and prepared the manuscript. Article Information DOI: 10.9734/IJECC/2018/42067 Received 12th May 2018 Accepted 25th May 2018 Published 7th June 2018 ABSTRACT Method Article 8(2): 118-137, 2018; Article no.IJECC.2018.009 Previously known as British Journal of Environment & Climate Change ISSN: 2231–4784 Estimating True Species Richness and the Degree of Hierarchical Structuring of Species Abundances in Eight Frog Communities from the North-Western Ghats of India Jean Béguinot1* 1Biogéosciences, UMR 6282, CNRS, Université Bourgogne Franche-Comté, 6, Boulevard Gabriel, 21000 Dijon, France. Received 12th May 2018 Accepted 25th May 2018 Published 7th June 2018 Received 12th May 2018 Accepted 25th May 2018 Published 7th June 2018 Received 12th May 2018 Accepted 25th May 2018 Published 7th June 2018 Method Article Method Article *Corresponding author: E-mail: jean-beguinot@orange.fr; ABSTRACT The Distribution of Species Abundances within natural communities – when properly analysed – can provide essential information regarding general aspects of the internal organisation of these communities. In particular, true species richness on the one hand and the intensity of the process of hierarchical structuring of species abundances on the other hand may be estimated independently and, thereby, can provide truly complementary information. In turn, specific issues may thereby be addressed. For example, whether one unique dominant factor or numerous combined factors are involved in the structuring process of a community can be tested contradictorily. Although these methods are not new conceptually, their implementation in common practice remains scarce. The reason is that the relevant implementation of these methods requires to be sure that virtually all member-species in the community have been sampled. As exhaustive samplings often reveal difficult to achieve in practice, an appropriate, least-biased procedure of numerical extrapolation of incomplete inventories is imperatively required. Considering the steadily increasing threats to the environment and biodiversity, especially facing the on-going climatic change, time has come now with ever greater urgency to go beyond the apparent limits of non-exhaustive sampling and make the most of what is available in terms of recorded field data, whatever the degree of incompleteness of species inventories. g p p As a modest and limited attempt to concretise this wish at the local level, I try, hereafter, to highlight the importance of additional information that may be unveiled through adequate post- analysis of a set of eight frog communities, recently inventoried by Katwate, Apte & Raut in an Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 amphibian hot-spot in the north-western Ghats of India. At last, the likely variations of both total species richness and the intensity of hierarchical structuring of species abundance are simulated as an answer to the steadily increasing influence of the ongoing climatic change. Keywords: Species diversity; species abundance; rank abundance distribution; amphibians; anurans; incomplete sampling; numerical extrapolation; climate change. 1. INTRODUCTION Considering together the five exhaustive Species Abundance Distributions and the three “numerically-completed” ones, I focused on the comparison between these eight frogs’ communities, regarding: (i) their respective levels of species richness and (ii) their respective patterns of abundances distribution. Beyond the mere description of abundance patterns, dealing with already complete or numerically extrapolated Species Abundance Distributions allows to relevantly address (i) the type and (ii) the strength of the process driving the hierarchical structuring of species abundances in each studied communities. Total species richness, taxonomic composition and hierarchical structuring of species abundance distribution are three main topics that together provide a good deal of information about species communities in the wild. The Species Abundance Distribution (especially under the form of the “Rank Abundance Distribution”) is a convenient tool for characterising species communities this way, but this requires, yet, that the sampling effort has been sufficient enough for the resulting abundance distribution being (quasi) exhaustive. This complementary, functional-type approach stands out by its particular interest in the context of the on-going climate change. Indeed, even before climatic change is expected to significantly affect the taxonomic composition within animal communities, it is the functional aspects of these communities – such as the hierarchical structuring of species abundances – that are likely to be impacted first. And frog communities, especially sensitive to climatic parameters, are among the priorities to be addressed in this respect [4,5]. Exhaustive samplings, however, are difficult to obtain and rarely reached in practice, especially when having to deal with species rich communities, such as most invertebrates’ assemblages. But even in some vertebrates’ communities, comprehensive species inventories may occasionally require very large sampling sizes, hard to implement in practice, when one or more of the less common member species happen to be excessively rare. Hopefully, even in such case, it remains possible to extract far much information than would be expected from substantially incomplete samplings, by implementing an appropriate numerical extrapolation procedure [1,2]. While the taxonomic identification of the still undetected species remains, of course, impossible, two other major descriptive features of communities (total species richness and the hierarchical structuring of species abundances) can be extrapolated fairly accurately, on the only basis of data extracted from substantially incomplete samples. 2.2 Numerical Extrapolation Procedures Applied to the Three Incomplete Inventories Extrapolation Procedures Three Incomplete - Not only provides an overview of both the true (total) species richness of the sampled community and the diversity of the respective abundances of member species, only provides an overview of both the species richness of the sampled community and the diversity of the respective abundances of member * Total species richness: the least estimation of the number of still undetected species at the end of partial sampling and the resulting estimation of the total species richness of the partially community are derived according to the procedure defined in [9,10] and briefly summarised in Appendix 1. Estimates are based on the numbers fx observed x-times during partial sampling (x = 1 to 5: Figs. A1.1 to A1.3 in Appendix 1). : the least-biased estimation of the number of still undetected partial sampling and the resulting estimation of the total species partially sampled community are derived according to the e defined in [9,10] and briefly summarised in Appendix 1. Estimates are x of species times during partial sampling (x A1.1 to A1.3 in Appendix 1). * Total species richness: the least estimation of the number of still undetected species at the end of partial sampling and the resulting estimation of the total species richness of the partially community are derived according to the procedure defined in [9,10] and briefly summarised in Appendix 1. Estimates are based on the numbers fx observed x-times during partial sampling (x = 1 to 5: Figs. A1.1 to A1.3 in Appendix 1). : the least-biased estimation of the number of still undetected partial sampling and the resulting estimation of the total species partially sampled community are derived according to the e defined in [9,10] and briefly summarised in Appendix 1. Estimates are x of species times during partial sampling (x A1.1 to A1.3 in Appendix 1). p - But, also, can help addressing several important questions regarding the process driving the hierarchical structuration of the community (Fig , also, can help addressing several important questions regarding the kind of process driving the hierarchical of the community (Fig. 1). More precisely, these questions may relate to: More precisely, these questions may relate to: - The process of structuration community of species: for example, does only one (or very few) dominant factor is (are) at work to structure the community or, on the contrary, does many independent factors are contributing together. 2.2 Numerical Extrapolation Procedures Applied to the Three Incomplete Inventories Extrapolation Procedures Three Incomplete This may be tested by checking the conformity of the corresponding S.A.D. to either the series model or the log- respectively [12–16]; of structuration of a community of species: for example, does (or very few) dominant factor is (are) at work to structure the community or, many independent factors are contributing together. This may be tested by checking the conformity of the corresponding S.A.D. to either the log- -normal model g pp ) Species Abundance Distribution accurately exploit their full potential, the as-recorded Species Abundance Distributions (“S.A.D.s”) require [1,11]: pp ) Species Abundance Distribution: to eir full potential, the recorded Species Abundance Distributions (“S.A.D.s”) require [1,11]: - First, to be corrected for statistical sampling bias, resulting from the finite size of samplings and, for statistical sampling bias, resulting from the finite g - Second, and still more importantly, to be completed by numerical extrapolation to the extent that sampling is suspected to be incomplete, as revealed by the subsistence of singletons. , and still more importantly, to be by numerical extrapolation to the extent that sampling is suspected to be incomplete, as revealed by the p y [ ] - The degree of structuration of a community of species, which broadly refers to the level of unevenness between species abundances within the community. This may be appropriately tested by comparing the slope of the corresponding S.A.D. to either the “ideally even” model or the of a community species, which broadly refers to the level of unevenness between species abundances within the community. This may be appropriately tested by comparing the slope of the corresponding S.A.D. to the “ideally even” model or the p y [ ] - The degree of structuration of a community of species, which broadly refers to the level of unevenness between species abundances within the community. This may be appropriately tested by comparing the slope of the corresponding S.A.D. to either the “ideally even” model or the of a community species, which broadly refers to the level of unevenness between species abundances within the community. This may be appropriately tested by comparing the slope of the corresponding S.A.D. to the “ideally even” model or the The appropriate procedure of correction and least-biased numerical extrapolation of the as The appropriate procedure of correction and the numerical extrapolation of the as- Fig. 1. 2.1 Materials Katwate, Apte & Raut [3] reported on the inventories of eight frogs communities (Amphibians, anurans) from Phansad Wildlife Sanctuary, located in the Northern Western Ghats of India. Five of these inventories (labelled A, C, D, E, G) show no subsisting singletons (i.e. species sampled only once) and, accordingly, may be considered virtually exhaustive [6-8]. The other three inventories (labelled B, F, H) all retain, on the contrary, one or more singletons and, thus, likely remain more or less incomplete (as actually confirmed subsequently). Hereafter, I report on the analysis of the inventories of eight frogs communities originally sampled by Katwate, Apte & Raut [3] in northern- western Ghats of India. Among these eight inventories, five may be considered quasi exhaustive (since no singleton is actually subsisting in the samples), while the other three inventories remain more or less incomplete and thus require the implementation of numerical extrapolation to unveil the complete range of species abundance distribution. Details on the sites location where these frog communities were sampled, the local ecological conditions and constraints peculiar to these sites, 119 Béguinot; IJECC, 8(2): 118-137, 2018; Article no. , 2018; Article no.IJECC.2018.009 recorded S.A.D.s, described in details in [1], is briefly recalled in Appendix 2. described in details in [1], is the lists of species identities and the numbers of recorded individuals per species, are provided in the aforementioned reference [3]. the lists of species identities and the numbers of recorded individuals per species, are provided in After being corrected and accordingly, the S.A.D.: and extrapolated 2.2 Numerical Extrapolation Procedures Applied to the Three Incomplete Inventories Extrapolation Procedures Three Incomplete Schematic sketch showing how the combination of both historical and ecological contexts peculiar to a given community of species drive the relative “performance” latissimo - of each member species "i", thus generating the abundances in the community Schematic sketch showing how the combination of both historical and ecological contexts peculiar to a given community of species drive the relative “performance” species "i", thus generating the hierarchical structuring abundances in the community Schematic sketch showing how the combination of both historical and ecological contexts peculiar to a given community of species drive the relative “performance” - sensu hierarchical structuring of species Fig. 1. Schematic sketch showing how the combination of both historical and ecological contexts peculiar to a given community of species drive the relative “performance” latissimo - of each member species "i", thus generating the abundances in the community Schematic sketch showing how the combination of both historical and ecological contexts peculiar to a given community of species drive the relative “performance” species "i", thus generating the hierarchical structuring abundances in the community Schematic sketch showing how the combination of both historical and ecological contexts peculiar to a given community of species drive the relative “performance” - sensu hierarchical structuring of species 120 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 10f2 + 10f3 – 5f4 + f5) in all three cases: see the selective key in Appendix 1. “broken-stick” model. These two models provide two reference levels of structuration, namely the “ideally even” model characterises the zero level of structuration while the “broken-stick” model accounts for the degree of structuration that would be obtained by a random apportionment of relative abundances among all co-occurring species in the community [17]. Standardising the degree of structuration (the slope of the S.A.D.) to the “broken-stick” model is particularly relevant as this allows to set apart the “mechanistic”, trivial influence of species richness upon the level of unevenness of species abundances in the community [18 –20]. This “mechanistic” influence of species richness on the slope of the abundance distribution and, consequently, on the degree of community structuration, is demonstrated in Appendix 3). Thus standardised, the degree of structuration of a community becomes truly independent of the trivial influence of species richness. 2.2 Numerical Extrapolation Procedures Applied to the Three Incomplete Inventories Extrapolation Procedures Three Incomplete Accordingly, the corresponding least-biased estimations of the number Δ of species remaining undetected in the inventories of B, F, H, are given by Jackknife-5 and the resulting least-biased estimation is St = Ro + Δ, with Ro as the number of recorded species. For the five communities A, C, D, E, G, having no remaining singletons and thus considered to be comprehensively sampled, Δ thus equals 0 and, accordingly, the total species richness St is equal to the number Ro of already recorded species. All the results are summarised in Table 1. Note, in addition that, as might have been expected, the product of sample-size No times the relative abundance aSt of the rarest species in each sampled community is much less than 1 when dealing with incomplete samplings (communities B, F, H) and much greater than 1 when dealing with exhaustive samplings (communities A, C, D, E, G). 3.1 The Recorded or Estimated Total Species Richness of the Eight Frog Communities The ranked Species Abundance Distribution of community “F” (coarse grey dots and coarse solid line for the extrapolated part: ranks > 14) compared to two associated models: the “log-normal” distribution (dotted line) and the “log-series” distribution (double line) Fig. 3. The ranked Species Abundance Distribution of community “F” (coarse grey dots and coarse solid line for the extrapolated part: ranks > 14) compared to two associated models: the “log-normal” distribution (dotted line) and the “log-series” distribution (double line) These ranked Species Abundance Distributions highlight the detailed patterns of hierarchical structuring of species abundances which are specific to each studied community. In particular, the stronger the rate of abundance decrease (i.e. the steeper the slope of the ranked abundance distribution) and the more severe looks the hierarchical structuring. Yet, this descriptive approach does not relevantly account for the genuine strength of the structuring process at work in the community, because the slope of the 3.1 The Recorded or Estimated Total Species Richness of the Eight Frog Communities As a whole, abundance distributions best fit the corresponding “log-normal” model than the corresponding “log-series” model. Figs. 2 and 3 provide two typical examples of such close fitting of the Species Abundance Distribution to the corresponding “log-normal” distribution, for both an exhaustively sampled community (G) and an incompletely sampled community (F). As regards the three incompletely sampled communities (B, F, H) and considering the values of the numbers fx of species observed x-times in each of the three samples (see Figs. A1, A2, A3 in Appendix 1), it turns out that the least-biased nonparametric estimator of the number of undetected species is Jackknife-5 (JK-5 = 5f1 – Table 1. The sample-size No, the number of recorded species Ro, the selected least-biased estimator, the number of undetected species Δ, the total species richness St (either recorded for A, C, D, E, G, or extrapolated St = Ro+Δ for B, F, H), the relative abundance aSt of the rarest species (rank St). As expected, the sample-size multiplying the relative abundance of the rarest species (No.aSt) is << 1 in each of the three incomplete inventories (B, F, H) and >> 1 for each of the other five comprehensive inventories (A, C, D, E, G) Community No Ro Selected estimator Δ St aSt No.aSt B 468 11 JK-5 1.9 12.9 .0003 0.14 F 231 14 JK-5 2.8 16.8 .0006 0.14 H 417 10 JK-5 2.4 12.4 .0002 0.08 A 615 15 / 0 15 .0063 3.9 C 329 11 / 0 11 .0265 8.6 D 403 11 / 0 11 .0386 15.3 E 304 11 / 0 11 .0254 7.6 G 493 10 / 0 10 .0060 2.9 121 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 Fig. 2. The ranked Species Abundance Distribution of community “G” (coarse grey dots) compared to two associated models: the “log-normal” distribution (dotted line) and the “log- series” distribution (double line) Fig. 3. 3.1 The Recorded or Estimated Total Species Richness of the Eight Frog Communities The ranked Species Abundance Distribution of community “F” (coarse grey dots and coarse solid line for the extrapolated part: ranks > 14) compared to two associated models: the 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 species relative abundance species abundance rank G 0,0001 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 species relative abundance species abundance rank F 0,0001 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 species relative abundance species abundance rank F 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 species relative abundance species abundance rank G F G F ranked Species Abundance Distribution of community “G” (coarse grey two associated models: the “log-normal” distribution (dotted line) and t series” distribution (double line) nked Species Abundance Distribution of community “F” (coarse grey d ne for the extrapolated part: ranks > 14) compared to two associated mo mal” distribution (dotted line) and the “log-series” distribution (double l ng the Degree of Hierarchical g of Abundances in Species ties: From Pattern to the g Process ecies Abundance Distributions of ommunities are plotted in Figs. 4 vely, after all these distributions orrected and after the three ampled communities (B, F, H) extrapolated. These ranked Species Abundance Dis highlight the detailed patterns of hi structuring of species abundances w specific to each studied community. In the stronger the rate of abundance dec the steeper the slope of the ranked a distribution) and the more severe hierarchical structuring. Yet, this d approach does not relevantly accoun genuine strength of the structuring p work in the community, because the slo 3 4 5 6 7 8 9 10 11 species abundance rank 0,0001 0,001 0,01 0 1 2 3 4 5 6 7 8 9 10 11 12 13 species relative species abundance rank A 1 nce Fig. 2. The ranked Species Abundance Distribution of community “G” (coarse grey dots) compared to two associated models: the “log-normal” distribution (dotted line) and the “log- series” distribution (double line) series” distribution (double line) Fig. 3. 3.3 Quantifying the Degree of Hierarchical Structuring of Abundances in Species Communities: From Pattern to the Underlying Process The ranked Species Abundance Distribution of community “D” (coarse grey dots) and associated “broken-stick” distribution, computed for the same species richness (dashed line) line) Fig. 7. The ranked Species Abundance Distribution of community “E” (coarse grey dot the associated “broken-stick” distribution, computed for the same species richness (d line) Fig. 8. The ranked Species Abundance Distribution of community “G” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) Fig. 9. The ranked Species Abundance Distribution of community “B” (coarse grey dots and coarse solid line for the extrapolated part: ranks > 11) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 species relative abundance species abundance rank G 0,0001 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 species relative abundance species abundance rank B 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 species relative abundance species abundance rank G 0,0001 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 species relative abundance species abundance rank B G B Fig. 8. The ranked Species Abundance Distribution of community “G” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) ) Fig. 9. The ranked Species Abundance Distribution of community “B” (coarse grey dots and coarse solid line for the extrapolated part: ranks > 11) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) abundance distribution depends not only upon the structuring process itself but also depends on the level of species richness of the community. Indeed, all other things being equal, the rate (i.e. the slope) of abundance decrease is negatively dependent upon the level of species richness of the community, as highlighted in Appendix 3. Accordingly, the Species Abundance Distribution should relevantly be compared to the corresponding “broken-stick” model (i.e. the “broken-stick” model computed for the same level of species richness), in order to cancel the trivial influence of species richness level and, thus, unveil the genuine intensity of the structuring process. Thus, in Figs. 4 to 11, each complete (or completed) Species Abundance Distribution is plotted together with its corresponding “broken-stick” distribution. 3.3 Quantifying the Degree of Hierarchical Structuring of Abundances in Species Communities: From Pattern to the Underlying Process The ranked Species Abundance Distributions of the eight frog communities are plotted in Figs. 4 to 11 respectively, after all these distributions have been corrected and after the three incompletely sampled communities (B, F, H) have been duly extrapolated. Fig. 4. The ranked Species Abundance Distribution of community “A” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) Fig. 5. The ranked Species Abundance Distribution of community “C” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 species relative abundance species abundance rank A 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 species relative abundance species abundance rank C 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 species relative abundance species abundance rank C 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 species relative abundance species abundance rank A A C Fig. 4. The ranked Species Abundance Distribution of community “A” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) Fig. 5. The ranked Species Abundance Distribution of community “C” (coarse grey dots) and the associated “broken-stick” distribution computed for the same species richness (dashed Fig. 4. The ranked Species Abundance Distribution of community “A” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) line) Fig. 5. The ranked Species Abundance Distribution of community “C” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) 122 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 Fig. 6. The ranked Species Abundance Distribution of community “D” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) Fig. 7. The ranked Species Abundance Distribution of community “E” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) Fig. 8. The ranked Species Abundance Distribution of community “G” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) Fig. 9. 3.3 Quantifying the Degree of Hierarchical Structuring of Abundances in Species Communities: From Pattern to the Underlying Process The ranked Species Abundance Distribution of community “B” (coarse grey dots and coarse solid line for the extrapolated part: ranks > 11) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) abundance distribution depends not only upon the structuring process itself but also depends on the level of species richness of the community. Indeed, all other things being equal, the rate (i.e. the slope) of abundance decrease is negatively d d t th l l f i i h f level of species richness), in order to cancel the trivial influence of species richness level and, thus, unveil the genuine intensity of the structuring process. Thus, in Figs. 4 to 11, each complete (or completed) Species Abundance Di t ib ti i l tt d t th ith it 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 species relative abundance species abundance rank D 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 species relative abundance species abundance rank E 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 species relative abundance species abundance rank G 0,0001 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 species relative abundance species abundance rank B Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 species relative abundance species abundance rank E 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 species relative abundance species abundance rank D E D Fig. 6. The ranked Species Abundance Distribution of community “D” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) Fig. 7. The ranked Species Abundance Distribution of community “E” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) 1 1 Fig. 6. The ranked Species Abundance Distribution of community “D” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) Fig. 7. The ranked Species Abundance Distribution of community “E” (coarse grey dots) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) . 6. 4. DISCUSSION In a less detailed (and thus more reductionist) approach, the average slope of the Species Abundance Distribution provides a convenient, concise appreciation of the degree of hierarchical structuring. A “structuring index”, based on the average slope, can be defined accordingly. As aforementioned, to reliably reflect the genuine strength of the structuring process, this index must be stantardised to the average slope of the corresponding “broken-stick” distribution. Accordingly, an appropriate structuring index is relevantly defined as the ratio between the average slope of the actual abundance distribution and the average slope of the corresponding “broken-stick” distribution. To conform to the usual, conventional mode of plotting abundance distributions, the abundances will be classically log-transformed. Thus defined, the structuring index Istr is equal to: In a less detailed (and thus more reductionist) approach, the average slope of the Species Abundance Distribution provides a convenient, concise appreciation of the degree of hierarchical structuring. A “structuring index”, based on the average slope, can be defined accordingly. As aforementioned, to reliably reflect the genuine strength of the structuring process, this index must be stantardised to the average slope of the corresponding “broken-stick” distribution. Accordingly, an appropriate structuring index is relevantly defined as the ratio between the average slope of the actual abundance distribution and the average slope of the corresponding “broken-stick” distribution. To conform to the usual, conventional mode of plotting abundance distributions, the abundances will be classically log-transformed. Thus defined, the structuring index Istr is equal to: In a less detailed (and thus more reductionist) approach, the average slope of the Species Abundance Distribution provides a convenient, concise appreciation of the degree of hierarchical structuring. A “structuring index”, based on the average slope, can be defined accordingly. As aforementioned, to reliably reflect the genuine strength of the structuring process, this index must be stantardised to the average slope of the corresponding “broken-stick” distribution. Although the present study aims, first, at a general methodological purpose, rather than being focused toward a particular taxonomic target, a brief argumentation is provided however, supporting the choice of frogs as an appropriate illustrative taxonomic group for the application of the method. Amphibians in general, and frogs in particular, are among animal groups which are most sensitive to environmental changes, especially climatic modifications involving temperature and hygrometry [4,5]. 3.3 Quantifying the Degree of Hierarchical Structuring of Abundances in Species Communities: From Pattern to the Underlying Process This straightforwardly provides a reliable appreciation of the degree of hierarchical structuring of species abundances in each community. abundance distribution depends not only upon the structuring process itself but also depends on the level of species richness of the community. Indeed, all other things being equal, the rate (i.e. the slope) of abundance decrease is negatively dependent upon the level of species richness of the community, as highlighted in Appendix 3. Accordingly, the Species Abundance Distribution should relevantly be compared to the corresponding “broken-stick” model (i.e. the “broken-stick” model computed for the same 123 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 Fig. 10. The ranked Species Abundance Distribution of community “F” (coarse grey dots and coarse solid line for the extrapolated part: ranks > 14) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) Fig. 11. The ranked Species Abundance Distribution of community “H” (coarse grey dots and coarse solid line for the extrapolated part: ranks > 10) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) 0,0001 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 species relative abundance species abundance rank F 0,0001 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 species relative abundance species abundance rank H 0,0001 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 species relative abundance species abundance rank H 0,0001 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 species relative abundance species abundance rank F H Fig. 10. The ranked Species Abundance Distribution of community “F” (coarse grey dots and coarse solid line for the extrapolated part: ranks > 14) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) Fig. 11. The ranked Species Abundance Distribution of community “H” (coarse grey dots and coarse solid line for the extrapolated part: ranks > 10) and the associated “broken-stick” distribution, computed for the same species richness (dashed line) 4. DISCUSSION More specifically, amphibians in general and frogs in particular are typically stenothermic species, as such directly affected by the on-going climate changes, via the increase of temperature and resulting imposed shifts in local distributions, especially altitudinal increase when possible and, otherwise, local extinction [21–23]. Often connected to temperature evolution are more or less drastic changes in precipitation with resulting risks of shortage of water availability which is so important for most amphibians’ survival. Severe declines of various kinds of amphibians are already reported for this reason [24–26]. And both temperature and hygrometry are major drivers of reproductive activities which may thus be strongly affected by global climate change [27–29]. The issue is all the more acute when considering amphibians “hot-spots” having a high proportion of particularly fragile endemic species, Istr = [log(a1) – log(aSt)]/[log(a’1) – log(a’St)] that is: 4.2 The Hierarchical Structuring of Species Abundances: Only One Dominant Causal Factor or Many Independent Ones Jointly Involved? 4.2 The Hierarchical Structuring of Species Abundances: Only One Dominant Causal Factor or Many Independent Ones Jointly Involved? that is: Thus, it is in this sense that should be understood the following warning by noted that the three incompletely sampled communities B, F, H, are precisely those ones that are the most strongly structured, i.e. having the least even distribution of species abundances, as shown later in Fig. 12. Correlatively, in each of communities B, F, H, the rarest species have, by far, the smallest relative abundance levels: see Table 1. As a result, the product No.aSt of the abundance aSt of the rarest species times the sample-size No remains far less than unity in the incomplete samplings of communities B, F, H, while this product largely exceeds unity in the exhaustive samplings of the five other communities (Table 1). This, indeed, is the reason for the sampling incompleteness of as is the case in the western-Ghats of India [3]. Hence, the importance of assessing, and further analysing in detail, the current state of frog communities in this region. This implies not only drawing up species-lists as complete as possible but also to record (and if necessary to extrapolate numerically) the Species Abundance Distributions in each of these frog communities [16,30–35]. Species Abundance Distributions are not only of descriptive interest as a pattern, but also ought to be considered as a mean to address the process governing the hierarchical structuring of species abundances within communities. Thus, it is in this sense that should be understood the following warning by Southwood & Henderson [36]: "A great deal of time and expertise has been expended on the compilation of faunal lists for particular habitats, but the consequent increase in our understanding [...] is still meagre." noted that the three incompletely sampled communities B, F, H, are precisely those ones that are the most strongly structured, i.e. having the least even distribution of species abundances, as shown later in Fig. 12. Correlatively, in each of communities B, F, H, the rarest species have, by far, the smallest relative abundance levels: see Table 1. As a result, the product No.aSt of the abundance aSt of the rarest species times the sample-size No remains far less than unity in the incomplete samplings of communities B, F, H, while this product largely exceeds unity in the exhaustive samplings of the five other communities (Table 1). that is: This, indeed, is the reason for the sampling incompleteness of communities B, F, H (rather than a lesser sampling effort, as compared to the five exhaustively sampled communities). that is: Istr = log(a1/aSt)/log(a’1/a’St) (1) (1) Istr = log(a1/aSt)/log(a’1/a’St) (1 Istr = log(a1/aSt)/log(a’1/a’St) where a1 and aSt stand for the highest and the lowest abundances in the studied community and a’1 and a’St stand for the highest and the lowest abundances in the corresponding “broken-stick” distribution (i.e. computed for the same level of species richness St). Results are given in Table 2. 124 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 Table 2. The degree of hierarchical structuration (true unevenness) of species abundances, relevantly quantified by the structuring index ‘Istr’ defined as the average slope of the Species Abundance Distribution standardised to the average slope of the corresponding “broken- stick” distribution (data from Figs 4 to 11) Table 2. The degree of hierarchical structuration (true unevenness) of species abundances, relevantly quantified by the structuring index ‘Istr’ defined as the average slope of the Species Abundance Distribution standardised to the average slope of the corresponding “broken- stick” distribution (data from Figs. 4 to 11) Table 2. The degree of hierarchical structuration (true unevenness) of species abundances, relevantly quantified by the structuring index ‘Istr’ defined as the average slope of the Species Abundance Distribution standardised to the average slope of the corresponding “broken- stick” distribution (data from Figs. 4 to 11) Community St Sp. Abund. Distr. “broken-stick” structuring index log[a1/aSt] / log[a’1/a’St] a1 aSt a'1 a'St A 15 .1810 .0063 .2212 .0044 0.86 C 11 .2676 .0265 .2745 .0083 0.66 D 11 .2391 .0386 .2745 .0083 0.52 E 11 .2190 .0254 .2745 .0083 0.62 G 10 .2048 .0060 .2929 .0100 1.05 B 12.9 .3146 .00033 .2448 .0080 2.01 F 16.8 .2266 .00062 .2024 .0050 1.59 H 12.4 .2360 .00018 .2586 .0050 1.82 as is the case in the western-Ghats of India [3]. Hence, the importance of assessing, and further analysing in detail, the current state of frog communities in this region. This implies not only drawing up species-lists as complete as possible but also to record (and if necessary to extrapolate numerically) the Species Abundance Distributions in each of these frog communities [16,30–35]. Species Abundance Distributions are not only of descriptive interest as a pattern, but also ought to be considered as a mean to address the process governing the hierarchical structuring of species abundances within communities. 4.1 True Species Richness of Communities While the inventories of most invertebrate communities are often doomed to remain incomplete in practice - due to their usually high species richness including numerous rare species - the exhaustive sampling of vertebrates and, here of frog communities, is usually less out of reach. Thus, among the eight frog communities sampled by Katwate, Apte & Raut [3] in northern-western Ghats of India, five may be considered as already virtually exhaustive while the other three prove being only moderately incomplete (from 80% to 85% completeness: Table 1) but nevertheless require numerical extrapolation. Total species richness levels, either recorded (communities A, C, D, E, G) or extrapolated (communities B, F, H), range from 10 to 17 species. Interestingly, it should be Schematically, the structuration of species abundances within natural communities may result either from the influence of one dominant factor or from the interplay of numerous independent factors. As a result, the corresponding Species Abundance Distribution would fit more closely the “log-series” model or the “log-normal” model respectively [12–16]. Reliably testing each hypothesis requires, however, to consider the whole range of the Species Abundance Distribution [15,37–40]. Accordingly, if it cannot be recorded exhaustively, the Species Abundance Distribution must be numerically extrapolated. When considered along their whole range, the Species Abundance Distributions of the eight 125 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 species abundances, leaving aside the influence of the level of species richness, devoid of biological sense (Table 2). frog communities most often fit the “log-normal” model best (Figs. 2 & 3). This suggests that the hierarchical structuring of species abundances in these communities is generally driven by the combined influences of numerous, independent factors (related to ecological and/or historical constraints), rather than by the sole influence of one major, strongly determinant factor [15,39– 43]. frog communities most often fit the “log-normal” model best (Figs. 2 & 3). This suggests that the hierarchical structuring of species abundances in these communities is generally driven by the combined influences of numerous, independent factors (related to ecological and/or historical constraints), rather than by the sole influence of one major, strongly determinant factor [15,39– 43]. Thus removing the trivial influence of species richness St in the definition of the structuring index, Istr, warrants the independence a priori between Istr and St. Accordingly, an empirically observed dependence or, on the contrary, independence, between Istr and St will gain true biological significance. 4.3 The Degree of Hierarchical Structuring of Species Abundances in Each Community The degree of unevenness of the distribution of species abundances in a community mainly depends, of course, on the intensity of the hierarchical structuring. But, as aforementioned, the total species richness also influences “mechanically” the degree of unevenness, at the risk of providing, thus, a biased appreciation of the intensity of hierarchical structuring. This is because, the degree of species dominance unavoidably tends to decrease with increasing total species richness, all other things being equal: the dominance tends to be somewhat “diluted” by the increasing number of co- occurring species [1,18–20]. This trend – and its essentially numerical rather than biological origin – is clearly demonstrated theoretically by considering a constant process of abundance structuring (such as the random apportionment of abundances among species in the “broken-stick” model) applied to communities of varying species richness. The average steepness of the “broken- stick” distribution consistently decreases with increasing species richness: see Appendix 3. The intensity of the hierarchical structuring process, relevantly quantified by Istr, varies to a large extent, ranging from 0.52 to 2.01, according to communities (Fig. 12 and Table 2). No correlation is empirically highlighted between Istr and St (Fig. 12), which means that, here, the true intensity of the hierarchical structuring process, driving the species abundance pattern, develops independently of species richness in the community. This is an original and important finding that was by no means obvious a priori. Looking further in the detail of structuring process (Figs. 4 to 11, Fig. 12 and Table 3), it is worth noting that the hierarchical structuration may be either: - “regular”, i.e. with a gently varying rate in the abundance decrease, as observed in communities C, D, E, F, G, or - “regular”, i.e. with a gently varying rate in the abundance decrease, as observed in communities C, D, E, F, G, or - “irregular”, i.e. suddenly exhibiting a sharp acceleration of the decreasing rate of species abundances and, thus, a brutal and statistically significant recess of the abundance level for the few rarest species, as in communities A, B, H (Figs. 4, 9, 11). - “irregular”, i.e. suddenly exhibiting a sharp acceleration of the decreasing rate of species abundances and, thus, a brutal and statistically significant recess of the abundance level for the few rarest species, as in communities A, B, H (Figs. 4, 9, 11). 4.1 True Species Richness of Communities Hence, the interest of plotting Istr against St, as proposed in Figs. 12 & 13. In addition, this representation has the advantage of providing a synthetic overview of the main results derived from this study. 4.3 The Degree of Hierarchical Structuring of Species Abundances in Each Community 4.3 The Degree of Hierarchical Structuring of Species Abundances in Each Community Accordingly, a relevant appreciation of the intensity of the hierarchical structuring process requires to separate and leave out the purely “mechanical” influence of the level of species richness. This is appropriately achieved: Being limited to three communities out of eight, the “irregular” pattern invites to seek for some species-specific rather than generic causes. - Graphically, by plotting simultaneously the Species Abundance Distribution under study and the corresponding “broken-stick” model, computed for the same level of species richness (Figs. 4 to 11), - Graphically, by plotting simultaneously the Species Abundance Distribution under study and the corresponding “broken-stick” model, computed for the same level of species richness (Figs. 4 to 11), In this respect, the species list provided in Table 3 of the paper by Katwate, Apte & Raut [3] leads to the following remarks: - Quantitatively, by standardising the average slope of the Species Abundance Distribution under study to the average slope of the corresponding “broken-stick” model, leading to the definition of a structuring index, Istr (equation (1)), which thereby reflects the genuine contribution of the hierarchical structuring process driving - Fejervarya caperata Kuramoto et al. (in community A), Fejervarya cf. keralensis Dubois (in community B), Ramanella marmorata Jerdon (in comm. A & B), Uperodon globulosus Gunther (in community A), Sphaerotheca dobsonii 126 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 Gunther (in community F), Hylarana malabarica Tschudi (in community F) are by no means affected the same, although these species occur at similar or even lower levels of relative abundance. Boulenger (in communities A & H) are strongly affected by the recess of abundances, sharply disconnecting from the “broken-stick” model; while, on the contrary, y, Raorchestes bombayensis Annandale (in community C), Polypedates maculatus Gray (in community F), Indirana leithii Boulenger (in community F), Pseudophilautus cf. amboli Biju & Bossuyt (in community F), Indirana beddomii Now, what makes Fejervarya caperata, Fejervarya cf. keralensis, Ramanella marmorata, Uperodon globulosus, Sphaerotheca dobsonii specifically affected (as compared to the other six species cited above) remains conjectural. Fig. 12. A synthetic presentation of the situation of the eight frog communities with respect to two major quantitative features describing species communities: (i) the true (total) species richness St and (ii) the genuine intensity of the hierarchical structuring of species abundances, quantified by the structuring index Istr. White figures: exhaustively sampled communities; grey figures: communities requiring numerical extrapolations. The hierarchical structuring may be “regular” (i.e. 4.3 The Degree of Hierarchical Structuring of Species Abundances in Each Community roughly constant among species: discs) or “irregular” (i.e. with the sharp recess of abundance for the 3 or 4 rarest species: diamonds) 0,0 0,5 1,0 1,5 2,0 8 9 10 11 12 13 14 15 16 17 hierarchical structuring index Istr true species richness St G C E D F A H B less even more even 0,0 0,5 1,0 1,5 2,0 8 9 10 11 12 13 14 15 16 17 hierarchical structuring index Istr true species richness St G C E D F A H B less even more even Fig. 12. A synthetic presentation of the situation of the eight frog communities with Fig. 12. A synthetic presentation of the situation of the eight frog communities with respect to two major quantitative features describing species communities: (i) the true (total) species Fig. 12. A synthetic presentation of the situation of the eight frog communities with respect to two major quantitative features describing species communities: (i) the true (total) species richness St and (ii) the genuine intensity of the hierarchical structuring of species abundances, quantified by the structuring index Istr. White figures: exhaustively sampled communities; grey figures: communities requiring numerical extrapolations. The hierarchical structuring may be “regular” (i.e. roughly constant among species: discs) or “irregular” (i.e. with the sharp recess of abundance for the 3 or 4 rarest species: diamonds) Fig. 12. A synthetic presentation of the situation of the eight frog communities with respect to two major quantitative features describing species communities: (i) the true (total) species richness St and (ii) the genuine intensity of the hierarchical structuring of species abundances, quantified by the structuring index Istr. White figures: exhaustively sampled communities; grey figures: communities requiring numerical extrapolations. The hierarchical structuring may be “regular” (i.e. roughly constant among species: discs) or “irregular” (i.e. with the sharp recess of abundance for the 3 or 4 rarest species: diamonds) Table 3. Contrasting features of the Species Abundance Distributions between communities B, H, (and to a lesser extent A) and the other five communities: under a threshold abundance value ≈ 0.04, the decreasing rate of species abundances communities abruptly accelerates for communities A, B and H : see Figs. 4, 9, 11. 4.3 The Degree of Hierarchical Structuring of Species Abundances in Each Community The resulting sudden recess of species abundances below the “broken-stick” distribution, as a consequence of this sharp acceleration, is statistically significant (statistical test based on Bayesian inference: p < 0.05) What When B Sharp acceleration of decreasing rate For ai < 0.030 (i.e. ai < a9) H Sharp acceleration of decreasing rate For ai < 0.030 (i.e. ai < a9) A Less sharp acceleration of decreasing rate For ai < 0.023 (i.e. ai < a11) D No such acceleration Even down to ai = aSt = 0.038 C No such acceleration Even down to ai = aSt = 0.027 E No such acceleration Even down to ai = aSt = 0.015 F No such acceleration Even down to ai = aSt = 0.008 G No such acceleration Even down to ai = aSt = 0.006 127 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 4.5 Tentatively Speculating About the Effect of Climatic Change on the Features of the Species Abundance Distribution Yet, species-specific reasons for the brutal acceleration of the decreasing rate under a given threshold of relative abundance may be speculated and attributed to: (i) an intrinsic rarity of species being very rare all across their respective ranges of repartition ; Let consider a pejoration of environmental conditions assumed to occur around a given frog community – say community G, actually having 10 species with its Species Abundance Distribution shown in Figs. 2 and 8. This pejoration may be due, for example, to a steadily increasing climate change. It is assumed, here, that pejoration affects species abundances all the more than these abundances are already low, thus making the slope of the species abundances distribution becoming steadily steeper, as pejoration progressively increases. In addition, there inevitably exists some threshold level of absolute abundance below which the survival of a species becomes no longer possible, for example because of too low probability of finding mates for reproduction. Let this minimum survival threshold be fixed, for example, as half the absolute abundance of the rarest species (rank 10) as presently recorded, i.e. before pejoration goes on increasing. (ii) a local rarity of species, approaching, here, the limits of their respective ranges of repartition ; (iii) an occasional rarity of “vagrant” species, poorly adapted to the local ecological conditions prevailing in communities B, H, (A) and, accordingly, only present by more or less brief incursions; (iv) a rarity resulting from some negatively density-dependent detrimental factor, applying to those species specifically (such as the increasing difficulty of finding mates to reproduce, below some threshold level of abundance); ) (v) a rarity related to the stochastic character of colonisation events along time with, for example, exceptionally recent establishments assumed for those species in communities B, H, (A). ) (v) a rarity related to the stochastic character of colonisation events along time with, for example, exceptionally recent establishments assumed for those species in communities B, H, (A). Fig. 14 highlights graphically what is expected to happen with such increasing pejoration, in terms of (i) species richness St and (ii) hierarchical structuring intensity, Istr. Here, numerical extrapolations reach the limits of their explanatory capacities and going on any further would require specific biological knowledge regarding each of these species. 4.5 Tentatively Speculating About the Effect of Climatic Change on the Features of the Species Abundance Distribution In a first step (0  1), the hierarchical structuring intensity, Istr, will increase (see equation (1)) since a1/aSt steadily increases while a’1/a’St remains of course unchanged, as long as St remains equal to 10. 4.4 The Role of Forest Degradation on the Total Species Richness and the Intensity of the Hierarchical Structuring of Species Abundances Pristine forest (E, D): white figures ; intermediate degree of forest degradation (A, B, C, F): grey figures ; strong degrees of forest degradation (G, H): black figures 0,0 0,5 1,0 1,5 2,0 8 9 10 11 12 13 14 15 16 17 hierarchical structuring index Istr true species richness St G C E D F A H B less even more even 2 1 And so on, in a saw-tooth pattern, as shown in Fig. 14. (i) The steadily decrease of species richness St, consequence of the thinning effect due to the minimum abundance threshold for survival and (i) The steadily decrease of species richness St, consequence of the thinning effect due to the minimum abundance threshold for survival and g Let consider now the overall trend, behind the detail of the sequential, saw-tooth variations. As might have been expected, this overall trend mainly consist in: t, q g to the minimum abundance threshold for survival and (ii) A global increase of the genuine intensity of hierarchical structuring, Istr (note, yet, Fig. 13. Seeking for the possible influence of the degree of forest degradation on (i) the true species richness St and (ii) the intensity of the hierarchical structuring of species abundances Istr. Pristine forest (E, D): white figures ; intermediate degree of forest degradation (A, B, C, F): grey figures ; strong degrees of forest degradation (G, H): black figures Fig. 14. Simulation of the consequences of an increasing environmental pejoration (for example related to climate change,) on (i) the total species richness “St” and (ii) the genuine intensity of the hierarchical structuring “Istr” of species abundances for the frog community “G”. See text for the influence of this pejoration on the respective abundances of species 0,0 0,5 1,0 1,5 2,0 8 9 10 11 12 13 14 15 16 17 hierarchical structuring index Istr true species richness St G C E D F A H B less even more even 0,7 0,9 1,1 1,3 1,5 1,7 1,9 2,1 4 5 6 7 8 9 10 11 structuring intensity Istr species richness St 1 2 0 5 4 3 6 7 9 8 Let consider now the overall trend, behind the detail of the sequential, saw-tooth variations. 4.4 The Role of Forest Degradation on the Total Species Richness and the Intensity of the Hierarchical Structuring of Species Abundances As might have been expected, this overall trend mainly consist in: (ii) A global increase of the genuine intensity of hierarchical structuring, Istr (note, yet, 0,0 0,5 1,0 1,5 2,0 8 9 10 11 12 13 14 15 16 17 hierarchical structuring index Istr true species richness St G C E D F A H B less even more even 129 Fig. 13. Seeking for the possible influence of the degree of forest degradation on (i) the true species richness St and (ii) the intensity of the hierarchical structuring of species abundances Istr. Pristine forest (E, D): white figures ; intermediate degree of forest degradation (A, B, C, F): grey figures ; strong degrees of forest degradation (G, H): black figures Fig. 14. Simulation of the consequences of an increasing environmental pejoration (for example related to climate change,) on (i) the total species richness “St” and (ii) the genuine intensity of the hierarchical structuring “Istr” of species abundances for the frog community “G”. See text for the influence of this pejoration on the respective abundances of species 0,7 0,9 1,1 1,3 1,5 1,7 1,9 2,1 4 5 6 7 8 9 10 11 structuring intensity Istr species richness St 1 2 0 5 4 3 6 7 9 8 Fig. 13. Seeking for the possible influence of the degree of forest degradation on (i) the true species richness St and (ii) the intensity of the hierarchical structuring of species abundances Istr. Pristine forest (E, D): white figures ; intermediate degree of forest degradation (A, B, C, F): grey figures ; strong degrees of forest degradation (G, H): black figures Fig. 14. Simulation of the consequences of an increasing environmental pejoration (for example related to climate change,) on (i) the total species richness “St” and (ii) the genuine intensity of the hierarchical structuring “Istr” of species abundances for the frog community “G” S t t f th i fl f thi j ti th ti b d f i 0,7 0,9 1,1 1,3 1,5 1,7 1,9 2,1 4 5 6 7 8 9 10 11 structuring intensity Istr species richness St 1 2 0 5 4 3 6 7 9 8 Fig. 13. Seeking for the possible influence of the degree of forest degradation on (i) the true species richness St and (ii) the intensity of the hierarchical structuring of species abundances Istr. 4.4 The Role of Forest Degradation on the Total Species Richness and the Intensity of the Hierarchical Structuring of Species Abundances No consistent trend emerges in this respect that could yet have been expected (Fig. 13). Thus, pristine forests are by no means host to the most species-rich frog communities. And the hierarchical structuring of abundances fails, as well, to clearly correlate with the level of forest degradation. This suggests, among other possibilities, that historical aspects (such as the more or less stochastic succession of species colonisation events at a given site) may partially obliterate the more deterministic influence of environmental parameters, including the level of forest degradation. Alternatively, this may also signify that expectations on the subject (such as the compelling decrease of species richness with increasing disturbance) are simply irrelevant, here. Then, when the absolute abundance of the rarest species (rank 10) finally falls below the survival threshold, it disappears (step 1  2) and, consequently, the hierarchical structuring intensity, Istr, abruptly decreases because species ranked 9 – now becoming the rarest species – is appreciably more abundant than was species ranked 10 at the moment of its disappearance. Thus, at stage 2, Istr = log(a1/a9)/log(a’1/a’9) is lower than log(a1/a10)/log(a’1/a’10) at stage 1 (namely: Istr = 0.82 and Istr = 1.30, respectively). Then, with now St = 9, the same happen as for the first step at St = 10: the hierarchical structuring intensity Istr increases, as long as St remains equal to 9: (step 2  3). 128 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 And so on, in a saw-tooth pattern, as shown in Fig. 14. Let consider now the overall trend, behind the detail of the sequential, saw-tooth variations. As might have been expected, this overall trend mainly consist in: (i) The steadily decrease of species richness St, consequence of the thinning effect due to the minimum abundance threshold for survival and (ii) A global increase of the genuine intensity of hierarchical structuring, Istr (note, yet, Fig. 13. Seeking for the possible influence of the degree of forest degradation on (i) the true species richness St and (ii) the intensity of the hierarchical structuring of species abundances Istr. 4.4 The Role of Forest Degradation on the Total Species Richness and the Intensity of the Hierarchical Structuring of Species Abundances Pristine forest (E, D): white figures ; intermediate degree of forest degradation (A, B, C, F): grey figures ; strong degrees of forest degradation (G, H): black figures Fig. 14. Simulation of the consequences of an increasing environmental pejoration (for example related to climate change,) on (i) the total species richness “St” and (ii) the genuine intensity of the hierarchical structuring “Istr” of species abundances for the frog community “G” See text for the influence of this pejoration on the respective abundances of species Fig. 14. Simulation of the consequences of an increasing environmental pejoration (for example related to climate change,) on (i) the total species richness “St” and (ii) the genuine intensity of the hierarchical structuring “Istr” of species abundances for the frog community “G”. See text for the influence of this pejoration on the respective abundances of species 129 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 Fig. 15. The new Species Abundance Distribution when community “G” has reached stage 2 (St = 9 ; Istr = 0.83) as a consequence of the environmental pejoration (see Fig. 14). The arrow highlights the beginning separation from the log-normal model (dotted line) towards the “log- series” model (double line). Initial situation (step 0) of community “G” is provided at Fig. 2 0,001 0,01 0,1 1 0 1 2 3 4 5 6 7 8 9 10 species relative abundance species abundance rank FG FG FG Fig. 15. The new Species Abundance Distribution when community “G” has reached stage 2 (St = 9 ; Istr = 0.83) as a consequence of the environmental pejoration (see Fig. 14). The arrow highlights the beginning separation from the log-normal model (dotted line) towards the “log- series” model (double line). Initial situation (step 0) of community “G” is provided at Fig. 2 that, without standardisation to the “broken-stick”, the apparent unevenness level would, on the contrary, seem to decrease, instead of increase; see [35]). from the metapopulation context; that is implicitly out of reach from external inputs of new species that would possibly be better adapted to the currently evolving local environment. Such colonisation by “appropriate” new species would likely more or less compensate for both the reduction of abundances and the ultimate disappearance of the successively rarest species and, thus, would tend to more or less buffer the consequences of environmental pejoration on the shape of the Species Abundance Distribution. 5. CONCLUSION Estimating the level of total species richness in animal communities, as well as getting insights on the genuine causes and intensity of the hierarchical structuring of species abundances, are major topics that likely contribute to a more comprehensive understanding of these communities. Acquiring such knowledge also provides a basic reference for the future monitoring of the consequences of the on-going climatic change on living communities. However, this program imperatively requires performing exhaustive species inventories or, if impractical, impose to extrapolate numerically the incomplete samplings with minimum bias. An appropriate methodological approach in this respect is provided above and its implementation is exemplified by the treatment of a series of communities of tropical frogs, a particularly exposed and endangered group of animals, potentially under threat of excessive heat and drought. 4. Pounds JA, Crump ML. Amphibian declines and climatic disturbance: The case of the Golden Toad and the Harlequin Frog. Conservation Biology. 1994;8:72-85. g gy 5. Mc Callum ML. Future climate change spells catastrophe for Blanchard’s cricket frog, Acris blanchardi (Amphibia: Anura: Hylidae). Acta Herpetologica. 2010;5(1): 119-130. 6. Coddington JA, Agnarsson I, Miller JA, Kuntner M, Hormiga G. Undersampling bias: the null hypothesis for singleton species in tropical arthropod surveys. Journal of Animal Ecology. 2009;78:573- 584. 7. Gotelli NJ, Colwell RK. Estimating species richness. In: Biological Diversity: Frontiers in Measurement and Assessment. A.E. Magurran and B.J. McGill (Eds.). 2010;39- 54. Oxford University Press, Oxford. 345. 8. 8. Gotelli NJ, Chao A. Measuring and estimating species richness, species diversity, and biotic similarity from sampling data. In: Levin S.A. (ed.) Encyclopedia of Biodiversity. Second edition. Waltham, MA: Academic Press. 2013;5:195-211. ACKNOWLEDGEMENTS A fruitful advice from the Editor, on a previous version of the manuscript, is gratefully acknowledged. 9. ; Béguinot J. Theoretical derivation of a bias-reduced expression for the extrapolation of the Species Accumulation Curve and the associated estimation of total species richness. Advances in Research. 2016;7(3):1-16. DOI: 10.9734/AIR/2016/26387; <hal- 01367803> 4.4 The Role of Forest Degradation on the Total Species Richness and the Intensity of the Hierarchical Structuring of Species Abundances After having considered the consequences of environmental pejoration on species richness and the intensity of hierarchical structuring, let move now to the expected effect on the shape of the Species Abundance Distribution and its related functional significance. One might expect that, as the pejoration goes on increasing, the role of this detrimental factor would progressively become more and more predominant on the other ecological factors that drive the distribution of species abundances. Accordingly, it is expected that the Species Abundance Distribution progressively shifts from its original compliance with the “log-normal” model (see Figs. 2 and 3) towards a progressively better compliance with the “log-series” model [12–16]. This, indeed, is what is demonstrated by the simulation. Thus, as soon as stage 2 is reached (Fig. 15), the Species Abundance Distribution already clearly disconnects from the “log-normal” model, and is already halfway towards the “log- series” model. To now conclude this speculative section, I would like to draw attention on the practical interest of considering Species Abundance Distributions in the context of evolving environmental conditions. Devoting attention at each of the three main aspects that shape Species Abundance Distributions (i.e. species richness, hierarchical structuring intensity and selective fitting to either reference models), will offer a corresponding set of typically diagnostic features, able to reliably highlight the consequences of an increasing degree of environmental pejoration. As already emphasised, this may have major practical interest in the perspective of monitoring the consequences of environmental pejoration in general and, in particular, for the monitoring of this major cause of pejoration represented by the ongoing climatic change worldwide. However, it should be noted also that, in this schematically simplified scenario, the focused community is implicitly considered as isolated 130 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 of India. Journal of Threatened Taxa. 2013;5(2):3589-3602. DOI: 10.11609/JoTT.o3038 COMPETING INTERESTS Author has declared that no competing interests exist. REFERENCES 10. 10. Béguinot J. Extrapolation of the Species Accumulation Curve associated to “Chao” estimator of the number of unrecorded species: A mathematically consistent derivation. Annual Research & Review in Biology. 2016;11(4):1-19. DOI: 10.9734/ARRB/2016/30522; <hal 01477263 > 1. Béguinot J. How to extrapolate species abundance distributions with minimum bias when dealing with incomplete species inventories. Advances in Research. 2018; 13(4):1-24. ( ) DOI: 10.9734/AIR/2018/39002 2. 2. Béguinot J. Numerical extrapolation of the species abundance distribution unveils the true species richness and the hierarchical structuring of a partially sampled marine gastropod community in the Andaman Islands (India). Asian Journal of Environment and Ecology. 2018;6(4):1– 23. DOI: 10.9734/AJEE/2018/41293 11. Chao A, Hsieh T, Chazdon RL, Colwell RK, Gotelli NJ. Unveiling the species-rank abundance distribution by generalizing the Good-Turing sample coverage theory. Ecology. 2015;96(5):1189-1201. 12. May RM. Patterns of species abundance and diversity. In Cody M.L. & Diamond J.M. Ecology and Evolution of Communities. The Belknap Press of Harvard University. 1975;81-120. 3. Katwate U, Apte D, Raut R. Diversity and distribution of anurans in Phansad Wildlife Sanctuary (PWS), Northern Western Ghats 3. Katwate U, Apte D, Raut R. Diversity and distribution of anurans in Phansad Wildlife Sanctuary (PWS), Northern Western Ghats 131 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 13. Loreau M. Species abundance patterns and the structure of ground-beetle communities. Ann. Zool. Fennici. 1992;28: 49-56. 35 years at La Selva, Costa Rica. Proceedings of the National academy of Sciences USA. 2007;104:8352-8356. 25. McMenamin SK, Hadly EA, Wright CK. Climatic change and wetland dessication cause amphibian decline in world’s oldest National park. Proceedings of the National academy of Sciences USA. 2008;105: 16988-16993. 14. Magurran AE, Henderson PA. Explaining the excess of rare species in natural species abundance distributions. Nature. 2003;422:714-716. 15. Connolly SR, Hughes TP, Bellwood DR, Karlson RH. Community structure of corals and reef fishes at multiple scales. Science. 2005;309:1363-1365. 26. Rovito SM, Parra-Olea G, Vasquez- Almazan CR, Papenfuss TJ, Wake DB. Dramatic declines in Neotropical salamanders populations are an important part pf the global amphibian crisis. Proceedings of the National academy of Sciences USA. 2009;106:3231-3236. ; 16. Ulrich W, Soliveres S, Thomas AD, Dougill AJ, Maestre FT. Environmental correlates of species rank-abundance distributions in global drylands. Europe PMC Funders Group. 2016;20:56-64. 27. 27. Gibbs JP, Breisch AR. Climate warming and calling phenology of frogs near Ithaca, New York, 1900-1999. Conservation Biology. 2001;15:1175-1178. p 17. MacArthur RH. REFERENCES On the relative abundance of bird species. Proceedings of the National Academy of Sciences U.S.A. 1957;43:293-295. gy 28. Beebee T. Amphibian phenology and climate change. Conservation Biology. 2002;16:1454. 18. Ulrich W, Ollik M, Ugland KI. A meta-analysis of species-abundance distributions. Oikos. 2010;119:1149-1155. 29. Kusano T, Inoue M. Long-term trends towards earlier breeding of Japanese amphibians. Journal of Herpetology. 2008; 42:608-614. 19. Komonen A, Elo M. Ecological response hides behind the species abundance distribution: community response to low- intensity disturbance in managed grasslands. Ecology and Evolution. 2017; 7:8558-8566. 30. Cam E, Nichols JD, Sauer JR, Hines JE. On the estimation of species richness based on the accumulation of previously unrecorded species. Ecography. 2002;25: 102-108. 20. MacDonald ZG, Nielsen SE, Acorn JH. Negative relationships between species richness and evenness render common diversity indices inadequate for assessing long-term trends in butterfly diversity. Biodiversity Conservation. 2017;26:617- 629. 31. Van der Putten WH, Macel M, Visser ME. Predicting species distribution and abundance responses to climate change: why it is essential to include biotic interactions across trophic levels. Philosophical Transactions of the Royal Society B. 2010;365:2025-2034. 21. Seimon TA, Seimon A., Daszak, Halloy SRP, et al. Upward range extension of Andean anurans and chytridiomycosis to extreme elevations in response to tropical deglaciation. Global Change Biology. 2007;13:288-299. 32. Peel GT, Ward TM, Doubleday ZA, et al. Rapid assessment of fisheries species sensitivity to climate change. Climatic Change; 2014. DOI: 10.1007/s10584-014-1284-z 22. Raxworthy CJ, Rabibisoa RG, Rakotondrazafy AM, et al. Extinction vulnerability of tropical montane endemism warming and upslope deplacement: A preliminary appraisal for the highest massif in Madagascar. Global Change Biology. 2008;14:1703-1720. 33. Ehrlen J, Morris WM. Predicting changes in the distribution and abundance of species under environmental change. Ecology Letters. 2015;18:303-314. gy 34. Brandmayr P, Pizzolotto R. Climate change and its impact on epigean and hypogean carabid beetles. Periodicum Biologorum. 2016;118(3):147-162. 23. Milanovich JR, Peterman WE, Nibbelink NP, Maerz JC. Projected loss of a salamander diversity hotspot by consequence of projected global climate change. PLoS ONE. 2010;5(8):e 12189. 35. McCarthy J, Mokany K, Ferrier S, Dwyer J. Predicting community rank-abundance distributions under current and future climates. Ecography. 2017;40:1-11. 24. Whitfield SM, Bell KE, Philippi T, Sasa M, et al. Amphibian and Reptile declines over 132 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 36. Southwood TRE, Henderson PA. Ecological Methods. Blackwell Science Ltd., Oxford, U.K; 2000. distributions. Journal of Animal Ecology. 2013;82:721-738. ; 44. Béguinot J. APPENDIX 1 Each solution Rx (N) is appropriate for a given range of values of f1 compared to the other numbers fx (according to [9]): * for f1 up to f2  R1 (N) = (R(N0) + f1) – f1.N0/N * for f1 up to f2  R1 (N) = (R(N0) + f1) – f1.N0/N ( ) ( ( ) ) * for larger f1 up to 2f2 – f3  R2 (N) = (R(N0) + 2f1 – f2) – (3f1 – 2f2).N0/N – (f2 – f1).N0 2/N2 * for larger f1 up to 2f2 – f3  R2 (N) = (R(N0) + 2f1 – f2) – (3f1 – 2f2).N0/N – (f2 – f1).N0 2/N2 * for larger f1 up to 3f2 – 3f3 + f4  R3 (N) = (R(N0) + 3f1 – 3f2 + f3) – (6f1 – 8f2 + 3f3).N0/N – (– 4f1 + 7f2 – 3f3).N0 2/N2 – (f1 – 2f2 + f3).N0 3/N3 * for larger f1 up to 3f2 – 3f3 + f4  R3 (N) = (R(N0) + 3f1 – 3f2 + f3) – (6f1 – 8f2 + 3f3).N0/N – (– 4f1 + 7f2 – 3f3).N0 2/N2 – (f1 – 2f2 + f3).N0 3/N3 * for larger f1 up to 4f2 – 6f3 + 4f4 – f5  R4 (N) = (R(N0) + 4f1 – 6f2 + 4f3 – f4) – (10f1 – 20f2 + 15f3 – 4f4).N0/N – (– 10f1 + 25f2 – 21f3 + 6f4).N0 2/N2 – (5f1 – 14f2 + 13f3 – 4f4).N0 3/N3 – (– f1 + 3f2 – 3f3 + f4).N0 4/N4 * for f1 larger than 4f2 – 6f3 + 4f4 – f5  R5 (N) = (R(N0) + 5f1 – 10f2 + 10f3 – 5f4 + f5) – (15f1 – 40f2 + 45f3 – 24f4 + 5f5).N0/N – (– 20f1 + 65f2 – 81f3 + 46f4 – 10f5).N0 2/N2 – (15f1 – 54f2 + 73f3 – 44f4 + 10f5).N0 3/N3 – (– 6f1 + 23f2 – 33f3 + 21f4 – 5f5).N0 4/N4 – (f1 – 4f2 + 6f3 – 4f4 + f5).N0 5/N5 The associated non-parametric estimators of the number ΔJ of missing species in the sample [with ΔJ = R(N=∞) – R(N0) ] are derived immediately: The associated non-parametric estimators of the number ΔJ of missing species in the sample [with ΔJ = R(N=∞) – R(N0) ] are derived immediately: * f1 < f2  ΔJ1 = f1 ; R1 (N) * f2 < f1 < 2f2 – f3  ΔJ2 = 2f1 – f2 ; R2 (N) * 2f2 – f3 < f1 < 3f2 – 3f3 + f4  ΔJ3 = 3f1 – 3f2 + f3 ; R3 (N) * 3f2 – 3f3 + f4 < f1 < 4f2 – 6f3 + 4f4 – f5  ΔJ4 = 4f1 – 6f2 + 4f3 – f4 ; R4 (N) * f1 > 4f2 – 6f3 + 4f4 – f5  ΔJ5 = 5f1 – 10f2 + 10f3 – 5f4 + f5 ; R5 (N) N.B. REFERENCES An algebraic derivation of Chao’s estimator of the number of species in a community highlights the condition allowing Chao to deliver centered estimates. ISRN Ecology; 2014. ID 847328. DOI:10.1155/2014/847328; <hal-01101415> 37. Magurran AE. Species abundance distributions: Pattern or process? Functional Ecology. 2005;19:177-181. gy 38. McGill BJ, Etienne RS, Gray JS, et al. Species abundance distributions: Moving beyond single prediction theories to integration within an ecological framework. Ecology Letters. 2007;10:995-1015. 45. 45. Béguinot J. When reasonably stop sampling? How to estimate the gain in newly recorded species according to the degree of supplementary sampling effort. Annual Research & Review in Biology. 2015;7(5):300-308. DOI: 10.9734/ARRB/2015/18809; <hal-01228695> 39. Matthews TJ, Whittaker RJ. On the species abundance distribution in applied ecology and biodiversity management. Journal of Applied Ecology. 2015;52:443- 454. 40. Connolly SR, Hughes TP, Bellwood DR. A unified model explains commonness and rarity on coral reefs. Ecology Letters. 2017; 20:477-486. 46. O’Hara RB. Species richness estimators: how many species can dance on the head of a pin? Journal of Animal Ecology. 2005; 74:375-386. 41. Peters SE, Bork KB. Species abundance models: an ecological approach to inferring paleoenvironment and resolving paleoecological change in the Waldron Shale (Silurian). Palaios. 1999;14:234- 245. 47. Rajakaruna H, Drake DAR, Chan FT, Bailey SA. Optimizing performance of nonparametric species richness estimators under constrained sampling. Ecology and Evolution. 2016;6:7311-7322. 42. Sizling AL, Storch D, Sizlingova E, Reif J, Gaston KJ. Species abundance distribution results from a spatial analogy of central limit theorem. Proceedings of the National Academy of Sciences USA. 2009;106(16): 6691-6695. 48. Chen Y, Shen TJ. Rarefaction and extrapolation of species richness using an area-based Fisher’s logseries. Ecology and Evolution. 2017;7:10066-10078. 49. 49. Brose U, Martinez ND, Williams RJ. Estimating species richness: Sensitivity to sample coverage and insensitivity to spatial patterns. Ecology. 2003;84(9): 2364-2377. 43. Saether BE, Engen S, Grotan V. Species diversity and community similarity in fluctuating environments: Parametric approaches using species abundance 133 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 APPENDIX 1 Bias-reduced extrapolation of the Species Accumulation Curve and associated bias-reduced estimation of the number of still unrecorded species, based on the recorded numbers of species occurring 1 to 5 times Consider the survey of an assemblage of species of size N0 (with sampling effort N0 typically identified either to the number of recorded individuals or to the number of sampled sites, according to the inventory being in terms of either species abundances or species incidences), including R(N0) species among which f1, f2, f3, f4, f5, of them are recorded 1, 2, 3, 4, 5 times respectively. The following procedure, designed to select the less-biased solution, results from a general mathematical relationship that constrains the theoretical expression of any theoretical Species Accumulation Curves R(N) (see [9,44,45]): ∂xR(N)/∂Nx = (-1)(x-1) fx(N) /CN, x ≈ (– 1)(x-1) (x!/Nx) fx(N) ( ≈ as N >> x) (A1.1) , x ≈ (– 1)(x-1) (x!/Nx) fx(N) ( ≈ as N >> x) (A1.1) (A1.1) Compliance with the mathematical constraint (equation (A.1)) warrants reduced-bias expression for the extrapolation of the Species Accumulation Curves R(N) (i.e. for N > N0). Below are provided, accordingly, the polynomial solutions Rx (N) that respectively satisfy the mathematical constraint [1], considering increasing orders x of derivation ∂xR(N)/∂Nx. APPENDIX 1 1: As indicated above (and demonstrated in details in [9]), this series of inequalities define the ranges that are best appropriate, respectively, to the use of each of the five estimators, JK-1 to JK-5. That is the respective ranges within which each estimator will benefit of minimal bias for the predicted number of missing species. 134 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 Besides, it is easy to verify that another consequence of these preferred ranges is that the selected estimator will always provide the highest estimate, as compared to the other estimators. Interestingly, this mathematical consequence, of general relevance, is in line with the already admitted opinion that all non-parametric estimators provide under-estimates of the true number of missing species [7,8,46– 48]. Also, this shows that the approach initially proposed by Brose et al. [49] – which has regrettably suffered from its somewhat difficult implementation in practice – might be advantageously reconsidered, now, in light of the very simple selection key above, of far much easier practical use. N.B. 2: In order to reduce the influence of drawing stochasticity on the values of the fx, the as- recorded distribution of the fx should preferably be smoothened: this may be obtained either by rarefaction processing or by regression of the as-recorded distribution of the fx versus x. N.B. 3: For f1 falling beneath 0.6 x f2 (that is when sampling completeness closely approaches exhaustivity), then Chao estimator may alternatively be selected: see reference [10]. Figs. APPENDIX 1 A1.1, A1.2, A1.3 – The recorded values of the numbers fx of species recorded x-times (grey discs) and the regressed values of fx (black discs) derived to reduce the consequence of stochastic dispersion for the three incomplete samplings of frog communities labelled B, F, H 0,0 0,2 0,4 0,6 0,8 1,0 1,2 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 fx x B 0,0 0,5 1,0 1,5 2,0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 fx x F 0,0 0,2 0,4 0,6 0,8 1,0 1,2 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 fx x H 0,0 0,2 0,4 0,6 0,8 1,0 1,2 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 fx x H 0,0 0,2 0,4 0,6 0,8 1,0 1,2 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 fx x B 0,0 0,5 1,0 1,5 2,0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 fx x F B Figs. A1.1, A1.2, A1.3 – The recorded values of the numbers fx of species recorded x-times (grey discs) and the regressed values of fx (black discs) derived to reduce the consequence of stochastic dispersion for the three incomplete samplings of frog communities labelled B, F, H 135 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 Correction and extrapolation of the as-recorded Species Abundance Distribution (S.A.D.) N.B.: details regarding the derivation of the following expressions are provided in [1]. 1) Correction for bias of the recorded part of the S.A.D. 1) Correction for bias of the recorded part of the S.A.D. The bias-corrected expression of the true abundance, ãi, of species of rank ‘i' in the S.A.D. is given by: (A2.1) (A2.1) ãi = pi.(1+1/ni).(1–f1/N0)/(1+R0/N0) where N0 is the actually achieved sample size, R0 (=R(N0)) the number of recorded species, among which a number f1 are singletons (species recorded only once), ni is the number of recorded individuals of species ‘i’, so that pi = ni/N0 is the recorded frequency of occurrence of species ‘i', in the sample. The crude recorded part of the “S.A.D.” – expressed in terms of the series of as-recorded frequencies pi = ni/N0 – should then be replaced by the corresponding series of expected true abundances, ãi, according to equation (A2.1). 2) Extrapolation of the recorded part of the S.A.D. accounting for the complementary abundance distribution of the set of unrecorded species The following expression stands for the estimated abundance, ai, of the unrecorded species of rank i (thus for i > R0): ai = (2/Ni).(1– [∂R(N)/∂N]Ni)/(1+ R(Ni)/Ni) (A2.2) which, in practice, comes down to: ai ≈ (2/Ni)/(1+ R(Ni)/Ni) (A2.3) as f1(N) already becomes quite negligible as compared to N for the extrapolated part. This equation provides the extrapolated distribution of the species abundances ai (for i > R(N0)) as a function of the least-biased expression for the extrapolation of the species accumulation curve R(N) (for N > N0), ‘i' being equal to R(Ni). The key to select the least-biased expression of R(N) is provided at Appendix 1. 136 Béguinot; IJECC, 8(2): 118-137, 2018; Article no.IJECC.2018.009 APPENDIX 3 The trivial (“mechanistic”) contribution of the level of species richness to the degree of structuring of species abundances The trivial (“mechanistic”) contribution of the level of species richness to the degree of structuring of species abundances All things equal otherwise, the larger the species richness, the weaker is the slope of the Species Abundance Distribution. This can be easily exemplified and quantified, on a theoretical basis, by considering a theoretically constant structuring process - such as the random distribution of the relative abundances that characterises the “broken-stick” distribution model. By applying this model successively to a series of communities with increasing species richness, a steadily decrease of the slope of abundance distributions is highlighted: Fig. A3. Fig. A3. The “broken-stick” distribution model applied to species communities with increasing species richness St = 10, 20, 30, 60. Although the theoretical structuring process involved in the “broken-stick” model remains unchanged (random apportionment of relative abundances among member species), the slope of the species abundance distribution strongly depends upon (and monotonously decreases with) the level of species richness St © 2018 Béguinot; This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 0,0001 0,0010 0,0100 0,1000 1,0000 0 10 20 30 40 50 60 species relative abundance species abundance ranking St = 10 St = 20 St = 30 St = 60 Fig. A3. The “broken-stick” distribution model applied to species communities with increasing species richness St = 10, 20, 30, 60. Although the theoretical structuring process involved in the “broken-stick” model remains unchanged (random apportionment of relative abundances among member species), the slope of the species abundance distribution strongly depends upon (and monotonously decreases with) the level of species richness St © 2018 Béguinot; This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 Béguinot; This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 137
W2524418471.txt
https://publications.goettingen-research-online.de/bitstream/2/66429/1/document.pdf
en
Step(pe) up! Raising the profile of the Palaearctic natural grasslands
Biodiversity and conservation
2,016
cc-by
4,707
Biodivers Conserv (2016) 25:2187–2195 DOI 10.1007/s10531-016-1187-6 EDITORIAL Step(pe) up! Raising the profile of the Palaearctic natural grasslands Péter Török1 • Didem Ambarlı2 • Johannes Kamp3 Karsten Wesche4,5 • Jürgen Dengler6,5 • Published online: 26 September 2016 Ó Springer Science+Business Media Dordrecht 2016 Abstract Palaearctic steppes are primary grasslands dominating the landscape of the Eurasian Grassland Belt from Central and Eastern Europe to Northern China across the temperate zone of Eurasia. We also include structurally and floristically similar habitats in North Africa, Anatolia, and Iran. The biota of the steppes are diverse, including many endemic species. As a result of the high rate of anthropogenic conversion and widespread degradation, the Palaearctic steppes have become one of the most endangered terrestrial biomes of the world. These facts underline the importance of sustaining landscape-scale biodiversity in steppes and stress the necessity of their conservation and restoration. Literature about the ecology, biodiversity, and conservation of Palaearctic steppes is not easily accessible for an international audience. Therefore, summarising the current state of knowledge as well as knowledge gaps is very timely. This Special Issue on ‘‘Palaearctic steppes: ecology, biodiversity and conservation’’, comprises 17 research papers from many different regions throughout the biome, as well as a broad review synthesising current knowledge. Keywords Biodiversity  Eurasia  Eurasian Dry Grassland Group (EDGG)  Grassland conservation  Land use  Steppe biome & Péter Török molinia@gmail.com 1 MTA-DE Biodiversity and Ecosystem Services Research Group, Egyetem Square 1, Debrecen 4032, Hungary 2 Faculty of Agriculture and Natural Sciences, Düzce University, Konuralp, 81620 Düzce, Turkey 3 Institute of Landscape Ecology, University of Münster, Heisenbergstr. 2, 48149 Münster, Germany 4 Senckenberg Museum of Natural History Görlitz, P.O. Box 300154, 02806 Görlitz, Germany 5 German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany 6 Plant Ecology, Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Bayreuth, Universitätsstr. 30, 95447 Bayreuth, Germany 123 2188 Biodivers Conserv (2016) 25:2187–2195 Introduction The Palaearctic steppes form one of the largest continuous terrestrial natural habitats of the world. Their primary grasslands dominate the Eurasian Grassland Belt from Eastern Central Europe to Northern China across the temperate zone of Eurasia (Fig. 1). Steppes (in the wider sense) are also found in North Africa, Anatolia, and Iran (Wesche et al. 2016). Zonal steppes are generally treeless because of climatic aridity and/or rapid drainage of soil. In the forest-steppe zone, the mosaic character of the landscape with grasslands interspersed by scattered groups of trees and small woods is usually maintained by the grazing of domestic and wild ungulates and wildfires, which all prevent the establishment of extensive closed forests (Bredenkamp et al. 2002). Steppes are diverse in their abiotic conditions as well as their biotic composition, and they sustain a high number of endemic species (Dengler et al. 2014; Kajtoch et al. 2016). As typical steppes are characterised by fertile soils (often Chernozems), large areas of steppes have been converted to croplands in Europe and parts of Asia. Large-scale conversion started early in Europe, and by the end of the 19th century, most of the steppes of Eastern Europe (including Ukraine and European Russia) had been converted into cropland (Wesche et al. 2016). Across the Siberian and Central Asian steppes, the Virgin Lands Campaign of the Soviet Union led to Fig. 1 Simplified map of the Palaearctic steppe biome (with main steppe ecoregions after Wesche et al. 2016) with localisation of the studies included in this Special Issue: (1) Kuzemko et al. (2016); (2) Polyakova et al. (2016); (3) Sutcliffe et al. (2016); (4) Dembicz et al. (2016); (5) Kajtoch et al. (2016); (6) Weking et al. (2016); (7) Mathar et al. (2016); (8) Lameris et al. (2016); (9) Wang and Wesche (2016); (10) Addison and Greiner (2016); (11) Niu et al. (2016); (12) Novenko et al. (2016); (13) Deák et al. (2016); (14) Ambarlı et al. (2016); (15) Kamp et al. (2016); (16) Brinkert et al. (2016); (17) Kämpf et al. (2016). Reviews summarising data across countries are indicated by large asterisks (i.e. 5, 9, 10, 13, 14; numbers indicate approximate geographical centre for respective region of interest) 123 Biodivers Conserv (2016) 25:2187–2195 2189 large-scale conversion after the Second World War (Kamp et al. 2016). Widespread conversions resulted in steppes being one of the most threatened grassland types in the world; for example, about 57 % of the pristine Eurasian steppes on Chernozem soils were destroyed or degraded (Chibilev 1998). The proportion of steppe converted into cropland decreases from West to East across Eurasia: while in Ukraine 92–95 % of the pristine steppes have been ploughed, large, unconverted areas remain in Kazakhstan. In Turkey, more than 56 % of the natural steppe and steppe forest area has been lost (Ambarlı et al. 2016,), but in contrast in Mongolia, hardly any steppe has been converted to cropland, and in Chinese Inner Mongolia approx. 70 % of natural steppes remains. (Sudnik-Wójcikowska and Moysiyenko 2012; Wesche et al. 2016; White et al. 2000). However, in the unconverted steppes, overgrazing is often an equally serious threat (Wesche et al. 2016). According to the Millennium Ecosystem Assessment (World Resources Institute 2005), ‘‘Temperate grasslands, savannas and shrublands’’ (whose biggest share is the Palaearctic steppes) are unparalleled by any other biome worldwide in the combination of historical and ongoing habitat loss. This high threat level of the Palaearctic steppes and their vast importance for biodiversity stress the need for their conservation and restoration. This extraordinary conservation relevance, however, is not reflected by an equally good knowledge on distribution and ecology of the steppe bacteria, fungi, plants, and animals and the ecosystem processes of the biome: Research on grassland ecology and conservation is rather focussed on semi-natural grasslands in Europe (see Dengler et al. 2014), the North American prairies or tropical savannas. National research traditions, and the political barriers during the cold war of the 1950s into the 1970s resulted in knowledge on Palaearctic steppes being largely published in national languages in works difficult to obtain, and thus being hardly accessible to an international readership. Attempts to summarise existing knowledge and research on Palaearctic steppes beyond national borders and open them to an international platform are thus timely. This Special Issue of Biodiversity and Conservation, ‘‘Palaearctic steppes: ecology, biodiversity and conservation’’ aims at providing an overview of current research on ecology and biodiversity for an international audience. We also aim to showcase that steppes harbour high levels of biome-restricted biodiversity, whose endangerment by human-induced degradation and habitat loss is continuing. The Special Issue was initiated by the Eurasian Dry Grassland Group (EDGG; see Box 1; Vrahnakis et al. 2013) during its 11th international conference in Tula, Russia, in June 2014. While previous EDGG Special Issues (e.g. Dengler et al. 2014; Habel et al. 2013; Janišová et al. 2011) were mostly focused on the semi-natural (dry) grasslands of Europe, with only very few contributions from natural steppes being included, here we devote an entire journal issue to the Palaearctic steppe biome to highlight its poor international recognition as a globally important and highly threatened ecosystem. Our initiative extends and builds on a recent book with a similar focus (Werger and van Staalduinen 2012). This Special Issue contains 17 research articles and reviews, involving around 100 authors, and a comprehensive synthesis paper (Wesche et al. 2016). The studies are spread across the Palaearctic steppe biome (Fig. 1). Two contributions (Kajtoch et al. 2016; Sutcliffe et al. 2016) largely refer to semi-natural and extrazonal dry grasslands outside the steppe biome, addressing processes in these steppe-like grasslands that are also relevant for the natural steppes and can partly be connected to past situations when the respective study areas still belonged to the steppe biome. 123 2190 Biodivers Conserv (2016) 25:2187–2195 Box 1 The Eurasian Dry Grassland Group The Eurasian Dry Grassland Group (EDGG, formerly the European Dry Grassland Group) is an official working group of the International Association for Vegetation Science (IAVS) and was founded in 2008. The EDGG is a network of more than 1,000 researchers and conservationists from 60 countries interested in Palaearctic natural and semi-natural grasslands. The most important activities of the EDGG include ones to: (1) coordinate scientific and policy-related actions in grassland research, conservation and restoration in the whole Palaearctic realm; (2) facilitate the trans-national communication between researchers, site managers, policy and decision makers; (3) promote the development of databases for grassland classification, and of best-practice approaches to conservation and restoration; (4) organise annual conferences (the Eurasian Grassland Conference, EGC) and field workshops; and (5) synthesise current knowledge in Special Features of international journals. The EDGG also publishes the open-access Bulletin of the Eurasian Dry Grassland Group four times a year. Everybody who is interested in natural and semi-natural grasslands in the Palaearctic realm is invited to join, free of charge. Further information can be found on the homepage of EDGG (http://www.edgg.org/). Here, we introduce the individual articles, grouped into the main topic areas of: (1) patterns and drivers of biodiversity; (2) land-use changes and land management; and (3) conservation status, threats, and restoration. Patterns and drivers of biodiversity Semi-natural Palaearctic grasslands are known to be extraordinarily phyto-diverse at small spatial scales, including most of the known ‘‘world records’’ of vascular plant species richness at grain sizes below 100 m2 (Wilson et al. 2012; Dengler et al. 2016). Since they resemble ecologically and floristically the meadow steppes of the forest steppe zone in Eastern Europe and Middle Asia one might wonder why equally high or even higher small-scale richness values are not found in the natural meadow steppes. This Special Issue contains two contributions that applied standardised EDGG multi-scale phytodiversity sampling (Turtureanu et al. 2014) for the first time in natural steppe vegetation: Kuzemko et al. (2016) in Central Podolia, Ukraine, a part of the forest-steppe zone of the European steppe region, and Polyakova et al. (2016) for Khakassia, Russia, at the transition from the Middle Asian to the Mongolian region. Both author teams found high vascular plant species richness across spatial scales, with maxima, however, that were below the maxima in semi-natural grasslands of Central Europe. Taking research data from Western Siberia (Mathar et al. 2016) and Southern Ukraine (Dembicz et al. 2016) into account, the maximum vascular plant species richness for 100 m2 plot size decreases from Central Europe (133) over Khakassia (94), Central Podolia (86), and Southern Ukraine (73) to Western Siberia (54). The reasons for this unexpected pattern as well as some interesting findings with regard to scale dependence call for further data from other regions and their combined analysis. 123 Biodivers Conserv (2016) 25:2187–2195 2191 Two further projects analysed, within an island-biogeographic framework, the effect of local and landscape parameters on plant species diversity in isolated dry grassland patches in Transylvania, Romania (Sutcliffe et al. 2016), and kurgans in Southern Ukraine (Dembicz et al. 2016). In both areas, refuges for steppe vegetation are found within landscapes largely converted to cropland. Both studies found a strong top-down regulation of species richness, that is when a plot of defined size was located within a larger dry grassland/steppe patch and thus the species pool of the patch was presumably bigger, the richness on plots of 1 and 100 m2 (Ukraine) and 10 m2 (Transylvania) was higher as well. Such a strong species-pool effect within otherwise identical habitats has rarely been shown before. However, the mechanisms in the two regions seem to be different as in Transylvania mainly ruderal species became more diverse on plots located in larger grassland patches, while in Ukraine these were mainly steppe specialists. Kajtoch et al. (2016), reviewed a comprehensive set of studies that analysed genetic diversity patterns of 38 typical steppe taxa, both animals and plants, at the western margin of the continuous steppe biome. While the genetic patterns showed various taxon-specific peculiarities, the authors concluded from the relative genetic distinctness of isolated populations in the Pannonian region and in steppe-like grasslands in the Czech Republic, Poland, or Germany, which are normally considered as semi-natural, that many of these species may well have survived there during glaciations and did not just reach there after humans started to open the landscape. Land-use change and land management During the past century, land use and management of the Palaearctic steppes changed substantially. As in European non-steppe grasslands, conversion to arable lands, fragmentation, biodiversity loss by degradation, and the transition from extensive management to intensive use, were the main threats (Dengler et al. 2014; Wesche et al. 2016). The most important drivers behind these changes were ploughing during and after World War II, the modern agricultural revolution, and country-level policies such as the Virgin Lands Campaign of the Soviet Union targeted at maximising agricultural yield in the competitive global economy. More recently, some trends were reversed, namely, cropland abandonment and decreasing land-use intensity in marginal lands occurred in parts of the steppe after intensification in productive plains. These trends were especially pronounced in the Middle Asian steppes, where the collapse of the Soviet Union in 1991 triggered large-scale agricultural change (Kamp et al. 2016; Wesche et al. 2016). The consequences of both agricultural expansion and intensification as well as cropland abandonment on populations of plant and animal communities are discussed in several papers in the Special Issue (e.g. Lameris et al. 2016; Weking et al. 2016). Weking et al. (2016) showed that, for the Western Siberian forest-steppe, both used and abandoned croplands can provide suitable habitat for Orthoptera (grasshoppers and crickets). The authors concluded that abandoned croplands have a high potential for colonisation and rapid recovery of species-rich orthopteran communities 14 years after abandonment. Low-intensity grazing and hay making were found to support specialist species, and an increase in landscape heterogeneity was beneficial to these insects. This is in line with the findings of Buri et al. (2013), Humbert et al. (2012) and Mathar et al. (2016) for plant community composition and diversity patterns of grassland in the Western Siberian forest steppe. The joint analysis of local site conditions, functional traits, and management in relation to the surrounding landscape revealed that beside the general 123 2192 Biodivers Conserv (2016) 25:2187–2195 differences in community structure, there are major effects of land use and landscape-scale habitat transformation on the local plant diversity. Never ploughed large meadow steppe patches were characterised by the highest plant species richness and might therefore be used as reference sites in future restoration measures. Lameris et al. (2016) analysed the population-level consequences of large-scale agricultural abandonment on birds, using the Black Lark (Melanocorypha yeltoniensis), endemic to the steppes of Kazakhstan and fringing regions of Russia, as a model species. In abandoned croplands high densities were reached, but breeding success was low. Based on these findings, Lameris et al. (2016) discuss the potential of abandoned cropland to act as an ecological trap for steppe birds. Wang and Wesche (2016) evaluate the influence of grazing pressure on vegetation and soil indicators along a grazing intensity gradient based on an extensive review of the scattered Chinese literature. They found that the values of most indicators decreased with increasing grazing intensity, with the exception of soil pH, bulk density, and below-ground biomass, which all increased. Their overview suggests that local abiotic conditions need to be considered when evaluating the effects of grazing because the local environment and the climate interact with grazing intensity. These authors argue that spatio-temporal environmental variation and traditional knowledge of pastoralists should be integrated into local-level management decisions. These assumptions are also supported by Addison and Greiner (2016), who analysed the payment for ecosystem services (PES) schemes in the published literature with a social–ecological system (SES) framework. They found that this approach enabled a detailed and critical diagnosis of the social, economic and environmental impacts of PES-style policy interventions in a complex social-ecological system such as the Eurasian steppe. In line with the conclusions of the former paper’s assumptions, this review explicitly identified the importance of micro-economics and cultural values for the design and viability of ‘‘payment for ecosystem services’’ schemes. Niu et al. (2016) stress the importance of analyses based on plant functional traits in the evaluation of grazing effects on rangeland biodiversity. Based on the analysis of five leaf traits, they suggest that in Tibetan alpine meadows grazing tends to increase the competition among plant species for soil phosphorus, but decreases the competition for light, resulting in an increase in the functional richness of grazed plant communities. They highlight that the potential importance of grazing is that it mediates the competition for multiple resources in the ecosystems they studied, which should be carefully analysed in the planning of sustainable land use. Novenko et al. (2016) developed a novel view on land use and management in the European forest-steppe zone, based on detailed reconstructions of Mid and Late Holocene vegetation and climate dynamics. They showed that the current forest cover in the form of small patches is a result of high anthropogenic pressures in the past four centuries. Furthermore, climate change will provide competitive advantages to woodlands at the expense of grasslands in the forest-steppe ecotone. Thus their findings underlined the necessity of the preservation of existing grasslands. Conservation status, threats and restoration Temperate grasslands, including Palaearctic steppes, are the most threatened and the least protected terrestrial habitats in the world (Davis et al. 1995; Hoekstra et al. 2005; World Resources Institute 2005). Grasslands host significant levels of biodiversity in human- 123 Biodivers Conserv (2016) 25:2187–2195 2193 mediated landscapes (Gibson 2009). Therefore, conservation and restoration of grassland biodiversity, especially in agricultural landscapes, have been identified as priorities (Dengler et al. 2014; Török et al. 2011). The proportion of protected areas is higher than 10 % in the Palaearctic steppes, but varies largely across regions (Wesche et al. 2016). The identified threats to steppes have not affected the whole biome evenly; priorities in steppe conservation and restoration are therefore likely to vary regionally (Wesche et al. 2016). Deák et al. (2016) and Dembicz et al. (2016) show that in the European part of the steppe and forest steppe zone, only small, fragmented patches of steppe remained. They identified a need for the restoration of steppe habitat to increase landscape-scale connectivity. Deák et al. (2016) suggest that steppe vegetation can persist even in heavily degraded landscapes at certain structures, such as kurgans, road verges, and field margins, which can act as sources of species (i.e. donor sites for restoration). Ambarlı et al. (2016) considered the biodiversity of steppes in the Anatolian Biogeographic Region and concluded that the current area of protected sites, comprising only 1.5 % of that region, is insufficient to preserve its’ biodiversity. They developed a detailed to-do list for conservation authorities, which has the potential to mitigate further biodiversity loss and help to facilitate steppe restoration. Two papers of the Special Issue focus on steppe conservation in Kazakhstan. Kamp et al. (2016) conducted a threat analysis based on a horizon scanning approach. They suggest that the highest-ranked threats to steppe habitats and species are related to changes in land use, the direct persecution of wildlife, and rapid infrastructure development, which has in turn been triggered by rapid economic development and population growth. They also identified some new threats to steppe biodiversity in the form of habitat loss related to a potential future increase in the installation of photovoltaic and wind power stations, to the effects of climate change and changes in agriculture. Brinkert et al. (2016) analysed the restoration potential of abandoned arable land with a focus on the role of grazing. Their results suggest that even after 15–20 years of abandonment, steppe vegetation has not fully recovered on abandoned fields, but the recovery process can be accelerated by particular levels of grazing. In contrast to Europe and parts of Kazakhstan, where a high proportion of the steppes had been converted to cropland, arable farming remained patchy across the Western Siberian forest steppe as many areas are too wet for farming. In consequence, a patchy mixture of meadow steppes, croplands, wetlands, and birch forests, is still found there (Kämpf et al. 2016). Agricultural abandonment had positive consequences for particular plants and the vegetation as a whole ; the vegetation of arable land comprised mostly widely distributed weeds. Assuming an increasing demand for food and fibre, land-use strategies to reconcile biodiversity conservation and food production both for Western Siberia (Kämpf et al. 2016) and for Kazakhstan (Kamp et al. 2015) might rather promote a sustainable intensification of existing croplands rather than a new expansion of cropland into currently abandoned areas. Acknowledgments The Special Issue was planned by all authors of this Editorial and coordinated by J.D. P.T. led the writing of this Editorial to which all authors contributed. We thank all members of the Eurasian Dry Grassland Group (EDGG), particularly our colleagues in the Tula region of Russia, who made the conference possible that gave rise to this Special Issue. We are also indebted to the 100 authors and numerous reviewers of this Special Issue, Editor-in-Chief David L. Hawksworth, and the whole team of Biodiversity and Conservation to make this Special Issue possible. Aiko Huckauf kindly polished our English, while EDGG supported the linguistic editing here and in many of the Special Issue articles. 123 2194 Biodivers Conserv (2016) 25:2187–2195 References Addison J, Greiner R (2016) Applying the social–ecological systems framework to the evaluation and design of payment for ecosystem service schemes in the Eurasian steppe. Biodivers Conserv. doi:10.1007/ s10531-015-1016-3 Ambarlı D, Zeydanlı US, Balkız Ö, Aslan S, Karaçetin E, Sözen M, Ilgaz Ç, Gürsoy Ergen A, Lise Y, Demirbaş Çağlayan S, Welch HJ, Welch G, Turak AS, Bilgin CC, Özkil A, Vural M (2016) An overview of biodiversity and conservation status of steppes of the Anatolian Biogeographical Region. Biodivers Conserv. doi:10.1007/s10531-016-1172-0 Bredenkamp GJ, Spada F, Kazmierczak E (2002) On the origin of northern and southern hemisphere grasslands. Plant Ecol 163:209–229. doi:10.1023/a:1020957807971 Brinkert A, Hölzel N, Sidorova TV, Kamp J (2016) Spontaneous steppe restoration on abandoned cropland in Kazakhstan: grazing affects successional pathways. Biodivers Conserv. doi:10.1007/.s10531-0151020-7 Buri P, Arlettaz R, Humbert JY (2013) Delaying mowing and leaving uncut refuges boosts orthopterans in extensively managed meadows: evidence drawn from field-scale experimentation. Agric Ecosyst Environ 181:22–30. doi:10.1016/j.agee.2013.09.003 Chibilev AA (1998) Basics of steppe science (in Russian). Publisher House DIMUR, Orenburg Davis SD, Heywood VH, Hamilton AC (eds) (1995) Centres of plant diversity: a guide and strategy for their conservation, vol 2., Asia, Australasia and the PacificIUCN, Gland Deák B, Tóthmérész B, Valkó O, Sudnik-Wójcikowska B, Moysiyenko II, Bragina TM, Apostolova I, Dembicz I, Bykov NI, Török P (2016) Cultural monuments and nature conservation: a review of the role of kurgans in the conservation and restoration of steppe vegetation. Biodivers Conserv. doi:10. 1007/s10531-016-1081-2 Dembicz I, Moysiyenko II, Shaposhnikova A, Vynokurov D, Kozub Ł, Sudnik-Wójcikowska B (2016) Isolation and patch size drive specialist plant species density within steppe islands: a case study of kurgans in southern Ukraine. Biodivers Conserv. doi:10.1007/s10531-016-1077-y Dengler J, Janišová M, Török P, Wellstein C (2014) Biodiversity of Palaearctic grasslands: a synthesis. Agric Ecosyst Environ 182:1–14. doi:10.1016/j.agee.2013.12.015 Dengler J, Biurrun I, Apostolova I, Baumann E, Becker T, Becker U, Berastegi A, Boch S, Cancellieri L, Dembicz I, Didukh YP, Dolnik C, Ermakov N, Filibeck G, Garcia-Mijangos I, Giusso del Galdo G, Guarino R, Janišová M, Jaunatre R, Jensen K, Jeschke M, Ka˛cki Z, Kozub Ł, Kuzemko AA, Löbel S, Pedashenko H, Polyakova M, Ruprecht E, Szabó A, Vassilev K, Velev N, Weiser F (2016) Scaledependent plant diversity in Palaearctic grasslands: a comparative overview. Bull Eurasian Dry Grassl Group 31:12–26 Gibson JD (2009) Grasses and grassland ecology. Oxford University, New York Habel JC, Dengler J, Janišová M, Török P, Wellstein C, Wiezik M (2013) European grassland ecosystems: threatened hotspots of biodiversity. Biodivers Conserv 22:2131–2138 Hoekstra JM, Boucher TM, Ricketts TH, Roberts C (2005) Confronting a biome crisis: global disparities of habitat loss and protection. Ecol Lett 8:23–29. doi:10.1111/j.1461-0248.2004.00686.x Humbert JY, Ghazoul J, Richner N, Walter T (2012) Uncut grass refuges mitigate the impact of mechanical meadow harvesting on orthopterans. Biol Conserv 152:96–101. doi:10.1016/j.biocon.2012.03.015 Janišová M, Bartha S, Kiehl K, Dengler J (2011) Advances in the conservation of dry grasslands—introduction to contributions from the 7th European dry grassland meeting. Plant Biosyst 145:507–513. doi:10.1080/11263504.2011.603895 Kajtoch Ł, Cieślak E, Varga Z, Paul W, Mazur MA, Sramkó G, Kubisz D (2016) Phylogeographic patterns of steppe species in Eastern Central Europe: a review and the implications for conservation. Biodivers Conserv. doi:10.1007/s10531-016-1065-2 Kamp J, Urazaliev R, Balmford A, Donald PF, Green RE, Lamb AJ, Phalan B (2015) Agricultural development and the conservation of avian biodiversity on the Eurasian steppes: a comparison of landsparing and land-sharing approaches. J Appl Ecol 52:1578–1587 Kamp J, Koshkin MA, Bragina TM, Katzner TE, Milner-Gulland EJ, Schreiber D, Sheldon R, Shmalenko A, Smelansky I, Terraube J, Urazaliev R (2016) Persistent and novel threats to the biodiversity of Kazakhstan’s steppes and semi-deserts. Biodivers Conserv. doi:10.1007/s10531-016-1083-0 Kämpf I, Mathar W, Kuzmin I, Hölzel N, Kiehl K (2016) Post-Soviet recovery of grassland vegetation on abandoned fields in the forest steppe zone of Western Siberia. Biodivers Conserv. doi:10.1007/s10531016-1078-x Kuzemko AA, Steinbauer MJ, Becker T, Didukh YP, Dolnik C, Jeschke M, Naqinezhad A, Ugurlu E, Vassilev K, Dengler J (2016) Patterns and drivers of phytodiversity of steppe grasslands of Central Podolia (Ukraine). Biodivers Conserv. doi:10.1007/s10531-016-1060-7 123 Biodivers Conserv (2016) 25:2187–2195 2195 Lameris TK, Fijen TPM, Urazaliev R, Pulikova G, Donald PF, Kamp J (2016) Breeding ecology of the endemic Black Lark Melanocorypha yeltoniensis on natural steppe and abandoned croplands in postSoviet Kazakhstan. Biodivers Conserv. doi:10.1007/s10531-015-1041-2 Mathar WP, Kämpf I, Kleinebecker T, Kuzmin I, Tolstikov A, Tupitsin S, Hölzel N (2016) Floristic diversity of meadow steppes in the Western Siberian Plain: effects of abiotic site conditions, management and landscape structure. Biodivers Conserv. doi:10.1007/s10531-015-1023-4 Niu K, He J-S, Zhang S, Lechowicz MJ (2016) Grazing increases functional richness but not functional divergence in Tibetan alpine meadow plant communities. Biodivers Conserv. doi:10.1007/s10531-0150960-2 Novenko EY, Tsyganov AN, Rudenko OV, Volkova EV, Zuyganova IS, Babeshko KV, Olchev AV, Losbenev NI, Payne RJ, Mazei YA (2016) Mid- and late-Holocene vegetation history, climate and human impact in the forest-steppe ecotone of European Russia: new data and a regional synthesis. Biodivers Conserv. doi:10.1007/s10531-016-1051-8 Polyakova MA, Dembicz I, Becker T, Becker U, Demina ON, Ermakov N, Filibeck G, Guarino R, Janišová M, Jaunatre R, Kozub Ł, Steinbauer MJ, Suzuki K, Dengler J (2016) Scale- and taxon-dependent patterns of plant diversity in steppes of Khakassia, South Siberia (Russia). Biodivers Conserv. doi:10. 1007/s10531-016-1093-y Sudnik-Wójcikowska B, Moysiyenko II (2012) Kurgans in the ‘Wild Field’—a cultural heritage and refugium of the Ukrainian steppe. Wydawnictwa Uniwersytetu Warszawskiego, Warszawa Sutcliffe LME, Germany M, Becker U, Becker T (2016) How does size and isolation affect patches of steppe-like vegetation on slumping hills in Transylvania, Romania? Biodivers Conserv. doi:10.1007/ s10531-016-1108-8 Török P, Vida E, Deák B, Lengyel S, Tóthmérész B (2011) Grassland restoration on former croplands in Europe: an assessment of applicability of techniques and costs. Biodivers Conserv 20:2311–2332. doi:10.1007/s10531-011-9992-4 Turtureanu PD, Palpurina S, Becker T, Dolnik C, Ruprecht E, Sutcliffe LME, Szabó A, Dengler J (2014) Scale- and taxon-dependent biodiversity patterns of dry grassland vegetation in Transylvania (Romania). Agric Ecosyst Environ 182:15–24. doi:10.1016/j.agee.2013.10.028 Vrahnakis MS, Janišová M, Rūsin ¸ a S, Török P, Venn S, Dengler J (2013) The European Dry Grassland Group (EDGG): stewarding Europe’s most diverse habitat type. In: Baumbach H, Pfützenreuter S (eds) Steppenlebensräume Europas–Gefährdung, Erhaltungsmaßnahmen und Schutz. Thüringer Ministerium für Landwirtschaft, Forsten, Umwelt und Naturschutz, Erfurt, pp 417–434 Wang Y, Wesche K (2016) Vegetation and soil responses to livestock grazing in Central Asian grasslands: a review of Chinese literature. Biodivers Conserv. doi:10.1007/s10531-015-1034-1 Weking S, Kämpf I, Mathar W, Hölzel N (2016) Effects of land use and landscape patterns on Orthoptera communities in the Western Siberian forest steppe. Biodivers Conserv. doi:10.1007/s10531-016-1107-9 Werger MJA, van Staalduinen MA (eds) (2012) Eurasian steppes. Ecological problems and livelihoods in a changing world. Springer, Dordrecht Wesche K, Ambarlı D, Kamp J, Török P, Treiber J, Dengler J (2016) The Palaearctic steppe biome: a new synthesis. Biodivers Conserv. doi:10.1007/s10531-016-1214-7 White RP, Murray S, Rohweder M (2000) Pilot analysis of global ecosystems: grassland ecosystems. World Resources Institute, Washington Wilson JB, Peet RK, Dengler J, Pärtel M (2012) Plant species richness: the world records. J Veg Sci 23:796–802. doi:10.1111/j.1654-1103.2012.01400.x World Resources Institute (ed) (2005) Ecosystem and human well-being: biodiversity synthesis—A report of the Millennium Ecosystem Assessment. World Resources Institute, Washington 123
https://openalex.org/W2106361373
https://digitalcommons.unmc.edu/cgi/viewcontent.cgi?article=1039&context=com_pathmicro_articles
English
null
Differential effects of interleukin-17 receptor signaling on innate and adaptive immunity during central nervous system bacterial infection
Journal of neuroinflammation
2,012
cc-by
377
Differential effects of interleukin-17 receptor signaling on innate Differential effects of interleukin-17 receptor signaling on innate and adaptive immunity during central nervous system bacterial and adaptive immunity during central nervous system bacterial infection. infection. Differential effects of interleukin-17 receptor signaling on innate Differential effects of interleukin-17 receptor signaling on innate and adaptive immunity during central nervous system bacterial and adaptive immunity during central nervous system bacterial infection. infection. Tell us how you used this information in this short survey. Follow this and additional works at: https://digitalcommons.unmc.edu/com_pathmicro_articles Part of the Medical Microbiology Commons, and the Pathology Commons Tell us how you used this information in this short survey. Follow this and additional works at: https://digitalcommons.unmc.edu/com_pathmicro_articles Part of the Medical Microbiology Commons, and the Pathology Commons Part of the Medical Microbiology Commons, and the Pathology Commons University of Nebraska Medical Center University of Nebraska Medical Center DigitalCommons@UNMC DigitalCommons@UNMC Journal Articles: Pathology and Microbiology Pathology and Microbiology Summer 6-15-2012 Differential effects of interleukin-17 receptor signaling on innate Differential effects of interleukin-17 receptor signaling on innate and adaptive immunity during central nervous system bacterial and adaptive immunity during central nervous system bacterial infection. infection. Debbie Vidlak University of Nebraska Medical Center, dvidlak@unmc.edu Tammy Kielian University of Nebraska Medical Center, tkielian@unmc.edu University of Nebraska Medical Center University of Nebraska Medical Center DigitalCommons@UNMC DigitalCommons@UNMC Journal Articles: Pathology and Microbiology Pathology and Microbiology Summer 6-15-2012 Differential effects of interleukin-17 receptor signaling on innate Differential effects of interleukin-17 receptor signaling on innate and adaptive immunity during central nervous system bacterial and adaptive immunity during central nervous system bacterial infection. infection. Debbie Vidlak University of Nebraska Medical Center, dvidlak@unmc.edu Tammy Kielian University of Nebraska Medical Center, tkielian@unmc.edu University of Nebraska Medical Center University of Nebraska Medical Center DigitalCommons@UNMC DigitalCommons@UNMC Journal Articles: Pathology and Microbiology Journal Articles: Pathology and Microbiology Recommended Citation Recommended Citation Vidlak, Debbie and Kielian, Tammy, "Differential effects of interleukin-17 receptor signaling on innate and adaptive immunity during central nervous system bacterial infection." (2012). Journal Articles: Pathology and Microbiology. 40. https://digitalcommons.unmc.edu/com_pathmicro_articles/40 https://digitalcommons.unmc.edu/com_pathmicro_articles/40 This Article is brought to you for free and open access by the Pathology and Microbiology at DigitalCommons@UNMC. It has been accepted for inclusion in Journal Articles: Pathology and Microbiology by an authorized administrator of DigitalCommons@UNMC. For more information, please contact digitalcommons@unmc.edu.
https://openalex.org/W4327814654
https://link.springer.com/content/pdf/10.1007/s13132-023-01251-7.pdf
English
null
Innovation Business Model Based on New Technologies and Company Relationships
Journal of the knowledge economy
2,023
cc-by
10,161
Journal of the Knowledge Economy (2024) 15:2341–2360 https://doi.org/10.1007/s13132-023-01251-7 Journal of the Knowledge Economy (2024) 15:2341–2360 https://doi.org/10.1007/s13132-023-01251-7 Innovation Business Model Based on New Technologies and Company Relationships Adam Dymitrowski1   · Paweł Mielcarek2 Received: 24 January 2022 / Accepted: 24 February 2023 / Published online: 18 March 2023 © The Author(s) 2023 * Adam Dymitrowski adam.dymitrowski@ue.poznan.pl Extended author information available on the last page of the article * Adam Dymitrowski adam.dymitrowski@ue.poznan.pl Extended author information available on the last page of the article Introduction Currently, one way for companies to build a competitive position is to implement business model innovation (BMI). According to Hutahayan and Wahyono (2019, p. 264), BMI “is an organizational innovation through which firms explore new ways to define value proposition, create and capture value for customers, suppli- ers and partners.” With access to new technologies now available, some compa- nies try to implement a special type of BMI— BMI based on new technologies. As stated by Minatogawa et  al., (2020, p. 3), “new technologies are responsi- ble for enabling new business models.” In the literature (Adam Dymitrowski & Mielcarek, 2020), a list of what is called “new technology” can be found. These include autonomous robots, simulation, integration of horizontal and vertical sys- tems, Internet of Things, cyber security, cloud, additive production, augmented reality, Big Data, drones, AI, electric vehicles, and blockchain. Therefore, wher- ever in the following paper the term “BMI based on new technologies” is used, it refers to BMI which uses at least one of the technologies mentioned above. In the context of implementing BMI based on new technologies, the role of relationships developed by companies with other entities is important. Accord- ing to Nenonen and Storbacka (2010), successful BMI is characterized not only by proper configuration of the firm’s internal elements but also external adjust- ment of supplier and buyer. A similar point of view is presented by Holloway and Sebastiao (2010, p. 81)according to whom: “successfully implementing a busi- ness model requires the integration of resources, partners, suppliers, customers and other agents into cooperative networks that evolve with market conditions.” Moreover, when considering relationships developed by a company, Dellyana et  al. (2016)state that BMI describes the way of capturing value from entities identified within the network of relationships a company operates in. Similarly, according to Guo et al. (2013), BMI should be perceived as a firm’s purposefully developed network of relationships. Acknowledging this fact is of utmost impor- tance, because different networks of relationship result in different BMI (Delly- ana et al., 2016). Although relationships built with other entities by companies characterized by BMI based on new technologies are important, this problem has not been thor- oughly investigated in the literature and represents a significant research gap. Existence of the research gap in the context of BMI and a company’s relation- ships with other entities is supported by the opinions of some other authors. Abstract Fierce market rivalry between companies has forced a need to search for new ways of competing. One such way is to innovate the company’s business model innovation with the use of new technologies. In order to do so, companies often take advantage of relationships with different market actors. Although the existing literature pro- vides some general insight on this matter, there is still a significant research gap concerning the use of specific market actors by companies characterized by BMI based on new technologies. The aim of the paper is to assess the role of relationships developed by companies characterized by BMI based on new technologies with different types of entities. In order to achieve the aim of the paper, it was decided to perform both qualitative and quantitative research. For the qualitative research, a focus study with 12 participants was performed, and for the quantitative study, a computer-assisted telephone interview (CATI) with representatives from 483 companies was carried out. The data collection method included not only primary sources (interviews with managers) but secondary sources (e.g., company materi- als) as well. The main conclusion drawn from the presented research is that it is beneficial (in terms of technology as well as performance indicators — profits, sales, market share, and ROI) for companies characterized with BMI based on new tech- nologies to develop relationships with various types of entities. These various types should not only include suppliers or buyers, but competitors, the company’s internal and external units, universities and research centers, financing agencies, and govern- ment or local government administration as well. The results presented in the paper add significant value to the existing knowledge. Not only is the paper one of a few which touch on the matter of relationships developed by companies characterized by BMI based on new technologies, it also provides new information. It adds a new block to the theories of open innovation and resource-based view. Keywords  Business model innovation · New technology · Business relationships 456789) 3 456789) 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2342 Introduction For example, in the context of the engagement of different entities in the BMI pro- cess, Roth et al., (2021) state: “Yet, there is no clear indication of what role these actors play /…/. It is also unclear how these actors engage /…/.” Carayannis et al., (2015) provide insights in a similar manner: “the role of the value chain network has not been discussed /and/ would certainly be of value to explore.” When con- sidering BMI and companies’ external relationships, Velter et al., (2021) point out: “Research to understand the processes /…/ is only in its infancy”. The research gap was also identified by Foltean and Glovaţchi (2021, p. 392) who examined BMI in the context of one of the new technologies: “despite the need 1 3 1 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2343 /…/ to renew their business models to effectively create value for customers and capture value for the company, the strategic factors of business model innova- tion for IoT solutions have remained under-researched so far.” All these opinions indicate that in the context of BMI companies, information on the character and essence of relationships they develop with other entities has been underestimated so far.i The existence of a significant research gap in the context of BMI, new technolo- gies, and business relationships motivated the present authors to research this prob- lem. Thus, the aim of the paper is to assess the role of relationships developed by companies characterized by BMI based on new technologies. Following the Introduction, the paper is divided into six sections. The “Literature Review” section provides a critical analysis of the literature and highlights the main issues of the researched phenomenon. The “Methodology” section describes the applied research methods and the stand adopted. The outcomes of the study are pre- sented in the “Results” section. In the “Discussion” section, the results of the study are compared with the literature. The “Conclusions section” sums up the added value provided by the paper and provides recommendations both for representatives of science and business practice. The “References” section contains the list of lit- erature sources of information. The source of funding is provided in the “Funding”. Literature Review The phenomenon of relationships developed by companies characterized by BMI based on new technologies can be related to at least two management theories, namely, open innovation and the resource-based view (RBV). The theory of open innovation asserts that in order to build competitive advan- tage, companies should not steer away from innovation which is widely available, but should in fact acquire it from other entities. Open innovation stands in contrast to the traditionally secret and independent manner of developing innovation by compa- nies which used to serve as the basis for the closed innovation approach (Innovation 1.0). Open innovation theory changes the perception of boundaries existing between a company and entities identified within its environment which became less conven- tional and shaped a new way of perceiving innovation treated as a result of company interactions with other entities (Innovation 2.0). According to H. W. Chesbrough (2003), open innovation is: “a paradigm that assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to market, as the firms look to advance their technology.” This fact is extremely important for companies characterized by BMI based on new technologies. While their competi- tive advantage is based on BMI which make use of technology, companies charac- terized by BMI based on new technologies should avidly draw from other entities in order to increase their innovativeness.i In the context of open innovation, special attention should be paid to a specific change caused by the rise of the digital economy which has resulted in the creation of a new generation of innovation — embedded innovation (Innovation 3.0). To sur- vive in a highly competitive digitalized environment, companies build relationships 1 3 3 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2344 to aligned communities, networks, and stakeholders (Hafkesbrink & Evers, 2010) therefore becoming embedded in an environment with many different types of actors. In that sense, Innovation 3.0 builds on open innovation by conceptually embracing organizational capabilities in order for the company to be successfully embedded in a network of relationships (O’Reilly & Tushman, 2008). Literature Review The nature of embeddedness is determined by both implicit, e.g., trust culture (Hafkesbrink & Evers, 2010) and explicit (e.g., formal contracts) factors as well as explorative or exploitative, organic or mechanic factors (Tushman et al., 2003), depending on the nature and phase of the innovation process and the characteristics of the relation- ships. According to open innovation theory seen from the perspective of Innova- tion 3.0, there is no focal company which manages open innovation processes. On the contrary, open innovation processes are run by multiple actors at the same time (Hafkesbrink & Schroll, 2011).i As far as multiple actors are concerned in the literature, some specific entities are believed to be important in the case of business model innovation. These include suppliers, buyers, competitors, a company’s internal and external units, universities and research centers, financing agencies, government or local government admin- istration (Al-Nimer et al., 2021; Bao et al., 2021; Burton et al., 2021; Adam Dym- itrowski, 2017; Hao-Chen et al., 2013; Ricciardi et al., 2016; Siachou & Ioannidis, 2010). Since these types of entities are important for BMI, they are also vital for BMI based on new technologies. It has to be noted, however, that it is difficult to find sources in the literature that specifically discuss the role of different entities in reference to BMI based on new technologies. For this reason, the present discussion is based mainly on the literature concerning BMI in general, but whenever possible, references to BMI based on new technologies are made.l Information provided in the literature points out the positive influence of devel- oping relationships on companies characterized by BMI based on new technolo- gies. This positive influence is reflected in many benefits that companies gain from relationships such as knowledge (Yang et al., 2020), access to financial funds (Ensley et al., 2002), etc. However, there are still many unknowns and questions which deserve to be answered. One of those questions refers to the relevance of the wide range of different entities identified in the literature that companies charac- terized with BMI based on new technologies can develop relationships with. Are they equally important or do some entities play a greater role than others? Literature Review As there were so little information to be found in the literature on the comparison between relationships with different types of entities for companies characterized with BMI based on new technologies it was decided to examine this matter. This led to the for- mulation of the following research question. RQ1: How relevant are relationships with specific types of entities for companies characterized with BMI based on new technologies? Secondly, because of technology, the phenomenon of relationships developed by companies characterized by BMI based on new technologies with different types of entities is also related to the resource-based view (RBV) theory. The RBV the- ory asserts that a company’s competitive advantage is determined by its strategic 1 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2345 resources. Strategic resources could be assets that the company holds as well as their capabilities and competencies (Prahalad & Hamel, 1990). Because every company is characterized by a different set of strategic resources, they implement different strat- egies to utilize them and present different levels of competitive advantage. Accord- ing to RBV, the role of company managers is to identify those assets, capabilities and competencies and to develop them so as to outperform their competitors. This can be achieved when strategic resources are unique, firm-specific and not easily imitated or substituted, which enables companies to perform activities in a manner different from other market players (Hooley et al., 1998). resources. Strategic resources could be assets that the company holds as well as their capabilities and competencies (Prahalad & Hamel, 1990). Because every company is characterized by a different set of strategic resources, they implement different strat- egies to utilize them and present different levels of competitive advantage. Accord- ing to RBV, the role of company managers is to identify those assets, capabilities and competencies and to develop them so as to outperform their competitors. This can be achieved when strategic resources are unique, firm-specific and not easily imitated or substituted, which enables companies to perform activities in a manner different from other market players (Hooley et al., 1998). f This fact implies that not all types of resources are of equal importance for a company’s competitive advantage (Fahy & Smithee, 1999). In the case of compa- nies characterized by BMI based on new technologies, the technology used is of key importance. Literature Review In line with RBV assumptions, the more unique the set of technology that companies characterized by BMI based on new technologies utilize, the more innovative they are and the greater competitive advantage they have. In the literature (Foltean & Glovaţchi, 2021), it is stated that relationships devel- oped by companies characterized by BMI based on new technologies could result in the absorption of technology. However, the scope of this absorption remains unclear. Do companies characterized with BMI based on new technologies tend to expand their pool of technology or on the contrary — do they focus on selected types of technology? This gap in the research led to the formulation of the following research question. RQ2: How do relationships developed by companies characterized with BMI based on new technologies affect their technology pool? Last but not least, with respect to both open innovation and RBV, it is still unclear how the benefits gained thanks to both relationships developed with different types of entities as well as technology and affect the performance of companies character- ized with BMI based on new technologies, as described in the literature (Al-Nimer et al., 2021; Bao et al., 2021; Burton et al., 2021; Hao-Chen et al., 2013; Ricciardi et al., 2016). As stated by Adam Dymitrowski and Mielcarek (2021, p. 2110): “the existing literature identifies the effects /…/ but neglects to examine how these effects are reflected in company performance indicators.” Taking these facts into considera- tion, the third research question was formulated: RQ3: How do relationships developed by companies characterized with BMI based on new technologies influence their performance? RQ3: How do relationships developed by companies characterized with BMI based on new technologies influence their performance? Each of the three formulated research questions address the aim of the study — to assess the role of relationships developed by companies characterized by BMI based on new technologies. In this sense, the role of relationships for companies character- ized by BMI based on new technologies is understood in the context of the relevance and added value provided by specific actors, how they affect the technology pool of companies characterized by BMI based on new technologies as well as the role played in influencing their performance. 1 3 2346 Journal of the Knowledge Economy (2024) 15:2341–2360 It has already been shown that companies characterized with BMI based on new technologies can build relationships with different entities. These relationships can be beneficial in many ways. In the the opinion of H. Chesbrough and Schwartz (2007), relationships can grant access to the resources necessary for BMI. In the case of companies characterized with BMI based on new technologies, one type of resource is especially important — technology. Therefore, acknowledging the assumptions of open innovation theory and RBV, it seems that companies character- ized with BMI based on new technologies can utilize relationships with different types of entities in order to gain access to a number of technologies.i Taking these facts into consideration, the first hypothesis (H1) states that the greater the role of relationships built with different types of entities, the more tech- nologies companies characterized with BMI based on new technologies use. Technology absorbed by companies characterized with BMI based on new tech- nologies from different entities could be a valuable resource. However, technology is not the only benefit companies characterized with BMI based on new technolo- gies could receive from relationships with different types of entities. Technology is acknowledging the assumptions of open innovation theory and RBV, merely a tool to obtain favorable performance by companies. In this context, it is important to note that the purpose of developing relationships with different entities by companies is to perform better (Adam Dymitrowski, 2012), and this is indicated by the perfor- mance indicators. Taking these facts into consideration, the second hypothesis (H2) states that the greater the role of relationships built with different types of entities by companies characterized with BMI based on new technologies, the better the company perfor- mance indicators. RQ3: How do relationships developed by companies characterized with BMI based on new technologies influence their performance? Answering the three formulated research questions and verifying the two formu- lated research hypotheses will help to achieve the aim of the paper as well as add value to the theories of open innovation and RBV. Methodology Both sessions were based on a standardized interview questionnaire with 6 open questions referring to aspects such as the nature of relationships developed with different types of entities and per- formance indicators of BMI companies as well as one task which required inter- viewers to describe the companies’ BMI with a business model canvas. Both focus panel sessions were recorded, and transcripts were prepared. The analysis was then based on these transcripts. The analysis was performed using the specialist software — Altlas.ti. In order to ensure objectivity and provide high-quality information, the primary data were triangulated (Yin, 2009) with secondary data (such as materials about the companies available on the Internet). Therefore, the method of data col- lection included not only primary sources (interviews with managers) but secondary sources (e.g., company materials) as well. — Altlas.ti. In order to ensure objectivity and provide high-quality information, the primary data were triangulated (Yin, 2009) with secondary data (such as materials about the companies available on the Internet). Therefore, the method of data col- lection included not only primary sources (interviews with managers) but secondary sources (e.g., company materials) as well. — Altlas.ti. In order to ensure objectivity and provide high-quality information, the primary data were triangulated (Yin, 2009) with secondary data (such as materials about the companies available on the Internet). Therefore, the method of data col- lection included not only primary sources (interviews with managers) but secondary sources (e.g., company materials) as well. The second stage of the study took the form of quantitative research. The motiva- tion for choosing quantitative research was taken from the literature. For example, Bashir and Verma (2017) and Clauss (2017) point out that in case of future research on BMI, a quantitative approach should be used to enrich results from the existing qualitative studies. The method of the quantitative study was computer-assisted telephone interview (CATI). This method was chosen for a few reasons (Ragozzino et al., 2012). Firstly, it allows data to be gathered from many participants which makes the study reliable. Secondly, it allows any doubts of the interviewees to be dispelled by the interview- ers during the interview. Thirdly, the use of CATI allows information to be obtained from impenetrable sources such as companies characterized with BMI based on new technologies. Thus, CATI provides high-quality research data (Scandura & Wil- liams, 2000). During the interviews, a standardized survey questionnaire was used. Methodology In order to achieve the aim of the paper, answer the three questions posed, and verify the two research hypotheses; it was decided to perform a two-stage study.i The first stage of the study was qualitative research. The authors used the focus study method to collect raw data. Morgan (1998) defines focus study as a research technique where information necessary for the purposes of the study are collected by a researcher through interaction with a group of participants. It was decided to use focus study for a couple of reasons (Babbie & Benaquisto, 2013): (1) little time needed in order to collect information, (2) complementary to quantitative methods, (3) no requirements for large financial outlays. i To conduct the research, interviewers were selected from companies character- ized with BMI based on new technologies. In order for the company to be consid- ered as a company characterized with BMI based on new technologies two criteria needed to be met: (1) using at least one of the technologies: autonomous robots, simulation, integration of horizontal and vertical systems, Internet of Things, cyber 1 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2347 security, the cloud, additive production, augmented reality, Big Data; (2) positive answer to a filter question: “Is your company characterized with an innovative and unique way of doing business?”. The nature of the filter question was consistent with the essence of BMI definitions existing in the literature (Eppler & Hoffmann, 2011; Foss & Saebi, 2016; Katsamakas & Pavlov, 2020). Interviewers were selected only from top management staff, as they have the greatest knowledge on how the company operates; this is important in researching the phenomenon of BMI. While BMI refers to the manner of doing business which encompasses the whole company (Saur-Amaral et al., 2016), only top managers could answer questions about differ- ent aspects of BMI. Twelve independent interviewees took part in the focus study. In order to ensure efficiency in collecting information; interviewees were randomly divided into two groups (each consisting of six persons). Thus the focus study was performed in two separate focus panels, each of them lasting around 90 min. In order to coordinate the merit value of the study in both sessions, a professional moderator with experi- ence in qualitative methods facilitated the discussions. Methodology Questions in the questionnaire referred to types of technology that the firm uses, relationships with different entities, or performance indicators. In the case of performance indi- cators, both financial and non-financial indicators (profit, sales, market share, ROI) assessed on a 5-point Likert scale in comparison with the company’s competitors were used. Choosing these specific company performance indicators was supported 3 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2348 with conclusions from the qualitative stage and is approved in the literature on inno- vation (Adam Dymitrowski, 2014; Smajlović et al., 2019). In order to constitute a research sample, 3500 companies located in Poland were selected from the Bisnod database. Research sample selection criteria included: • Using at least one of the new technologies (autonomous robots, simulation, integration of horizontal and vertical systems, Internet of Things, cyber security, cloud, additive production, augmented reality, Big Data, drones, AI, electric vehi- cles and blockchain1 • Using at least one of the new technologies (autonomous robots, simulation, integration of horizontal and vertical systems, Internet of Things, cyber security, cloud, additive production, augmented reality, Big Data, drones, AI, electric vehi- cles and blockchain1 • Providing contact information to representatives of top management Providing contact information to representatives of top management was impor- tant, because (as explained before) only top managers have the full knowledge of how the company operates in the market and a full picture of the BMI. The 3500 companies were subjected to further selection in order to single out companies char- acterized with BMI. A filter question: “Does your company have an innovative busi- ness model which means a novel and unique way of doing business?”2 was used for this purpose. A positive answer to the filter question qualified a company to take part in the survey. This narrowed down the field to 483 companies when then took part in the survey. The study was performed between January 8th and January 14th, 2021. In the second stage of the study (quantitative research), the method of data collection included only primary sources (interviews with managers). In order to verify whether the data gathered for the quantitative study were affected by common method bias (Palmatier, 2016), Harman’s single-factor test was performed. 1  Taking into consideration results of the first (qualitative) stage of research in the second (quantitative) stage, it was decided to consider drones, AI, electric vehicles, and blockchain as new technologies as well. 2  Taking into consideration results of the first(qualitative) stage of research in the second (quantitative) stage, the filter question was slightly reformulated in order to efficiently identify BMI companies. Methodology All the variables used for the study were subjected to factor analysis with the principal axis factoring method and unrotated factor solution in order to identify if one general factor accounts for more than 50% of the co-variation (MacKenzie & Podsakoff, 2012). One general factor accounted for 24.37% of the total variance. This means that the research is not affected by common method bias. Results In order to answer the first research question (RQ1) which states: “How relevant are relationships with specific types of entities for companies characterized with BMI based on new technologies?”, the results of the qualitative stage of the study were considered first. Interviewees, when asked about the role of relationships with spe- cific types of entities in case of companies characterized with BMI based on new technologies, confirmed that suppliers, buyers, competitors, the company’s internal 1 3 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2349 units, universities and research centers, and financing agencies are important. When it comes to suppliers one of the interviewers said: “We had such a need from cli- ents to quickly implement /…/ and then we faced many questions /…/ We started looking for partners who would be able to add competences in various areas.” This means that relevance of suppliers translates into being engaged in the creation of BMI based on new technologies. In this sense, suppliers provide expert competen- cies which help to generate added value for BMI purposes. When it comes to buyers one of the interviewers said: “Did those partners, or our partners, our clients have any part in creating our business model? Probably yes, indirectly. Well, above all they had a need, so they had some influence on the creation of our business model.” This means that relevance of buyers translates into directing the changes necessary for BMI based on implementation of new technologies. By analyzing buyers’ needs, a company identifies the existing demand and adjusts its BMI accordingly. When it comes to competitors one of the interviewers said: “I would say to the competition /…/ they started doing pretty similar things /…/ and this is where an interesting race took place.” This means that relevance of competitors translates into motivating the implementation of BMI based on new technologies. It also provides a benchmark for the company which can be used to either innovate the existing business model or fur- ther improve BMI based on new technologies. When it comes to a company’s inter- nal units, one of the interviewers said: “In our company every employee undergoes mandatory /…/ training. Quarterly, there are newer and more advanced trainings.” This means that relevance of internal units (similar to suppliers) translates into pro- viding added value (in terms of competencies) to BMI based on new technologies. Results Deviation Buyers 483 3.69 0.915 Competitors 483 3.66 0.944 Company’s internal units 483 3.58 1.055 Suppliers 483 3.44 1.052 Company’s external units 483 3.41 1.013 Financing agencies 483 3.32 1.057 Universities/research centers 483 3.26 1.080 Government or local govern- ment administration 483 3.24 1.032 Valid N 483 by companies characterized with BMI based on new technologies is presented in Table 1.i Findings from the information in Table 1 reveal that firstly relationships with a company’s external units as well as government or local government administration (which were not identified as relevant in the case of the qualitative study) appeared to be important for companies characterized by BMI based on new technologies, while each of the mean scores exceeded 3 (which referred to “no opinion”). Sec- ondly, relationships with different entities are not equally important for companies characterized by BMI based on new technologies. The type of entities which play the greatest role for companies characterized by BMI based on new technologies are buyers and the ones which play the smallest role are government or local govern- ment administration (however, they are still relevant). Thirdly, the fact that mean scores may seem to be similar is caused by a small dispersion of the minimum and maximum rating scale (1–5). However, the difference in means of entities with the greatest (buyers) and smallest (government or local government administration) roles is 0.45 which represents a high significance. i In order to answer the second research question (RQ2) which states: “How do relationships developed by companies characterized with BMI based on new tech- nologies affect their technology pool?” and verify the first hypothesis (H1), which states: “The greater the role of relationships built with different types of entities, the more technologies companies characterized with BMI based on new technologies use,” companies were divided into clusters. Identification of clusters was based on companies’ similarity to each other in terms of the significance of relationships with different types of entities. For identification, cluster analysis was performed using the Ward’s method for binary variables. The square of the Euclidean distance was taken as the measure of distance. The division into clusters was made on the basis of a dendrogram. Two clusters of companies were identified. There were 148 compa- nies (30.6%) in the first cluster and 335 companies (69.4%) in the second cluster. Results When it comes to universities and research centers one of the interviewers said: “We were contacted by a polytechnic which was planning a project with another techno- logical partner and they needed a company with more or less our skills.” This means that relevance of universities translates into providing complementary competen- cies and thus creating new forms of cooperation. Such cooperation could take the form of strategic partnership and result in BMI based on new technologies. When it comes to financing agencies one of the interviewers said: “The first project, now the second – are co-financed from EU funds.” This means that relevance of financing agencies translates into providing resources necessary to implement BMI based on new technologies. While both innovative and technological activities are financially demanding, such a role is especially important in the case of SMEs. The performed qualitative study did not confirm the relevance of entities such as The performed qualitative study did not confirm the relevance of entities such as a company’s external units or government or local government administration. None of the interviews considered these entities as relevant in the context of relationships developed by companies characterized with BMI based on new technologies. How- ever, having considered the results existing in the literature (A Dymitrowski & Rata- jczak-Mrozek, 2019; Maglio & Spohrer, 2013), it was decided to include these types of entities in the quantitative stage of research.i In order to enrich the results of the qualitative study and answer the first research question (RQ1) “How relevant are relationships with specific types of entities for companies characterized with BMI based on new technologies?” in a comprehen- sive manner, the results of the quantitative stage of study were considered. The assessment of relevance of relationships developed with specific types of entities 1 3 3 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2350 Table 1   Relevance of relationships developed with specific types of entities by companies characterized with BMI based on new technologies 1, not relevant at all; 2, irrelevant; 3, no opinion; 4, relevant; 5, very relevant. N Mean Std. Table 1   Relevance of relationships developed with specific types of entities by companies characterized with BMI based on new technologies Results In order to compare the two clusters in terms of role of relationships built with differ- ent types of entities, a Mann–Whitney U test was performed (Tables 2 and 3). 1 3 1 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2351 Table 2   Comparisons of two clusters in terms of role of relationships built with different types of entities Ward method N Mean rank Sum of ranks Suppliers 1 148 127.71 18,900.50 2 335 292.49 97,985.50 Total 483 Buyers 1 148 176.75 26,159.00 2 335 270.83 90,727.00 Total 483 Competitors 1 148 154.61 22,882.00 2 335 280.61 94,004.00 Total 483 Company’s internal units 1 148 138.21 20,455.00 2 335 287.85 96,431.00 Total 483 company’s external units 1 148 126.50 18,722.00 2 335 293.03 98,164.00 Total 483 Universities/research centers 1 148 112.97 16,720.00 2 335 299.00 100,166.00 Total 483 Financing agencies 1 148 126.75 18,759.50 2 335 292.91 98,126.50 Total 483 Government or local government administration 1 148 115.15 17,042.50 2 335 298.04 99,843.50 Total 483 Two observations can be deduced from the information in Tables 2 and 3. Firstly, the mean ranks of all types of entities were higher in the case of companies from cluster 2 in comparison to companies from cluster 1. This means that companies from cluster 2 assess the role of relationships built with all types of entities higher than companies from cluster 1. Secondly, test statistics proved the statistical signifi- cance (p < 0.001) of the results for all types of entities.i In order to answer RQ2 and verify H1, the two identified clusters of companies were compared from the perspective of new technology utilization. Table 4 presents their characteristics. From the information presented in Table  4, it can be deduced that companies from cluster 1 more frequently (in comparison to companies from cluster 2) use the following technologies: cyber security and cloud. On the other hand, compa- nies from cluster 2 more frequently (in comparison to companies from cluster 1) use the following technologies: autonomous robots, simulation, integration of horizon- tal and vertical systems, IoT, additive production, augmented reality, Big Data, AI, electric vehicles, drones and blockchain. 1 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2352 able 3   Test statistics for Table 2 . Results Grouping variable: Ward method Suppliers Buyers Competitors Company’s internal units Company’s external units Universities/ research centers Financing agencies Government or local government adminis- tration Mann–Whitney U 7874.500 15,133.000 11,856.000 9429.000 7696.000 5694.000 7733.500 6016.500 Wilcoxon W 18,900.500 26,159.000 22,882.000 20,455.000 18,722.000 16,720.000 18,759.500 17,042.500 Z  − 12.625  − 7.286  − 9.758  − 11.551  − 12.786  − 14.107  − 12.620  − 13.959 Asymp. sig. (2-tailed) 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Table 3   Test statistics for Table 2 i i bl d h d Suppliers Buyers Competitors Company’s internal units Company’s external units Universities/ research centers Financing agencies Government or local government adminis- tration Mann–Whitney U 7874.500 15,133.000 11,856.000 9429.000 7696.000 5694.000 7733.500 6016.500 Wilcoxon W 18,900.500 26,159.000 22,882.000 20,455.000 18,722.000 16,720.000 18,759.500 17,042.500 Z  − 12.625  − 7.286  − 9.758  − 11.551  − 12.786  − 14.107  − 12.620  − 13.959 Asymp. sig. (2-tailed) 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1 3 1 3 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2353 Table 4   Characteristics of the two identified clusters Clusters 1 (N = 148) 2 (N = 335) New technologies Autonomous robots 17.57% 20.30% Simulation 16.22% 40.60% Integration of horizontal and verti- cal systems 12.84% 27.16% IoT 29.73% 40.90% Cyber security 58.78% 43.28% Cloud 60.14% 56.12% Additive production 10.81% 17.01% Augmented reality 4.73% 16.72% Big Data 14.19% 33.73% AI 11.49% 19.40% Electric vehicles 5.41% 11.64% Drones 3.38% 7.76% Blockchain 4.05% 4.48% What is important is that in 11 out of 13 cases, companies from cluster 2 more frequently use specific new technologies than companies from cluster 1. Therefore, it is justified to state that companies from cluster 2 use more technologies than com- panies from cluster 1. Summing up the information provided in Tables 2, 3, and 4, it must be acknowl- edged that for companies from cluster 2 the role of relationships built with differ- ent types of entities is greater compared to companies from cluster 1. Additionally, companies from cluster 2 use more technologies than companies from cluster 1. Therefore, it can be stated that the greater the role of relationships built with dif- ferent types of entities, the more technologies companies characterized with BMI based on new technologies use; this means that H1 is supported.i Positive verification of H1 helped to answer RQ2. Results It transpires that relation- ships developed by companies characterized with BMI based on new technologies affect their technology pool in a positive way. This means that they help to increase the technology pool used by companies characterized with BMI based on new technologies. In order to answer the third research question (RQ3) which states: “How do rela- tionships developed by companies characterized with BMI based on new technolo- gies influence their performance?” and verify the second hypothesis (H2), which states: “The greater the role of relationships built with different types of entities by companies characterized with BMI based on new technologies, the better the com- pany performance indicators.” As in the case of the first hypothesis, a Mann–Whit- ney U test was performed (Tables 5 and 6). This helped to compare the clusters in terms of different company performance indicators. f Again, two observations can be deduced from the information in Tables 5 and 6. Firstly, the mean ranks of all company performance indicators (profit, sales, market 1 3 3 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2354 Table 5   Comparison of two clusters in terms of company performance indicators Ward method N Mean rank Sum of ranks Profit 1 148 207.04 30,642.50 2 335 257.44 86,243.50 Total 483 Sales 1 148 199.34 29,502.00 2 335 260.85 87,384.00 Total 483 Market share 1 148 203.61 30,134.50 2 335 258.96 86,751.50 Total 483 ROI 1 148 186.60 27,617.00 2 335 266.47 89,269.00 Total 483 Ward method N Mean rank Sum of ranks Profit 1 148 207.04 30,642.50 2 335 257.44 86,243.50 Total 483 Sales 1 148 199.34 29,502.00 2 335 260.85 87,384.00 Total 483 Market share 1 148 203.61 30,134.50 2 335 258.96 86,751.50 Total 483 ROI 1 148 186.60 27,617.00 2 335 266.47 89,269.00 Total 483 Ward method N Mean rank Sum of ranks Table 6   Test statistics for Table 5 a. Grouping variable: Ward method Profit Sales Market share ROI Mann–Whitney U 19,616.500 18,476.000 19,108.500 16,591.000 Wilcoxon W 30,642.500 29,502.000 30,134.500 27,617.000 Z  − 4.017  − 4.815  − 4.358  − 6.251 Asymp. sig. (2-tailed) 0.000 0.000 0.000 0.000 Table 6   Test statistics for Table 5 share, and ROI) were higher in the case of companies from cluster 2 compared to com- panies from cluster 1. This means that performance indicators of companies from clus- ter 2 are higher than companies from cluster 1. Results Secondly, test statistics proved the sta- tistical significance (p < 0.001) of the results for all company performance indicators. These two observations justify stating that the greater role of relationships built with different types of entities by companies characterized with BMI based on new tech- nologies, the better the company performance indicators. Therefore, H2 is supported.i Positive verification of H2 helped to answer RQ3. It occurs that relationships devel- oped by companies characterized with BMI based on new technologies affect their per- formance in a positive way. This means that they help to improve performance indica- tors of companies characterized with BMI based on new technologies. 1 3 Table 5   Comparison of two clusters in terms of company performance indicators Discussion When comparing the results presented in the paper with the literature, a few aspects should be highlighted. Firstly, it is difficult to discuss the role of relationships devel- oped by companies characterized by BMI based on new technologies with different 1 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2355 types of entities, because of the existence of a significant research gap. Although there are studies which touch on relations of BMI companies in general (e.g., Adam Dymitrowski, 2017), it is difficult to find the research examining both BMI and busi- ness relationships and new technologies with a few exceptions (e.g., Y. Guo et al., 2021; Paiola & Gebauer, 2020) which either concentrated on specific aspects of relationships or specific technologies. i Secondly, the positive role of developing business relationships by companies characterized with BMI based on new technologies presented in the paper is in line with some other research accessible in the literature (different from difficult to be found research examining BMI and business relationships and new technologies at the same time). Results presented in the present paper confirm the benefits of busi- ness cooperation described by Adam Dymitrowski and Soniewicki (2015), the posi- tive influence of BMI on companies’ competitive advantage presented by Siachou and Ioannidis (2010), and the benefits of technology utilization described by Zane and DeCarolis (2016).The results presented in the paper further confirm that posi- tive effects described in case of companies characterized with BMI apply also in the case of companies characterized with BMI based on new technologies. Thirdly, the results presented in the paper about the positive role of relationships seen from the perspective of four different company performance indicators are in line with some other research (Adam Dymitrowski, 2014) which used the same set of indicators in order to assess the effects of a company’s innovativeness as well as (Smajlović et al., 2019) who used 3 out of 4 indicators (profit, sales and market share) to assess BMI efficiency. This fact allows us to have confidence in the results presented in the paper. When discussing the results, it should also be stated that the applied method (cluster analysis using the Ward’s method for binary variables) had a strong influ- ence on the research outcomes. Identifying two clusters of companies allowed a comparison to be made and the role of different entities for each of the clusters to be assessed. Discussion Nevertheless, the conclusions could have been more in-depth if there were more clusters. Perhaps, if more than two clusters had been identified, it would have been possible to grasp the eventual differences in the roles of specific entities. How- ever, the two clusters were what the applied method delivered, and it was accepted by the authors in line with an honest and reliable research stand. Conclusions The aim of the paper was to assess the role of relationships developed by companies characterized by BMI based on new technologies. The aim was achieved by per- forming an extensive empirical study. With the use of both focus study and CATI methods, a large number of companies characterized with BMI based on new tech- nologies were investigated.i The main conclusion from the presented research is that it is beneficial for companies characterized with BMI based on new technologies to develop rela- tionships with various types of entities. These various types should include not only suppliers or buyers, but competitors, the company’s internal and external 3 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2356 units, universities and research centers, financing agencies, and government or local government administration as well. It was empirically proven that the greater the role of relationships built with different types of entities, the more technologies companies characterized with BMI based on new technologies use, which increases their competitiveness. Addi- tionally, the greater the role of relationships built with different types of entities by companies characterized with BMI based on new technologies, the better the company performance in terms of profit, sales, market share, and ROI. i This paper is one of a few researches, with the exception of Y. Guo et  al. (2021) and Paiola and Gebauer (2020), which touch on the matter of relationships developed by companies characterized by BMI based on new technologies. The results presented in the paper add significant value to the existing knowledge by adding new blocks to the theory of open innovation and RBV. In the case of the open innovation theory (H. W. Chesbrough, 2006), the results provide additional value by assessing the relevance of specific types of entities important from the perspective of BMI based on new technologies. It was proven that entities are not equally important for companies characterized with BMI based on new technologies. Although suppliers, buyers, competitors, a company’s internal and external units, universities and research centers, financ- ing agencies, and government or local government administration are all relevant, relationships developed with buyers and competitors are of utmost importance. This fact enriches the theory of open innovation by promoting the development of relationships with competitors. Conclusions Furthermore, the results identify the roles of specific entities engaged in BMI based on new technologies processes therefore helping to better understand open innovation theory seen from the perspective of innovation 3.0 by giving more in-detail information on their embeddedness. In the case of RBV (Fahy & Smithee, 1999; Prahalad & Hamel, 1990), infor- mation presented in the paper helped to identify the influence of relationships on specific types of resources (new technologies). It was proven that relationships help to gain access to technologies such as autonomous robots, simulation, inte- gration of horizontal and vertical systems, IoT, additive production, augmented reality, Big Data, AI, electric vehicles, drones, and blockchain. On the other hand, restricting relationships results in developing cyber security and cloud. Therefore RBV was enriched with the presented results not only by identifying new regu- larities for specific types of companies — those characterized with BMI based on new technologies — but also exploring relationships between relationships and specific new technologies. i Taking into consideration the results, a few recommendations for both researchers and representatives of business practice were suggested. In the case of researchers, it is recommended to research the phenomenon of companies characterized by BMI based on new technologies on large research samples. Only large research samples allow interesting conclusions to be drawn in the case of such complex research subjects. In this research, the CATI method proved to be very efficient. It is therefore recommended to use this type of method, because it allows eventual doubts of interviewees to be dispelled by the interviewer during 1 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2357 the interview and also allows information from impenetrable sources such as companies characterized with BMI based on new technologies to be obtained. the interview and also allows information from impenetrable sources such as companies characterized with BMI based on new technologies to be obtained. In the case of representatives of business practice, it is recommended to engage suppliers and buyers in technology development and BMI implementation. This can be achieved by creating joint project teams. It is also recommended to decrease the rivalry with competitors in favor of cooperation. Such cooperation can be started with activities relating to fields with the lowest level of competition. Conclusions In order to implement BMI based on new technologies, it is recommended to implement employee empowerment programs along with new policies aimed at better and more effective communication. It is also recommended to constantly check the business offer for expertise from universities and research centers, which can act as a source of innovation. Last but not least, it is recommended to build close relationships with financing agencies and government or local government administration by imple- mentation of personalized communication and invite them to company events. All the recommended activities should result in gaining access to new technologies and achieving more favorable market results by companies characterized by BMI based on new technologies.f In the future, it would be interesting to investigate differences in performance indicators resulting from different forms of cooperation (e.g., occasional transac- tions vs. business alliances) of companies characterized by BMI based on new tech- nologies. It would also be interesting to examine the role of relationships built with different types of entities by companies characterized with BMI based on new tech- nologies on different sizes and forms of ownerships and operating in different mar- kets. That is why future research on these aspects is recommended. Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Com- mons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ ses/​by/4.​0/. Funding  The project financed within the Regional Initiative for Excellence program of the Minister of Education and Science of Poland, years 2019–2023, grant no. 004/RID/2018/19, financing 3,000,000 PLN. Babbie, E. R., & Benaquisto, L. (2013). Fundamentals of Social Research. Nelson Education Limited. Bao, H., Wang, C., & Tao, R. (2021). Examining the effects of governmental networking with environ- mental turbulence on the geographic searching of business model innovation generations. Journal of Knowledge Management, 25(1), 157–174. https://​doi.​org/​10.​1108/​JKM-​06-​2020-​0484 References 3rd Economics, Business and Organiza- tion Research Conference, Rome, Italy. Dymitrowski, Adam, & Mielcarek, P. (2020). Business model innovation based on new technologies and companies behavior. Presented at the EBOR Conference. 3rd Economics, Business and Organiza- tion Research Conference, Rome, Italy. y Dymitrowski, A., & Mielcarek, P. (2021). Business model innovation based on new technologies and its influence on a company’s competitive advantage. Journal of Theoretical and Applied Electronic Commerce Research, 16(6), 2110–2128. https://​doi.​org/​10.​3390/​jtaer​16060​118 Dymitrowski, A., & Mielcarek, P. (2021). Business model innovation based on new technologies and its influence on a company’s competitive advantage. Journal of Theoretical and Applied Electronic Commerce Research 16(6) 2110–2128 https://doi org/10 3390/jtaer16060118 Dymitrowski, Adam, & Soniewicki, M. (2015). Companies cooperation in the internationalization pro- cess and their competitive advantage. Presented at the 31st Annual IMP Conference and Doctoral Colloquium, Kolding: University of Southern Denmark. Dymitrowski, Adam, & Soniewicki, M. (2015). Companies cooperation in the internationalization pro- cess and their competitive advantage. Presented at the 31st Annual IMP Conference and Doctoral Colloquium, Kolding: University of Southern Denmark. q g y Dymitrowski, A., & Ratajczak-Mrozek, M. (2019). The changing roles of a multinational enterprise’s subsidiaries and headquarters in innovation transfer: A network perspective. Creativity And Innova- tion Management, 28(4), 550–562. https://​doi.​org/​10.​1111/​caim.​12344 p g Ensley, M., Pearson, A., & Amasone, A. (2002). Understanding the dynamics of new venture top man- agement teams - Cohesion, conflict, and new venture performance. Journal Of Business Venturing, 17(4), 365–386. https://​doi.​org/​10.​1016/​S0883-​9026(00)​00065-3f ( ) p g ( ) Eppler, M. J., & Hoffmann, F. (2011). Challenges and visual solutions for strategic business model inno- vation. In M. Hülsmann & N. Pfeffermann (Eds.), Strategies and communications for innovations: An integrative management view for companies and networks (pp. 25–36). Berlin, Heidelberg: Springer Berlin Heidelberg. https://​doi.​org/​10.​1007/​978-3-​642-​17223-6_3i Fahy, J., & Smithee, A. (1999). Strategic marketing and the resource based view of the firm. y ( ) g g f fi Foltean, F. S., & Glovaţchi, B. (2021). Business model innovation for IoT solutions: An exploratory study of strategic factors and expected outcomes. Amfiteatru Economic, 23(57), 392–411. https://​doi.​org/​ 10.​24818/​EA/​2021/​57/​392 Foss, N. J., & Saebi, T. (2016). Fifteen years of research on business model innovation: How far have we come, and where should we go? Journal of Management, 43(1), 200–227. https://​doi.​org/​10.​1177/​ 01492​06316​675927 Guo, H., Zhao, J., & Tang, J. (2013). The role of top managers’ human and social capital in busi- ness model innovation. Chinese Management Studies, 7(3), 447–469. References Al-Nimer, M., Abbadi, S. S., Al-Omush, A., & Ahmad, H. (2021). Risk management practices and firm performance with a mediating role of business model innovation Observations from Jordan. Journal of Risk & Financial Management, 14(3), 1–20. Babbie, E. R., & Benaquisto, L. (2013). Fundamentals of Social Research. Nelson Education Limited.f Bao, H., Wang, C., & Tao, R. (2021). Examining the effects of governmental networking with environ- mental turbulence on the geographic searching of business model innovation generations. Journal of Knowledge Management, 25(1), 157–174. https://​doi.​org/​10.​1108/​JKM-​06-​2020-​0484 3 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2358 Bashir, M., & Verma, R. (2017). Why Business model innovation is the new competitive advantage. IUP Journal of Business Strategy, 14(1), 7–17. Burton, J., Gruber, T., & Gustafsson, A. (2021). Fostering collaborative research for customer experi- ence-Connecting academic and practitioner worlds. Journal of Business Research, 130, 736–740. https://​doi.​org/​10.​1016/j.​jbusr​es.​2020.​04.​053 p g j j Carayannis, E. G., Sindakis, S., & Walter, C. (2015). Business model innovation as lever of organiza- tional sustainability. Journal of Technology Transfer, 40(1), 85–104. https://​doi.​org/​10.​1007/​ s10961-​013-​9330-y Chesbrough, H. W. (2003). Open innovation: The new imperative for creating and profiting from technol- ogy. In Harvard Business School Press Books (p. 1). http://​search.​ebsco​host.​com/​login.​aspx?​direct=​ true&​db=​bsu&​AN=​11212​912&​lang=​pl&​site=​bsi-​live. Retreived: 12.01.2023 Chesbrough, H. W. (2006). Open business models: How to thrive in the new innovation landscape. In Harvard Business School Press Books (pp. 1–1). Chesbrough, H., & Schwartz, K. (2007). Innovating business models with co-development partnership Research-Technology Management, 50(1), 55–59. https://​doi.​org/​10.​1080/​08956​308.​2007.​11657​41 Clauss, T. (2017). Measuring business model innovation: Conceptualization, scale development, an proof of performance. R&D Management, 47(3), 385–403.f Dellyana, D., Simatupang, T. M., & Dhewanto, W. (2016). Business model innovation in different strate- gic networks. International Journal of Business, 21(3), 191–215. Dymitrowski, Adam. (2012). Cooperation in the internationalization process in relation to company’s innovativeness and success. Presented at the Developing Networks in International Marketing and Purchasing, 5th International IMP Asia Conference, Goa Dymitrowski, Adam. (2014). The role of innovations created in the internationalization process for com- pany performance. Warszawa: Wydawnictwo Naukowe PWN. https://​books.​google.​pl/​books?​id=​ xXhQC​wAAQB​AJ&​lpg=​PA3&​dq=​role%​20of%​20inn​ovati​on%​20cre​ated%​20in%​20the%​20int​ernat​ ional​izati​on&​hl=​pl&​pg=​PA162#v=​onepa​ge&q=​role%​20of%​20inn​ovati​on%​20cre​ated%​20in%​ 20the%​20int​ernat​ional​izati​on&f=​false. Retreived: 9.03.2023f Dymitrowski, Adam. (2017). Business model innovation and relationships with different entities. Annual International Conference on Innovation & Entrepreneurship, 83–90. Dymitrowski, Adam. (2017). Business model innovation and relationships with different entities. Annual International Conference on Innovation & Entrepreneurship, 83–90. Dymitrowski, Adam, & Mielcarek, P. (2020). Business model innovation based on new technologies and companies behavior. Presented at the EBOR Conference. References https://​doi.​org/​10.​1108/​ CMS-​03-​2013-​0050 1 1 3 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2359 Guo, Y., Zhu, Y., & Chen, J. (2021). Business model innovation of IT-enabled customer participating in value co-creation based on the affordance theory: A case study. Sustainability, 13(10), 5753. https://​ doi.​org/​10.​3390/​su131​05753 g Hafkesbrink, J., & Evers, J. (2010). Innovation 3.0 – Embedding into community knowledge: the rel- evance of trust as enabling factor for collaborative organizational learning. In Competence Manage- ment for Open Innovation – Tools and IT-Support to Unlock the Potential of Open Innovation. Eul Verlag. Hafkesbrink, J., & Schroll, M. (2011). Innovation 3.0: Embedding into community knowledge - Collabo- rative organizational learning beyond open innovation. Journal of Innovation Economics & Man- agement, 7(1), 55–92. https://​doi.​org/​10.​3917/​jie.​007.​0055 Hao-Chen, H., Mei-Chi, L., Lee-Hsuan, L., & Chien-Tsai, C. (2013). Overcoming organizational iner- tia to strengthen business model innovation: An open innovation perspective. Journal of Organiza- tional Change Management, 26(6), 977–1002. https://​doi.​org/​10.​1108/​JOCM-​04-​2012-​0047 Holloway, S. S., & Sebastiao, H. J. (2010). The role of business model innovation in the emergence of markets: A missing dimension of entrepreneurial strategy? Journal of Strategic Innovation & Sus- tainability, 6(4), 80–95. y Hooley, G., Broderick, A., & Möller, K. (1998). Competitive positioning and the resource-based view of the firm. Journal of Strategic Marketing, 6(2), 97–116. https://​doi.​org/​10.​1080/​09652​54980​00000​03 i Hutahayan, B., & Wahyono. (2019). A review and research agenda in business model innovation. Inter- national Journal of Pharmaceutical and Healthcare Marketing, 13(3), 264–287. https://​doi.​org/​10.​ 1108/​IJPHM-​12-​2017-​0073 Katsamakas, E., & Pavlov, O. (2020). AI and business model innovation: Leverage the AI feedback loop Journal of Business Models, 8(2), 22–30.f MacKenzie, S. B., & Podsakoff, P. M. (2012). Common method bias in marketing: Causes, mechanisms, and procedural remedies. Journal of Retailing, 88(4), 542–555. https://​doi.​org/​10.​1016/j.​jretai.​2012.​ 08.​001 Maglio, P., & Spohrer, J. (2013). A service science perspective on business model innovation. INDUS- TRIAL MARKETING MANAGEMENT, 42(5), 665–670. https://​doi.​org/​10.​1016/j.​indma​rman.​2013.​ 05.007 Minatogawa, V. L. F., Franco, M. M. V., Rampasso, I. S., Anholon, R., Quadros, R., Durán, O., & Batoc- chio, A. (2020). Operationalizing business model innovation through big data analytics for sustain- able organizations. Sustainability, 12(1), 277. https://​doi.​org/​10.​3390/​su120​10277 g y p g Morgan, D. L. (1998). The Focus Group Guidebook. SAGE Publications, Inc. Morgan, D. L. (1998). The Focus Group Guidebook. SAGE Publications, Inc. N S & St b k K (2010) B i d l d i C t li i t k d l Morgan, D. L. (1998). References The Focus Group Guidebook. SAGE Publications, Inc. Nenonen, S., & Storbacka, K. (2010). Business model design: Conceptualizing networked value co-crea- tion. International Journal of Quality and Service Sciences, 2(1), 43–59. Morgan, D. L. (1998). The Focus Group Guidebook. SAGE Publications, Inc. Nenonen, S., & Storbacka, K. (2010). Business model design: Conceptualizing networked value co-cre tion. International Journal of Quality and Service Sciences, 2(1), 43–59. O’Reilly, C. A., & Tushman, M. L. (2008). Ambidexterity as a dynamic capability: Resolving the inno- vator’s dilemma. Research in Organizational Behavior, 28, 185–206. https://​doi.​org/​10.​1016/j.​riob.​ 2008.​06.​002 Paiola, M., & Gebauer, H. (2020). Internet of things technologies, digital servitization and business model innovation in BtoB manufacturing firms. Industrial Marketing Management, 89, 245–264. https://doi org/10 1016/j indmarman 2020 03 009 p g j Palmatier, R. W. (2016). Improving publishing success at JAMS: Contribution and positioning. Journal of the Academy of Marketing Science, 44(6), 655–659. https://​doi.​org/​10.​1007/​s11747-​016-​0497-2 Prahalad, C. K., & Hamel, G. (1990). The core competence of the corporation. Harvard Business Review, 68(3), 79–91. Ragozzino, R., Chintakananda, A., & Reuer, J. J. (2012). The use of quantitative methodologies in com- petitive strategy research. (G. B. Dagnino, Ed.)Handbook of Research on Competitive Strategy (pp. 379–396). Cheltenham: Edward Elgar Publishing Ltd. g g Ricciardi, F., Zardini, A., & Rossignoli, C. (2016). Organizational dynamism and adaptive business model innovation: The triple paradox configuration. Journal of Business Research, 69(11), 5487– 5493. https://doi.org/10.1016/j.jbusres.2016.04.154 i 5493. https://​doi.​org/​10.​1016/j.​jbusr​es.​2016.​04.​154 Roth, S., Mentges, S., & Robbert, T. (2021). Actor engagement in business model innovation - The role of experimentation in new ventures’ business model design. Marketing ZFP - Journal of Research & Management, 43(4), 45–60. Saur-Amaral, I., Soares, R. R., & Proença, J. F. (2016). Business model innovation: Where do we stand? ISPIM Conference Proceedings, 1–23. 1 3 Journal of the Knowledge Economy (2024) 15:2341–2360 2360 Scandura, T. A., & Williams, E. A. (2000). Research methodology in management: Current practices, trends, and implications for future research. Academy of Management Journal, 43(6), 1248–1264. https://​doi.​org/​10.​2307/​15563​48f Siachou, E., & Ioannidis, A. (2010). Knowledge transfer in strategic alliances: Moderating effects of lim- ited absorptive capacity and powerful relationships on business model innovation performance. Pro- ceedings of the European Conference on Knowledge Management, 933–943. Smajlović, S., Umihanić, B., & Turulja, L. (2019). The interplay of technological innovation and busi- ness model innovation toward company performance. Management, 24(2), 63–79. https://​doi.​org/​10.​ 30924/​mjcmi.​24.2.5 j Tushman, M. L., Smith, W. K., Wood, R. References C., Westerman, G., & O’Reilly, C. A. (2003). Innovation Streams and ambidextrous organizational designs: On building dynamic capabilities. Velter, M. G. E., Bitzer, V., Bocken, N. M. P., & Kemp, R. (2021). Boundary work for collaborative sustainable business model innovation: The journey of a Dutch SME. Journal of Business Models, 9(4), 36–66.l Yang, D., Wei, Z., Shi, H., & Zhao, J. (2020). Market orientation, strategic flexibility and business model innovation. The Journal of Business & Industrial Marketing, 35(4), 771–784. https://​doi.​org/​10.​ 1108/​JBIM-​12-​2018-​0372 Yin, R. K. (2009). Case study research: Design and methods. SAGE Publications. https://​books.​google.​ pl/​books?​id=​FzawI​AdilH​kC. Retreived: 7.12.2022 Zane, L. J., & DeCarolis, D. M. (2016). Social networks and the acquisition of resources by technology- based new ventures. Journal of Small Business & Entrepreneurship, 28(3), 203–221. https://​doi.​org/​ 10.​1080/​08276​331.​2016.​11620​48 Publisher’s Note  Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Publisher’s Note  Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Adam Dymitrowski1   · Paweł Mielcarek2 Paweł Mielcarek pawel.mielcarek@ue.poznan.pl Paweł Mielcarek pawel.mielcarek@ue.poznan.pl Paweł Mielcarek pawel.mielcarek@ue.poznan.pl 1 Department of International Marketing, Institute of International Business and Economics, Poznań University of Economics and Business, Poznań, Poland 2 Department of Organization and Management Theory, Institute of Management, Poznań University of Economics and Business, Poznań, Poland 2 Department of Organization and Management Theory, Institute of Management, Poznań University of Economics and Business, Poznań, Poland 2 Department of Organization and Management Theory, Institute of Management, Poznań University of Economics and Business, Poznań, Poland 1 3 1 3
https://openalex.org/W4390547301
https://pubs.aip.org/aip/rsi/article-pdf/doi/10.1063/5.0158497/18285906/013901_1_5.0158497.pdf
English
null
A versatile pressure-cell design for studying ultrafast molecular-dynamics in supercritical fluids using coherent multi-pulse x-ray scattering
Review of scientific instruments online/Review of scientific instruments
2,024
cc-by
15,064
RESEARCH ARTICLE | JANUARY 03 2024 RESEARCH ARTICLE | JANUARY 03 2024 A versatile pressure-cell design for studying ultrafast molecular-dynamics in supercritical fluids using coherent multi-pulse x-ray scattering a)Author to whom correspondence should be addressed: h 24 October 2024 04:40:18 ABSTRACT Supercritical fluids (SCFs) can be found in a variety of environmental and industrial processes. They exhibit an anomalous thermodynamic behavior, which originates from their fluctuating heterogeneous micro-structure. Characterizing the dynamics of these fluids at high tem- perature and high pressure with nanometer spatial and picosecond temporal resolution has been very challenging. The advent of hard x-ray free electron lasers has enabled the development of novel multi-pulse ultrafast x-ray scattering techniques, such as x-ray photon correlation spectroscopy (XPCS) and x-ray pump x-ray probe (XPXP). These techniques offer new opportunities for resolving the ultrafast microscopic behavior in SCFs at unprecedented spatiotemporal resolution, unraveling the dynamics of their micro-structure. However, harnessing these capabilities requires a bespoke high-pressure and high-temperature sample system that is optimized to maximize signal intensity and address instrument-specific challenges, such as drift in beamline components, x-ray scattering background, and multi-x-ray-beam overlap. We present a pressure cell compatible with a wide range of SCFs with built-in optical access for XPCS and XPXP and discuss critical aspects of the pressure cell design, with a particular focus on the design optimization for XPCS. © 2024 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). https://doi.org/10.1063/5.0158497 Pc, and the critical temperature, Tc, of some of the most common SCFs, along with their typical applications. A versatile pressure-cell design for studying ultrafast molecular-dynamics in supercritical fluids using coherent multi-pulse x-ray scattering A versatile pressure-cell design for studying ultrafast molecular-dynamics in supercritical fluids using coherent multi-pulse x-ray scattering Cite as: Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0 Submitted: 17 May 2023 • Accepted: 24 November 2023 • Published Online: 3 January 2024 Articles You May Be Interested In Ultrafast x-ray pump x-ray probe transient absorption spectroscopy: A computational study and proposed experiment probing core-valence electronic correlations in solvated complexes J. Chem. Phys. (June 2021) Design of a compact hard x-ray split-delay system based on variable-gap channelcut crystals AIP Conf. Proc. (January 2019) Ultrafast x-ray pump x-ray probe transient absorption spectroscopy: A computational study and proposed experiment probing core-valence electronic correlations in solvated complexes J. Chem. Phys. (June 2021) Design of a compact hard x-ray split-delay system based on variable-gap channelcut crystals AIP Conf. Proc. (January 2019) 24 October 2024 04:40:18 24 October 2024 04:40:18 Review of Scientific Instruments Review ofi ARTICLE pubs.aip.org/aip/rsi AFFILIATIONS 1 Department of Mechanical Engineering, Stanford University, Stanford, California 94305, USA 2SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA 3RIKEN SPring-8 Center, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148, Japan 4Chemical and Materials Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA y, , , 3RIKEN SPring-8 Center, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148, Japan 4Chemical and Materials Sciences Division Pacific Northwest National Laboratory Richl Review of Scientific Instruments Review of Scientific Instruments ARTICLE pubs.aip.org/aip/rsi TABLE I. Critical pressure and temperature of pure fluids of practical interest. Data from NIST.10 Fluid Pc (MPa) Tc (K) Applications CO2 7.38 304 CO2 sequestration, power cycles, solvent H2O 22.1 647 Subsurface reservoirs, chemical processing CH4 4.61 191 Propulsion, subsurface reservoirs, solvent Xe 5.84 290 Solvent, spacecraft propulsion O2 5.04 155 Rocket propulsion SO2 7.78 430 Industrial processes C12H26 1.81 658 Rocket propulsion, jet engines NH3 11.3 405 Fertilizer, refrigeration, transportation CHF3 4.82 299 Organic synthesis, refrigeration, plasma etching SF6 3.76 318 Gaseous dielectric medium N2O 7.23 310 Rocket propulsion, internal combustion engine TABLE I. Critical pressure and temperature of pure fluids of practical interest. Data from NIST.10 excellent repeatability, and operation with different fluids and mix- tures, albeit at reduced pressures compared to diamond anvil cells. Optical access for x-ray, visible, or neutron beams is provided by specialized windows.37 Table II provides a summary of published pressure-cell designs aimed at the study of SCFs along with their typical applications. By leveraging prior work on pressure cells for x-ray-based measurements, here we present a pressure cell that is specifically designed for multi-pulse FEL experiments. This pressure cell has been demonstrated at pressures up to 30 MPa and temperatures up to 675 K, thereby enabling the examination of supercritical water and all other fluids listed in Table I. By considering particu- larly stringent requirements on the intensity, speckle contrast, and signal-to-noise ratio (SNR), the pressure cell is primarily optimized for sp-XPCS experiments. The flexible design also enables exper- iments with more conventional x-ray techniques, such as XPXP and small/wide angle x-ray scattering (S/WAXS). So far, this cell has been successfully used for sp-XPCS experiments at the Linac Coherent Light Source (LCLS, SLAC National Accelerator Labora- tory, Menlo Park, CA, USA), for XPXP experiments at the SPring-8 Angstrom Compact-Free Electron Laser (SACLA, SPRING-8, Koto, Sayo, Hyogo prefecture, Japan), and for S/WAXS experiments at the Stanford Synchrotron Radiation Lightsource (SSRL, SLAC National Accelerator Laboratory, Menlo Park, CA, USA). our fundamental understanding of SCFs and pivotal to the future development of SCF applications. This requires extensive measure- ments of the nano-scale structure and dynamics of supercritical fluids. The remainder of this paper has the following structure. In Sec. II, we summarize essential sp-XPCS theory to guide the design of the pressure cell. In Sec. Review of Scientific Instruments III, we present the detailed design, dimen- sions, methods, and suppliers used to manufacture the pressure cell. With relevance to ensuring repeatability for high temperature con- ditions, this section also discusses the assembly procedure that we found to yield optimal stability and performance. The thermal and mechanical performance of the cell is then characterized in Sec. IV, and conclusions are presented in Sec. V. 24 October 2024 04:40:18 l Hard x-ray and neutron scattering techniques, characterized by wavelengths shorter than 10 Å, are particularly suitable to probe these structural heterogeneities and have therefore received considerable attention over the past few decades.15–18 In particu- lar, recent developments in x-ray free electron laser (FEL) light sources, capable of generating very bright femtosecond (fs) pulses, and in hard x-ray split-and-delay optics (SDO)19–21 have enabled novel ultrafast (fs-to-ps) two-pulse x-ray techniques, such as split- pulse x-ray photon correlation spectroscopy (sp-XPCS)22–24 and x-ray pump x-ray probe (XPXP). XPCS is the x-ray counterpart of dynamic light scattering and has the unique capability of studying the dynamic behavior of disordered matter at picosecond time scales and nanometer spatial scales, while XPXP measurements enable the examination of non-thermal and non-equilibrium states by perturb- ing the sample with a highly focused fs-x-ray pulse and measuring the subsequent microscopic structural evolution with a delayed x-ray probe pulse with femtosecond temporal resolution in the delay line. While these new coherent x-ray techniques enable mea- surements at unprecedented spatiotemporal resolution to examine the molecular behavior of SCFs, they introduce unique challenges that are associated with beam alignment, spatial coherence, and scattering intensity. Therefore, new SCF sample systems that are specifically tailored for these novel ultrafast multi-pulse methods are needed. I. INTRODUCTION Supercritical fluids (SCFs) exhibit anomalous behaviors char- acterized by strong variations in thermodynamic properties, such as density, compressibility, and heat capacity, around the Widom line,1 representing an extension of the liquid–gas phase boundary into the supercritical regime. This thermodynamic variability makes SCFs useful for a wide range of applications in biology,2 food processing,3 material synthesis,4 and energy production.5 SCFs also occur natu- rally in geophysical environments, such as deep oceans,6 geothermal reservoirs,7 carbon dioxide (CO2) sequestration sites,8 and even on some extraterrestrial bodies.9 In Table I, we list the critical pressure, Variations in thermodynamic properties of SCFs arise from their unique microscopic structure and dynamics, which is governed by inter-molecular interactions and a universal liquid–gas critical point behavior.11 When moving away from the critical point, the thermodynamic anomalies persist over an extended region within the supercritical regime around the Widom line, which separates the gas-like and liquid-like phase states.12,13 These thermodynamic anomalies are caused by self-similar cluster structures at the nano- scale.14 The ability to study the cluster behavior and the interac- tion of these clusters with solvated species is critical for advancing Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-1 II. BACKGROUND ON SP-XPCS THEORY XPCS is the counterpart of dynamic light scattering at hard x-ray wavelengths and measures the sample dynamics through the intermediate scattering function (ISF),44 f (Q, Δt). Here, Q is the angular wave number of the corresponding length scale under inves- tigation and Δt is the sample evolution time, and its definition in the scattering geometry in shown is Fig. 1. For sample dynamics on fs-to-ps time scale and nm length scale, the ISF can be measured using the sp-XPCS technique, the schematic of which is shown in Fig. 1. In sp-XPCS, a fs x-ray FEL pulse is split into a pulse pair with a SDO,21 and both x-ray pulses are sent to the same location on the sample along the same direc- tion with a controlled relative delay time Δt between the two pulses. This pulse pair produces a complex interference pattern on the area detector, illustrated in Fig. 1, and is referred to as a speckle pattern. The sharpness of the speckle pattern, quantified by its contrast β, is influenced by the atomic motion in the sample during the inter- val Δt between the pulses in the pair. Therefore, by determining the speckle contrast β for different Δt, one can measure the ISF and extract information about the sample dynamics.i Different high pressure cells have been proposed for high- energy scattering studies of SCFs, such as diamond anvil cells25–27 and pressure cells.28–43 While diamond anvil cells are the preferred choice for achieving extreme pressures, they come with the restric- tion of small sample size, large pressure and temperature gradients, and limited control over pressure and temperature.26,27 In con- trast, pressure cells provide direct control over operating conditions, The definition of the speckle contrast and its relation to the ISF in sp-XPCS is45 Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-2 Review of Scientific Instruments ARTICLE pubs.aip.org/aip/rsi TABLE II. Pressure cell used for the study of SCFs’ nano-scale properties and structure. II. BACKGROUND ON SP-XPCS THEORY Expanded from Kawai et al.37 Be: beryllium; Be-PEEK: beryllium-reinforced polyether ether ketone; BS: window fixed using a Bridgman seal; BW: brazed window; c-BN: cubic boron nitride; DLS: dynamic light scattering; EH: electrically heated; GPS: window fixed using a Poulter seal, initially affixed with adhesive glue; IXS: inelastic x-ray scattering; PC: pressure cell; P-jump: pressure jump; PS: window fixed using a Poulter seal; SR: stirred reactor; SAXS: small-angle x-ray scattering; SPS: window fixed using a spring loaded Poulter seal; TRIR: time-resolved infrared absorption spectroscopy; WAXS: wide-angle x-ray scattering; WH: water heated; and XAS: x-ray absorption spectroscopy. II. BACKGROUND ON SP-XPCS THEORY β(Q, Δt) ≡⟨I2 tot⟩ ⟨Itot⟩2 −1 = β1r2 + β2(1 −r)2 + 2μr(1 −r) min (β1, β2)f (Q, Δt), (1) At a low photon count rate, I ≤10−2 photon/pixel/pattern, which is common for sp-XPCS on SCFs, the shot-noise-induced SNR can be estimated as46 (1) SNR ≡β σβ ≈Iβ(NpixelNpattern 2(1 + β) ) 1 2 , (2) (2) where β(Q, Δt) is the contrast of the speckle pattern from the pulse pair at a specific angular wave number Q and a specific relative delay time Δt of the pulse pair. Itot is the scattering intensity from the pulse pair at a detector pixel with an angular wave number of Q and Itot = I1 + I2, where I1 and I2 are scattering intensity contributions of each single pulse in the pulse pair. The angular bracket ⟨⋅⟩indi- cates the average value of the quantity over a series of x-ray pulses. r = ⟨I1⟩/⟨Itot⟩is the average intensity ratio between the two pulses in the pulse pair. β1 and β2 are the speckle contrasts if only one pulse in the pulse pair is diffracted by the sample. μ ∈[0, 1] mea- sures the effective overlap between the two pulses on the sample and is sensitive to both spatial and angular overlap of the two pulses.il where σβ is the standard deviation of the estimation of the speckle contrast β, I is the average photon count rate, Npixel is the number of pixels within the region of interest on the area detector, and Npattern is the number of patterns collected. Equation (2) can be used to esti- mate the shot-noise-induced SNR for β, β1, and β2. In each case, I is the corresponding mean scattering intensity ⟨Itot⟩, ⟨I1⟩, and ⟨I2⟩. g g y The scattered x-ray intensity at the detector per pixel and per pulse is given as I = I0 d exp [−d datt ]( dσ dΩ) Th dΩ, (3) (3) The effective overlap μ has significant influence on the sp-XPCS measurement sensitivity and is affected by both the SDO design and its alignment. With the latest grating-based SDO design,21 almost identical hard x-ray pulse pairs, β1 ≈β2, can be generated with μ ≥0.9 over an extended range of delay times Δt ∈[0, 10] ps. How- ever, due to x-ray source and optics drifts, such a high μ value cannot be maintained over an entire measurement, which usually lasts more than 6 h. II. BACKGROUND ON SP-XPCS THEORY d and L designate the sample thickness and sample-to-detector distance, respectively; ⃗Kin is the central wave-vector of the incident x-ray pulse pair; ⃗Kout is defined for each detector pixel and is the central wave-vector of the scattered x-ray pulse, pointing from the sample to each individual pixel in the detector; ⃗Q = ⃗Kout −⃗Kin and Q = ∣⃗Q∣are defined for each pixel on the detector; and I1 and I2 represent the speckle pattern intensity of the individual pulses on the area detector. At fs-to-ps time separation between pulses (Δt), the area detector cannot separate the two diffraction patterns arising from each individual pulse and only records the total diffraction pattern Itot = I1 + I2. Review of Scientific Instruments pubs.aip.org/aip/rsi FIG. 1. Operating principle of sp-XPCS. d and L designate the sample thickness and sample-to-detector distance, respectively; ⃗Kin is the central wave-vector of the incident x-ray pulse pair; ⃗Kout is defined for each detector pixel and is the central wave-vector of the scattered x-ray pulse, pointing from the sample to each individual pixel in the detector; ⃗Q = ⃗Kout −⃗Kin and Q = ∣⃗Q∣are defined for each pixel on the detector; and I1 and I2 represent the speckle pattern intensity of the individual pulses on the area detector. At fs-to-ps time separation between pulses (Δt), the area detector cannot separate the two diffraction patterns arising from each individual pulse and only records the total diffraction pattern Itot = I1 + I2. FIG. 1. Operating principle of sp-XPCS. d and L designate the sample thickness and sample-to-detector distance, respectively; ⃗Kin is the central wave-vector of the incident x-ray pulse pair; ⃗Kout is defined for each detector pixel and is the central wave-vector of the scattered x-ray pulse, pointing from the sample to each individual pixel in the detector; ⃗Q = ⃗Kout −⃗Kin and Q = ∣⃗Q∣are defined for each pixel on the detector; and I1 and I2 represent the speckle pattern intensity of the individual pulses on the area detector. At fs-to-ps time separation between pulses (Δt), the area detector cannot separate the two diffraction patterns arising from each individual pulse and only records the total diffraction pattern Itot = I1 + I2. II. BACKGROUND ON SP-XPCS THEORY References Method Cell type Window material Window thickness Aperture Fluid Operating conditions Nishikawa and Takematsu28 SAXS WH PC with BW Be 2.0 mm 8.5 mm CO2 10 MPa, 333 K Pfund et al.29 SAXS EH PC with BW Diamond 500 μm 3.0 mm Solutions in sCO2, Xe 50 MPa, 319 K Nishikawa and Morita30 SAXS WH PC with PS Diamond 400 μm 4.0 mm CHF3 15 MPa, 333 K Hoffmann et al.31 TRIR EH PC with Pt washer seals Laser drilled diamond 1.0 mm 5.0 mm Solutions in sH2O/sCO2 38 MPa 673 K Koga et al.32 SAXS, DLS EH PC with SPS Diamond 500 μm 2.0 mm Solutions in sCO2 70 MPa Fulton et al.33 XAS EH PC with GPS Diamond 25 μm 300 μm Solutions in sH2O/sCO2 100 MPa 773 K Testemale et al.34 XAS, SAXS Cold wall Be 1.5 mm ⋅⋅⋅ Aqueous solutions 200 MPa IXS He furnace Sapphire 600 μm ⋅⋅⋅ 873 K Grunwaldt et al.35 XAS EH PC with stirrer Be-PEEK 500 μm ⋅⋅⋅ Catalysis in sCO2 25 MPa, 493 K Ando et al.36 SAXS PC with PS Diamond 500 μm 1.2 mm Protein in H2O 400 MPa, 300 K Kawai et al.37 XAS EH PC with BW c-BN 800 μm 3.0 mm Catalysis in H2 10 MPa, 900 K Brooks et al.38 SAXS WH P-jump PC with GPS, BS Diamond 1.0 mm 2.5 mm Soft condensed matter 500 MPa WAXS 393 K Hermida-Merino et al.39 S/WAXS, XAS EH SR PC with BW Diamond 400 μm 4 mm Solutions in sCO2 21 MPa, 393 K Skinner et al.40 WAXS EH PC with PS Diamond 250 μm ⋅⋅⋅ H2O 360 MPa, 300 K Rai et al.41 SAXS WH PC with BS Diamond 500 μm 1.5 mm Solutions in H2O 400 MPa, 353 K Miller et al.42 SAXS PC with BS Diamond 500 μm 1.5 mm Protein in H2O 400 MPa, 350 K Present SAXS, WAXS, EH PC with GPS Diamond 100 μm 1.0 mm H2O, CO2, Xe 30 MPa sp-XPCS, XPXP 675 K ev Sci Instrum 95 013901 (2024); doi: 10 1063/5 0158497 Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-3 95, 013901-3 Review of Scientific Instruments ARTICLE pubs.aip.org/aip/rsi FIG. 1. Operating principle of sp-XPCS. II. BACKGROUND ON SP-XPCS THEORY A realignment and geometric optimization of the SDO is therefore needed approximately every 30 min to maintain this high μ value.21 Therefore, in Sec. III D, we present our design of a high resolution beam profile monitoring system tailored for the pressure cell to optimize x-ray pulse overlap μ. where I0 is the incident x-ray photon flux, (dσ/dΩ)Th is the differ- ential cross section for Thompson scattering, and dΩ is the solid angle of the pixel with respect to the sample. datt is the x-ray attenua- tion length, which depends on the sample composition and density. (dσ/dΩ)Th is determined from S/WAXS measurement, described in Appendix B, and is dependent on the sample composition, pressure, and temperature, as well as the angular wave number Q.i For a specific x-ray light source, by reducing d or increasing L, one increases the contrast β.45 This, however, reduces the scattering intensity I, as shown in Eq. (3). According to Eq. (2), the net influ- ence on the SNR of β depends on their product. One therefore needs to thoroughly examine the feasible experimental parameter space for each specific sample to find the optimal values for the geometric parameters d and L. In practice, the x-ray photon shot noise is another major source of uncertainty for the measurement of the speckle contrasts β, β1, and β2. Usually millions of speckle patterns need to be accumulated to reach a signal-to-noise ratio (SNR) of the contrast measurement β that is sufficiently high to discern the variation of f (Q, Δt) as a function of Δt. The SNR of β has a complex dependence on the sample thickness, d, and the distance between sample and detector, L, through the contrast β itself and the mean scattering intensity I. Choosing d and L for an optimal SNR of β can greatly improve the measurement efficiency in sp-XPCS. In the following, we estimate the optimal geometric parameters d and L to perform sp-XPCS measurements on supercritical water at 25 MPa and 653 K, considering specifically the angular wave num- ber Q = 0.1 Å−1. The FEL operating conditions are representative of the XPP instrument at LCLS, with an x-ray photon energy of 9.5 keV, an energy full-width-half-maximum (FWHM) bandwidth Rev. Sci. Instrum. II. BACKGROUND ON SP-XPCS THEORY 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-4 Review of Scientific Instruments ARTICLE pubs.aip.org/aip/rsi of ΔE = 0.4 eV, an x-ray beam size of 3 μm, an incident x-ray pho- ton flux of I0 = 3 × 108 photons per pulse on the sample, and an x-ray repetition rate of 120 Hz. The detector pixel size is assumed to be 50 μm, corresponding to an Epix100 detector.47 The results of the analysis are shown in Fig. 2. Figure 2(a) shows the scattering intensity at the detector per pixel as a function of sample thickness d and detector distance L using Eq. (3). Figure 2(b) shows the single pulse speckle contrast as a function of d and L. We have assumed a Gaussian spatiotemporal beam profile of the x-ray pulse with x-ray beam parameters specified above to calculate the speckle contrast β following the derivations given in Refs. 45 and 48. significantly in a range spanning from tens of micrometers to sev- eral millimeters, since the thermodynamic condition and angular wave-vector Q of the sample determine its differential cross section in Eq. (3) and the elastic scattering intensity I on the detector. There- fore, in the pressure cell design presented in this paper, we integrate a flexible procedure to adjust the sample thickness by changing a sin- gle component, allowing us to vary the sample thickness in the range d ∈[200 μm, 3 mm]. Due to deformation under high temperature and pressure conditions and unavoidable assembly uncertainties, the sample thickness during the experiment can differ from its design value. We therefore measure the sample thickness before conduct- ing any experiment. The procedure to perform these measurements is presented in Sec. IV B and Appendix F. Limited by the background noise level of modern hard x-ray area detectors and numerical instabilities in current state-of-the- art analysis algorithms, if the x-ray scattering I is too weak (I < 10−5 photon/pixel/pattern) or if the single pulse speckle con- trast β is too low (β < 0.01), the speckle contrast analysis will be heavily dominated by photon shot noise and systematic error from the analysis algorithm and therefore cannot be used to measure the sample dynamics. In Fig. 2, we have marked these inaccessible regions of the geometric parameter space in gray. III. PRESSURE CELL The pressure cell presented in this study is adapted from pre- vious designs introduced in Table II and combines several features to improve its flexibility and suitability for multi-pulse x-ray experi- ments. The demonstrated working temperature and pressure of this pressure cell are 675 K and 30 MPa.49 These conditions are chosen to enable experiments with a variety of fluids of practical relevance, including water and dodecane, which both have a high critical tem- perature (Table I). To facilitate optical experiments at both x-ray and visible wavelengths, we employ large optical windows and large accessible scattering angles so that this pressure cell can be utilized at a variety of x-ray beamlines. The key features of this pressure cell are (i) variable sample thickness, (ii) metal-to-metal seal for high temperature operation, (iii) thin diamond windows to reduce back- ground scattering, and (iv) integrated diagnostics to enable in situ x-ray beam monitoring. The computer aided design (CAD) files for the pressure cell are provided in STEP format as the supplementary material. In Fig. 2(c), we plot the SNR as a function of d and L, assum- ing 1 h of continuous data acquisition with a 120 Hz FEL repetition rate following Eq. (2). The pixel number Npixel as a function of sample-detector distance L is calculated according to the model described in Appendix C. As shown in Fig. 2(c), within the feasible region (non-gray region), the maximum SNR for sp-XPCS mea- surements is achieved for a sample thickness of d ≈0.8 mm and detector distance L ≈1 m. For these geometric parameters, 1 h of data acquisition yields an SNR = 18.8. If we assume that the SDO is optimized such that r ≈0.5 and μ ≈1, then SNR = 18.8 guaran- tees that a 5% change in f (Q, Δt) will be statistically significant. Following the same procedure, systematic SNR analysis can be con- ducted for different pressures, temperatures, angular wave numbers, and evolution time to plan experiments and optimize the sensor and sample geometries ahead of a beamtime. 24 October 2024 04:40:18 A. Pressure-cell design and manufacturing The cutting plane used in (a) is orthogonal to that used in (c); (b) zoomed-in view of the sample cavity, optical access apertures, and diamond windows; (c) exploded cut view showing the four main components of the cell assembly: main body, cone, retaining nut, and scintillator; and (d) magnified view of the window support surface (top) and the assembled diamond window (bottom) acquired under a Leica S9i microscope (Deerfield, IL, USA). (a)–(c) The FEL pulses are traveling from left to right. 24 October 2024 04:40:18 24 October 2024 04:40:18 FIG. 3. 3D model of the versatile pressure cell. (a) Cut view showing the fully assembled pressure cell and the integration of the heating system. The cutting plane used in (a) is orthogonal to that used in (c); (b) zoomed-in view of the sample cavity, optical access apertures, and diamond windows; (c) exploded cut view showing the four main components of the cell assembly: main body, cone, retaining nut, and scintillator; and (d) magnified view of the window support surface (top) and the assembled diamond window (bottom) acquired under a Leica S9i microscope (Deerfield, IL, USA). (a)–(c) The FEL pulses are traveling from left to right. and monitoring of the window, this aperture is placed at the end of a viewing port. The viewing port consists in a 9 mm-deep unpol- ished 60○conical bore. An off-axis high resolution imaging system, presented in Sec. III D, is attached to the cell to visually inspect the windows and the sample during experiments. The sample cav- ity is an open-end 10 mm-diameter 1.58 mm-deep cylinder, shown in cyan in Figs. 3(a) and 3(b), and has separate inlet and outlet sam- ple lines, also shown in cyan in Figs. 3(a) and 3(c). The inlet and outlet lines are drilled perpendicular to each other, which allows for bleeding off any air present in the sample cavity during initial filling of the cell. It also enables the operation of this pressure cell as either a hydrostatic cell or a flow cell. The sample feed lines are 0.8 mm in diameter and are terminated by 1/16 in. high pressure taper seal grade 5 titanium tube fittings from High Pressure Equipment (Erie, PA, USA). Extending from the open end of the cylindri- cal sample cavity is a 60○8.66 mm-deep conical section. At the and 3(c)]: the main body [golden brown in Fig. A. Pressure-cell design and manufacturing We emphasize here that for different sample compositions, sample thermodynamic conditions, x-ray beam characteristics, and detector specifications, the optimal sample thickness d can vary Figure 3 shows the pressure cell and its main features. This pressure cell assembly consists of four main components [Figs. 3(a) FIG. 2. Determination of optimal experimental parameters for sp-XPCS experiments at Q = 0.1 Å−1 with supercritical water at 25 MPa and 653.15 K. The geometrical parameters of interest are the sample thickness d and the sample-to-detector distance L. (a) Scattering intensity I at the detector, (b) single pulse speckle contrast β1, and (c) shot-noise-induced SNR of the contrast measurement with Npattern = 4.3 × 105 diffraction patterns, corresponding to 1 h of data acquisition at a 120 Hz FEL repetition rate at LCLS. The gray region represents conditions of I and β in which current state-of-the-art analysis tools cannot reliably extract physical information. The boundaries of these inaccessible regions are I < 10−5 photon/pixel/pattern in (a) and β < 0.01 in (b). Experimental conditions: 50 μm detector pixel size, 9.5 keV photon energy, 3 μm beam diameter, 3 × 108 photon per pulse, 0.4 eV FWHM energy bandwidth, and full transverse coherence. FIG. 2. Determination of optimal experimental parameters for sp-XPCS experiments at Q = 0.1 Å−1 with supercritical water at 25 MPa and 653.15 K. The geometrical parameters of interest are the sample thickness d and the sample-to-detector distance L. (a) Scattering intensity I at the detector, (b) single pulse speckle contrast β1, and (c) shot-noise-induced SNR of the contrast measurement with Npattern = 4.3 × 105 diffraction patterns, corresponding to 1 h of data acquisition at a 120 Hz FEL repetition rate at LCLS. The gray region represents conditions of I and β in which current state-of-the-art analysis tools cannot reliably extract physical information. The boundaries of these inaccessible regions are I < 10−5 photon/pixel/pattern in (a) and β < 0.01 in (b). Experimental conditions: 50 μm detector pixel size, 9.5 keV photon energy, 3 μm beam diameter, 3 × 108 photon per pulse, 0.4 eV FWHM energy bandwidth, and full transverse coherence. Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-5 Review of Scientific Instruments Review ofi pubs.aip.org/aip/rsi Scientific Instruments FIG. 3. 3D model of the versatile pressure cell. (a) Cut view showing the fully assembled pressure cell and the integration of the heating system. B. X-ray windows and their installation and removal The main body of the pressure cell assembly also serves as a heat bath for the SCF sample. Heat is supplied by eight cartridge heaters located in the bores shown in red in Fig. 3(a). The temperature of the main body is monitored using a resistance temperature detector (RTD), shown in yellow in Fig. 3(a), and whose sensing element is placed near the sample cavity. X-ray optical access is provided by two single-crystal, type IIa, diamond windows, 100 μm thick and 4 mm in diameter (Applied Diamond, Wilmington, DE, USA). The thickness needs to be mini- mized to reduce the scattering background of the windows, and the optimal thickness was determined using the following equation:38 To assess the alignment of the x-ray pulses on the sample dur- ing sp-XPCS and XPXP experiments, a x-ray scintillator screen, made of YAG crystals, is installed at the edge of the main body [Fig. 3(c)]. The upstream surface of the YAG screen is coplanar with the mid-plane of the sample cavity and, therefore, only requires a short transverse translation during experiments to measure the pulse overlap on the sample. pmax = 4 3 √ 1 −ν + ν2 ( t a) 2 σy, (4) (4) where pmax is the maximum sample pressure before failure, t is the window thickness, a is the unsupported aperture radius, and σy and ν are the yield strength and Poisson ratio of type IIa diamond. The material properties of the diamond window are provided in Appendix G. The 100 μm window thickness provides a safety factor of 1.9 at the maximum design pressure of 30 MPa. During an over- pressurization test, we observed a diamond window failure at ∼690 bars, larger than the theoretical value estimated using Eq. (4). At the typical hard x-ray energy of 10 keV used at LCLS and SACLA for sp-XPCS experiments, each window transmits 92% of the incident pulses. The cone [dark blue in Fig. 3(c)] is inserted into the main body on the detector side and pressed in place using the retaining nut. It seals the sample cavity by forming a metal-to-metal swaged seal with the main body. That is achieved by having a slight mismatch between the angle of the female conical bore on the main body (60○) and the male conical surface of the cone (59○), as illustrated in Fig. 3(c). B. X-ray windows and their installation and removal The metal-to-metal contact between the two parts then occurs along a single circular line, forming a seal. Both conical surfaces are manu- factured using single-point diamond turning52 to obtain an accurate geometry and fine surface finish. When pressed together by tighten- ing the retaining nut, the two conical surfaces deform slightly at the contact line and create a very reliable swaged seal capable of oper- ating at high pressure and high temperature.53 At the contact line between the male and female parts, there is a small step characterized by a change in the angle of the male cone, emphasized in Fig. 3(b) with a yellow line. This small step allows us to more precisely set the location at which the two conical parts mate and ensures that the positioning of the cone is repeatable. Multiple cones were manufac- tured with different step heights, providing an affordable approach to adjust the sample thickness d to specific experimental conditions and optimize the SNR for XPCS and XPXP measurements. The laser/x-ray light passes through a 1 mm diameter aperture at the center of the cone. An inner 60○conical bore [shown in green in Fig. 3(a)] is also machined in the cone to transmit photons scattered at large angles toward the detector. Given the high operating temperature and pressure, the thin diamond windows are attached to the cell with a Poulter seal.54 With this design, the diamond window rests on a highly polished metal seat. Following the design recommendations by Sherman and Stadt- muller,53 the seats of the Poulter seal are placed on small pedestals [Fig. 3(b)] that are not perfectly flat but form a shallow cone with a 0.3○angle between 0.6 ≤r ≤0.9 mm from the center of the aperture, as illustrated in Fig. 4(a). The metal surfaces supporting the diamond windows are machined with the single-point diamond turning tech- nique, yielding an optically reflective surface finish with a precise geometry and a circular lay without the need for additional polish- ing. During operation, the pressure within the sample cavity deforms the seat and window, forming a tight seal capable of operating at very high pressures, as shown in Fig. 4(b). 24 October 2024 04:40:18 A Poulter seal, although highly effective at high pressures, does not seal at ambient or low-pressure conditions (P ≲2 MPa). A typi- cal solution to this issue is to affix the window onto its supporting surface. A. Pressure-cell design and manufacturing 3(c)] supporting the upstream x-ray window, a cone [dark blue in Figs. 3(a) and 3(c)] supporting the detector-side x-ray window and sealing the sample cavity when pressed against the main body, a retaining nut [gray in Figs. 3(a) and 3(c)], and a scintillator assembly [dark purple in Fig. 3(c)]. The sample cavity is shown in Fig. 3(b), and the opti- cal paths of the FEL pulses and the scattered light are shown in green in Figs. 3(a)–3(c). All components are machined in-house at the SLAC National Accelerator Laboratory from grade 5 Ti-6Al-4V titanium alloy, selected for its mechanical properties at high- temperature and its proven chemical inertness with supercritical water and supercritical aqueous solutions.50,51 The main body is a square cuboid with external dimensions of 40.5 × 76.2 × 76.2 mm3. Located at the center of the main body, facing the light source, is the laser/x-ray aperture, a 1 mm-diameter hole leading to the sample cavity. In order to allow visual inspection Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-6 95, 013901-6 Review of Scientific Instruments ARTICLE and beamline infrastructure is used. Details of this interface are presented in Appendix D. downstream end of the main body is a 50 mm-diameter 20.2 mm- deep M50 × 1.5 fine-pitched threaded hole that the retaining nut is threaded into during operation. B. X-ray windows and their installation and removal Procedure for installing diamond window in the pressure cell: (a) apply moderate pressure on the diamond window and apply adhesive along the outer rim with a thin brush and (b) during operation, fluid pressure on the sample deforms the diamond window and forms a Poulter seal. Not to scale. FIG. 4. Procedure for installing diamond window in the pressure cell: (a) apply moderate pressure on the diamond window and apply adhesive along the outer rim with a thin brush and (b) during operation, fluid pressure on the sample deforms the diamond window and forms a Poulter seal. Not to scale. (Teledyne ISCO 100DM, Lincoln, NE, USA) is used for fluid deliv- ery and pressurization. The pressure in the cell is regulated by a proportional-integral-derivative (PID) controller driven by the pump’s internal pressure sensor. An additional redundant pressure sensor is placed near the pressure cell, achieving a measurement accuracy of the absolute pressure of the sample of ±0.12 MPa. Dur- ing extended continuous operation of the pressure, pressure stability was measured to be better than ±0.02 MPa over 60 h, which is further discussed in Sec. IV A. A pressure relief valve (Swagelok, Solon, OH, USA) is added to the system for safety and compliance with pressure vessel regulations. seat of the seal. We found that the direct application of the adhesive between the diamond window and the metal surface would result in excess adhesive being present, which would inevitably leak into the sample or the beam path during high-temperature experiments. The cone, pressure cell body, and diamond windows are then oven-cured at 300 ○C for 30 min. After curing and cooling the pressure cell, excess adhesive is cleaned by placing the cone and pressure cell body in an ethanol bath, within an ultrasonic cleaner (Branson Ultrason- ics Corp., Danbury, CT, USA) for 15 min. The ultrasonic cleaning can significantly weaken the excess adhesive exposed to the ethanol but will not break the bond between the diamond and its metal sup- port. The excess adhesive can then be removed with a cotton tip applicator. 24 October 2024 04:40:18 The temperature of the pressure cell is monitored with a 1/4 in. diameter 100Ω platinum resistance temperature detector (Omega Engineering, Norwalk, CT, USA) whose location is shown in yellow in Fig. 3(a). B. X-ray windows and their installation and removal However, at and above the critical temperature of water, most adhesives melt and ultimately contaminate the sample and the optical path. In what follows, we briefly describe an affixing proce- dure that we found effective at minimizing issues associated with adhesive contamination, particularly when conducting experiments at high temperatures. The retaining nut is hexagonal, with an overall length of 35 and a 76.3 mm width. It has a 15 mm-long M50 × 1.5 fine pitch thread to screw into the main body of the cell. The thread was selected to apply sufficient torque to preload the swaged conical seal and to have a high mechanical strength.38 The threading on the retaining nut is the major potential failure point of this design. We performed a pressure safety analysis to guarantee a safety factor of 11.3 for the retaining nut threading with a maximum working pressure of 30 MPa. The analysis is summarized in Appendix A. The retaining nut also has an internal conical bore with a 60○included angle to transmit scattered x-ray photons over a large angular range. A small amount of Silver Goop high temperature lubricant (Swagelok, Solon, OH, USA) can be applied to the threads for lubrication. We selected a high vacuum sealant, Vacseal (original formu- lation, Space Environment Labs, Boulder, CO, USA), for its high operating temperature and low viscosity. We start by thoroughly cleaning the surfaces of the Poulter seal and diamond with ace- tone. The diamond window is then placed and centered onto its seat and clamped using either a soft wood rod or a vacuum tweezer. A thin brush is then used to deposit a small amount of adhesive on the metallic seat of the Poulter seal, along the outer rim of the dia- mond window. Capillary forces will allow the low-viscosity adhesive to wick into the gap between the diamond window and the metal To achieve fast, safe, and reproducible installation and removal of the pressure cell in the case of unexpected incidents during exper- iments, a customized installation interface between the pressure cell Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-7 95, 013901-7 Review of Scientific Instruments Review ofi Scientific Instruments FIG. 4. B. X-ray windows and their installation and removal The temperature signal is picked up by a temperature controller (CryoCon Model 24C, Cryogenic Control Systems, Rancho Santa Fe, CA, USA), which is executing a PID control loop to stabilize the temperature. The control signal drives the voltage output of an external DC power supply (BK Precision, Yorba Linda, CA, USA), which provides electric power to the eight pp To break the adhesive bonds between the diamond window and the Poulter eat after the completion of an experiment, the parts are placed in an acetone bath within an ultrasonic cleaner for 15 min. A. Pressure and temperature envelope The thermal stability and step-response characterization of the pressure cell is presented in Fig. 7. The test was conducted with a 500 μm-thick supercritical water sample. Prior to the test, the PID parameters of the temperature controller were optimized using its built-in auto-tune functionality for a target temperature of 673.15 K. Figure 7(a) shows the temperature and pressure time profiles dur- ing initial heating of the water sample from room temperature (295.32 K) to the target temperature of 673.15 K with a nominal pressure of 25 MPa. A heating rate of 54.2 K/min is achieved, and after 15 min, the temperature stabilizes within 0.2 K of the target. Figure 7(b) shows the thermal response for a change of the setpoint temperature from a steady state of 653.15–658.15 K. After an over- shoot to 662.08 K at t = 1 min, the temperature stabilizes to 658.15 K within 0.1 K of the target in less than 5 min. Over an extended measurement of 60 h at steady state, we are able to maintain a constant pressure with less than 0.017 MPa peak-to-peak fluctua- tions and a constant temperature with less than 0.22 K peak-to-peak fluctuations. C. Pressure and temperature control Figure 5 shows a diagram of the pressure and temperature control system used for the operation of this cell. A syringe pump FIG. 5. Piping and instrumentation diagram showing the arrangement of the fluid delivery system and the heating stage. FIG. 5. Piping and instrumentation diagram showing the arrangement of the fluid delivery system and the heating stage. Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 95, 013901-8 95, 013901-8 Review of Scientific Instruments ARTICLE pubs.aip.org/aip/rsi cartridge heaters (Briskheat, Columbus, OH, USA) on the pressure cell, each rated at 250 W. relative position between the scintillator screen with respect to the sample cavity. Therefore, after optimizing the x-ray optics alignment with the scintillator screen, we can move the pressure cell to com- pensate the relative position between the scintillator and the sample cavity, ensuring optimal x-ray overlap and placing the focus spot in the middle of the sample cavity. A motorized translation is placed on the beamline to switch between the sample and scintillator. In Appendix E, we present in more detail the motion system required to achieve an efficient and precise sample alignment and a rapid sample-scintillator translation. To reduce the heat loss and to improve temperature stabil- ity, the pressure cell is thermally insulated using high-temperature ceramic paper (Fiberfrax 970, Unifrax, Tonawanda, NY, USA). In addition, the cell is separated from beamline components with four 9.5 mm-outer-diameter 12.7 mm-long grade L5 ceramic posts (McMasterCarr, Elmhurst, IL, USA) to minimize metal-to-metal heat losses. An additional temperature probe is placed inside the sample cavity, in direct contact with the SCF, to provide a redundant and more accurate temperature measurement. A small high-accuracy 0.5 mm-diameter K-type thermocouple probe (Omega Engineering, Norwalk, CT, USA) was used for this purpose. It is inserted into the sample cavity through the tubing of the sample inlet line. D. X-ray alignment and sample motion For multi-pulse x-ray measurements, such as XPXP and sp- XPCS, the spatial and angular alignment of x-ray pulses is crucial to optimize the SNR of the measurements [Eq. (1)]. For hard x-ray pulses at FELs, the focused x-ray beam size typically used for such measurements is on the order of 1–3 μm. Due to inherent electron and device instability, it is common practice to check and if neces- sary adjust the x-ray beam overlap at 30 min time-intervals during operation.21 To reduce the time associated with beam monitoring and alignment, we designed a dedicated imaging system to facilitate this process, which is shown in Fig. 6. In this setup, a right angle mirror (12.5 μm protected gold coated N-BK7 right angle mirror, Edmund Optics, Barrington, NJ, USA) is installed tangent to the x-ray beam path. A high magnification camera assembly (ZYLA-5.5- USB3, Andor, Belfast, UK), with a 152.5 mm extension tube and a 10× Mitutoyo (Kanagawa, Japan) telecentric microscope objective with a spatial resolution of 325 nm, is used to image the x-ray beam profile on the scintillator attached to the side of the cell, shown in yel- low in Fig. 6. The scintillator screen is a 5 mm × 5 mm × 20 μm YAG crystal and is mounted within a slot machined in the main body of the cell. l During operation with supercritical water, the leakage rate of the cell is less than 9 μl h−1. During x-ray experiments, to avoid accu- mulated effects of sample irradiation, such as heating and ionization, we typically operate the cell as a flow cell with a low flow rate. B. Sample thickness The bottom of the slot is parallel to and located 300 μm down- stream to the front surface of the sample cavity. This defines the For XPXP and sp-XPCS measurements, the sample thickness has a significant impact on the SNR. We therefore characterize the FIG. 6. (a) Imaging system with a high-resolution camera, a right-angle mirror, and a scintillator screen; (b) schematics of the optical path of the diagnostic system. l1 and l2 measure the distance from the lens to the mirror and from the mirror to the scintillator screen, respectively. The total distance, l1 + l2 = 51 mm, corresponds to the working distance of the objective lens. FIG. 6. (a) Imaging system with a high-resolution camera, a right-angle mirror, and a scintillator screen; (b) schematics of the optical path of the diagnostic system. l1 and l2 measure the distance from the lens to the mirror and from the mirror to the scintillator screen, respectively. The total distance, l1 + l2 = 51 mm, corresponds to the working distance of the objective lens. Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-9 Review of Scientific Instruments Review ofi ARTICLE pubs.aip.org/aip/rsi Scientific Instruments FIG. 7. Temperature (red) and pressure (blue) for different operating conditions: (a) transient heating of the sample from room temperature (295.32 K) to 673.15 K at 25 MPa at a heating rate of 54.2 K/min and (b) changing of sample temperature from 653.15 to 658.15 K at 25 MPa. C. Signal-to-background analysis and x-ray scattering experiments Upon repeating the measurement with different sample densities and therefore different attenuation lengths, ξ2, the sample thickness can be evaluated as d = ξ1ξ2 ξ1 −ξ2 (ln τ1 −ln τ2), (5) Δd = ξ1ξ2 ξ1 −ξ2 [(Δτ1 τ1 ) 2 + (Δτ2 τ2 ) 2 ] 1 2 , (6) (5) Δd = ξ1ξ2 ξ1 −ξ2 [(Δτ1 τ1 ) 2 + (Δτ2 τ2 ) 2 ] 1 2 , (6) (6) with τi ≡Ii/I0 for i = {1, 2}. Representative measurements are shown in Fig. 8 for a cell configuration with a nominal sample thick- ness of 1 mm. In Fig. 8, the slope of each line corresponds to τi. Following Eq. (5), one can readily derive the actual sample thickness as 954 ± 108 μm. The attenuation measurement of the sample thick- ness is not limited to x-ray pulses and can also be carried out using a visible wavelength laser, as further discussed in Appendix F. FIG. 9. Mean scattering intensity, I, at different scattering angular wave numbers, Q (Å−1), from the empty pressure cell and the pressure cell filled with a supercriti- cal water sample at 653.15 K and 25 MPa with an x-ray photon energy of 9.5 keV with a beam size of 1 μm at the XPP instrument at LCLS. FIG. 10. X-ray speckle contrast of x-ray pulse pairs for Δt of 1 and 7 ps at Q of 0.04 ˚A −1 and 0.1 ˚A −1 for the 954 μm-thick supercritical H2O sample at 653.15 K and 25 MPa with an x-ray photon energy of 9.5 keV and a beam size of 1 μm at the XPP instrument at LCLS. ness is not limited to x-ray pulses and can also be carried out using a visible wavelength laser, as further discussed in Appendix F. FIG. 8. Correlation plot of the transmitted x-ray intensity I1 against the incident x-ray intensity I0 for two sample conditions: empty and full. One can derive the sample thickness following Eq. (5). FIG. 10. X-ray speckle contrast of x-ray pulse pairs for Δt of 1 and 7 ps at Q of 0.04 ˚A −1 and 0.1 ˚A −1 for the 954 μm-thick supercritical H2O sample at 653.15 K and 25 MPa with an x-ray photon energy of 9.5 keV and a beam size of 1 μm at the XPP instrument at LCLS. Rev. Sci. Instrum. C. Signal-to-background analysis and x-ray scattering experiments In x-ray scattering experiments that are conducted with sam- ples contained in pressure cells, it is important to minimize the scattering from the cell’s windows and achieve a high signal-to- background ratio. For different types of x-ray scattering techniques, the background level can vary significantly due to geometric con- strains. Since our pressure cell operates in the atmosphere, scat- tering from the air and diamond windows contribute primarily to the background scattering. In this section, we present com- parisons between signal and background scattering levels for sp- XPCS and XPXP experiments. In addition, measured quantities for studying microscopic dynamics in SCFs are also presented in this section. FIG. 7. Temperature (red) and pressure (blue) for different operating conditions: (a) transient heating of the sample from room temperature (295.32 K) to 673.15 K at 25 MPa at a heating rate of 54.2 K/min and (b) changing of sample temperature from 653.15 to 658.15 K at 25 MPa. The sp-XPCS has strict requirements on the optimal sample- detector geometry (see Sec. II), which limits the achievable signal- to-background ratio. In our commissioning measurements with the pressure cell, performed at the XPP instrument at LCLS, we com- pared the background scattering of the empty pressure cell to the sample thickness at the beginning of each experiment using x-ray attenuation. This technique requires independent measurements of the intensities of the incident (I0) and transmitted (I1) x-ray pulses at different sample densities. FIG. 9. Mean scattering intensity, I, at different scattering angular wave numbers, Q (Å−1), from the empty pressure cell and the pressure cell filled with a supercriti- cal water sample at 653.15 K and 25 MPa with an x-ray photon energy of 9.5 keV with a beam size of 1 μm at the XPP instrument at LCLS. Assuming that the attenuation length of the sample is ξ1 and the sample thickness is d, we have I1 = ηI0 exp {−d/ξ1}, with η being a constant representing the x-ray energy loss unrelated to sample attenuation. C. Signal-to-background analysis and x-ray scattering experiments The comparison of the scattering intensity for the empty cell and the cell with the SCF sample is shown in Fig. 9. The scattering of the empty cell is less than 4 × 10−4 photon/pixel/pulse over a wide Q-range. The signal- to-background ratio ranges between 4 and 5 over the whole area detector (Q ∈[0.02, 0.15] Å−1). These results demonstrate that the pressure cell is able to provide a high signal-to-background ratio at low scattering angles for experiments on supercritical water. probe pulse energy in Fig. 11(a) are, respectively, 5 and 8.15 μJ and different colors denote the different delay times between the two x-ray pulses. Because scattering intensities for different delay times show differences that are only visible though self-reference normal- ization, which are shown in Fig. 11(b), the scattering signals from H2O in Fig. 11(a) are shifted vertically for better visualization. The curves for 0, 1, 10, and 100 ps, are shifted by a numerical value of 0, 50, 100, and 150, respectively, in Fig. 11(a). 24 October 2024 04:40:18 The inbuilt scintillator greatly facilitates the alignment of the pump and probe x-ray pulses. This allows us to explore multiple temperature and pressure conditions during this 60 h beamtime. For each temperature–pressure condition, we performed XPXP mea- surements at multiple delay times. For 645 K and 23 MPa, shown in Fig. 11(b), a total of 13 delay times were measured between 0 and 100 ps. We normalized the scattering intensity I(Q) based on the average scattering intensity of Q ∈[2.0, 2.7 ˚A −1]. The averaged normalized intensity of Q ∈[0.14, 0.4 ˚A −1] is shown in Fig. 11(b) as a function of different delay times between the pump and probe x-ray pulses for three pump pulse energies, 2.4, 4.8, and 8.1 μJ. The probe pulse has an average pulse energy of 8.15 μJ. This self- normalized measurement shows unequivocally an increase in the scattering signal within 10 ps and has a clear dependency on the pump pulse energy. This time and length scale is close to that of the lifetime and spatial extend of generic molecular clusters near the critical point.14 Therefore, we believe that the observed struc- ture factor change reflects the destruction and reorganization of the molecular clusters induced by the strong x-ray pump pulses. Detailed analysis is ongoing to determine the origin of the observed phenomena. C. Signal-to-background analysis and x-ray scattering experiments The black curve shows the scattering signal from an empty pressure cell, while the other curves shows the scattering signal level with H2O in the pressure cell at 645 K and 23 MPa with a thickness of 800 μm. The legend 0, 1, 10, and 100 ps refers to the delay time between the two x-ray pulses in this XPXP measurement. The curves for 0, 1, 10, and 100 ps are shifted vertically by 0, 50, 100, and 150, respectively, with respect to their original value for a better visualization. The average pump and probe pulse energy are 5 and 8.15 μJ, respectively, with an x-ray photon energy of 10 keV. (b) Total scattering intensity within Q ∈[0.14, 0.4 ˚A −1] normalized by the total scattering intensity within Q ∈[2.0, 2.7 ˚A −1] as a function of delay time between the pump pulse and probe pulse. The probe pulse has, on average, 8.15 μJ, while the pump pulse energy is shown in the legend. FIG. 11. (a) Mean scattering intensity, I(Q), as a function of angular wave numbers, Q (Å−1). The black curve shows the scattering signal from an empty pressure cell, while the other curves shows the scattering signal level with H2O in the pressure cell at 645 K and 23 MPa with a thickness of 800 μm. The legend 0, 1, 10, and 100 ps refers to the delay time between the two x-ray pulses in this XPXP measurement. The curves for 0, 1, 10, and 100 ps are shifted vertically by 0, 50, 100, and 150, respectively, with respect to their original value for a better visualization. The average pump and probe pulse energy are 5 and 8.15 μJ, respectively, with an x-ray photon energy of 10 keV. (b) Total scattering intensity within Q ∈[0.14, 0.4 ˚A −1] normalized by the total scattering intensity within Q ∈[2.0, 2.7 ˚A −1] as a function of delay time between the pump pulse and probe pulse. The probe pulse has, on average, 8.15 μJ, while the pump pulse energy is shown in the legend. scattering of the cell with a 954 μm-thick supercritical H2O sam- ple at 653.15 K and 25 MPa. The x-ray photon energy was 9.5 keV with an x-ray beam size of 1 μm. The sample-to-detector distance was 2 m, and the detector pixel size was 50 μm. C. Signal-to-background analysis and x-ray scattering experiments 95, 013901 (2024); doi: 10.1063/5.0158497 95, 013901-10 © Author(s) 2024 FIG. 8. Correlation plot of the transmitted x-ray intensity I1 against the incident x-ray intensity I0 for two sample conditions: empty and full. One can derive the sample thickness following Eq. (5). FIG. 10. X-ray speckle contrast of x-ray pulse pairs for Δt of 1 and 7 ps at Q of 0.04 ˚A −1 and 0.1 ˚A −1 for the 954 μm-thick supercritical H2O sample at 653.15 K and 25 MPa with an x-ray photon energy of 9.5 keV and a beam size of 1 μm at the XPP instrument at LCLS. FIG. 8. Correlation plot of the transmitted x-ray intensity I1 against the incident x-ray intensity I0 for two sample conditions: empty and full. One can derive the sample thickness following Eq. (5). FIG. 8. Correlation plot of the transmitted x-ray intensity I1 against the incident x-ray intensity I0 for two sample conditions: empty and full. One can derive the sample thickness following Eq. (5). Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-10 Review of Scientific Instruments ARTICLE pubs.aip.org/aip/rsi FIG. 11. (a) Mean scattering intensity, I(Q), as a function of angular wave numbers, Q (Å−1). The black curve shows the scattering signal from an empty pressure cell, while the other curves shows the scattering signal level with H2O in the pressure cell at 645 K and 23 MPa with a thickness of 800 μm. The legend 0, 1, 10, and 100 ps refers to the delay time between the two x-ray pulses in this XPXP measurement. The curves for 0, 1, 10, and 100 ps are shifted vertically by 0, 50, 100, and 150, respectively, with respect to their original value for a better visualization. The average pump and probe pulse energy are 5 and 8.15 μJ, respectively, with an x-ray photon energy of 10 keV. (b) Total scattering intensity within Q ∈[0.14, 0.4 ˚A −1] normalized by the total scattering intensity within Q ∈[2.0, 2.7 ˚A −1] as a function of delay time between the pump pulse and probe pulse. The probe pulse has, on average, 8.15 μJ, while the pump pulse energy is shown in the legend. Review of Scientific Instruments pubs.aip.org/aip/rsi FIG. 11. (a) Mean scattering intensity, I(Q), as a function of angular wave numbers, Q (Å−1). C. Signal-to-background analysis and x-ray scattering experiments g g p p Following the signal-to-background measurements, we per- formed sp-XPCS measurements of supercritical H2O at the same experiment condition for two delay times, Δt = 1 and 7 ps. At each delay time, the elastic x-ray diffraction intensities for x-ray pulse pairs were collected over 30 min with a pulse repetition rate of 120 Hz and an average pulse energy of 0.3 μJ per pulse pair. For simplicity of analysis, we divided the area detector into two Q-regions, respectively, covering Q ∈{0.02, 0.06 ˚A −1} and Q ∈{0.06, 0.12 ˚A −1}. We refer to these regions as Q = 0.04 ˚A −1 and Q = 0.1 ˚A −1, respectively. The measured x-ray speckle contrasts are shown in Fig. 10. By measuring the x-ray speckle contrast for additional Q and Δt, one can then derive the ISF using Eq. (1). g The signal-to-background ratio can be much higher in exper- iments such as XPXP measurements, where the sample thickness and detector geometry are less constrained. Figure 11(a) shows the background scattering signal with an empty pressure cell and the scattering signal with the H2O sample in the pressure cell in a XPXP measurement at SACLA/Spring8. H2O was maintained at 645 K and 23 MPa with a nominal thickness of 800 μm. The sample detec- tor distance is 14.12 cm, and the pixel size is 50 μm. A tungsten beamstop with a diameter of 1 mm is installed right behind the pres- sure cell. This greatly reduces the static background signal from air scattering. The photon energy is 10 keV, and the average pump and Author Contributions Priyanka Muhunthan: Data curation (equal); Formal analysis (equal); Investigation (equal); Methodology (lead); Software (equal); Visualization (equal); Writing – original draft (equal); Writing – review & editing (equal). Haoyuan Li: Data curation (equal); Formal analysis (equal); Investigation (equal); Methodology (equal); Visual- ization (equal); Writing – original draft (equal); Writing – review & editing (equal). Guillaume Vignat: Data curation (equal); Investi- gation (lead); Methodology (equal); Visualization (equal); Writing – original draft (equal); Writing – review & editing (equal). Edna R. Toro: Formal analysis (equal); Investigation (equal); Methodology (lead). Khaled Younes: Investigation (supporting); Resources (supporting). Yanwen Sun: Formal analysis (equal); Investigation (supporting); Methodology (equal); Resources (supporting); Soft- ware (equal). Dimosthenis Sokaras: Funding acquisition (equal); Investigation (equal); Resources (equal); Supervision (equal); Writing – review & editing (equal). Thomas Weiss: Investi- gation (supporting); Resources (supporting). Ivan Rajkovic: Investigation (supporting); Resources (supporting). Taito Osaka: Investigation (supporting); Resources (supporting) Ichiro Inoue: Investigation (supporting); Resources (supporting). Sanghoon Song: Investigation (supporting); Resources (supporting). Takahiro Sato: Investigation (supporting); Resources (supporting). Diling Zhu: Investigation (supporting); Methodology (equal); Project administration (equal); Resources (supporting). John L. Fulton: Investigation (supporting); Methodology (equal); Writing – review & editing (equal). Matthias Ihme: Conceptualization (lead); Funding acquisition (equal); Investigation (equal); Methodol- ogy (equal); Project administration (lead); Resources (equal); Supervision (equal); Writing – review & editing (equal). 5. adjustable geometry of the sample and detector to optimize SNR during sp-XPCS measurements; and 6. incorporation of in situ diagnostic into the pressure cell to monitor beam overlap. We provide a detailed description of the pressure cell and a pro- cedure to achieve reliable operation when using SCF samples. The CAD files for this apparatus are included in the present article as the supplementary material. The apparatus has been commissioned and used for sp-XPCS, XPXP, WAXS, and SAXS experiments on SCFs. It has been demonstrated to have exceptional temperature and pressure stability during extended acquisition periods required for experimental multi-pulse, ultrafast measurements of SCFs at x-ray FELs. AUTHOR DECLARATIONS 2. provide visible and x-ray optical access to the SCF sample by 100 μm-thick single crystal diamond windows; ACKNOWLEDGMENTS Financial support from the U.S. Department of Energy, Office of Science, under DOE (BES) Award Nos. DE-SC0021129 (P.M.) and DE-SC0022222 (H.L., G.V., and K.Y.) is gratefully acknowl- edged. Work by J.L.F. was supported by the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences, Con- densed Phase and Interfacial Molecular Science program (Grant No. FWP 16248). Use of the Linac Coherent Light Source (LCLS), SLAC National Accelerator Laboratory, is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC02-76SF00515. Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accel- erator Laboratory, is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract The authors have no conflicts to disclose. The authors have no conflicts to disclose. 4. low scattering background, typically yielding a signal-to- background ratio of 4–5 at low scattering angle with super- critical water; SUPPLEMENTARY MATERIAL The complete CAD file of the pressure cell, including the pres- sure cell body, cone, and the retaining nut, is provided in the STEP format to facilitate the verification and utilization for other researchers. Conflict of Interest 3. maximum design pressure of 30 MPa and maximum design temperature of 675 K, with a factor of safety of 1.9; V. CONCLUSIONS The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of NIGMS or NIH. Some XFEL experiments reported in this work were performed at BL3 of SACLA with the approval of the Japan Synchrotron Radi- ation Research Institute (JASRI) (Proposal Nos. 2022B8017 and 2023A8012). 1. construction from titanium for chemical inertness and machining using single point diamond turning to reduce requirements for manual processing and polishing; 1. construction from titanium for chemical inertness and machining using single point diamond turning to reduce requirements for manual processing and polishing; requirements for manual processing and polishing DATA AVAILABILITY Data sharing is not applicable to this article as no new data were created or analyzed in this study. V. CONCLUSIONS The advent of x-ray FELs has enabled the development of ultra- fast multi-pulse x-ray scattering techniques, such as sp-XPCS and Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-11 Review of Scientific Instruments ARTICLE pubs.aip.org/aip/rsi No. DE-AC02-76SF00515. The Pilatus detector at beamline 4-2 at SSRL was funded under National Institutes of Health Grant No. S10OD021512. The SSRL Structural Molecular Biology Program is supported by the DOE Office of Biological and Environmental Research and the National Institutes of Health, National Institute of General Medical Sciences (Grant No. P30GM133894). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of NIGMS or NIH. Some XFEL experiments reported in this work were performed at BL3 of SACLA with the approval of the Japan Synchrotron Radi- ation Research Institute (JASRI) (Proposal Nos. 2022B8017 and 2023A8012). XPXP measurements, which have opened exciting new opportuni- ties to characterize nano-scale ultrafast dynamic processes occurring in SCFs. In the present work, we introduce a pressure cell design that is optimized for conducting sp-XPCS and XPXP experiments on SCFs. The pressure cell is able to create and contain samples of numerous SCFs, including substances with high critical temperature and pressure, such as water or dodecane. The cell is designed to maintain thermodynamic conditions precisely over the long dura- tion of x-ray FEL experiments. The pressure cell has the following features: XPXP measurements, which have opened exciting new opportuni- ties to characterize nano-scale ultrafast dynamic processes occurring in SCFs. In the present work, we introduce a pressure cell design that is optimized for conducting sp-XPCS and XPXP experiments on SCFs. The pressure cell is able to create and contain samples of numerous SCFs, including substances with high critical temperature and pressure, such as water or dodecane. The cell is designed to maintain thermodynamic conditions precisely over the long dura- tion of x-ray FEL experiments. The pressure cell has the following features: No. DE-AC02-76SF00515. The Pilatus detector at beamline 4-2 at SSRL was funded under National Institutes of Health Grant No. S10OD021512. The SSRL Structural Molecular Biology Program is supported by the DOE Office of Biological and Environmental Research and the National Institutes of Health, National Institute of General Medical Sciences (Grant No. P30GM133894). APPENDIX A: PRESSURE SAFETY ANALYSIS The metal cell body and cone is designed with sufficient materi- als thickness (at least 5 mm) to prevent mechanical failure during an Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-12 Review of Scientific Instruments Review ofi ARTICLE pubs.aip.org/aip/rsi Scientific Instruments FIG. 12. Measurements of the averaged x-ray scattering intensity of supercriti- cal water at different temperatures and a pressure of 25 MPa. These data were acquired at the BL4-2 beamline at SSRL with a photon energy of 15 keV and a photon flux of 2.5 × 1012 photons per second. T is the torque required to tighten the retaining nut into the main body of the pressure cell. For c = 0.3, D = 50 mm, and T = 300 Nm, the axial load, F, is 20 kN. For a ductile material, such as grade 5 Ti-6Al-4V alloy, the shear strength is estimated to be 0.58 times its tensile strength, σmax,shear ≈880 MPa. This corresponds to a safety factor of 11.3. APPENDIX C: DETECTOR PIXEL NUMBER We estimate the pixel number by counting the number of pix- els with angular wave-vectors within the target Q-range on an area detector. For simplicity, we assume that the area detector is orthog- onal to the incident x-ray propagation direction ⃗Kin [Fig. 13(a)]. The overall beamline geometry is depicted in Fig. 13(a). For a given x-ray detector distance L and detector pixel size, one can calculate the angular wave-vector ⃗Q = ⃗Kout −⃗Kin for each pixel. To maximize the pixel number within the target Q-range, the central pixel of the detector is placed at an angular wave-vector ⃗Q at the center of the target Q range. F As < σmax,shear, (A1) As = πnLeKn,max[ 1 2n + 0.577 35(Es,min −Kn,max)], (A2) (A1) (A2) where F is the maximum axial load, As is the shear area, n = 667 threads/m is the number of threads per unit length, Le > 5 mm is the engagement length of the thread, Kn,max = 48.7 mm is the maxi- mum minor diameter of the internal thread, and Es,min = 48.9 mm is the minimum pitch diameter of the external thread. To calculate the maximum axial load, we used F = T c D, where c is the coefficient of friction for Ti 6-Al-4V, D is the major diameter of the threads, and g g For the pixel number estimation used in Sec. II, we assume that the detector has a pixel size of 50 μm and a resolution of 1500 × 1500 pixel. For each sample–detector distance L, we first cal- culate the angular wave-vector ⃗Q for each pixel and then count the FIG. 13. (a) Model to calculate the angular wave-vector ⃗Q for each pixel on the area detector. (b) Pixel number for different detector distance L at an incident x-ray photon energy of 9.5 keV. We assume a 1500 × 1500 pixel detector, with a pixel size of 50 μm. The center of the area detector is assumed to be positioned Q = 0.1 ˚A −1. We count the pixel number within Q ∈[0.08 ˚A −1, 0.12 ˚A −1] for each L. FIG. 13. (a) Model to calculate the angular wave-vector ⃗Q for each pixel on the area detector. (b) Pixel number for different detector distance L at an incident x-ray photon energy of 9.5 keV. We assume a 1500 × 1500 pixel detector, with a pixel size of 50 μm. APPENDIX B: DIFFRACTION CROSS SECTION To estimate the x-ray scattering intensity for various sample thicknesses and detector distances, we performed SAXS measure- ments of supercritical water at 25 MPa at different temperatures at SSRL (beamline BL4-2) with a photon energy of 15 keV and a photon flux of 2.5 × 1012 photons per second. The sample thickness was d = 400 μm with a detector-sample distance of 31.6 cm and a detector pixel size of 172 μm. FIG. 12. Measurements of the averaged x-ray scattering intensity of supercriti- cal water at different temperatures and a pressure of 25 MPa. These data were acquired at the BL4-2 beamline at SSRL with a photon energy of 15 keV and a photon flux of 2.5 × 1012 photons per second. The background-subtracted and averaged scattering intensities are shown in Fig. 12 for different sample temperatures. We have per- formed the analysis presented in Sec. II at Q = 0.1 ˚A −1 and 653.15 K. The Thomson scattering cross section (dσ/dΩ)Th is computed using Eq. (3). In Eq. (3), dΩ is taken to be the solid angle spanned by each pixel. over-pressurization event. The main point of failure of the pressure cell, besides the diamond windows, is the threads on the retain- ing nut. We followed the analysis of Brooks et al.38 to ensure that the shear stress experienced by these threads is less than the shear strength of the titanium alloy, APPENDIX E: MOTION AXES The depth of field of the imaging system presented in Fig. 6 is only 6.2 μm. A precise, repeatable, and motorized motion system is therefore required to align the SCF sample, the static sample, and the YAG scintillator screen to the FEL pulses and the imaging system and to allow switching between these different devices. Within the coordinate system defined in Fig. 6(a), two linear motorized stages are required for the x- and y-motion of the pressure cell to adjust the relative position between the pressure cell and the x-ray pulse, and a 50 mm travel range is required for the x-axis in order to cover the sample, the scintillator screen, and the static sample. In addi- tion, three linear stages are required for the x, y, z motion of the x-ray beam profile monitor with respect to the pressure cell to optimize the imaging quality of the x-ray beam profile monitor on the scintillator screen. Due to the limited working distance of the imaging system (Fig. 6), the right angle mirror also requires two manual x and z stages to adjust its position with respect to the x-ray beam profile monitor. In this way, one can optimize the distribution of the work- ing distance between l1 and l2 (Fig. 6) for an optimal heat insulation between the lens and the cell, necessary to avoid thermal distortion artifacts in the imaging system. FIG. 14. Pressure cell assembly as typically used during measurements. X-ray FEL pulses are traveling from left to right. The pressure cell is shown in golden-brown, the scintillator and its holder are shown in in white, and the static sample and its holder are shown in in green. Vertical optical posts are used to keep the electrical cable and piping out of the beam path. An aluminum intermediary plate (gray) is used to attach all these components to a Newport kinematic mount (black), which interfaces with the beamline. Four ceramic posts are located between the cell and the aluminum plate to thermally insulate the cell and improve its thermal stability. Ceramic fiber paper is also wrapped around the cell for thermal insulation (not shown here). APPENDIX C: DETECTOR PIXEL NUMBER The center of the area detector is assumed to be positioned Q = 0.1 ˚A −1. We count the pixel number within Q ∈[0.08 ˚A −1, 0.12 ˚A −1] for each L. Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 Review of Scientific Instruments Review of Scientific Instruments pubs.aip.org/aip/rsi pixel number within Q ∈{0.08 ˚A −1, 0.12 ˚A −1}. The correspond- ing pixel number for each L is reported in Fig. 13(b) and was used in Eq. (2) to obtain the SNR reported in Fig. 2(c). commonly found at a number of lightsources, or to a motion stage through three M4 screws. The fluid lines and cartridge heaters are also equipped with quick-disconnect connectors. After removal, the cell can be quickly cooled down in water so that leaks or failures can be addressed. APPENDIX D: BEAMLINE INSTALLATION The static sample assembly (green in Fig. 14) holds a static sam- ple of silica nanopowder coplanar with the YAG scintillator screen and the mid-plane of the sample. This static sample is used to deter- mine the effective overlap μ within a pulse pair [Eq. (1)].21 Similar to the YAG scintillator screen, it can be quickly accessed by a transverse translation in order to perform regular calibration over the course of an experiment. Beamtime at FEL facilities is currently a very limited resource. This pressure cell therefore requires a high level of reliability and must accommodate rapid field repairs if any unexpected issues were to occur during an experiment. The high working temperature of the cell is a major obstacle for these field repairs, as the first step in repairs is disassembly from the beamline. To address the high temperature, four 1/4 in. −20 threading holes are included on the intermediate mounting plate in Fig. 14. This allows users to install two long 1/2 in. standard optical posts as a safe handle to remove the pressure cell from the beamline even with the pressure cell at high temperature, as shown in Fig. 14. To facilitate the installation and to increase the portability, the pressure cell assembly can be installed on a Newport BKL-4 kinematic mount (shown in Fig. 14), APPENDIX F: LASER ATTENUATION MEASUREMENT OF SAMPLE THICKNESS X-ray attenuation measurements are not always possible to characterize the sample thickness. One can also use visible lasers to measure the sample thickness using a laser attenuation measure- ment. This was done by measuring the transmission of laser light through the fluid sample using a photo-diode or a commercial laser power-meter. Our sample thickness measurement setup is shown in Fig. 15. g A 520 nm laser was used to measure the laser intensity atten- uation. To obtain reliable attenuation measurements, we tightly focus the laser beam on the pressure cell to a spot size smaller than the optical entrance, which is 1 mm in diameter. Since water does not significantly absorb light at 520 nm, a [Fe(phen)3]SO4 dye (Ferroin) was dissolved in water. The extinction coefficient (ε) of this aqueous solution was measured as 11 210 M−1 cm−1 by ultra- violet visible spectroscopy. The sample thickness can be determined following FIG. 14. Pressure cell assembly as typically used during measurements. X-ray FEL pulses are traveling from left to right. The pressure cell is shown in golden-brown, the scintillator and its holder are shown in in white, and the static sample and its holder are shown in in green. Vertical optical posts are used to keep the electrical cable and piping out of the beam path. An aluminum intermediary plate (gray) is used to attach all these components to a Newport kinematic mount (black), which interfaces with the beamline. Four ceramic posts are located between the cell and the aluminum plate to thermally insulate the cell and improve its thermal stability. Ceramic fiber paper is also wrapped around the cell for thermal insulation (not shown here). FIG. 14. Pressure cell assembly as typically used during measurements. X-ray FEL pulses are traveling from left to right. The pressure cell is shown in golden-brown, the scintillator and its holder are shown in in white, and the static sample and its holder are shown in in green. Vertical optical posts are used to keep the electrical cable and piping out of the beam path. An aluminum intermediary plate (gray) is used to attach all these components to a Newport kinematic mount (black), which interfaces with the beamline. Four ceramic posts are located between the cell and the aluminum plate to thermally insulate the cell and improve its thermal stability. Ceramic fiber paper is also wrapped around the cell for thermal insulation (not shown here). REFERENCES The mea- sured deviation from the nominal value is induced by a combination of the machining error and the deformation of the metal parts under the large preloaded force on the retaining nut. 9D. Bolmatov, D. Zav’yalov, M. Gao, and M. Zhernenkov, “Structural evolution of supercritical CO2 across the Frenkel line,” J. Phys. Chem. Lett. 5, 2785–2790 (2014). 10P. Linstrom and W. Mallard, NIST Chemistry WebBook (National Institute of Standards and Technology, Gaithersburg, MD, 2023). 11H. E. Stanley, “Scaling, universality, and renormalization: Three pillars of modern critical phenomena,” Rev. Mod. Phys. 71, S358–S366 (1999). 12G. G. Simeoni, T. Bryk, F. A. Gorelli, M. Krisch, G. Ruocco, M. Santoro, and T. Scopigno, “The Widom line as the crossover between liquid-like and gas-like behaviour in supercritical fluids,” Nat. Phys. 6, 503–507 (2010). 13S. Artemenko, P. Krijgsman, and V. Mazur, “The Widom line for supercritical fluids,” J. Mol. Liq. 238, 122–128 (2017). REFERENCES pressure cell. Property Ti-6Al-4Va Type IIa CVD diamondb Density (g/mm3) 4.43 3.515 Hardness, Knoop 363 90 GPa Tensile strength, yield (MPa) 880 500–1400 Modulus of elasticity (GPa) 113.8 1050 Compressive yield strength (MPa) 970 >110 000 Fracture toughness (MPa m1/2) 75 Poisson’s ratio 0.342 0.1–0.29 Shear modulus (GPa) 44 Shear strength (GPa) 550 aProperties are from the ASM Aerospace Specification Metals, Inc. website. bProperties are from the single-crystal CVD diamond data sheet of Applied Diamond USA. 1P. F. McMillan and H. E. Stanley, “Going supercritical,” Nat. Phys. 6, 479–480 (2010). 2E. L. N. Escobar, T. A. da Silva, C. L. Pirich, M. L. Corazza, and L. Pereira Ramos, “Supercritical fluids: A promising technique for biomass pretreatment and fractionation,” Front. Bioeng. Biotechnol. 8, 252 (2020). 24 October 2024 04:40:18 3B. Ahangari and J. Sargolzaei, “Extraction of lipids from spent coffee grounds using organic solvents and supercritical carbon dioxide,” J. Food Process. Preserv. 37, 1014–1021 (2013). 4X. Zhang, S. Heinonen, and E. Levänen, “Applications of supercritical carbon dioxide in materials processing and synthesis,” RSC Adv. 4, 61137–61152 (2014). 5 5H. Chen, D. Y. Goswami, and E. K. Stefanakos, “A review of thermodynamic cycles and working fluids for the conversion of low-grade heat,” Renewable Sustainable Energy Rev. 14, 3059–3067 (2010). 6H. Maynard-Casely, “Supercritical fluids in planetary environments,” in The Liq- uid and Supercritical Fluid States of Matter, edited by J. E. Proctor (CRC Press, 2020), pp. 181–198. 7M. P. Ishmael, M. Z. Lukawski, and J. W. Tester, “Isobaric heat capacity (Cp) measurements of supercritical fluids using flow calorimetry: Equipment design and experimental validation with carbon dioxide, methanol, and carbon dioxide- methanol mixtures,” J. Supercrit. Fluids 117, 72–79 (2016). 8S. M. Benson and D. R. Cole, “CO2 sequestration in deep sedimentary formations,” Elements 4, 325–331 (2008). where I0 and I are the laser intensity before and after the sample, respectively, and c is the dye concentration. We used the photo- diode intensity measured with pure water as I0, thereby accounting for the transmissivity of the diamond windows. To determine the sample thickness, we measured the transmissivity with multiple dye concentrations. A sample thickness of 440 ± 35 μm is obtained for a cone designed with a nominal sample thickness of 600 μm. APPENDIX F: LASER ATTENUATION MEASUREMENT OF SAMPLE THICKNESS (F1) I = I0 exp {−εcd}, Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-14 Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 Review ofi pubs.aip.org/aip/rsi Scientific Instruments FIG. 15. Setup for sample thickness measurements. (left) Dye used for absorption measurements. (middle) Laser absorption through the entrance optical hole in the pressure cell. (right) The intensity of photo-diode placed at the exit optical hole in the pressure cell. FIG. 15. Setup for sample thickness measurements. (left) Dye used for absorption measurements. (middle) Laser absorption through the entrance optical hole in the pressure cell. (right) The intensity of photo-diode placed at the exit optical hole in the pressure cell. TABLE III. Mechanical properties of materials utilized in the construction of the pressure cell. pubs.aip.org/aip/rsi 35J 16T. Morita, K. Kusano, H. Ochiai, K.-i. Saitow, and K. Nishikawa, “Study of inho- mogeneity of supercritical water by small-angle x-ray scattering,” J. Chem. Phys. 112, 4203–4211 (2000). 35J. D. Grunwaldt, M. Ramin, M. Rohr, A. Michailovski, G. R. Patzke, and A. Baiker, “High pressure in situ x-ray absorption spectroscopy cell for studying simultaneously the liquid phase and the solid/liquid interface,” Rev. Sci. Instrum. 76, 054104 (2005). 17R. Ishii, S. Okazaki, I. Okada, M. Furusaka, N. Watanabe, M. Misawa, and T. Fukunaga, “A neutron scattering study of the structure of supercritical carbon dioxide,” Chem. Phys. Lett. 240, 84–88 (1995). 36N. Ando, P. Chenevier, M. Novak, M. W. Tate, and S. M. Gruner, “High hydrostatic pressure small-angle X-ray scattering cell for protein solution stud- ies featuring diamond windows and disposable sample cells,” J. Appl. Crystallogr. 41, 167–175 (2008). 18U. Ranieri, S. Klotz, R. Gaal, M. M. Koza, and L. E. Bove, “Diffusion in dense supercritical methane from quasi-elastic neutron scattering measurements,” Nat. Commun. 12, 1958 (2021). 37T. Kawai, W.-J. Chun, K. Asakura, Y. Koike, M. Nomura, K. Bando, S. Ted Oyama, and H. Sumiya, “Design of a high-temperature and high-pressure liquid flow cell for x-ray absorption fine structure measurements under catalytic reaction conditions,” Rev. Sci. Instrum. 79, 014101 (2008). 19W. Lu, B. Friedrich, T. Noll, K. Zhou, J. Hallmann, G. Ansaldi, T. Roth, S. Serkez, G. Geloni, A. Madsen, and S. Eisebitt, “Development of a hard X-ray split-and- delay line and performance simulations for two-color pump-probe experiments at the European XFEL,” Rev. Sci. Instrum. 89, 063121 (2018). 38N. J. Brooks, B. L. L. E. Gauthe, N. J. Terrill, S. E. Rogers, R. H. Templer, O. Ces, and J. M. Seddon, “Automated high pressure cell for pressure jump x-ray diffraction,” Rev. Sci. Instrum. 81, 064103 (2010). 20T. Hirano, T. Osaka, Y. Morioka, Y. Sano, Y. Inubushi, T. Togashi, I. Inoue, S. Matsuyama, K. Tono, A. Robert et al., “Performance of a hard X-ray split-and- delay optical system with a wavefront division,” J. Synchrotron Radiat. 25, 20–25 (2018). 39D. Hermida-Merino, G. Portale, P. Fields, R. Wilson, S. P. Bassett, J. Jennings, M. Dellar, C. Gommes, S. M. Howdle, B. C. M. Vrolijk, and W. Bras, “A high pressure cell for supercritical CO2 on-line chemical reactions studied with x-ray techniques,” Rev. Sci. Instrum. 85, 093905 (2014). 21H. Li, Y. Sun, J. Vila-Comamala, T. Sato, S. Song, P. Sun, M. H. Seaberg, N. pubs.aip.org/aip/rsi Wang, J. Hastings, M. Dunne, P. Fuoss, C. David, M. Sutton, and D. Zhu, “Generation of highly mutually coherent hard-x-ray pulse pairs with an amplitude-splitting delay line,” Phys. Rev. Res. 3, 043050 (2021). 40L. B. Skinner, M. Galib, J. L. Fulton, C. J. Mundy, J. B. Parise, V.-T. Pham, G. K. Schenter, and C. J. Benmore, “The structure of liquid water up to 360 MPa from x-ray diffraction measurements using a high Q-range and from molecular simulation,” J. Chem. Phys. 144, 134504 (2016). 22W. Roseker, S. Hruszkewycz, F. Lehmkühler, M. Walther, H. Schulte- Schrepping, S. Lee, T. Osaka, L. Strüder, R. Hartmann, M. Sikorski, S. Song, A. Robert, P. Fuoss, M. Sutton, G. Stephenson, and G. Grübel, “Towards ultrafast dynamics with split-pulse X-ray photon correlation spectroscopy at free electron laser sources,” Nat. Commun. 9, 1704 (2018). 41D. K. Rai, R. E. Gillilan, Q. Huang, R. Miller, E. Ting, A. Lazarev, M. W. Tate, and S. M. Gruner, “High-pressure small-angle X-ray scattering cell for biological solutions and soft materials,” J. Appl. Crystallogr. 54, 111–122 (2021). 23F. Perakis, G. Camisasca, T. J. Lane, A. Späh, K. T. Wikfeldt, J. A. Sellberg, F. Lehmkühler, H. Pathak, K. H. Kim, K. Amann-Winkel et al., “Coherent X-rays reveal the influence of cage effects on ultrafast water dynamics,” Nat. Commun. 9, 1917 (2018). 42R. C. Miller, C. Cummings, Q. Huang, N. Ando, and R. E. Gillilan, “Inline small-angle X-ray scattering-coupled chromatography under extreme hydrostatic pressure,” Protein Sci. 31, e4489 (2022). 24Y. Shinohara, T. Osaka, I. Inoue, T. Iwashita, W. Dmowski, C. W. Ryu, Y. Sarathchandran, and T. Egami, “Split-pulse X-ray photon correlation spec- troscopy with seeded X-rays from X-ray laser to study atomic-level dynamics,” Nat. Commun. 11, 6213 (2020). 43F. Bencivenga, “The high-frequency dynamics of liquids and supercritical fluids,” Ph.D. thesis, Université Joseph-Fourier, Grenoble, France, 2006. 44B. Ackerson, P. Pusey, and R. Tough, “Interpretation of the interme- diate scattering function at short times,” J. Chem. Phys. 76, 1279–1282 (1982). 25A. Jayaraman, “Diamond anvil cell and high-pressure physical investigations,” Rev. Mod. Phys. 55, 65–108 (1983). 45Y. Sun, “Two-pulse X-ray photon correlation spectroscopy at the Linac coherent light source,” Ph.D. thesis, Stanford University, Stanford, CA, 2020. 26R. Letoullec, J. P. Pinceaux, and P. Loubeyre, “The membrane diamond anvil cell: A new device for generating continuous pressure and temperature variations,” High Pressure Res. 1, 77–90 (1988). 46S. O. Hruszkewycz, M. Sutton, P. H. Fuoss, B. Adams, S. Rosenkranz, K. pubs.aip.org/aip/rsi F. Ludwig, W. Roseker, D. Fritz, M. Cammarata, D. Zhu, S. Lee, H. Lemke, C. Gutt, A. Robert, G. Grübel, and G. B. Stephenson, “High contrast x-ray speckle from atomic-scale order in liquids and glasses,” Phys. Rev. Lett. 109, 185502 (2012). 27R. L. Smith and Z. Fang, “Techniques, applications and future prospects of dia- mond anvil cells for studying supercritical water systems,” J. Supercrit. Fluids 47, 431–446 (2009). 28K. Nishikawa and M. Takematsu, “Construction of sample holder for X-ray diffraction experiments on supercritical fluids,” Jpn. J. Appl. Phys. 32, 5155–5158 (1993). 47M. Sikorski, Y. Feng, S. Song, D. Zhu, G. Carini, S. Herrmann, K. Nishimura, P. Hart, and A. Robert, “Application of an ePix100 detector for coherent scatter- ing using a hard X-ray free-electron laser,” J. Synchrotron Radiat. 23, 1171–1179 (2016). 29D. Pfund, T. Zemanian, J. Linehan, J. Fulton, and C. Yonker, “Fluid structure in supercritical xenon by nuclear magnetic resonance spectroscopy and small angle X-ray scattering,” J. Phys. Chem. 98, 11846–11857 (1994). 48Evaluation of coherence factor for high ⃗Q data, https://www.physics.mcgill.ca/ ∼mark/coherence/yorick/highqbeta.pdf, accessed 22 September 2023. 49A beamtime summary report for experiments 2022B8017 and 2023A8012 at Spring8/SACLA demonstrating operation of the pressure cell at these conditions is available upon request to the corresponding author. 30K. Nishikawa and T. Morita, “Small-angle X-ray-scattering study of supercritical trifluoromethane,” J. Phys. Chem. B 101, 1413–1418 (1997). 31M. M. Hoffmann, R. S. Addleman, and J. L. Fulton, “Short-pathlength, high- pressure flow cell for static and time-resolved infrared spectroscopy suitable for supercritical fluid solutions including hydrothermal systems,” Rev. Sci. Instrum. 71, 1552–1556 (2000). 50P. Kritzer, “Corrosion in high-temperature and supercritical water and aqueous solutions: A review,” J. Supercrit. Fluids 29, 1–29 (2004). 51X. Tang, S. Wang, L. Qian, Y. Li, Z. Lin, D. Xu, and Y. Zhang, “Corrosion behav- ior of nickel base alloys, stainless steel and titanium alloy in supercritical water containing chloride, phosphate and oxygen,” Chem. Eng. Res. Des. 100, 530–541 (2015). 32T. Koga, S. Zhou, B. Chu, J. L. Fulton, S. Yang, C. K. Ober, and B. Erman, “High-pressure cell for simultaneous small-angle x-ray scattering and laser light scattering measurements,” Rev. Sci. Instrum. 72, 2679–2685 (2001). 52S. Suet To, V. H. Wang, and W. B. Lee, “Single point diamond turning technology,” in Materials Characterisation and Mechanism of Micro-Cutting in Ultra-Precision Diamond Turning (Springer, 2018), pp. 3–6. 33J. L. Fulton, Y. Chen, S. M. Heald, and M. APPENDIX G: MECHANICAL PROPERTIES l 14F. Simeski and M. Ihme, “Supercritical fluids behave as complex networks,” Nat. Commun. 14, 1996 (2023). The mechanical properties of materials utilized in the construc- tion are shown in Table III. 15K. Nishikawa, I. Tanaka, and Y. Amemiya, “Small-angle X-ray scattering study of supercritical carbon dioxide,” J. Phys. Chem. 100, 418–421 (1996). Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-15 Review of Scientific Instruments Review of Scientific Instruments ARTICLE pubs.aip.org/aip/rsi pubs.aip.org/aip/rsi Balasubramanian, “High-pressure, high-temperature x-ray absorption fine structure transmission cell for the study of aqueous ions with low absorption-edge energies,” Rev. Sci. Instrum. 75, 5228–5231 (2004). 53W. Sherman and A. Stadtmuller, Experimental Techniques in High-Pressure Research (Wiley, Chichester, 1987). 34D. Testemale, R. Argoud, O. Geaymond, and J. L. Hazemann, “High pres- sure/high temperature cell for x-ray absorption and scattering techniques,” Rev. Sci. Instrum. 76, 043905 (2005). 54T. C. Poulter and F. Buckley, “Diamond windows for withstanding very high pressures,” Phys. Rev. 41, 364–365 (1932). Rev. Sci. Instrum. 95, 013901 (2024); doi: 10.1063/5.0158497 © Author(s) 2024 95, 013901-16
https://openalex.org/W4379162487
https://www.researchsquare.com/article/rs-2988304/latest.pdf
English
null
Unlabeled Data Selection for Active Learning in Image Classification
Research Square (Research Square)
2,023
cc-by
6,682
Unlabeled Data Selection for Active Learning in Image Classification Unlabeled Data Selection for Active Learning in Image Classification Version of Record: A version of this preprint was published at Scientific Reports on January 3rd, 2024. See the published version at https://doi.org/10.1038/s41598-023-50598-z. Keywords: License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Additional Declarations: No competing interests reported. Version of Record: A version of this preprint was published at Scientific Reports on January 3rd, 2024. See the published version at https://doi.org/10.1038/s41598-023-50598-z. Page 1/19 Page 1/19 Abstract Active Learning has emerged as a viable solution for addressing the challenge of labeling extensive amounts of data in data-intensive applications such as computer vision and neural machine translation. The main objective of Active Learning is to automatically identify a subset of unlabeled data samples for annotation. This identification process is based on an acquisition function that assesses the value of each sample for model training. In the context of computer vision, image classification is a crucial task that typically requires a substantial training dataset. This research paper intro-duces innovative selection methods within the Active Learning framework, aiming to identify informative images from unlabeled datasets while minimizing the number of required training data. The proposed methods, namely Similarity-based Selection, Prediction Probability-based Selection, and Competence-based Active Learning, have been extensively evaluated through experiments conducted on popular datasets like Cifar10 and Cifar100. The experimental results demonstrate that the proposed methods outperform random selection and conventional selection techniques. The superior performance of the novel selection methods underscores their effectiveness in enhancing the Active Learning process for image classification tasks. Introduction Image classification has become a critical technology across various industries, covering applications from healthcare, public safety to intelligent transportation. However, building a high-quality image classification model typically requires a large labeled dataset. In practice, such datasets are often not readily available and the process of labeling images is time-consuming and expensive. This situation greatly hampers the progress and applications of image classification models, particularly in sectors requiring swift responses. It restricts the system scalability and may lead to inferior model performance due to insufficient diversity in labeled data, thus compromising the model's ability to generalize to new scenarios. In such cases, it becomes crucial to select a subset of images from the unlabeled datasets that can be labeled to create a training set capable of achieving high classification accuracy. Active Learning is a popular approach in machine learning that reduces the cost and effort of labeling large amounts of data by iteratively selecting the most informative samples to label. By doing so, it aims to reduce the size of the labeled training set needed to train a high-performing model, which can be especially useful in cases where labeling is expensive or time-consuming. Through active learning, we can not only build effective image classification models in data-scarce or hard-to-obtain scenarios, but also better adapt to the continually evolving and changing data environments, such as emerging social media platforms and high-resolution satellite images. Active Learning has been successfully applied to a variety of tasks, including image classification1,2,3, target detection4, and semantic segmentation5,6, with immense potential for future applications in image classification and other machine learning domains. There are various Active Learning query strategies that rely on informativeness7 select the most valuable samples for the current model. Informativeness-based methods select unlabeled samples with the Page 2/19 Page 2/19 highest uncertainty, while representativeness8 emphasizes the diversity of samples that align with the underlying data distribution of the unlabeled data pool. However, both Active Learning methods have been criticized for overemphasizing data selection and neglecting the model's comprehension ability. As a result, some of the samples selected by Active Learning may exceed the model's comprehension ability, leading to local optimization and poor results. Moreover, splitting the training set data into too many training batches can significantly increase training time. Introduction Therefore, there's an urgent need to develop more efficient and balanced Active Learning methods that consider both informativeness and representativeness, and the model's learning capacity, to ensure high performance and efficiency. Considering the limitations of traditional Active Learning strategies and the growing demand for efficient, adaptable, and high-performing image classification models, we utilize the Active Learning approach to propose three novel methods within the framework of deep neural models. Based on previous literature, our proposition aligns with the imperative need to balance the informative and representative qualities, and align it with the model's learning capacity. The first method, called similarity-based selection, is based on the similarity between unlabeled images and the labeled image datasets. This method ensure that the selected unlabeled data is representative of the already labeled data and helps avoid the selection bias that can occur with purely uncertainty-based selection methods, and promotes better coverage of the data distribution space. The second method, Prediction Probability-based Selection main idea is to test the image classification of the initially trained deep learning model in the unlabeled datasets, and get the probability that each unlabeled data belongs to each category, and determine whether to use this unlabeled data to train model next cycle. By basing the selection on the model's current performance on the unlabeled data, the new data incorporated into the training set is both informative and within the model's learning capacity. The third Method is Competence-based Active Learning, is inspired by the way humans teach algorithms, progressing from easier to more challenging concepts. This method adapts the selection strategy to the model's learning pace and capacity, which is particularly important in the context of deep learning models that are prone to getting stuck in local optima. Particularly, we make the following two contributions: First: Considering data informativeness and representativeness, alongside the model's learning capacity, our paper presents three novel Active Learning methods for selecting data for image classification. The first method uses the prediction probability of unlabeled images, while the second method uses the similarity between the unlabeled images and the labeled image datasets. And third method, we introduce the concept of learning difficulty based on the prediction probability of unlabeled images, and define the learning ability of the model. Active Learning Active Learning has proven to be effective in various applications, including image classification1,3,10,11, image retrieval12, image captioning13, object detection14, and regression15,16. In recent years, Active Learning strategies have been categorized into three main categories: informativeness16,17,18,19,20, representativeness8,10, and hybrid approaches21,22. Informativeness-based methods focus on selecting the most uncertain samples to clarify the areas of highest uncertainty in the model's knowledge, thus promoting more robust learning. Representativeness-based methods aim to enhance the model's generalization ability by exposing it to diverse training examples, ensuring the selected samples capture the full range of data variability. Hybrid approaches combine both informativeness and representativeness criteria to extract the most valuable information from the unlabeled data pool, thereby optimizing the efficiency and effectiveness of the learning process. Despite the success of these strategies, each method has its limitations. For example, informativeness-based methods overlook the fact that not all diverse samples are equally informative or beneficial for training, while representativeness-based methods might overlook rare yet informative instances. Hybrid approaches, though aiming to balance these issues, often introduce increased complexity and computational costs. Therefore, our work aims to develop novel active learning strategies that address these limitations while maintaining high performance in image classification tasks. Introduction By comparing the ability of the model and the difficulty of the training data, we can select training data more effectively, and each round of training can select a flexible number of samples. Second: The experiments conducted on the Cifar10 and Cifar1009 datasets show that our proposed Active Learning methods outperform previous approaches in terms of effectiveness and stability in the image classification task. Our methods not only improve the generalization ability of the model but also reduce the training time compared to previous work. By offering innovative solutions that address these Page 3/19 Page 3/19 pivotal aspects, we intend to bridge the existing gaps and propel the advancement of image classification technology. pivotal aspects, we intend to bridge the existing gaps and propel the advancement of image classification technology. Informativeness-based method Informativeness-based approaches are considered as the best strategy in Active Learning and they can be categorized into bayesian16 and non-bayesian23 frameworks. The bayesian approach, such as the one proposed by Gal et al.16, uses Monte Carlo Dropout to estimate the uncertainty of the unlabeled data. However, this method requires dense dropout layers, which can reduce the convergence speed and result in huge computational costs for large-scale learning. In contrast, the non-bayesian frameworks, such as the one proposed by Li et al.23, use an information density measure and an uncertainty measure to select pivotal instances for labeling in image classification. However, these methods may suffer from bias towards dense data regions and might overlook potentially valuable outliers. Recent work has attempted to overcome these limitations, for instance Ash et al.24 proposed a new method to measure data uncertainty by calculating the expected gradient length, while Li et al.25 rethought the structure of the loss prediction module and defined the acquisition function as a learning-to-rank problem. Yoo et al.7 and He et al.26 employ a loss module to learn the loss of a target model and select data based on their output loss. Despite these advancements, the challenge of balancing model uncertainty with computational Page 4/19 Page 4/19 efficiency and holistic data representation still persists. Overemphasis on uncertainty often leads to biases towards more challenging samples, leaving out simpler yet diverse instances that could improve the model's overall generalization capability. Representativeness-Based method Representativeness-Based method usually uses a pre-trained self-supervised model to cluster the unlabeled data and select samples from each cluster that are most dissimilar to the already labeled samples. This method achieves good results in image classification tasks while reducing the number of labeled samples needed for training. In summary, representativeness-based methods focus on selecting diverse samples to enhance the robustness and generalization ability of the model. Sener et al8 regard the step of selecting data as an issue of finding a current optimal set. In other words, a fixed number of samples are selected from the unlabeled data for the sake of adding to the set, and the newly added samples need to satisfy the maximum Euclidean distance from the samples in the set. The Core set method has been proved to be a relatively successful Active Learning algorithm. The Core-set method single out the samples by minimizing the Euclidian distance between the unlabeled data and labeled data in the feature space. However, the performance of this method is critically restricted by the data category in the datasets. To address this, Sinha et al.27 instead employ an adversarial approach to diversity-based sample query, which selects the unlabeled data based on the discriminator’s output, regards it as a selection criteria. However, the effectiveness and robustness of this approach can be influenced by the quality and reliability of the discriminator's output. Furthermore, Bengar et al.28 integrated Active Learning with self-supervised pre-training, but further evaluation and analysis are required to assess its specific implementation and performance in different scenarios. While the representative-based methods mentioned above offer valuable insights, they still face specific limitations in accurately selecting the most informative and representative samples, which directly impact the efficiency and effectiveness of the sample selection process. These limitations include potential biases in diversity selection, the influence of discriminator output quality. Therefore, there is a need for further advancements and novel approaches to address these limitations and improve the overall sample selection process in Active Learning. Method Our image classification framework is based on Active Learning, which involves a large pool of unlabeled data and a labeled dataset . In each cycle, we select N samples for annotation to maximize our classification model's performance. Active Learning methods typically allocate the budget sequentially over a few cycles, with the batch-mode variant labeling b samples per cycle as the only viable option for CNN31 training. At the start of each cycle, we train the model on the labeled set and then use our proposed acquisition function to select a certain amount of data from to add to . We then retrain the model using the updated dataset and repeat this process until all selected samples are trained. The acquisition function is the most crucial component and the main point of difference among Active Learning methods in the literature. Figure 1 provides an overview of our Active learning framework, our objective is to identify the most valuable images from unlabeled datasets, which can enhance the model's performance. To achieve this goal, we have developed methods for selecting informative images for image classification within an Active Learning framework. DU DL DL DU DL Our proposed selection methods include Similarity-based Selection, which is used solely for selecting data, and Prediction Probability-Based Selection, which is combined with the Curriculum Active Learning method we introduced as Competence-based Active Learning for model training. Data selection can be approached from two perspectives: the data itself and the model being used. From the perspective of data, the coverage of information contained in the images is a critical factor in our selection process. When considering the model, we select data that is more beneficial to the current model. In the context of image classification, our selection of images is based on the degree of difficulty in classifying the images for the current model. Curriculum Learning The concept of Curriculum Learning draws inspiration from the learning process observed in humans and animals, where they gradually take on more challenging tasks once they have mastered easier ones. This approach has been a topic of interest for many years 29. In traditional machine learning, models often randomly select small batches of data from the training set and update the model parameters using stochastic gradient descent. However, with the emergence of deep learning techniques like RNNs and Transformers, which employ highly non-convex loss functions, these models can frequently get trapped in local optima, leading to prolonged training times and subpar generalization performance. Page 5/19 Based on a thorough analysis of the research mentioned in 30, we have developed an innovative approach for data selection in image classification. Our method revolves around assessing the difficulty of unlabeled images for the model's learning process, primarily based on the probability assigned by the model to its current predictions. Drawing inspiration from curriculum learning, we also consider the model's learning capacity and carefully choose the most appropriate images, taking into account their difficulty within the unlabeled dataset. Extensive experiments have demonstrated that our proposed method yields substantial reductions in training iteration steps while simultaneously enhancing the model's generalization performance. Similarity-based Selection We use image embeddings to calculate the similarity between images and exclude images that are similar to those already selected. Image embedding is a low-dimensional continuous image space representation. To estimate the score of an image, we follow these steps: Page 6/19 Page 6/19 Sscore (s) = max l∈DL (cos (emb(s), emb(l)) 1 The score of an image s is determined using its embedding, represented by emb(s). To compute this score, we first calculate the similarity between image s and all the images in the labeled datasets. The largest value of this similarity is selected as the similarity of image s to the labeled datasets. A higher indicates that image s is more dissimilar to the labeled datasets. We select image s to be included in , if it has significant image information and is not redundant with high probability. We believe that these dissimilar images are more valuable to the current model than other similar images, considering the image information. At each iteration, we select the top N images based on their and add them to while removing them from . The Fig. 2 shows the algorithm. Sscore (s) DL Sscore (s) DL DU Prediction Probability-Based Selection To enhance the selection of images for Active Learning, we propose using the Prediction Probabilities of images in image classification. Firstly, we train an Image Classification Model using labeled images. We then use this model to predict the labels of images in that are not labeled. Some images are predicted with high accuracy while others are not. We assume that the images with poor predictions contain new information that the current model needs to learn, while the images with high accuracy have already been learned. Based on this assumption, we select the images with poor predictions to be added to the labeled datasets, which helps to strengthen the model's learning ability. DU When using a pre-trained model to predict unlabeled images, we can compute the probability of each category to which the samples may belong. This is done by obtaining the output probabilities from the softmax layer of the model. Probset (Di U) = {Prob (Di U ∈c0) , Prob (Di U ∈c1) , … … . . , Prob (Di U ∈cn)} Probset (Di U) = {Prob (Di U ∈c0) , Prob (Di U ∈c1) , … … . . , Prob (Di U ∈cn)} 2 In general, we select the category with the highest probability for image classification. If the maximum probability has a significant advantage over the probabilities of other categories, we consider the model to be confident in its prediction. However, if the maximum predicted probability is close to the probabilities of other categories, the model may have difficulty accurately classifying the sample. Therefore, we use the prediction probability as a score to select images for Active Learning. If the maximum predicted probability is high, we assume that the model has learned the information in the sample and does not need to be added to the labeled datasets. If the maximum predicted probability is not high enough, we assume that the model needs to learn the information contained in the sample, and thus the sample should be added to the labeled datasets. In general, we select the category with the highest probability for image classification. If the maximum probability has a significant advantage over the probabilities of other categories, we consider the model to be confident in its prediction. However, if the maximum predicted probability is close to the probabilities of other categories, the model may have difficulty accurately classifying the sample. Prediction Probability-Based Selection Therefore, we use the prediction probability as a score to select images for Active Learning. If the maximum predicted probability is high, we assume that the model has learned the information in the sample and does not need to be added to the labeled datasets. If the maximum predicted probability is not high enough, we assume that the model needs to learn the information contained in the sample, and thus the sample should be added to the labeled datasets. Page 7/19 PScore (i) = 1 −max (Probset (Di U)) max (Probset (Di U)) 3 The larger the is, the worse the sample is predicted. Hence, we select the first N largest images as the new samples and add them to meanwhile remove the new samples from . Figure 3 shows the algorithm 2 as follows: PScore (i) PScore (i) DL DU The larger the is, the worse the sample is predicted. Hence, we select the first N largest images as the new samples and add them to meanwhile remove the new samples from . Figure 3 shows the algorithm 2 as follows: PScore (i) PScore (i) DL DU Competence-based Active Learning We have proposed a training framework called Competence-Based Active Learning, which combines Prediction Probability-Based Selection with curriculum learning(32). The idea behind this framework is that by selecting training samples that are appropriate for the current level of competence of the model, we can improve its performance. We define two central concepts for this framework, as follows: Difficulty The learning difficulty of a sample can be defined as its, which indicates how poorly the sample is predicted by the current model. When an unlabeled sample has a low, it suggests that the current model struggles to predict it accurately, indicating that the sample is difficult to classify. Therefore, we can use as a measure of the difficulty of a sample for the current model. Difficulty (i) = PScore (i) Difficulty (i) = PScore (i) Datasets CIFAR-10 and CIFAR-100 are widely used benchmark datasets in the field of computer vision. The CIFAR- 10 datasets contain 50,000 training images and 10,000 test images, with each image belonging to one of 10 classes: airplane, automobile, bird, cat, deer, dog, frog, horse, ship, and truck. The CIFAR-100 datasets also contain 50,000 training images and 10,000 test images, but with each image belonging to one of 100 fine-grained classes, which are grouped into 20 coarse-grained classes. Both datasets have an image size of 32x32 pixels and the images are in RGB color format. The CIFAR-10 and CIFAR-100 datasets are challenging benchmark datasets for image classification tasks and have been widely used in many research studies in the field of computer vision. Competence The competence of a learner can be seen as a value between 0 and 1, which reflects the learner's growth during its training. This value is defined as a function of the learner's state, specifically as the proportion of unlabeled data that the learner is allowed to select from at a given time t (measured in terms of training steps). The unlabeled data are ranked based on their difficulty, and the learner is allowed to use the top portion of them at time t. In the condition of the root form, compared to other functions, can obtain best performance to measure the competence of current model, because of that in our paper we define as follows: c (t) c (t) Csqrt (t) ≜min(1, √t + C 2 0 ) 1 −C 2 0 T 5 5 Page 8/19 Page 8/19 Where is the total duration of the curriculum learning stage and . An example of the relation between difficulty and competence is shown in Fig. 4. We also present Algorithm 3. T C0 ≜C (0) ≥0 Where is the total duration of the curriculum learning stage and . An example of the relation between difficulty and competence is shown in Fig. 4. We also present Algorithm 3. T C0 ≜C (0) ≥0 Where is the total duration of the curriculum learning stage and . An example of the relation between difficulty and competence is shown in Fig. 4. We also present Algorithm 3. As shown in Fig. 5, our proposed method for Competence-Based Active Learning consists of a systematic approach to selecting training samples based on the estimated difficulty of a sample and the current competence of the model. At each training cycle, we calculate the model's competence value, which ranges from 0 to 1. If the competence value is greater than the difficulty value, then we select images to add to the labeled datasets for the next training cycle. This process is repeated until the model reaches a satisfactory level of performance. T C0 ≜C (0) ≥0 Experimental Setup and Baselines For our experiments, we randomly selected 10% of the training set as our initial labeled set, which consisted of 5,000 images. The remaining 45,000 images were used as the unlabeled set. Our implementation of the proposed method is based on the PyTorch deep learning framework33. We used a pre-trained ResNet-1834 model as our base model for all experiments. We implemented the Competence-Based Active Learning method as described in the previous sections. We used Prediction Probability Based Selection to rank the unlabeled images in terms of difficulty, and used the competence function to decide how many of the top difficult images to add to the labeled set at each iteration. We trained the model using stochastic gradient descent (SGD) with a learning rate of 0.1, momentum of 0.9, and weight decay of 5e-4. We train the models for 100 epochs and reduce the learning rate by a factor of 0.5 at 60 and 80 epochs. During the training process, we apply standard data augmentation techniques, such as random cropping from zero-padded images, random horizontal flipping, and image normalization by the channel mean and standard deviation computed over the training set. To efficiently solve the optimization problem, we use the Python scikit-image library. The reported results are averaged over 3 runs, and the evaluation metric is the accuracy on the test set. Page 9/19 We performed experiments with different sizes of the initial labeled set and different values for the competence function. We also compared our method to several baseline methods, including Random Sampling, Uncertainty Sampling, and Query by Committee. We evaluated the performance of the models based on their accuracy on the test set after each iteration. We conducted experiments to compare the performance of our proposed method with two baseline methods: Random sampling and BALD. To ensure a fair comparison, we used the official code of these methods and adapted them into our code to ensure an identical setting. We evaluated our method and the baselines on the CIFAR10 and CIFAR100 datasets. Performance on CIFAR10 Tables 1 and 3 provide clear evidence of the varying performances of different methods. In particular, the results demonstrate that similarity-based and prediction probability-based selections outperform random sampling in CIFAR10. However, the performance of similarity-based selection is notably volatile, while random sampling outperforms similarity-based selection in the initial few rounds of training. After eight rounds of training, similarity-based selection achieves a 0.03% higher accuracy than random sampling. Overall, if sufficient training rounds are completed, similarity-based selection is superior. In each cycle of training, prediction probability-based selection achieves approximately 3% higher accuracy than random sampling. Moreover, at certain training cycles, the accuracy of prediction probability-based selection exceeds that of BALD, and after eight rounds of training, its accuracy is 1.13% higher than BALD. It should be noted that competence-based active learning yields a high accuracy of 92.25% with just four rounds of training, reducing the time required for training and achieving higher accuracy than previous methods. Performance on CIFAR100 Table 2 and Table 4 show clear differences in performance between the different active learning methods on CIFAR100. Similarity-based selection performs worse than Random sampling at each round, with lower accuracy. Prediction Probability based selection achieves good performance, but during the first three rounds, its accuracy improvement over Random sampling is not significant. However, there is a significant improvement in accuracy starting from the fourth round. Active Learning iterates for 8 rounds before ending, but achieves a slightly higher final accuracy than Prediction Probability based selections. Table 2 quantitatively reflects the performance differences between the different methods, with Similarity- based selections having a final round accuracy 1.52% lower than Random sampling. Prediction Probability based selection achieves an average improvement of 3.21% over Random sampling and 1.41% over BALD. Competence-based Active Learning achieves a growing improvement of 4.91% on average over Prediction Probability based selections across the cycles. Discussions Page 10/19 Image classification plays a crucial role in various industries and sectors, but the need for large labeled datasets poses significant challenges in model development. Active Learning offers a promising solution by reducing the cost and effort of labeling data through the selection of informative samples. In this study, we propose three novel Active Learning methods, namely similarity-based selection, prediction probability-based selection, and competence-based Active Learning, to address the limitations of traditional approaches and enhance the efficiency and effectiveness of sample selection in image classification. As for the performance of Proposed Methods in comparison to existing methods, our proposed Active Learning methods demonstrate several advantages. Firstly, similarity-based selection offers a distinct improvement over random sampling, especially after several rounds of training. By leveraging the similarity between unlabeled images and the labeled dataset, this method ensures that the selected unlabeled data is representative of the already labeled data, thereby reducing selection bias and promoting better coverage of the data distribution space. This aligns with the findings of Sener et al., who emphasize the importance of selecting diverse samples to enhance the robustness and generalization ability of the model. In contrast, random sampling lacks the capability to strategically select informative samples, leading to suboptimal learning efficiency, as supported by the observations of Settles. Secondly, prediction probability-based selection consistently outperforms random sampling and even the commonly used BALD method. By incorporating the model’s current performance on the unlabeled data, this method effectively identifies samples that are both informative and within the model’s learning capacity. This is in line with the works of Yoo et al. and He et al., who utilize loss modules to learn the loss of a target model and select data based on their output loss. The effectiveness of prediction probability-based selection in reducing training time and achieving higher accuracy is further supported by the experiments conducted on CIFAR10 and CIFAR100 datasets, consistent with the findings of previous research 16, 25. Lastly, competence-based Active Learning stands out by adapting the selection strategy to the model’s learning pace and capacity. Inspired by the concept of curriculum learning, this method progresses from easier to more challenging concepts, enabling better optimization and reducing the risk of converging to local optima. This aligns with the research of Bengio et al. and Weston et al., who highlight the importance of gradually increasing the difficulty of training samples. Discussions The effectiveness of competence- based Active Learning in reducing training time and achieving higher accuracy with fewer training rounds is demonstrated in the experiments conducted on CIFAR10 and CIFAR100 datasets. However, it is important to note that our proposed methods also have their limitations. Similarity-based selection may exhibit volatility in performance, as observed in the experiments on CIFAR10, and may require several training rounds before outperforming random sampling consistently. This aligns with the findings of Sinha et al. 27, who propose an adversarial approach to diversity-based sample query but acknowledge the influence of the quality and reliability of the discriminator’s output on the effectiveness and robustness of the approach. Furthermore, competence-based Active Learning may not be the ideal Page 11/19 Page 11/19 choice when the learning capacity of the model is already well-balanced or when a more diverse exploration of the data space is required, as noted by Bengar et al. in their integration of Active Learning with self-supervised pre-training. As for the application Scenarios of Proposed Methods, similarity-based selection ensures that the selected unlabeled data aligns with the underlying data distribution of the labeled data, thus enhancing the model's robustness and generalization ability. Similarity-based selection is especially beneficial in scenarios where preserving the overall data distribution is crucial, such as image classification tasks with complex and diverse datasets. It helps to avoid selection bias that can occur with purely uncertainty- based selection methods and promotes better coverage of the data distribution space. This aligns with the findings of Sener et al., who emphasize the importance of representative-based methods in enhancing the robustness and generalization ability of the model 8. Secondly, by evaluating the model's current performance on the unlabeled data, Prediction probability- based selection method effectively identifies samples that are both informative and within the model's learning capacity. Prediction probability-based selection is well-suited for scenarios where the initial trained model exhibits relatively high accuracy. It can be particularly useful in tasks where continuous learning and adaptation are required, such as image classification in dynamic and evolving environments. This aligns with the work of Yoo et al., who employ a loss module to learn the loss of a target model and select data based on their output loss 7. The selection based on the model's prediction probabilities ensures that the new data incorporated into the training set is both informative and aligned with the model's current knowledge. Discussions Thirdly, competence-based Active Learning method adapts the selection strategy to the model's learning pace and capacity, making it particularly suitable for deep learning models that are prone to getting stuck in local optima. Competence-based Active Learning is beneficial in scenarios where careful consideration of the model's learning capacity is required. It helps to optimize the learning process by gradually introducing more challenging samples as the model's comprehension and learning ability improve. This concept aligns with the ideas of curriculum learning, where models gradually tackle more challenging tasks after mastering easier ones 29. Competence-based Active Learning reduces training time and resource requirements while achieving higher accuracy. Competing interests: None. Competing interests: None. The corresponding author is responsible for submitting a competing interests statement on behalf of all authors of the paper. Data Availability The datasets used and/or analysed during the current study are openly available at http://www.cs.toronto.edu/~kriz/learning-features-2009-TR.pdf, reference number [9]. Author contributions statement X.L. conceived the experiment(s), Y.L. and H.F. conducted the experiment(s), X.L. and Y.C. analysed the results. All authors reviewed the manuscript. Conclusions Our study introduces three novel Active Learning methods specifically designed for training neural machine learning models in the context of image classification. Among these methods, the Prediction Probability-based se-lection method showcases impressive performance across both the CIFAR10 and CIFAR100 datasets. While the Similarity-based selection method exhibits only a marginal enhancement on the CIFAR10 dataset, it still contributes to the overall improvement. Notably, the Competence-based Active Learning method surpasses all other methods in terms of image classification accuracy for both datasets, showcasing its superiority in model training. Page 12/19 Page 12/19 Looking ahead, it would be advantageous to further investigate the incorporation of supplementary image features to better quantify dissimilarities between images. This exploration can contribute to enhancing the handling of low-resource scenarios. Additionally, future experiments should encompass larger datasets and a greater number of iterations, while employing robust state-of-the-art baseline systems for comprehensive comparison. As the field of machine image classification continues to evolve, data selection methods should evolve in tandem, aligning with the specific characteristics and requirements of the models being utilized. By adapting and refining these methods, we can continue to advance the capabilities and performance of image classification models. References 1. Ding, C. et al. Hyperspectral image classification promotion using clustering inspired active learning. Remote Sensing 14, 596 (2022). 2. Beluch, W.H. et al. The Power of Ensembles for Active Learning in Image Classification. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (2018). 3. Hemmer, P., Kühl, N., & Schöffer, J. Deep evidential active learning for image classification. Deep Learning Applications 3, 171–192 (2022). 4. Käding, C. Active Learning for Regression Tasks with Expected Model Output Changes – Supplementary Material. In: BMVC (2018). 5. Wang, J. et al. Semi-supervised Active Learning for Instance Segmentation via Scoring Predictions. arXiv (2020). Page 13/19 Page 13/19 6. Golestaneh, S.A., & Kitani, K.M. Importance of Self-Consistency in Active Learning for Semantic Segmentation. arXiv (2020). 7. Yoo, D., & Kweon, I.S. Learning Loss for Active Learning. In: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019). 8. Sener, O., & Savarese, S. Active Learning for Convolutional Neural Networks: A Core-Set Approach. arXiv (2018). 9. Krizhevsky, A. Learning Multiple Layers of Features from Tiny Images (2012). 10. Saito, P., Suzuki, C., & Gomes, J.F. Robust active learning for the diagnosis of parasites. Pattern Recognition (2015). 11. Shen, Y. et al. TBAL: Two-stage batch-mode active learning for image classification. Signal Process Image Commun 106, 116731 (2022). 12. Dan, Z., & Fei, W. et al. Interactive localized content based image retrieval with multiple-instance active learning. Pattern Recognition (2010). 13. Jin, Q. et al. Deep active learning models for imbalanced image classification. Knowl-Based Syst 257 (2022). 14. Bengar, J.Z. et al. Temporal Coherence for Active Learning in Videos. arXiv (2019). 15. Bemporad, A. Active Learning for Regression by Inverse Distance Weighting. Information Sciences 626, 275–292 (2023). 16. Gal, Y., Islam, R., & Ghahramani, Z. Deep Bayesian Active Learning with Im 16. Gal, Y., Islam, R., & Ghahramani, Z. Deep Bayesian Active Learning with Image Data. arXiv (2017). 17. Sinha, A., Namkoong, H., & Duchi, J. Variational Adversarial Active Learning. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) (2019). 18. Wang, Q., Guo, K., & Cai, H. Portal-Worlds: Clustering Documents in Information Space, arXiv (2019). 18. Wang, Q., Guo, K., & Cai, H. Portal-Worlds: Clustering Documents in Information Space, arXiv (2019). 19. Sener, O., & Savarese, S. Active Learning for Convolutional Neural Networks: A Core-Set Approach. 18. Wang, Q., Guo, K., & Cai, H. Portal-Worlds: Clustering Documents in Inform 19. References Sener, O., & Savarese, S. Active Learning for Convolutional Neural Networks: A Core-Set Approach. arXiv (2017). 20. Bengar, J.Z., Raducanu, B., & van de Weijer, J. When Deep Learners Change Their Mind: Learning Dynamics for Active Learning. arXiv (2021). 21. Tekler, Z.D. et al. A hybrid active learning framework for personal thermal comfort models. Build Environ, 234, 110148 (2023). 22. Yang, Y., & Loog, M. A variance maximization criterion for active learning. Pattern Recognition 78, 358–70 (2018). 23. Li, X., & Guo, Y. Adaptive Active Learning for Image Classification. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (2013). p. 859–66. 24. Ash, J.T., Zhang, C., & Krishnamurthy, A. DEEP BATCH ACTIVE LEARNING BY DIVERSE, UNCERTAIN GRADIENT LOWER BOUNDS. arXiv (2020). 25. Li, M. et al. Learning to Rank for Active Learning: A Listwise Approach. In: 2020 25th International Conference on Pattern Recognition (ICPR). IEEE (2021). Page 14/19 Page 14/19 26. Haibo, H., & Garcia, E.A. Learning from Imbalanced Data. IEEE Trans Knowl Data Eng 21(9), 1263–84 (2009). 27. Sinha, S., Ebrahimi, S., & Darrell, T. Variational Adversarial Active Learning. arXiv (2019). 28. Bengar, J.Z. et al. Reducing Label Effort: Self-Supervised meets Active Learning. In: 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). IEEE (2021). 29. Zhang, P., Xu, X., & Xiong, D. Active Learning for Neural Machine Translation. International Conference on Asian Language Processing (2018). 30. Wang, Z. et al. Image Quality Assessment: From Error Visibility to Structural Similarity. IEEE Trans on Image Process 13(4), 600–12 (2004). 31. Krizhevsky, A., Sutskever, I., & Hinton, G.E. ImageNet classification with deep convolutional neural networks. Commun ACM 60(6), 84–90 (2017). 31. Krizhevsky, A., Sutskever, I., & Hinton, G.E. ImageNet classification with deep convolutional neural networks. Commun ACM 60(6), 84–90 (2017). 32. Platanios, E.A. et al. Competence-based Curriculum Learning for Neural Machine Translation. arXiv (2019). 32. Platanios, E.A. et al. Competence-based Curriculum Learning for Neural Machine Translation. arXiv (2019). 33. Paszke, A. et al. Automatic differentiation in PyTorch. NIPS (2017). 33. Paszke, A. et al. Automatic differentiation in PyTorch. NIPS (2017). 33. Paszke, A. et al. Automatic differentiation in PyTorch. NIPS (2017). 34. He, K. et al. Deep Residual Learning for Image Recognition. arXiv (2015). 34. He, K. et al. Deep Residual Learning for Image Recognition. arXiv (2015). Tables Table 1 Table 1 Accuracy of Active Learning Methods on CIFAR10 Method Cycle 2 Cycle 4 Cycle 6 Cycle 8 Random Sampling 82.86% 86.54% 88.29% 89.86% BALD 85.55% 89.37% 91.16% 92.43% Similarity-Based Selection 82.68% 85.83% 88.34% 89.89% Prediction Probability-Based Selection 87.28% 90.17% 92.67% 93.56% Accuracy of Active Learning Methods on CIFAR10 Page 15/19 Table 2 Accuracy of Active Learning Methods on CIFAR100 Method Cycle 2 Cycle 4 Cycle 6 Cycle 8 Random Sampling 48.71% 57.70% 63.14% 67.31% BALD 49.86% 58.95% 65.95% 69.58% Similarity-Based Selection 47.29% 56.11% 61.46% 65.79% Prediction Probability-Based Selection 51.67% 61.13% 66.54% 70.36% Table 3 Accuracy of competence-based Active Learning on CIFAR10 Cycles Cycle 2 Cycle 4 Cycle 6 Cycle 8 Number of labeled data 8181 13059 21516 25000 Competence-based Active Learning 81.02% 87.32% 92.95% 92.25% Table 4 Accuracy of competence-based Active Learning on CIFAR100 Cycles Cycle 2 Cycle 4 Cycle 6 Cycle 8 Number of labeled data 18514 21902 24801 25000 Competence-based Active Learning 64.23% 66.32% 67.56% 71.14% Table 2 Table 3 Accuracy of competence-based Active Learning on CIFAR10 Cycles Cycle 2 Cycle 4 Cycle 6 Cycle 8 Number of labeled data 8181 13059 21516 25000 Competence-based Active Learning 81.02% 87.32% 92.95% 92.25% Table 4 Accuracy of competence-based Active Learning on CIFAR100 Cycles Cycle 2 Cycle 4 Cycle 6 Cycle 8 Number of labeled data 18514 21902 24801 25000 Competence-based Active Learning 64.23% 66.32% 67.56% 71.14% Figures Page 16/19 Figure 1 an overview of our Active Learning framework Figure 2 the algorithm 1 the algorithm 1 Figure 1 an overview of our Active Learning framework an overview of our Active Learning framework Page 17/19 Page 17/19 Figure 4 Curriculum Learning Figure 3 the algorithm 2 Page 18/19 Figure 5 Page 19/19 Page 19/19
https://openalex.org/W4321793811
http://science-gate.com/IJAAS/Articles/2023/2023-10-02/1021833ijaas202302009.pdf
English
null
What determines employees’ job satisfaction and loyalty? Evidence from Vietnamese enterprises
International journal of advanced and applied sciences
2,023
cc-by
7,865
1. Introduction Additionally, businesses’ earnings are largely dependent on employee turnover (Gazioglu and Tansel, 2006). *Employee loyalty has been defined as the capacity of employees or staff members of a company to remain and contribute effectively to their positions for an extended period of time. Many studies have identified the main factors affecting employee satisfaction and loyalty in developed countries. However, not many studies have been conducted in emerging countries. Among these countries, Vietnam has an average economic growth rate (GDP) of more than 7% in the 1990s and early 2000s and significantly more than 8% from 2006- 2018, becoming one of the fastest-growing economies globally.As a result of the severe rivalry that has resulted from the fast development in the number of businesses in Vietnam, the demand for human resources has expanded significantly. In order to distinguish themselves and increase their competitiveness, firms are continually searching for and enhancing the features of their company operations. According to Santa Cruz et al. (2014), people are viewed as a key weapon and a durable competitive advantage for the success of businesses, but other factors are easily mimicked by rivals. Nevertheless, many businesses in Vietnam struggle to hire and keep laborers. One explanation is that employees can readily alter their work environment by voluntarily transferring to other workplaces in search of better roles and welfare circumstances (Phuong and Vinh, 2020). When long- term employees leave their positions, businesses suffer significant training costs (Chaturvedi, 2010). As a result of the unpredictability of the business climate and the ferocity of the business competition, employees play a significant role in practically all businesses; consequently, many firms have recently focused more on job happiness, job performance, and employee loyalty. Therefore, in this study, we examine the factors that influence employee satisfaction and loyalty in many industries in Vietnam. The rest of the paper is as follows. Section 2 examines the literature review and develops hypotheses. Section 3 describes the data and research method. Section 4 shows results and discussions. Section 5 provides conclusions. Hoang Phuong Trinh 1, Dao Hong Van 2, The Kien Nguyen 3, * 1Breau of Research Management and International Cooperation, VNU University of Medicine and Pharmacy, Hanoi, Vietnam 2International Training and Cooperation Institute, East Asia University of Technology, Hanoi, Vietnam 3Center for Socio-Economic Analysis and Databases (CSEAD), VNU University of Economics and Business, Hanoi, Vietnam A B S T R A C T Job satisfaction and loyalty of employees are key determinants for the sustainable development of the business. This study specifies factors that influence employee loyalty with employee happiness serving as a mediator. The sample survey involved 369 employees in different industries in Vietnam. The empirical results show that wages, benefits, working conditions, training, promotion opportunity, workplace relationship, and autonomy at work positively affect both employee satisfaction and loyalty. Our study complements the literature by providing firms with strategies for fostering a supportive environment that would further increase employee loyalty and contribute to the successful sustainability of organizations with satisfied employees. Article history: Received 5 July 2022 Received in revised form 7 October 2022 Accepted 22 October 2022 Keywords: Employee loyalty Satisfied employees Businesses Vietnam Article history: Received 5 July 2022 Received in revised form 7 October 2022 Accepted 22 October 2022 Keywords: Employee loyalty Satisfied employees Businesses Vietnam Article history: Received 5 July 2022 Received in revised form 7 October 2022 Accepted 22 October 2022 Keywords: Employee loyalty Satisfied employees Businesses Vietnam Article history: Received 5 July 2022 Received in revised form 7 October 2022 Accepted 22 October 2022 Article history: Received 5 July 2022 Received in revised form 7 October 2022 Accepted 22 October 2022 Keywords: Employee loyalty Satisfied employees Businesses Vietnam © 2022 The Authors. Published by IASE. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). © 2022 The Authors. Published by IASE. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). * Corresponding Author. Email Address: nguyenthekien@vnu.edu.vn (T. K. Nguyen) https://doi.org/10.21833/ijaas.2023.02.009 Corresponding author's ORCID profile: https://orcid.org/0000-0002-9404-5239 2313-626X/© 2022 The Authors. Published by IASE. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) International Journal of Advanced and Applied Sciences, 10(2) 2023, Pages: 67-76 International Journal of Advanced and Applied Sciences, 10(2) 2023, Pages: 67-76 Contents lists available at Science-Gate 2.1. Employees’ job satisfaction definition There are many different definitions of job satisfaction and possible causes of job satisfaction. 67 Trinh et al/International Journal of Advanced and Applied Sciences, 10(2) 2023, Pages: 67-76 complete employee welfare facilities will improve employee productivity and work efficiency. Some concepts are well known, such as job satisfaction is a positive response to work (Staines and Quinn, 1979); job satisfaction is a state in which employees have a clear, effective orientation towards work in the organization (Jones and Vroom, 1964) or really enjoy their work (Locke, 1976); Job satisfaction is an attitude, expressed in feelings, beliefs, and behaviors (Taylor and Weiss, 1972). According to Luddy (2005), job satisfaction is the emotional and emotional response to different aspects of an employee’s job. Some concepts are well known, such as job satisfaction is a positive response to work (Staines and Quinn, 1979); job satisfaction is a state in which employees have a clear, effective orientation towards work in the organization (Jones and Vroom, 1964) or really enjoy their work (Locke, 1976); Job satisfaction is an attitude, expressed in feelings, beliefs, and behaviors (Taylor and Weiss, 1972). According to Luddy (2005), job satisfaction is the emotional and emotional response to different aspects of an employee’s job. p y p y y Ashraf (2020) has studied the direct and indirect influence of demographic factors (gender, age, income level, education, tenure, and design), employee compensation, benefits, job satisfaction, and organizational commitment in private universities in Bangladesh. Data were collected from 515 teachers at Bangladesh University and analyzed through SEM structural equation modeling. The results show that, although demographic factors have no direct impact on organizational commitment, they have an indirect impact on organizational commitment through the mediation of compensation structure and job satisfaction and enthusiasm in the teacher’s work. Besides, compensation structure also has a significant mediating role in the relationship between demographic structure and the job satisfaction of lecturers. The study contributes to clarifying that demographics and salary packages are the most important factors for lecturers to influence organizational commitment in this study. The limitation of the study is that the sample used here is only 20 selected private universities, but there are no public universities, so the ability to generalize the results of the study is limited. Masood et al. (2014) analyzed the factors affecting employee satisfaction in Pakistani public and private organizations. 2.2.1. Wages Wages are the right that employees are entitled to in return for their sacrifices for the organization. Wages include all forms of financial compensation, services, incentives, and benefits received by employees, and it manifests as part of the employment relationship (Mikkelson et al., 2017). According to Maslow’s (1943) hierarchy of needs theory (Maslow, 1943), it was recommended that an increase in income leads to better motivation and that when employees are motivated to work harder and more conscientiously, the productivity ratio increases and a motivated employee is more willing to do and complete the tasks assigned by the company than a worker with less motivation (Murty and Hudiwinarsih, 2012). According to Yee (2018), wages and benefits have a positive influence on employees’ behavior and attitude toward work. Kampelmann et al. (2018) stated that people are motivated by salary, which has an impact on employees’ decision to join a company. H1: Income has positive effects on the employees’ job satisfaction. Alam (2020) studied the impact of wages, benefits, and welfare facilities on employee productivity and employee motivation. The results show that wages are important in attracting and motivating good employees. Therefore, enterprise managers that provide suitable wage packages and 2.1. Employees’ job satisfaction definition After surveying 200 people in Bahawalpur City and selecting 155 observations, the study applied descriptive research methods, reliability testing by Cronbach’s Alpha coefficient, and regression analysis. The author points out that income greatly affects employee satisfaction. Organizations that pay their employees fairly according to the obligations and responsibilities they perform in their work increase employee satisfaction levels. Alshitri (2013) explored the factors affecting the overall job satisfaction of 432 employees in a public research and development (R&D) center in Saudi Arabia. The study builds on 5 factors affecting employee satisfaction including salary, promotion, superiors, colleagues, and nature of work. The results show that income is the factor that has the strongest impact on employee job satisfaction. Tanjeen (2013) and Kabir and Parvin (2011) believed that income is also an important factor and has a positive relationship with employee satisfaction at work. Employees are always interested in income issues to meet the needs of themselves and their families. Only when the income is consistent with the job and fair and reasonable the employees can rest assured to devote to the development of the company. Therefore, we hypothesize that: According to Spector (1997), job satisfaction, job satisfaction in general, and job aspects in particular are simply how people feel about their jobs and aspects of their work. According to this understanding, job satisfaction is the attitude (positive or negative) towards the job. According to Kreitner and Kinicki (2007), job satisfaction mainly reflects the degree to which an individual loves their job, that is, the employee’s feelings or emotions towards the job. The level of satisfaction with components or aspects of work is the influencing attitude and recognition of employees about different aspects of work. Some authors have detailed job satisfaction for different aspects of work (Kreitner and Kinicki, 2007; Smith et al., 1997). However, this approach often confuses constitutive factors and factors affecting employee satisfaction. For example, interaction with colleagues, leadership, or compensation policy affects satisfaction rather than a constitutive factor of satisfaction. 2.2.4. Training and promotion opportunities When an employee gets promoted, it is to a position with a higher wage grade or, in certain cases, to a job with significantly larger responsibilities within the same grade. Career promotion is not only necessary to fulfill physical needs, but also to satisfy individual psychological needs and always leads to higher productivity and positive relationship building. Opportunities for career promotion are characterized by employees having greater responsibility, authority, compensation, and autonomy in employee decisions (Okolocha, 2021). Therefore, promotion is an important component of job satisfaction. According to Okolocha (2021), career advancement not only helps employees achieve their economic needs through job enrichment but also helps employees achieve career growth. Career advancement is expected to strengthen employees psychologically, create job satisfaction, and improve overall employee performance. In the study of Azar and Shafighi (2013), the authors examine the effect of work motivation on employee performance and found that promotion opportunities positively impact employee performance. 2.2.2. Employee benefits Perry et al. (2010) explained that employee benefit is a broad term that includes various 68 Trinh et al/International Journal of Advanced and Applied Sciences, 10(2) 2023, Pages: 67-76 benefits, facilities, and services provided to employees by employers to promote and motivate their employees. Employee benefits embrace the state of health, happiness, satisfaction, preservation, and development of human resources and also help to promote the motivation of employees (Tiwari, 2014). Tiwari (2014) also stated that health, safety, and benefits are motivations to promote employee performance. The variety of benefits offered by employers will have an immediate impact on workers’ health, physical and mental performance, alertness, and overall performance. Thereby contributing to higher productivity of the whole company. This result is also found in Evelyne et al. (2018), who have shown that benefits policies have an important role in improving employee performance. In contrast, an inadequate benefits program can bring about industrial disputes, crises, and situations that can slow down productivity (Hanaysha and Hussain, 2018). In addition, employee benefits programs in both developed and developing societies will also affect workforce dynamics (Hassan et al., 2020). Based on these findings, we hypothesize that: advanced working conditions so that it is easy for employees to work effectively. Tanjeen (2013) studied the job satisfaction of employees in the telecommunications industry in Bangladesh. The author presents the influencing factors as working conditions, safety at work, autonomy at work, relationship with colleagues, relationship with superiors, income, and promotion. Based on the questionnaire survey, 5-level Likert scale, and regression analysis, the author proves that working conditions are one of the factors that contribute the most to job satisfaction. The company should provide all necessary resources such as information, tools, and equipment to employees to perform their duties most effectively. García- Almeida et al. (2015), Javed et al. (2014), and Chegini et al. (2019) believed that working conditions affect the job satisfaction of employees. All employees care about their working conditions, and they will feel satisfied if the working time is suitable and the working environment is safe and comfortable. We, therefore, hypothesize that: H3: Working conditions have positive effects on the employees’ job satisfaction. H2: Employee benefits have positive effects on the employees’ job satisfaction. 2.2.3. Working conditions According to Böckerman and Ilmakunnas (2006), working conditions provided to employees by the organization such as the level of safety, comfort, health, happiness, etc. According to Nwachukwu and Chladková (2017), the working environment refers to the conditions of an organization and a favorable working environment can improve company performance. Working conditions are beneficial when an organization provides its employees with a safe and healthy environment, basic benefits, facilities, and other conditions such as good lighting, and ventilation (Rožman et al., 2017). Arnold and Feldman (1986) argued that when employees work in poor working conditions, they may feel that management does not appreciate or recognize their efforts or work completed. Greenberg and Baron (2003) indicated that workers want working conditions that provide more physical comfort and convenience. A lack of such working conditions among other things can negatively impact the mental and physical well-being of workers. Masood et al. (2014) analyzed the factors affecting employee satisfaction in Pakistani public and private organizations. After surveying 200 people in Bahawalpur City and selecting 155 observed samples, the study applied descriptive research methods, convenience sampling, reliability testing by Cronbach’s Alpha coefficient, and regression analysis. The author points out that working conditions are the most important factor in promoting employee satisfaction. Management can create work efficiency by creating comfortable and Elnaga and Imran (2013) believed that training has a close relationship with promotion because training often has the ultimate aim of promoting or improving skills, thereby improving employee performance. Chegini et al. (2019) and Ramman (2011) also had similar results and Masood et al. (2014) found that training and research did not have much influence on employee satisfaction. We, therefore, hypothesize that: 69 Trinh et al/International Journal of Advanced and Applied Sciences, 10(2) 2023, Pages: 67-76 H4: Training and promotion opportunities have positive effects on the employees’ job satisfaction. employee empowerment or employee autonomy in work has a strong impact on the company’s revenue. Bellmann and Hübler (2021) investigated the relationship between Work-from-Home and job satisfaction at different Work-from-Home agreements. Results show that working from home as an aspect of work quality can improve self-control and facilitate work and family life through a flexible organization at work. Puhakka et al. (2021) assessed autonomy at work by the freedom to choose the work undertaken and the decisions about the work. 2.2.6. Job characteristics Employees’ interests in job characteristics usually are different. Young workers usually care about promotion opportunities more than older workers do because opportunities decline with age (Mehrabian and Blum, 1996). In contrast, older workers tend to value meaningful work. Zahra Cheginy et al. (2014) conducted a survey of employees at companies in many different fields. The results show that when the work is diverse and creative, it will bring joy to the employees. Besides, challenging work will help the employees not get bored. In addition, the job creates opportunities for the employees to develop skills that will bring great satisfaction to employees. And this factor always has a positive impact on the satisfaction of employees in companies. Abdullah et al. (2009) discovered that a rise in employee satisfaction could result in a rise in employee engagement and has the potential to make both the employee and employer equally loyal to the organization. According to Mobley et al. (1979), employees with a low degree of job satisfaction are more likely to resign. This is corroborated by research by Shaw (1999) that examines the association between work satisfaction and the propensity to quit. If a person’s job satisfaction is low, there is a substantial likelihood that he or she will leave the position, according to the study. Moreover, employees in such a circumstance are prone to be absent from work. Walker (2005) also discovered that satisfied employees are more likely to remain loyal if they consider their organization to have an opportunity to learn and improve, as well as a clearly defined career path inside the firm. H6: Job characteristics have positive effects on the employees’ job satisfaction. 2.3. Job satisfaction and employees’ loyalty H5: Workplace relationships have positive effects on the employees’ job satisfaction. Employee loyalty can be described as employees’ commitment to the organization’s success and their conviction that working for this business is their best alternative. Not only do they intend to remain with the firm, but they are also unresponsive to job offers and do not aggressively seek other work. Employee loyalty is a form of organizational citizenship that demonstrates dedication to the organization via the promotion of its interests and image to the outside world. Employee loyalty is an expression of organizational commitment, which is the relative intensity of an individual’s identification with and participation with a certain company. 2.2.5. Workplace relationships Workplace relationships are relationships between individuals in an organization. This relationship is one of the important factors affecting the engagement of employees in the organization (Bui et al., 2022). Alshitri (2013) showed that workplace relationship is an important factor affecting employee satisfaction. The relationship with colleagues and superiors reflects the extent to which members of an individual’s workgroup are perceived as supportive and competent in their respective duties. Research results show that if there are friendly and supportive colleagues, the employees will be more satisfied with their work and more committed to the organization (Tanjeen, 2013). We, therefore, hypothesize that: H7: Autonomy at work has positive effects on the employees’ job satisfaction. 2.2.3. Working conditions The results of the study reveal that the level of autonomy and competence have a positive effect on employee satisfaction. From the above findings, we hypothesize that: 3. Data and methods Table 1 shows the demographic profile of the study participants. Most of the respondents are highly educated (with the majority being undergraduate or above) and are middle managers or staff. The total number of survey questionnaires distributed is 500. Among them, the total number of completed questionnaires is 369 (around 73.8%). Interviewees are randomly selected from the population for questionnaire administration. Face- to-face, drop-off, and email methods were employed to distribute the questionnaire. 2.2.7. Autonomy at work Job autonomy is defined as the degree to which work gives employees the freedom to choose what, when, and how they do their work (Parker et al., 2001). Greater work autonomy reduces constraints from other work factors and improves the individual’s job performance (Saragih, 2015). Work autonomy can be an important factor in reducing stress and improving work quality because it encourages employees to feel effective, accountable, and trusted by others in the organization (Matteson et al., 2021). From the above findings, we hypothesize that: H8: Job satisfaction has positive effects on the employees’ loyalty. We also examine the indirect effects of wages, benefits, working conditions, training and promotion opportunity, workplace relationship, job characteristics, and autonomy at work on the employees’ loyalty. For those indirect effects, we Javed et al. (2014) conducted a study on the factors affecting employee satisfaction by analyzing a sample of 200 people. The authors find that 70 Trinh et al/International Journal of Advanced and Applied Sciences, 10(2) 2023, Pages: 67-76 illustrate hypotheses H9a–H9g as in the research framework in Fig. 1. illustrate hypotheses H9a–H9g as in the research framework in Fig. 1. Wages Benefits Working conditions Training and promotion opportunities Working place relationship Job characteristics Autonomy at work Job satisfaction Employees's loyalty Control variables: Age Experience H1 H2 H3 H4 H5 H6 H7 H8 H9a H9b H9c H9d H9e H9f H9g Fig. 1: Research framework Wages H1 Benefits Job satisfaction Working conditions H8 H9a Employees's loyalty Working place relationship Control variables: Age Experience Fig. 1: Research framework AVE, and factor loadings. The CA met the recommended value higher than 0.70, the value 4. Results and discussions Before studying the causal effects of variables, we first ensure the validity and reliability of the study model using the factor loadings, Cronbach’s alpha (CA), Average Variance Extracted (AVE), and Composite Reliability (CR). The collected data was subsequently cleaned and analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM) with the aid of Smart- PLS software. Table 1: Demographic profile Criteria Number Percentage (%) Gender Male 191 51.76 Female 178 48.24 Educations High school 110 24.64 Undergraduate 175 47.42 Master 71 19.24 Ph.D. 13 3.52 Job positions Senior manager 34 9.21 Middle manager 116 31.44 Staffs 219 59.35 Working experiences <1 year 111 30.08 14 years 131 35.50 59 years 78 21.14 1014 years 38 10.30 >15 years 11 2.98 Table 2 shows the summary statistics for each construct and item along with the results of CA, CR, AVE, and factor loadings. The CA met the recommended value higher than 0.70, the value Table 1: Demographic profile Table 2 shows the summary statistics for each construct and item along with the results of CA, CR, 71 Trinh et al/International Journal of Advanced and Applied Sciences, 10(2) 2023, Pages: 67-76 ranges from 0.73 to 0.85. The CR ranging from 0.83 to 0.90 also fulfilled the criteria as it was above the minimum recommended value of 0.70 (Hair et al., 2017). The AVE value of the four variables was within the range of 0.50 and 0.66, which fulfilled the recommended value above 0.50. The factor loadings satisfy the recommended value above 0.4 (Hair et al., 2017). Table 2: Summary statistics, validity, and reliability for constructs and items Constructs/Items Min Max Mean Std. Factor loading Questions TN Wages (CA=0.758; CR=0.846; AVE=0.580) 1.25 5.00 3.344 0.666 TN1 Your current salary is commensurate with your ability. 1.00 5.00 3.463 0.821 0.719 TN2 You are perfectly fine living with your current salary. 1.00 5.00 3.241 0.865 0.845 TN3 The payment of wages to the company’s employees is fair and transparent. 1.00 5.00 3.393 0.860 0.729 TN4 The company’s allowances and commissions are reasonably. 1.00 5.00 3.276 0.952 0.747 PL Employee benefits (CA=0.753; CR=0.835; AVE=0.504) 1.60 5.00 3.251 0.643 PL1 You are satisfied with the company's bonus 1.00 5.00 3.152 0.908 0.690 PL2 Are you satisfied with the way the company handles employee benefits. 1.00 5.00 3.100 0.969 0.681 PL3 The company organizes annual travel. 4. Results and discussions 1.00 5.00 3.060 0.934 0.733 PL4 You are satisfied with the company’s annual travel. 1.00 5.00 3.691 0.835 0.624 PL5 The company creates conditions for employees to participate in cultural and artistic movements, fitness and sports clubs. 1.00 5.00 3.252 0.884 0.808 DK Working conditions (CA=0.853; CR=0.895; AVE=0.631) 1.00 5.00 3.227 0.701 DK1 You are provided with full equipment to work. 1.00 5.00 3.247 0.886 0.780 DK2 Good workplace facilities (garage, dining room, restrooms...). 1.00 5.00 3.160 0.890 0.867 DK3 You feel safe at work. 1.00 5.00 3.333 0.860 0.807 DK4 Your working environment is airy, clean and comfortable. 1.00 5.00 3.133 0.892 0.728 DK5 Your working time is flexible and reasonable. 1.00 5.00 3.263 0.893 0.785 DT Training and promotion (CA=0.786; CR=0.848; AVE=0.530) 1.80 5.00 3.482 0.594 DT1 You are introduced and oriented to the job from the very beginning. 1.00 5.00 3.431 0.795 0.805 DT2 You have many opportunities for job skills training. 2.00 5.00 3.450 0.706 0.681 DT3 You have more opportunities to promote in your career. 2.00 5.00 3.463 0.780 0.706 DT4 The company encourages you to participate in advanced training courses. 1.00 5.00 3.450 0.899 0.769 DT5 The company has policies and conditions for promotion that are widely and clearly announced to all employees. 1.00 5.00 3.618 0.871 0.668 QH Workplace relationship (CA=0.816; CR=0.868; AVE=0.524) 1.33 5.00 3.296 0.655 QH1 Your boss is friendly and always listens to employees’ opinions. 1.00 5.00 3.347 0.920 0.757 QH2 Your superiors always support employees in their work. 1.00 5.00 3.347 0.917 0.720 QH3 The bosses treat employees equally. 1.00 5.00 3.165 0.883 0.771 QH4 Your co-workers are friendly. 1.00 5.00 3.363 0.917 0.732 QH5 Employees in the departments are always happy to cooperate and help each other in their work. 1.00 5.00 3.252 0.926 0.769 QH6 You learn a lot from your superiors and colleagues. 1.00 5.00 3.301 0.878 0.576 DD Job characteristics (CA=0.802; CR=0.871; AVE=0.629) 1.25 5.00 3.367 0.662 DD1 You can make good use of your personal capacity for your work. 1.00 5.00 3.306 0.873 0.866 DD2 Your work does not create undue pressure 1.00 5.00 3.412 0.751 0.720 DD3 You can balance work and personal life. 1.00 5.00 3.415 0.807 0.751 DD4 Your work is interesting and you love your work. 4. Results and discussions 1.00 5.00 3.336 0.900 0.827 TC Autonomy at work (CA=0.730; CR=0.831; AVE=0.552) 1.75 5.00 3.617 0.613 TC1 You have the right to decide all the work in your area of responsibility. 2.00 5.00 3.767 0.766 0.719 TC2 You can take a leave as long as the job is done. 1.00 5.00 3.762 0.829 0.739 TC3 You are trusted by your superiors and empowered to make your own decisions. 1.00 5.00 3.507 0.854 0.779 TC4 You are assigned work by your superiors and can improve in your own way. 1.00 5.00 3.434 0.848 0.733 HL Satisfaction (CA=0.874; CR=0.908; AVE=0.665) 1.40 5.00 3.520 0.732 HL1 You are satisfied with the fairness in the distribution of benefits of the company. 1.00 5.00 3.515 0.804 0.818 HL2 You are satisfied with the salary and amount of work compared to others in the company. 1.00 5.00 3.531 0.897 0.829 HL3 You are satisfied with the current security of the company. 1.00 5.00 3.613 0.899 0.839 HL4 You are satisfied with the current working environment, decision making and work methods of the company. 1.00 5.00 3.599 0.910 0.812 HL5 You are satisfied with the stability of your current job. 1.00 5.00 3.344 0.980 0.777 TT Loyalty (CA=0.771; CR=0.853; AVE=0.593) 1.50 5.00 3.363 0.632 TT1 You want to work for a long time at your current company. 1.00 5.00 3.463 0.929 0.653 TT2 You are enjoying and enjoying your current job. 1.00 5.00 3.407 0.796 0.787 TT3 You see the company as your second family. 1.00 5.00 3.220 0.786 0.805 TT4 You will stay at the company even though another company offers a higher salary. 1.00 5.00 3.363 0.783 0.824 The analysis results in Table 3 also show that there is no problem of multicollinearity between the variables because the value of the variance inflation factor (VIF) ranges from 1 00 to 2 564 which is adjusted R2 of employees’ satisfaction is 0.471; the adjusted R2 of employees’ loyalty is 0.471; the adjusted R2 of employee loyalty is 0.387) (Hair et al., 2019) Besides the SRMR coefficient is 0 063 (less adjusted R2 of employees’ satisfaction is 0.471; the adjusted R2 of employees’ loyalty is 0.471; the adjusted R2 of employee loyalty is 0.387) (Hair et al., 2019). 4. Results and discussions Table 4: Results of the structural model on direct effects Direct effects β p-value t-value Conclusion TNHL 0.179*** 0.003 2.987 H1 is supported PLHL 0.138** 0.028 2.200 H2 is supported DKHL 0.131** 0.024 2.258 H3 is supported DTHL 0.240*** 0.000 4.397 H4 is supported QHHL 0.131** 0.035 2.110 H5 is supported DDHL -0.059 0.308 1.019 H6 is rejected TCHL 0.154*** 0.001 3.272 H7 is supported HLTT 0.622*** 0.000 18.754 H8 is supported Notes: *** and ** are significant at 1% and 5%, respectively Satisfaction Loyalty Wages Autonomy Benefits Training and promotion Relationships HL1 HL2 HL3 HL4 HL5 PL5 PL4 PL3 PL2 PL1 TN1 TN2 TN3 TN4 Working conditions DK5 DK4 DK3 DK2 DK1 TT1 TT2 TT3 TT4 TC4 TC3 TC2 TC1 Age Experience Job characteristics DD4 DD3 DD2 DD1 DT1 DT2 DT3 DT4 DT4 QH1 QH2 QH3 QH4 QH5 QH6 0.021 -0.079 0.653 0.787 0.805 0.824 0.622 0.818 0.829 0.839 0.812 0.777 0.719 0.719 0.845 0.729 0.747 0.138 0.690 0.681 0.733 0.624 0.808 0.131 0.708 0.867 0.807 0.728 0.785 0.240 0.805 0.681 0.706 0.769 0.668 0.131 0.757 0.720 0.771 0.732 0.769 0.576 -0.059 0.886 0.720 0.751 0.827 0.154 0.719 0.739 0.779 0.733 Fig. 4. Results and discussions Besides, the SRMR coefficient is 0.063 (less than the threshold of 0.08) (Henseler et al., 2016) and the RMS Theta value is less than 0.12 (Hair et al., 2017), proving that the theoretical research model is consistent with the actual data. The analysis results in Table 3 also show that there is no problem of multicollinearity between the variables because the value of the variance inflation factor (VIF) ranges from 1.00 to 2.564, which is lower than the maximum of 10 as suggested in Hair et al. (2017). The adjusted-R2 values of the dependent variables are all much larger than the minimum threshold of 0.10 (specifically, the 72 Trinh et al/International Journal of Advanced and Applied Sciences, 10(2) 2023, Pages: 67-76 Trinh et al/International Journal of Advanced and Applied Sciences, 10(2) 2023, Pages: 67-76 Table 3: VIF results TN PL DK DT QH DD TC HL TT C1 C2 TN 1.939 PL 2.154 DK 2.097 DT 1.698 QH 2.564 DD 2.412 TC 1.436 HL 1.000 TT C1 1.077 C2 1.077 Adjusted R2HL = 0.471 Adjusted R2TT = 0.387 SRMR = 0.063 Rms Theta = 0.115 Notes: C1: Control variable 1 (Age); C2: Control variable 2 (Working experience) Control variable 1 (Age); C2: Control variable 2 (Working experience) Table 4 and Fig. 2 illustrate the results of direct effects using the PLS-SEM model. The structural model results support most of the research hypotheses that have been proposed in the research model, except for hypothesis H6. Table 5 shows the indirect effects of wages, benefits, working conditions, training and promotion opportunity, workplace relationship, job characteristics, and autonomy at work on the employees’ loyalty with employees’ satisfaction as mediators. 4. Results and discussions 2: PLS-SEM results Table 5: Results of the structural model on direct effects Indirect effects β p value t value Conclusions Table 4: Results of the structural model on direct effects Direct effects β p-value t-value Conclusion TNHL 0.179*** 0.003 2.987 H1 is supported PLHL 0.138** 0.028 2.200 H2 is supported DKHL 0.131** 0.024 2.258 H3 is supported DTHL 0.240*** 0.000 4.397 H4 is supported QHHL 0.131** 0.035 2.110 H5 is supported DDHL -0.059 0.308 1.019 H6 is rejected TCHL 0.154*** 0.001 3.272 H7 is supported HLTT 0.622*** 0.000 18.754 H8 is supported Notes: *** and ** are significant at 1% and 5%, respectively Satisfaction Loyalty Wages Autonomy Benefits Training and promotion Relationships HL1 HL2 HL3 HL4 HL5 PL5 PL4 PL3 PL2 PL1 TN1 TN2 TN3 TN4 Working conditions DK5 DK4 DK3 DK2 DK1 TT1 TT2 TT3 TT4 TC4 TC3 TC2 TC1 Age Experience Job characteristics DD4 DD3 DD2 DD1 DT1 DT2 DT3 DT4 DT4 QH1 QH2 QH3 QH4 QH5 QH6 0.021 -0.079 0.653 0.787 0.805 0.824 0.622 0.818 0.829 0.839 0.812 0.777 0.719 0.719 0.845 0.729 0.747 0.138 0.690 0.681 0.733 0.624 0.808 0.131 0.708 0.867 0.807 0.728 0.785 0.240 0.805 0.681 0.706 0.769 0.668 0.131 0.757 0.720 0.771 0.732 0.769 0.576 -0.059 0.886 0.720 0.751 0.827 0.154 0.719 0.739 0.779 0.733 Fig. 2: PLS-SEM results Table 5: Results of the structural model on direct effects Indirect effects β p-value t-value Conclusions TNHLTT 0.039** 0.012 2.530 H9a is supported PLHLTT 0.029* 0.068 1.825 H9b is supported DKHLTT 0.031** 0.048 1.979 H9c is supported DTHLTT 0.049*** 0.008 2.650 H9d is supported QHHLTT 0.032** 0.045 2.010 H9f is supported DDHLTT -0.013 0.395 0.851 H9g is rejected TCHLTT 0.034** 0.018 2.378 H9h is supported Notes: ***, **, and* are significant at 1%, 5%, and 10%, respectively 5. Conclusions This study’s primary purpose is to determine which factors have the strongest and most significant influence on employee happiness and loyalty, as well as the extent of that influence. The empirical findings propose that for an organization to achieve a high level of employee satisfaction and loyalty, it must pay close attention to all factors that provide significant correlations and unique contributions as a good predictor of employee satisfaction and loyalty, whether directly or 4.6. Impact of job characteristics on satisfaction and loyalty Among all examined factors in our study, job characteristics are the only factor that does not have any impact on employees’ satisfaction and loyalty. It means that once employees decide to take the job, they have understood the characteristics of that job. And, since the natural characteristics of the job are not changed too much, it may have no influence on employees. 4.3. Impact of working conditions on satisfaction and loyalty Autonomy at work is another factor that has a positive impact on employees’ satisfaction and loyalty. Autonomy at work helps employees reveal their abilities, solve problems and take responsibility for their own actions. Employees will feel they are capable, they are shown, and have a high sense of responsibility as well as feel satisfied when they are trusted by their superiors (Tanjeen, 2013). Working condition is also a factor that brings positive effects on employees’ satisfaction and loyalty. Working conditions can be improved in many ways, such as ensuring facilities and equipment for the job; creating a safe, clean, and comfortable working environment; arranging flexible working hours, etc. Employees will feel more comfortable and satisfied at work if the working time at the company is appropriate, there is no overtime and the working environment is safe and comfortable (Masood et al., 2014). 4.2. Impact of benefits on satisfaction and loyalty Based on the empirical results, benefits positively affect employees’ satisfaction and loyalty. The benefit is a factor that many people care about when choosing a job and it has a significant impact on employees’ job satisfaction (Gabriel and Nwaeke, 2015). Bandara et al. (2022) found that benefits such as bonuses on holidays, health insurance, social insurance, full benefits of vacation, sightseeing tours, etc. have a positive impact on employees’ job satisfaction. Besides, employees will feel secure and increase their work productivity if they feel that they and their families are protected. Increasing benefits for employees and their families will make employees stick with the company for a long time. 4.8. Impact of job satisfaction on employees’ loyalty Job satisfaction is proved to be a main factor that improves the loyalty of employees. This result is consistent with Kim et al. (2005), in which, employees who are satisfied with their jobs exhibit stronger organizational loyalty than those who are not. When employees have high job satisfaction and are eager to remain devoted to the organization, employee loyalty will be greater. 4.4. Impact of training and promotion opportunity on satisfaction and loyalty Training and promotion opportunity is proven to be a driver of employees’ satisfaction and loyalty. To be able to improve employee satisfaction with the company, it is necessary to create peace of mind about the future for employees. In other words, building a reasonable and fair promotion route for each employee will make employees feel more secure at work and will increase employee satisfaction with the company. 4.1. Impact of wages on satisfaction and loyalty 4.1. Impact of wages on satisfaction and loyalty satisfied with the company’s salary; the salary is commensurate with their capacity as well as the company’s salary is fair and transparent. The test results show that wage is positively correlated with satisfied with the company’s salary; the salary is commensurate with their capacity as well as the company’s salary is fair and transparent. The test results show that wage is positively correlated with For the impacts of wages on employees’ satisfaction, survey participants are relatively 73 Trinh et al/International Journal of Advanced and Applied Sciences, 10(2) 2023, Pages: 67-76 employee satisfaction and employee loyalty. Income is one of the major factors affecting employee satisfaction at work. Yee (2018) pointed out that appropriate adjustment of salary, bonus, and allowance policies is extremely necessary to improve job satisfaction and meet employees’ aspirations. This contributes to creating trust and long-term attachment of highly qualified employees who continue to contribute and bring benefits to the company. employees’ contributions; leaders treating employees fairly; colleagues willing to help each other at work; employees always receiving the support of leaders at work, etc. have a positive impact on employee job satisfaction. Employees need to be considered effective partners and friends at work, so building good relationships with subordinates is a top priority factor to becoming a successful leader. However, many people in high positions often think that new subordinates must focus on relationships with superiors and ignore this responsibility. Therefore, many companies have reduced employee satisfaction to an alarming level. Conflict of interest García‐Almeida DJ, Fernández‐Monroy M, and De Saá‐Pérez P (2015). Dimensions of employee satisfaction as determinants of organizational commitment in the hotel industry. Human Factors and Ergonomics in Manufacturing and Service Industries, 25(2): 153-165. https://doi.org/10.1002/hfm.20539 The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. 4.5. Impact of workplace relationship on satisfaction and loyalty Workplace relationships have a positive influence on employees’ satisfaction and loyalty. Good working relationships such as leaders always acknowledging 74 Trinh et al/International Journal of Advanced and Applied Sciences, 10(2) 2023, Pages: 67-76 indirectly. Additionally, we believe that a higher level of rewards and benefits, a comfortable and conducive working environment, training programs provided to employees by firms, and employee job satisfaction might contribute to a higher level of employee loyalty. Consequently, the researcher concludes that the determinants of employee loyalty that companies and organizations must value and employee job satisfaction; training and promotion opportunities given to them, rewards and benefits offered to the employee, as well as working conditions, should be a top priority for any organization. Chaturvedi V (2010). A study on factors affecting job satisfaction of employees in hotel industry: A study with reference to few categorized hotels in NCR. Management Prudence, 1(2): 40- 51. Chegini Z, Asghari Jafarabadi M, and Kakemam E (2019). Occupational stress, quality of working life and turnover intention amongst nurses. Nursing in Critical Care, 24(5): 283- 289. https://doi.org/10.1111/nicc.12419 PMid:30873678 Elnaga A and Imran A (2013). The effect of training on employee performance. European Journal of Business and Management, 5(4): 137-147. Evelyne N, Kilika J, and Muathe SM (2018). Job characteristics and employee performance in private equity firms in Kenya. IOSR Journal of Business and Management, 20(1): 6-70. https://doi.org/10.11648/j.jhrm.20180602.15 Gabriel JMO and Nwaeke LI (2015). Non-financial incentives and job satisfaction among hotel workers in Port Harcourt. Journal of Scientific Research and Reports, 6(3): 228-236. https://doi.org/10.9734/JSRR/2015/15900 PMid:26510776 References Gazioglu S and Tansel A (2006). Job satisfaction in Britain: Individual and job related factors. Applied Economics, 38(10): 1163-1171. https://doi.org/10.1080/00036840500392987 Abdullah MM, Uli J, and Parasuraman B (2009). Job satisfaction among secondary school teachers. Jurnal Kemanusiaan, 13: 11-18. Greenberg J and Baron RA (2003). Behavior in organizations: Understanding and managing the human side of work. Prentice-Hall, Pennsylvania State University, Pennsylvania, USA. Alam M (2020). Organisational processes and COVID-19 pandemic: Implications for job design. Journal of Accounting and Organizational Change, 16(4): 599-606. https://doi.org/10.1108/JAOC-08-2020-0121 Hair JF, Risher JJ, Sarstedt M, and Ringle CM (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1): 2-24. https://doi.org/10.1108/EBR-11-2018-0203 Alshitri KI (2013). An investigation of factors affecting job satisfaction among R&D center employees in Saudi Arabia. Journal of Human Resources Management Research, 2013: 279369. https://doi.org/10.5171/2013.279369 ( ) https://doi.org/10.1108/EBR-11-2018-0203 Hair JF, Sarstedt M, Ringle CM, and Gudergan SP (2017). Advanced issues in partial least squares structural equation modeling. SAGE Publications, Thousand Oaks, USA. https://doi.org/10.1007/978-3-319-05542-8_15-1 Arnold HJ and Feldman DC (1986). Organizational behavior. McGraw-Hill College, New York, USA. Ashraf MA (2020). Demographic factors, compensation, job satisfaction and organizational commitment in private university: An analysis using SEM. Journal of Global Responsibility, 11(4): 407-436. https://doi.org/10.1108/JGR-01-2020-0010 Hanaysha JR and Hussain S (2018). An examination of the factors affecting employee motivation in the higher education sector. Asia-Pacific Journal of Management Research and Innovation, 14(1-2): 22-31. https://doi.org/10.1177/2319510X18810626 Hassan NM, Abu-Elenin MM, Elsallamy RM, and Kabbash IA (2020). Job stress among resident physicians in Tanta University Hospitals, Egypt. Environmental Science and Pollution Research, 27(30): 37557-37564. https://doi.org/10.1007/s11356-020-08271-9 PMid:32157529 Azar M and Shafighi AA (2013). The effect of work motivation on employees' job performance (Case study: Employees of Isfahan Islamic Revolution Housing Foundation). International Journal of Academic Research in Business and Social Sciences, 3(9): 432-445. https://doi.org/10.6007/IJARBSS/v3-i9/231 70(5): 681-690. https://doi.org/10.1111/j.1540-6210.2010.02196.x 70(5): 681-690. https://doi.org/10.1111/j.1540-6210.2010.02196.x moderating role of age and gender. IZA Journal of Labor Economics, 7: 1. https://doi.org/10.1186/s40172-017-0061-4 Phuong TTK and Vinh TT (2020). Job satisfaction, employee loyalty and job performance in the hospitality industry: A moderated model. Asian Economic and Financial Review, 10(6): 698-713. https://doi.org/10.18488/journal.aefr.2020.106.698.713 Kim WG, Leong JK, and Lee YK (2005). Effect of service orientation on job satisfaction, organizational commitment, and intention of leaving in a casual dining chain restaurant. International Journal of Hospitality Management, 24(2): 171-193. https://doi.org/10.1016/j.ijhm.2004.05.004 Puhakka IJ, Nokelainen P, and Pylväs L (2021). Learning or leaving? Individual and environmental factors related to job satisfaction and turnover intention. Vocations and Learning, 14(3): 481-510. https://doi.org/10.1007/s12186-021-09275-3 Kreitner R and Kinicki A (2007). Organizational behavior. 7th Edition, McGraw-Hill/Irwin, New York, USA. Locke J (1976). The correspondence of John Locke. Oxford University Press, Oxford, UK. Ramman M (2011). Factors affecting job satisfaction of the employees in travel and tourism companies in Amman. International Bulletin of Business Administration, 12(1): 78- 102. Luddy N (2005). Job satisfaction amongst employees at a public health institution in the Western Cape. Ph.D. Dissertation, University of the Western Cape, Bellville, South Africa. Maslow AH (1943). Preface to motivation theory. Psychosomatic Medicine, 5: 85–92. https://doi.org/10.1097/00006842-194301000-00012 Rožman M, Treven S, and Čančer V (2017). Motivation and satisfaction of employees in the workplace. Business Systems Research: International Journal of the Society for Advancing Innovation and Research in Economy, 8(2): 14-25. https://doi.org/10.1515/bsrj-2017-0013 Masood A, Aslam R, and Rizwan M (2014). Factors affecting employee satisfaction of the public and private sector organizations of Pakistan. International Journal of Human Resource Studies, 4(2): 97-121. https://doi.org/10.5296/ijhrs.v4i2.5902 Santa Cruz FG, López-Guzmán T, and Cañizares SMS (2014). Analysis of job satisfaction in the hotel industry: A study of hotels in Spain. Journal of Human Resources in Hospitality and Tourism, 13(1): 63-80. Matteson ML, Ming Y, and Silva DE (2021). The relationship between work conditions and perceptions of organizational justice among library employees. Library and Information Science Research, 43(2): 101093. https://doi.org/10.1016/j.lisr.2021.101093 , ( ) https://doi.org/10.1080/15332845.2013.807394 Saragih S (2015). The effects of job autonomy on work outcomes: Self efficacy as an intervening variable. International Research Journal of Business Studies, 4(3): 203 - 215. https://doi.org/10.21632/irjbs.4.3.203-215 Mehrabian A and Blum JS (1996). Temperament and personality as functions of age. The International Journal of Aging and Human Development, 42(4): 251-269. https://doi.org/10.2190/1QCY-VETT-JJAY-3EY1 PMid:8835610 Shaw JD (1999). Job satisfaction and turnover intentions: The moderating role of positive affect. 70(5): 681-690. https://doi.org/10.1111/j.1540-6210.2010.02196.x The Journal of Social Psychology, 139(2): 242-244. https://doi.org/10.1080/00224549909598378 p // g/ PMid:32157529 Henseler J, Hubona G, and Ray PA (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management and Data Systems. 116(1): 2-20. https://doi.org/10.1108/IMDS-09-2015-0382 Bandara SGDK, Abdeen FN, Disaratna V, and Perera BAKS (2022). Employee welfare and job satisfaction in the Sri Lankan hotel industry. International Journal of Construction Management, 22(15): 3045-3054. https://doi.org/10.1080/15623599.2020.1839705 Javed M, Khan MA, Yasir M, Aamir S, and Ahmed K (2014). Effect of role conflict, work life balance and job stress on turnover intention: Evidence from Pakistan. Journal of Basic and Applied Scientific Research, 4(3): 125-133. Bellmann L and Hübler O (2021). Working from home, job satisfaction and work–life balance–robust or heterogeneous links? International Journal of Manpower, 42(3): 424-441. https://doi.org/10.1108/IJM-10-2019-0458 Jones SC and Vroom VH (1964). Division of labor and performance under cooperative and competitive conditions. The Journal of Abnormal and Social Psychology, 68(3): 313-320. https://doi.org/10.1037/h0042378 PMid:14126846 Böckerman P and Ilmakunnas P (2006). Do job disamenities raise wages or ruin job satisfaction? International Journal of Manpower, 27(3): 290-302. https://doi.org/10.1108/01437720610672185 Kabir MN and Parvin MM (2011). Factors affecting employee job satisfaction of pharmaceutical sector. Australian Journal of Business and Management Research, 1(9): 113-123. https://doi.org/10.52283/NSWRCA.AJBMR.20110109A13 Bui S, Le-Nguyen K, “Neo” Bui Q, Jacks T, and Palvia P (2022). IT workplace preferences, job demands, and work exhaustion. Journal of Computer Information Systems, 62(6): 1199-1210. https://doi.org/10.1080/08874417.2021.2001770 Kampelmann S, Rycx F, Saks Y, and Tojerow I (2018). Does education raise productivity and wages equally? The 75 Trinh et al/International Journal of Advanced and Applied Sciences, 10(2) 2023, Pages: 67-76 70(5): 681-690. https://doi.org/10.1111/j.1540-6210.2010.02196.x p // g/ PMid:8835610 Mikkelson AC, Hesse C, and Sloan D (2017). Relational communication messages and employee outcomes in supervisor/employee relationships. Communication Reports, 30(3): 142-156. https://doi org/10 1080/08934215 2017 1300677 Smith CS, Tisak J, Hahn SE, and Schmieder RA (1997). The measurement of job control. Journal of Organizational Behavior: The International Journal of Industrial, Occupational and Organizational Psychology and Behavior, 18(3): 225-237. https://doi.org/10.1002/(SICI)1099- 1379(199705)18:3<225::AID-JOB797>3.0.CO;2-E ( ) https://doi.org/10.1080/08934215.2017.1300677 Mobley WH, Griffeth RW, Hand HH, and Meglino BM (1979). Review and conceptual analysis of the employee turnover process. Psychological Bulletin, 86(3): 493–522. https://doi.org/10.1037/0033-2909.86.3.493 Spector PE (1997). Job satisfaction: Application, assessment, causes, and consequences. Volume 3, SAGE Publications, Thousand Oaks, USA. https://doi.org/10.4135/9781452231549 Murty WA and Hudiwinarsih G (2012). Effect of compensation, motivation and organizational commitment on employee performance of accounting department (Case Study on Manufacturing Companies in Surabaya). The Indonesian Accounting Review, 2(2): 215-228. https://doi.org/10.14414/tiar.v2i02.97 Staines GL and Quinn RP (1979). American workers evaluate the quality of their jobs. Monthly Labor Review, 102(1): 3-12. Tanjeen E (2013). A study on factors affecting job satisfaction of telecommunication industries in Bangladesh. IOSR Journal of Business and Management, 8(6): 80-86. https://doi.org/10.9790/487X-0868086 Nwachukwu CE and Chladková H (2017). Human resource management practices and employee satisfaction in microfinance banks in Nigeria. Trends Economics and Management, 11(28): 23-35. https://doi.org/10.13164/trends.2017.28.23 Taylor KE and Weiss DJ (1972). Prediction of individual job termination from measured job satisfaction and biographical data. Journal of Vocational Behavior, 2(2): 123-132. https://doi.org/10.1016/0001-8791(72)90043-7 Okolocha BC (2021). Job satisfaction and employee productivity: Evidence from selected universities in South-East, Nigeria. International Journal of Business and Law Research, 9(1): 127-138. Tiwari U (2014). Job satisfaction and work motivation among the teaching staff of higher education institutions of Madhya Pradesh. International Journal of Advances in Social Sciences, 2(3): 160-164. Parker SK, Wall TD, and Cordery JL (2001). Future work design research and practice: Towards an elaborated model of work design. Journal of Occupational and Organizational Psychology, 74(4): 413-440. https://doi.org/10.1348/096317901167460 Walker A (2005). The emergence of age management in Europe. International Journal of Organisational Behaviour, 10(1): 685- 697. Perry JL, Hondeghem A, and Wise LR (2010). Revisiting the motivational bases of public service: Twenty years of research and an agenda for the future. Public Administration Review, Yee LC (2018). An analysis on the relationship between job satisfaction and work performance among academic staff in Malaysian private universities. Journal of Arts and Social Sciences, 1(2): 64-73. 76
https://openalex.org/W3112798388
https://www.researchsquare.com/article/rs-119647/latest.pdf
English
null
Determinants of clinical practice guidelines’ utilization for the management of musculoskeletal disorders: a scoping review
BMC musculoskeletal disorders
2,021
cc-by
7,987
Determinants of clinical practice guidelines’ utilization for the management of musculoskeletal disorders: A scoping review Delphine Sorondo  (  dsorondo@ifec.net ) L’Institut Franco-Européen de Chiropraxie Cyrille Delpierre  Equipe EQUITY, unité mixte de recherche INSERM-UPS 1027, Toulouse, France Pierre Côté  Faculty of Health Sciences, University of Ontario Institute of Technology, Oshawa, Ontario, Canada Louis-Rachid Salmi  Univ. Bordeaux, ISPED, Centre INSERM U1219-Bordeaux Population Health, F-33000 Bordeaux, France; Christine Cedraschi  7Division of General Medical Rehabilitation, University of Geneva, Geneva, Switzerland. Anne Taylor-Vaisey  Faculty of Health Sciences, University of Ontario Institute of Technology, Oshawa, Ontario, Canada Nadège Lemeunier  Equipe EQUITY, unité mixte de recherche INSERM-UPS 1027, Toulouse, France Research Article Keywords: clinical practice guidelines, musculoskeletal disorders, adherence Posted Date: December 10th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-119647/v1 License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Determinants of clinical practice guidelines’ utilization for the management of musculoskeletal disorders: A scoping review g disorders: A scoping review Delphine Sorondo  (  dsorondo@ifec.net ) L’Institut Franco-Européen de Chiropraxie Cyrille Delpierre  Equipe EQUITY, unité mixte de recherche INSERM-UPS 1027, Toulouse, France Pierre Côté  Faculty of Health Sciences, University of Ontario Institute of Technology, Oshawa, Ontario, Canada Louis-Rachid Salmi  Univ. Bordeaux, ISPED, Centre INSERM U1219-Bordeaux Population Health, F-33000 Bordeaux, France; Christine Cedraschi  7Division of General Medical Rehabilitation, University of Geneva, Geneva, Switzerland. Anne Taylor-Vaisey  Faculty of Health Sciences, University of Ontario Institute of Technology, Oshawa, Ontario, Canada Nadège Lemeunier  Equipe EQUITY, unité mixte de recherche INSERM-UPS 1027, Toulouse, France Delphine Sorondo  (  dsorondo@ifec.net ) L’Institut Franco-Européen de Chiropraxie EQUITY, unité mixte de recherche INSERM-UPS 1027, Toulouse, France Abstract CONTEXT: Many clinical practice guidelines have been developed for the management of musculoskeletal disorders (MSDs). However, there is a gap between evidence-based knowledge and clinical practice, and reasons are poorly understood. Understanding why healthcare providers use clinical practice guidelines is essential to improve their implementation, dissemination, and adherence. AIM: To identify determinants of clinical practice guidelines’ utilization by health care providers involved in the assessment and management of MSDs. METHOD: A scoping review of the literature was conducted. Three databases were searched from inception to December 2019. Article identification, study design, methodological quality, type of healthcare providers, MSDs, barriers and facilitators associated with guidelines’ utilization were extracted from selected articles. RESULTS: 7667 citations were retrieved, and 43 articles were selected. 51% of studies were from Europe, and most were quantitative studies (64%) following a cross-sectional design (88%). Almost 80% of articles dealt with low back pain guidelines, and the most studied healthcare providers were general practitioners or physiotherapists. Five main barriers to guideline utilization were expressed by providers: 1) disagreement between recommendations and patient expectations; 2) guidelines not specific to individual patients; 3) unfamiliarity with “non-specific” term, or with the bio psychosocial model of MSDs; 4) time consuming; and 5) heterogeneity in guideline methods. Four main facilitators to guideline utilization were cited: 1) clinician’s interest in evidence-based practice; 2) perception from clinicians that the guideline will improve triage, diagnosis and management; 3) time efficiency; and 4) standardized language. RESULTS: 7667 citations were retrieved, and 43 articles were selected. 51% of studies were from Europe, and most were quantitative studies (64%) following a cross-sectional design (88%). Almost 80% of articles dealt with low back pain guidelines, and the most studied healthcare providers were general practitioners or physiotherapists. Five main barriers to guideline utilization were expressed by providers: 1) disagreement between recommendations and patient expectations; 2) guidelines not specific to individual patients; 3) unfamiliarity with “non-specific” term, or with the bio psychosocial model of MSDs; 4) time consuming; and 5) heterogeneity in guideline methods. Four main facilitators to guideline utilization were cited: 1) clinician’s interest in evidence-based practice; 2) perception from clinicians that the guideline will improve triage, diagnosis and management; 3) time efficiency; and 4) standardized language. CONCLUSION: Identifying modifiable determinants is the first step in developing implementation strategies to improve guideline utilization in clinical practice. Research Article Keywords: clinical practice guidelines, musculoskeletal disorders, adherence Posted Date: December 10th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-119647/v1 License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License License:   This work is licensed under a Creative Commons Attribution 4.0 International License. R d F ll Li Page 1/18 Page 1/18 Contributions To The Literature lack of studies focusing on both barriers and facilitators of all practitioners involved in the management of one pathology; lack of studies focusing on both barriers and facilitators of all practitioners involved in the management of one pathology; No study has investigated the barriers and facilitators of guidelines’ utilization in all healthcare practitioners managing MSDs; Here, the emphasis is putted on the management and the assessment of a disorder not depending on a profession; Providing an overview of determinants related to guideline utilization by Providing an overview of determinants related to guideline utilization by health care providers; Odd situation: some determinants are both barriers and facilitators. Odd situation: some determinants are both barriers and facilitators. Odd situation: some determinants are both barriers and facilitators. Introduction Musculoskeletal disorders (MSDs) are the leading cause of years lived with disability in the world (1). These disorders affect people of all ages but the prevalence peaks in older individuals (2). The Centers for Disease Control and Prevention (CDC) define MSDs as grade I-II sprain/strains, tendinitis, tendinosis, tendinopathy, neuropathies and nonspecific pain of the upper extremity, lower extremity, or spine. MSDs can impact health-related quality of life, social interactions and work habilitations (2). Consequently, MSDs have economic repercussions for patients and society (2). Many clinical practice guidelines exist to inform the management of MSDs (3–8). The CDC define guidelines as guidance documents for clinical practice. They are generally developed by synthesizing the best evidence on patient-centered care (4, 5). For that reason, clinicians are encouraged to use guidelines to improve: 1) health outcomes in patients, 2) quality of clinical decisions by healthcare professionals, 3) efficiency of the healthcare system, 4) safety of care, and 5) cost effectiveness (9). Although encouraged, guideline utilization by clinicians is suboptimal (10), even if barriers and facilitators of guideline utilization and adherence have been identified in the literature (11–13). In their framework Cabana et al. identified nine barriers involved in physicians’ utilization: 1) lack of familiarity, 2) lack of awareness, 3) lack of agreement, 4) lack of self-efficacy, 5) lack of positive outcome expectancy, 6) lack of motivation, 7) external barriers, 8) patient-related barriers; and 9) context-related barriers. However, previous research focused on barriers related to one type of health care practitioners (mainly physicians) for one chronic disease such as diabetes, cancer, osteoarthritis, or low back pain (11). Consequently, pathology and healthcare practitioners could be relevant factors (barriers or facilitators) of guidelines’ utilization. There is a lack of studies focusing on both barriers and facilitators of all practitioners involved in the management of one pathology. To our knowledge, no study has investigated the barriers and facilitators of guidelines’ utilization in all healthcare practitioners managing MSDs. This knowledge could inform implementation strategies. Therefore, we conducted a scoping review of the literature to describe the determinants of clinical practice guidelines’ utilization for the assessment and management of MSDs. Method Our scoping review of the literature followed the methods proposed by Arksey and O’Malley (12–14) and included five steps: 1) identification of the research question; 2) identifying relevant studies; 3) selection of studies; 4) charting data with critical appraisal; and 5) collation, synthesis, and reporting results. Our review complies with the Reporting Items for Systematic Reviews and Meta-Analyzes extension for Scoping Reviews (PRISMA-ScR) statement (15). We added one step to the methodology proposed by Arksey and O’Malley and critically appraised the methodological quality of relevant studies. Although quality assessment of studies is not yet a standard methodological step when conducting a scoping review, it is recommended in the PRISMA Scoping Review (15). Step 1: Identifying the research question Page 3/18 Page 3/18 Our research question was: “What are the determinants of use of clinical practice guidelines by healthcare providers for the assessment and management of musculoskeletal disorders?”. Step 2 : Identifying relevant studies Our research question was: “What are the determinants of use of clinical practice guidelines by healthcare providers for the assessment and management of musculoskeletal disorders?”. Step 2 : Identifying relevant studies A search strategy was developed in collaboration with a health-science librarian and reviewed by a second health-science librarian using the Peer Review of Electronic Search Strategies (PRESS) Checklist (16, 17) (See Appendix S1 for MEDLINE search strategy). Three electronic databases (MEDLINE, Embase and AMED, through Ovid Technologies) were systematically searched from inception to December 1st, 2019 Search terms included subject headings specific to each database (e.g. MeSH in MEDLINE) and free text words relating to: “musculoskeletal disorders” AND “health practitioners” AND “guidelines”. The search strategy was first developed in MEDLINE and then adapted to the other bibliographic databases. We used the PRISMA-ScR flow chart to report number of articles at each stage (15). Step 3: Study selection Step 3: Study selection Screening Two reviewers (DS and NL) independently screened all articles in two phases. In phase 1, reviewers screened titles and abstracts and classified articles as irrelevant, relevant, and possibly relevant. In phase 2, the full text of potentially relevant articles was reviewed for eligibility. When reviewers disagreed, they discussed until reaching consensus. If consensus could not be reached, the article was independently screened by a third reviewer (CD or PC) who discussed with the initial pair of reviewers to resolve disagreement. Step 4: Charting data Eligibility criteria Eligible articles met the following inclusion criteria: 1) peer-reviewed articles published in English, French or Spanish; 2) investigation of determinants of guideline utilization focusing on barriers and facilitators (any factors that influence the utilization of evidence-based musculoskeletal guidelines); 3) source population included healthcare providers involved in the management of musculoskeletal disorders; and 4) epidemiological (controlled trials, cohort or cross-sectional studies), qualitative or mixed-method study designs. We excluded: 1) cadaveric or animal studies; and 2) books, book reviews, book chapters, conference abstracts, conference papers, editorials or letters to the editor, and literature reviews. Screening Extraction of data The lead author (DS) extracted data from all relevant studies and built an evidence table. A second reviewer (NL) checked the validity of the data extraction. Extracted data included: 1) article identification (first author name, publication date and country); 2) study design (cross-sectional, cohort, randomized controlled trial; qualitative or mixed methods); 3) type of healthcare provider (DC: Doctor of Chiropractic; DO: Doctor of Osteopathy; MD: Medical Doctor; OT: Occupational Therapist; PT: Physiotherapist); 4) type Page 4/18 Page 4/18 of musculoskeletal disorders (low back pain, whiplash, neck pain, upper limbs, lower limbs, mixed MSDs); 5) guidelines related barriers and facilitators; and 6) quality of the study (low, medium, high). Critical appraisal of studies Pairs of reviewers (DS and NL) independently critically appraised relevant studies. Internal validity consensus of articles among reviewers was reached through discussion. A third independent reviewer was involved when consensus could not be reached (CD). For qualitative studies, methodological quality was assessed using the COnsolidated criteria for REporting Qualitative research Checklist (COREQ) (18). For quantitative studies, methodological quality was assessed using the critical appraisal tools developed by Salmi (19). The tool allows the classification of various study designs according to their methodological quality in one of 4 levels of internal validity: very good, quite good, low but acceptable, and unacceptable. According to this classification, if the article complied with all internal-validity criteria in the quality checklist, the level of internal validity was assessed as “very good”. If the article missed some criteria but followed all major ones defined by the checklist, the level of internal validity was assessed as “quite good”. If one or more of those major criteria were missing, the level of internal validity was noted as “low but acceptable”. And, finally, if the article followed none of the criteria, the level of internal validity was “unacceptable”. We did not exclude articles based with unacceptable quality. Rather, we used internal validity as a criteria to stratify the synthesis and classified studies in 3 categories: 1) low internal validity (gathering low but acceptable and unacceptable levels of the checklist) a; 2) moderate internal validity (quite good internal validity); and 3) high internal validity (very good level). Extraction of data Step 5: Collation, synthesis, and reporting the results We extracted the following data and synthesized them according to the two following steps: We extracted the following data and synthesized them according to the two following steps: We extracted the following data and synthesized them according to the tw 1. Study characteristics: first author, year of publication, country, study design, healthcare provider(s), musculoskeletal disorder(s), methodological quality. 1. Study characteristics: first author, year of publication, country, study design, healthcare provider(s), musculoskeletal disorder(s), methodological quality. Reported determinants of guidelines’ use: barriers and facilitators were extracted and classified according to the theory of planned behavior (TPB)(20). This theory is the most frequent used classification to understand how determinants could influence clinicians’ practice (21). This model approaches behavior by referring to three main concepts. The first concerns the attitudes and behavioral intention of healthcare providers toward guideline utilization. The second deals with the influence of subjective and social norms on guideline use. Finally, the third concept relates to perceived power and the perceived behavioral control. Attitudes toward guideline use focusses on clinicians’ cognitive and emotional beliefs about their behavior, and individual positive or negative evaluation of the use of guidelines. This part includes the Page 5/18 intention to perform a given behavior and therefore refers to motivational factors that may influence a behavior: if you have a strong intention to perform the behavior, you will perform it. intention to perform a given behavior and therefore refers to motivational factors that may influence a behavior: if you have a strong intention to perform the behavior, you will perform it. The subjective norms refer to the perception of usual behavior by other peoples, and the perceived pressure to comply with this behavior, including an individual’s motivation and cultural or social context influence. The perceived behavioral control deals with the availability of skills needed to carry out the behavior, including expected external factors such as available resources and opportunities (e.g. skills, time, and cooperation of others). This part deals with factors linked with perceived ease or difficulty to perform a behavior. These three concepts can influence each other. The more favorable the attitude and subjective norm with respect to a given behavior and the greater the perceived control, the stronger the intention to perform the behavior. Results Our search retrieved 7667 citations (Fig. 1). After removing duplicates (n = 1333), we screened 6334 articles. During the phase 1 screening, 6192 articles were irrelevant, and 142 full text were examined. During the phase 2 screening, 99 articles were excluded for the following reasons: 1) outcomes did not focus on guideline utilization (n = 79); 2) MSDs were not the only condition studied and the results were not stratified by disorders (n = 13); 3) publication type was not eligible (commentaries) (n = 6); 4) full-text article was not available (n = 1). Therefore, our synthesis included 43 articles (Table 1) (3, 23–58). Extraction of data Thus, barriers can be obstacles to the intention to perform the expected behavior―in our case guidelines utilization―and thus act as negative predictors of intention, because they contribute to an unfavorable evaluation of the use of guidelines. Obversely, facilitators act as positive predictors of intention and thus contribute to a favorable evaluation of the use of guidelines. 2. Interpretation of findings: We used mind mapping (22) to synthesize barriers or facilitators as a visual interpretation. Barriers included in subjective norms We identified barriers related to clinicians’ judgment and perception of their own behavior by other people. Health care providers reported to be influenced by non-compliance of their instructors during their training (3, 62), non-compliance of colleagues or other professionals in their practice (3, 27, 29, 39, 45, 49, 53, 59). For example, when they had experienced the feeling of being in competition with other practitioners (45, 62). Moreover, authorities and public health policies could have an impact on clinicians perceiving guidelines as mandatory (45). Finally, long-term patients could also have an impact on guidelines’ utilization; clinicians could be afraid to lose these patients if they do not satisfy their expectations (26, 27, 60–63). Barriers linked to clinicians’ attitudes towards their behavior Clinicians who feel frustrated, anxious or a perceived loss of autonomy when using guidelines were less likely to use them (3, 40, 47, 49, 53, 57, 59–61). Furthermore, being afraid of missing information such as clinical signs or patient information, was also perceived as a barrier to use guidelines (3, 49, 53, 54). The perception of a gap between the biopsychosocial model of care recommended by guidelines and their current practice (for example biomedical approach)(33, 51, 53, 56, 60, 61), a culture of suspicion about guidelines (45), and a skeptical view of medicine or evidence-based practice (30, 62) were identified as barriers of guideline utilization. Study Characteristics Most articles (67%, 29/43) were published after 2009, 30% (n = 12) between 2001 and 2009, and 3% (n =  2) were published before 2001 (Table 1). Studies were mainly conducted in Europe (51%, n = 22), and North America (35%, n = 15), with a lower proportion elsewhere (7% in New Zealand or Australia (n = 3), 5% in Israel (n = 2) and 2% in Africa (n = 1)). Low back pain was the most studied disorder (81%, n = 35), followed by neck pain and associated disorders (12%, n = 5), lower limb disorders (n = 1), and two articles evaluated mixed MSDs. Most studies (63%, n = 27) used epidemiological designs, 30% (n = 13) used qualitative designs and 7% (n = 3) used mixed methods. Most epidemiological studies were cross- sectional (85%, n = 23), 11% (n = 3) were cohorts, and one was a randomized controlled trial. Forty percent of studies (n = 17) investigated physiotherapists; 30% (n = 13) medical doctors; 9% (n = 4) doctors of Page 6/18 Page 6/18 Page 6/18 chiropractic; 2% (n = 1) occupational therapists; 2% (n = 1) doctors of osteopathy; and 16% (n = 7) investigated multiple professions. chiropractic; 2% (n = 1) occupational therapists; 2% (n = 1) doctors of osteopathy; and 16% (n = 7) investigated multiple professions. Regarding methodological quality, 42% (n = 18), 30% (n = 12) and 30%(n = 13) were of low, medium and high-quality level, respectively. Finally, we found no difference between determinants related to internal validity, country, type of healthcare providers or MSDs. Finally, we found no difference between determinants related to internal validity, country, type of healthcare providers or MSDs. Barriers to guidelines’ utilization Barriers to guidelines’ utilization are reported in Fig. 2 according to their frequency of citation in the literature and detailed below according to the planned behavior theory. Facilitators included in subjective norms These determinants involved how clinicians practice and interact with others (64). Relationships and social interactions with colleagues, superiors, and public health authorities can influence guideline utilization (29, 31, 39, 48, 61, 65). Moreover, clinicians who use recommendations prefer to perceive that the guidelines are commonly used in practice by others in their field (42, 46). Having good experiences with recommended multidisciplinary approaches (64) encourages clinicians to maintain this behavior in practice. In this way, they use guidelines as a common and shared language between different professions (42, 47, 48, 62). Clinicians who want to legitimize their own practice in front of others (62) use guidelines in practice. Finally, it is reported that clinicians need to trust those who developed guidelines (3, 47) and must have financial resources supported by authorities to work in accordance with guidelines (47, 48, 61). Facilitators linked to clinicians’ attitudes towards their behavior A practitioner’s motivation to provide good clinical care, positive behaviors toward using guidelines and professionalism were frequently associated with compliance (3, 26, 53). Providers interested in scientific literature used guidelines more frequently (3, 25, 30, 42, 45, 49, 59). Clinicians who are interested in evidence-based practice are more likely to use recommendations from guidelines (23, 25, 36). A practitioner’s motivation to provide good clinical care, positive behaviors toward using guidelines and professionalism were frequently associated with compliance (3, 26, 53). Providers interested in scientific literature used guidelines more frequently (3, 25, 30, 42, 45, 49, 59). Clinicians who are interested in evidence-based practice are more likely to use recommendations from guidelines (23, 25, 36). Furthermore, clinicians practicing in a hospital or a clinic with a large volume of MSDs patients reported using guidelines more often (24, 34, 44). Furthermore, clinicians practicing in a hospital or a clinic with a large volume of MSDs patients reported using guidelines more often (24, 34, 44). Barriers involved in clinicians perceived behavioral control Barriers were related to clinicians’ perception of how they control their behavior. Guidelines may be perceived as non-practical for current practice (28, 39, 44, 49, 52–54, 60, 63–65) or reported to be too restrictive, theoretical, long, cumbersome (3, 30, 31, 46, 47, 57, 59–61, 65) or outdated (59, 62). The number of available guidelines may be viewed as too large for practitioners (45, 47), with a lack of consistency in their methodology (3, 39, 42, 47, 53, 59, 65). Consequently, clinicians may be confused when selecting a guideline. Furthermore, terminology used is sometimes perceived to be unclear, Page 7/18 Page 7/18 Page 7/18 particularly regarding the term “non-specific” used to describe some MSDs such as neck or low back pain (23, 30, 39, 40, 46, 47, 49, 64). me clinicians reported that they are not sufficiently trained to use guideline In addition, some clinicians reported that they are not sufficiently trained to use guideline recommendations. For example, clinicians who are not trained to use yellow flags, or the biopsychosocial approach would be challenged with using them to manage patients (27, 37–39, 41, 42, 46, 55, 59–61). Barriers to compliance also include the ability to provide recommended multimodal care, and accessibility and reimbursement for healthcare services (26–28, 30, 39, 42, 49, 59, 65). For these reasons, some practitioners perceived guidelines as not adapted to the needs of their patients, limiting the interest in using guidelines to inform care for individual cases. , p y y g recommendations. For example, clinicians who are not trained to use yellow flags, or the biopsychosocial approach would be challenged with using them to manage patients (27, 37–39, 41, 42, 46, 55, 59–61). Barriers to compliance also include the ability to provide recommended multimodal care, and accessibility and reimbursement for healthcare services (26–28, 30, 39, 42, 49, 59, 65). For these reasons, some practitioners perceived guidelines as not adapted to the needs of their patients, limiting the interest in using guidelines to inform care for individual cases. Facilitators to guidelines’ utilization All facilitators to guideline utilization are reported in Fig. 2. All facilitators to guideline utilization are reported in Fig. 2. Facilitators linked to clinicians’ attitudes towards their behavior Facilitators involved in clinicians’ perceived behavioral control Determinants may be linked to clinicians’ perception of control about their ability to use guidelines. Recommendations must be perceived as accessible, concise, clear, adapted to daily practice, useful and relevant for use by clinicians (42, 46, 48, 49, 59, 61). nked to clinicians’ perception of control about their ability to use guidelines. Determinants may be linked to clinicians’ perception of control about their ability to use guidelines. Recommendations must be perceived as accessible concise clear adapted to daily practice useful and Determinants may be linked to clinicians’ perception of control about their ability to use guidelines. Recommendations must be perceived as accessible, concise, clear, adapted to daily practice, useful and relevant for use by clinicians (42, 46, 48, 49, 59, 61). Page 8/18 Page 8/18 Providers who aim to improve their practice tend to use more guidelines. Practice improvement occurs when providers view guidelines s tools to help form clinical judgments, inform patient communication, improve patients’ triage, and be more efficient (26, 28–30, 39, 48, 61). Some clinicians expressed the need to be trained by having access to education sessions about guidelines utilization (52, 65). Providers who aim to improve their practice tend to use more guidelines. Practice improvement occurs when providers view guidelines s tools to help form clinical judgments, inform patient communication, improve patients’ triage, and be more efficient (26, 28–30, 39, 48, 61). Some clinicians expressed the need to be trained by having access to education sessions about guidelines utilization (52, 65). Summary of Evidence Our scoping review provides an overview of determinants related to guideline utilization by health care providers. Most studies focusing on guideline utilization used a cross-sectional design. Barriers to guideline utilization were more common than facilitators. We did not find any difference between determinants influencing utilization of guidelines related to healthcare provider or MSDs. This suggests that barriers and facilitators highlighted in this scoping review may apply to various healthcare providers who manage MSDs. The majority of determinants identified in this review were reported from high or moderate internal validity studies. We note that only a few determinants associated with patient characteristics have been identified, underscoring the fact that the literature on guideline use is largely focused on clinician characteristics. Our results suggest that obstacles and facilitators tend to hold opposite views. For example, guideline users perceive them as adaptable to daily practice because they are relevant, useful, accessible, concise and clear. Altenatively, non-users perceive guidelines as not improving healthcare quality because they are restrictive, cumbersome, theoretical, too plentiful, and time consuming. According to clinicians’ behavior, two concepts that influence guideline utilization depend on a clinician’s perception of the factor (Fig. 2). The first concept is a positive practice orientation such as feeling comfortable with the management of yellow flags and biopsychosocial factors which are supported by guidelines. On the other hand, clinicians with a biomedical practice seem to have difficulties considering the biopsychosocial model recommended by guidelines. Second, the habit of working with this kind of tool is important. We can differentiate between clinicians who are familiar with recommendations or classifications and those who are not, and consequently feel frustrated or powerless using these tools. We found that perception of clinical behavior by colleagues, other professionals or authorities could have both negative and positive influence on clinicians’ guideline utilization. Moreover, past experiences can enhance or limit the use of guidelines. Having a positive experience with others when guidelines recommend multidisciplinary approaches in the management of a patient can encourage practitioners to repeat the experience and apply guidelines. On the contrary, when clinicians feel at a disadvantage compared to other professions, or experience disagreement without explanations about multidisciplinary management of a patient, they may not use guidelines. Finally, authorities impact the use of guidelines through the diffusion of tools and by adding value to clinical management following guideline recommendations. Strengths and limitations A strength of our scoping review is its comprehensive scope. We focused our research on all MSDs to emphasize the importance of patient-centered care for these disorders in a multidisciplinary approach. This clinical situation involves all healthcare providers and data were described from a clinical point of view. We used the Theory of Planned Behavior. This is the most frequently classification used in implementation science (13)., This theory helps identify healthcare providers’ determinants of intension to use, their use of guidelines, and their beliefs towards guidelines. This is a major step in developing targeted interventions for clinicians’ adherence. Future interventions must focus on maintaining, sustaining and encouraging guideline use, and thus encourage positive behaviors that improve diagnosis and patient management. Finally, we performed a critical appraisal, t a limitation mentioned in previous scoping reviews on this topic (15). Our critical appraisal revealed that two thirds of determinants were extracted from high or medium quality studies. One third of determinants, therefore, needs to be carefully considered. Our scoping review has some limitations. Because we searched only three databases (adhering to standard scoping review methodology), we may have missed some studies. Also, we did not search the grey literature, and we restricted languages to English, Spanish or French. Comparison with previous reviews of the literature Comparison with previous reviews of the literature Our results concerning barriers to guideline utilization agree with previous studies (11, 66) 62). Cabana et al. also reported that barriers to guideline use include: lack of awareness, lack of familiarity, lack of agreement with specific guidelines or guidelines in general, lack of self-efficacy, lack of outcome expectancy, lack of motivation, external barriers linked with patient factors, guideline factors or environmental factors (11). Furthermore, in their scoping review, Fischer et al. identified the following barriers among physicians: lack of awareness, a lack of familiarity, lack of agreement, self-efficacy, skills, outcome expectancy and motivation (66). However, our scoping review adds to the literature by identifying a complete list of barriers and facilitators of guideline utilization in a broad range of health care providers who manage patients with MSDs. Importantly, our review found no association between determinants and professions. Our determinants are classified using a standardized framework and visually displayed in a mind-map (Fig. 2). Summary of Evidence Clinicians use guidelines if they feel supported to work in accordance with Page 9/18 Page 9/18 recommendations. If they feel they are not supported and perceive guidelines as imposed, their attitude toward the use of guidelines is negative. CONCLUSION and PERSPECTIVES Implementation strategies need to be oriented toward determinants expressed by clinicians, the major users of guidelines. Implementation tools must be developed that are tailored to clinicians’ expectations and that are informed by facilitators of utilization and that avoid barriers to orient work on implementation strategies. Our study identifies determinants for public health policy makers and professional associations that need to be prioritized when implementing guidelines. Whether the use of Page 10/18 guidelines varies according to the social characteristics of patients could also be an interesting question for further research. guidelines varies according to the social characteristics of patients could also be an interesting question for further research. Authors’ contributions DS, CD, PC, and NL developed the research questions and scope of the study. DS and NL conducted phase 1 and 2 screening and data charting. DS drafted the manuscript, prepare tables and figure with NL’s contribution. ATV developed the literature search strategies in collaboration with the other authors. DS, NL, CD, PC, LRS, and CC contributed to the organization, analysis, and interpretation of the results. All authors read and approved the final manuscript. Declarations Corresponding Author: Delphine Sorondo, Institut Franco-Européen de Chiropraxie, 72 chemin de la Flambère-31300 Toulouse, France and UMR; Email: dsorondo@ifec.net; Telephone: +33 (0)5.61.16.23.10. Funding This study was funded by the Institut Franco-Européen de Chiropraxie in a PhD project. This association was not involved in the collection of data, data analysis, interpretation of data, or drafting of the manuscript. Acknowledgement The authors acknowledge and thank Mr Hainan Yu and Dr Margareta Nordin, for their help and suggestions. Ethics approval and consent to participate Not applicable Availability of data and materials Not applicable Consent for publication Not applicable References 1. Green BN, Johnson CD, Haldeman S, Griffith E, Clay MB, Kane EJ, et al. A scoping review of biopsychosocial risk factors and co-morbidities for common spinal disorders. PLoS One. 2018;13(6):e0197987. 1. Green BN, Johnson CD, Haldeman S, Griffith E, Clay MB, Kane EJ, et al. A scoping review of biopsychosocial risk factors and co-morbidities for common spinal disorders. PLoS One. 2018;13(6):e0197987. 2. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;390(10100):1211-59. 3. Bussieres AE, Patey AM, Francis JJ, Sales AE, Grimshaw JM, Brouwers M, et al. Identifying factors likely to influence compliance with diagnostic imaging guideline recommendations for spine disorders among chiropractors in North America: a focus group study using the Theoretical Domains Framework. Implement Sci. 2012;7:82. 4. Wong JJ, Côté P, Sutton DA, Randhawa K, Yu H, Varatharajan S, et al. Clinical practice guidelines for the noninvasive management of low back pain: A systematic review by the Ontario Protocol for Traffic Injury Management (OPTIMa) Collaboration. Eur J Pain. 2017;21(2):201-16. 5. Côté P, Wong JJ, Sutton D, Shearer HM, Mior S, Randhawa K, et al. Management of neck pain and associated disorders: A clinical practice guideline from the Ontario Protocol for Traffic Injury Management (OPTIMa) Collaboration. Eur Spine J. 2016;25(7):2000-22. 6. Chou R, Qaseem A, Snow V, Casey D, Cross JT, Jr., Shekelle P, et al. Diagnosis and treatment of low back pain: a joint clinical practice guideline from the American College of Physicians and the American Pain Society. Ann Intern Med. 2007;147(7):478-91. 7. Nielens H, Zundert J, Mairiaux P, Gailly J, Van den Hecke N, Mazina D, et al. Chronic low back pain. Good clinical practice (GCP). 2006. 8. de Campos TF. Low back pain and sciatica in over 16s: assessment and management NICE Guideline [NG59]. J Physiother. 2017;63(2):120. 9. Woolf SH, Grol R, Hutchinson A, Eccles M, Grimshaw J. Clinical guidelines: potential benefits, limitations, and harms of clinical guidelines. BMJ. 1999;318(7182):527-30. 10. Samaan Z, Mbuagbaw L, Kosa D, Borg Debono V, Dillenburg R, Zhang S, et al. A systematic scoping review of adherence to reporting guidelines in health care literature. J Multidiscip Healthc. 2013;6:169-88. 11. Cabana MD, Rand CS, Powe NR, Wu AW, Wilson MH, Abboud PA, et al. Why don't physicians follow clinical practice guidelines? A framework for improvement. JAMA. 1999;282(15):1458-65. 12. Conflict of Interest The authors declare that they have no conflict of interest. Page 11/18 Page 11/18 References Arksey H, O'Malley L. Scoping studies: towards a methodological framework. International Journal of Social Research Methodology. 2005;8(1):19-32. 13. Levac D, Colquhoun H, O'Brien KK. Scoping studies: advancing the methodology. Implement Sci. 2010;5:69. 14. O'Brien KK, Colquhoun H, Levac D, Baxter L, Tricco AC, Straus S, et al. Advancing scoping study methodology: a web-based survey and consultation of perceptions on terminology, definition and Page 12/18 methodological steps. BMC Health Serv Res. 2016;16:305. methodological steps. BMC Health Serv Res. 2016;16:305. methodological steps. BMC Health Serv Res. 2016;16:305. 15. Tricco AC, Lillie E, Zarin W, O'Brien KK, Colquhoun H, Levac D, et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med. 2018;169(7):467-73. 16. McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS Peer Review of Electronic Search Strategies: 2015 Guideline Statement. J Clin Epidemiol. 2016;75:40-6. 16. McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS Peer Review of Electronic Search Strategies: 2015 Guideline Statement. J Clin Epidemiol. 2016;75:40-6. 17. Sampson M, McGowan J, Cogo E, Grimshaw J, Moher D, Lefebvre C. An evidence-based practice guideline for the peer review of electronic search strategies. J Clin Epidemiol. 2009;62(9):944-52. 18. Tong A, Sainsbury P, Craig J. Consolidated Criteria for Reporting Qualitative Research (COREQ): A 32- Item Checklist for Interviews and Focus Groups. International journal for quality in health care : journal of the International Society for Quality in Health Care / ISQua. 2008;19:349-57. 19. Salmi RL. Lecture critique et communication médicale scientifique. Comment lire, présenter, rédiger et publier une étude clinique ou épidémiologique. 3e édition ed. Issy-les-Moulineaux, France: Elsevier Masson SAS; 2012. 20. Ajzen I. The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes. 1991;50:179-211. 20. Ajzen I. The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes. 1991;50:179-211. 21. Liang L, Abi Safi J, Gagliardi AR. Number and type of guideline implementation tools varies by guideline, clinical condition, country of origin, and type of developer organization: content analysis of guidelines. Implementation science : IS. 2017;12(1):136. 21. Liang L, Abi Safi J, Gagliardi AR. Number and type of guideline implementation tools varies by guideline, clinical condition, country of origin, and type of developer organization: content analysis of guidelines. Implementation science : IS. 2017;12(1):136. 22. XMind 2020 [Available from: https://www.xmind.net/fr/. 23. Epstein-Sher S, Jaffe DH, Lahad A. Are They Complying? References Physicians' Knowledge, Attitudes, and Readiness to Change Regarding Low Back Pain Treatment Guideline Adherence. Spine. 2017;42(4):247-52. 23. Epstein-Sher S, Jaffe DH, Lahad A. Are They Complying? Physicians' Knowledge, Attitudes, and Readiness to Change Regarding Low Back Pain Treatment Guideline Adherence. Spine. 2017;42(4):247-52. 24. Ladeira CE, Samuel Cheng M, Hill CJ. Physical therapists' treatment choices for non-specific low back pain in Florida: an electronic survey. J Man Manip Ther. 2015;23(2):109-18. 24. Ladeira CE, Samuel Cheng M, Hill CJ. Physical therapists' treatment choices for non-specific low back pain in Florida: an electronic survey. J Man Manip Ther. 2015;23(2):109-18. 25. Corkery MB, Edgar KL, Smith CE. A survey of physical therapists' clinical practice patterns and adherence to clinical guidelines in the management of patients with whiplash associated disorders (WAD). J Man Manip Ther. 2014;22(2):75-89. 26. Chenot JF, Scherer M, Becker A, Donner-Banzhoff N, Baum E, Leonhardt C, et al. Acceptance and perceived barriers of implementing a guideline for managing low back in general practice. Implement Sci. 2008;3:7. 27. Baker R, Lecouturier J, Bond S. Explaining variation in GP referral rates for x-rays for back pain. Implement Sci. 2006;1:15. 28. Brijnath B, Bunzli S, Xia T, Singh N, Schattner P, Collie A, et al. General practitioners knowledge and management of whiplash associated disorders and post-traumatic stress disorder: implications for patient care. BMC Fam Pract. 2016;17:82. 29. Clement CM, Stiell IG, Lowe MA, Brehaut JC, Calder LA, Vaillancourt C, et al. Facilitators and barriers to application of the Canadian C-spine rule by emergency department triage nurses. Int Emerg Nurs. Page 13/18 Page 13/18 2016;27:24-30. 30. Bishop FL, Dima AL, Ngui J, Little P, Moss-Morris R, Foster NE, et al. "Lovely Pie in the Sky Plans": A Qualitative Study of Clinicians' Perspectives on Guidelines for Managing Low Back Pain in Primary Care in England. Spine. 2015;40(23):1842-50. 31. Maas MJ, van Dulmen SA, Sagasser MH, Heerkens YF, van der Vleuten CP, Nijhuis-van der Sanden MW, et al. Critical features of peer assessment of clinical performance to enhance adherence to a low back pain guideline for physical therapists: a mixed methods design. BMC Med Educ. 2015;15:203. 32. Bernhardsson S, Oberg B, Johansson K, Nilsen P, Larsson ME. Clinical practice in line with evidence? A survey among primary care physiotherapists in western Sweden. J Eval Clin Pract. 2015;21(6):1169-77. 33. Gremeaux V, Coudeyre E, Viviez T, Bousquet PJ, Dupeyron A. References Do Teaching General Practitioners' Fear- Avoidance Beliefs Influence Their Management of Patients with Low Back Pain? Pain Pract. 2015;15(8):730-7. 34. Learman KE, Ellis AR, Goode AP, Showalter C, Cook CE. Physical therapists' clinical knowledge of multidisciplinary low back pain treatment guidelines. Phys Ther. 2014;94(7):934-46. 34. Learman KE, Ellis AR, Goode AP, Showalter C, Cook CE. Physical therapists' clinical knowledge of multidisciplinary low back pain treatment guidelines. Phys Ther. 2014;94(7):934-46. 35. Matzon JL, Lutsky KF, Maloney M, Beredjiklian PK. Adherence to the AAOS upper-extremity clinical practice guidelines. Orthopedics. 2013;36(11):e1407-11. 35. Matzon JL, Lutsky KF, Maloney M, Beredjiklian PK. Adherence to the AAOS upper-extremity clinical practice guidelines. Orthopedics. 2013;36(11):e1407-11. 36. Rebbeck T, Macedo LG, Maher CG. Compliance with clinical guidelines for whiplash improved with a targeted implementation strategy: a prospective cohort study. BMC Health Serv Res. 2013;13:213. 36. Rebbeck T, Macedo LG, Maher CG. Compliance with clinical guidelines for whiplash improved with a targeted implementation strategy: a prospective cohort study. BMC Health Serv Res. 2013;13:213. 37. Hendrick P, Mani R, Bishop A, Milosavljevic S, Schneiders AG. Therapist knowledge, adherence and use of low back pain guidelines to inform clinical decisions--a national survey of manipulative and sports physiotherapists in New Zealand. Man Ther. 2013;18(2):136-42. 37. Hendrick P, Mani R, Bishop A, Milosavljevic S, Schneiders AG. Therapist knowledge, adherence and use of low back pain guidelines to inform clinical decisions--a national survey of manipulative and sports physiotherapists in New Zealand. Man Ther. 2013;18(2):136-42. 38. Simmonds MJ, Derghazarian T, Vlaeyen JW. Physiotherapists' knowledge, attitudes, and intolerance of uncertainty influence decision making in low back pain. Clin J Pain. 2012;28(6):467-74. 38. Simmonds MJ, Derghazarian T, Vlaeyen JW. Physiotherapists' knowledge, attitudes, and intolerance of uncertainty influence decision making in low back pain. Clin J Pain. 2012;28(6):467-74. 39. Poitras S, Durand MJ, Côté AM, Tousignant M. Guidelines on low back pain disability: interprofessional comparison of use between general practitioners, occupational therapists, and physiotherapists. Spine. 2012;37(14):1252-9. 39. Poitras S, Durand MJ, Côté AM, Tousignant M. Guidelines on low back pain disability: interprofessional comparison of use between general practitioners, occupational therapists, and physiotherapists. Spine. 2012;37(14):1252-9. interprofessional comparison of use between general practitioners, occupational therapists, and physiotherapists. Spine. 2012;37(14):1252-9. 40. Jeffrey JE, Foster NE. A qualitative investigation of physical therapists' experiences and feelings of managing patients with nonspecific low back pain. Phys Ther. 2012;92(2):266-78. 40. Jeffrey JE, Foster NE. References A qualitative investigation of physical therapists' experiences and feelings of managing patients with nonspecific low back pain. Phys Ther. 2012;92(2):266-78. 41. Derghazarian T, Simmonds MJ. Management of low back pain by physical therapists in quebec: how are we doing? Physiother Can. 2011;63(4):464-73. 41. Derghazarian T, Simmonds MJ. Management of low back pain by physical therapists in quebec: how are we doing? Physiother Can. 2011;63(4):464-73. 42. Poitras S, Durand MJ, Côté AM, Tousignant M. Use of low-back pain guidelines by occupational therapists: a qualitative study of barriers and facilitators. Work. 2011;39(4):465-75. 42. Poitras S, Durand MJ, Côté AM, Tousignant M. Use of low-back pain guidelines by occupational therapists: a qualitative study of barriers and facilitators. Work. 2011;39(4):465-75. 43. Fullen BM, Baxter GD, Doody C, Daly LE, Hurley DA. General practitioners' attitudes and beliefs regarding the management of chronic low back pain in Ireland: a cross-sectional national survey. Clin J Pain. 2011;27(6):542-9. 43. Fullen BM, Baxter GD, Doody C, Daly LE, Hurley DA. General practitioners' attitudes and beliefs regarding the management of chronic low back pain in Ireland: a cross-sectional national survey. Clin J Pain. 2011;27(6):542-9. Page 14/18 Page 14/18 44. Kooijman MK, Swinkels IC, Veenhof C, Spreeuwenberg P, Leemrijse CJ. Physiotherapists' compliance with ankle injury guidelines is different for patients with acute injuries and patients with functional instability: an observational study. J Physiother. 2011;57(1):41-6. 45. Corbett M, Foster N, Ong BN. GP attitudes and self-reported behaviour in primary care consultations for low back pain. Fam Pract. 2009;26(5):359-64. 46. Côté AM, Durand MJ, Tousignant M, Poitras S. Physiotherapists and use of low back pain guidelines: a qualitative study of the barriers and facilitators. J Occup Rehabil. 2009;19(1):94-105. 47. Harting J, Rutten GM, Rutten ST, Kremers SP. A qualitative application of the diffusion of innovations theory to examine determinants of guideline adherence among physical therapists. Phys Ther. 2009;89(3):221-32. 48. Rutten G, Kremers S, Rutten S, Harting J. A theory-based cross-sectional survey demonstrated the important role of awareness in guideline implementation. J Clin Epidemiol. 2009;62(2):167-76 e1. 49. Dahan R, Borkan J, Brown JB, Reis S, Hermoni D, Harris S. The challenge of using the low back pain guidelines: a qualitative research. J Eval Clin Pract. 2007;13(4):616-20. 50. Pincus T, Foster NE, Vogel S, Santos R, Breen A, Underwood M. Attitudes to back pain amongst musculoskeletal practitioners: a comparison of professional groups and practice settings using the ABS-mp. Man Ther. 2007;12(2):167-75. 51. Table 1 Due to technical limitations Table 1 is available as a download in the Supplementary Files. Assoc. 1997;41(3):145-54. Barriers and Strategies in Guideline Implementation-A Scoping Review. Healthcare (Basel). 2016;4(3). 66. Fischer F, Lange K, Klose K, Greiner W, Kraemer A. Barriers and Strategies in Guideline Implementation-A Scoping Review. Healthcare (Basel). 2016;4(3). Appendix S1 Appendix S1 was not provided with this version of the manuscript. Assoc. 1997;41(3):145-54. Assoc. 1997;41(3):145-54. 59. Parr S, May S. Do musculoskeletal physiotherapists believe the NICE guidelines for the management of non-specific LBP are practical and relevant to their practice? A cross sectional survey. Physiotherapy. 2014;100(3):235-41. 60. Cowell F, Gillespie S, Cheung G, Brown D. Complex regional pain syndrome in distal radius fractures: How to implement changes to reduce incidence and facilitate early management. J Hand Ther. 2018;31(2):201-5. 61. Stilwell P, Hayden J, Rosiers P, Harman K, French S, Curran J, et al. A qualitative study of doctors of chiropractic in a Nova Scotian practice-based research network: Barriers and facilitators to the screening and management of psychosocial factors for patients with low back pain. Journal of Manipulative and Physiological Therapeutics. 2018;41(1):25-33. 62. Figg-Latham J, Rajendran D. Quiet dissent: The attitudes, beliefs and behaviours of UK osteopaths who reject low back pain guidance - A qualitative study. Musculoskelet Sci Pract. 2017;27:97-105. 62. Figg-Latham J, Rajendran D. Quiet dissent: The attitudes, beliefs and behaviours of UK osteopaths who reject low back pain guidance - A qualitative study. Musculoskelet Sci Pract. 2017;27:97-105. 63. Selby K, Cornuz J, Cohidon C, Gaspoz JM, Senn N. How do Swiss general practitioners agree with and report adhering to a top-five list of unnecessary tests and treatments? Results of a cross- sectional survey. Eur J Gen Pract. 2018;24(1):32-8. 63. Selby K, Cornuz J, Cohidon C, Gaspoz JM, Senn N. How do Swiss general practitioners agree with and report adhering to a top-five list of unnecessary tests and treatments? Results of a cross- sectional survey. Eur J Gen Pract. 2018;24(1):32-8. 64. Suman A, Schaafsma FG, Buchbinder R, van Tulder MW, Anema JR. Implementation of a Multidisciplinary Guideline for Low Back Pain: Process-Evaluation Among Health Care Professionals. Journal of Occupational Rehabilitation. 2017;27(3):422-33. 64. Suman A, Schaafsma FG, Buchbinder R, van Tulder MW, Anema JR. Implementation of a Multidisciplinary Guideline for Low Back Pain: Process-Evaluation Among Health Care Professionals. Journal of Occupational Rehabilitation. 2017;27(3):422-33. 65. Akindele M, Rabiu M, Useh E. Assessment of the awareness, adherence, and barriers to low back pain clinical practice guidelines by practicing physiotherapists in a low-resourced country. Physiother Res Int. 2019:e1811. 65. Akindele M, Rabiu M, Useh E. Assessment of the awareness, adherence, and barriers to low back pain clinical practice guidelines by practicing physiotherapists in a low-resourced country. Physiother Res Int. 2019:e1811. 66. Fischer F, Lange K, Klose K, Greiner W, Kraemer A. References Poiraudeau S, Rannou F, Le Henanff A, Coudeyre E, Rozenberg S, Huas D, et al. Outcome of subacute low back pain: influence of patients' and rheumatologists' characteristics. Rheumatology (Oxford). 2006;45(6):718-23. 52. Schectman JM, Schroth WS, Verme D, Voss JD. Randomized controlled trial of education and feedback for implementation of guidelines for acute low back pain. J Gen Intern Med. 2003;18(10):773-80. 53. Espeland A, Baerheim A. Factors affecting general practitioners' decisions about plain radiography for back pain: implications for classification of guideline barriers--a qualitative study. BMC Health Serv Res. 2003;3(1):8. 54. Schers H, Braspenning J, Drijver R, Wensing M, Grol R. Low back pain in general practice: reported management and reasons for not adhering to the guidelines in The Netherlands. Br J Gen Pract. 2000;50(457):640-4. 55. Bishop A, Foster NE, Thomas E, Hay EM. How does the self-reported clinical management of patients with low back pain relate to the attitudes and beliefs of health care practitioners? A survey of UK general practitioners and physiotherapists. Pain. 2008;135(1-2):187-95. 55. Bishop A, Foster NE, Thomas E, Hay EM. How does the self-reported clinical management of patients with low back pain relate to the attitudes and beliefs of health care practitioners? A survey of UK general practitioners and physiotherapists. Pain. 2008;135(1-2):187-95. 56. Coudeyre E, Rannou F, Tubach F, Baron G, Coriat F, Brin S, et al. General practitioners' fear-avoidance beliefs influence their management of patients with low back pain. Pain. 2006;124(3):330-7. 57. Hurley L, Yardley K, Gross AR, Hendry L, McLaughlin L. A survey to examine attitudes and patterns of practice of physiotherapists who perform cervical spine manipulation. Man Ther. 2002;7(1):10-8. Page 15/18 58. Biggs L, Hay D, Mierau D. Canadian chiropractors' attitudes towards chiropractic philosophy and scope of practice: implications for the implementation of clinical practice guidelines. J Can Chiropr Figures Page 16/18 Figure 1 Flow chart of articles screening Determinants of guidelines ‘utilization emerging from the literature Determinants of guidelines ‘utilization emerging from the literature Figure 1 Flow chart of articles screening Flow chart of articles screening Flow chart of articles screening Figure 2 Page 17/18 Supplementary Files This is a list of supplementary files associated with this preprint. Click to download. ScopingRedactionTables.pdf Page 18/18 Page 18/18
https://openalex.org/W2114491220
https://europepmc.org/articles/pmc3016343?pdf=render
English
null
Split tendon transfers for the correction of spastic varus foot deformity: a case series study
Journal of foot and ankle research
2,010
cc-by
5,592
© 2010 Vlachou and Dimitriadis; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. RESEARCH Open Access * Correspondence: vlahma@yahoo.com 1Mitera General, Maternity and Children’s Hospital, Department of Paediatric Orthopaedics, 6 Erytrou Stavrou & Kifisias street, Marousi 15123, Athens- Greece Full list of author information is available at the end of the article Abstract Background: Overactivity of anterior and/or posterior tibial tendon may be a causative factor of spastic varus foot deformity. The prevalence of their dysfunction has been reported with not well defined results. Although gait analysis and dynamic electromyography provide useful information for the assessment of the patients, they are not available in every hospital. The purpose of the current study is to identify the causative muscle producing the deformity and apply the most suitable technique for its correction. Methods: We retrospectively evaluated 48 consecutive ambulant patients (52 feet) with spastic paralysis due to cerebral palsy. The average age at the time of the operation was 12,4 yrs (9-18) and the mean follow-up 7,8 yrs (4-14). Eigtheen feet presented equinus hind foot deformity due to gastrocnemius and soleus shortening. According to the deformity, the feet were divided in two groups (Group I with forefoot and midfoot inversion and Group II with hindfoot varus). The deformities were flexible in all cases in both groups. Split anterior tibial tendon transfer (SPLATT) was performed in Group I (11 feet), while split posterior tibial tendon transfer (SPOTT) was performed in Group II (38 feet). In 3 feet both procedures were performed. Achilles tendon sliding lengthening (Hoke procedure) was done in 18 feet either preoperatively or concomitantly with the index procedure. Results: The results in Group I, were rated according to Hoffer’s clinical criteria as excellent in 8 feet and satisfactory in 3, while in Group II according to Kling’s clinical criteria were rated as excellent in 20 feet, good in 14 and poor in 4. The feet with poor results presented residual varus deformity due to intraoperative technical errors. Conclusion: Overactivity of the anterior tibial tendon produces inversion most prominent in the forefoot and midfoot and similarly overactivity of the posterior tibial tendon produces hindfoot varus. The deformity can be clinically unidentifiable in some cases when Achilles shortening co-exists producing foot equinus. By identifying the muscle causing the deformity and performing the appropriate technique, very satisfying results were achieved in the majority of our cases. In three feet both muscles contributed to a combined deformity and simultaneous SPLATT and SPOTT were considered necessary. For complex foot deformities where the component of cavus co-exists, supplementary procedures are required along with the index operation to obtain the best result. Split tendon transfers for the correction of spastic varus foot deformity: a case series study Maria Vlachou1*, Dimitris Dimitriadis1,2 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 JOURNAL OF FOOT AND ANKLE RESEARCH JOURNAL OF FOOT AND ANKLE RESEARCH Introduction transfers is to affect the muscle-tendon complex in a way that it neither inverts nor everts the foot maintain- ing thus its stability and flexibility. Varus foot is often secondary to cerebral palsy and split tibialis anterior (SPLATT) or posterior tibialis tendon transfers (SPOTT) are commonly performed to correct the deformity. In both procedures the distal part of the tendon is splitting longitudinally, half of the tendon is detached from its medial insertion and is reattached to the lateral side of the foot [1]. The goal of the semi- The SPLATT as described by Hoffer et al [2] corrects supination and varus deformity of the midfoot second- ary to spasticity of the anterior tibial muscle. Equino- varus hindfoot deformity is most common in children with spastic hemiplegia and is caused by spasticity of the posterior tibial muscle that very often is associated with weakness of the peroneal muscles and tightness of the heel cord [Figure 1]. The reported clinical outcomes of SPLATT and SPOTT have been generally good but have been Page 2 of 11 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Figure 1 A 12 year-old female patient with Rt equinovarus hind foot deformity on weight bearing position. Figure 1 A 12 year-old female patient with Rt equinovarus hind foot deformity on weight bearing position. female patient with Rt equinovarus hind foot deformity on weight bearing position. Figure 1 A 12 year-old female patient with Rt equinovarus hind foot deformity on weight bearing position Our inclusion criteria were: 1. ambulatory or poten- tially ambulatory patients with cerebral palsy, 2. age no less than 6 years at the time of the operation, 3. varus deformity of the hind foot during gait (stance and swing phase), 4. flexible varus foot deformity, and 5. follow-up at least 4 years. Eigtheen feet presented equinus hind foot deformity due to triceps shortening. According to the deformity, the feet were divided in two groups (Group I with predominant forefoot and midfoot inver- sion and Group II with predominant hindfoot varus). The deformities were flexible in all cases in both groups. The first group consisted of 11 patients (11 feet, 9 female-2 male) all unilateral, 10 of them presenting hemiplegia and one quadriplegia. They also presented prominent forefoot and midfoot inversion due to over- activity of the anterior tibial tendon (AT), associated with a mild cavus component [Figure 2, 3]. Introduction Patients in this group underwent the SPLATT (Hoffer’s procedure). The second group consisted of 34 patients (38 feet, 24 female-10 male). The hemiplegic patients were 20, the diplegic 11 and the quadriplegic 3. They presented prominent varus hindfoot which persisted during the entire gait cycle due to the overactive PT. Patients in this group underwent the split PT tendon transfer (Green’s procedure). Eighteen feet presented also equi- nus hind foot deformity, requiring concomitant Achilles considerably varied [2-9]. SPLATT was first described by Kaufer et al [10] and was popularized by Green et al [4] and Kling et al [6] as a technique that bal- ances the hind part of the foot and maintains the plan- tar flexion power, but it should be applied only to patients from 4 to 6 years of age due to the potential risk of converting the foot to a valgus deformity in children younger than 4 years. Prerequisites of split tendon transfers is the ability or the potential ability for walking. Contraindications include a fixed bony deformity, and severe contraction mainly concerning the anterior tibialis, as the transferred semi-tendon can not reach the cuboid bone. Three patients (3 feet), two hemiplegic and one diplegic that were not included in the groups, underwent both procedures because both muscles con- tributed to a combined deformity and simultaneous SPLATT and SPOTT were performed. Clinical evalua- tion was based on the inspection of the patients while standing and walking, the range of motion of the foot and ankle, callus formation and the foot appearance using the clinical criteria of Hoffer et al [1] in Group I and of Kling et al [6] in Group II. According to Hoffer [1], the result was considered very good when there was no deformity postoperatively, total foot contact on the ground and proper shoe wearing. Satisfactory was con- sidered when there was mild varus, valgus or equinus deformity, small foot contact and overnight braces were used. Poor was considered when there was overcorrec- tion, undercorrection or equinus > 5° and braces were available. According to Kling [6] excellent results were graded when the child managed to walk with a planti- grade foot, without fixed or postural deformity, in a reg- ular shoe having no callosities. Patients and parents were pleased with the result and no brace was required post-operatively. Results were graded good in children who walk with less than 5° varus, valgus, or equinus posture of the hind foot, wearing regular shoes, having no callosities and were satisfied with the outcome. Feet with recurrent equinovarus deformity, or overcorrected into a valgus or calcaneovalgus deformity were consid- ered as poor results. Figure 2 Lateral view of the same foot with mild cavus component. The position of the hind foot was evaluated according to the criteria of Chang et al [11] for the surgical out- come. Severe varus was defined when the hind foot was in > 10° varus and additional operations were required, mild varus when the hind foot was in 5° to 10° of varus and no additional operation was required, neutral when the hind foot was in neutral position or in less than 5° of varus or valgus, mild valgus when the hind foot is in 5° to 10° of valgus with no additional operations and severe valgus when the hind foot was in more than 10° of valgus and additional operations were required. cord lengthening. Three patients (3 feet), two hemiplegic and one diplegic that were not included in the groups, underwent both procedures because both muscles con- tributed to a combined deformity and simultaneous SPLATT and SPOTT were performed. Clinical evalua- tion was based on the inspection of the patients while standing and walking, the range of motion of the foot and ankle, callus formation and the foot appearance using the clinical criteria of Hoffer et al [1] in Group I and of Kling et al [6] in Group II. According to Hoffer [1], the result was considered very good when there was no deformity postoperatively, total foot contact on the ground and proper shoe wearing. Satisfactory was con- sidered when there was mild varus, valgus or equinus deformity, small foot contact and overnight braces were used. Poor was considered when there was overcorrec- tion, undercorrection or equinus > 5° and braces were available. According to Kling [6] excellent results were graded when the child managed to walk with a planti- grade foot, without fixed or postural deformity, in a reg- ular shoe having no callosities. Patients and parents were pleased with the result and no brace was required post-operatively. Results were graded good in children who walk with less than 5° varus, valgus, or equinus posture of the hind foot, wearing regular shoes, having no callosities and were satisfied with the outcome. Feet with recurrent equinovarus deformity, or overcorrected into a valgus or calcaneovalgus deformity were consid- ered as poor results. cord lengthening. Materials and methods Written parental permission was obtained to allow the use of information held in the hospital records to be used in this review as Institutional Review Board (IRB) does not exist in our country. The cohort of the study consisted of 48 consecutive ambulant or potentially ambulant patients (52 feet) with spastic paralysis and dynamic equinovarus foot defor- mity that underwent split anterior (SPLATT) or split posterior (SPOTT) tendon transfer. The hemiplegic patients were 32, the diplegic 12 and the quadriplegic 4. Page 3 of 11 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Figure 2 Lateral view of the same foot with mild cavus component. Figure 2 Lateral view of the same foot with mild cavus component. Surgical procedures In SPLATT, the first incision exposed the insertion of the tendon which was split longitudinally as far as through the musculotendinous junction. The medial half of the tendon was left attached to the first metatarsal and first cunei- form, but the lateral half was detached from its insertion. The split lateral half of the tendon was passed subcuta- neously into the incision made over the cuboid and then was inserted into the holes made in the bone and either sutured to itself under moderate tension or if the length of the stump was not sufficient, anchoring was carried out with any other technique (pull-out wire, anchoring to the periosteum, etc.). For SPOTT, four separate incisions were used according to Green et al [4]. The first incision two centimetres long was positioned over the insertion of the posterior tibialis tendon on the navicular. The distal end of the tendon was identified and its sheath was opened. Figure 3 Postperative lateral views of the patient after plantar soft tissue release, Achilles lengthening and concomitant split posterior tendon transfer. Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Page 4 of 11 Page 4 of 11 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 lateral views of the patient after plantar soft tissue release, Achilles lengthening and concomitant split Figure 3 Postperative lateral views of the patient after plantar soft tissue release, Achilles lengthening and concomitant split posterior tendon transfer. fourth incision was made along the peroneus brevis and begun distal to the lateral malleolus and continued dis- tally just proximal to the insertion of the peroneus bre- vis on the base of the fifth metatarsal. The distal part of the sheath was opened and the split posterior tibial ten- don was sutured to the peroneal brevis tendon onto the cuboid by fish-mouth technique. The tension should be adjusted so that the hind part of the foot will rest in neutral position, by holding the foot in neutral and pull- ing hard on the posterior tibial tendon and slightly reducing the pull. The heel-cord lengthening was usually performed prior to the procedure and a long cast was applied with the knee extended and the foot in neutral position. The patient could bear weight on the cast as tolerated and four weeks later the cast was changed and a short walking cast was applied. Surgical procedures If the patient was able to dorsiflex the foot and ankle to neutral, no postopera- tive brace was used. The tendon was split longitudinally and the plantar half was dissected from its insertion. The free end was grasped and the tendon was split longitudinally as far proximally as possible. The second incision begun at the level of the medial malleolus and continued for approxi- mately six centimetres. The free half of the tendon was transferred into the proximal incision and the longitudi- nal split in the tendon was continued to the musculo- tendinous junction. A third incision is made directly posterior to the lateral malleolus beginning at the proxi- mal tip of the malleolus and continuing proximally. The peroneus brevis was identified and its sheath was split longitudinally. The distal stump of the split posterior tibial tendon in the second incision was threaded into a tendon-passer that passed the split portion directly pos- terior to the tibia and fibula and anterior to all the neu- rovascular and tendinous structures so as to enter laterally to the opened sheath of peroneus brevis. The Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Page 5 of 11 Table 1 Results. Number in parentheses is the total number of the feet and the percentage of the results according to the involvement Group II Excellent (20) Good (14) Poor (4) Hemiplegia (22) 20 (90,9%) 2 (9,09%) - Diplegia (12) - 12 (100%) - Quadriplegia (4) - 1 (25%) 3 (75%) Group I Excellent (8) Satisfactory (3) Poor Hemiplegia (10) 8 (80%) 2 (20%) - Diplegia - - - Quadriplegia (1) - 1(100%) - Both SPLATT- SPOTT Excellent (2) Satisfactory or Good (1) Poor Hemiplegia (2) 2 (100%) - - Diplegia (1) - 1 (100%) - Quadriplegia - - - Table 1 Results. Surgical procedures Number in parentheses is the total number of the feet and the percentage of the results according to the involvement Table 2 Supplementary operations performed concomitant with the index operation (SPLATT) Supplementary operations Feet (No) Group I Plantar soft tissue releases 11 Transcutaneous flexor tenotomies 8 Jones (transfer of the long toe extensor tendon to the neck of the 1st metatarsal) 5 Table 2 Supplementary operations performed concomitant with the index operation (SPLATT) and 2 satisfactory results. In the first group due to mild cavus foot component supplementary operations were performed at the same time with the index procedure [Figure 3, 4]. Plantar soft tissue releases (open release of the plantar aponeurosis+release of the plantar muscles from their insertion into the calcaneus) were performed in 11 feet, transcutaneous flexor tenotomies in 8, and Jones procedure in 5 feet (Table 2). The mean range of motion at the last follow-up was 10-20° of dorsiflexion, 30-40° of plantarflexion, 25-30° of foot inversion and 15-20° of foot eversion. No overcor- rection or undercorrection was reported. Results Evaluation of the results was carried out using the clini- cal criteria of Hoffer [1] in group one and Kling and Kaufer [6] in group two (Tables 1, 2). In the former, very good results were obtained in 8 feet and satisfac- tory in 3. In the later one, 22 feet were excellent, 12 good and 4 poor. The 3 feet that underwent simulta- neously both of the procedures presented 1 excellent In the second group, 23 feet presenting concomitant cavus foot component that underwent supplementary operations performed at the same time with the index operation. Plantar soft tissue releases were performed in 15 feet, Jones procedure in 5, long extensor tendons transfer to the metatarsals in 2, as well as transcutaneous Figure 4 Postoperative anterior and posterior views of the same patient in six years follow-up. Figure 4 Postoperative anterior and posterior views of the same patient in six years follow-up. Page 6 of 11 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Table 3 Supplementary operations performed concomitant and after the index operation (SPOTT) Supplementary operations Feet (No) Group II Transcutaneous flexor tenotomies 23 Achilles cord lengthenings 18 Plantar soft tissue releases 15 Jones 5 Extensor tendons transfer to the metatarsals 2 After index operation Calcaneocuboid fusion (Evans) 4 Table 3 Supplementary operations performed concomitant and after the index operation (SPOTT) underwent calcaneocuboid fusion sixteen and eighteen months after the index operation. The mean value of mild varus was (-14,5 ± 12,2°) and concerning the feet with the hind foot in neutral position the mean value was 5.0 ± 7.4°. The results in patients with hemiplegic pattern were better and significantly different than the diplegic and quadriplegic ones (p = 0.005), by using the chi-square analyses as statistical significant involvement at p < 0.01 in the second group (Table 1). All patients with an excellent result were brace free at the last follow-up with significant improvement in gait, able to walk with plantigrade feet, use of regular shoes and parent’s satis- faction with the outcome. The patients with good results continued to use a night brace (AFO). All of them had good correction of the hind foot equinus and the ankle was able to dorsiflex to at least 90°. Results The patients pre- senting a poor result required continued bracing because of the severe varus residual deformity, appear- ing excessive weight bear on the lateral border of the foot and having painful callosities. These patients required further foot realignment (calcaneocuboid fusion). flexor tenotomies in 23 feet (Table 3). It has also been required concomitant Achilles cord lengthening in 18 feet due to the equinus position of the hind foot. None of the feet presented mild or severe valgus postoperatively, while 4 feet presented severe varus deformity and Figure 5 A 10 year-old male patient with Rt varus hind foot and mild cavus deformity. Discussion It is generally accepted that overactivity of the AT is responsible for varus-inversion forefoot deformity, whereas the overactivity of PT causes equinovarus hind- foot deformity. Between these two conditions the second is much more common. However, the cause of the deformity can not be clinically identified in some cases, especially when Achilles shortening co-exists. The use of dynamic electromyography and gait analysis can be helpful, but it can not be available in every Institution. Twenty-seven out of thirty-eight feet in the second group presented concomitant cavus foot component and underwent supplementary operations performed conco- mitant with the index operation. Plantar soft tissue release was the most common out of these procedures, as the release constitutes a keystone procedure for lengthening the shortened base of the foot, and its con- tribution to the successful outcome for the correction of the cavus component cannot be overemphasized [Figure 5, 6]. Our results in hemiplegic patients were better and significantly different than the diplegic and quadriplegic ones, indicating that the underlying neurologic impaire- ment affect the results of the surgery [Figure 7, 8]. One of our prerequisite for split tibialis tendon transfers was the ability of the patients for walking or the potential of standing and ambulation [Figure 9, 10, 11 and 12]. The simple lengthening of the posterior tibialis tendon weak- ens the muscle, and if the tendon and the heel cord are lengthened, then plantar-flexion strength is significantly reduced. Figure 5 A 10 year-old male patient with Rt varus hind foot and mild cavus deformity. Page 7 of 11 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Figure 6 Increased pressure areas are demonstrated on podoscope. Figure 6 Increased pressure areas are demonstrated on podoscope. Figure 6 Increased pressure areas are demonstrated on podoscope. tendons transfer to the metatarsals aimed to improve the metatarsophalangeal dysfunction, to enhance ankle dorsiflexion and in association with the transcutaneous flexor tenotomies in several toes to correct the claw- ing. Although overcorrection is more difficult to treat [13] we did not observe any, while the poor results in SPLATT included severe varus deformity in 4 feet that required calcaneocuboid fusion. One of our inclusion criteria was the age of the patients at the time of the surgery to be more than 6 years, as it is an important factor for the final outcome. Discussion Ruda and Frost [14] reported that after intramuscular posterior tendon All reports regarding split tendon transfers showed favourable results [4-8,11,12] with our study support- ing the same. Two factors that should be considered to perform the procedures are: the flexibility of the defor- mity and the dorsiflexion of the ankle to at least 5°- 10° beyond neutral. The fixed bony deformity prevents complete correction of the equinovarus position of the foot and if it co-exists, a bone procedure should be considered before the tendon transfer, to prevent per- sistent varus. In the present series, only flexible defor- mities passively corrected were included. The extensor Figure 7 Postoperative neutral position of the hind foot after plantar soft tissue release and split posterior tendon transfer. Figure 7 Postoperative neutral position of the hind foot after plantar soft tissue release and split posterior tendon transfer. Figure 7 Postoperative neutral position of the hind foot after plantar soft tissue release and split posterior tendon transfer. Figure 8 Final result in a five year follow-up. Figure 8 Final result in a five year follow-up. Figure 7 Postoperative neutral position of the hind foot after plantar soft tissue release and split posterior tendon transfer. Figure 7 Postoperative neutral position of the hind foot after plantar soft tissue release and split posterior tendon transfer. Figure 8 Final result in a five year follow-up. Page 8 of 11 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 postoperative period and the final results can be esti- mated only after the skeletal growth [11]. Figure 9 A seven-year old female patient with severe equinovarus hind foot deformity with inability to stand and walk. Residual varus deformity in our series were attribu- ted to technical intraoperative errors in balancing the tension between the medial and lateral tendon halves. Four feet underwent bone procedure for the correction of the hindfoot deformity at a later stage. In 3 feet, some technical difficulty was encountered in suturing the split posterior tibial tendon to the peroneus brevis, as the split half being short. Although we performed concomitant intramuscular lengthening of this part of the tendon so as to be sufficient for transfer, we do not recommend it as the tendon loose more of its power. Discussion Additionally, in 3 feet both muscles contributed to a combined deformity, which was defined only intraopera- tively, and therefore simultaneous SPLATT and SPOTT were satisfactorily performed [Figure 13, 14]. Figure 9 A seven-year old female patient with severe equinovarus hind foot deformity with inability to stand and walk. The purpose of doing split tendon transfers as opposed to whole tendon transfers in children with cerebral palsy has been considered to be more effec- tive, as it distributes equally the muscle power, elimi- nating the possibility of residual deformity or overcorrection. Anterior transposition or rerouting of the posterior tibial tendon has been previously described [16] but calcaneus deformity may be a result in spastic muscles, by converting the PT into an ankle dorsiflexor [17]. lengthening in 29 patients, the reccurence in varus observed in two, being less than 6 years of age. Lee and Bleck [15] reported a reccurence of 29% in patients less than 8 years at the time of the operation, as the spastic muscle tends to retain its contractile properties even if it is weakened or transferred at an age younger than 8 years. In conclusion, the rapid bone growth in children that underwent split tibialis tendon transfers in less than 6 years of age, may lead to reccurence. We selected a follow-up period of more than 4 years as the failure rate increases with the The anterior transfer of the posterior tibial muscle through the interosseous membrane is an attractive Figure 10 Postoperative posterior and anterior views after Achilles lengthening and concomitant bilateral split posterior tendon transfer. rative posterior and anterior views after Achilles lengthening and concomitant bilateral split posterior tendon Figure 10 Postoperative posterior and anterior views after Achilles lengthening and concomitant bilateral transfer. Figure 10 Postoperative posterior and anterior views after Achilles lengthening and concomitant bilateral split posterior tendon transfer. Page 9 of 11 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 Figure 11 Final result on podoscope. Figure 11 Final result on podoscope. Figure 12 Lateral view in a 4 year follow-up. Figure 12 Lateral view in a 4 year follow-up. Page 10 of 11 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 In complex deformities, other supplementary procedures may be required to achieve the best possible outcome. In complex deformities, other supplementary procedures may be required to achieve the best possible outcome. References 1. Hoffer MM, Reiswig JA, Garrett AM, Perry J: The split anterior tibial tendon transfer in the treatment of spastic varus hindfoot of childhood. Orthop Clin North Am 1974, 5:31-8. 1. Hoffer MM, Reiswig JA, Garrett AM, Perry J: The split anterior tibial tendon transfer in the treatment of spastic varus hindfoot of childhood. Orthop Clin North Am 1974, 5:31-8. In the majority of our cases, the deforming force was successfully determined preoperatively and the final results justified the applied operative procedure. 2. Hoffer MM, Bakarat G, Koffman M: 10 year follow-up of split anterior tibial tendon transfer in cerebral palsied patients with spastic equinovarus deformity. J Pediatr Orthop 1985, 5:432-4. 2. Hoffer MM, Bakarat G, Koffman M: 10 year follow-up of split anterior tibial tendon transfer in cerebral palsied patients with spastic equinovarus deformity. J Pediatr Orthop 1985, 5:432-4. 3. Edwards P, Hsu J: SPLATT combined with tendo Achilles lengthening for spastic equinovarus in adults: results and predictors of surgical outcome. Foot Ankle 1993, 14:335-8. 4. Green NE, Griffin PP, Shiavi R: Split posterior tibial tendon in spastic cerebral palsy. J Bone Joint Surg 1983, 65-A:748-754. Figure 14 Anterior view of the Rt foot after split anterior tibial tendon transfer in a 4 year follow-up. p y g 5. Kapaya H, Yamada S, Nagasawa T, Ishihara Y, Kodama H, Endoh H: Split posterior tibial tendon transfer for varus deformity of hindfoot. Clin Orthop and Relat Res 1996, 323:254-260. 6. Kling TF, Kaufer H, Hensinger RN: Split posterior tibial tendon transfers in children with cerebral spastic paralysis and equinovarus deformity. J Bone Joint Surg 1985, 67-A:186-194. 7. Medina PA, Karpman RR, Yeung AT: Split posterior tibial tendon transfer for spastic equinovarus foot deformity. Foot Ankle 1989, 10:65-67. 8. Synder M, Kumar SJ, Stecyk MD: Split tibialis posterior tendon transfer and tendo-achillis lengthening for spastic equinovarus feet. J Paediatr Orthop 1993, 13:20-23. 8. Synder M, Kumar SJ, Stecyk MD: Split tibialis posterior tendon transfer and tendo-achillis lengthening for spastic equinovarus feet. J Paediatr Orthop 1993, 13:20-23. 9. Vogt JC: Split anterior tibial transfer for spastic equinovarus foot deformity: retrospective study of 73 operated feet. J Foot Ankle Surg 1998, 37:2-7. 9. Vogt JC: Split anterior tibial transfer for spastic equinovarus foot deformity: retrospective study of 73 operated feet. J Foot Ankle Surg 1998, 37:2-7. 10. Kaufer H: Split tendon tranfers. Orthop Trans 1977, 1:191. 11. Discussion Figure 13 Intraoperative view of a six year old hemiplegic patient with varus forefoot deformity. Consent Written informed consent was obtained from the patient for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal. Authors’ contributions MV: Analysis and interpretation of data, preparation of the manuscript, acquisition of pictures and additional materials, corresponding author. DD: Approved the final manuscript. MV: Analysis and interpretation of data, preparation of the manuscript, acquisition of pictures and additional materials, corresponding author. DD: Approved the final manuscript. procedure as it removes the actual deforming force and balances the weak or absent anterior tibial and peroneal muscles, but is effective in patients with nonspastic paralytic equinovarus deformities of the foot [18] A con- tinuously spastic posterior tibial muscle will maintain its spasticity when transferred and if a heel cord lengthen- ing is performed concomitant with the anterior transfer of the posterior tibialis, a calcaneus deformity may likely result. All authors read and approved the final manuscript. All authors read and approved the final manuscript. Author details 1Mit G l 1Mitera General, Maternity and Children’s Hospital, Department of Paediatric Orthopaedics, 6 Erytrou Stavrou & Kifisias street, Marousi 15123, Athens- Greece. 2Pendeli Children’s Hospital, Department of Paediatric Orthopaedics, 8 Ippocratous street, N.Pendeli 15236, Athens-Greece. Figure 13 Intraoperative view of a six year old hemiplegic patient with varus forefoot deformity. Competing interests The authors declare that they have no competing interests. The authors declare that they have no competing interests. Received: 2 May 2010 Accepted: 14 December 2010 Published: 14 December 2010 References Chang CH, Albarracin JP, Lipton GE, Miller F: Long-term follow-up of surgery for equinovarus foot deformity in children with cerebral palsy. Journal of Paediatric Orthopaedics 2002, 22:792-799. 12. Saji MJ, Upadhyay SS, Hsu LCS, Leong JCY: Split tibialis posterior transfer for equinovarus deformity in cerebral palsy. Long-term results of a new surgical procedure. J Bone Joint Surg 1993, 75-B:498-501. 13. Fulford GE: Surgical management of ankle and foot deformities in cerebral palsy. Clin Orthop 1990, 253:55-61. 14. Ruda R, Frost HM: Cerebral palsy. Spastic varus and forefoot adductus, treated by intramuscular posterior tibial tendon lengthening. Clin Orthop 1971, 79:61-70. 14. Ruda R, Frost HM: Cerebral palsy. Spastic varus and forefoot adductus, treated by intramuscular posterior tibial tendon lengthening. Clin Orthop 1971, 79:61-70. Figure 14 Anterior view of the Rt foot after split anterior tibial tendon transfer in a 4 year follow-up. Figure 14 Anterior view of the Rt foot after split anterior tibial tendon transfer in a 4 year follow-up. 15. Lee CL, Bleck EE: Surgical correction of equinus deformity in cerebral palsy. Dev Med Child Neurol 1980, 22:287-92. Page 11 of 11 Page 11 of 11 Vlachou and Dimitriadis Journal of Foot and Ankle Research 2010, 3:28 http://www.jfootankleres.com/content/3/1/28 16. Baker LD, Hill LM: Foot alignment in the cerebral palsy patient. J Bone Joint Surg 1964, 46A:1-15. 17. Basset FH, Baker LD: Equinus deformity in cerebral palsy. Curr Pract Orthop Surg 1966, 3:59-74. 18. Root L, Kirz P: The result of posterior tibial tendon surgery in 83 patients with cerebral palsy. Dev Med Child Neurol 1982, 24:241-242. doi:10.1186/1757-1146-3-28 Cite this article as: Vlachou and Dimitriadis: Split tendon transfers for the correction of spastic varus foot deformity: a case series study. Journal of Foot and Ankle Research 2010 3:28. 16. Baker LD, Hill LM: Foot alignment in the cerebral palsy patient. J Bone Joint Surg 1964, 46A:1-15. 17. Basset FH, Baker LD: Equinus deformity in cerebral palsy. Curr Pract Orthop Surg 1966, 3:59-74. 18. Root L, Kirz P: The result of posterior tibial tendon surgery in 83 patients with cerebral palsy. Dev Med Child Neurol 1982, 24:241-242. doi:10.1186/1757-1146-3-28 Cite this article as: Vlachou and Dimitriadis: Split tendon transfers for the correction of spastic varus foot deformity: a case series study. Journal of Foot and Ankle Research 2010 3:28. doi:10.1186/1757-1146-3-28 Cite this article as: Vlachou and Dimitriadis: Split tendon transfers for the correction of spastic varus foot deformity: a case series study. References Journal of Foot and Ankle Research 2010 3:28. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit
https://openalex.org/W4286825518
https://zenodo.org/records/2589568/files/6676.pdf
English
null
Possibilities of pathogenetic correction of hyperkinetic disorders taking into account an acid-base balance
DOAJ (DOAJ: Directory of Open Access Journals)
2,019
cc-by
4,486
The journal has had 7 points in Ministry of Science and Higher Education parametric evaluation. Part B item 1223 (26/01/2017). 1223 Journal of Education, Health and Sport eISSN 2391-8306 7 © The Authors 2019; This article is published with open access at Licensee Open Journal Systems of Kazimierz Wielki University in Bydgoszcz, Poland Open Access. This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author (s) and source are credited. This is an open access article licensed under the terms of the Creative Commons Attribution Non commercial license Share alike. (http://creativecommons.org/licenses/by-nc-sa/4.0/) which permits unrestricted, non commercial use, distribution and reproduction in any medium, provided the work is properly cited. The authors declare that there is no conflict of interests regarding the publication of this paper. Received: 20.02.2019. Revised: 28.02.2019. Accepted: 08.03.2019. Hertsev V. N., Stoyanov A. N., Muratova T. N., Vastyanov R. S., Kolesnik E. A. Possibilities of pathogenetic correction of hyperkinetic disorders taking into account an acid-base balance. Journal of Education, Health and Sport. 2019;9(3):158-169. eISNN 2391-8306. DOI http://dx.doi.org/10.5281/zenodo.2589568 http://ojs.ukw.edu.pl/index.php/johs/article/view/6676 Hertsev V. N., Stoyanov A. N., Muratova T. N., Vastyanov R. S., Kolesnik E. A. Possibilities of pathogenetic correction of hyperkinetic disorders taking into account an acid-base balance. Journal of Education, Health and Sport. 2019;9(3):158-169. eISNN 2391-8306. DOI http://dx.doi.org/10.5281/zenodo.2589568 http://ojs.ukw.edu.pl/index.php/johs/article/view/6676 Hertsev V. N., Stoyanov A. N., Muratova T. N., Vastyanov R. S., Kolesnik E. A. Possibilities of pathogenetic correction of hyperkinetic disorders taking into account an acid-base balance. Journal of Education, Health and Sport. 2019;9(3):158-169. eISNN 2391-8306. DOI http://dx.doi.org/10.5281/zenodo.2589568 http://ojs.ukw.edu.pl/index.php/johs/article/view/6676 UDC 616.8: 615.217 Abstract As a result of analysis of the available scientific data, a significant relationship between hyperkinetic syndromes and changes in the acid-base state has been revealed. The provoking effect of alkalosis on the occurrence and severity of hyperkinetic disorders was confirmed. An own example of effective treatment of patient with essential myoclonus with taking in account his acid-base state has been given. The addition of acetylsalicylic acid to the treatment with clonazepam caused a more significant decrease in the severity of hyperkinetic disorders and improved the patient’s general condition and his quality of life. So that we suggest studying of acid-base balance in patients with hyperkinetic syndromes and syndrome of increased neuromuscular excitability in the outpatient setting and in hospital conditions at the making of initial diagnosis, and also recommend studying of acid-base balance in patients who already have neurological diagnoses, if such a study has not been made previously. Correction of acid-base status in the treatment of patients with hyperkinetic syndromes and the syndrome of increased neuromuscular excitability contributes to greater effectiveness of therapy than just symptomatic treatment of hyperkinetic disorders. 158 Key words: acid-base balance, alkalosis, essential myoclonus, hyperkinetic disorders ВОЗМОЖНОСТИ ПАТОГЕНЕТИЧЕСКОЙ КОРРЕКЦИИ ГИПЕРКИНЕТИЧЕСКИХ НАРУШЕНИЙ С УЧЕТОМ СОСТОЯНИЯ КИСЛОТНО-ОСНОВНОГО БАЛАНСА В. Н. Герцев, А. Н. Стоянова, Т. Н. Муратова, Р. С. Вастьянов, Е. А. Колесник Е. А. Колесник Одесский Национальный Медицинский Университет В результате анализа имеющихся научных данных выявлена существенная взаимосвязь между гиперкинетическими синдромами и изменениями кислотно- основного состояния. Подтверждено провоцирующее действие алкалоза на возникновение и выраженность гиперкинетических нарушений. Приведен собственный пример эффективного лечения пациента с эссенциальной миоклонус с учетом его кислотно-основного состояния. Авторы предлагают изучать кислотно-основного баланс у пациентов с гиперкинетическими синдромами и синдромом повышенной нервно-мышечной возбудимости в амбулаторных и в стационарных условиях при постановке первоначального диагноза, а также рекомендуют такого рода диагностику для пациентов, уже имеющих неврологические диагнозы. Коррекция кислотно- основного состояния способствует большей эффективности терапии, чем просто симптоматическое лечение таких нарушений. Ключевые слова: кислотно-щелочной баланс, алкалоз, эссенциальный миоклонус, гиперкинетические расстройства Ключевые слова: кислотно-щелочной баланс, алкалоз, эссенциальный миоклонус, гиперкинетические расстройства Relevance of the topic. Hyperkinesias occupy a significant proportion of the neurological symptoms and syndromes that practicing neurologists reveal in their routine practice. One of these hyperkinesis is myoclonus. The term myoclonus is defined as sudden, rapid, shock-like movement. These movements can be “positive” or “negative”. Positive myoclonus leads to muscle contraction or muscle groups contaction. Asterixis or negative myoclonus is a short-term loss of muscle tone followed by contraction of other muscles, which leads to a nod type movement. These involuntary movements often have a 159 characteristic sawtooth pattern and they usually disappear during sleep. Typically, a myoclonus is a short (10–50 ms, rarely more than 100 ms), irregular muscle contractions, often without noticeable movement. Myoclonus amplitude can vary significantly. The lightning nature of a rectangular myoclonus wave helps in its differentiation from tremor (rhythmic oscillations), chorea (large, smooth movements), dystonia (reduction duration more than 100 ms, often with a twisting position), ticks (pulse duration> 100 ms, can be temporarily suppressed ), or fasciculations (single muscles involved, minimal motor effect [1, 2]. Myoclonus can be physiological, familial, observed with progressive myoclonus epilepsy, lysosomal glycogen metabolism disorders, mitochondrial dysfunction, secondary due to congenital metabolic disturbances, injuries, neurodegenerative diseases, renal and hepatic insufficiency, non-ketone hyperglycemia and hypercapnia, alkalosis, alkalosis, alkalosis, alkalosis, alkalosis, alkalosis, alkalosis [3-6]. The stabilization of the acid-base state of the human body is provided by phosphate (1% of the buffer capacity of blood, its role in the tissues, especially in the kidneys, is very significant), bicarbonate (10% of the buffer capacity of blood), protein and hemoglobin (about 70% of the buffer blood capacity) buffer systems and the functioning of specific physiological mechanisms of compensation in some organs (lungs, kidneys, liver, gastrointestinal tract, bone tissue) [7-9]. Phosphate buffer system provides regulation of acid-base balance within cells, mainly kidney tubules. Phosphate buffer consists of two components: - Na2HPO4 (alkali) and NaH2PO4 (acid). Bicarbonate buffer system is a buffer of blood and intercellular fluid, it maintains the balance of HCO3 / CO2. Where: H + HCO3 <----> H2CO3 <----> CO2 + H2O H + HCO3 <----> H2CO3 <----> CO2 + H2O HCO3 functions as a base. CO2 (carbon dioxide) - as an acidic substance. Thus, an increase in HCO3 (bicarbonate) or a decrease in CO2 will make the blood more alkaline. Reducing HCO3 or increasing CO2 makes the environment more acidic. CO2 levels are physiologically regulated by the pulmonary system through respiration, while HCO3 levels are regulated by the kidneys through reabsorption. Thus, respiratory alkalosis is a decrease in the CO2 content in serum. Although it is theoretically possible to reduce the production of 160 CO2, this condition is mainly the result of hyperventilation, when CO2 is exhaled through the lungs [10]. Protein buffer system - the main intracellular buffer. It accounts for about 75% of the buffer capacity of the intracellular fluid. The components of the protein buffer are an acid weakly dissociating protein (protein COOH) and salts of a strong base (protein COONa). Hemoglobin buffer system is the most capacious blood buffer. It consists of the acidic component - oxygenated HbO2 and alkaline - non-oxygenated Hb. Bone carbonates are a depot for buffer systems of the whole body. They contain deposited a significant amount of salts of carbonic acid. With a rapid increase in the acid content, this system provides up to 30-40% of the buffer capacity. Changes in the acid-base state are possible both in the direction of alkalosis and in the direction of acidosis. At the same time, as a rule, more attention is paid to the development of acidosis in the pathogenesis of diseases, including neurological ones, although both of these conditions have a negative effect on the functional state of the nervous system. Alkalosis might be compensated and uncompensated. With compensated alkalosis, the indicators of the acid-base status of the blood are within the normal range and only changes in buffer systems and regulatory mechanisms are observed. With uncompensated alkalosis, the pH exceeds the upper limit of normal, which is caused by an excess of bases and a violation of the physiological mechanisms of regulation of acid-base balance. The main causes of metabolic alkalosis are listed below [11]: Chloride depletion: gastric diseases: vomiting, mechanical drainage, bulimia chloruretic diuretics: bumetanide, chlorothiazide, metalazone, etc. H + HCO3 <----> H2CO3 <----> CO2 + H2O diarrhea: villous adenoma, congenital chloride diarrhea, posthypercapnic state reduction of chlorides in food with a base load: chloride-deficient infant formula gastrocystoplasty reduction of chlorides in food with a base load: chloride-deficient infant formula gastrocystoplasty glucocorticoid-suppressed, carcinoma mineralocorticoid excess primary excess of deoxycorticosterone: deficiency of 11β- and 17α-hydroxylase drugs: licorice (glycyrrhizic acid) in the form of confectionery or flavoring, carbenoxolone primary excess of deoxycorticosterone: deficiency of 11β- and 17α-hydroxylase drugs: licorice (glycyrrhizic acid) in the form of confectionery or flavoring, carbenoxolone 161 Liddle syndrome secondary aldosteronism excess adrenal corticosteroids: primary, secondary, exogenous severe hypertension: malignant, accelerated, renovascular hemangiopericytoma, nephroblastoma, renal cell carcinoma Bartter syndrome and Gitelman syndrome and their variants laxative abuse, clay consumption Hypercalcemic condition hypercalcemia in malignant tumors acute or chronic milk alkaline syndrome Other carbenicillin, ampicillin, penicillin bicarbonate intake: massive or in the presence of renal failure way out of starvation hypoalbuminemia excess adrenal corticosteroids: primary, secondary, exogenous severe hypertension: malignant, accelerated, renovascular hemangiopericytoma, nephroblastoma, renal cell carcinoma Bartter syndrome and Gitelman syndrome and their variants laxative abuse, clay consumption Bartter syndrome and Gitelman syndrome and their variants laxative abuse, clay consumption carbenicillin, ampicillin, penicillin bicarbonate intake: massive or in the presence of renal failure way out of starvation Acid-alkaline imbalance in various metabolic disorders naturally leads to disruption of the functioning of the brain and spinal cord. Compared with acidosis, patients with alkalosis have more severe neurological symptoms that are difficult to correct [12-16]. This is due, in particular, to the greater sensitivity of GABA-ergic neurons to alkalosis than to acidosis [12]. Alkalosis can provoke the development of many neurological symptoms, in particular, myoclonus. With a sharp change in pH above 7.55, a significant decrease in cerebral blood flow is observed with the development of seizures and coma [17]. Photo-myoclonus and myoclonus-like hyperkinesis have been described in metabolic alkalosis [18, 19]. In 2003, the first case of myoclonus caused by metabolic alkalosis due to vomiting associated with drug intake was described, in which severe hyponatremia, bipocalemia and alkalosis were also observed [20]. A case of metabolic alkalosis and myoclonus caused by the use of antacids containing sodium bicarbonate in a person with a pre-existing cerebrovascular disease was described in Japan [21]. H + HCO3 <----> H2CO3 <----> CO2 + H2O Also described is the case of the occurrence of myoclonus in a 90-year-old patient on the background of long-term use of licorice contained in the antacid preparation [22] Neuromuscular symptoms of metabolic alkalosis include, in addition to myocloni, also paresthesias and fasciculations, which may be associated with a decrease in the content of ionized calcium in serum. At the same time, Chvostek’s symptom is usually negative. 162 Fasciculations and tetany are generally more common than myoclonus. It is assumed that tetany is caused not only by a decrease in the concentration of ionized calcium in serum, but is also associated with an increase in pH-dependent myofibrillary sensitivity to calcium [23, 24]. In addition to metabolic alkalosis, respiratory alkalosis is also isolated. It is the most common acid-base imbalance, with the same frequency occurring in men and women. The frequency and prevalence of the disease depends on the etiology. Accordingly, the level of morbidity and mortality also depends on the etiology of the disease. In almost all cases, respiratory alkalosis is induced by hyperventilation, leading to central mechanisms, hypoxemia, pulmonary pathology and iatrogeny [10]. The central causes are head injuries, strokes, hyperthyroidism, anxiety disorders, pain, stress, the effects of certain drugs, drugs such as salicylates and various intoxications [10]. Hypoxic stimulation leads to hyperventilation in an attempt to correct hypoxia due to the loss of CO2. Pulmonary causes include pulmonary emboli, pneumothorax, pneumonia, and acute asthma or COPD exacerbations. Iatrogenic causes are primarily associated with hyperventilation in intubated patients with mechanical ventilation [10]. There are the following pathogenetic aspects of the development of respiratory alkalosis in various somatic diseases [25]: Hyperthyroidism: hyperthyroidism increases the severity of ventilation chemoreflexes, thereby causing hyperventilation. The severity of chemoreflexes normalized in the treatment of hyperthyroidism. Pregnancy: Progesterone levels increase during pregnancy. Progesterone stimulates the respiratory center, which can lead to respiratory alkalosis, which is common in pregnant women. [26]. Congestive heart failure: in patients with congestive heart failure (and other diseases with a decrease in cardiac output) hyperventilation is observed at rest, during exercise and during sleep. This is due to the fact that pulmonary vascular and interstitial receptors are stimulated due to pulmonary stagnation. In addition, low cardiac output and hypotension stimulate respiration by acting on the arterial baroreceptors. Chronic / severe liver disease. Several mechanisms have been proposed to explain hyperventilation associated with liver disease. H + HCO3 <----> H2CO3 <----> CO2 + H2O Elevated levels of progesterone, ammonia, vasoactive intestinal peptide and glutamine can stimulate respiration. Patients with severe liver disease or portal hypertension may have pulmonary arteriovenous anastomoses in the lungs or portal pulmonary shunts, leading to hypoxemia. This stimulates peripheral 163 chemoreceptors and leads to hyperventilation, and the degree of respiratory alkalosis correlates with the severity of liver failure. [26] Salicylate overdose: Respiratory alkalosis initially develops, followed by metabolic acidosis, which causes secondary hyperventilation. Fever and sepsis: Fever and sepsis can manifest as hyperventilation, even before the development of hypotension. The exact pathogenetic mechanism of this condition is unknown, but it is believed that it is due to the stimulation of the carotid sinus or hypothalamus with increasing body temperature. Gram-negative sepsis: before the development of fever, hypoxia or hypotension, acute respiratory alkalosis develops, which may be the only early symptom. [26]. Pain: Hyperventilation can be caused by stimulation of peripheral and central chemoreceptors, as well as behavior control systems. Hyperventilation syndrome, which is also known as psychogenic hyperventilation, was first described in 1935 [27]. Hyperventilation is triggered by stress and anxiety, both of which act on the behavioral control of breathing. Hyperventilation stops during sleep, when the behavioral control system is inactive, and only the metabolic system controls respiration. The diagnosis of hyperventilation syndrome is a diagnosis of exclusion, it is necessary to exclude all organic diseases, including, above all, life-threatening conditions, such as: pulmonary embolism, myocardial ischemia, hyperthyroidism, before making this diagnosis [28]. Respiratory alkalosis, in turn, can be acute and chronic. This is determined based on the level of metabolic compensation for respiratory disease. Excessive levels of HCO3 are buffered to maintain physiological pH through renal reduction of H secretion and increased secretion of HCO3, however, this metabolic process takes several days, while respiratory disease can alter CO2 levels in minutes or hours. Thus, acute respiratory alkalosis is associated with high bicarbonate levels, since there was not enough time to reduce HCO3 levels, and chronic respiratory alkalosis was associated with low and normal HCO3 levels [10]. The symptoms of respiratory alkalosis depend on its duration, severity and underlying disease causing hyperventilation. Hyperventilation syndrome can mimic many other serious diseases and includes weakness, cardiac arrhythmias, increased neuromuscular excitability, tingling in the fingers and toes and around the lips (paresthesia), chest pain, with pronounced alkalosis, tetany can develop [29, 30]. H + HCO3 <----> H2CO3 <----> CO2 + H2O Acute onset of hypocapnia can cause cerebral vasoconstriction with a decrease in cerebral blood flow and such neurological symptoms as 164 dizziness, confusion, syncope and convulsions. The first cases of spontaneous hyperventilation with the development of dizziness and tingling, followed by the development of tetany, were described in 1922 in patients with cholecystitis, abdominal distension and hysteria. [31]. Haldane JS, Poulton EP. (1908) described painful tingling in the hands and feet, numbness and sweating of the hands, and cerebral symptoms that occurred after experimental hyperventilation. [32]. Treatment of respiratory alkalosis is aimed at treating the underlying pathology. In patients with anxiety disorders, anxiolytics are used. Beta-adrenergic blockers can help control sympathicotonia, which can lead to hyperventilation syndrome in some patients. [28]. Determining the presence of sympathicotonia in the cardiovascular system in clinical practice is most appropriate, from our point of view, using the Kerdo index or cardiointervalometry. Treatment of respiratory alkalosis primarily depends on the cause of it. Antibiotics are effective for infectious diseases. For embolic diseases, anticoagulant therapy is necessary. Support for lung ventilation may be required in patients with acute respiratory failure, asthma, acute or chronic obstructive pulmonary disease. In patients who are on artificial ventilation, it may be necessary to regulate the ventilation parameters with a decrease in the respiratory rate. In this group of patients, it is also necessary to control the content of arterial and venous gases. In severe cases, the pH can be directly restored using acidifying agents [10]. Generally accepted in clinical practice is the provision of the mandatory control of acid-base balance in intensive care units and intensive care units. In other cases, much less attention is paid to the study of acid-base balance, which primarily applies to outpatient patients, in particular, to patients with a neurological profile. This situation is explained in particular by the fact that the indicators of acid-base balance are in fairly tight boundaries and their significant changes in most cases cause serious violations of the patient’s health, leading to their hospitalization in the intensive care unit and intensive care unit. It has been established that with metabolic alkalosis with pH 7.55, the risk of death is 45%, with indicators above 7.65 the risk increases significantly and reaches 80% [33,34]. The results of our own observations: Under our observation was the patient, who was sent to us for a consultation with myoclonic hyperkineses. H + HCO3 <----> H2CO3 <----> CO2 + H2O In the study of indicators of acid-base status of the blood, a pronounced alkalosis with a pH of 7.75 was detected. In connection with the naturally arising doubts about the reliability of the analysis, a repeated study was performed. With repeated analysis, the pH was at the level of 7.65. Data from laboratory and instrumental methods of research of a patient: Data from laboratory and instrumental methods of research of a patient: TSH - 1.24 µMO / ml 165 Urine: straw yellow, clear, specific gravity 1014, pH - 6.0, protein - no, glucose - no Leukocytes - 2-3 in the field of view, epithelium flat 1-2 in the field of view. MRI of the brain: MR signs of moderate expansion of convective cerebrospinal fluid spaces in the frontal regions, uneven expansion of perivascular spaces. Volume and focal formations of the brain was not detected. EEG showed no signs of epileptic activity. The fundus of the eye: the optic nerve discs are pale pink, clear boundaries, narrowed arteries, dilated veins. Diagnosis: OI Angiopathy of the retina. Myoclonic hyperkinesis was observed in neurological status. Meningeal and focal signs were not found. Chvostek’s and Trousseau’s signs were absent. For the purpose of differential diagnosis between metabolic and gas alkalosis, a study was made to determine the content of bicarbonate levels in blood serum, the level of which, as is known, increases with metabolic alkalosis. An increase in serum bicarbonate levels above normal was found, indicating metabolic alkalosis. The content of ionized calcium in the patient’s blood was within the normal range. Serum potassium and magnesium levels were also within the normal range, which made it possible to exclude the presence of Bartter and Gitelman syndrome. In order to conduct pathogenetic and symptomatic therapy, the patient was prescribed acetylsalicylic acid at a dosage of 75 mg 1 time per day and clonazepam at the standard dosage, which led to a pH shift to 7.45 after 1 month and a significant reduction in the severity of myoclonic hyperkineses. Conclusions: Conclusions: 166 1. As a result of our analysis of the available scientific data, a significant relationship has been revealed between hyperkinetic syndromes and changes in the acid-base state. 2. The provoking effect of alkalosis on the occurrence and severity of hyperkinetic disorders was revealed. 2. The provoking effect of alkalosis on the occurrence and severity of hyperkinetic disorders was revealed. 3. H + HCO3 <----> H2CO3 <----> CO2 + H2O In connection with the above, we consider it expedient to study acid-base balance in patients with hyperkinetic syndromes and syndrome of increased neuromuscular excitability in the outpatient setting and in hospital conditions at the initial diagnosis, and we also recommend the study of indicators of acid-base balance in patients with hyperkinetic syndromes and syndrome of increased neuromuscular excitability, already having neurological diagnoses, if such a study has not been performed previously. 4. Correction of the acid-base state in the treatment of patients with hyperkinetic syndromes and the syndrome of increased neuromuscular excitability contributes to a greater effectiveness of the therapy given than the symptomatic treatment of hyperkineses only. 4. Correction of the acid-base state in the treatment of patients with hyperkinetic syndromes and the syndrome of increased neuromuscular excitability contributes to a greater effectiveness of the therapy given than the symptomatic treatment of hyperkineses only. References: Available from: https://www.ncbi.nlm.nih.gov/books/NBK482117/ 10. Brinkman JE, Sharma S. Physiology, Alkalosis, Respiratory. [Updated 2018 Jan 27]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2018 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK482117/ 11. John H. Galla. Metabolic Alkalosis J Am Soc Nephrol 11: 369–375, 2000 12. Zhang S, Sun P, Sun Z, Zhang J, Zhou J, Gu Y. Cortical GABAergic neurons are more severely impaired by alkalosis than acidosis. BMC Neurology. 2013;13:192. doi:10.1186/1471-2377-13-192. 12. Zhang S, Sun P, Sun Z, Zhang J, Zhou J, Gu Y. Cortical GABAergic neurons are more severely impaired by alkalosis than acidosis. BMC Neurology. 2013;13:192. doi:10.1186/1471-2377-13-192. 13. Bennett JC. In: Cecil Textbook of Medicine. Bennett JC, Plum F, editor. Philadelphia: W. B. Saunder Co; 1996. 13. Bennett JC. In: Cecil Textbook of Medicine. Bennett JC, Plum F, editor. Philadelphia: W. B. Saunder Co; 1996. 14. Acid–base Disturbances. DuBose TD. In: Harrison’s Principles of Internal Medicine. Fauci AS, editor. New York: McGraw-Hill; 1997. 14. Acid–base Disturbances. DuBose TD. In: Harrison’s Principles of Internal Medicine. Fauci AS, editor. New York: McGraw-Hill; 1997. 15. Acidosis and Alkalosis. Okuda T, Kurokawa K, Papadakis MA. In: Current Medical Diagnosis & Treatment. Tierney LM, McPhee SJ, Papadakis MA, editor. Stamford: Appleton & Lange; 1998. Fluid and Electrolyte Disorders; pp. 824–849. 16. Nowak TJ, Handford AG. In: Fluid and Electrolyte Imbalances., in Pathophysiology. Nowak TJ, Handford AG, editor. Boston: Martin J. Lange; 2004. pp. 422– 445. 17. Fraley DS, Adler S, Bruns F. Life-threatening metabolic alkalosis in a comatose patient. South Med J 72: 1024–1025, 1979 18. Adachi M, Ikemoto Y, Kubo K, Takuma C. Seizure-like movements during induction of anaesthesia with sevoflurane. Br J Anaesth 68: 214–215, 1992. 19. Victor M. The role of hypomagnesemia and respiratory alkalosis in the genesis of alcohol-withdrawal symptoms. Ann N Y Acad Sci 215:235– 248, 1973 20. P Simons, I Nadra, P G McNally Metabolic alkalosis and myoclonus Postgrad Med J 2003;79:414–415 21. Okada K, Kono N, Kobayashi S, et al. Metabolic alkalosis and myoclonus from antacid ingestion. Internal Medicine 1996;35:515–6 22. Ishiguchi T, Mikita N, Iwata T, Nakata H, Sato H, Higashimoto Y, Fujimoto H, Yoshida S, Itoh H. Myoclonus and Metabolic Alkalosis from Licorice in Antacid Internal Medicine 43: 59–62, 2004 23. Kaye M, Somerville PJ, Lowe G, et al. Hypocalcaemic tetany and metabolic alkalosis in a dialysis patient: an unusual event. Am J Kidney Dis 1997;30:440–4. 24. Westerblad H, Allen DG. References: 1. Vercueil, L. Myoclonus and movement disorders. Neurophysiol. Clin. 2006, 36, 327–331. 1. Vercueil, L. Myoclonus and movement disorders. Neurophysiol. Clin. 2006, 36, 327–331. 2. Abdo, W.F.; van de Warrenburg, B.P.; Burn, D.J.; Quinn, N.P.; Bloem, B.R. The clinical approach to movement disorders. Nat. Rev. Neurol. 2010, 6, 29–37 2. Abdo, W.F.; van de Warrenburg, B.P.; Burn, D.J.; Quinn, N.P.; Bloem, B.R. The clinical approach to movement disorders. Nat. Rev. Neurol. 2010, 6, 29–37 3. Caviness JN. Myoclonus. Mayo Clin Proc 1996; 71(7): 679-88. 3. Caviness JN. Myoclonus. Mayo Clin Proc 1996; 71(7): 679-88. 4. Richard K. Disorders of movement and Imbalance. Harrison’s, Principles of Internal Medicine, 16th Ed ; McGraw-Hill Medical Publication Division 2005; 139. 5. Allen CMC, Lueck CJ, Dennis M. Neurological Disease. Davidson’s Principles & practice of medicine; 20th Ed. Churchill Livingstone 2005;1182. 5. Allen CMC, Lueck CJ, Dennis M. Neurological Disease. Davidson’s Principles & practice of medicine; 20th Ed. Churchill Livingstone 2005;1182. 6. Charles RA. Neurological Disease. Kumar and Clark: Clinical Medicine: 6th Ed; Elervier Saunders 2005; 1232 6. Charles RA. Neurological Disease. Kumar and Clark: Clinical Medicine: 6th Ed; Elervier Saunders 2005; 1232 7. Patofiziologiya : uchebnik [Pathophysiology]: v 2 t. / pod red. V.V. Novitskogo, Ye.D. Gol'dberga, O.I. Urazovoy. - 4-ye izd., pererab. i dop. - GEOTAR-Media, 2009. - T. 1. - 848 s. : il. (in Russian) 7. Patofiziologiya : uchebnik [Pathophysiology]: v 2 t. / pod red. V.V. Novitskogo, Ye.D. Gol'dberga, O.I. Urazovoy. - 4-ye izd., pererab. i dop. - GEOTAR-Media, 2009. - T. 1. - 848 s. : il. (in Russian) 8. Patofiziologiya: uchebnik [Pathophysiology]: v 2 t. / pod red. V.V. Novitskogo, Ye.D. Gol'dberga, O.I. Urazovoy. - 4-ye izd., pererab. i dop. - GEOTAR-Media, 2009. - T. 2. - 640 s. : il. (in Russian) 8. Patofiziologiya: uchebnik [Pathophysiology]: v 2 t. / pod red. V.V. Novitskogo, Ye.D. Gol'dberga, O.I. Urazovoy. - 4-ye izd., pererab. i dop. - GEOTAR-Media, 2009. - T. 2. - 640 s. : il. (in Russian) 9. Litvitskiy, P.F. Patofiziologiya [Pathophysiology]. V 2 t. - 5-ye izd., pererab. i dop. – M.: GEOTAR-Media, 2016. – 624s. (in Russian) 9. Litvitskiy, P.F. Patofiziologiya [Pathophysiology]. V 2 t. - 5-ye izd., pererab. i dop. – M.: GEOTAR-Media, 2016. – 624s. (in Russian) 167 10. Brinkman JE, Sharma S. Physiology, Alkalosis, Respiratory. [Updated 2018 Jan 27]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2018 Jan-. 34. Swagata Tripathy. Extreme metabolic alkalosis in intensive care. Indian J Crit Care Med. 2009 Oct-Dec; 13(4): 217–220. References: Mechanism underlying changes of tetanic [Ca2+]i and force in skeletal muscle. Acta Physiol Scand 1996;156:407–16. 168 25. Ryland P Byrd . Respiratory Alkalosis. Apr 24, 2014. https://emedicine.medscape.com/article/301680-differential 26. DuBose TD, Jr. Acidosis and Alkalosis. Kasper DL, Braunwald E, Fauci AS, Hauser Sl, Longo DL, Jameson JL,eds. Harrison's Principles of Internal Medicine. 16th. New York, NY: McGraw-Hill; 2005. 270-1. 27. Gardner WN. The pathophysiology of hyperventilation disorders. Chest. 1996 Feb. 109(2):516-34. 28. Effros RM, Wesson JA. Acid-Base Balance. Mason RJ, Broaddus VC, Murray JF, Nadel JA, eds. Murray and Nadel's Textbook of Respiratory Medicine. 4th ed. Philadelphia, PA: Elsevier Saunders; 2005. Vol 1: 192-93. 29. Adrogue HJ, Madias NE: Management of life-threatening acidbase disorders. N Engl J Med 338: 107–111, 1998 30. Phillipson EA, Duffin J. Hypoventilation and Hyperventilation Syndromes. Mason RJ, Broaddus VC, Murray JF, Nadel JA, eds. Murray and Nadel's Textbook of Respiratory Medicine. 4th ed. Philadelphia, PA: Elsevier Saunders; 2005. Vol 2: 2069-70, 2080-84. 31. Goldman A. Clinical tetany by forced respiration. JAMA. 1922. 78:1193-95. 32. Haldane JS, Poulton EP. The effects of want of oxygen on respiration. J Physiol. 1908. 37:390-407. 33. Anderson LE, Henrich WL Alkalemia-associated morbidity and mortality in medical and surgical patients. South Med J. 1987 Jun; 80(6):729-33. 34. Swagata Tripathy. Extreme metabolic alkalosis in intensive care. Indian J Crit Care Med. 2009 Oct-Dec; 13(4): 217–220. 169
https://openalex.org/W2094783210
https://europepmc.org/articles/pmc3804047?pdf=render
English
null
Management of Crown Root Fracture by Interdisciplinary Approach
Case Reports in Dentistry/Case reports in dentistry
2,013
cc-by
2,098
Hindawi Publishing Corporation Case Reports in Dentistry Volume 2013, Article ID 138659, 4 pages http://dx.doi.org/10.1155/2013/138659 Hindawi Publishing Corporation Case Reports in Dentistry Volume 2013, Article ID 138659, 4 pages http://dx.doi.org/10.1155/2013/138659 Hindawi Publishing Corporation Case Reports in Dentistry Volume 2013, Article ID 138659, 4 pages http://dx.doi.org/10.1155/2013/138659 K. Radhakrishnan Nair,1 Anoop N. Das,1 Manoj C. Kuriakose,1 and Nandakumar Krishnankutty2 1 Department of Conservative Dentistry and Endodontics, Azeezia College of Dental Sciences and Research, Kollam 691537, India 2 Department of Periodontics, Azeezia College of Dental Sciences and Research, Kollam 691537, India Correspondence should be addressed to K. Radhakrishnan Nair; radhnair@yahoo.com Received 7 July 2013; Accepted 31 August 2013 Academic Editors: G. K. Kulkarni, P. Lopez Jornet, L. J. Oesterle, and E. F. Wright Copyright © 2013 K. Radhakrishnan Nair et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Fracture of tooth after trauma is distressing to a person because of the discomfort and pain due to pulpal injury. Crown root fractures of anterior teeth cause concomitant periodontal injury and there will be concern about appearance, and aesthetics. Management of pulpal and periodontal tissue relieves pain and restoration of tooth form regains patients confidence. Restoration of fractured tooth will be accepted readily if it is minimally invasive, less expensive, and aesthetically acceptable. Reattachment is an option for restoration of anterior teeth compared to other artificial replacements because of its appearance as natural. This method is favourable when the fractured fragment is intact and available. Utilization of pulp space for retention of fragment is achieved by the insertion of a dentine bonding post. This case report describes a case of tooth reattachment after trauma in which the pulp space is utilized to bond a fiber-reinforced post for retention after periodontal tissue management. 1. Introduction A conservative method for management of the crown root fracture when the intact fragment is available is the reattachment technique. It is a method which has been tried long before [5]. This method is gaining wide acceptance because of its several advantages over artificial replacements like composite resin or full coverage restorations. It can offer long lasting aesthetics and is reasonably a simple procedure [6, 7].f Tooth fracture can occur at any age due to trauma. Sports accidents and fights are more common among teenagers and automobile accidents are seen in all age groups. Impact of trauma on tooth varies from mild enamel chipping to complex crown root fractures. Aesthetic and functional implications of tooth fracture depend upon its severity and age of the patient. About 5% of all dental traumas are found to be associated with crown root fractures [1]. Severe pain arising from crown root fractures can be either due to pulpal exposure or due to concomitant periodontal injury or both. It is cost effective and can be completed in less chair side time. When endodontic therapy is indicated, the pulp space available after obturation can be used for retention of the fragment by using posts bonded to root canal. This case report describes an interdisciplinary approach to the management of two complicated crown root fractures of maxillary central incisors after an automobile accident. Clinical considerations for the management of crown root fractures include extent and pattern of fracture, restorability of remaining tooth, availability of fractured fragment, and damage to the attachment apparatus [2, 3]. Extension of fracture subgingivally raises concern about biological width violation. Periodontal flap surgery combined with osteoplasty procedures is indicated for deep subgingival fractures to satisfy the requirement of biological width [4]. 2. Case Report A forty-year-old male patient was referred to the Depart- ment of Conservative Dentistry and Endodontics with 2 Case Reports in Dentistry Figure 1: Preoperative view. the complaint of broken front teeth. He had a history of road traffic accident with sustained hand and facial injuries and had fracture of two maxillary central incisors. He went to a nearby hospital immediately because of pain for medical aid and took some medications. He had no relevant medical history and reported to the department next day due to elevation of pain in the area. Extra oral examination revealed lacerations with swelling of upper lips. Intraorally lacerations were present on buccal mucosa. Gingiva appeared to be erythematous in the upper front region and there was bleeding on probing. Both the upper central incisors were fractured with pulpal exposure. The horizontal fracture line was on the middle of the labial surface extending obliquely to the subgingival area on the palatal side (Figure 1). The incisal fragments were mobile and during talking, pain increased due to mobility. An IOPA radiograph showed the crown of 11 and 21 with fracture line extending subgingivally and the root and periapical area was found to be normal. This was diagnosed as a case of complicated crown root fracture with irreversible pulpitis.ht Figure 1: Preoperative view. Figure 2: Gingivectomy of 11 and 21. p p p The incisal fragments were removed after local anesthesia as a single piece and kept in normal saline immediately. The various options to restore the teeth were explained to the patient. After listening, the patient expressed the willingness to reattach the broken part. Single visit endodontics was done and root canal was obturated with gutta-percha using AH Plus as the sealer. Gingivectomy was done for 11 and 21 to bring the fracture line supragingival (Figure 2). The patient reported to the clinic after one day for the reattachment pro- cedure. Root canal preparation for the post was done sequen- tially using the Tenax Fiber Trans drill (Coltene Whaledent). Corresponding fiber reinforced composite post was selected (Tenax Fiber Trans-Coltene Whaledent) to check the fit and occlusal clearance. The occlusal end of the post was shortened with a diamond disc to the desired length. The prepared root canal was conditioned using self-etching non rinse conditioner (ParaBond-Coltene Whaledent). Fixing of the post in the root canal was done using dual cure luting material (ParaCore-Coltene Whaledent). 2. Case Report To facilitate polymerization, curing LED light (Woodpecker) was applied through the tip of the post into the root canal for 20 seconds. About 2 mm of the post was visible beyond the incisal margin after fixing (Figure 3). Figure 2: Gingivectomy of 11 and 21. Figure 3: After fiber post fixation. Figure 3: After fiber post fixation. g A small recess was prepared in the pulp chamber of fractured segment of 11 and 21 and was tried against the remaining crown portion with the post for approximation. The opposite surface of the fractured crown was then etched with 37% phosphoric acid and the fragment was luted in the correct position using dual cure resin (ParaCore-Coltene Whaledent) with slight pressure. Excess of the material was removed using a sharp instrument from the edges and was light cured for 20 seconds for faster polymerization. A bevel was prepared on the margins of the approximating surfaces of 11 and 21 on the labial side and the margins were sealed with nanocomposite (Brilliant NG-Coltene Whaledent). Polishing of the surface was done with polishing disks which ensured an aesthetic blending of the margins (Figure 4).t with satisfactory aesthetics. Periodontal status was good with 1 mm pocket. Gingival tissues had a normal texture with a normal contouring (Figure 5). Intraoral periapical radiograph showed intact tooth structure with intact lamina dura (Figure 6). References [1] J. D. Andreason, F. M. Andreason, and L. Andersson, Textbook and Colour Atlas of Traumatic Injuries to Teeth, Blackwell, Oxford, UK, 4th edition, 2007. [2] S. Olsburgh, T. Jacoby, and I. Krejci, “Crown fractures in the permanent dentition: pulpal and restorative considerations,” Dental Traumatology, vol. 18, no. 3, pp. 103–115, 2002. Figure 5: Postoperative view after one year. Figure 6: Postoperative radiograph after one year. [3] A. Reis, C. Francci, A. D. Loguercio, M. R. Carrilho, and L. E. R. Filho, “Re-attachment of anterior fractured teeth: fracture strength using different techniques,” Operative Dentistry, vol. 26, no. 3, pp. 287–294, 2001. [4] L. N. Baratieri, S. Monteiro, C. A. Cardoso, and M. A. C. Andrada, “Coronal fracture with invasion of the biologic width: a case report,” Quintessence International, vol. 24, no. 2, pp. 85– 91, 1993. [5] A. Chosack and E. Eidelman, “Rehabilitating of a fractured incisor using the patient’s natural crown: a case report,” Journal of Dentistry for Children, vol. 71, pp. 19–21, 1994. [6] A. Reis, A. D. Loguercio, A. Kraul, and E. Matson, “Reat- tachment of fractured teeth: a review of literature regarding techniques and materials,” Operative Dentistry, vol. 29, no. 2, pp. 226–233, 2004. [7] E. A. V. Maia, L. N. Baratieri, M. A. C. de Andrada, S. Monteiro Jr., and E. M. de Ara´ujo Jr., “Tooth fragment reattachment: fun- damentals of the technique and two case reports,” Quintessence International, vol. 34, no. 2, pp. 99–107, 2003. Figure 6: Postoperative radiograph after one year. [8] B. Farik, E. C. Munksgaard, and J. O. Andreasen, “Impact strength of teeth restored by fragment-bonding,” Dental Trau- matology, vol. 16, no. 4, pp. 151–153, 2000. advantages over conventional methods of restoration. It retains the translucency of natural tooth and its abrasive resistance is better than composites.f [9] B. Farik and E. C. Munksgaard, “Fracture strength of intact and fragment-bonded teeth at various velocities of the applied force,” European Journal of Oral Sciences, vol. 107, no. 1, pp. 70– 73, 1999. It is less time consuming and is cost effective. Several studies have shown that the impact strength of reattached tooth is not significantly different from that of intact natural tooth [8, 9].t [10] B. Akkayan and T. G¨ulmez, “Resistance to fracture of endodon- tically treated teeth restored with different post systems,” Jour- nal of Prosthetic Dentistry, vol. 87, no. 4, pp. 3. Discussion Fracture of anterior teeth after trauma adversely affects the emotional well-being of a person in addition to the discom- fort and pain. Complexity and extension of fracture along with the associated injury to the tooth influence the restora- tive design. Reattachment of the tooth is an option when the broken fragment is intact and available. It has several Patient was recalled after six months and one year. On examination, 11 and 21 were found to be asymptomatic 3 Case Reports in Dentistry Case Reports in Dentistry Case Reports in Dentistry Figure 4: Immediate postoperative view. utilized to attach a post for auxiliary retention. Metallic and nonmetallic posts are available with different properties. Fiber posts which have the modulus of elasticity similar to that of root dentin are used here to bond with the root and are preferred to metal posts because of less stress concentration on the root and there is low incidence of root fracture [10]. There is less tooth preparation with a fiber post compared to cast post; thus, the tooth is conserved more. Failures of post and core occur by debonding of the core and due to root fracture [11]. Available clinical evaluation for longevity of reattachment shows medium-term prospects for this technique [12, 13]. A seven-year follow-up of crown reattachment showed mild discoloration of crown without any evidence of fracture [14]. Long-term followup is required to assess the longitivity of reattachment technique. Improvement in adhesive technol- ogy may provide a long-lasting bonding of the fragments to improve the prospects of this technique in future. Figure 4: Immediate postoperative view. Figure 5: Postoperative view after one year. References 431–437, 2002.f Reattachment procedure is often multidisciplinary dic- tated by the extension of tooth fracture and injury to the attachment apparatus. This case was a subgingival frac- ture and gingivectomy was done to bring the fracture line supragingival. Pulp space after root canal treatment was [11] E. Asmussen, A. Peutzfeldt, and T. Heitmann, “Stiffness, elastic limit, and strength of newer types of endodontic posts,” Journal of Dentistry, vol. 27, no. 4, pp. 275–278, 1999. [12] I. A. ¨Oz, M. C. Haytac¸, and M. S. Toroˇglu, “Multidisciplinary approach to the rehabilitation of a crown-root fracture with Case Reports in Dentistry 4 original fragment for immediate esthetics: a case report with 4- year follow-up,” Dental Traumatology, vol. 22, no. 1, pp. 48–52, 2006. [13] C. L. Capp, M. I. Rodo, R. Tawaki, G. M. Castanho, M. A. Carmago, and A. A. deClara, “Reattachment of rehydrated dental fragment using two techniques,” Dental Traumatology, vol. 25, pp. 95–99, 2009. [14] J. C. M. de Castro, W. R. Poi, D. Pedrini, A. R. F. Tiveron, D. A. Brandini, and M. A. M. de Castro, “Multidisciplinary approach for the treatment of a complicated crown-root fracture in a young patient: a case report,” Quintessence International, vol. 42, no. 9, pp. 729–734, 2011.
https://openalex.org/W4313443674
https://hal-univ-bourgogne.archives-ouvertes.fr/hal-03822534/document
English
null
Multimodal approach for the prediction of atrial fibrillation detected after stroke: SAFAS study
Archives of cardiovascular diseases. Supplements
2,023
cc-by
8,251
To cite this version: Lucie Garnier, Gauthier Duloquin, Alexandre Meloux, Karim Benali, Audrey Sagnard, et al.. Mul- timodal Approach for the Prediction of Atrial Fibrillation Detected After Stroke: SAFAS Study. Frontiers in Cardiovascular Medicine, 2022, 9, pp.949213. ￿10.3389/fcvm.2022.949213￿. ￿hal-03822534￿ Multimodal Approach for the Prediction of Atrial Fibrillation Detected After Stroke: SAFAS Study Lucie Garnier, Gauthier Duloquin, Alexandre Meloux, Karim Benali, Audrey Sagnard, Mathilde Graber, Geoffrey Dogon, Romain Didier, Thibaut Pommier, Catherine Vergely, et al. Multimodal Approach for the Prediction of Atrial Fibrillation Detected After Stroke: SAFAS Study Lucie Garnier1,2, Gauthier Duloquin1,2, Alexandre Meloux2, Karim Benali3, Audrey Sagnard3, Mathilde Graber1,2, Geoffrey Dogon2, Romain Didier2,3, Thibaut Pommier2,3, Catherine Vergely2, Yannick Béjot1,2 and Charles Guenancia2,3* 1 Department of Neurology, University Hospital, Dijon, France, 2 Pathophysiology and Epidemiology of Cerebro-Cardiovascular Diseases (EA 7460), Faculty of Health Sciences, Université de Bourgogne, Université de Bourgogne Franche-Comté, Dijon, France, 3 Department of Cardiology, University Hospital, Dijon, France Background: Intensive screening for atrial fibrillation (AF) has led to a better recognition of this cause in stroke patients. However, it is currently debated whether AF Detected After Stroke (AFDAS) has the same pathophysiology and embolic risk as prior-to-stroke AF. We thus aimed to systematically approach AFDAS using a multimodal approach combining clinical, imaging, biological and electrocardiographic markers. Edited by: Hung-Fat Tse, The University of Hong Kong, Hong Kong SAR, China Methods: Patients without previously known AF admitted to the Dijon University Hospital (France) stroke unit for acute ischemic stroke were prospectively enrolled. The primary endpoint was the presence of AFDAS at 6 months, diagnosed through admission ECG, continuous electrocardiographic monitoring, long-term external Holter during the hospital stay, or implantable cardiac monitor if clinically indicated after discharge. Reviewed by: Alexander Carpenter, University of Bristol, United Kingdom Mei Qiu, Reviewed by: Alexander Carpenter, University of Bristol, United Kingdom Mei Qiu, Shenzhen Longhua District Central Hospital, China Shenzhen Longhua District Central Hospital, China *Correspondence: Charles Guenancia charles.guenancia@gmail.com Results: Of the 240 included patients, 77 (32%) developed AFDAS. Compared with sinus rhythm patients, those developing AFDAS were older, more often women and less often active smokers. AFDAS patients had higher blood levels of NT-proBNP, osteoprotegerin, galectin-3, GDF-15 and ST2, as well as increased left atrial indexed volume and lower left ventricular ejection fraction. After multivariable analysis, galectin-3 ≧9 ng/ml [OR 3.10; 95% CI (1.03–9.254), p = 0.042], NT-proBNP ≧290 pg/ml [OR 3.950; 95% CI (1.754–8.892, p = 0.001], OPG ≥887 pg/ml [OR 2.338; 95% CI (1.015– 5.620), p = 0.046) and LAVI ≥33.5 ml/m2 [OR 2.982; 95% CI (1.342–6.625), p = 0.007] were independently associated with AFDAS. Specialty section: This article was submitted to Cardiac Rhythmology, a section of the journal Frontiers in Cardiovascular Medicine Received: 20 May 2022 Accepted: 20 June 2022 Received: 20 May 2022 Accepted: 20 June 2022 Published: 13 July 2022 HAL Id: hal-03822534 https://u-bourgogne.hal.science/hal-03822534v1 Submitted on 20 Oct 2022 L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, whether they are pub- lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. ORIGINAL RESEARCH published: 13 July 2022 doi: 10.3389/fcvm.2022.949213 ORIGINAL RESEARCH published: 13 July 2022 doi: 10.3389/fcvm.2022.949213 Keywords: atrial fibrillation, stroke, atrial cardiopathy, biomarkers, Holter, echocardiography Keywords: atrial fibrillation, stroke, atrial cardiopathy, biomarkers, Holter, echocardiography INTRODUCTION were excluded because long-term external Holter screening could not be done. Atrial fibrillation (AF) is one of the most common causes of ischemic stroke. It is associated with a fivefold increased risk of stroke and accounts for more than one in five strokes (1, 2). However, many studies showed that even with continuous electrocardiographic monitoring (CEM), many AF episodes are not clinically diagnosed (3). It has been estimated that one third of patients with cryptogenic stroke may in fact have undetected asymptomatic AF (1, 4). In this setting, implantable cardiac monitors (ICM) are now commonly implanted in patients with cryptogenic stroke, in accordance with CRYSTAL-AF trial results (1). However, only one third of patients with ICM will eventually develop new-onset AF (5). Systematic anticoagulation in cryptogenic stroke patients failed to demonstrate a clinical benefit as compared to aspirin in the NAVIGATE-ESUS or RESPECT-ESUS trials (6, 7), supporting the emergence of a new concept known as AFDAS (Atrial Fibrillation Detected After Stroke and Transient Ischemic Attack). Although some studies tend to show that AFDAS has a different pathophysiology and embolic risk than AF, little is known about the underlying mechanisms of this condition (8). Oral consent was obtained from all patients or their representative. This study was validated by a national ethics committee and conducted in accordance with the ethical principles of the Declaration of Helsinki and the recommendations of Good Clinical Practice (CPP Sud Méditerranée I n◦2018-A00345-50, clinical trials NCT03570060). Heart Rate Monitoring - the modulator: ANS, assessed by heart rate variabi - the triggers, as assessed by inflammatory mediators (CRP, ST2, GDF-15), the burden of premature atrial contractions and the presence of left ventricular dysfunction or acute myocardial injury. Patients received continuous and sequential cardiac monitoring which included ECG at admission, CEM in the stroke unit, and long-term Holter ECG (SpiderFlash, Microport, France) during the entire stay in the neurology department. The SpiderFlash Holter allows the recording of arrhythmic episodes regardless of their duration, capturing the events and documenting them by means of ECG samples. The device was programmed to record every rhythmic event for 7 days, regardless of the duration of the supraventricular arrhythmia. An experienced cardiologist (CG) who was blinded to the patient’s clinical data performed the Holter ECG analysis. If the diagnosis was uncertain, a second cardiologist, blinded to the first results, also analyzed the records. There was no discordance between the two analyses. Citation: Garnier L, Duloquin G, Meloux A, Benali K, Sagnard A, Graber M, Dogon G, Didier R, Pommier T, Vergely C, Béjot Y and Guenancia C (2022) Multimodal Approach for the Prediction of Atrial Fibrillation Detected After Stroke: SAFAS Study. Front. Cardiovasc. Med. 9:949213. doi: 10.3389/fcvm.2022.949213 Garnier L, Duloquin G, Meloux A, Benali K, Sagnard A, Graber M, Dogon G, Didier R, Pommier T, Vergely C, Béjot Y and Guenancia C (2022) Multimodal Approach for the Prediction of Atrial Fibrillation Detected After Stroke: SAFAS Study. Front. Cardiovasc. Med. 9:949213. doi: 10.3389/fcvm.2022.949213 Conclusion: A multimodal approach combining imaging, electrocardiography and original biological markers resulted in good predictive models for AFDAS. These results also suggest that AFDAS is probably related to an underlying atrial cardiopathy. Clinical Trial Registration: [www.ClinicalTrials.gov], identifier [NCT03570060]. Keywords: atrial fibrillation, stroke, atrial cardiopathy, biomarkers, Holter, echocardiography July 2022 | Volume 9 | Article 949213 1 Frontiers in Cardiovascular Medicine | www.frontiersin.org New Markers of AF Detected After Stroke Garnier et al. Biomarker Assay Biological samples were stored in the stroke unit refrigerator at 3◦C for a maximum of 24 h. Tubes were centrifuged at 3,500 rpm for 5 min at 4◦C to recover the serum, and then aliquoted. The aliquots were then immediately transferred to the freezer (−80◦C) until use. The assay was performed on thawed serum. The Enzyme-Linked Immuno-Sorbent Assay technique was used for galectin-3 (DGAL30, R&D systems, Minneapolis, United States) and the multiplex technique for osteoprotegerin (OPG), ST2, and GDF15 (R&D systems, Minneapolis, United States) following the manufacturer’s recommendations. Three components are involved in the development of all types of arrhythmia (9): the substrate, the modulator [the autonomic nervous system (ANS)] and the triggering factor(s). We thus aimed to approach systematically AFDAS pathophysiology in stroke patients using a multimodal approach combining clinical, imaging, biological and electrocardiographic markers: - the atrial substrate (i.e. atrial cardiopathy), as assessed by left atrial dimensions, and by blood biomarkers of fibrosis (galectin-3, osteoprotegerin) and of cardiac remodeling (NT-pro-BNP), Clinical, Biological and Imaging Data During Hospital Stay Within 48 h of admission, we collected patients’ demographic and clinical data. Upon admission to the stroke unit, patients underwent additional examinations, including brain and intra/extra-cranial vessel imaging, electrocardiogram (ECG), echocardiography [transthoracic with bubble test for patent foramen ovale (PFO) ± transesophageal] and a standard biological workup supplemented by sampling for biomarkers. Frontiers in Cardiovascular Medicine | www.frontiersin.org RESULTS ECG: P-wave duration (ms) and p-wave terminal force (PTF) [amplitude of the terminal negative portion of the P-wave in V1 x the duration of the terminal negative portion of the P-wave in V1)]. Statistical Analysis We performed ROC curves analyses to assess the relationship and the best cut-offvalues between AF and the biological, imaging and electrocardiographic markers of atrial cardiopathy. After ROC curve, the best predictive value for AF was 887 pg/ml for OPG, 18,350 pg/ml for ST2, 1,320 pg/ml for GDF-15, 11 ng/ml for galectin-3, 290 pg/ml for NT-pro-BNP, 33.5 ml/m2 for LAVI, 38 for SDNN and 11 for pNN50. Continuous data were expressed as medians (25th–75th percentile) and dichotomous data as numbers (percentages). A Mann-Whitney test or Student’s t-test was used to compare continuous data, and the Chi-square test or Fisher’s test was used for dichotomous data. The optimal threshold to discriminate AF from the continuous data of interest was obtained with the receiver-operating characteristic (ROC) curve with the best sensitivity and specificity according to the Youden index. Variables entered into the multivariate model were chosen according to their univariate relationship with an inclusion and exclusion cut-offat 5%. Two multivariate backward stepwise logistic regression models were used, one to predict all recorded AFDAS from admission to 6-month follow-up (model 1) and the second one focusing on AFDAS diagnosed after the stay in the stroke unit, including HRV variables (model 2). A p-value < 0.05 was considered statistically significant. Analyses were performed using SPSS software (26.0, IBM Inc., United States). During the 6 months of follow-up, there were significantly more deaths in the AFDAS group than in the sinus rhythm group [10 (13%) vs. 3 (2%), p = 0.001]. There was also a trend toward more frequent bleeding in AF patients at 6 months. There was no difference in the recurrence rate of stroke or TIA. Follow-Up We collected the length of stay in each unit, where the patient was discharged to after hospitalization, any intercurrent hospital events, etiological diagnosis according to the TOAST classification (13) as well as the NIHSS score, modified Rankin score and discharge treatments. AFDAS patients also had higher blood levels of NT-pro- BNP (p < 0.001) (Table 2). Plasma levels of OPG (p < 0.001), galectin-3 (p = 0.026), GDF 15 (p = 0.001) and ST2 (p = 0.027) were higher in AFDAS patients. Patients with AFDAS more frequently had LA dilatation as assessed by increased left atrial indexed volume (LAVI) (p < 0.001), and had lower LVEF (p = 0.030) (Table 3). Patients were contacted by phone at 3 months and seen for an outpatient visit at 6 months. Data was collected regarding vital status, current treatments, cardiovascular events (ischemic stroke, myocardial infarction, heart failure hospitalization, atrial fibrillation or atrial flutter), vascular or hemorrhagic recurrence, and any hemorrhagic event. In patients without evidence of AF at admission or during CEM in the stroke unit, (N = 158), pNN50 (p < 0.001) and SDNN (p = 0.007), both calculated on the first day of the CEM, were higher in patients who subsequently developed AFDAS. AFDAS was also associated with higher burden of premature atrial contractions (PAC), (p < 0.001), non-sustained supraventricular tachycardias (p < 0.001) and premature ventricular contractions (PVC) (p < 0.001) on CEM. Patients implanted with an ICM had a follow-up cardiology consultation at 6 weeks and then every 3 months. If the patient was equipped with a remote monitoring system, the ICM data were analyzed every week and the patient was contacted if a rhythm disorder was detected. Decisions regarding the treatment of AF episodes were made by the attending physician. Study Design and Population We conducted a prospective study (SAFAS: Stepwise screening for silent Atrial Fibrillation After Stroke) in adult patients hospitalized between March 31, 2018, and January 18, 2020, in the stroke unit of the Dijon Bourgogne University Hospital. We included patients with ischemic stroke according to the World Health Organization criteria: a clinical syndrome characterized by a focal loss of cerebral or ocular function, of sudden onset, without obvious etiology at initial management and confirmed by imaging. If no arrhythmia was detected and no etiology found for the ischemic stroke after the diagnostic workup, an ICM (REVEAL XT or Linq, Medtronic, United States) was indicated, as recommended by international guidelines in case of cryptogenic stroke (10). ICM detects AF by analyzing the irregularity and inconsistency of successive R-R intervals within a minimum time frame (5). Atrial fibrillation was defined according to European guidelines (11). Atrial flutter patients were included in the AF group. Patients with a history of AF or atrial flutter, as well as those with a pacemaker or an implantable cardioverter defibrillator with an atrial lead (not eligible for the stepwise screening strategy), adults under guardianship, pregnant or breastfeeding women, and those who refused to participate in the study were excluded. Patients who were not under the primary care area of the Dijon University Hospital (transfer to a department outside the University Hospital after acute management of stroke) July 2022 | Volume 9 | Article 949213 2 New Markers of AF Detected After Stroke Garnier et al. Atrial Fibrillation Detected After Stroke Associated Factors Among the 1,796 patients admitted to the stroke unit between March 2018 and January 2020, 265 were eligible for inclusion, and 240 were finally analyzed (Figure 1). During the 6 months of follow-up, 77 patients (32%) developed AFDAS and 163 patients (64%) maintained sinus rhythm. Clinical characteristics and complementary exam results are presented in Tables 1–4. Heart rate variability (HRV) on CEM tracings were measured as previously described (12): average pNN50 (marker of parasympathetic nervous system activation) corresponding to the proportion derived by dividing NN50 [the number of interval differences of successive sinus node depolarization (NN) intervals greater than 50 ms] by the total number of NN intervals, and SDNN [the standard deviation of all intervals between adjacent QRS complexes resulting from sinus node depolarization (NN)], on the first day of recording of the stroke unit CEM. Only sequences with normal QRS characteristics during 24 h (sinus rhythm) were analyzed for HRV study. If AF was diagnosed on the ECG at entry or on the first day of monitoring, ANS parameters were not analyzed. y Compared with sinus rhythm patients, the patients who developed AFDAS were older (p < 0.001), were more often women, were less often active smokers (p = 0.001), had a higher NIHSS score on admission (p = 0.001), and were likely to have a premorbid mRS ≥2 (p < 0.001). The CHA2DS2VASc score at admission (calculated without including the current episode of stroke) was also higher in the AFDAS group (p < 0.001), and AFDAS patients were more likely to have undergone acute revascularization therapy by thrombolysis and/or mechanical thrombectomy (p = 0.002) (Table 1). On brain CT-scan imaging, the stroke location of patients with AFDAS more frequently involved the superficial middle cerebral artery territory (p < 0.001), especially when the insula was involved (p = 0.003). Predictive Models for Atrial Fibrillation Detected After Stroke Two multivariate models were performed, one to predict all recorded AFDAS (model 1) and another model (model Frontiers in Cardiovascular Medicine | www.frontiersin.org Frontiers in Cardiovascular Medicine | www.frontiersin.org July 2022 | Volume 9 | Article 949213 3 New Markers of AF Detected After Stroke Garnier et al. FIGURE 1 | Flow chart of the SAFAS study. FIGURE 1 | Flow chart of the SAFAS study. TABLE 1 | Clinical characteristics of patients [n (%) or median (IQR)]. | p [ ( ) ( )] SR [n = 163 (68%)] AFDAS [n = 77 (32%)] p Risk factors Age, years 65.79 (54.90–74.96) 81.27 (71.68–85.85) <0.001 Age ≥77 years 31.00 (19.00) 49.00 (63.30) <0.001 Female sex 68.00 (41.70) 45.00 (58.40) 0.015 BMI, kg/m2 26.26 (23.75–29.19) 26.44 (23.10–29.79) 0.778 Obesity (BMI > 30 kg/m2) 35.00 (21.90) 16.00 (22.9) 0.869 High blood pressure 86.00 (52.80) 50.00 (64.90) 0.076 Hypercholesterolemia 49.00 (30.10) 21.00 (27.30) 0.657 Diabetes 30.00 (18.40) 16.00 (20.80) 0.663 Active smoking 41.00 (25.20) 6.00 (7.90) 0.001 Active or withdrawn alcohol consumption 13.00 (8.00) 5.00 (6.70) 0.799 Obstructive sleep apnea 14.00 (8.60) 9.00 (11.80) 0.483 Previous kidney failure 2.00 (1.20) 3.00 (3.90) 0.331 Previous cancer 26.00 (16.00) 10.00 (13.00) 0.548 Recent infection (<1 month) 6.00 (3.70) 6.00 (7.90) 0.206 Cardiovascular history Stroke or TIA 25.00 (15.50) 13.00 (17.10) 0.757 Peripheral artery disease 2,00 (1.20) 1,00 (1.30) 1,000 Heart failure 5.00 (3.10) 5.00 (6.60) 0.296 Cardiac valve disease 7,00 (4.30) 6.00 (7.90) 0.357 Clinical data at admission Systolic pressure, mmHg 155.00 (138.25–175.00) 161.00 (139.50–178.50) 0.910 Diastolic pressure, mmHg 87.00 (75.25–95.00) 81.00 (70.00–92.50) 0.061 Blood glucose, g/l 1.17 (1.02–1.37) 1.11 (0.99–1.35) 0.288 NIHSS score 4.00 (1.00–7.00) 6.00 (3.00–12.75) 0.001 Premorbid mRS ≥2 20.00 (12.70) 28.00 (37.30) <0.001 CHA2DS2VASc score 2.00 (1.00–4.00) 4.00 (2.00–4.00) <0.001 Acute revascularization therapy 54.00 (33.10) 42.00 (54.50) 0.002 IQR, interquartile range; SR, sinus rhythm; BMI, Body mass index; TIA, transient ischemic attack; NIHSS, National Institute of Health Stroke Scale; mRS, modified Rankin scale. SR [n = 163 (68%)] IQR, interquartile range; SR, sinus rhythm; BMI, Body mass index; TIA, transient ischemic attack; NIHSS, National Institute of Health Stroke Scale; mRS, modified Rankin IQR, interquartile range; SR, sinus rhythm; BMI, Body mass index; TIA, transient ischemic attack; NIHSS, National Institute of Health Stroke Scale; mRS, modified Rankin scale. Predictive Models for Atrial Fibrillation Detected After Stroke In model 1, among the variables significantly associated with AF in bivariate analysis, galectin-3 ≥9 ng/ml [OR 3.10; 95% CI (1.03–9.254), p = 0.042], NT-pro-BNP ≥290 pg/ml [OR 2) focusing on AFDAS diagnosed after patients’ stay in the stroke unit (> 48 h usually), including HRV variables (Table 4). July 2022 | Volume 9 | Article 949213 Frontiers in Cardiovascular Medicine | www.frontiersin.org 4 New Markers of AF Detected After Stroke Garnier et al. TABLE 2 | Biological, imaging and electrocardiographic characteristics of patients at admission [n (%) or median (IQR)]. Sinus rhythm A TABLE 2 | Biological, imaging and electrocardiographic characteristics of patients at admission [n (%) or median (IQR)]. Predictive Models for Atrial Fibrillation Detected After Stroke IQR, interquartile range; SR, sinus rhythm; AF, Atrial fibrillation CRP, C-reactive protein; NT-pro-BNP, N-Terminal pro-brain natriuretic peptide; ST2, Suppression of Tumorigenicity 2; GDF15, growth differentiation factor 15; cerebral anterior artery; MCA, middle cerebral artery; ECG, electrocardiogram; LBB, left bundle branch block; RBB, right bundle branch block; PTF, p-wave terminal force. 3.950; 95% CI (1.754–8.892, p = 0.001], OPG ≥887 pg/ml [OR 2.338; 95% CI (1.015–5.620), p = 0.046] and LAVI ≥33.5 ml/m2 [OR 2.982; 95% CI (1.342–6.625), p = 0.007] were independently associated with AFDAS. CI (0.818–0.940)]. For model 1, the positive predictive value was 63% and the negative predictive value was 80%. For model 2, the positive predictive value was 71% and the negative predictive value was 83%. In model 2, including HRV variables, galectin-3 ≥9 ng/ml [OR 6.587; 95% CI (1.529–28.376) p = 0.011], NT-Pro-BNP ≥290 pg/ml [OR 4.676; 95% CI (1.655–13.210), p = 0.004], OPG ≥887 pg/ml [OR 3.350; 95% CI (1.060–10.590) p = 0.040] and pNN50 ≥11 [OR 8.260; 95% CI (2.795–24.406), p < 0.001] were independently associated with AFDAS after discharge from the stroke unit. Predictive Models for Atrial Fibrillation Detected After Stroke Sinus rhythm AFDAS p Biological data CRP, mg/mL 2.90 (2.90–5.00) 2.95 (2.90–6.10) 0.269 Creatinine, µmol/l 72.00 (62.00–85.00) 74.00 (63.00–88.00) 0.476 Troponin, µg/l 0.02 (0.02–0.02) 0.02 (0.02–0.04) 0.417 NT-Pro-BNP, pg/ml 129.00 (60.00–331.00) 843.00 (303.25–2069.50) <0.001 NT-pro-BNP ≥290 pg/ml 43.00 (28.70) 54.00 (77.10) <0.001 TSH, µg/ml 1.32 (0.76–2.07) 1.16 (0.78–1.88) 0.772 Galectin 3, ng/ml 11.03 (8.24–14.33) 12.45 (10.03–16.29) 0.026 Galectin 3 ≥9 ng/ml 106.00 (68.40) 68.00 (88.30) 0.001 ST2, pg/ml 17147.90 (12932.97–26956.95) 21.202.68 (14708.56–31836.67) 0.027 ST2 ≥18,350 pg/ml 63.00 (39.90) 48.00 (63.20) 0.001 Osteoprotegerin, pg/ml 905.60 (757.07–1280.77) 1139.30 (912.92–1598.76) <0.001 Osteoprotegerin ≥887 pg/ml 80.00 (50.60) 60.00 (77.90) <0.001 GDF15, pg/ml 1573.64 (1003.80–2270.86) 2142.63 (1363.14-2931.12) 0.001 GDF15 ≥1,320 pg/ml 94.00 (59.90) 61.00 (79.20) 0.003 Imaging data Multi-territory stroke 19.00 (11.70) 6.00 (7.80) 0.360 Vertebro-basilar stroke 58.00 (35.60) 18.00 (23.40) 0.058 Bilateral stroke 15.00 (9.20) 6.00 (7.80) 0.718 Insular stroke 27.00 (16.60) 26.00 (33.80) 0.003 Cerebellar stroke 18.00 (11.00) 7.00 (9.10) 0.821 Thalamic stroke 9.00 (5.50) 5.00 (6.50) 0.773 Anterior choroidal stroke 10.00 (6.10) 0.00 (0.00) 0.033 CAA stroke 6.00 (3.70) 4.00 (5.20) 0.730 MCA superficial stroke 73.00 (44.80) 53.00 (68.80) <0.001 MCA deep stroke 43.00 (26.40) 22.00 (28.60) 0.721 ECG data LBB (n = 180) 3.00 (2.40) 2.00 (3.50) 0.685 RBB (n = 180) 7.00 (5.70) 5.00 (8.80) 0.523 P-wave duration max, ms (n = 111) 100.00 (100.00–120.00) 120.00 (100.00–120.00) 0.570 PTF, mV.ms 4.00 (4.00–8.00) 6.00 (4.00–8.00) 0.407 PTF ≥4 mv.ms (n = 111) 41.00 (47.10) 17.00 (70.80) 0.063 PTF ≥5 mv.ms (n = 111) 38.00 (46.30) 20.00 (69.00) 0.051 PR duration, ms 168.00 (148.00–191.00) 172.00 (154.00–196.00) 0.214 QRS duration, ms 90,00 (82.50–98.00) 92.00 (82.00–108.00) 0.385 Corrected QTc duration, ms 423.00 (409.00–444.00) 435.00 (413.50–449.50) 0.189 IQR, interquartile range; SR, sinus rhythm; AF, Atrial fibrillation CRP, C-reactive protein; NT-pro-BNP, N-Terminal pro-brain natriuretic peptide; ST2, Suppression of Tumorigenicity 2; GDF15, growth differentiation factor 15; cerebral anterior artery; MCA, middle cerebral artery; ECG, electrocardiogram; LBB, left bundle branch block; RBB, right bundle branch block; PTF, p-wave terminal force. IQR, interquartile range; SR, sinus rhythm; AF, Atrial fibrillation CRP, C-reactive protein; NT-pro-BNP, N-Terminal pro-brain natriuretic peptide; ST2, Suppression of Tumorigenicity 2; GDF15, growth differentiation factor 15; cerebral anterior artery; MCA, middle cerebral artery; ECG, electrocardiogram; LBB, left bundle branch block; RBB, right bundle branch block; PTF, p-wave terminal force. DISCUSSION Univariate Multivariate Variable OR 95% CI p OR 95% CI P Model 1 (n = 240) Age ≥77 yo 7.45 4.06–13.67 <0.001 Female sex 1.96 1.13–3.45 0.016 Active smoking 0.26 0.10–0.63 0.003 Insular stroke 2.57 1.37–4.81 0.003 LAVI ≥33.5 ml/m2 5.20 2.62–10.32 <0.001 2.982 1.34–6.63 0.007 PFO 0.16 0.04–0.68 0.013 NT-pro-BNP ≥290 pg/ml 8.39 4.34–16.26 <0.001 3.950 1.75–8.89 0.001 Galectin-3 ≥9 ng/ml 3.49 1.61–7.57 0.002 3.101 1.04–9.25 0.042 ST2 ≥18,350 pg/ml 2.59 1.47–4.55 0.001 OPG ≥887 pg/ml 3.44 1.85–6.41 <0.001 2.338 1.02–5.62 0.046 GDF15 ≥1,320 pg/ml 2.56 1.35–4.83 0.004 Model 2 (n = 158) Age ≥77 yo 6.07 2.81–13.11 <0.001 LAVI ≥33.5 ml/m2 4.37 1.88–10.17 0.001 NT-pro-BNP ≥290 pg/ml 6.83 3.05–15.32 <0.001 4.676 1.66–13.21 0.004 Galectin-3 ≥9 ng/ml 7.04 2.04–24.25 0.002 6.587 1.53–28.38 0.011 ST2 ≥18,350 pg/ml 2.56 1.23–5.36 0.012 OPG ≥887 pg/ml 2.99 1.34–6.67 0.007 3.350 1.06–10.59 0.040 GDF15 ≥1,320 pg/ml 2.72 1.19–6.23 0.018 PNN50 ≥11 5.75 2.67–12.39 <0.001 8.260 2.80–24.41 <0.001 SDNN ≥38* 4.34 2.04–9.33 <0.001 AF, atrial fibrillation; CI, confidence interval; HR, hazard ratio.*Not included in the multivariate analysis due to collinearity with PNN50 (R = -0.74). • Several clinical and imaging parameters, novel blood biomarkers (such as galectin-3 and osteoprotegerin), and association between atrial cardiopathy markers and the new concept of AFDAS. TABLE 3 | cardiac work-up [n (%) or median (IQR)]. Sinus rhythm AFDAS p CEM data (n = 224) 199.00 (88.84) 25.00 (11.16) PAC, day 1 1.00 (0.00–4.75) 9.00 (2.00–26.50) <0.001 NSSVT, day 1 0.00 (0.00–1.00) 3.00 (1.00–9.00) <0.001 NSVT, day 1 3.50 (1.00–7.00) 11.00 (2.50–23.00) <0.001 pNN50 (n = 158) 2.00 (0.00–9.55) 14.11 (4.13–22.39) <0.001 Sinus variability (SDNN) (n = 158) 29.08 (21.19–46.77) 41.67 (27.13–72.50) 0.002 pNN50 ≥11 (n = 158) 25.00 (21.40) 25.00 (61.00) <0.001 SDNN ≥38 (n = 158) 36.00 (30.80) 27.00 (65.90) <0.001 Echocardiographic data LA diameter, cm 3.60 (3.20–3.93) 4.10 (3.60–4.40) <0.001 LA surface, cm2 17.70 (15.05–22.20) 20.80 (17.03–25.87) 0.001 LA volume, mm3 45,00 (35.30–61.25) 60.90 (42.00–81.60) <0.001 LAVI, ml/m2 25.84 (19.45–33.25) 35.80 (25.87–43.86) <0.001 LAVI ≥33.5 ml/m2 (n = 188) 32.00 (23.50) 32.00 (61.50) <0.001 LVEF,% 60.00 (56.00–66.15) 59.90 (55.00–63.50) 0.030 PFO 26.00 (16.50) 2.00 (3.00) 0.004 SR, sinus rhythm; AF, atrial fibrillation; PAC, premature atrial contractions; NSSVT, non-sustained supra ventricular tachycardia; NSVT, non-sustained ventricular tachycardia; LAVI, left atrial indexed volume; LVEF, left ventricular ejection fraction; PFO, patent foramen ovale. DISCUSSION The main results of this prospective study in ischemic stroke patients without previous AF or an obvious etiology at admission are as follows (Figure 3): • Our sequential, continuous and early rhythm monitoring approach detected AFDAS in 32% of patients at 6 months of follow-up. The ROC curves of these models illustrate their predictive performance for AFDAS in our cohort (Figure 2) [model 1: AUC 0.829, 95% CI (0.764–0.894); model 2: AUC 0.879, 95% July 2022 | Volume 9 | Article 949213 Frontiers in Cardiovascular Medicine | www.frontiersin.org 5 New Markers of AF Detected After Stroke Garnier et al. TABLE 3 | cardiac work-up [n (%) or median (IQR)]. Sinus rhythm AFDAS p CEM data (n = 224) 199.00 (88.84) 25.00 (11.16) PAC, day 1 1.00 (0.00–4.75) 9.00 (2.00–26.50) <0.001 NSSVT, day 1 0.00 (0.00–1.00) 3.00 (1.00–9.00) <0.001 NSVT, day 1 3.50 (1.00–7.00) 11.00 (2.50–23.00) <0.001 pNN50 (n = 158) 2.00 (0.00–9.55) 14.11 (4.13–22.39) <0.001 Sinus variability (SDNN) (n = 158) 29.08 (21.19–46.77) 41.67 (27.13–72.50) 0.002 pNN50 ≥11 (n = 158) 25.00 (21.40) 25.00 (61.00) <0.001 SDNN ≥38 (n = 158) 36.00 (30.80) 27.00 (65.90) <0.001 Echocardiographic data LA diameter, cm 3.60 (3.20–3.93) 4.10 (3.60–4.40) <0.001 LA surface, cm2 17.70 (15.05–22.20) 20.80 (17.03–25.87) 0.001 LA volume, mm3 45,00 (35.30–61.25) 60.90 (42.00–81.60) <0.001 LAVI, ml/m2 25.84 (19.45–33.25) 35.80 (25.87–43.86) <0.001 LAVI ≥33.5 ml/m2 (n = 188) 32.00 (23.50) 32.00 (61.50) <0.001 LVEF,% 60.00 (56.00–66.15) 59.90 (55.00–63.50) 0.030 PFO 26.00 (16.50) 2.00 (3.00) 0.004 SR, sinus rhythm; AF, atrial fibrillation; PAC, premature atrial contractions; NSSVT, non-sustained supra ventricular tachycardia; NSVT, non-sustained ventricular tachycardia; LAVI, left atrial indexed volume; LVEF, left ventricular ejection fraction; PFO, patent foramen ovale. TABLE 4 | Univariate and multivariate analysis of AFDAS predictors. • Several clinical and imaging parameters, novel blood biomarkers (such as galectin-3 and osteoprotegerin), and electrocardiographic parameters such as PNN50 were associated with AFDAS. We can thus confirm the LVEF,% 60.00 (56.00–66.15) 59.90 (55.00–63.50) 0.030 PFO 26.00 (16.50) 2.00 (3.00) 0.004 SR, sinus rhythm; AF, atrial fibrillation; PAC, premature atrial contractions; NSSVT, non-sustained supra ventricular tachycardia; NSVT, non-sustained ventricular tachycardia; LAVI, left atrial indexed volume; LVEF, left ventricular ejection fraction; PFO, patent foramen ovale. TABLE 4 | Univariate and multivariate analysis of AFDAS predictors. Univariate Multivariate Variable OR 95% CI p OR 95% CI P Model 1 (n = 240) Age ≥77 yo 7.45 4.06–13.67 <0.001 Female sex 1.96 1.13–3.45 0.016 Active smoking 0.26 0.10–0.63 0.003 Insular stroke 2.57 1.37–4.81 0.003 LAVI ≥33.5 ml/m2 5.20 2.62–10.32 <0.001 2.982 1.34–6.63 0.007 DISCUSSION Model 1 associates galectin-3 = 9 ng/ml; NT-pro-BNP ≥290 pg/ml; OPG ≥887 pg/ml and LAVI ≥33.5 ml/m2 for all AFDAS prediction (n = 240). Model 2 associates galectin-3 ≥9 ng/ml; NT-Pro-BNP ≥290 pg/ml; OPG ≥887 pg/ml and pNN50 ≥11 for AFDAS occurring after a stay in the stroke unit: AUC, area under the curve. OPG, osteoprotegerin. FIGURE 2 | ROC curve for models 1 and 2. Model 1 associates galectin-3 = 9 ng/ml; NT-pro-BNP ≥290 pg/ml; OPG ≥887 pg/ml and LAVI ≥33.5 ml/m2 for all AFDAS prediction (n = 240). Model 2 associates galectin-3 ≥9 ng/ml; NT-Pro-BNP ≥290 pg/ml; OPG ≥887 pg/ml and pNN50 ≥11 for AFDAS occurring after a stay in the stroke unit: AUC area under the curve OPG osteoprotegerin FIGURE 2 | ROC curve for models 1 and 2. Model 1 associates galectin-3 = 9 ng/ml; NT-pro-BNP ≥290 pg/ml; OPG ≥887 pg/ml and LAVI ≥33.5 ml/m2 for all AFDAS prediction (n = 240). Model 2 associates galectin-3 ≥9 ng/ml; NT-Pro-BNP ≥290 pg/ml; OPG ≥887 pg/ml and pNN50 ≥11 for AFDAS occurring after a stay in the stroke unit: AUC, area under the curve. OPG, osteoprotegerin. stay in the stroke unit: AUC, area under the curve. OPG, osteoprotegerin. FIGURE 3 | SAFAS study main results. FIGURE 3 | SAFAS study main results. stasis, endothelial damage and thrombus formation (15). This hypothesis is supported by recent data suggesting that atrial fibrosis increases thromboembolic risk regardless of atrial rhythm: this is the concept of atrial cardiopathy (16, 17). In our study, we found a strong association between LA remodeling and AFDAS, as assessed by LA dilatation (increased LA diameter, surface and LAVI). The optimal threshold of LAVI associated with the risk of AF occurrence was 33.5 ml/m2. This threshold corresponds to the threshold of mild dilatation on echocardiography (18) and is close to the Carrazco study cut-off(30 ml/m2) (19), but lower than models of AFDAS. These models could help to better stratify the screening strategy for AFDAS, especially for the use of ICM after hospitalization for stroke. DISCUSSION SR, sinus rhythm; AF, atrial fibrillation; PAC, premature atrial contractions; NSSVT, non-sustained supra ventricular tachycardia; NSVT, non-sustained ventricular tachycardia; LAVI, left atrial indexed volume; LVEF, left ventricular ejection fraction; PFO, patent foramen ovale. TABLE 4 | Univariate and multivariate analysis of AFDAS predictors. Univariate Multivariate Variable OR 95% CI p OR 95% CI P Model 1 (n = 240) Age ≥77 yo 7.45 4.06–13.67 <0.001 Female sex 1.96 1.13–3.45 0.016 Active smoking 0.26 0.10–0.63 0.003 Insular stroke 2.57 1.37–4.81 0.003 LAVI ≥33.5 ml/m2 5.20 2.62–10.32 <0.001 2.982 1.34–6.63 0.007 PFO 0.16 0.04–0.68 0.013 NT-pro-BNP ≥290 pg/ml 8.39 4.34–16.26 <0.001 3.950 1.75–8.89 0.001 Galectin-3 ≥9 ng/ml 3.49 1.61–7.57 0.002 3.101 1.04–9.25 0.042 ST2 ≥18,350 pg/ml 2.59 1.47–4.55 0.001 OPG ≥887 pg/ml 3.44 1.85–6.41 <0.001 2.338 1.02–5.62 0.046 GDF15 ≥1,320 pg/ml 2.56 1.35–4.83 0.004 Model 2 (n = 158) Age ≥77 yo 6.07 2.81–13.11 <0.001 LAVI ≥33.5 ml/m2 4.37 1.88–10.17 0.001 NT-pro-BNP ≥290 pg/ml 6.83 3.05–15.32 <0.001 4.676 1.66–13.21 0.004 Galectin-3 ≥9 ng/ml 7.04 2.04–24.25 0.002 6.587 1.53–28.38 0.011 ST2 ≥18,350 pg/ml 2.56 1.23–5.36 0.012 OPG ≥887 pg/ml 2.99 1.34–6.67 0.007 3.350 1.06–10.59 0.040 GDF15 ≥1,320 pg/ml 2.72 1.19–6.23 0.018 PNN50 ≥11 5.75 2.67–12.39 <0.001 8.260 2.80–24.41 <0.001 SDNN ≥38* 4.34 2.04–9.33 <0.001 AF, atrial fibrillation; CI, confidence interval; HR, hazard ratio.*Not included in the multivariate analysis due to collinearity with PNN50 (R = -0.74). TABLE 4 | Univariate and multivariate analysis of AFDAS predictors. • Several clinical and imaging parameters, novel blood biomarkers (such as galectin-3 and osteoprotegerin), and electrocardiographic parameters such as PNN50 were associated with AFDAS. We can thus confirm the • The use of a multimodal approach based on the 3 key determinants of arrhythmia resulted in highly predictive Frontiers in Cardiovascular Medicine | www.frontiersin.org July 2022 | Volume 9 | Article 949213 6 New Markers of AF Detected After Stroke Garnier et al. FIGURE 2 | ROC curve for models 1 and 2. Model 1 associates galectin-3 = 9 ng/ml; NT-pro-BNP ≥290 pg/ml; OPG ≥887 pg/ml and LAVI ≥33.5 ml/m2 for all AFDAS prediction (n = 240). Model 2 associates galectin-3 ≥9 ng/ml; NT-Pro-BNP ≥290 pg/ml; OPG ≥887 pg/ml and pNN50 ≥11 for AFDAS occurring after a stay in the stroke unit: AUC, area under the curve. OPG, osteoprotegerin. FIGURE 3 | SAFAS study main results. FIGURE 2 | ROC curve for models 1 and 2. Left Atrial Substrate: Morphological, Biological and Electrical Assessment Several studies have demonstrated the association between LA dilatation and AF. Some have even suggested that increased LAVI could be associated with stroke independently of AF onset (14). LA enlargement may promote blood July 2022 | Volume 9 | Article 949213 Frontiers in Cardiovascular Medicine | www.frontiersin.org New Markers of AF Detected After Stroke Garnier et al. findings suggest that this biomarker could be of great clinical value for targeted AF screening given its strong and independent predictive value of AFDAS in our study. the threshold of 44–45 ml/m2 found in some studies that have shown this association in the context of cryptogenic stroke (20). In addition to LA dimensions, several research teams have suggested the use of electrocardiographic markers of atrial cardiopathy such as PTFV1. This parameter has been associated with increased risk of AF after adjustment for other markers of atrial cardiopathy such as LA dimensions and NT-pro- BNP (21, 22). PTFV1 may be a marker of atrial changes such as fibrosis and elevated filling pressure that are not fully revealed by echocardiographic or serum biomarker assessments. In our study, in a sample of patients (n = 111) in whom these measurements were feasible, we did not find a significant association between these ECG markers and AFDAS, contrary to LA dilatation or biomarkers of atrial substrate. This could be related to the population size or to the inclusion of more powerful markers of atrial cardiopathy in the prediction models. Taken together, these results suggest that these biomarkers could be of great clinical value for targeted AF screening and atrial cardiopathy diagnosis, given their strong and independent predictive value of AFDAS. Modulator The ANS acts as a modulator of AF onset through the modulation of atrial electro-physiological properties. Adami et al. demonstrated that patients with R-R interval variability after ischemic stroke had an increased risk of AF (33). In our second multivariate model, pNN50 ≧11 was associated with an eightfold higher risk of AFDAS in patients without previous evidence of AF on ECG at admission or during CEM in the stroke unit. This analysis is particularly interesting because these data can be automatically extracted from CEM data in the stroke unit, making it feasible in routine clinical practice. We suggest that, if confirmed in further studies, temporal HRV measurements could be included in the cardiac work-up after stroke, similar to LAVI or NT-pro-BNP levels. Moreover, three biomarkers of atrial cardiopathy were associated with AFDAS in our study: - In both predictive models, galectin-3, a biomarker of fibrosis (23), was independently associated with AFDAS. Galectin-3 blood levels are increased in AF patients, are independently correlated with LA volume (24) and predict AF onset and recurrence after AF ablation (25). Although the exact pathophysiological mechanisms by which galectin-3 promotes AF are still unclear, it appears to play an important role in fibrotic processes. It could therefore be a potential marker of interest for atrial cardiopathy. Atrial Fibrillation Triggers Inflammation plays a role in the initiation, persistence and recurrence of AF. In our study, several inflammatory mediators know (ST2, GDF15, CRP) were associated with the occurrence of AF in bivariate analysis but did not remain significantly associated with AF in our predictive models. This suggests that the pathophysiology of AFDAS is more likely to involve chronic remodeling (atrial cardiopathy) rather that acute triggers such as inflammation or acute myocardial dysfunction. p y - Osteoprotegerin is a protein is expressed in endothelial and smooth muscle cells and is involved in the regulation of the inflammatory response and remodeling of the extracellular matrix (26). Its association with AF was only recently suggested. Cao et al. showed that AF patients had higher atrial gene expression of the OPG/RANK/RANKL axis and a higher RANKL/OPG ratio, particularly in paroxysmal AF (27). This expression was also well correlated with markers of atrial remodeling including markers of apoptosis, pro-inflammatory factors, and the matrix metalloproteinase/tissue inhibitors of metalloproteinases system regulating extracellular matrix degradation (28). OPG could therefore be associated with AF through atrial remodeling processes, and could be suggested as a new marker of atrial cardiopathy. p y - Osteoprotegerin is a protein is expressed in endothelial and smooth muscle cells and is involved in the regulation of the inflammatory response and remodeling of the extracellular matrix (26). Its association with AF was only recently suggested. Cao et al. showed that AF patients had higher atrial gene expression of the OPG/RANK/RANKL axis and a higher RANKL/OPG ratio, particularly in paroxysmal AF (27). This expression was also well correlated with markers of atrial remodeling including markers of apoptosis, pro-inflammatory factors, and the matrix metalloproteinase/tissue inhibitors of metalloproteinases system regulating extracellular matrix degradation (28). OPG could therefore be associated with AF through atrial remodeling processes, and could be suggested as a new marker of atrial cardiopathy. Finally, the prognostic significance of AFDAS remains uncertain. Further studies are needed to assess the benefit of anticoagulants in AFDAS on the risk of stroke recurrence. In this regard, the ARCADIA trial, which aims to compare an anticoagulant strategy with apixaban vs. aspirin in patients with cerebral infarction of undetermined etiology with recognized markers of atrial cardiopathy (P-wave terminal force > 5,000 µV.ms in V1, serum NT-pro-BNP > 250 pg/mL, or left atrial diameter index ≥3 cm/m2) (31) should add significant knowledge to this clinical issue. REFERENCES 10. Kernan WN, Ovbiagele B, Black HR, Bravata DM, Chimowitz MI, Ezekowitz MD, et al. Guidelines for the prevention of stroke in patients with stroke and transient ischemic attack: a guideline for healthcare professionals from the American heart association/American stroke association. Stroke. (2014) 45:2160–236. doi: 10.1161/STR.0000000000000024 1. Sanna T, Diener HC, Passman RS, Di Lazzaro V, Bernstein RA, Morillo CA, et al. Cryptogenic stroke and underlying atrial fibrillation. N Engl J Med. (2014) 370:2478–86. doi: 10.1056/NEJMoa1313600 1. Sanna T, Diener HC, Passman RS, Di Lazzaro V, Bernstein RA, Morillo CA, et al. Cryptogenic stroke and underlying atrial fibrillation. N Engl J Med. (2014) 370:2478–86. doi: 10.1056/NEJMoa1313600 11. Kirchhof P, Benussi S, Kotecha D, Ahlsson A, Atar D, Casadei B, et al. 2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS. Europace. (2016) 18:1609–78. doi: 10.5603/KP.2016.0172 2. Sposato LA, Cipriano LE, Saposnik G, Vargas ER, Riccio PM, Hachinski V. Diagnosis of atrial fibrillation after stroke and transient ischaemic attack: a systematic review and meta-analysis. Lancet Neurol. (2015) 14:377–87. doi: 10.1016/S1474-4422(15)70027-X 12. Sagnard A, Guenancia C, Mouhat B, Maza M, Fichot M, Moreau D, et al. Involvement of autonomic nervous system in new-onset atrial fibrillation during acute myocardial infarction. J Clin Med. (2020) 9:1481. doi: 10.3390/ jcm9051481 3. Dilaveris PE, Kennedy HL. Silent atrial fibrillation: epidemiology, diagnosis, and clinical impact. Clin Cardiol. (2017) 40:413–8. doi: 10.1002/clc. 22667 13. Adams HP, Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, et al. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in acute stroke treatment. Stroke. (1993) 24:35–41. doi: 10.1161/01.STR.24.1.35 4. Hart RG, Diener HC, Coutts SB, Easton JD, Granger CB, O’Donnell MJ, et al. Embolic strokes of undetermined source: the case for a new clinical construct. Lancet Neurol. (2014) 13:429–38. doi: 10.1016/S1474-4422(13)70 310-7 5. Brachmann J, Morillo CA, Sanna T, Di Lazzaro V, Diener HC, Bernstein RA, et al. Uncovering atrial fibrillation beyond short-term monitoring in cryptogenic stroke patients: three-year results from the cryptogenic stroke and underlying atrial fibrillation trial. Circ Arrhythm Electrophysiol. (2016) 9:e003333. doi: 10.1161/CIRCEP.115.003333 14. Hamatani Y, Ogawa H, Takabayashi K, Yamashita Y, Takagi D, Esato M, et al. Left atrial enlargement is an independent predictor of stroke and systemic embolism in patients with non-valvular atrial fibrillation. Sci Rep. (2016) 6:31042. doi: 10.1038/srep31042 15. AUTHOR CONTRIBUTIONS LG, GDu, AS, AM, GDo, RD, MG, YB, CV, and CG: substantial contributions to the conception, design of the work, the acquisition, analysis, and interpretation of data for the work. KB, TP, CV, YB, and CG: drafting the work and revising it critically for important intellectual content. All authors have substantially approved its submission to the journal and are prepared to take public responsibility for the work. LG, GDu, AS, AM, GDo, RD, MG, YB, CV, and CG: substantial contributions to the conception, design of the work, the acquisition, analysis, and interpretation of data for the work. KB, q y p TP, CV, YB, and CG: drafting the work and revising it critically for important intellectual content. All authors have substantially approved its submission to the journal and are prepared to take public responsibility for the work. FUNDING The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. The SAFAS study was funded by an unrestricted grant from Microport CRM. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication. ACKNOWLEDGMENTS The studies involving human participants were reviewed and approved by the CPP Sud Méditerranée I n◦2018-A00345-50. Written informed consent for participation was not required for We thank Suzanne Rankin for English revision of the manuscript. CONCLUSION this study in accordance with the national legislation and the institutional requirements. In order to improve the cost-effectiveness of long-term external Holter recordings and ICM implantations, it is essential to target the patients most at risk of AFDAS, who should benefit from a prolonged rhythm screening strategy. Our multimodal approach combining imaging, electrocardiography and original biological markers of atrial cardiopathy resulted in good predictive models for AFDAS at 6-month follow-up. These results also suggest that AFDAS is probably not be an epiphenomenon related to the acute stroke but rather related to underlying atrial cardiopathy. Further studies are needed to evaluate the embolic risk and the indication for anticoagulation in these AFDAS patients. In order to improve the cost-effectiveness of long-term external Holter recordings and ICM implantations, it is essential to target the patients most at risk of AFDAS, who should benefit from a prolonged rhythm screening strategy. Our multimodal approach combining imaging, electrocardiography and original biological markers of atrial cardiopathy resulted in good predictive models for AFDAS at 6-month follow-up. These results also suggest that AFDAS is probably not be an epiphenomenon related to the acute stroke but rather related to underlying atrial cardiopathy. Further studies are needed to evaluate the embolic risk and the indication for anticoagulation in these AFDAS patients. Limitations - NT-proBNP levels are increased in stroke patients diagnosed with AF, and are reported to be higher in case of cardioembolic stroke (29, 30). In our study, NT-proBNP values over 290 pg/ml were significantly associated with the occurrence of AFDAS in both models, a threshold comparable to another study on cryptogenic stroke (30). Moreover, NT-proBNP levels > 250 pg/ml were used as a surrogate of atrial cardiopathy in the ARCADIA study (31). Finally, in the TARGET-AF study of stroke patients whose AF was detected by early and prolonged heart rate recordings, Suissa et al. suggested that low BNP levels could virtually exclude the risk of secondary AF (32). These Our study has certain limitations. First, it was a monocentric study on a population based exclusively at the Dijon University Hospital, and we excluded patients referred by other hospitals, which limited the number of inclusions. In addition, some patients with ischemic stroke were not admitted to the stroke unit and therefore could not be included. The study follow-up was limited to 6 months in the study design, in contrast to some studies that completed up to 3 years of monitoring (1, 19). This could have led to an underestimation of AF incidence and to false negatives in the sinus rhythm group. However, in the study by Carrazco et al. 80% of AF cases were diagnosed within the first 6 months of screening (19). - NT-proBNP levels are increased in stroke patients diagnosed with AF, and are reported to be higher in case of cardioembolic stroke (29, 30). In our study, NT-proBNP values over 290 pg/ml were significantly associated with the occurrence of AFDAS in both models, a threshold comparable to another study on cryptogenic stroke (30). Moreover, NT-proBNP levels > 250 pg/ml were used as a surrogate of atrial cardiopathy in the ARCADIA study (31). Finally, in the TARGET-AF study of stroke patients whose AF was detected by early and prolonged heart rate recordings, Suissa et al. suggested that low BNP levels could virtually exclude the risk of secondary AF (32). These July 2022 | Volume 9 | Article 949213 Frontiers in Cardiovascular Medicine | www.frontiersin.org 8 New Markers of AF Detected After Stroke Garnier et al. REFERENCES Left atrial volume: important risk marker of incident atrial fibrillation in 1655 older men and women. Mayo Clin Proc. (2001) 76:467–75. doi: 10.4065/76.5.467 31. Kamel H, Longstreth W, Tirschwell DL, Kronmal RA, Broderick JP, Palesch YY, et al. The atrial cardiopathy and antithrombotic drugs in prevention after cryptogenic stroke randomized trial: rationale and methods. Int J Stroke. (2019) 14:207–14. doi: 10.1177/1747493018799981 21. Kamel H, Bartz TM, Elkind MSV, Okin PM, Thacker EL, Patton KK, et al. Atrial cardiopathy and the risk of ischemic stroke in the CHS (Cardiovascular Health Study). Stroke. (2018) 49:980–6. doi: 10.1161/STROKEAHA.117. 020059 32. Suissa L, Bresch S, Lachaud S, Mahagne MH. Brain natriuretic peptide: a relevant marker to rule out delayed atrial fibrillation in stroke patient. J Stroke Cerebrovasc Dis. (2013) 22:e103–10. doi: 10.1016/j.jstrokecerebrovasdis.2012. 08.010 22. Kamel H, Hunter M, Moon YP, Yaghi S, Cheung K, Di Tullio MR, et al. Electrocardiographic left atrial abnormality and risk of stroke: Northern Manhattan study. Stroke. (2015) 46:3208–12. doi: 10.1161/STROKEAHA.115. 009989 33. Adami A, Gentile C, Hepp T, Molon G, Gigli GL, Valente M, et al. Electrocardiographic RR interval dynamic analysis to identify acute stroke patients at high risk for atrial fibrillation episodes during stroke unit admission. Transl Stroke Res. (2018) 10:273–8. doi: 10.1007/s12975-018- 0645-8 23. Yu L, Ruifrok WPT, Meissner M, Bos EM, van Goor H, Sanjabi B, et al. Genetic and pharmacological inhibition of galectin-3 prevents cardiac remodeling by interfering with myocardial fibrogenesis. Circ Heart Fail. (2013) 6:107–17. doi: 10.1161/CIRCHEARTFAILURE.112.971168 24. Gurses KM, Yalcin MU, Kocyigit D, Canpinar H, Evranos B, Yorgun H, et al. Effects of Persistent atrial fibrillation on serum galectin-3 levels. Am J Cardiol. (2015) 115:647–51. doi: 10.1016/j.amjcard.2014.12.021 Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. 25. Gong M, Cheung A, Wang Q, Li G, Goudis CA, Bazoukis G, et al. Galectin-3 and risk of atrial fibrillation: a systematic review and meta-analysis. J Clin Lab Anal. (2020) 34:e23104. doi: 10.1002/jcla.23104 Publisher’s Note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. 26. REFERENCES Anaissie J, Monlezun D, Seelochan A, Siegler JE, Chavez-Keatts M, Tiu J, et al. Left atrial enlargement on transthoracic echocardiography predicts left atrial thrombus on transesophageal echocardiography in ischemic stroke patients. BioMed Res Int. (2016) 2016:7194676. doi: 10.1155/2016/7194676 6. Diener HC, Sacco RL, Easton JD, Granger CB, Bernstein RA, Uchiyama S, et al. Dabigatran for prevention of stroke after embolic stroke of undetermined source. N Engl J Med. (2019) 380:1906–17. doi: 10.1056/NEJMoa18 13959 16. Calenda BW, Fuster V, Halperin JL, Granger CB. Stroke risk assessment in atrial fibrillation: risk factors and markers of atrial myopathy. Nat Rev Cardiol. (2016) 13:549–59. doi: 10.1038/nrcardio.2016.106 7. Hart RG, Sharma M, Mundl H, Kasner SE, Bangdiwala SI, Berkowitz SD, et al. Rivaroxaban for stroke prevention after embolic stroke of undetermined source. N Engl J Med. (2018) 378:2191–201. 17. Kamel H, Healey JS. Cardioembolic stroke. Circ Res. (2017) 120:514–26. doi: 10.1161/CIRCRESAHA.116.308407 8. Sposato LA, Chaturvedi S, Hsieh CY, Morillo CA, Kamel H. Atrial fibrillation detected after stroke and transient ischemic attack: a novel clinical concept challenging current views. Stroke. (2022) 53:e94–103. doi: 10.1161/ STROKEAHA.121.034777 18. Lang RM, Badano LP, Mor-Avi V, Afilalo J, Armstrong A, Ernande L, et al. Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European association of cardiovascular imaging. Eur Heart J Cardiovasc Imaging. (2015) 16:233–70. doi: 10.1093/ehjci/jev014 9. Coumel P, Maison-Blanche P. Complex dynamics of cardiac arrhythmias. Chaos Interdiscip J Nonlinear Sci. (1991) 1:335–42. doi: 10.1063/1.165845 July 2022 | Volume 9 | Article 949213 Frontiers in Cardiovascular Medicine | www.frontiersin.org 9 New Markers of AF Detected After Stroke Garnier et al. 19. Carrazco C, Golyan D, Kahen M, Black K, Libman RB, Katz JM. Prevalence and risk factors for paroxysmal atrial fibrillation and flutter detection after cryptogenic ischemic stroke. J Stroke Cerebrovasc Dis OffJ Natl Stroke Assoc. (2018) 27:203–9. doi: 10.1016/j.jstrokecerebrovasdis.2017.08.022 29. Rodriguez-Yanez M, Arias-Rivas S, Santamaria-Cadavid M, Sobrino T, Castillo J, Blanco M. High pro-BNP levels predict the occurrence of atrial fibrillation after cryptogenic stroke. Neurology. (2013) 81:444–7. doi: 10.1212/WNL. 0b013e31829d8773 30. Fonseca AC, Matias JS, Pinho e Melo T, Falcão F, Canhão P, Ferro JM. N- Terminal probrain natriuretic peptide as a biomarker of cardioembolic stroke. Int J Stroke. (2011) 6:398–403. doi: 10.1111/j.1747-4949.2011.00606.x 20. Tsang TS, Barnes ME, Bailey KR, Leibson CL, Montgomery SC, Takemoto Y, et al. Frontiers in Cardiovascular Medicine | www.frontiersin.org July 2022 | Volume 9 | Article 949213 REFERENCES Rochette L, Meloux A, Rigal E, Zeller M, Cottin Y, Vergely C. The role of osteoprotegerin in the crosstalk between vessels and bone: its potential utility as a marker of cardiometabolic diseases. Pharmacol Ther. (2018) 182:115–32. doi: 10.1016/j.pharmthera.2017.08.015 27. Cao H, Li Q, Li M, Od R, Wu Z, Zhou Q, et al. Osteoprotegerin/RANK/RANKL axis and atrial remodeling in mitral valvular patients with atrial fibrillation. Int J Cardiol. (2013) 166:702–8. doi: 10.1016/j.ijcard.2011.11.099 Copyright © 2022 Garnier, Duloquin, Meloux, Benali, Sagnard, Graber, Dogon, Didier, Pommier, Vergely, Béjot and Guenancia. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. 28. Cao H, Wang J, Xi L, Røe OD, Chen Y, Wang D. Dysregulated atrial gene expression of osteoprotegerin/receptor activator of nuclear factor-κB (RANK)/RANK ligand axis in the development and progression of atrial fibrillation. Circ J OffJ Jpn Circ Soc. (2011) 75:2781–8. doi: 10.1253/circj.CJ- 11-0795 July 2022 | Volume 9 | Article 949213 Frontiers in Cardiovascular Medicine | www.frontiersin.org 10
https://openalex.org/W3185144433
http://izvestiya.asu.ru/article/download/%282021%293-10/8088
Russian
null
Russian Printed Paskhalistic Books of the 18th — Early 20th Centuries
Izvestiâ Altajskogo gosudarstvennogo universiteta
2,021
cc-by
3,485
Russian Printed Paskhalistic Books of the 18th — Early 20th Centuries S.V. Tsyb1,2, T.V. Kaigorodova2 1Altai State University (Barnaul, Russia) 2Altai Branch of Russian Presidential Academy of Nation Economy and Public Administration (Barnaul, Russia) 1Altai State University (Barnaul, Russia) 2Altai Branch of Russian Presidential Academy of Nation Economy and Public Administration (Barnaul, Russia) 1Altai State University (Barnaul, Russia) 2Altai Branch of Russian Presidential Academy of Nation Economy and Public Administration (Barnaul, Russia) The article deals with the process of transformation of the old handwritten tradition of describing Paskhaliya into a printed one. Understanding the calculations of the day of Easter was important for the daily life of the population of Ancient Rus, and therefore Old Russian writers paid attention to describing the rules of Easter calculations. For a long time, these descriptions took the form of handwritten manuscripts. After the reforms of Peter the Great in Russia, works of this genre began to take the form of printed editions. The authors aim to consider the features of the transformation of the handwritten manuscripts into modern books. As part of study, it has been found that the descriptions of Paskhaliya, published in the typographic way first, tried to repeat the handwritten samples, but then began to turn into popular descriptions of the rules for calculating Easter. Moreover, the authors of these writings looked to the development of new ways of calculating the dates of the Easter celebration. It has been linked to the fact that after the authors-priests (18th century), secular writers (journalists, officials, officers, etc.) joined the genre of describing Paskhaliya in the first half of the 19th century. The way of transformation of Paskhalistics into an entertaining genre of popular-science literature became likely, but in the second half of the 19th century the representatives of academic science restored the scientific status of this field of knowledge. At present, the achievements of the science of Paskhaliya have become an important element in the study of the chronology of ancient Russian history. In modern science, studying the history of timekeeping, Paskhalistics became one of the necessary elements for studying the chronology of ancient Russian history. It can be recognized that the printed editions of Paskhaliya played an important role in the development of modern chronological science. Рассматривается процесс превращения старин- ной рукописной традиции описания Пасхалии в пе- чатную. Умение рассчитывать день празднования Пасхи было неотъемлемым элементом жизни насе- ления Древней Руси, что заставляло древнерусских писателей составлять руководства для пасхальных расчетов. Key words: handwritten teхts, Paskhaliya, Paskhalistics, printed books, Russian chronology. Русская печатная пасхальная книжность... Русская печатная пасхальная книжность... УДК 002.2:27 ББК 76.103(2)5+86.37 1Алтайский государственный университет (Барнаул, Россия) 2Алтайский филиал Российской академии народного хозяйства и государственной службы при Президенте РФ (Барнаул, Россия) Russian Printed Paskhalistic Books of the 18th — Early 20th Centuries S.V. Tsyb1,2, T.V. Kaigorodova2 1Altai State University (Barnaul, Russia) 2Altai Branch of Russian Presidential Academy of Nation Economy and Public Administration (Barnaul, Russia) Известия АлтГУ. Исторические науки и археология. 2021. №3 (119) 3]. Однако описания различных элементов расчетов Пасхи совсем не походили на таблицы с изложени- ем результатов редукции, поэтому другой пасха- лист, преподаватель Киевской духовной академии иеромонах, а позже епископ Ириней уточнил вы- вод своего «коллеги», отделив от хронологии осо- бую церковную «ветвь»: «Хронология вообще есть наука о правильном исчислении времени, и поэто- му “Церковная хронология”… есть наука о опреде- лении в каждом данном году дня Пасхи и всех за- висящих от оной движимых праздников» [13, с. 1]. Получалось, что, с одной стороны, пасхалистика была связана, хотя и косвенно, с историко-хроно- логическим знанием, но, с другой — она обособля- лась от исторических проблем церковно-пасхаль- ной оболочкой. Первые изложения правил пасхальных расчетов, ориентированные на массового читателя, появились в «Календарях-месяцесловах», с 1728 г. ежегодно из- даваемых Императорской Академией наук при уча- стии Синода. Уже в первых выпусках «Календарей» помещались небольшие таблички с указанием пас- хальных элементов текущего года (Основания, Круги Луны и Солнца, Вруцелето и пр.) и календарное рас- писание важнейших православных праздников. С 1736 г. эти таблички приняли законченную форму («Церковное счисление») и после того уже не меня- лись до начала ХХ в. В выпуске того же года к таб- лице была приложена краткая и весьма сбивчивая статейка с пояснением правил ее использования (ее изложение см.: [2, с. 543–544]). Чуть позже в том же издании появились еще несколько похожих за- меток, которые писались «во удовольствие любо- пытным» и поэтому передавали пасхально-счетные правила весьма приблизительно и нередко с грубы- ми ошибками [3, с. 72–94; 4, с. 74–109; 5, прил. 1]. В последующие годы отмечается всплеск в разви- тии печатной пасхалистки. Объяснялось это в пер- вую очередь тем, что с начала XIX в. она стала уделом светских писателей. Произведения авторов из ду- ховного сословия, опубликованные в XIX в., можно пересчитать без особого труда (например: [14–18]), тогда как количество светских авторов точному уче- ту не поддается. Новоиспеченными пасхалистами становились в эти годы и чиновники, и живопис- цы, и морские и сухопутные офицеры, и журнали- сты и прочие (наиболее примечательные сочине- ния: [19–26]). В 80–90-е гг. XVIII в. за типографское издание пасхальных описаний взялись самые компетент- ные в этой области авторы — православные свя- щеннослужители, которые представили русским читателям несколько сочинений, достаточно пол- но, но не всегда безошибочно раскрывающих сек- реты греко-российского пасхального счета [6–9; 10, с. 41–47]. Russian Printed Paskhalistic Books of the 18th — Early 20th Centuries S.V. Tsyb1,2, T.V. Kaigorodova2 Долгое время эти описания имели форму рукописей. После реформ, проведенных в России Петром I, такие сочинения стали появляться в типо- графской форме. Авторы исследовали особенности трансформации рукописной традиции в книжную форму. В ходе исследования выяснилось, что издан- ные типографским способом описания Пасхалии сна- чала старались повторять рукописные образцы, но за- тем стали превращаться в популярные описания правил расчетов Пасхи. Это было связано с тем, что после авто- ров-священнослужителей (XVIII в.) к жанру описания Пасхалии в первой половине XIX в. присоединились светские сочинители (журналисты, чиновники, офи- церы и др.). Вероятным стало превращение пасха- листики в развлекательный жанр научно-популярной литературы, но во второй половине XIX в. представи- тели академической науки восстановили научный статус этой области знания. Благодаря этому старин- ные научные знания о Пасхалии стали важнейшим элементом в изучении хронологии древнерусской истории. В современной науке, изучающей историю отечественного времяисчисления, пасхалистика ста- ла одним из необходимых элементов изучения хро- нологии древнерусской истории. Можно признать, что печатные издания Пасхалии сыграли важную роль в становлении современной хронологической науки. Ключевые слова: рукописные тексты, Пасхалия, пас- халистика, типографские книги, русская хронология. Key words: handwritten teхts, Paskhaliya, Paskhalistics, printed books, Russian chronology. Key words: handwritten teхts, Paskhaliya, Paskhalistics, printed books, Russian chronology. DOI: 10.14258/izvasu(2021)3-10 71 Известия АлтГУ. Исторические науки и археология. 2021. №3 (119) ний. Так, в 1787 г. протоиерей Н.В. Зырин, один из авторитетных пасхалистов своего времени, писал по этому поводу: «Пасхи число… найти… без кру- гов Солнечных и Лунных и прочего… не мож- но, что есть хронологическое; то из сего следует, что Пасхалия соединена с Хронологией, или она есть дополнение Хронологии». При этом ясно, что под «Хронологией» Н.В. Зырин, как и все его современники, понимал механистический пере- счет (редукцию) старинных дат на эру от Рождества Христова: «Хронология есть наука размерять, раз- личать и разделять или полагать время каждому приключению, когда оное происходило» [12, с. 3]. Однако описания различных элементов расчетов Пасхи совсем не походили на таблицы с изложени- ем результатов редукции, поэтому другой пасха- лист, преподаватель Киевской духовной академии иеромонах, а позже епископ Ириней уточнил вы- вод своего «коллеги», отделив от хронологии осо- бую церковную «ветвь»: «Хронология вообще есть наука о правильном исчислении времени, и поэто- му “Церковная хронология”… есть наука о опреде- лении в каждом данном году дня Пасхи и всех за- висящих от оной движимых праздников» [13, с. 1]. Получалось, что, с одной стороны, пасхалистика была связана, хотя и косвенно, с историко-хроно- логическим знанием, но, с другой — она обособля- лась от исторических проблем церковно-пасхаль- ной оболочкой. Восемнадцатое столетие стало пограничным мо- ментом в истории Русской православной церкви. Бурная эпоха петровских преобразований вынудила эту организацию приспосабливаться к новым усло- виям и не терять своего влияния на духовную жизнь общества, для чего необходимо было наукообразить традиционные формы воздействия на массовое со- знание. Жанр календарно-хронологической пись- менности (иначе — Пасхалия) представлял для этих целей удобное поле деятельности, поскольку отра- жал астрономо-математические знания Древнего мира и Средневековья и угождал общественному ин- тересу к точным наукам. В XVIII в. и даже в XIX в. про- должали появляться рукописные Пасхалии [1, с. 6, 7, 278, 304, 306–317], однако постепенно предпочте- ние стала получать типографская форма их изда- ния, позволявшая охватить широкую читательскую аудиторию. ний. Так, в 1787 г. протоиерей Н.В. Зырин, один из авторитетных пасхалистов своего времени, писал по этому поводу: «Пасхи число… найти… без кру- гов Солнечных и Лунных и прочего… не мож- но, что есть хронологическое; то из сего следует, что Пасхалия соединена с Хронологией, или она есть дополнение Хронологии». При этом ясно, что под «Хронологией» Н.В. Зырин, как и все его современники, понимал механистический пере- счет (редукцию) старинных дат на эру от Рождества Христова: «Хронология есть наука размерять, раз- личать и разделять или полагать время каждому приключению, когда оное происходило» [12, с. Русская печатная пасхальная книжность... ническая машина, показывающая дни праздников церковного года и пасхально-расчетные эле- менты. Ее придумал и сконструировал конюшен- ный императора Александра II офицер Александр Головацкий. Любопытно, что эта поделка привлек- ла внимание двух известных академиков (астронома В.К. Вишневского и историка А.А. Куника) и была удостоена академической Демидовской премии [32; 33]. Интересно также и то, что рецензию на книжку В.К. Вишневского об этой машине напечатал в сто- личных «Ведомостях» Н.Г. Чернышевский, бывший в то время преподавателем Кадетского корпуса и на- чинающим журналистом [34]. Особенно показательна в этом отношении исто- рия изучения русской ручной Пасхалии. Впервые описание ручного способа счета было издано свя- щенником В. Петровым в 1784 г. [8, с. 46–143]. Это сообщение, однако, долго оставалось незамеченным, может быть, просто непонятным, так как ручная Пасхалия была описана этим автором сложно и гро- моздко. Так, например, священник И.П. Алексеев, со- временник и «коллега» В. Петрова, после прочтения его книги записал: «Признаюсь я, достопочтимый читатель, что… о употреблении Руки Дамаскина ис- кусства совершенного не стяжал, потому что… ни же видывал оную» [7, с. 99]. Увеличение количества публикаций и проявле- ние интереса к модернизации Пасхалии сделало не- обходимым даже появление специальных обзорных трудов, дающих любителям пасхально-счетного зна- ния возможность ориентироваться в этом многооб- разии (например: [35]). Другую редакцию ручной Пасхалии очень гра- мотно и с исчерпывающей полнотой описал несколь- ко позже один из лучших в XVIII в. знатоков пасхаль- ной науки и первый ее преподаватель в российских духовных учебных заведениях Симон Рязанский [40]. Он настолько глубоко проник в суть ручного метода, что не мог не задаться вопросам о том, какой вид расчетов появился на Руси раньше — арифмети- ческий или ручной, была ли ручная Пасхалия ориги- нальным русским изобретением или позаимствова- на у греков, имел ли отношение к ее созданию Иоанн Дамаскин и др. Из всех этих соображений архиепи- скопа Симона сложилось сочинение, ставшее опы- том исторического исследования ручной Пасхалии, причем некоторые его выводы имеют научную цен- ность и в наши дни. Развиваясь в подобном направлении, пасхали- стика вполне могла бы превратиться в разновид- ность популярной занимательной литературы. Так бы и произошло, если бы к пасхальной тематике начиная с первой половины XIX в. не обратились представители серьезной академической науки (са- мые заметные публикации: [35–39]). Тем самым они как бы символизировали окончательное ста- новление пасхального направления в развитии хро- нологического знания. На этом, однако, экскурсы в историю ручного пасхального счета и закончились. Известия АлтГУ. Исторические науки и археология. 2021. №3 (119) Эти публикации вызвали большой читательский интерес, что ясно хотя бы из того, что одна из таких книг, написанная членом Синода, Российской и Александро-Невской академий, епи- скопом Тверским и Кашинским Мефодием, выдержа- ла шесть изданий с 1793 г. (последнее издание: [11]). В эти же годы наметился интерес к изобрете- нию новых способов расчета Пасхи. Так, знаком- ство с пасхальной формулой К.-Ф. Гаусса, впервые опубликованной в России в 1838 г. [27], привело к созданию «отечественной математической моде- ли» счета (формула профессора Николаевской академии Генерального штаба, академика ИАН А.Н. Савича), которая, впрочем, при проверке ока- залась лишь разновидностью формулы известно- го немецкого ученого [28; 29, с. 597]. Тогда же стали издаваться многочисленные простенькие таблич- ки, предназначенные для самого неискушенного читателя и не только упрощавшие, но часто и ис- кажавшие правила пасхальных расчетов (напри- мер: [30; 31]). Наконец, была даже изобретена меха- Придание всем этим сочинениям ученого ста- туса уже в эти годы потребовало от авторов опре- деления их места среди прочего научного знания. Сразу же возникло мнение о том, что пасхали- стика относится к области хронологических зна- 72 Русская печатная пасхальная книжность... Библиографический список 16. Делицин П.С., протоиерей. Способ находить в данном году день Святой Пасхи Христовой у христиан как православных, так и западных // Чтения в Московском Обществе любителей духовного просвещения. М., 1865. 1. Романова А.А. Древнерусские календарно-хроноло- гические источники XV–XVII вв. СПб., 2002. 2. Перевощиков М.Д. Обозрение «Русских календа- рей, или месяцесловов» // Магазин землеведения и путе- шествий. Т. 3. М., 1854. 17. Палама Е., священник. Летосчисление, или Стиль, установленный неотступно от расчисления Пасхалии. Таганрог, 1875. 17. Палама Е., священник. Летосчисление, или Стиль, установленный неотступно от расчисления Пасхалии. Таганрог, 1875. 3. Попов Н.И. Изъяснение поставляемого в кален- дарь церковного счисления // Санкт-Петербургский ка- лендарь на лето от Р. Х. 1757-е. СПб., 1756. 18. Голубинский Д.Ф. О времени празднования Пас- хи у христиан востока и запада // Богословский вестник. 1892. № 4 (апрель). 4. Попов Н.И. Продолжение изъяснения о поставляемом в календарь церковного счисления // Санкт-Петербургский календарь на лето от Р. Х. 1758-е. СПб., 1758. 19. Башарулов М.П. Аксиома, для всякого чина, состо- яния, пола и возраста преполезная. СПб., 1804. 5. О солнечном Круге и о литерах недельных // Санкт- Петербургский календарь на лето от Р. Х. 1769-е. СПб., 1768. Приложение 1. 20. Рубан А.А. Неизменяемая Пасхалия, или Весь пас- хальный на 7980 лет оборот. М., 1832. 6. Прхрв Л. (Прохоров Л.) Руководство, каким обра- зом найдена Пасхалия. М., 1786. 21. Тромонин К.Я. Легчайшее руководство для узна- ния в каждом из прошедших и будущих годов чисел Пас- хи Христовой и переходящих праздников. М., 1842. 7. Алексеев И.П., священник. Краткое руководство к удобному познанию знаков. М., 1787. 22. Петров А. Руководство к уразумению указателей и Пасхалии. СПб., 1851. 8. Петров В., священник. Рука богословля, или Наука изъяснения о Пасхалии. М., 1787. 23. Семилиоров П. Пасхалия. М., 1855. 9. Феоктист, епископ (Мочульский). Опыт герменев- тического объяснения о Пасхалии. М., 1799 24. Г.М. (Мещеринов Г.В.). Православная Пасхалия. СПб., 1876. 25. Фролов О.П. Вечный православный календарь. Архангельск, 1889. 10. Ириней, епископ (Фальковский И.Я.). Статья из церковной хронологии // Киевский месяцеслов на лето от Р. Х. 1800-е. Киев, 1799. 26. Рыдзевский А. Определение дня Пасхи по юлиан- скому и григорианскому календарям // Известия Русско- го астрономического Общества. 1900. Вып. VIII. № 4-6. 11. Мефодий, епископ (Смирнов). Правило пасхаль- ного круга. М., 1806. 12. Зырин Н.В., протоиерей. Неисходимый Индикти- он, или Пасхалия Зрячая. М., 1799. 27. Гауссов способ вычисления Пасхи для какого-либо данного года // Месяцеслов на 1839 год. СПб., 1838. 13. Ириней, епископ (Фальковский И.Я.). Известия АлтГУ. Исторические науки и археология. 2021. №3 (119) Пасхалия — С.Ц., Т.К.] придумана весьма остроум- но, но едва ли может взойти в общее употребление, потому что требует сильной памяти или же столь продолжительного навыка… “Ручная Пасхалия” мо- жет привлечь только любопытство» [44, с. 121–122]. употребления в русской исторической и богослужеб- ной письменности (об этом см.: [45, с. 51–77]). Благодаря усилиям ученых и любителей исто- рико-хронологического знания старинные науч- ные знания о Пасхалии стали важнейшим элемен- том в изучении хронологии древнерусской истории. В современной науке, изучающей историю отече- ственного времяисчисления, пасхалистика стала одним из необходимых элементов изучения древ- нерусских систем учета времени, и поэтому можно признать, что печатные издания Пасхалии сыграли важную роль в становлении современной хроноло- гической науки. Полноценное соединение пасхалистики с исто- рико-хронологической наукой произошло только во второй половине XIX в., и главная заслуга в этом принадлежала страстному любителю хронологии, московскому чиновнику П.В. Хавскому. В лучших своих сочинениях он старался не только предста- вить обобщенное или детальное описание пасхаль- но-счетных элементов, но и исследовать историю их Русская печатная пасхальная книжность... Для светских ав- торов-пасхалистов эта схема подсчетов оказалась слишком мудреной; в лучшем случае они использо- вали в своих сочинениях лишь отдельные ее элемен- ты и главным образом для того, чтобы щегольнуть знанием церковной учености. «Профессиональные» же пасхалисты предпочли историческим исследо- ваниям усовершенствование старинной системы, произвольно внося в нее новые элементы и вы- брасывая все, что казалось им сложным. Так, уже в 30-е гг. XIX в. профессор Киевской духовной ака- демии протоиерей И. Скворцов опубликовал свою редакцию ручной Пасхалии, не похожую ни на одну из известных ранее [41]. Несколько позже эта редак- ция, которую правильно назвать уже не «русской», а «скворцовской», была немного изменена и допол- нена на Западной Украине и издана под видом «Руки Дамаскина», т.е. с необоснованными претензиями на архаичность [42]. Безусловной сильной стороной пасхального на- правления был системный принцип описания ма- териала; впрочем, как-то иначе представлять свой предмет пасхалистика и не могла, поскольку в цер- ковном времяисчислении все элементы были тесно связаны между собой, каждый из них имел свое ме- сто в четко построенной структуре. Только на та- ких условиях могла успешно функционировать вся схема определения Пасхи и других переходящих праздников. Например, дату Пасхи легко вычислить по Кругу Луны и годовому Вруцелету, но понятие о Круге Луны невозможно сформировать без знаний Эпакт, Оснований, длины лунного и солнечного го- дов и прочего, как и смысл вруцелетных обозначе- ний трудно постичь без знаний о Круге Солнца, юли- анском високосе и т.д. Однако каждый элемент пасхальной системы и вся она как целое воспринимались исследовате- лями Пасхалии статичными явлениями, сложив- шимися сразу и вдруг еще в древности, в первые столетия существования христианства, и с тех пор не претерпевшими якобы никаких изменений. Консервативность пасхально-хронологического на- правления приводила к тому, что внутри него из- живались даже те немногочисленные сюжеты исто- рических наблюдений, которые время от времени появлялись в сочинениях некоторых авторов. Когда же в 60-е гг. XIX в. пермский священник И.Н. Яковкин опубликовал свой еще более усовер- шенствованный вариант ручных расчетов, от ста- ринной русской основы здесь уже мало что остава- лось [43, с. 349–432]. К примеру, академик-астроном М.Д. Перевощиков так оценил в своей рецензии этот раздел книги священника-пасхалиста: «Она [ручная 73 Библиографический список Сокраще- ние церковной хронологии, называемой просто наукой о Пасхалии. М., 1797. 28. Буняковский В.Я. Описание подвижной таблицы для определения месяца и числа Св. Пасхи без всяких вы- числений // Морской сборник. 1857. № 12. 14. Ненарокомов У.С., протоиерей. Примечания и объяснения на Пасхалию. М., 1804. 29. Черухин И.Н. Календарь для хронологических справок // Русская старина. Т. VIII. 1873. 15. Тяжелов А.И., священник. Руководство к Пасха- лии для употребления в духовных училищах. М., 1820. 30. Петров К.М. Справочный табличный календарь с Пасхалией. Вильна, 1887. 16 табл. 74 Русская печатная пасхальная книжность... 32. Вишневский В.К. Описание хронологической ма- шины Ал. Головацкого. СПб., 1855. Русская печатная пасхальная книжность... 31. Иоффе Г. Полный общедоступный календарь ста- рого и нового стилей с вечной Пасхалией. М., 1891. 4 табл. 39. Шляков Н.В. Легкий способ определения дня неде- ли и Пасхи в любом году // Известия Отделения русско- го языка и словесности Императорской Академии наук. 1905. Т. Х. Кн. 3. 31. Иоффе Г. Полный общедоступный календарь ста- рого и нового стилей с вечной Пасхалией. М., 1891. 4 табл. 39. Шляков Н.В. Легкий способ определения дня неде- ли и Пасхи в любом году // Известия Отделения русско- го языка и словесности Императорской Академии наук. 1905. Т. Х. Кн. 3. 32. Вишневский В.К. Описание хронологической ма- шины Ал. Головацкого. СПб., 1855. 32. Вишневский В.К. Описание хронологической ма- шины Ал. Головацкого. СПб., 1855. 40. Симон (Тодорский). Пасхалии Зрячей для выклад- ки ручной показание в чертежах обеих рук // Зырин Н.В., протоиерей. Неисходимый Индиктион, или Пасхалия Зрячая. М., 1799. 33. Куник А.А. Отзыв о хронологической машине г. Головацкого // 24-е присуждение учрежденных П.Н. Де- мидовым наград. СПб., 1855. 33. Куник А.А. Отзыв о хронологической машине г. Головацкого // 24-е присуждение учрежденных П.Н. Де- мидовым наград. СПб., 1855. 34. [Чернышевский Н.Г.] Рец. на: Вишневский В.К. Описание хронологической машины… // Санкт- Петербургские ведомости. 1855. 5 ноября. № 243. 34. [Чернышевский Н.Г.] Рец. на: Вишневский В.К. Описание хронологической машины… // Санкт- Петербургские ведомости. 1855. 5 ноября. № 243. 41. Скворцов И.М., протоиерей. Русская ручная Пас- халия. Киев, 1836. 35. Н.Г. (Глубоковский Н.Н.). Православная Пасхалия и общедоступные пособия и руководства о хронологии // Христианское чтение. 1892. № 3-4. 42. Рука Дамаскина, из тьмы забвения изъятая. Львов, 1856. 43. Яковкин И.Н., священник. Пасхалия арифметиче- ская и ручная. СПб., 1862. 35. Шуберт Ф.И. Русский месяцеслов // Санкт- Петербургский карманный месяцеслов на лето от Р. Х. 1815-е. СПб., 1814. 44. Перевощиков М.Д. Разбор сочинения священни- ка Иоанна Яковкина «Пасхалия арифметическая и руч- ная» // 32-е присуждение учрежденных П.Н. Демидовым наград. СПб., 1863. 36. Шуберт Ф.И. Непременный календарь греко-рос- сийской церкви. СПб., 1823. 36. Шуберт Ф.И. Непременный календарь греко-рос- сийской церкви. СПб., 1823. 45. Курсакова Е.Н., Цыб С.В. Петр Васильевич Хав- ский — законовед и исследователь русской истории и хронологии. Барнаул, 2014. 37. Перевощиков М.Д. Правила времяисчисления, принятого православной церковью. М., 1850. 37. Перевощиков М.Д. Правила времяисчисления, принятого православной церковью. М., 1850. 38. Предтеченский Е.А. Церковное времяисчисление и критический обзор существующих правил определения Пасхи. СПб., 1892. 38. Предтеченский Е.А. Церковное времяисчисление и критический обзор существующих правил определения Пасхи. СПб., 1892.
https://openalex.org/W4310339639
https://zenodo.org/records/7375004/files/V17I11A125.pdf
English
null
INFLUENCE OF SERVQUAL MODEL ON CUSTOMER LOYALTY WITH SPECIAL REFERENCE TO RETAIL OUTLETS IN BANGALORE
Zenodo (CERN European Organization for Nuclear Research)
2,022
cc-by
4,864
DOI 10.5281/zenodo.7375004 DOI 10.5281/zenodo.7375004 Abstract Companies have begun to focus on developing strategies for maintaining better relationships and to retain the existing customers as well as to attract new customers to widen their customer base. This requires companies to focus on fulfilling the changing requirements of the customers and making changes to the existing products and services if needed. This ensures that the company is customer-oriented rather than being just profit-oriented. Thus, this research aims at determining the influence of SERVQUAL towards customer loyalty especially with respect to retail outlets in Bengaluru city and providing suggestions to the service providers towards the implementation of the proven dimensions of the study and measures to provide improved and efficient service to their customers. The successful implementation would impact the satisfaction levels of the customers and therefore would minimize the gap between the expectation and service delivery by the retail outlets. Therefore, this research study throws light on factors such as customer satisfaction and service quality and its impact on customer loyalty especially with respect to retailing sectors, thus enabling the retailers to design and develop strategies that would help them in satisfying their customers and converting them to become the loyal customers of their brand of product or service. Dr. P ARCHANA Assistant Professor, Department of MBA and Research Centre, RNSIT, Bengaluru. INFLUENCE OF SERVQUAL MODEL ON CUSTOMER LOYALTY WITH SPECIAL REFERENCE TO RETAIL OUTLETS IN BANGALORE Dr. RAKESH. N Assistant Professor, Department of MBA and Research Centre, RNSIT, Bengaluru. Dr. U BHOJANNA Professor and HOD, Department of MBA and Research Centre, RNSIT, Bengaluru. Dr. U BHOJANNA Professor and HOD, Department of MBA and Research Centre, RNSIT, Bengaluru. Z., ben Hamed, A., & al Mubarak, M.,201911). Therefore, it is found that the growing retail sector of India should focus on developing structured scale to provide better and efficient service to its customer as it has got a significant impact on the satisfaction levels and in-turn influencing customer’s intention to continue their business with the same service provider which is termed as Customer Loyalty. 1. INTRODUCTION India is one of the fastest growing economies with respect to the retail sector resulting in the increase of demand for the retail space by 7.8 million squares.ft in 2019. The expansion of the retail business from physical platform to online platform has indeed increased the demand for various products and services thus making Service Quality as one of the important considerations. The developments and advancements in the retail framework of India has resulted in the increased competition and thus making the retail players to design strategies for their survival and growth making Service Quality as an important dimension. Companies have begun to focus on developing strategies for maintaining better relationships and to retain the existing customers as well as to attract new customers to widen their customer base. The competitive business environment is forcing the companies to move from traditional business forums to that of contemporary approaches to maintain long term relationships with the customers. These include strategies such as CRM, Relationship marketing which is creating a huge impact on the perception of the customers influencing their satisfaction and their loyalty towards the business organizations. 1620 | V 1 7 . I 1 1 1620 | V 1 7 . I 1 1 DOI 10.5281/zenodo.7375004 DOI 10.5281/zenodo.7375004 The pre-requisites of a company's success are strongly dependent on the two factors including Customer satisfaction and Service quality. These two factors have significant impact on the patronage motives of a customer thus impacting their loyalty and repurchase intentions (Bourne, P. A.,201610).The various strategies of companies towards maintaining and developing a long lasting relationship with customers including relationship marketing has a significant impact on the establishing a strong association with particular service provider and even impacting their experience and perception towards continuing their relation(Al Mubarak, Z., ben Hamed, A., & al Mubarak, M.,201911). 3.1 Research Questions The objective of the research study is to determine the effectiveness of the SERVQUAL model on Customer loyalty in the retail outlets. With this objective in mind, some of the important research questions developed is: 1) What is the demographic profile of the customers visiting retail outlets in Bengaluru city? 2) How do consumers perceive the service quality when they visit retail outlets? 3) What are the SERVQUAL dimensions considered as important by Bengaluru population visiting retail outlets? 4) Are customers satisfied by the service quality provided by retail outlets in Bengaluru city? 5) Which are the SERVQUAL dimensions impacting customer satisfaction and customer loyalty in retail outlets in Bengaluru city? Objectives of the Study 3. RESEARCH METHODOLOGY The retail sector has led to the growth of Indian economy contributing about 10 percent of the country’s GDP and thus occupying fifth position with respect to retailing in the global framework. The service quality dimensions have paved way for numerous retail outlets to differentiate themselves in terms of their service towards their customers. The Bengaluru city being home for people across globe and reflecting cross and multi- linguistic population who are ready to try and accept with innovations and new technologies and processes were chosen as respondents of the study as the research statistics proves a good number of customers in this metropolitan city moving towards organized retailing. This has triggered the interest towards determining the influence of Service quality dimensions on customer Loyalty especially with respect to retail outlets in Bangalore city. The research includes considering both unorganized and organized retail formats for convenience purpose. By using Morgan’s table for sample size calculation, around 387 samples were contacted to collect data. However, by eliminating wrong entries, invalid responses, around 310 sample responses were considered for the study. DOI 10.5281/zenodo.7375004 2. REVIEW OF LITERATURE The SERVQUAL dimensions have significant impact on customer satisfaction and the proper implementation and execution of these scales would result in high growth potential and opportunities in the current competitive environment (Naik et al. 2012). Sabrina Tazreen (2012) emphasized that quality measurement scales should be industry-specific, and any changes required needs to be incorporated into the scale. It is also suggested that more contemporary models need to be used other than SERVQUAL scale as the business environment is becoming more challenging and needs to consider additional dimensions for efficient servicing of customers which in turn results in modification of the existing SERVQUAL scale. Kanchan and Aditi Sharma (2017) showed that customers have very high levels of expectations with respect to quality of service in hotels considering the cleanliness and hygiene maintained by the service providers as one of the most important factors. Tangibility and empathy dimensions are the two major factors impacting customer perceptions but are under performed by hotels and needs to be concentrated by managers (Kumar et al.2017). Employees Behavior is one of the major determinants of customer satisfaction in Hospitality platforms (Alison et al. 1999). The old, aged customers had preference for empathetic and reliable service whereas youngsters had importance for highly responsive and assured services by the service provider (Blesic et al. 2011). The effective implementation of the dimensions will improve customer’s perception towards the service provider and in turn will impact their repurchase intentions (Asubonteng et al. 1996). Aakash Ashok Kamble, Praful Sarangdhar (2015), their research highlighted that customers' expectation towards the inputs given by faculties and the delivery processes were not satisfied and had significant impact on the student’s interest levels. The introduction of the concept of relationship marketing, the banks are coming out with various strategies to retain the existing customers and to attract new customers to their services (Sampana et al. 2014). Jagbir Singh Dalal (2015), the research study revealed that tangibility played the most important role in forming the perception in the minds of customer followed by assurance, empathy, reliability, and then responsiveness. 1621 | V 1 7 . I 1 1 1621 | V 1 7 . I 1 1 DOI 10.5281/zenodo.7375004 3.3 Sample Design As the research study consists of both unorganized and organized retail formats of Bengaluru city with respect to purchase of FMCG, the number of frequent retail customers are close to the total population of Bengaluru city. For a more scientific approach, the reports from source Statista.com provides us data on regular retail customers of FMCG in Bengaluru as 10.3 million customers. Upon the data available, Morgan table for sample size calculation is used to determine the total respondents to be considered for the study. As a result, around 384 samples were contacted to collect data. However, by eliminating wrong entries, invalid responses, around 310 sample responses were considered for the study. As being the resident of Bengaluru from past 30 years, considering the vibrant changes in the retail environment and the purchase patterns, this place was considered to conduct the research study. Bengaluru being the top metropolitan city would help in exploring the various contexts of research study and even help the researcher in determining other new dimension for the present study. Stratified sampling method considering dis-proportionate samples through systematic random sampling are chosen from different retail formats including Hyper markets, Supermarkets and Local Kirana outlets in and around Bengaluru city. Around 384 questionnaires were administered to collect the data, whereas after removing unanswered and invalid responses, a sample of 310 responses were considered for the research study. 3.4 Formulation of Hypothesis I. To test the Significant difference in perception of service quality between selected demographic variables of respondents following hypotheses has been framed. 3.2 Objectives of the Study 1) To identify the factors of SERVQUAL model impacting customer satisfaction and Loyalty in organized and unorganized FMCG retail outlets in Bengaluru. 2) To develop the theoretical model on factors of SERVQUAL dimensions impacting customer satisfaction and customer loyalty in organized and unorganized FMCG retail outlets in Bengaluru. 3) To analyze the factors of SERVQUAL model impacting customer satisfaction and Loyalty in organized and unorganized FMCG retail outlets in Bengaluru. 3) To analyze the factors of SERVQUAL model impacting customer satisfaction and Loyalty in organized and unorganized FMCG retail outlets in Bengaluru. 1622 | V 1 7 . I 1 1 Source: Primary data Age is an important factor affecting consumer buying behaviour. The above table shows the ANOVA test result to analyze the significant difference between perceptions of service quality between Age group of respondents. It was found that F value is 1.97 and significant value is more than 0.05. The study accepted the null hypothesis. It is concluded that there is no significant difference between perception of service quality and age group of respondents. This finding is in line with the finding of christia (2016). DOI 10.5281/zenodo.7375004 DOI 10.5281/zenodo.7375004 4. ANALYSIS AND INTERPRETATION The differences in the service quality of retail outlets have been examined among demographic variables of the respondents. This analysis on the differences in the service quality of the retail outlets among the heterogeneity of customers may help retail outlets to bring out appropriate marketing strategies to improve the service quality of retail outlets. In addition to the assessment of service quality, the major factors influencing the service quality of the retail outlets are to be identified to formulate the marketing strategies of the retail outlets. Table 1: Significant difference in perception of service quality between male and female respondents Source: Primary data Gender N Mean Std. deviation T value Sig. Male 169 4.07 0.48 3.02 0.003 Female 141 3.92 0.45 1: Significant difference in perception of service quality between male and female respondents The above table shows T test result to analyze the significant difference in perception of service quality between Male and female of respondents. The mean scores of Male and Female was 4.07 and 3.92 respectively. It was found that the p value is less than 0.05 and the study accepted the alternative hypothesis. It can be concluded that there is a significant difference between the perception of service quality and Gender of the respondents in Bengaluru. This finding is in line with the finding of Ying Kwok et al (2016). Table 2: Significant difference in perception of service quality between Age group of respondents Age group N Mean Std. deviation F value Sig. Less than 20 years 8 3.77 0.496 1.97 0.118 21 to 30 years 206 4.05 0.468 31 to 40 years 62 3.94 0.485 Above 40 years 34 3.91 0.495 Table 2: Significant difference in perception of service quality between Age group o respondents Source: Primary data I. To test the Significant difference in perception of service quality between selected demographic variables of respondents following hypotheses has been framed. I. To test the Significant difference in perception of service quality between selected demographic variables of respondents following hypotheses has been framed. Ha1: There is a significant difference in perception of service quality between male and female respondents Ha1: There is a significant difference in perception of service quality between male and female respondents H01: There is no significant difference in perception of service quality between male and female respondents Ha2: There is a significant difference in perception of service quality between age group of respondents H02: There is no significant difference in perception of service quality between age group of respondents II. To test the research framework following hypotheses has been developed Ha1: There is a significant influence of service quality on customer satisfaction H01: There is no significant influence of service quality on customer satisfaction Ha2: There is a significant influence of service quality on customer loyalty H02: There is no significant influence of service quality on customer loyalty Ha3: There is a significant influence of customer satisfaction on customer loyalty H03: There is no significant influence of customer satisfaction on customer loyalty 1623 | V 1 7 . I 1 1 5. STRUCTURAL EQUATION MODEL USING SMART- PL Structural Equation Modelling is applied in this study to test the theoretical constructs which are composite. The major approaches used for SEM is through covariance-based method and Partial Least Square method. PLS is based on structural Equation Model is applied to a greater 1624 | V 1 7 . I 1 1 DOI 10.5281/zenodo.7375004 DOI 10.5281/zenodo.7375004 DOI 10.5281/zenodo.7375004 level in the recent periods after the development of software named SMART-PLS by Ringle et al.(2005). The major advantage of this software is that, results can be obtained using a smaller sample size (Benaroch, Lichtenstein, & Robinson, 2006) which is difficult in co-variance based structural equation model software. Using SMART- PLS, reliability and validity of the instruments has to be checked along with the model testing. Figure 1: Evaluation of Measurement Model g 5.1 Path Coefficients Table 3: Path Coefficient Customer Loyalty Customer satisfaction Service quality Customer Loyalty Customer satisfaction 0.373 Service quality 0.470 0.647 Path coefficients are standardized path coefficients. Path weights ranges from +1 to -1. Weight close to 1 indicates the strongest paths. Weight close to 0 signifies the weak paths. Above th path weight of customer satisfaction and customer loyalty (0.373) shows customer have positive effect on customer loyalty. The path weights of 0.473 implies Service quality hav positive impact on Customer Loyalty. Service quality at 0.647, has a positive influence o Customer satisfaction. Since the standardized data are involved, it can be implied that dependin on the above path coefficients that the complete degree of the Service quality on custome satisfaction is approximately twice that of customer loyalty. 5.1 Path Coefficients 5.1 Path Coefficients Table 3: Path Coefficient Customer Loyalty Customer satisfaction Service quality Customer Loyalty Customer satisfaction 0.373 Service quality 0.470 0.647 Table 3: Path Coefficient Customer Loyalty Customer satisfaction Service quality Path coefficients are standardized path coefficients. Path weights ranges from +1 to -1. Weights close to 1 indicates the strongest paths. Weight close to 0 signifies the weak paths. Above the path weight of customer satisfaction and customer loyalty (0.373) shows customer have a positive effect on customer loyalty. The path weights of 0.473 implies Service quality have positive impact on Customer Loyalty. Service quality at 0.647, has a positive influence on Customer satisfaction. Since the standardized data are involved, it can be implied that depending on the above path coefficients that the complete degree of the Service quality on customer satisfaction is approximately twice that of customer loyalty. Path coefficients are standardized path coefficients. Path weights ranges from +1 to -1. Weights close to 1 indicates the strongest paths. Weight close to 0 signifies the weak paths. DOI 10.5281/zenodo.7375004 Figure 2: Path Coefficient 5.2 Outer Loading Table 4: Outer Loading Customer Loyalty Customer satisfaction Service Quality Assurance 0.876 Complaning_Behaviour 0.794 Empathy 0.827 Location 0.870 Offers promotions 0.819 Price sensitivity 0.762 Product services 0.903 Purchase Intentions 0.827 Reliability 0.864 Responsiveness 0.864 Service facility 0.893 Tangibility 0.718 WOM 0.664 Outer loadings are considered to be measured in a form of item reliability coefficient for reflective models. The closer the loadings are to 1, the more is the reliability of the latent variable. Additionally, for a well-fitting reflective model, path loadings must be more than 0.70 (Henseler, Ringle, Sarstedt, 2012:269). Also, the thumb rule is that the factor loading below 0.4 should be eliminated if elimination improves composite reliability (Hair et al., 2014:103). Since all the items have shown outer loadings above 0.7 or close to 0.7 the study accepted all the items considered in the study. Figure 2: Path Coefficient Figure 2: Path Coefficient 5.2 Outer Loading 5.2 Outer Loading Table 4: Outer Loading Customer Loyalty Customer satisfaction Service Quality Assurance 0.876 Complaning_Behaviour 0.794 Empathy 0.827 Location 0.870 Offers promotions 0.819 Price sensitivity 0.762 Product services 0.903 Purchase Intentions 0.827 Reliability 0.864 Responsiveness 0.864 Service facility 0.893 Tangibility 0.718 WOM 0.664 Table 4: Outer Loading Outer loadings are considered to be measured in a form of item reliability coefficient for reflective models. The closer the loadings are to 1, the more is the reliability of the latent variable. Additionally, for a well-fitting reflective model, path loadings must be more than 0.70 (Henseler, Ringle, Sarstedt, 2012:269). Also, the thumb rule is that the factor loading b l 0 4 h ld b li i d if li i i i i li bili ( i l Outer loadings are considered to be measured in a form of item reliability coefficient for reflective models. The closer the loadings are to 1, the more is the reliability of the latent variable. Additionally, for a well-fitting reflective model, path loadings must be more than 0.70 (Henseler, Ringle, Sarstedt, 2012:269). Also, the thumb rule is that the factor loading below 0.4 should be eliminated if elimination improves composite reliability (Hair et al., 2014:103). Since all the items have shown outer loadings above 0.7 or close to 0.7 the study accepted all the items considered in the study. 0.70 (Henseler, Ringle, Sarstedt, 2012:269). Above the path weight of customer satisfaction and customer loyalty (0.373) shows customer have a positive effect on customer loyalty. The path weights of 0.473 implies Service quality have positive impact on Customer Loyalty. Service quality at 0.647, has a positive influence on Customer satisfaction. Since the standardized data are involved, it can be implied that depending on the above path coefficients that the complete degree of the Service quality on customer satisfaction is approximately twice that of customer loyalty. 1625 | V 1 7 . I 1 1 1625 | V 1 7 . I 1 1 DOI 10.5281/zenodo.7375004 5.3 Structural Model Confirmation of Path through Bootstrapping Table 5: Structural Model Confirmation of Path through Boot strapping Original Sample (O) Sample Mean (M) Standard Deviation (STDEV) T Statistics P Values Customer satisfaction -> Customer Loyalty 0.373 0.372 0.060 6.234 0.000 Service Quality -> Customer Loyalty 0.470 0.472 0.053 8.919 0.000 Service Quality -> Customer satisfaction 0.647 0.647 0.051 12.787 0.000 5.3 Structural Model Confirmation of Path through Bootstrapping The above table shows the t-value which is signified for the structural (inner) model. Through bootstrapping with 5000 samples, where sub-samples were resulting from the actual sample, which provides the respective t-test results for accepting or rejecting the structural path. The significance was stated at 5% level, where the calculated t-value, should be above critical t- values of 1.96. It is observed that, the path between to customer satisfaction to customer loyalty (6.234), service quality to customer loyalty (8.919) and service quality to customer satisfaction (12.787) are significant at 5% level. Also, the thumb rule is that the factor loading below 0.4 should be eliminated if elimination improves composite reliability (Hair et al., 2014:103). Since all the items have shown outer loadings above 0.7 or close to 0.7 the study accepted all the items considered in the study. 1626 | V 1 7 . I 1 1 1626 | V 1 7 . I 1 1 DOI 10.5281/zenodo.7375004 it has got a significant impact on the satisfaction levels and in-turn influencing customer’s intention to continue their business with the same service provider which is termed as Customer Loyalty. Therefore, this research study throws light on factors such as customer satisfaction and service quality and its impact on customer loyalty especially with respect to retailing sectors, thus enabling the retailers to design and develop strategies that would help them in satisfying their customers and converting them to become the loyal customers of their brand of product or service. 6. CONCLUDING REMARKS A deductive approach is followed for testing the proposed research model. This hypothetical model examines the relationship between service quality and customer loyalty, service quality and customer satisfaction, and customer loyalty and customer satisfaction. The relationship between service quality and customer loyalty through the mediating effect of customer satisfaction. The research study has come out with various important findings that would help retailers across Bengaluru city to design and develop strategies to attract and retain customers to their outlets. Bengaluru is the biggest metropolitan city with a varied population from different cultures has always offered numerous opportunities for people across the globe. The retail outlets across Bengaluru have got varied dimensions to expand their wings and to prove their competitiveness in this ever-growing world. From the research study, various important findings were made, which when implemented by the retail outlets would help them in expanding their customer base. The demographical analysis of the respondents has shown that the majority of the customers visiting the retail outlet were male. Therefore, it is suggested that the retail owners should come up with strategies to attract the female population as they are the decision- makers with respect to purchases made. The competitive business environment is forcing companies to move from traditional business forums to contemporary approaches to maintain long-term relationships with customers. These include strategies such as CRM, Relationship marketing which are creating a huge impact on the perception of the customers influencing their satisfaction and their loyalty towards the business organizations. Therefore, it is found that the growing retail sector of India should focus on developing a structured scale to provide better and efficient service to its customer as 1627 | V 1 7 . I 1 1 1627 | V 1 7 . I 1 1 DOI 10.5281/zenodo.7375004 DOI 10.5281/zenodo.7375004  Muhammad Shafiq, Muhammad Azhar Naeem, Service Quality Assessment of Hospitals in Asian Context: An Empirical Evidence from Pakistan, the Journal of Health Care Organization, 54(1), 2017, Pp.1-12.  Dr Ranjith P V, Service Quality In Hospitals - An Empirical Study, Iosr Journal Of Business And Management (Iosr-Jbm), 20(4), 2018, Pp.11-15.  Jagbir Singh Dalal, Prioritization of Various Dimensions of Service Quality in Hospitality Industry, International Journal of Management (Ijm), 6(6), 2015, Pp.12-28.  Cusick, J. (2013). A Review Of: ‘Social Media in Travel, Tourism and Hospitality: Theory, Practice and Cases.’ Tourism Geographies, 16(1), Pp.161–162.  Echchabi Abdelghani, Applying Servqual To Banking Services: An Exploratory Study In Morocco, Studies In Business And Economics, 62.  Magnus So¨Derlund, Measuring Customer Loyalty With Multi-Item Scales, International Journal Of Service Industry Management, 17(1), 2006, Pp.76-98.  Maladi, M., Nirwanto, N., &Firdiansjah, A. (2019). The Impact of Service Quality, Company Image and Switching Barrier on Customer Retention: Mediating Role of Customer Satisfaction. International Journal of Applied Business and International Management, 4(2), Pp.57–64.  Dr.Satyarth Kumar Singh, Signs Of Corruption in Selection Process in Retail Sector in India, Casirj, 5(12), 2014, Pp.117-118.  Mohd Ghadafi Bin Shari, Servqual: Customer Satisfaction Towards The Services Offered, JabatanPerdaganganPoliteknik Seberang Perai.  Dr Vishal Srivastava, Dr Manoj Kumar Srivastava, Dr R K Singhal, Challenges For Organized Retailing In India, Think India Journal, 22 (14), 2019, Pp.15584 – 15597.  Vijay Panchawatkar, Organized And Unorganized Retailing In India: Will They Co- Exist?, Indian Institute Of Foreign Trade, Pp.1-17.  Factors Influencing Consumer Purchase Intention toward Organic Food Products, Journal Of Channel And Retailing, 2012.  Ms. Monika Talreja, Dr. Dhiraj Jain, Changing Consumer Perceptions towards Organized Retailing from Unorganized Retailing – An Empirical Analysis, International Journal of Marketing, Financial Services & Management Research, 2(6), 2013, Pp.73-85.  Prof. Vivek Shaurya, Prof. Shailesh Pandey, Fdi and Unorganized Retail in India, Ijress, 4(5), 2014, Pp.9-22.  Dr Vishal Srivastava, Dr Manoj Kumar Srivastava, Dr R K Singhal, Challenges For Organized Retailing In Indiathink India Journal, 22(14), 2019,Pp.15584-15597.  Collin.C.Williams, Consumer Services and Economic Development, 2009.  Vivek Kumar Tripathi, TanuMarwah, Relationship between Post Purchase Services by Private  Nasir, A., Mushtaq, H., & Rizwan, M. (2014). Customer Loyalty in Telecom Sector of Pakistan. Journal of Sociological Research, 5(1).  Gârdan, D. A., &Gârdan (Geangu), I. P. (2015). The Social and Economic Factors Influence upon the Healthcare Services Consumers Behaviour. BIBLIOGRAPHY  Khare, A., &Khare, A. (2011). Blending Information Technology in Indian Travel and Tourism Sector. Services Marketing Quarterly, 32(4), 302–317.  Takhire, M., & M.R, T. J. (2015). Evaluation of Effective Factors on Customer Decision-Making Process in the Online Environment. International Journal of Managing Public Sector Information and Communication Technologies, 6(3), 01–11.  Berry, L. L., Parasuraman, A., & Zeithaml, V. A. (1988). The Service-Quality Puzzle. Business Horizons, 31(5), 35–43.  Application of Gronroos’ Service Quality Model in Co-Operative Banks: An Exploratory. (2020). International Journal for Research in Engineering Application & Management, 339–345.  Trupti Sachin Gupte, T. S. G. (2019). Challenges Faced By the Hr Department for Retaining Talent in the Organised Retail Sector. International Journal of Human Resource Management and Research, 9(3), 85–90.  Dutta, A., Shome, S., &Angur, M. (2011). Credibility of Management Education for Enhanced Sustainable Development: A Strategic Quality Of Life Model Perspective. Ssrn Electronic Journal.  Hennig-Thurau, T., &Thurau, C. (2003). Customer Orientation Of Service Employees—Toward A Conceptual Framework Of A Key Relationship Marketing Construct. Journal of Relationship Marketing, 2(1– 2), 23–41.  Dr. Akhilesh Tiwari, &Dr. Amitabh Roy. (2020). Consumers’ Buying Activities In Relative To Green Commodities. Gis Business, 15(1), 253–262. Https://Doi.Org/10.26643/Gis.V15i1.18377  Kamble, A. A., &Sarangdhar, P. (2015). Assessing Service Quality and Customer Satisfaction in Management Education Using Servqual Model. Journal of Commerce and Management Thought, 6(2), 369.  Bourne, P. A. (2016). Customer Satisfaction of Policing the Jamaican Society: Using Servqual to Evaluate Customer Satisfaction. Journal of Healthcare Communications, 1(3).  Al Mubarak, Z., Ben Hamed, A., & Al Mubarak, M. (2019). Impact Of Corporate Social Responsibility On Bank’s Corporate Image. Social Responsibility Journal, 15(5), 710– 722.  Lukong Paul Berinyuy, Using the Servqual Model to Assess Service Quality and Customer Satisfaction, Umeå School of Business, 2010  Vidya B. Panicker, Dr Khalil Ahmad Mohammad, A Study On The Service Quality Attributes Of Parlour Service Employees And Their Contribution To Customer Satisfaction In The Beauty Care Service Industry, International Journal Of Business And Management Invention, 6(11), 2017, Pp. 22-28.  Parisa Islam Khan, Ayesha Tabassum, Service Quality and Customer Satisfaction of the Beauty-Care Service Industry in Dhaka: A Study on High-End Women’s Parlors, The Journal of Business in Developing Nations, 12, 2011, Pp.32-58. 1628 | V 1 7 . I 1 1 DOI 10.5281/zenodo.7375004 DOI 10.5281/zenodo.7375004 Annals of “SpiruHaret”. Economic Series, 15(2), 45.  Mahadi Hasan Miraz Et Al., M. H. M. E. A. (2020). Factors Affecting Consumers Intention To Use Blockchain Based Services (Bbs) In The Hotel Industry. International Journal Of Mechanical And Production Engineering Research And Development, 10(3), Pp. 8891–8902. 1629 | V 1 7 . I 1 1 DOI 10.5281/zenodo.7375004  Manzoor Ahmed, Shafi Ullah, Zia Ul HaqParacha, The Retail Food Sector In Pakistan, International Journal Of Academic Research In Business And Social Sciences, 2(12), 2012,Pp.112-128.  Van Kenhove, P., De Wulf, K., & Van Waterschoot, W. (1999). The Impact of Task Definition on Store- Attribute Saliences and Store Choice. Journal of Retailing, 75(1), 125–137.  Sommerfield, T. (2013). Sayed Faqir Hussain Shah. Bmj, 347(Nov04 3), F6435.  Souitaris, V., &Balabanis, G. (2007). Tailoring Online Retail Strategies to Increase Customer Satisfaction and Loyalty. Long Range Planning, 40(2), 244–261.  Prado Román, A., Blanco González, A., & Mercado Idoeta, C,. Customer Satisfaction, Loyalty, and Commitment in Online Markets. Esic Market Economic and Business Journal, 44(2), 2012.  Moisescu, O. I., Gică, O. A., Müller, V. O., & Müller, C. A. (2019). Can Corporate Fairness Towards Public Authorities Enhance Customer Loyalty? A Multi-Sectorial Investigation in a Developing Country. Sustainability, 12(1), 2013, Pp.187.  Vanpariya, B., &Ganguly, P. Servqual versus Servperf: An Assessment from Indian Banking Sector. Ssrn Electronic Journal. 2011.  Dr.Gantasala V. Prabhakar, Servqual and Customer Satisfaction: The Mediating Influence of Communication in the Privatized Telecom Sector, 3(3), 2013, Pp.135- 155 1630 | V 1 7 . I 1 1
https://openalex.org/W4223972953
https://zenodo.org/records/6467930/files/Xoldorova%20Mahliyo%20Ibroximjon%20qizi.pdf
Quechua
null
UMUMIY O'RTA TA'LIM MAKTABLARI DARS JARAYONLARIDA DIDAKTIK VOSITALARDAN FOYDALANISH TEXNOLOGIYALARINI TAKOMILLASHTIRISH
Zenodo (CERN European Organization for Nuclear Research)
2,022
cc-by
1,359
UMUMIY O'RTA TA'LIM MAKTABLARI DARS JARAYONLARIDA DIDAKTIK VOSITALARDAN FOYDALANISH TEXNOLOGIYALARINI TAKOMILLASHTIRISH https://doi.org/10.5281/zenodo.6467930 Xoldorova Mahliyo Ibroximjon qizi Namangan Davlat universiteti Pedagogika - psixologiya fakulteti Ta'lim menejmenti kafedrasi Ta 'lim muassasalarini boshqaruv 1 bosqich magistratura talabasi. Xoldorova Mahliyo Ibroximjon qizi Namangan Davlat universiteti Pedagogika - psixologiya fakulteti Ta'lim menejmenti kafedrasi Ta 'lim muassasalarini boshqaruv 1 bosqich magistratura talabasi. Annontatsiya: Ushbu maqolada umumiy o'rta ta'lim maktablari dars jarayonlarida didaktik vositalardan foydalanish texnologiyalarini takomillashtirish haqida fikr yuritilgan. Kalit so’zlar: Dars, ta’lim, didaktika, axborot, samara, multimedia, zamonaviy t l i Annontatsiya: Ushbu maqolada umumiy o'rta ta'lim maktablari dars jarayonlarida didaktik vositalardan foydalanish texnologiyalarini takomillashtirish haqida fikr yuritilgan. Kalit so’zlar: Dars, ta’lim, didaktika, axborot, samara, multimedia, zamonaviy texnologiya. Bugungi kunda butun dunyoda axbоrоt texnоlоgiyalari keng ko’lamda rivоjlanmоqda. Shubhasiz, ta’lim jarayonida yangi axbоrоt texnоlоgiyalaridan maqsadli foydalanishni yo’lga qo’yish zarurdir. Zamоnaviy jamiyat axbоrоt uzatish hajmi va tezligi jihatidan chegaralanmagan butunjahоn axbоrоt tarmоg’idan faоl fоydalanishi bilan harakterlanadi. Multmediya va Internet texnоlоgiyalarining paydo bo’lishi va keng tarqalishi AKT ni mulоqоt, tarbiya, jahоn hamjamiyatiga kirib bоrish vоsitasida ishlatish imkоnini beradi. Bugungi kunda barcha sohalar kabi o’quv jarayonini ham kompyuter va axborot texnologiyalarisiz tasavvur etish qiyin. Bu esa kompyuter va axborot texnologiyalarining imkoniyatlaridan foydalanish barcha masalalarning yechimini hal qiladi, ya’ni axborotlarni uzatish va qayta ishlash- bu bilim, malaka va ko’nikmalarni to’liq shakllantirishni kafolatlaydi degani emas, chunki bularning barchasi faqatgina o’qitishning samarali qo’shimcha vositalaridan biri bo’lib hisoblanadi xolos. Ana shuning uchun ham zamonaviy axborot-texnologiyalardan ta’lim tizimida foydalanish quyidagi yo’nalishlarda amalga oshiri¬ladi: - axborot-kommunikatsion texnologiyalar o’rganish ob’ekti sifatida, ya’ni tala¬balar bilim olish jarayonida yangi axborot texnologiyalar, shu jumladan kompyuter, mulьtimediya, masofadan o’qitish, Internet texnologiyalari va ularning tarkibiy qismlari hamda foydalanish sohalari bo’yicha umumiy tushuncha va malakalarga ega bo’ladilar; - axborot-kommunikatsion texnologiyalar o’qitish vositasi sifatida, ya’ni za¬monoviy axborot va pedagogik texnologiyalar asosida talabalarga bilim be¬riladi, ya’ni umumta’lim hamda mutaxassislik fanlarini o’qitishda axbo¬rot-kommunikatsion texnologiyalardan foydalaniladi. Ma’ruza, amaliy va laboratoriya mashg’ulotlari kompyuterlarning zamonaviy dasturiy vosita¬lari asosida tashkil etiladi, shu bilan birga fanlararo integratsiya amalga oshiriladi; - ta’lim jarayonini boshqarish vositasi sifatida, ya’ni ta’lim muassasasi¬ning o’quv, ma’naviy-ma’rifiy va ilmiy-tatqiqot ishlari faoliyati sama¬radorligini oshirishda axborot-kommunikatsion texnologiyalar asosida ax¬borotlashtirish, tahlil va bashorat qilish tizimini yaratish hamda uni amaliyotga jalb etish. Ta’lim sohasidagi barcha islohatlarning asosiy maqsadi ma’naviy jihatdan mukammal rivojlangan insonlarni tarbiyalash, ta’lim tizimini takomillashtirish, dars jarayonlarini yangi pedagogik va axborot texnologiyalari asosida har tomonlama zamon talabiga mos ravishda amalga oshirishdan iboratdir. Shuning uchun ham bugungi kunda ta’lim - tarbiya tizimida kompyuter va axborot texnologiyalarining zamonoviy texnologiyalaridan samarali foydalanishga alohida e’tibor berilmoqda. Xoldorova Mahliyo Ibroximjon qizi Namangan Davlat universiteti Pedagogika - psixologiya fakulteti Ta'lim menejmenti kafedrasi Ta 'lim muassasalarini boshqaruv 1 bosqich magistratura talabasi. Bu esa ta’lim jarayonida o’quvchilarga turli fanlardan bilim beruvchi pedagog kadrlarni axborot texnologiyalarining zamonaviy vositalalaridan foydalanishlari uchun, eng avvalo bu sohadagi bilim va malaka darajalarini oshirish, ta’lim tizimini texnik jihatdan ta’minlash, internetdan foydalanish imkoniyatlarini to’la yaratib berish orqaligina samarali natijaga erishish mumkin. Ta’lim tizimi sifati va samaradorligini oshirishning yana bir asosiy usullaridan biri o’quv jarayonida zamonaviy axborot kommunikasion texnologiyalarni, shu jumladan multimediyali o’quv kurslarini qo’llash, o’qituvchi va o’quvchining interfaol o’zaro aloqalarini ta’minlash, multimediali o’quv kurslari va darsliklarini ishlab chiqishda yuqori malakali kadrlarni jalb etishdan iborat bo’ladi. Multimedia axborotlarni har xil ko’rinishlarda tasvirlash va dinamik obrazlarini yaratish, uni ko’rish va eshitish organlari orqali qabul qilish va tasavvur etish imkoniyatlarini yaratadi. Multimedia texnologiyalarida an’anaviy texnologiyalarga qaraganda axborotlar matn ko’rinishda emas, balki tasvir, ovoz va harakatlar ko’rinishida ifodalanilishi o’quvchilarni darslarda faolroq, diqqatliroq intiluvchan va qiziquvchan bo’lishga o’rgatadi, chunki tavsiya qilinadigan har bir axborot ularning ishtiroki va harakati orqali amalga oshiriladi. Ta’lim tizimida multimedia texnologiyalari nazariy, amaliy, ko’rgazmali, ma’lumotli, trenajyorli va nazorat qismlarini birlashtirish yo’li bilan o’quvchilarga ijobiy va samarali ta’sir etuvchi vosita hisoblanadi. Bundan tashqari ta’lim tizimida multimediali o’quv kurslaridan foydalanish nazariy materiallarning namoyishlarini sifatli video yozuvlari, virtual laboratoriya ishlari va amaliyotlarni, turli jarayonlarning imitasion animasiyali modellarini yaratish imkonini beradi, bu uchun o’quvchilarning o’quv sinflari, kompyuter sinflari, o’qitishning texnik vositalari xonasida, uslubiy xonalarda, kutubxonalarda amaliy shug’ullanishlarini tashkillashtirish lozim bo’ladi. Ta’lim tizimida foydalaniladigan barcha multimediali o’quv kurslari amaliy tadbiqdan va tajribadan o’tgan bo’lishi bilan birga, o’ziga xos pedagogik-psixologik xususiyatlarga ham ega bo’lishi kerak. INNOVATIVE DEVELOPMENTS AND RESEARCH IN EDUCATION International scientific-online conference Part 5, 23.04.2022 O‘quv yurtlarida beriladigan bilim ilmiy harakterga ega bo‘lishi fan-texnikaning so‘nggi yutuk va kashfiyotlarini o‘zida ifoda etishi lozim. Shunday ekan, o‘qituvchi ilm- fandagi yangiliklardan xabardor bo‘lishi lozim, o‘quv fanlari ham ilm-fan asosida yaratiladi. O‘qitishning ilmiylik tamoyillari ta’lim jarayonida o‘quvchi-talabalarni xozirgi zamon fan-texnika taraqqiyoti darajasidagi ilmiy bilimlar bilan qurollantirish, ayniksa talaba yoshlarni ilmiy-tadqiqot usullari bilan tanishtirib borishga karatilgan. Ilmiylik ta’limning mazmuniga ham, usullariga ham aloqadordir. Shunday ekan, bilim, ilm-fan bilan o‘kuv predmeti o‘rtasida hamkorlik o‘zaro bog’liqlik bo‘lishiga erishish lozim. Ta’limning hamma bosqichlarida ilmiy izoxlardan foydalanmoq lozim. Nazariy bilimlarning amaliyot bilan, turmush tajribalari bilan bog’lab olib borish ta’limning yetakchi qoidalaridan hisoblanadi. Ta’lim-tarbiya soxasidagi yutuqlar, eng avvalo nazariya bilan amaliyotning o‘zaro boglikligiga asoslanadi. Shundagina o‘kuvchi-talaba o‘rganayotgan o‘quv materiallarining tub moxiyatini tushunib yetadi va amaliyotda ulardan foydalana oladi. Buning uchun o‘qituvchi ta’lim jarayonida o‘quvchilarning faol ishtirok etishlariga erishmok lozim. Faol ishtirok esa bilimlarni ongli, tushunib o‘zlashtirishga olib keladi. Ta’limdagi onglilik va faollik, o‘quvchidagi ko‘tarinki kayfiyat, ko‘prok bilishga intilish, mustakil fikrlash va xulosalar chikarishga undaydi. Bilimlarni ongli va faol o‘zlashtirish o‘kitish jarayonining psixologik tomonlarida o‘z ifodasini topadi. O‘qitish jarayonini ko‘rgazmali tashkil etish zarur. Ham eshitish, ham ko‘rsatish orqali o‘quv materiallarini idrok qilish, ularni ongli va puxta o‘zlashtirish, bilimlarni turmushdagi zaruriyatini anglab yetishlariga asos soladi, dikkatni barqarorlashtiradi. Shuning uchun ko‘rgazmali materiallar o‘rganilayotgan mavzuning mazmuniga mos kelishi, o‘quvchi-talabaning yoshi va bilim darajasiga muvofiklashgan bo‘lishi, hamda ulardan foydalanishning samarali yo‘l va vositalarini qo‘llash va ishlab chiqish lozim. INNOVATIVE DEVELOPMENTS AND RESEARCH IN EDUCATION International scientific-online conference Part 5, 23.04.2022 Multimediali o’quv kurslarining pedagogik-psixologik xususiyatlari bilim va ko’nikmalarni shakllantirish uchun foydalaniladigan o’quv materiallarining tasvirlanish hamda ifodalanish formasiga va ko’rinishiga bog’liq bo’ladi. Ular faqatgina misol va masalalar yechish, amaliy va laboratoriya mashg’ulotlarini bajarish jarayonidagina emas, balki butun o’quv jarayonida o’quvchilarni bilim, malaka va ko’nikmalarini shakllantirishga qaratilishi lozim. Ta’lim tizimida yaratilayotgan multimedia o’quv kurslarining asosiy xususiyatlaridan biri, shu mavzuni o’rganishning ma’lum bir nozik jihatlari bilan aniqlanadi, ular esa o’z navbatida katta sondagi ko’rgazmali materiallarni talab qiladi, chunki ularning ishtirokisiz jonli dunyoning turli tumanligini, uni qurishni zarurligini, biologik, ximik va fizika jarayonlarning hosil bo’lish mexanizmini va rivojlanishini to’liq namoyish qilib bo’lmaydi. Ta’lim tizimi uchun multimediali o’quv kurslarini yaratishda shu sohaning asosiy didaktik masalalaridan biri – o’qitishni modellashtirish va tasavvurlash obyektlariga ta’sir qilishning umumiy metodlari muhim o’rinlardan birini egallaydi. Tarixiy taraqqiyot davomida ijtimoiy tajribalar ko‘paya borgan sari, ta‘lim jarayonida beriladigan bilimlar mazmunining xarakteri va doirasi ham o‘zgaradi. Shunday qilib, ma‘lum dasturga asoslangan, ma‘lum maqsadga qaratilgan maxsus ijtimoiy dorilfunun- maktab paydo bo‘ladi. Endi esa maktabdagi faoliyat turi, uni amalga oshirish usuli va vositalarini asoslab berish zaruriyati paydo bo‘lgan. Shunday qilib didaktika fani yuzaga keladi. Didaktika (grekcha didasko – o‘qitaman) ta‘lim va ma‘lumot haqidagi fandir. Insonning tarbiyasi rivojlanishi va shaxs sifatida shakllanishida ta‘lim va ma‘lumot muhim ahaiyatga ega. Ma‘lumot-bu egallagan, tizimlashtirilgan bilim, ko°nikma va malakalar, hosil qilingan dunyoqarashlar majmui. Ta‘lim-o‘qituvchi rahbarligida o‘tkaziladigan, o‘quvchilarni bilim, ko‘nikma va malakalar bilan qurollantirilgan, ularning bilish qobiliyatlarini o‘stiradigan va dunyoqarashini tarkib toptiradigan jarayondir. Ta‘lim va ma‘lumot bir-biri bilan mustahkam bog‘liq. Ma‘lumot bu ta‘limning natijasi, ta‘lim esa ma‘lumot olishning asosiy yo‘lidir. Didaktika fani ta‘lim va ma‘lumotning muhim muammolarini o‘rganish bilan birga «kimni o‘qitish kerak», «nimaga o‘rgatish kerak», «qanday o‘qitish kerak» kabi savollarga ham javob bo‘ladi. Ta’lim tamoyillari o‘quv yurtlari oldida turgan ulkan vazifalar asosida belgilanadi. Ular o‘zaro bir-biri bilan mustaxkam bog’lik xolda bir sistemani tashkil etadi, har bir darsda didaktik tamoyillarning bir nechasi ishtirok etishi mumkin. Ular ta’lim oldida turgan asosiy maqsadlarni xal etishga o‘z hissasini ko‘shadi. Ta’lim tizimi islox qilinayotgan xozirgi jarayonda o‘quvchi-talabalarga mustaxkam bilim berish, ularni erkin, mustakil fikrlay oladigan insonlar qilib tarbiyalashda, ta’lim tamoyillarining moxiyatini chukur anglash va xayotga tadbiq etish muxim muammolardan biridir. FOYDALANILGAN ADABIYOTLAR RO’YXATI: 1. Аxмеджaнoв М.М., Тyxтaевa З.Ш. Дидaктик вocитaлap мaжмyacи. Укув кУллaнмa. -Т.: <^н вa теxнoлoгиялap», 200В. -100-б. 1. Аxмеджaнoв М.М., Тyxтaевa З.Ш. Дидaктик вocитaлap мaжмyacи. Укув кУллaнмa. -Т.: <^н вa теxнoлoгиялap», 200В. -100-б. 2. uz.denemetr.com 3. Олимoв К.Т. Maxcyc фaнлapдaн укув aдaбиëтлapини яpaтишнинг нaзapий вa ycny-бий acocлapи. Педaг. фaн. дoк. ... диc. - Т.: ТДПУ, 2005. -274-б. 3. Олимoв К.Т. Maxcyc фaнлapдaн укув aдaбиëтлapини яpaтишнинг нaзapий вa ycny-бий acocлapи. Педaг. фaн. дoк. ... диc. - Т.: ТДПУ, 2005. -274-б. 4. fayllar.org 4. fayllar.org 5. Mycлимoв Н.А. Электpoн дapcлик яpaтиш метoдик тaмoйиллapи вa теxнoлoгия-лapи. I Infocom.uz, 2004. -62-66-б.
https://openalex.org/W2527123381
https://europepmc.org/articles/pmc5037443?pdf=render
English
null
Layer-specific femorotibial cartilage T2 relaxation time in knees with and without early knee osteoarthritis: Data from the Osteoarthritis Initiative (OAI)
Scientific reports
2,016
cc-by
8,350
Layer-specific femorotibial cartilage T2 relaxation time in knees with and without early knee osteoarthritis: Data from the Osteoarthritis Initiative (OAI) received: 27 April 2016 accepted: 09 September 2016 Published: 27 September 2016 received: 27 April 2016 accepted: 09 September 2016 Published: 27 September 2016 W. Wirth1,2, S. Maschek1,2, F. W. Roemer3,4 & F. Eckstein1,2 Magnetic resonance imaging (MRI)-based spin-spin relaxation time (T2) mapping has been shown to be associated with cartilage matrix composition (hydration, collagen content & orientation). To determine the impact of early radiographic knee osteoarthritis (ROA) and ROA risk factors on femorotibial cartilage composition, we studied baseline values and one-year change in superficial and deep cartilage T2 layers in 60 subjects (age 60.6 ± 9.6 y; BMI 27.8 ± 4.8) with definite osteophytes in one knee (earlyROA, n = 32) and with ROA risk factors in the contralateral knee (riskROA, n = 28), and 89 healthy subjects (age 55.0 ± 7.5 y; BMI 24.4 ± 3.1) without signs or risk factors of ROA. Baseline T2 did not differ significantly between earlyROA and riskROA knees in the superficial (48.0 ± 3.5 ms vs. 48.1 ± 3.1 ms) or the deep layer (37.3 ± 2.5 ms vs. 37.3 ± 1.8 ms). However, healthy knees showed significantly lower superficial layer T2 (45.4 ± 2.3 ms) than earlyROA or riskROA knees (p ≤ 0.001) and significantly lower deep layer T2 (35.8 ± 1.8 ms) than riskROA knees (p = 0.006). Significant longitudinal change in T2 (superficial: 0.5 ± 1.4 ms; deep: 0.8 ± 1.3 ms) was only detected in healthy knees. These results do not suggest an association of early ROA (osteophytes) with cartilage composition, as assessed by T2 mapping, whereas cartilage composition was observed to differ between knees with and without ROA risk factors. Articular cartilage spin-spin (transverse) relaxation time (T2) is known to be associated with cartilage composi- tion (hydration, collagen integrity and orientation)1–3 and has been shown to correlate with histological grading4,5 and cartilage mechanical properties2,6. T2 has thus gained interest as an imaging biomarker for detecting and monitoring “early” stages of osteoarthritis (OA)2,3,7, a stage at which therapeutic intervention is potentially more successful than at more advanced stages of the disease. Several studies have reported T2 to differentiate between subjects with and without radiographic OA (ROA) in femorotibial8,9, patellar10, acetabular11, and gleno-humeral cartilage12. Yet, other studies were unable to confirm differences in cartilage T2 between subjects with and without ROA13, or found T2 to not differentiate between different stages of OA8. www.nature.com/scientificreports www.nature.com/scientificreports www.nature.com/scientificreports Scientific Reports | 6:34202 | DOI: 10.1038/srep34202 Methods d At each of 5 sub- sequent annual visits (baseline through 48 month follow-up), the OAI collected clinical data and acquired both 3T MRI of the knees19 and bilateral fixed-flexion radiographs.h il g p The primary comparison of knees with and without early ROA was performed in a cohort of OAI participants with unilateral early ROA that has been described in previous publications20,21, and was selected based on the following criteria: (1) A definite osteophyte in one knee (definite ROA), based on the OAI site readings, 1) A definite osteophyte in one knee (definite ROA), based on the OAI site readings,i ii (2) no definite or possible osteophyte in the contralateral knee, ii (2) no definite or possible osteophyte in the contralateral knee, i 3) no radiographic joint space narrowing (JSN) in either knee, according to the OARSI atlas. i (3) no radiographic joint space narrowing (JSN) in either knee, according to the OARSI atlas This specific choice in OAI participants, in particular exclusion of any radiographic JSN, was made, so that the analysis of cartilage T2 was restricted to the early stages of ROA, i.e. formation of an osteophyte in one knee, whereas the other knee still is free of any sign of radiographic change. According to the site radiographic read- ings, these specific conditions were fulfilled by 84 of the 4796 OAI participants. All cases were then reviewed by an expert musculoskeletal radiologist (F.R.), who confirmed these specific radiographic selection criteria in 61 of the 84 participants20,21. In previous analyses of this very same sample of 61 subjects20,21, we observed the cartilage thickness at baseline in the external medial and lateral femur to be greater in earlyROA knees than in contra-lateral riskROA knees20. However, we did not observe a significant longitudinal change in femorotibial cartilage thickness in either the earlyROA (osteophyte) knees or in the contralateral riskROA knees over a one year follow-up period, using the same regions of interest as studied here21. y p p g g Further, our analysis included participants from the OAI “non-exposed”, healthy reference cohort. Of the 122 healthy reference cohort participants, 92 had follow-up MR images and were confirmed to be free of any radio- graphic abnormalities by the central radiographic readings18 in addition to being free of OA risk factors18,22. Layer-specific femorotibial cartilage T2 relaxation time in knees with and without early knee osteoarthritis: Data from the Osteoarthritis Initiative (OAI) Further, knee cartilage T2 was reported to be longer and more heterogeneous in subjects at risk of developing OA than in healthy reference subjects, despite similar prevalence of cartilage, bone marrow or meniscus lesions14.fi p g However, few studies have differentially analyzed laminar (superficial and deep zone) cartilage T2 in context of ROA status, although it has been recognized that (a) superficial cartilage displays significantly longer T2 than deep zone cartilage2,15; (b) spatial assessment of knee cartilage T2 using laminar and texture analysis may improve discrimination of cartilage matrix abnormalities in OA16, and (c) superficial zone cartilage was more sensitive to the presence of semi-quantitatively graded cartilage lesions than deep layer cartilage, and thus potentially more sensitive in detecting compositional differences of the cartilage in the early stages of knee OA17. 1Institute of Anatomy, Paracelsus Medical University Salzburg & Nuremberg, Salzburg, Austria. 2Chondrometrics GmbH, Ainring, Germany. 3Department of Radiology, University of Erlangen-Nuremberg, Erlangen, Germany. 4Quantitative Imaging Center (QIC), Department of Radiology, Boston University School of Medicine, Boston, MA, USA. Correspondence and requests for materials should be addressed to W.W. (email: wolfgang.wirth@pmu.ac.at) Scientific Reports | 6:34202 | DOI: 10.1038/srep34202 www.nature.com/scientificreports/ The purpose of the current study therefore was to investigate whether superficial and deep zone femorotibial cartilage T2 times differ cross-sectionally between knees with and without early ROA, and/or between knees with and without risk factors of OA. Secondly, we studied whether longitudinal change in cartilage T2 times over 1-year differ between knees with and without early ROA, and/or between knees with and without risk factors of OA. Methods d Study participants. The participants for this analysis were selected from the Osteoarthritis Initiative cohort (OAI; http://www.oai.ucsf.edu/, clinicaltrials.gov identifier: NCT00080171)18. The OAI was approved by the Committee on Human Research, the Institutional Review Board for the University of California, San Francisco (UCSF). All OAI participants provided written informed consent and this study was carried out in accordance with the IRB-approved OAI data user agreement. At baseline, the OAI cohort included 4796 participants aged 45–79 years that were recruited at one of four clinical sites18. General exclusion criteria of the OAI were presence of rheumatoid or other inflammatory arthritis, bilateral end-stage knee OA, inability to walk without aids, and MRI contraindications18. Of the 4796 participants, the 1390 participants enrolled in the progression cohort had both symptomatic (i.e. pain, aching or stiffness in the past year) and radiographic OA (osteophytes and/or joint space narrowing in fixed-flexion radiographs) in one or both of their knees. The 3284 incidence cohort partici- pants were at risk of developing knee OA, but did not have both symptomatic and radiographic OA at baseline in either knee. The remaining 122 participants of the OAI were selected as “non-exposed”, healthy controls and had no radiographic abnormalities in either knee according to the OAI clinical site readings18. These participants also were free of clinical signs of knee OA, and not exposed to risk factors for developing knee OA, such as obesity, knee injury, knee surgery, a family history of TKA in a biological parent or sibling, Heberden’s nodes, or repetitive knee bending during daily activities. For further details on these OA cohorts, please see ref. 18. Methods d Three participants, who developed early signs of radiographic OA (KLG 1) at the 1 year follow-up, were excluded from the analysis, resulting in 89 healthy reference participants included in the analysis. MR Imaging. Sagittal 3 Tesla multi-echo spin-echo (MESE) MR images were acquired for cartilage T2 analy- ses in one of the knees of all OAI participants (usually the right knee, Fig. 1)18,19. The repetition time was 2700 ms, and the echo times were 10, 20, 30, 40, 50, 60, and 70 ms (slice thickness 3.0 mm, in-plane resolution 0.3125 mm). All imaging parameters were kept constant between baseline and follow-up. Baseline MR images for one of the knees were available for 60 of the 61 participants and 1-year follow-up MR images were available for 50 of the 61 participants. In 32 participants, the MESE images (of the right knee) happened to be available for the knee with osteophytes (earlyROA); in 28 participants, the MESE images (of the right knee) happened to be available for the contralateral knee without osteophytes (riskROA). MESE images were available for all 92 healthy reference knees. T2 analysis of femorotibial cartilage. Segmentation of the cartilage of the medial and lateral tibia (MT/ LT) and the medial and lateral weight-bearing femoral condyles (cMF/cLF) was performed manually in the MESE MR images by experienced readers, by processing all images that displayed tibial and weight-bearing cartilage across the entire knee (Fig. 1)23. The tibial cartilage was segmented from its anterior to posterior end, and the femoral cartilage throughout a weight-bearing region of interest, as defined previously24. Baseline and follow-up images were displayed simultaneously, in order to ensure a consistent selection of the region of interest analyzed in the longitudinal analysis, but with the readers blinded to acquisition dates in order to exclude bias. Because cartilage T2 is known to display spatial variation with tissue depth2,15, the segmented cartilages were then compu- tationally divided into the top (superficial) and bottom (deep) 50%, based on the local distance between the seg- mented cartilage surface and bone interface23 (Fig. 1). Cartilage T2 times (in ms) were computed for each voxel by fitting a mono-exponential decay curve to the measured signal intensities using a non-linear method25 (1), Scientific Reports | 6:34202 | DOI: 10.1038/srep34202 2 www.nature.com/scientificreports/ Figure 1. Sagittal multi-echo spin-echo (MESE) images showing the medial tibia (MT) and the medial femur (MF). Methods d (A–C) MESE images with the shortest (10 ms, A), an intermediate (40 ms, B), and the longest echo time (70 ms, C). (D) T2 map of the (medial) femorotibial cartilages, with values demonstrated by color coding. (E) T2 map showing the region of interest used to define the central, weight-bearing part of the MF (cMF). (F) T2 map showing the segmentation of the MT and the cMF. Figure 1. Sagittal multi-echo spin-echo (MESE) images showing the medial tibia (MT) and the medial femur (MF). (A–C) MESE images with the shortest (10 ms, A), an intermediate (40 ms, B), and the longest echo time (70 ms, C). (D) T2 map of the (medial) femorotibial cartilages, with values demonstrated by color coding. (E) T2 map showing the region of interest used to define the central, weight-bearing part of the MF (cMF). (F) T2 map showing the segmentation of the MT and the cMF. with the 1st echo (10 ms) excluded to reduce the impact of stimulated echoes2. Voxels with R2 <​ 0.66 for the curve fitting were eliminated, to avoid contribution from voxels with low image quality23. Statistical analysis. Statistical analyses were conducted using IBM SPSS 22 software (IBM Corporation, Armonk, NY). The primary analytic focus was to determine whether baseline T2 values (in ms) in superficial or deep femorotibial cartilage layers averaged over all four femorotibial plates differed between “earlyROA” knees with osteophytes and between “riskROA” knees that were exposed to the same risk factors, but were yet with- out osteophytes. The co-primary analytic focus was then to compare “earlyROA” and “riskROA” knees with the healthy reference knees not exposed to OA risk factors. In view of the 6 parallel comparison made (3 groups ×​ 2 layers), a p-value of <​0.00833 (=​0.05/6) was deemed to indicate statistical significance. Crude analyses were performed using unpaired, two-sided t-tests. An ANCOVA was then used to check whether the results were con- sistent when adjusting for age, sex, and BMI. Cohen D was used as a measure of effect size.h j g gf The secondary analytic focus was on whether longitudinal (one year) change in T2 values (in ms) in the super- ficial or deep femorotibial cartilage layers differed between the three groups and the same statistical approaches were used as for the baseline comparison. To that end, change in T2 was measured in each individual and then averaged across the cohort. Methods d A paired, two-sided t-test was used to evaluate within-knee change between baseline and follow-up for each layer and group, with p <​ 0.05 indicating a significant change over time in a descriptive context. A paired, two-sided t-test was also used to evaluate whether longitudinal change in the superficial layer T2 was stronger than that in deep layer T2. These tests were also performed for the four femorotibial cartilage plates separately, but no further adjustments for multiple parallel statistical testing were made in view of the exploratory nature of these analyses. Results D Demographics and qualitative observations. The 32 earlyROA knees were from participants who were 60.2 ±​ 10.0 y old, with a BMI of 27.6 ±​ 4.6 (56% female) and the 28 riskROA knees were from participants who were 61.1 ±​ 9.4 y old, with a BMI of 28.0 ±​ 5.0 (50% female, Table 1). The 89 healthy reference participants were 55.0 ±​ 7.5 y old, with a BMI of 24.4 ±​ 3.1 (60% female) and hence were significantly younger and less obese (both p ≤​ 0.001) than both the riskROA and earlyROA participants. The differences in age and BMI between the riskROA and the earlyROA participants were not statistically significant (p ≥​ 0.35). No significant between-group differences were observed for the cartilage thickness or minimum radiographic joint space width at baseline (Table 1). Results D minJSW: Minimum radiographic joint space width from fixed-flexion x-rays. MFTC/LFTC.ThC: Mean cartilage thickness in the medial/lateral femorotibial compartment. The height measurement was missing for one of the participants from the risk ROA group. Risk ROA (N = 28) Mean ± SD (95% CI) Early ROA (N = 32) Mean ± SD (95% CI) Healthy (N = 89) Mean ± SD (95% CI) Risk ROA vs. Early ROA Crude/Adjusted Cohen’s D Risk ROA vs. Healthy Crude/Adjusted Cohen’s D Early ROA vs. Healthy Crude/Adjusted Cohen’s D Avg Deep 37.3 ±​ 1.8 37.3 ±​ 2.5 35.8 ±​ 1.8 0.983/0.984 <​0.001/0.006 <​0.001/0.011 (36.6, 38.0) (36.4, 38.2) (35.4, 36.2) 0.01 0.81 0.73 Superficial 48.1 ±​ 3.1 48.0 ±​ 3.5 45.4 ±​ 2.3 0.932/0.931 <​0.001/0.001 <​0.001/<​0.001 (46.9, 49.3) (46.7, 49.3) (44.9, 45.9) 0.02 1.04 0.96 MT Deep 34.0 ±​ 1.8 33.3 ±​ 1.8 33.0 ±​ 1.9 0.140/0.137 0.020/0.401 0.511/0.509 (33.3, 34.7) (32.6, 33.9) (32.6, 33.4) 0.39 0.51 0.14 Superficial 43.6 ±​ 2.5 43.4 ±​ 2.9 41.6 ±​ 2.9 0.812/0.902 0.001/0.006 0.002/0.004 (42.6, 44.5) (42.4, 44.5) (40.9, 42.2) 0.06 0.72 0.64 cMF Deep 41.8 ±​ 3.8 42.5 ±​ 5.9 39.3 ±​ 3.4 0.595/0.628 0.001/0.008 <​0.001/0.007 (40.4, 43.3) (40.4, 44.6) (38.6, 40.1) 0.14 0.71 0.76 Superficial 52.8 ±​ 5.8 53.4 ±​ 6.0 49.6 ±​ 3.8 0.662/0.683 0.001/0.027 <​0.001/0.001 (50.5, 55.0) (51.3, 55.6) (48.8, 50.4) 0.11 0.72 0.86 LT Deep 32.0 ±​ 1.4 32.5 ±​ 2.1 31.0 ±​ 1.9 0.350/0.377 0.012/0.031 0.001/0.003 (31.5, 32.6) (31.7, 33.2) (30.6, 31.4) 0.24 0.55 0.73 Superficial 45.5 ±​ 3.6 44.5 ±​ 4.3 42.4 ±​ 2.6 0.368/0.390 <​0.001/<​0.001 0.001/0.006 (44.1, 46.9) (43.0, 46.1) (41.9, 43.0) 0.23 1.07 0.67 cLF Deep 41.2 ±​ 2.8 40.8 ±​ 3.2 39.7 ±​ 2.8 0.622/0.542 0.013/0.082 0.059/0.123 (40.1, 42.3) (39.7, 41.9) (39.1, 40.3) 0.13 0.54 0.39 Superficial 50.5 ±​ 4.1 50.7 ±​ 4.0 48.1 ±​ 2.9 0.901/0.969 0.001/0.007 <​0.001/0.001 (48.9, 52.1) (49.2, 52.1) (47.4, 48.7) 0.03 0.76 0.80 Table 2. Baseline T2 values in knees without ROA but with risk factors for ROA (risk ROA), in knees with early ROA, and in healthy reference knees. SD =​ standard deviation; Avg =​ average values across all four femorotibial cartilage plates; MT =​ medial tibia; cMF =​ weight-bearing (central) medial femur; LT =​ lateral tibia; cLF =​ weight-bearing (central) lateral femur; for a definition of the regions of interest, please also see Fig. 1. Table 2. Results D BL =​ Baseline; Y1 =​ year 1 follow-up; SD =​ standard deviation; Risk ROA: Participants without ROA but with risk factors for ROA in the analyzed knee; Early ROA: Participants with early ROA in the analyzed knee; Healthy: Participants from the healthy reference cohort; Values in brackets show the demographic data for the participants from the risk ROA and early ROA group, for which no Y1 follow-up MR images were available. minJSW: Minimum radiographic joint space width from fixed-flexion x-rays. MFTC/LFTC.ThC: Mean cartilage thickness in the medial/lateral femorotibial compartment. The height measurement was missing for one of the participants from the risk ROA group. Table 1. Participant demographics. BL =​ Baseline; Y1 =​ year 1 follow-up; SD =​ standard deviation; Risk ROA: Participants without ROA but with risk factors for ROA in the analyzed knee; Early ROA: Participants with early ROA in the analyzed knee; Healthy: Participants from the healthy reference cohort; Values in brackets show the demographic data for the participants from the risk ROA and early ROA group, for which no Y1 follow-up MR images were available. minJSW: Minimum radiographic joint space width from fixed-flexion x-rays. MFTC/LFTC.ThC: Mean cartilage thickness in the medial/lateral femorotibial compartment. The height measurement was missing for one of the participants from the risk ROA group. Table 1. Participant demographics. BL =​ Baseline; Y1 =​ year 1 follow-up; SD =​ standard deviation; Risk ROA: Participants without ROA but with risk factors for ROA in the analyzed knee; Early ROA: Participants with early ROA in the analyzed knee; Healthy: Participants from the healthy reference cohort; Values in brackets show the demographic data for the participants from the risk ROA and early ROA group, for which no Y1 follow-up MR images were available. minJSW: Minimum radiographic joint space width from fixed-flexion x-rays. MFTC/LFTC.ThC: Mean cartilage thickness in the medial/lateral femorotibial compartment. The height measurement was missing for one of the participants from the risk ROA group. Table 1. Participant demographics. BL =​ Baseline; Y1 =​ year 1 follow-up; SD =​ standard deviation; Risk ROA: Participants without ROA but with risk factors for ROA in the analyzed knee; Early ROA: Participants with early ROA in the analyzed knee; Healthy: Participants from the healthy reference cohort; Values in brackets show the demographic data for the participants from the risk ROA and early ROA group, for which no Y1 follow-up MR images were available. Results D Only one knee from the risk ROA group showed an increase (from KLG 0 to KLG2) over the one-year follow-up period according to the OAI central KLG readings (incident definite medial compartment osteophytes, but no joint space narrowing).i j p g In all groups and cartilage plates, cartilage T2 was longer in the superficial than in the deep cartilage layer (Table 2): In the healthy reference participants, the femorotibial baseline cartilage T2 in the superficial layer was 9.6 ±​ 2.2 ms longer (95% CI [9.2, 10.1] ms) than in the deep layer and similar differences were observed in the earlyROA (10.7 ±​ 2.5 ms, 95% CI [9.8, 11.6] ms) and in the riskROA knees (10.8 ±​ 2.0 ms, 95% CI [10.0, 11.6] Scientific Reports | 6:34202 | DOI: 10.1038/srep34202 3 www.nature.com/scientificreports/ Risk ROA BL (n = 28) (BL & Y1, n = 26) Early ROA BL (n = 32) (BL & Y1, n = 24) Healthy BL & Y1 (n = 89) Male N/% 14/50.0% (14/53.8%) 14/43.8% (10/41.7%) 36/40.4% Female N/% 14/50.0% (12/46.2%) 18/56.3% (14/58.3%) 53/59.6% No pain N/% 14/50.0% (12/46.2%) 10/31.3% (8/33.3%) 89/100.0% Infrequent pain N/% 8/28.6% (8/30.8%) 12/37.5% (9/37.5%) 0/0.0% Frequent pain N/% 6/21.4% (6/23.1%) 10/31.1% (7/29.2%) 0/0.0% Age [years] Mean ±​ SD 61.1 ±​ 9.4 (60.7 ±​ 9.6) 60.2 ±​ 10.0 (61.5 ±​ 9.8) 55.0 ±​ 7.5 BMI [kg/m2] Mean ±​ SD 28.0 ±​ 5.0 (28.1 ±​ 5.2) 27.6 ±​ 4.6 (27.4 ±​ 4.2) 24.4 ±​ 3.1 Weight [kg] Mean ±​ SD 80.2 ±​ 15.6 (81.3 ±​ 15.5) 76.4 ±​ 15.5 (76.3 ±​ 13.6) 69.1 ±​ 12.0 Height [cm] Mean ±​ SD 168.3 ±​ 8.4 (169.2 ±​ 7.9) 166.2 ±​ 9.2 (166.9 ±​ 9.3) 167.8 ±​ 8.8 minJSW [mm] Mean ±​ SD 4.9 ±​ 1.0 (4.9 ±​ 1.0) 4.6 ±​ 0.8 (4.7 ±​ 0.7) 4.8 ±​ 0.8 MFTC.ThC [mm] Mean ±​ SD 3.5 ±​ 0.5 (3.5 ±​ 0.5) 3.5 ±​ 0.5 (3.6 ±​ 0.5) 3.4 ±​ 0.5 LFTC.ThC [mm] Mean ±​ SD 3.9 ±​ 0.5 (4.0 ±​ 0.4) 4.1 ±​ 0.5 (4.1 ±​ 0.5) 3.8 ±​ 0.5 Table 1. Participant demographics. Results D Baseline T2 values in knees without ROA but with risk factors for ROA (risk ROA), in knees with early ROA, and in healthy reference knees. SD =​ standard deviation; Avg =​ average values across all four femorotibial cartilage plates; MT =​ medial tibia; cMF =​ weight-bearing (central) medial femur; LT =​ lateral tibia; cLF =​ weight-bearing (central) lateral femur; for a definition of the regions of interest, please also see Fig. 1. ms). Baseline T2 was consistently longer in the weight-bearing femoral cartilage than in the tibial cartilage, with differences of 5–10 ms across cartilage layers (superficial vs. deep), compartments (medial vs. lateral), and groups (Table 2). Baseline cartilage T2 values were, however, similar between the medial and lateral femorotibial com- partment, with differences of <​3 ms across the different layers, plates and groups (Table 2). ms). Baseline T2 was consistently longer in the weight-bearing femoral cartilage than in the tibial cartilage, with differences of 5–10 ms across cartilage layers (superficial vs. deep), compartments (medial vs. lateral), and groups (Table 2). Baseline cartilage T2 values were, however, similar between the medial and lateral femorotibial com- partment, with differences of <​3 ms across the different layers, plates and groups (Table 2). Baseline between-group T2 analysis. No statistically significant difference in baseline T2 was detected between the 32 earlyROA knees and the 28 riskROA knees from the 60 participants with discordant osteophyte status (Table 2). The mean crude difference between these groups across the femorotibial cartilages was 0.1 ms (95% CI [−​1.7, 1.8] ms; p =​ 0.93) for the superficial layer T2, and 0.0 ms (95% CI [−​1.2, 1.1] ms; p =​ 0.98) for the Baseline between-group T2 analysis. No statistically significant difference in baseline T2 was detected between the 32 earlyROA knees and the 28 riskROA knees from the 60 participants with discordant osteophyte status (Table 2). The mean crude difference between these groups across the femorotibial cartilages was 0.1 ms (95% CI [−​1.7, 1.8] ms; p =​ 0.93) for the superficial layer T2, and 0.0 ms (95% CI [−​1.2, 1.1] ms; p =​ 0.98) for the Scientific Reports | 6:34202 | DOI: 10.1038/srep34202 4 www.nature.com/scientificreports/ Risk ROA (N = 26) Mean ± SD (95% CI) Early ROA (N = 24) Mean ± SD (95% CI) Healthy (N = 89) Mean ± SD (95% CI) Risk ROA vs. Early ROA Crude/Adjusted Cohen’s D Risk ROA vs. Results D The mean crude difference between healthy vs riskROA knees was −​2.7 ms (95% CI [−​3.8, −​1.6] ms; p <​ 0.001) for superficial T2, and −​1.5 ms (95% CI [−​2.3, −​0.7] ms; p <​ 0.001) for deep layer T2; the difference was greater for superficial (Cohen’s D =​ 1.04) than for deep cartilage (Cohen’s D =​ 0.81) and remained statistically significant when adjusting for age, sex, and BMI (Table 2). The mean crude difference between healthy and earlyROA knees was −​2.6 ms (95% CI [−​3.7, −​1.5] ms; p <​ 0.001) for superficial layer T2, and −​1.5 ms (95% CI [−​2.3, −​0.7] ms; p <​ 0.001) for deep layer T2; the differ- ence was again greater for the superficial (Cohen D =​ 0.96) than for the deep cartilage layers (Cohen D =​ 0.73). When adjusting for age, sex, and BMI, the difference remained statistically significant for the superficial layer (p <​ 0.001), but did not reach the adjusted significance level (p <​ 0.0083) for the deep layer (p =​ 0.01, Table 2). Table 2 also shows the results for superficial and deep layers in the four femorotibial cartilage plates separately. Longitudinal between-group T2 analysis. No statistically significant longitudinal change was noted in either the superficial or deep femorotibial cartilage layers of riskROA (p ≥​ 0.27, Table 3) or earlyROA knees (p ≥​ 0.41, Table 3). However, a significant increase in T2 between baseline and 1-year follow-up was noted in healthy reference knees across superficial (0.5 ±​ 1.4 ms; 95% CI [0.2, 0.9] ms; p <​ 0.001) and deep (0.8 ±​ 1.3 ms; 95% CI [0.5, 1.1] ms; p <​ 0.001) femorotibial cartilage (Table 3); the rate of change differed significantly between both layers (p =​ 0.04). These longitudinal changes in femorotibial cartilage T2 in healthy reference knees were significantly greater than in the riskROA and earlyROA knees (Table 3); however, the difference only remained statistically significant for the deep layer in earlyROA vs. healthy reference knees when adjusting for age, sex, BMI, and multiple comparisons (Table 3). Table 3 also shows the results for superficial and deep layers in the 4 cartilage plates separately. Results D Healthy Crude/Adjusted Cohen’s D Early ROA vs. Healthy Crude/Adjusted Cohen’s D Avg Deep 0.0 ±​ 1.7 −​0.2 ±​ 1.1 0.8 ± 1.3 0.684/0.583 0.010/0.032 0.001/0.002 (−​0.7, 0.7) (−​0.6, 0.3) (0.5, 1.1) 0.12 0.58 0.78 Superficial −​0.4 ±​ 1.8 −​0.1 ±​ 1.5 0.5 ± 1.4 0.581/0.694 0.006/0.024 0.041/0.029 (−​1.1, 0.3) (−​0.8, 0.5) (0.2, 0.9) 0.16 0.62 0.48 MT Deep −​0.3 ±​ 1.8 0.0 ±​ 1.6 0.8 ± 1.7 0.504/0.533 0.003/0.013 0.033/0.082 (−​1.1, 0.4) (−​0.7, 0.7) (0.5, 1.2) 0.19 0.67 0.50 Superficial −​0.4 ±​ 1.8 0.1 ±​ 1.8 0.7 ± 1.8 0.323/0.358 0.008/0.044 0.175/0.202 (−​1.2, 0.3) (−​0.7, 0.9) (0.3, 1.0) 0.28 0.60 0.31 cMF Deep 0.3 ±​ 2.9 −​0.3 ±​ 2.5 1.0 ± 2.1 0.461/0.409 0.169/0.314 0.012/0.019 (−​0.9, 1.4) (−​1.3, 0.7) (0.5, 1.4) 0.21 0.31 0.59 Superficial −​0.5 ±​ 4.5 −​0.5 ±​ 4.2 0.4 ±​ 2.6 0.993/0.904 0.195/0.219 0.196/0.060 (−​2.3, 1.3) (−​2.3, 1.3) (−​0.1, 0.9) 0.00 0.29 0.30 LT Deep −​0.1 ±​ 1.9 −​0.2 ±​ 0.9 0.9 ± 1.5 0.730/0.512 0.010/0.026 0.001/0.002 (−​0.9, 0.7) (−​0.6, 0.1) (0.5, 1.2) 0.10 0.58 0.77 Superficial −​0.2 ±​ 1.8 −​0.1 ±​ 0.9 0.6 ± 1.5 0.872/0.937 0.024/0.089 0.025/0.041 (−​0.9, 0.5) (−​0.5, 0.3) (0.3, 0.9) 0.05 0.51 0.52 cLF Deep 0.1 ±​ 1.8 −​0.2 ±​ 1.3 0.6 ± 1.8 0.545/0.516 0.182/0.227 0.038/0.023 (−​0.6, 0.9) (−​0.7, 0.4) (0.3, 1.0) 0.17 0.30 0.48 Superficial −0.5 ± 1.0 0.0 ±​ 1.1 0.6 ± 2.1 0.133/0.138 0.020/0.056 0.212/0.334 (−0.9, −0.1) (−​0.5, 0.4) (0.1, 1.0) 0.43 0.52 0.29 Table 3. Longitudinal (one year) change in T2 values in knees without ROA but with risk factors for ROA (risk ROA), in knees with early ROA, and in healthy reference knees. SD =​ standard deviation; Avg =​ average values across all four femorotibial cartilage plates; MT =​ medial tibia; cMF =​ weight-bearing (central) medial femur; LT =​ lateral tibia; cLF =​ weight-bearing (central) lateral femur; for a definition of the regions of interest, please also see Fig. 1; significant change between baseline and one year follow up with p <​ 0.05 is marked in italics, and with p <​ 0.01 in bold letters. Table 3. Longitudinal (one year) change in T2 values in knees without ROA but with risk factors for ROA (risk ROA), in knees with early ROA, and in healthy reference knees. Results D SD =​ standard deviation; Avg =​ average values across all four femorotibial cartilage plates; MT =​ medial tibia; cMF =​ weight-bearing (central) medial femur; LT =​ lateral tibia; cLF =​ weight-bearing (central) lateral femur; for a definition of the regions of interest, please also see Fig. 1; significant change between baseline and one year follow up with p <​ 0.05 is marked in italics, and with p <​ 0.01 in bold letters. deep layer T2. The ANCOVA analysis with adjustment for differences in age, sex, and BMI resulted in compara- ble, non-significant p-values (Table 2). p yh y jf g p ble, non-significant p-values (Table 2). Overall, the femorotibial T2 values were observed to be shorter in the 92 non-exposed healthy reference cohort knees than in the earlyROA and riskROA knees (Table 2). The mean crude difference between healthy vs riskROA knees was −​2.7 ms (95% CI [−​3.8, −​1.6] ms; p <​ 0.001) for superficial T2, and −​1.5 ms (95% CI [−​2.3, −​0.7] ms; p <​ 0.001) for deep layer T2; the difference was greater for superficial (Cohen’s D =​ 1.04) than for deep cartilage (Cohen’s D =​ 0.81) and remained statistically significant when adjusting for age, sex, and BMI (Table 2). The mean crude difference between healthy and earlyROA knees was −​2.6 ms (95% CI [−​3.7, −​1.5] ms; p <​ 0.001) for superficial layer T2, and −​1.5 ms (95% CI [−​2.3, −​0.7] ms; p <​ 0.001) for deep layer T2; the differ- ence was again greater for the superficial (Cohen D =​ 0.96) than for the deep cartilage layers (Cohen D =​ 0.73). When adjusting for age, sex, and BMI, the difference remained statistically significant for the superficial layer (p <​ 0.001), but did not reach the adjusted significance level (p <​ 0.0083) for the deep layer (p =​ 0.01, Table 2). Table 2 also shows the results for superficial and deep layers in the four femorotibial cartilage plates separately. p yh y jf g p ble, non-significant p-values (Table 2). Overall, the femorotibial T2 values were observed to be shorter in the 92 non-exposed healthy reference cohort knees than in the earlyROA and riskROA knees (Table 2). Discussion This interpretation is supported by a study that identified significant differences in glenohumeral cartilage T2 of subjects with primary OA (which supposedly suffered from common OA risk factors) versus those without OA, but not in those with secondary (post-traumatic) OA versus those without OA12. Nevertheless, fur- ther studies with larger number of participants should be performed to confirm this hypothesis and to identify the specific set of risk factors responsible for longer cartilage T2. pi p g g The results of the longitudinal analysis are somewhat puzzling. Although we have previously shown that the early ROA and non-ROA knees studied here did not display measureable changes in cartilage thickness over one year of follow-up21, and although is well known that cartilage T2 increases with age2,33, we have no convincing explanation why a significant increase was detectable in healthy reference participants over a relatively short (one-year) observation interval, while no change was observed in ROA and non-ROA knees with risk factors of OA. It is, however, unlikely that the increase observed in the healthy reference cohort was caused by the analysis method used in the current study, because the readers were blinded to the acquisition order and dates during the analysis to avoid a potential systematic bias and because random precision errors would not have affected all car- tilages in such a consistent manner. Potentially, the “ceiling effect” discussed previously might be responsible for the stable cartilage T2 times observed in the ROA and non-ROA knees. Further, T2 shortening has been observed in some cases when further cartilage degradation occurs. When this is the case, the average T2 of degraded car- tilage may actually remain stable, whereas the variability in T2 may continue to increase. Therefore, T2 texture analysis14,34 of femorotibial cartilage may be used in future studies, to test this hypothesis. Previously, Stahl et al. also were unable to demonstrate significant change in T2 over one year in age-matched subjects with and without OA9, but the sample (n =​ 8 vs. 10) was relatively small. Baum et al.35, in contrast, reported cartilage T2 to significantly increase over 2 years in subjects with and without OA risk factors, but neither presence of risk factors nor the presence of baseline cartilage lesions were significantly associated with the increase in femorotibial cartilage T2. Discussion Using a laminar analysis approach, femorotibial cartilage T2 was not observed to differ significantly between knees with definite early ROA and knees that had risk factors for developing knee OA in cross-sectional anal- yses, in either superficial or deep femorotibial cartilage layers. It is important to note that, in contrast to previ- ous studies, the knees with and without established ROA had similar risk factors, in that they had an identical contra-lateral knee OA status (no ROA in case of earlyROA knees, and earlyROA for in case of no ROA knees). Preferably, we would have directly compared femorotibial cartilage T2 between the earlyROA and the con- tralateral riskROA knee of the same person (between-knee, within-person comparison), as previously done for Scientific Reports | 6:34202 | DOI: 10.1038/srep34202 5 www.nature.com/scientificreports/ cartilage thickness20,21. However, this was impossible, because the OAI only acquired MESE images of the right knees in each participant. Yet, comparing right knees with osteophytes (early ROA) and right knees without osteophytes (riskROA) in the above sample with discordant osteophyte status was selected as the “next best” approach, because contra-lateral knee ROA status has been identified as an important predictor of progression of knee OA26 and by proceeding as described, knees with and without ROA were both selected based on a similar background of risk factors for developing ROA per inclusion criteria. A potential explanation of the observations made is that T2 changes occur “very early” in the disease process and are irreversible, once present. The lack of differentiation between the earlyROA and riskROA knees may be a result of a ceiling effect, with the cartilage T2 changes having occurred in both earlyROA and riskROA knees already, without progressing any further.fi g g y y p g g y In contrast, femorotibial cartilage T2 differed significantly between knees from the healthy reference cohort when compared to both knees with risk factors for developing OA and established early ROA; this difference remained significant when adjusting for age, sex and BMI. Interestingly, the differences between knees with and without knee OA risk factors were greater for superficial than for deep femorotibial cartilage layers, indi- cating that superficial T2 maybe more sensitive to variation of cartilage composition with risk factor status of OA. These results extend previous findings of superficial zone cartilage being more sensitive to the presence of semi-quantitatively graded cartilage lesions than deep (bone) layer cartilage17. Discussion q y g g p ( ) y g A limitation of our study is that cartilage lesion scores were not available for the knees studied, but it has been previously reported that OAI knees with risk factors (but without ROA) had similar prevalence of cartilage, bone marrow and meniscus lesions as participants of the OAI healthy reference cohort14. Another limitation of this study is the lack of study-specific data on the test-retest precision of cartilage T2 values for the manual segmen- tation method used in this study. However, previous studies have shown a good test-retest precision for cartilage morphometry analyses using the same quality-controlled manual segmentation method and the same definition for the central, weight-bearing parts of the femur27,28. In addition, previous studies reported adequate test-retest precision errors for cartilage T2 analyses2,15,29 and the OAI used a continuous quality assurance process to ensure the long-term stability and quality of the MRI acquisitions30. Despite discordant ROA status, no significant differ- ences in cartilage T2 times were observed between knees with and contralateral knees without osteophytes (early vs. risk ROA) in the cross-sectional analysis; in contrast, cartilage T2 was significantly lower in knees from the healthy reference cohort than in risk and early ROA knees (with and without osteophytes). The participants in the healthy reference cohort were enrolled based on not being exposed to risk factors of developing OA, whereas the participants with unilateral knee OA were from the OAI incidence or progression cohort and displayed risk factors of incident OA that made them eligible for participating in the OAI. The results therefore indicate that it is the risk factors of incident knee OA that affect the cartilage T2, rather than radiographic status (presence of osteophytes). Previous studies have demonstrated an effect of BMI on cartilage T231,32, a known risk factor of incident OA. It is beyond the scope of the current paper to identify specific risk factors that may be responsible for alterations in cartilage T2, but it is important to note that, in the presence of risk factors, presence of osteophytes does not appear to affect cartilage T2. The cross-sectional findings of the current study therefore indicate that the differences in cartilage T2 observed between knees with divergent ROA status reported in previous studies8–12 may actually be due to differences in risk factor profiles between cohorts rather than due to actual differences in ROA status. Scientific Reports | 6:34202 | DOI: 10.1038/srep34202 Conclusion In conclusion, this study did not identify differences in superficial or deep femorotibial cartilage T2 between knees with definite early ROA and contralateral knees without signs of ROA but with risk factors for developing OA. However, significant differences in T2 were detected between knees from subjects without vs. those with risk factors of OA. These differences were stronger for superficial than for deep cartilage T2 and prevailed when adjusting for age, sex and BMI. Over 1 year, a longitudinal increase in T2 was noted in the superficial and deep layers of healthy reference subjects without risk factors, but not in knees with early ROA or at risk of developing OA. These results suggest that differences in cartilage T2 previously observed between ROA and non-ROA car- tilage may actually be due to differences in risk factor profiles between cohorts rather than to actual differences in ROA status. Discussion Although one study reported an inverse correlation of longitudinal T2 changes over 2 years versus baseline T2 values and morphological cartilage abnormalities7, cartilage lesions and other structural abnormalities on MRI were observed to be similar between healthy reference subjects and those with risk factors of OA (but without ROA)14, and thus this observation does not provide a likely explanation for the observed difference in longitudi- nal T2 change between healthy reference knees and knees with risk factors of knee OA. Hence, further studies are needed to elucidate during which OA disease stages, and under which conditions, longitudinal T2 changes occur in femorotibial cartilage, and whether some currently unknown phenomena may be in place that inhibit normal age-related increase of cartilage T22,33 to be detectable in specific stages of early OA. Scientific Reports | 6:34202 | DOI: 10.1038/srep34202 6 www.nature.com/scientificreports/ Radiography is frequently used for the enrollment of participant in studies, because radiographic scores (e.g. KLG or JSN) have been shown to discriminate between knees with and without subsequent cartilage loss36,37 and because the technique is affordable for large studies. Although systematically comparing cartilage T2 relax- ation parameters between well-defined radiographic strata represents only one of several approaches necessary for qualifying cartilage T2 as a biomarker in (early) knee OA, we feel it is important to relate cartilage T2 to a well-accepted standard of structural staging of knee OA. References References 1. Liess, C., Luesse, S., Karger, N., Heller, M. & Glueer, C. C. Detection of changes in cartilage water content using MRI T2-mapping in vivo. Osteoarthritis.Cartilage. 10, 907–913 (2002). 1. Liess, C., Luesse, S., Karger, N., Heller, M. & Glueer, C. C. Detection of changes in cartilage water content using MRI T2-mapping in vivo. Osteoarthritis.Cartilage. 10, 907–913 (2002). g 2. Mosher, T. J. & Dardzinski, B. J. Cartilage MRI T2 relaxation time mapping: overview and applications. Semin. Musculoskelet. Radiol 8, 355–368 (2004). 3. Baum, T. et al. Cartilage and meniscal T2 relaxation time as non-invasive biomarker for knee osteoarthritis and cartilage repai procedures. Osteoarthr. Cart. 21, 1474–1484 (2013). 4. Kim, T. et al. An in vitro comparative study of T2 and T2* mappings of human articular cartilage at 3-Tesla MRI using histology a the standard of reference. Skelet. Radiol. 43, 947–954 (2014). 5. David-Vaudey, E., Ghosh, S., Ries, M. & Majumdar, S. T2 relaxation time measurements in osteoarthritis. Magn Reson Imaging 22 673–682 (2004). ( ) 6. Lammentausta, E. et al. T2 relaxation time and delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) of human patellar cartilage at 1.5 T and 9.4 T: Relationships with tissue mechanical properties. J. Orthop. Res. 24, 366–374 (2006). g p p p J p , ( ) 7. Jungmann, P. M. et al. T2 relaxation time measurements are limited in monitoring progression, once advanced cartilage defects a the knee occur: Longitudinal data from the osteoarthritis initiative. J. Magn Reson. 38, 1415–1424 (2013). 8. Dunn, T. C., Lu, Y., Jin, H., Ries, M. D. & Majumdar, S. T2 relaxation time of cartilage at MR imaging: comparison with severity o knee osteoarthritis. Radiology 232, 592–598 (2004). gy 9. Stahl, R. et al. MRI-derived T2 relaxation times and cartilage morphometry of the tibio-femoral joint in subjects with and withou osteoarthritis during a 1-year follow-up. Osteoarthritis. Cartilage. 15, 1225–1234 (2007). g y p g 0. Li, X. et al. Spatial distribution and relationship of T1rho and T2 relaxation times in knee cartilage with osteoarthritis. Magn Reson 61, 1310–1318 (2009). 1. Wyatt, C. et al. Cartilage T1rho and T2 Relaxation Times in Patients With Mild-to-Moderate Radiographic Hip Osteoarthritis Arthritis Rheumatol. 67, 1548–1556 (2015). 12. Lee, S. Y. et al. T2 relaxation times of the glenohumeral joint at 3.0 T MRI in patients with and without primary and secondary osteoarthritis. Acta Radiol. 0284185114556304 (2014).f 3. Koff, M. F., Amrami, K. K. References & Kaufman, K. R. Clinical evaluation of T2 values of patellar cartilage in patients with osteoarthritis Osteoarthr. Cart. 15, 198–204 (2007). 4. Joseph, G. B. et al. Texture analysis of cartilage T2 maps: individuals with risk factors for OA have higher and more heterogeneou knee cartilage MR T2 compared to normal controls-data from the osteoarthritis initiative. Arthritis Res. Ther. 13, R153 (2011). h 15. Dardzinski, B. J. & Schneider, E. Radiofrequency (RF) coil impacts the value and reproducibility of cartilage spin-spin (T2) relaxation time measurements. Osteoarthritis Cartilage 21, 710–720 (2013).i g 6. Carballido-Gamio, J. et al. Spatial analysis of magnetic resonance T1rho and T2 relaxation times improves classification between subjects with and without osteoarthritis. Med. Phys. 36, 4059–4067 (2009). j y 7. Schooler, J. et al. Longitudinal evaluation of T1rho and T2 spatial distribution in osteoarthritic and healthy medial knee cartilage Osteoarthr. Cart. 22, 51–62 (2014). 18. Eckstein, F., Wirth, W. & Nevitt, M. C. Recent advances in osteoarthritis imaging-the Osteoarthritis Initiative. Nat. Rev. Rheumatol. 8, 622–630 (2012).h 19. Peterfy, C. G. G., Schneider, E. & Nevitt, M. The osteoarthritis initiative: report on the design rationale for the magnetic resonance imaging protocol for the knee. Osteoarthr. Cart. 16, 1433–1441 (2008). 0. Cotofana, S. et al. Cartilage thickening in early radiographic human knee osteoarthritis-within-person, between-knee comparison Arthritis Care Res. (Hoboken.) 64, 1681–1690 (2012). Arthritis Care Res. (Hoboken.) 64, 1681–1690 (2012) 21. Cotofana, S. et al. Longitudinal (1-year) change in cartilage thickness in knees with early knee osteoarthritis: A within-person between-knee comparison-data from the OAI. Arthritis Care Res. (Hoboken.) 66, 636–641 (2014). 22. Eckstein, F. et al. Reference values and Z-scores for subregional femorotibial cartilage thickness–results from a large population- based sample (Framingham) and comparison with the non-exposed Osteoarthritis Initiative reference cohort. Osteoarthritis Cartilage 18, 1275–1283 (2010). g 23. Wirth, W. et al. Longitudinal analysis of MR spin–spin relaxation times (T2) in medial femorotibial cartilage of adolescent vs mature athletes: dependence of deep and superficial zone properties on sex and age. Osteoarthr. Cartil. 22, 1554–1558 (2014). i 4. Eckstein, F. et al. Proposal for a nomenclature for magnetic resonance imaging based measures of articular cartilage in osteoarthritis Osteoarthr. Cart. 14, 974–983 (2006). Osteoarthr. Cart. 14, 974 983 (2006). 25. Li, X. & Hornak Joseph, P. T2 Calculations in MRI: Linear versus Nonlinear Methods. J. Imaging Sci. Technol. 38, 154–157 (19 25. Li, X. & Hornak Joseph, P. Author Contributions W.W. and F.E. were responsible for (1) the conception and design of the study. W.W., S.M., F.W.R. and F.E. were involved in (1) data acquisition, analysis and interpretation; (2) drafting the article or revising it critically and (3) final approval of the version to be submitted. Acknowledgements g We would like to thank the OAI participants, OAI investigators, OAI clinical and technical staff, the OAI coordinating center and the OAI funders for providing this unique public data base. The study and data acquisition was funded by the OAI, a public-private partnership comprised of five contracts (N01-AR-2-2258; N01-AR-2-2259; N01-AR-2-2260; N01-AR-2-2261; N01-AR-2-2262) funded by the National Institutes of Health, a branch of the Department of Health and Human Services, and conducted by the OAI Study Investigators. Private funding partners of the OAI include Merck Research Laboratories; Novartis Pharmaceuticals Corporation, GlaxoSmithKline; and Pfizer, Inc. Private sector funding for the OAI is managed by the Foundation for the National Institutes of Health. The sponsors were not involved in the design and conduct of this particular study, in the analysis and interpretation of the data, and in the preparation, review, or approval of the manuscript. We would further like to thank the Paracelsus Medial University research fund (PMU FFF E-13/17/090-WIR) and the German Bundesministerium für Bildung und Forschung (BMBF 01EC1408D) for supporting the image analysis of the MESE images. Sabine Mühlsimer and Barbara Wehr (PhD) are to be thanked for their help with cartilage segmentation in this study. www.nature.com/scientificreports/ www.nature.com/scientificreports/ 9. Mosher, T. J. et al. Knee articular cartilage damage in osteoarthritis: analysis of MR image biomarker reproducibility in ACRIN-PA 4001 multicenter trial. Radiology 258, 832–842 (2011).h gy 0. Schneider, E. & NessAiver, M. The Osteoarthritis Initiative (OAI) magnetic resonance imaging quality assurance update. Osteoarthr Cartil. 21, 110–116 (2013). , ( ) 31. Baum, T. et al. Correlation of magnetic resonance imaging-based knee cartilage T2 measurements and focal knee lesions with body mass index: thirty-six-month followup data from a longitudinal, observational multicenter study. Arthritis Care Res. (Hoboken.) 65, 23–33 (2013). 32. Serebrakian, A. T. et al. Weight loss over 48 months is associated with reduced progression of cartilage T2 relaxation time values: data from the osteoarthritis initiative. J Magn Reson. 41, 1272–1280 (2015). g 3. Mosher, T. J. et al. Age dependency of cartilage magnetic resonance imaging T2 relaxation times in asymptomatic women. Arthriti Rheum. 50, 2820–2828 (2004). 34. Urish, K. L. et al. T2 texture index of cartilage can predict early symptomatic OA progression: data from the osteoarthritis initiative. Osteoarthritis.Cartilage. 21, 1550–1557 (2013). g , ( ) 35. Baum, T. et al. Changes in knee cartilage T2 values over 24 months in subjects with and without risk factors for knee osteoarthritis and their association with focal knee lesions at baseline: Data from the osteoarthritis initiative. J. Magn Reson. 35, 370–378 (2012). g 36. Eckstein, F. et al. Rates of Change and Sensitivity to Change in Cartilage Morphology in Healthy Knees and in Knees With Mild, Moderate, and End-Stage Radiographic Osteoarthritis: Results From 831 Participants From the Osteoarthritis Initiative. Arthritis Care Res. (Hoboken.) 63, 311–319 (2011). 37. Wirth, W. et al. Lateral and Medial Joint Space Narrowing Predict Subsequent Cartilage Loss in the Narrowed, but not in the N narrowed Femorotibial Compartment-Data from the Osteoarthritis Initiative. Osteoarthr. Cartil. 22, 63–70 (2013). References T2 Calculations in MRI: Linear versus Nonlinear Methods. J. Imaging Sci. Technol. 38, 154–157 (1994). 26 C t f S B i h O Hit l W Wi th W & E k t i F I l i f tibi l til thi k l t d t it f t 25. Li, X. & Hornak Joseph, P. T2 Calculations in MRI: Linear versus Nonlinear Methods. J. Imaging Sci. Technol. 38, 154–157 (1994). 26. Cotofana, S., Benichou, O., Hitzl, W., Wirth, W. & Eckstein, F. Is loss in femorotibial cartilage thickness related to severity of contra- lateral radiographic knee osteoarthritis? longitudinal data from the Osteoarthritis Initiative Osteoarthr Cart 22 2059 2066 25. Li, X. & Hornak Joseph, P. T2 Calculations in MRI: Linear versus Nonlinear Methods. J. Imaging Sci. Technol. 38, 154–157 (1994). 26. Cotofana, S., Benichou, O., Hitzl, W., Wirth, W. & Eckstein, F. Is loss in femorotibial cartilage thickness related to severity of contra- lateral radiographic knee osteoarthritis? –longitudinal data from the Osteoarthritis Initiative. Osteoarthr. Cart. 22, 2059–2066 (2014). 7. Eckstein, F. et al. Double echo steady state magnetic resonance imaging of knee articular cartilage at 3 Tesla: a pilot study for the Osteoarthritis Initiative. Ann.Rheum Dis. 65, 433–441 (2006). 28. Eckstein, F. et al. Brief report Two year longitudinal change and testeretest-precision of knee cartilage morphology in a pilot study for the osteoarthritis initiative 1, 2. Osteoarthr. Cart. 15, 1326–1332 (2007). Scientific Reports | 6:34202 | DOI: 10.1038/srep34202 7 Scientific Reports | 6:34202 | DOI: 10.1038/srep34202 Additional Informationi Competing financial interests: W.W. is co-owner and has a part time employment with Chondrometrics GmbH (Ainring, Germany). S.M. is co-owner and has a part time employment with Chondrometrics GmbH. F.R. is chief medical officer and co-owner of Boston Imaging Core Lab (BICL). F.E. is CEO and co-owner of Chondrometrics GmbH. He provides consulting services to MerckSerono, Synarc and Servier, and has held educational lectures for Medtronic. He has received funding support (for studies not related to the current one) from Pfizer, Eli Lilly, Stryker, Novartis, MerckSerono, Glaxo Smith Kline, Wyeth, Centocor, Abbvie, Kolon, Synarc, Ampio, and Orthotrophix. How to cite this article: Wirth, W. et al. Layer-specific femorotibial cartilage T2 relaxation time in knees with and without early knee osteoarthritis: Data from the Osteoarthritis Initiative (OAI). Sci. Rep. 6, 34202; doi: 10.1038/srep34202 (2016). This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ © The Author(s) 2016 Scientific Reports | 6:34202 | DOI: 10.1038/srep34202 8
https://openalex.org/W3121618042
http://eprints.ibb.waw.pl/2145/1/animals-11-01048.pdf
English
null
Seroprevalence of <i>Toxoplasma gondii</i> among sylvatic rodents in Poland
bioRxiv (Cold Spring Harbor Laboratory)
2,021
cc-by
5,963
    Citation: Grzybek, M.; Antolová, D.; Tołkacz, K.; Alsarraf, M.; Behnke-Borowczyk, J.; Nowicka, J.; Paleolog, J.; Biernat, B.; Behnke, J.M.; Bajer, A. Seroprevalence of Toxoplasma gondii among Sylvatic Rodents in Poland. Animals 2021, 11, 1048. https://doi.org/10.3390/ani11041048 Academic Editor: Mathew Crowther Received: 20 February 2021 Accepted: 2 April 2021 Published: 8 April 2021 † These authors contributed equally to this work. Simple Summary: Toxoplasma gondii is a significant pathogen affecting humans and animals. Rodents are known to be reservoir hosts of T. gondii and therefore play a significant role in the dissemination of this parasite. We conducted seromonitoring for T. gondii in four sylvatic rodent species in Poland. We report an overall seroprevalence of 5.5% (3.6% for Myodes glareolus and 20% for other vole species). Seroprevalence in bank voles varied significantly between host age and sex. Our results, therefore, make a significant contribution to the understanding of the role of wild rodent populations in the maintenance and dissemination of T. gondii and identify key factors that affect the magnitude of seroprevalence in specific host populations. Citation: Grzybek, M.; Antolová, D.; Tołkacz, K.; Alsarraf, M.; Behnke-Borowczyk, J.; Nowicka, J.; Paleolog, J.; Biernat, B.; Behnke, J.M.; Bajer, A. Seroprevalence of Toxoplasma gondii among Sylvatic Rodents in Poland. Animals 2021, 11, 1048. https://doi.org/10.3390/ani11041048 Citation: Grzybek, M.; Antolová, D.; Tołkacz, K.; Alsarraf, M.; Behnke-Borowczyk, J.; Nowicka, J.; Paleolog, J.; Biernat, B.; Behnke, J.M.; Bajer, A. Seroprevalence of Toxoplasma gondii among Sylvatic Rodents in Poland. Animals 2021, 11, 1048. https://doi.org/10.3390/ani11041048 Academic Editor: Mathew Crowther Abstract: Toxoplasma gondii is an intracellular Apicomplexan parasite with a broad range of interme- diate hosts, including humans and rodents. Rodents are considered to be reservoirs of infection for their predators, including cats, felids, pigs, and wild boars. We conducted a multi-site, long-term study on T. gondii in northeastern Poland. The study aimed to monitor the seroprevalence of T. gondii in the four abundant vole species found in the region (Myodes glareolus, Microtus arvalis, Microtus agrestis, and Alexandromys oeconomus) and to assess the influence of both extrinsic (year of study and study site) and intrinsic (host sex and host age) factors on seroprevalence. A bespoke enzyme-linked immunosorbent assay was used to detect antibodies against T. gondii. We examined 577 rodent individuals and detected T. gondii antibodies in the sera of all four rodent species with an overall seroprevalence of 5.5% [4.2–7.3] (3.6% [2.6–4.9] for M. glareolus and 20% [12–30.9] for M. Article Seroprevalence of Toxoplasma gondii among Sylvatic Rodents in Poland Maciej Grzybek 1,*, Daniela Antolová 2 , Katarzyna Tołkacz 3,4, Mohammed Alsarraf 4, Maciej Grzybek 1,*, Daniela Antolová 2 , Katarzyna Tołkacz 3,4, Mohammed Alsarraf 4, Jolanta Behnke-Borowczyk 5, Joanna Nowicka 1 , Jerzy Paleolog 6 , Beata Biernat 1 , Jerzy M. Behnke 7,† and Anna Bajer 4,† j y y Jolanta Behnke-Borowczyk 5, Joanna Nowicka 1 , Jerzy Paleolog 6 , Beata Biernat 1 , Jerzy M. Behnke 7,† and Anna Bajer 4,† Jolanta Behnke-Borowczyk 5, Joanna Nowicka 1 , Jerzy Paleolog 6 , Beata Biernat 1 , Jer and Anna Bajer 4,† 1 Department of Tropical Parasitology, Institute of Maritime and Tropical Medicine, Medical University of Gdansk, Powstania Styczniowego 9B, 81-519 Gdynia, Poland; joanna.nowicka@gumed.edu.pl (J.N.); beata.biernat@gumed.edu.pl (B.B.) 1 Department of Tropical Parasitology, Institute of Maritime and Tropical Medicine, Medical University of Gdansk, Powstania Styczniowego 9B, 81-519 Gdynia, Poland; joanna.nowicka@gumed.edu.pl (J.N.); beata.biernat@gumed.edu.pl (B.B.) 2 Institute of Parasitology, Slovak Academy of Sciences, 040 01 Košice, Slovakia; antolova@saske.sk 3 3 Institute of Biochemistry and Biophysics, Polish Academy of Sciences, 02-106 Warsaw, Poland; k.h.tolkacz@ibb.waw.pl 4 Department of Eco-Epidemiology of Parasitic Diseases, Institute of Developmental Biology and Biomedical Sciences, Faculty of Biology, University of Warsaw, Miecznikowa, 02-096 Warsaw, Poland; muha@biol uw edu pl (M A ); anabena@biol uw edu pl (A B ) 5 Department of Forest Phytopathology, Faculty of Forestry and Wood Technology, Poznan University of Life Sciences, 60-637 Poznan, Poland; jbehnke@up.poznan.pl j p p p 6 Department of Zoology and Animal Ecology, Faculty of Environmental Biology, University of Life Sciences in Lublin, 20-950 Lublin, Poland; jerzy.paleolog@up.lublin.pl 7 School of Life Sciences, University of Nottingham, University Park, Nottingham NG7 2RD, UK; jerzy.behnke@nottingham.ac.uk j y g * Correspondence: maciej.grzybek@gumed.edu.pl; Tel.: +48-58-3491941   Citation: Grzybek, M.; Antolová, D.; Tołkacz, K.; Alsarraf, M.; Behnke-Borowczyk, J.; Nowicka, J.; Paleolog, J.; Biernat, B.; Behnke, J.M.; Bajer, A. Seroprevalence of Toxoplasma gondii among Sylvatic Rodents in Poland. Animals 2021, 11, 1048. https://doi.org/10.3390/ani11041048 Academic Editor: Mathew Crowther Received: 20 February 2021 Accepted: 2 April 2021 Published: 8 April 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ animals animals animals animals animals 1. Introduction There is currently considerable interest in understanding not only the transmission of pathogens but also the range of different variables that influence infection dynamics. Among these, both extrinsic factors (e.g., geographic location) and intrinsic factors (e.g., host sex) are known to play varying but crucial roles in exposure of hosts, and their susceptibility, to infection [1–3]. Analyzing pathogen dynamics in their wildlife reservoirs is essential in providing a good understanding of their epidemiology and facilitating informed decisions on appropriate measures for their control [4–6]. Wild rodents pose a particular threat for human communities because they constitute the most abundant and diversified group of all living mammals [7] and often adopt a synanthropic existence. Although some zoonotic parasites are not transmissible directly from rodents to humans, or pose just a low risk of direct transmission, predation of rodents by carnivore pets may cause infections in these animals, leading to subsequent contamination of households and other human-related environments [8,9]. Toxoplasma gondii (T. gondii) is an intracellular Apicomplexan parasite with a broad range of intermediate hosts, including humans and rodents [10]. The parasite is present in the tachyzoite stage and changes into bradyzoites, as a result of the conversion of tachyzoites into slow-dividing stages, that eventually form tissue cysts [11]. These can pass from host to host via the food chain and across the placenta resulting in congenitally acquired infections. Rodents are considered to be reservoirs of infection for their predators that include cats, pigs, and dogs. Felid species are the definitive hosts of T. gondii and the only hosts that can shed T. gondii oocysts into the environment [12]. In 2017, 194 confirmed human congenital toxoplasmosis cases were reported from 22 EU countries. France accounted for 79% of all cases. The number of congenital infections per 100,000 newborns was 5.3 in the European Union and European Economic Area. The highest incidence (number of cases/per 100,000 live births/year) was reported in France (19.9), followed by Slovenia (9.9), Poland (4.5), and Bulgaria (3.1) [13]. In 2018, only 25 cases of congenital toxoplasmosis were reported in Poland, and in 2019 even fewer were reported, with only 14 confirmed cases [14]. We conducted a multi-site, long-term study on T. gondii in northeastern Poland. Our objectives were to monitor seroprevalence of T.   arvalis, M. agrestis, and A. oeconomus). Seroprevalence in bank voles varied significantly between host age and sex. Seroprevalence increased with host age and was higher in females than males. These results contribute to our understanding of the distribution and abundance of T. gondii in voles in Poland and confirm that T. gondii also circulates in M. glareolus and M. arvalis, M. agrestis and A. oeconomus. Therefore, they may potentially play a role as reservoirs of this parasite in the sylvatic environment. Received: 20 February 2021 Accepted: 2 April 2021 Published: 8 April 2021 Received: 20 February 2021 Accepted: 2 April 2021 Published: 8 April 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Keywords: Toxoplasma gondii; rodents; seromonitoring; rodent-borne diseases; prevention https://www.mdpi.com/journal/animals Animals 2021, 11, 1048. https://doi.org/10.3390/ani11041048 Animals 2021, 11, 1048 2 of 7 1. Introduction gondii in the four abundant vole species found in the region (Myodes glareolus, Microtus arvalis, Microtus agrestis, and Alexandromys oeconomus) and to assess variation in seroprevalence attributable to both intrinsic and extrinsic factors that were quantified. 2. Materials and Methods Our study sites are located in the Mazury Lake District region in north-eastern Poland. The sites and methods used for trapping rodents, and for sampling and processing trapped animals, have all been thoroughly described [15–18]. Briefly, we used locally constructed Polish wooden live-capture traps. Wheat seeds and peanut butter were used as bate to lure animals into the traps. Trapping was carried out using approximately 300 traps per night, placed in 30–40 m long parallel or divergent lines, 15 m either side of tracks running through the sites and two traps were placed within 2–3 m of one another at each point. Bank voles were sampled in 2002, 2006, and 2010 in three local but disparate forest sites. Other species of voles were sampled only in 2013 from fallow meadows close to one of the forest sites. We examined 577 individuals (M. glareolus n = 507; M. agrestis n = 10; M. arvalis n = 46; and A. oeconomus n = 14). Rodent serum was collected and frozen at −72 ◦C until further analyses. Serological enzyme-linked immunosorbent assay (ELISA) was used to detect antibod- ies to Toxoplasma gondii in sera. The sensitivity of ELISA method with goat anti-mouse polyvalent antibodies on sera of several rodent species, including Microtus arvalis and Myodes glareolus, was validated by several studies [19–22]. Commercially available T. gondii antigen (CD Creative Diagnostics, New York, NY, USA) prepared from RH strain [23,24] was used for determination of seropositivity according to Reiterová et al. [21]. Final dilu- Animals 2021, 11, 1048 3 of 7 tion of antigen was 3.4 µg protein/mL of dilution buffer. Since no positive control sera from T. gondii infected M. arvalis and M. glareolus were available, the cut-off value was determined according to Naguleswaran et al. [25]. The first cut-off value was determined by the mean of all sera on the microtiter plate plus 3 standard deviations (SD). Sera with OD above this value were excluded and the remaining sera were used for calculation of mean absorption of negative samples (Mneg) and SDneg. Sera with OD values above Mneg + 4 SDneg were considered to be positive. g p The statistical approach has been documented comprehensively in our earlier publica- tions [1,26]. For analysis of prevalence, we used maximum likelihood techniques based on log-linear analysis of contingency tables in the software package IBM SPSS Statistics Version 21 (Armonk, NY, USA). 2. Materials and Methods This approach is based on categorical values of the fac- tors of interest, which are used to fit hierarchical log-linear models to multidimensional cross-tabulations using an iterative proportional-fitting algorithm and detect associations between the factors, one of which may be presence/absence of infection. Prevalence values are given in the text and table with 95% confidence limits in square brackets, and in the figure with 95% confidence intervals. 3. Results We examined 577 rodent individuals, and found T.gondii antibodies in the sera of all four rodent species, with an overall seroprevalence of 5.5% (Table 1). There was a significant difference in seroprevalence between vole species (χ23 = 22.58; p = 0.001) with M. arvalis, M. agrestis, and A. oeconomus showing 5.6-fold higher seroprevalence (20% [12–30.9]) than M. glarolus (3.6% [2.6–4.9]). Table 1. Seroprevalence of T. gondii in four rodent species in Poland. Seroprevalence is given in percentages with 95% CL in brackets. Species Negative Positive Total Seroprevalence (%) ± CL95 M. agrestis 7 3 10 30.0 [8.7–61.9] M. arvalis 37 9 46 19.6 [9.1–36.8] A. oeconomus 12 2 14 14.3 [2.6–42.6] Myodes graelous 489 18 507 3.6 [2.6–4.9] Overall 545 32 577 5.5 [4.2–7.3] Table 1. Seroprevalence of T. gondii in four rodent species in Poland. Seroprevalence is given in percentages with 95% CL in brackets. In a log-linear model restricted to M. arvalis, M. agrestis, and A. oeconomus there was no difference between these three species (χ22 = 0.8, p = 0.7), nor between the sexes (χ21 = 0.37; p = 0.55) or age classes (χ22 = 4.67; p = 0.097). However, the latter was close to significance and reflected peak seroprevalence in young adult voles (35.7 [15.28–62.89]) in comparison to zero seroprevalence among the youngest voles and 18.0% [9.46–30.87] among the oldest (Figure 1). We therefore confined further analyses to bank voles (M. glareolus). In a log-linear model confined to bank voles, and with year of sampling (3 years) and site (3 sites) taken into account, T.gondii seroprevalence differed significantly between the sexes of M. glareolus (χ21 =4.34; p = 0.037) and was 3.5 times higher for female (5.5% [3.6–8.1]) compared with male (1.6% [0.7–3.4]) bank voles (Figure 1). p g T. gondii seroprevalence increased significantly with host age (χ22 = 11.57; p = 0.003), peaking in the oldest bank voles (6.1% [2.77–12.47]), but was lower in bank voles from age class 2 (mostly young adults; 3.5% [1.22–9.50]). No immature bank voles were found to be seropositive. The data in Figure 1 also indicate that seroprevalence increased with host age faster among female bank voles compared with males, although the interaction between age and sex was not significant (χ 22 = 0.28; p = 0.87). 4 of 7 4 of 7 Animals 2021, 11, 1048 Animals 2021, 11 Figure 1. Seroprevalence of T. ( ing older animals 4. Discussion In a log-linear model confined to bank voles, and with year of sampling (3 years) and site (3 sites) taken into account, T.gondii seroprevalence differed significantly between the Our results confirm that in the wild M. glareolus, M. arvalis, M. agrestis, and A. oecono- mus have contact with T. gondii and become infected. Therefore, they may potentially play a role as reservoirs of this parasite in the sylvatic environment [27]. sexes of M. glareolus (χ21 =4.34; p = 0.037) and was 3.5 times higher for female (5.5% [3.6– 8.1]) compared with male (1.6% [0.7–3.4]) bank voles (Figure 1). T. gondii seroprevalence increased significantly with host age (χ22 = 11.57; p = 0.003), peaking in the oldest bank voles (6.1% [2.77–12.47]), but was lower in bank voles from age According to the meta-analysis carried out by Galeh and colleagues [28], the overall seroprevalence of anti-Toxoplasma IgG antibodies in rodents in North America, Australia, and Asia was measured at 5%, 4%, and 4%, respectively. The authors report 1% T. gondii seroprevalence in Europe. class 2 (mostly young adults; 3.5% [1.22–9.50]). No immature bank voles were found to be seropositive. The data in Figure 1 also indicate that seroprevalence increased with host age faster among female bank voles compared with males, although the interaction be- tween age and sex was not significant (χ 22 = 0.28; p = 0.87). 4. Discussion Our results confirm that in the wild M. glareolus, M. arvalis, M. agrestis, and A. oecono- mus have contact with T. gondii and become infected. Therefore, they may potentially play Here, we report an overall seroprevalence of T. gondii in M. glareolus, M. arvalis, M. agrestis, and A. oeconomus of 5.5%, with M. arvalis, M. agrestis, and A. oeconomus showing a considerably higher seroprevalence at 20%. Although the reason for this discrepancy between the rodent genera is not clear, we have noted that cats from local farms are often observed in the meadows where we trapped Microtus/ Alexandromys spp., but seldom enter the forests to which bank voles are confined. This is in line with the results obtained with radio-collared farm cats in Switzerland, which kept to a short distance from houses and preferred meadows over forests [29]. 3. Results gondii in bank voles in Poland by host sex and by host age class (class 1—immature juvenile voles, n = 138; class 2—young adult voles, n = 173; and class 3—breed- 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 Age class 1 Age class 2 Age class 3 Male voles Female voles Seroprevalence ±CI95 Figure 1. Seroprevalence of T. gondii in bank voles in Poland by host sex and by host age class (class 1—immature juvenile voles, n = 138; class 2—young adult voles, n = 173; and class 3—breeding older animals, n = 196). Error bars indicate 95% CI. Male voles Female voles Figure 1. Seroprevalence of T. gondii in bank voles in Poland by host sex and by host age class l 1 i t j il l 138 l 2 d lt l 173 d l 3 b d Figure 1. Seroprevalence of T. gondii in bank voles in Poland by host sex and by host age class (class 1—immature juvenile voles, n = 138; class 2—young adult voles, n = 173; and class 3—breeding older animals, n = 196). Error bars indicate 95% CI. ( ing older animals 4. Discussion mus a e co ac i gondii a d beco e i ec ed e e o e, ey ay po e ia y p ay a role as reservoirs of this parasite in the sylvatic environment [27]. According to the meta-analysis carried out by Galeh and colleagues [28], the overall seroprevalence of anti-Toxoplasma IgG antibodies in rodents in North America, Australia, and Asia was measured at 5%, 4%, and 4%, respectively. The authors report 1% T. gondii seroprevalence in Europe. Rodents living in an environment with limited populations of cats are less exposed to oocysts [30,31]. Seroprevalence of T. gondii in rodents differs significantly between rural and urban environments [32,33]. Urban rodents show higher T. gondii seroprevalence than individuals living in the rural environment [22,34,35], reflecting a difference betweeen these environments in the degree of contamination by oocysts from felids [31,36,37]. seroprevalence in Europe. Here, we report an overall seroprevalence of T. gondii in M. glareolus, M. arvalis, M. agrestis, and A. oeconomus of 5.5%, with M. arvalis, M. agrestis, and A. oeconomus showing a considerably higher seroprevalence at 20%. Although the reason for this discrepancy be- tween the rodent genera is not clear, we have noted that cats from local farms are often observed in the meadows where we trapped Microtus/ Alexandromys spp., but seldom en- ter the forests to which bank voles are confined. This is in line with the results obtained with radio-collared farm cats in Switzerland, which kept to a short distance from houses and preferred meadows over forests [29]. Rodents living in an environment with limited populations of cats are less exposed We found that female bank voles were 3.5 times more likely to be infected with T. gondii than males, and, in this respect, our data contrast with reports in the literature in which T. gondii seropositivity in male rodents has been recorded generally to be higher than in females [17,28]. It was not unexpected to find in our study that older animals had a higher serological positive rate than juveniles, since the current work was based on the presence/absence of specific antibody against T. gondii, reflecting the history of previous infections and not necessarily a current infection [26,38]. Older animals will have had a longer period over which to encounter the infective stages of T. gondii, and hence would have experienced greater likelihood of infection than younger individuals [2,9,26]. 5. Conclusions The results presented in this paper provide a significant and novel contribution to our understanding of the seroprevalence rate of T. gondii within vole populations. The World Organization for Animal Health recommends assessment of infections in wild rodents to enable effective control and thereby reduction of exposure of domestic animals and humans to zoonotic parasites. However, all appropriate action should be carried out with due regard for animal welfare and biodiversity. Further studies are necessary, therefore, to reveal comprehensively the status of toxoplasmosis in wildlife and to assess the risk of infection for local inhabitants, as well as for visitors to the region. Author Contributions: The study was conceived and designed by M.G., D.A., and B.B. Supervision of the long-term monitoring of bank vole populations in the region was by J.M.B. and A.B. Samples were collected in the field by J.M.B., A.B., M.A., M.G., K.T., and J.B.-B. The immunological analysis and laboratory work was conducted by D.A., K.T., J.N., J.M.B., A.B., and M.G. Data handling was carried out by M.G. Statistical analysis was carried by J.M.B. and M.G. The manuscript was written by M.G., B.B., and J.M.B. in consultation with all co-authors. M.G., D.A., A.B., and J.M.B. revised the manuscript. All authors have read and agreed to the published version of the manuscript. Funding: We also thank the University of Nottingham, University of Warsaw, Institute of Parasitology, Slovak Academy of Sciences, and the Medical University of Gda´nsk for financial support. JMB was supported by the Royal Society, the British Ecological Society, and the Grabowski Fund. AB was supported by the Polish State Committee for Scientific Research and the British Council’s Young Scientist Programme). This research was funded through the 2018–2019 BiodivERsA joint call for research proposals, under the BiodivERsA3 ERA-Net COFOUND programme. MG was supported by the National Science Centre, Poland under BiodivERsA3 programme (2019/31/Z/NZ8/04028). Institutional Review Board Statement: This study was conducted to the guidelines of the Decla- ration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of the Guidelines for the Care and Use of Laboratory Animals of the Polish National Ethics Committee for Animal Experimentation. Our project was approved by the First Warsaw Local Ethics Committee for Animal Experimentation which also has overarching responsibility for field work involving the trapping and culling of wild vertebrates for scientific purposes (ethical license numbers 73/2010, 148/2011 and 406/2013). ( ing older animals 4. Discussion Rodents living in an environment with limited populations of cats are less exposed to oocysts [30,31]. Seroprevalence of T. gondii in rodents differs significantly between rural and urban environments [32 33] Urban rodents show higher T gondii seroprevalence than p g y g Transmission of the parasite from wildlife to human habitats may occur especially in rural areas where cats escape human settlements and forage on wild rodents [39,40]. Animals 2021, 11, 1048 5 of 7 5. Conclusions Data Availability Statement: Derived data supporting the findings of this study are available from the corresponding author (M.G.) on request. Acknowledgments: We thank Ewa Mierzejewska for her help in rodent trapping and the fieldwork. MG thanks Alicja Rost and Ewa Zieliniewicz for their assistance in the laboratory. Acknowledgments: We thank Ewa Mierzejewska for her help in rodent trapping and the fieldwork. MG thanks Alicja Rost and Ewa Zieliniewicz for their assistance in the laboratory. Acknowledgments: We thank Ewa Mierzejewska for her help in rodent trapping and the fieldwork. MG thanks Alicja Rost and Ewa Zieliniewicz for their assistance in the laboratory. Conflicts of Interest: The authors declare no conflict of interest. Conflicts of Interest: The authors declare no conflict of interest. Conflicts of Interest: The authors declare no conflict of interest. References 1. Grzybek, M.; Bajer, A.; Bednarska, M.M.; Al-Sarraf, M.; Behnke-Borowczyk, J.; Harris, P.D.; Price, S.J.; Brown, G.S.; Osborne, S.-J.; Si´nski, E.; et al. Long-term spatiotemporal stability and dynamic changes in helminth infracommunities of bank voles (Myodes glareolus) in NE Poland. Parasitology 2015, 142, 1722–1743. [CrossRef] 1. Grzybek, M.; Bajer, A.; Bednarska, M.M.; Al-Sarraf, M.; Behnke-Borowczyk, J.; Harris, P.D.; Price, S.J.; Brown, G.S.; Osborne, S.-J.; Si´nski, E.; et al. Long-term spatiotemporal stability and dynamic changes in helminth infracommunities of bank voles (Myodes glareolus) in NE Poland. Parasitology 2015, 142, 1722–1743. [CrossRef] g gy 2. Behnke, J.M.; Bajer, A.; Harris, P.D.; Newington, L.; Pidgeon, E.; Rowlands, G.; Sheriff, C.; Kuli´s-Malkowska, K.; Si´nski, E.; Gilbert, F.S.; et al. Temporal and between-site variation in helminth communities of bank voles (Myodes glareolus) from N.E. Poland: 2. The infracommunity level. Parasitology 2008, 135, 999–1018. [CrossRef] [PubMed] 2. Behnke, J.M.; Bajer, A.; Harris, P.D.; Newington, L.; Pidgeon, E.; Rowlands, G.; Sheriff, C.; Kuli´s-Malkowska, K.; Si´nski, E.; Gilbert, F.S.; et al. Temporal and between-site variation in helminth communities of bank voles (Myodes glareolus) from N.E. Poland: 2. The infracommunity level. Parasitology 2008, 135, 999–1018. [CrossRef] [PubMed] y gy 3. Rabalski, L.; Kosinski, M.; Smura, T.; Aaltonen, K.; Kant, R.; Sironen, T.; Szewczyk, B.; Grzybek, M. Detection and molecular characterisation of SARS-CoV-2 in farmed mink (Neovison vison) in Poland. bioRxiv 2020. [CrossRef] y gy 3. Rabalski, L.; Kosinski, M.; Smura, T.; Aaltonen, K.; Kant, R.; Sironen, T.; Szewczyk, B.; Grzybek, M. Detection and molecular characterisation of SARS-CoV-2 in farmed mink (Neovison vison) in Poland. bioRxiv 2020. [CrossRef] 4. Achazi, K.; R˚užek, D.; Donoso-Mantke, O.; Schlegel, M.; Ali, H.S.; Wenk, M.; Schmidt-Chanasit, J.; Ohlmeyer, L.; Rühe, F.; Vor, T.; et al. Rodents as Sentinels for the Prevalence of Tick-Borne Encephalitis Virus. Vector-Borne Zoonotic Dis. 2011, 11, 641–647. [CrossRef] [PubMed] 4. Achazi, K.; R˚užek, D.; Donoso-Mantke, O.; Schlegel, M.; Ali, H.S.; Wenk, M.; Schmidt-Chanasit, J.; Ohlmeyer, L.; Rühe, F.; Vor, T.; et al. Rodents as Sentinels for the Prevalence of Tick-Borne Encephalitis Virus. Vector-Borne Zoonotic Dis. 2011, 11, 641–647. [CrossRef] [PubMed] 5. Grzybek, M.; Cybulska, A.; Tołkacz, K.; Alsarraf, M.; Behnke-Borowczyk, J.; Szczepaniak, K.; Strachecka, A.; Paleolog, J.; Moskwa, B.; Behnke, J.M.; et al. Seroprevalence of Trichinella spp. infection in bank voles (Myodes glareolus)—A long term study. Int. J. Parasitol. Parasites Wildl. 2019, 9. [CrossRef] 5. 5. Grzybek, M.; Cybulska, A.; Tołkacz, K.; Alsarraf, M.; Behnke-Borowczyk, J.; Szczepaniak, K.; Strachecka, A.; Paleolog, J.; Moskwa, B.; Behnke, J.M.; et al. Seroprevalence of Trichinella spp. infection in bank voles (Myodes glareolus)—A long term study. Int. J. Parasitol. Parasites Wildl. 2019, 9. [CrossRef] 6. Behnke, J.M. Structure in parasite component communities in wild rodents: Predictability, stability, associations and interactions or pure randomness? Parasitology 2008, 135, 751–766. [CrossRef] 6. Behnke, J.M. Structure in parasite component communities in wild rodents: Predictability, stability, or pure randomness? Parasitology 2008, 135, 751–766. [CrossRef] References Grzybek, M.; Cybulska, A.; Tołkacz, K.; Alsarraf, M.; Behnke-Borowczyk, J.; Szczepaniak, K.; Strachecka, A.; Paleolog, J.; Moskwa, B.; Behnke, J.M.; et al. Seroprevalence of Trichinella spp. infection in bank voles (Myodes glareolus)—A long term study. Int. J. Parasitol. Parasites Wildl. 2019, 9. [CrossRef] 6. Behnke, J.M. Structure in parasite component communities in wild rodents: Predictability, stability, associations and interactions or pure randomness? Parasitology 2008, 135, 751–766. [CrossRef] Animals 2021, 11, 1048 6 of 7 7. Wilson, D.E.; Reeder, D.M. Mammal Species of the World, 3rd ed.; Johns Hopkins University Press: Baltimore, MD, USA, 2005; Volume 1, ISBN 9780801882210. Ö 8. Waindok, P.; Özbakı¸s-Beceriklisoy, G.; Janecek-Erfurth, E.; Springer, A.; Pfeffer, M.; Leschnik, M.; Strube, C. Parasites in brains of wild rodents (Arvicolinae and Murinae) in the city of Leipzig, Germany. Int. J. Parasitol. Parasites Wildl. 2019, 10, 211–217. [CrossRef] 9. Grzybek, M.; Sironen, T.; Mäki, S.; Tołkacz, K.; Alsarraf, M.; Strachecka, A.; Paleolog, J.; Biernat, B.; Szczepaniak, K.; Behnke- Borowczyk, J.; et al. Zoonotic Virus Seroprevalence among Bank Voles, Poland, 2002–2010. Emerg. Infect. Dis. 2019, 25, 1607–1609. [CrossRef] 10. Johnson, H.J.; Koshy, A.A. Latent Toxoplasmosis Effects on Rodents and Humans: How Much is Real and How Much is Media Hype? MBio 2020, 11. [CrossRef] 11. Hill, D.; Dubey, J.P. Toxoplasma gondii: Transmission, diagnosis and prevention. Clin. Microbiol. Infect 11. Hill, D.; Dubey, J.P. Toxoplasma gondii: Transmission, diagnosis and prevention. Clin. Microbiol. Infect. 2002, 8, 634–640. [CrossRef] 12. Tenter, A.M.; Heckeroth, A.R.; Weiss, L.M. Toxoplasma gondii: From animals to humans. Int. J. Parasitol. 2000, 30, 1217–1258. [CrossRef] y p g g p f 12. Tenter, A.M.; Heckeroth, A.R.; Weiss, L.M. Toxoplasma gondii: From animals to humans. Int. J. Parasitol. 2000, 30, 1217–1258. [CrossRef] [ ] 13. ECDC. Annual Epidemiological Report for 2017; ECDC: Stockholm, Sweden, 2019. p g p f 14. NIPH—NIH National Institute of Public Health—National Institute of Hygiene in Poland. Available online: http://wwwold.pzh. gov.pl/oldpage/epimeld/index_p.html (accessed on 20 December 2020). 15. Tołkacz, K.; Alsarraf, M.; Kowalec, M.; Dwu˙znik, D.; Grzybek, M.; Behnke, J.M.; Bajer, A. Bartonella infections in three species of Microtus: Prevalence and genetic diversity, vertical transmission and the effect of concurrent Babesia microti infection on its success. Parasites Vectors 2018, 11, 491. [CrossRef] [PubMed] 16. Behnke, J.M.; Barnard, C.J.; Bajer, A.; Bray, D.; Dinmore, J.; Frake, K.; Osmond, J.; Race, T.; Sinski, E. References Variation in the helminth community structure in bank voles (Clethrionomys glareolus) from three comparable localities in the Mazury Lake District region of Poland. Parasitology 2001, 123, 401–414. [CrossRef] [PubMed] gy 17. Grzybek, M.; Bajer, A.; Behnke-Borowczyk, J.; Al-Sarraf, M.; Behnke, J.M. Female host sex-biased parasitism with the rodent stomach nematode Mastophorus muris in wild bank voles (Myodes glareolus). Parasitol. Res. 2014, 114, 523–533. [CrossRef] 18. Tołkacz, K.; Bednarska, M.; Alsarraf, M.; Dwu˙znik, D.; Grzybek, M.; Welc-Fal˛eciak, R.; Behnke, J.M.; Bajer, A. Prevalence, genetic identity and vertical transmission of Babesia microti in three naturally infected species of vole, Microtus spp. (Cricetidae). Parasites Vectors 2017, 10, 1–12. [CrossRef] ová, K.; Stanko, M.; Zalesny, G.; Friˇcová, J.; Dvorožˇnáková, E. Small mammals: Paratenic hosts for species of Sl ki J H l i th l 2013 87 52 58 [C R f] [P bM d] ová, D.; Reiterová, K.; Stanko, M.; Zalesny, G.; Friˇcová, J.; Dvorožˇnáková, E. Small mammals: Paratenic host 19. Antolová, D.; Reiterová, K.; Stanko, M.; Zalesny, G.; Friˇcová, J.; Dvorožˇnáková, E. Small mammals: Toxocara in eastern Slovakia. J. Helminthol. 2013, 87, 52–58. [CrossRef] [PubMed] ara in eastern Slovakia. J. Helminthol. 2013, 87, 52–58. [CrossRef] [PubMed] 20. Essbauer, S.; Schmidt, J.; Conraths, F.J.; Friedrich, R.; Koch, J.; Hautmann, W.; Pfeffer, M.; Wölfel, R.; Finke, J.; Dobler, G.; et al. A new Puumala hantavirus subtype in rodents associated with an outbreak of Nephropathia epidemica in South-East Germany in 2004. Epidemiol. Infect. 2006, 134. [CrossRef] p f 21. Reiterová, K.; Antolová, D.; Zale´sny, G.; Stanko, M.; Špilovská, S.; Mošanský, L. Small rodents— toxocarosis in different habitats of Slovakia. Helminthologia 2013, 50. [CrossRef] lová, D.; Zale´sny, G.; Stanko, M.; Špilovská, S.; Mošanský, L. Small rodents—Permanent reservoirs of ent habitats of Slovakia. Helminthologia 2013, 50. [CrossRef] 22. Reperant, L.A.; Hegglin, D.; Tanner, I.; Fischer, C.; Deplazes, P. Rodents as shared indicators for zoonotic parasites of carnivores in urban environments. Parasitology 2009, 136, 329–337. [CrossRef] gy 23. Hughes, H.P.; Van Knapen, F.; Atkinson, H.J.; Balfour, A.H.; Lee, D.L. A new soluble antigen preparation of Toxoplasma gondii and its use in serological diagnosis. Clin. Exp. Immunol. 1982, 49, 239–246. 24. Opsteegh, M.; Teunis, P.; Mensink, M.; Züchner, L.; Titilincu, A.; Langelaar, M.; van der Giessen, J. Evaluation of ELISA test characteristics and estimation of Toxoplasma gondii seroprevalence in Dutch sheep using mixture models. Prev. Vet. Med. 2010, 96, 232–240. [CrossRef] 25. References Prevalence of Antibodies to Toxoplas across an Urban–Rural Gradient. J. Wildl. Dis. 2010, 46, 977–980. [CrossRef] [PubMed] across an Urban Rural Gradient. J. Wildl. Dis. 2010, 46, 977 980. [CrossRef] [PubMed] 34. Mercier, A.; Garba, M.; Bonnabau, H.; Kane, M.; Rossi, J.-P.; Darde, M.-L.; Dobigny, G. Toxoplasmosis seroprevalence in urban rodents: A survey in Niamey, Niger. Mem. Inst. Oswaldo Cruz 2013, 108, 399–407. [CrossRef] 34. Mercier, A.; Garba, M.; Bonnabau, H.; Kane, M.; Rossi, J.-P.; Darde, M.-L.; Dobigny, G. Toxoplasmosis rodents: A survey in Niamey, Niger. Mem. Inst. Oswaldo Cruz 2013, 108, 399–407. [CrossRef] 35. Murphy, R.G.; Williams, R.H.; Hughes, J.M.; Hide, G.; Ford, N.J.; Oldbury, D.J. The urban house mouse (Mus domesticus) as a reservoir of infection for the human parasite Toxoplasma gondii: An unrecognised public health issue? Int. J. Environ. Health Res. 2008, 18, 177–185. [CrossRef] 35. Murphy, R.G.; Williams, R.H.; Hughes, J.M.; Hide, G.; Ford, N.J.; Oldbury, D.J. The urban house mouse (Mus domesticus) as a reservoir of infection for the human parasite Toxoplasma gondii: An unrecognised public health issue? Int. J. Environ. Health Res. 2008, 18, 177–185. [CrossRef] 36. DeFeo, M.L.; Dubey, J.P.; Mather, T.N.; Rhodes, R.C., III. Epidemiologic investigation of seroprevalen gondii in cats and rodents. Am. J. Vet. Res. 2002, 63, 1714–1717. [CrossRef] [PubMed] 37. Ding, H.; Gao, Y.-M.; Deng, Y.; Lamberton, P.H.L.; Lu, D.-B. A systematic review and meta-analysis of the seroprevalence of Toxoplasma gondii in cats in mainland China. Parasites Vectors 2017, 10, 27. [CrossRef] 37. Ding, H.; Gao, Y.-M.; Deng, Y.; Lamberton, P.H.L.; Lu, D.-B. A systematic review and meta-analysis of the seroprevalence of Toxoplasma gondii in cats in mainland China. Parasites Vectors 2017, 10, 27. [CrossRef] p g 38. Grzybek, M.; Tołkacz, K.; Sironen, T.; Mäki, S.; Alsarraf, M.; Behnke-Borowczyk, J.; Biernat, B.; Nowicka, J.; Vaheri, A.; Henttonen, H.; et al. Zoonotic Viruses in Three Species of Voles from Poland. Animals 2020, 10, 1820. [CrossRef] 38. Grzybek, M.; Tołkacz, K.; Sironen, T.; Mäki, S.; Alsarraf, M.; Behnke-Borowczyk, J.; Biernat, B.; Nowicka, J.; Vaheri, A.; Henttonen, H.; et al. Zoonotic Viruses in Three Species of Voles from Poland. Animals 2020, 10, 1820. [CrossRef] 39. Meerburg, B.G.; Singleton, G.R.; Kijlstra, A. Rodent-borne diseases and their risks for public health. Crit. Rev. Microbiol. 2009, 35, 221–270. [CrossRef] 39. Meerburg, B.G.; Singleton, G.R.; Kijlstra, A. Rodent-borne diseases and their risks for public health. Crit. Rev. Microbiol. 2009, 35, 221–270. [CrossRef] 40. 32. Pavlova, E.V.; Kirilyuk, E.V.; Naidenko, S.V. Occurrence Pattern of Influenza A Virus, Coxiella burnetii, Toxoplasma gondii, and Trichinella sp. in the Pallas Cat and Domestic Cat and Their Potential Prey Under Arid Climate Conditions. Arid Ecosyst. 2016, 6, 277–283. [CrossRef] References Naguleswaran, A.; Hemphill, A.; Rajapakse, R.P.V.J.; Sager, H. Elaboration of a crude antigen ELISA for serodiagnosis of caprine neosporosis: Validation of the test by detection of Neospora caninum-specific antibodies in goats from Sri Lanka. Vet. Parasitol. 2004, 126, 257–262. [CrossRef] 26. Grzybek, M.; Alsarraf, M.; Tołkacz, K.; Behnke-Borowczyk, J.; Biernat, B.; Sta´nczak, J.; Strachecka, A.; Guz, L.; Szczepaniak, K.; Paleolog, J.; et al. Seroprevalence of TBEV in bank voles from Poland-a long-term approach. Emerg. Microbes Infect. 2018, 7, 145. [CrossRef] 27. Jittapalapong, S.; Sarataphan, N.; Maruyama, S.; Hugot, J.-P.; Morand, S.; Herbreteau, V. Toxoplasmos Survey and First Evidences in Thailand Vector-Borne Zoonotic Dis 2011 11 231–237 [CrossRef] 27. Jittapalapong, S.; Sarataphan, N.; Maruyama, S.; Hugot, J.-P.; Morand, S.; Herbreteau, V. Toxoplasmosis in Rodents: Ecological Survey and First Evidences in Thailand. Vector-Borne Zoonotic Dis. 2011, 11, 231–237. [CrossRef] Jittapalapong, S.; Sarataphan, N.; Maruyama, S.; Hugot, J. P.; Morand, S.; Herbreteau, V. Toxoplasmosis i Survey and First Evidences in Thailand. Vector-Borne Zoonotic Dis. 2011, 11, 231–237. [CrossRef] 28. Galeh, T.M.; Sarvi, S.; Montazeri, M.; Moosazadeh, M.; Nakhaei, M.; Shariatzadeh, S.A.; Daryani, A gondii Seroprevalence in Rodents: A Systematic Review and Meta-Analysis. Front. Vet. Sci. 2020, 7. Sarvi, S.; Montazeri, M.; Moosazadeh, M.; Nakhaei, M.; Shariatzadeh, S.A.; Daryani, A. Global Status of Tox g p y y 29. Weber, J.-M.; Dailly, L. Food habits and ranging behaviour of a group of farm cats (Felis catus) in a Swiss mountainous area. J. Zool. 1998, 245, S0952836998286092. [CrossRef] 30. Afonso, E.; Poulle, M.L.; Lemoine, M.; Villena, I.; Aubert, D.; Gilot-Fromont, E. Prevalence of Toxoplasma gondii in small mammals from the Ardennes region, France. Folia Parasitol. 2007, 54, 313–314. [CrossRef] [PubMed] onso, E.; Poulle, M.L.; Lemoine, M.; Villena, I.; Aubert, D.; Gilot Fromont, E. Prevalence of Toxoplasma gondii om the Ardennes region, France. Folia Parasitol. 2007, 54, 313–314. [CrossRef] [PubMed] 31. Afonso, E.; Thulliez, P.; Pontier, D.; Gilot-Fromonte, E. Toxoplasmosis in prey species and consequences for prevalence in feral cats: Not all prey species are equal. Parasitology 2007, 134, 1963–1971. [CrossRef] Animals 2021, 11, 1048 7 of 7 32. Pavlova, E.V.; Kirilyuk, E.V.; Naidenko, S.V. Occurrence Pattern of Influenza A Virus, Coxiella burnetii, Toxoplasma gondii, and Trichinella sp. in the Pallas Cat and Domestic Cat and Their Potential Prey Under Arid Climate Conditions. Arid Ecosyst. 2016, 6, 277–283. [CrossRef] 33. Lehrer, E.W.; Fredebaugh, S.L.; Schooley, R.L.; Mateus-Pinilla, N.E. References Thompson, R.C.A.; Lymbery, A.J.; Smith, A. Parasites, emerging disease and wildlife conservation. Int. J. Parasitol. 2010, 40, 1163–1170. [CrossRef] 40. Thompson, R.C.A.; Lymbery, A.J.; Smith, A. Parasites, emerging disease and wildlife conservation. Int. J. Parasitol. 2010, 40, 1163–1170. [CrossRef]
https://openalex.org/W4327853895
https://are-journal.com/are/article/download/116/112
English
null
Human capital efficiency in initiative groups accepting internally displaced persons in the eastern and southern Ukraine
Agricultural and resource economics
2,017
cc-by
5,464
HUMAN CAPITAL EFFICIENCY IN INITIATIVE GROUPS ACCEPTING INTERNALLY DISPLACED PERSONS IN THE EASTERN AND SOUTHERN UKRAINE The article analyzes characteristics and deviations from the approach to rural development via local initiative groups that has been fully accepted as a method in most part of the developed societies. It has been found, that in Ukraine such groups function better if they are composed of officials, responsible management and heads of local agencies. However, during the antiterrorist operation in 2014; in order to relocate, adapt and stabilize communities in areas of conflict in Ukraine, mixed action groups were often formed that contained a share of IDPs (internally displaced persons) and civil society activists. Such groups have shown themselves fairly well during the 2014–2016 biennium, and their potential was found to be suitable for further economic development of rural areas in Eastern Ukraine, including possible early recovery economic projects in the approximation to the conflict zone, where only voluntary associations are seen as able to produce small, but real economic effects. Features of the structure, performance, motivation of these groups and associations are highlighted in the article further below. The relevance of incentives for small and medium businesses as a way of creating new jobs in these villages and municipalities is separately discussed. Key words: efficiency, development, initiative group, internally displaced persons, settl Introduction and review of literature. Scientists around the world are paying close attention to the study of social factors of sustainable development of local rural communities inhabiting small settlements. Works on this topic have appeared since the 1970s. And develop to the present day. In particular, Cheryl King [1], Horst Rittel [2], Camilla Stivers [3], Melvin Webber [4], P. Fredericksen [5] and the others came to the conclusion that the degree of success with which the local village community copes with its tasks, objectives and problems depends to a large extent on the social capital of managers and Leaders of these rural communities, and stressed the need to increase investment in the development of such leaders. For measuring efficiency results of the mixed initiative groups working in the area of stabilization of communities that accept IDPs several rounds of research were conducted in 2016, the results of which have not yet been widely published. The survey, which formed part of the mentioned research [6], covered representatives of the initiative groups from 34 communities – project participants of a program of re-socialization of IDPs in hosting communities in Eastern and Southern regions of Ukraine. JEL: Q01, A23, J11 JEL: Q01, A23, J11 at least 50 % of IDPs. The purpose of the article is to show productive features of irregularly formed initiative groups in local settlements that accepted IDPs, which could be useful for rural economic advancement of conflict-affected territories. Results and discussion. Research of group performance was conducted in order to show sustainability of local action (initiative) groups after about a year of targeted intervention. The aim was to show their strengths and weaknesses1, and to show the degree of their response to such intervention, as follows from the findings: The question «What social micro-projects were implemented in your community under the program?» – has shown that all participating communities know about at least one of their micro-projects, and some even named 3 of them. This indicates that respondents are very well informed about the role of program development, the essence of intervention and the project name. All groups also know the name of the donor or, at least, an implementer, that shows that the group members are quite responsive to prolonged, regular, intensive external publicity actions. The question: «Please assess the usability of your micro-project (name) for the community on a five-point scale2» showed that members of the community initiative groups were not able to give such an assessment, although gave us merely the names of their small initiatives. This means that they are either not able to think analytically, or do not want to evaluate the effectiveness of the project because they fear the consequences regarding further support. In general, it may indicate unfair approach to the study, no significant experience of participants and the absence of comparative base in their minds. The question: «How strongly united is now your initiative group?3» we got very optimistic results, as compared to other similar studies [7]. The responses seem to be reflecting the groups’ desire to continue cooperation with the territorial development organizations and fearing consequences of recognition of existing misunderstandings and conflicts that might still exist in the groups. In general, however, it is also a sign of the capacity for rapid mobilization of human capital in the host community residents of the South and East of Ukraine. Answers to the question: «What small projects successfully continue working in your community?» showed that almost all communities have active small initiatives, and some have 2 or 3 active projects. Four of the 34 communities (Baydivka, Novokrasnivka, Polovynkine, and Shulhynka) answered that they had no active projects4. Vol 3 No 3 2017 6 ISSN 2414 584X 1 If we consider these features as the basis for the implementation of development projects and, specifically, adaptation of IDPs; 2 Where 1 – rated as “not effective at all”, and 5 – rated as “the most effective”; 3 Using a 4-level scale gradations, from 1= “very united and we continue our joint work”, to 4 = “we are not united at all, in fact, we broke and do not work together anymore”. 4 We must note that these communities have experienced organizational difficulties or disorder and conflict in teams, or potential weakness of the group as a whole. 4 We must note that these communities have experienced organizational difficulties or disorder and conflict in teams, or potential weakness of the group as a whole. HUMAN CAPITAL EFFICIENCY IN INITIATIVE GROUPS ACCEPTING INTERNALLY DISPLACED PERSONS IN THE EASTERN AND SOUTHERN UKRAINE The group included Vol. 3, No. 3, 2017 5 ISSN 2414-584X Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com p y p 2 Where 1 – rated as “not effective at all”, and 5 – rated as “the most effective”; 3 1 If we consider these features as the basis for the implementation of development p specifically, adaptation of IDPs; 2 at least 50 % of IDPs. Because communities were chosen as project partners due to their locations and performance of the role of hosting platforms for IDPs, the overall level of 1 If we consider these features as the basis for the implementation of development projects and, specifically, adaptation of IDPs; 2 h 1 d “ ff i ll” d d “ h ff i ” ere 1 – rated as “not effective at all”, and 5 – rated as “the most effective”; ng a 4-level scale gradations, from 1= “very united and we continue our joint work”, t e not united at all, in fact, we broke and do not work together anymore”. 4 We must note that these communities have experienced organizational difficulties or disorder and conflict in teams, or potential weakness of the group as a whole. Vol. 3, No. 3, 2017 ISSN 2414-584X 6 Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com sustainability of over 88% can be considered strong and acceptable. Fig. 1. Distribution of answers to question: «How strongly united is now your initiative group?», N=34 Source: author’s research Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com ainability of over 88% can be considered strong and acceptable. sustainability of over 88% can be considered strong and acceptable. Fig. 1. Distribution of answers to question: «How strongly united is now your initiative group?» N=34 Fig. 1. Distribution of answers to question: «How strongly united is now your initiative group?», N=34 Source: author’s research. Source: author s research. Answers to the question «Does your initiative group plan to continue cooperarion in the future?» – have shown a very optimistic result: Fig. 2. Distribution of answers to question: «Does your initiative group plan to continue cooperarion in the future?», N=34 S th ’ h Fig. 2. Distribution of answers to question: «Does your initiative group plan to continue cooperarion in the future?», N=34 Source: author’s research. This result, among other things, indicates a high level of value-added social capital5 and, in general, the success of implemented small projects. However, as the percentage of positive responses is very high, some of them can show the reluctance to reveal the true situation and real motives dominating in groups. At the same time, the degree of extra motivation, acquired by the groups as a result of positive successful cooperation, can be rated as high. 5 In the understanding a social «glue» that connects a group in relationships of trust and productive cooperation. Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com iastic work, but probably tend to quickly break down in the case of failure6. The question «What exactly are you going to do?» showed that only 8 of the 34 communities (approx. 22 %) have no clear plans, while all others had clearly identified areas of future performance and sometimes even knew the source of funds for their implementation. This means that community groups and activities continued cooperation even after the development funding from the IDP project source. At the same time, most of the groups indicated infrastructure projects as priorities, and only 3 of 34 responses indicated «soft» projects (green tourism, activities in clubs, co- operatives). This points to the fact that members of groups work under the concept in which the focus of development is strongly given to its technical support, while the element of human development is moved far to the background. Then the respondents were asked a question: «In the future, what projects you would like and could implement more effectively to prevent irregular work migration from your village or town?». The purpose of the question was to determine the severity of the problems of ordinary labor migration7 as well as potential ways of reaction of the initiative group to the issue. As a result, however, more than half of the responses have not been clearly defined. Another 9 % of respondents identified the work migration issue as irrelevant for their settlements. Up to 10 % of respondents acknowledged the serious character of the migration issue but did not determine any ways to resolve it. Only 6 of the 34 groups indicated specific ways, usually relevant in such situations. All other answers showed either the general willingness to “do something” to address this issue, or the typical infrastructure proposals. Thus, we can determine that the problem of migration in classic form for most communities that have accepted IDPs under normal conditions is not much relevant, although some lack of jobs is felt in at least a half of the communities. Interestingly, only two groups have proposed to create businesses in agriculture8, and one group reminded on the need for investors to deal with unemployment issues. Thus, with separate exceptions, it seems highly unpromising develop private entrepreneurship in response to unemployment in these communities. This, however, was shown in similar and past research [8]. Vol. 3, No. 3, 2017 8 ISSN 2414-584X 6 Therefore their social capital was high at the moment of research but probably not sustainable in the long run. 7 As separate to the type of chaotic refugeeitype migration caused by violent conflict in the East. 8 A small farm, among other proposals, in vill. Nyzhnya Duvanka and a grapes processing plant in the vill.Studenok. at least 50 % of IDPs. In other words, groups in these communities have been quickly formed, showed themselves as cheerful and Vol. 3, No. 3, 2017 ISSN 2414-584X 7 Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com 8 A small farm, among other proposals, in vill. Nyzhnya Duvanka and a grapes processing plant in the vill.Studenok. Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com The question «Please rate the relationship of your initiative group with local, district authorities» – received very positive responses displayed below. Compared to other similar studies, we have a very high percentage of positive responses. This can partly be explained by the fact that the authorities in the region are in conditions close to the territory of anti-terrorist operation and are therefore sensitive to community needs. On the other hand, we must recognize that the decision-making processes in the «state-community» relationship in this region Vol. 3, No. 3, 2017 ISSN 2414-584X 8 Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com require separate treatment and study of other scientists. Fig. 3. Distribution of answers to question: «Please rate the relationship of your initiative group with local, district authorities», N=34 Source: author’s research. Answers to the question: «In your opinion, has there been an increase of visitors to the institution in which the reconstruction was funded by the donor, compared to the time when it stayed without repairs?» – received almost unequivocally positive responses. Fig. 4. Distribution of answers to question: «In your opinion, has there been an increase of visitors to the institution in which the reconstruction was funded by the donor, compared to the time when it stayed without repairs?», N=34 Source: author’s research. As you can see, this distribution shows a very high efficiency of measures aimed at restoration of infrastructure in the communities, and not only because the community accepted IDPs9 from other regions and this necessitated the renovations, Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com require separate treatment and study of other scientists. Fig. 3. Distribution of answers to question: «Please rate the relationship of your initiative group with local, district authorities», N=34 Source: author’s research. Answers to the question: «In your opinion, has there been an increase of visitors to the institution in which the reconstruction was funded by the donor, compared to the time when it stayed without repairs?» – received almost unequivocally positive Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com require separate treatment and study of other scientists. require separate treatment and study of other scientists. q p y Fig. 3. Distribution of answers to question: «Please rate the relationship of your initiative group with local, district authorities», N=34 Source: author’s research. 9 Answers in the «Other» group were concerned with the fact that the renovations have not yet begun and it was thus difficult to measure the increase in attendance. Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com Answers to the question: «In your opinion, has there been an increase of visitors to the institution in which the reconstruction was funded by the donor, compared to the time when it stayed without repairs?» – received almost unequivocally positive responses. responses. Fig. 4. Distribution of answers to question: «In your opinion, has there been an increase of visitors to the institution in which the reconstruction was funded by the donor, compared to the time when it stayed without repairs?», N=34 Source: author’s research. As you can see, this distribution shows a very high efficiency of measures aimed at restoration of infrastructure in the communities and not only because the Fig. 4. Distribution of answers to question: «In your opinion, has there been an increase of visitors to the institution in which the reconstruction was funded by the donor, compared to the time when it stayed without repairs?», N=34 Source: author’s research. Fig. 4. Distribution of answers to question: «In your opinion, has there been an increase of visitors to the institution in which the reconstruction was funded by the donor, compared to the time when it stayed without repairs?», N=34 Source: author’s research. As you can see, this distribution shows a very high efficiency of measures aimed at restoration of infrastructure in the communities, and not only because the community accepted IDPs9 from other regions and this necessitated the renovations, As you can see, this distribution shows a very high efficiency of measures aimed at restoration of infrastructure in the communities, and not only because the community accepted IDPs9 from other regions and this necessitated the renovations, 9 Answers in the «Other» group were concerned with the fact that the renovations have not yet begun and it was thus difficult to measure the increase in attendance. Vol. 3, No. 3, 2017 ISSN 2414-584X ISSN 2414-584X 9 Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com but also because these facilities have long, sometimes from the mid 1980s, stayed without any sufficient repairs and the communities obviously assessed the renovations as public benefits. The question «What have you personally done to improve the local social adaptation project10?» – has received the following answers. Fig. 5. Distribution of answers to question: “What have you personally done to improve the local social adaptation project?”, N=34 S th ’ h Fig. 5. 10 The respondents could indicate up to 3 options in their answers. Vol. 3, No. 3, 2017 10 10 The respondents could indicate up to 3 options in their answers. Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com Distribution of answers to question: “What have you personally done to improve the local social adaptation project?”, N=34 S h ’ h p Source: author’s research. More than half of respondents participated in the initiative groups, of whom approximately a half has supervised repair works and the other half was preparing the opening events. Interestingly, the option «was among the visitors at the opening» was chosen by only five people, and the option «attended training» was not chosen at all. This means that the group clearly divided functions between the project administration and the public action. Training has not been a priority for the group's core, despite the effort spent on its organization [8] as it appears that some people were implementing the local projects, and quite other people attended capacity building trainings. In order to obtain a clearer picture of the social structure and the effectiveness of the initiative group, polling on gender issues was conducted in host communities in the East and South of Ukraine in 2015 as part of a larger research. Gender of respondents from 34 communities was distributed at 82.4 % women vs. 17.6 % men. As we can see, the majority of respondents were women. This structure of initiative groups, and especially – the activists who are centers of ideas and sources of decisions – shows that in the target region, women traditionally occupy leading roles in such initiatives and sectors of the labor market. There is probably a fairly small proportion of men in such groups due to the fact that they didn’t show much interest in the group work; occupied with their own employment and earning money; or men ISSN 2414-584X 10 Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com were absent in the settlement (temporarily left it because of the conflict). However, this only strengthens the hypothesis that most of the groups’ decisions will have a «female» character. The age of respondents from 34 communities was distributed as follows. The age of respondents from 34 communities was distributed as follows. Fig 6 Distribution of age of respondents N=34 g p Fig. 6. Distribution of age of respondents, N=34 Fig. 6. Distribution of age of respondents, N=34 g Source: author’s research. In this example we can see that initiative groups are mostly female, and are strongly represented by participants aged 36–42 and 50–57, and underrepresented by members under 35 and 43–49. Also the age distribution «gap» in observed in the interval of 52 to 53. So these two groups aged 36-42 and 50–57 apparently represent a «junior» and «senior» active and educated community members11. j y Below is an analysis of a pair of related gender-based questions, namely, answers to the questions: «Was it necessary for men in your group to perform female work?» (Fig. 7) and «as it necessary for women in your group to perform men’s work» (Fig. 8). Fig. 7. Distribution of answers to question: «Was it necessary for men in your group to perform female work?», N=34 Source: author’s research. 11 Of which at least half is IDPs – as the research has covered the IDP accepting communities. Fig. 7. Distribution of answers to question: «Was it necessary for men in your group to perform female work?», N=34 S h ’ h g p p , Source: author’s research. 11 Of which at least half is IDPs – as the research has covered the IDP accepting communities. Vol. 3, No. 3, 2017 ISSN 2414-584X 11 Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com Fig. 8. Distribution of answers to question: «Was it necessary for women in your group to perform men’s work?», N=34 Source: author’s research. Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com Fig. 8. Distribution of answers to question: «Was it necessary for women in your group to perform men’s work?», N=34 S h ’ h g p Source: author’s research. The answer to the questions above have shown show that the initiative groups that worked on adaptation of IDPs felt the lack of men and their roles have not always been adequately distributed. Obviously, in times of crisis, activists, especially women, often took the men's work, especially in the situations of very low social activity of men or the men’s absence in the initiative groups. Below is an analysis of questions asked to determine the degree of development of groups in terms of socio-gender «specialization». Fig. 9. Distribution of answers to question: «Did you feel that your team lacked (…male support, female support, nothing)?», N=34 Source: author’s research. Fig. 6. Distribution of age of respondents, N=34 As you can see, about 18% of the group was formed so that functional male support was lacking there. Note that the question «Did you feel ...» also had an answer option «female support», but it was not chosen by anyone. So, not only can it be stated that women were actively involved in the projects, but we’d like to emphasize once again that women sometimes performed typically men’s work as the Fig. 9. Distribution of answers to question: «Did you feel that your team lacked (…male support, female support, nothing)?», N=34 Source: author s research. As you can see, about 18% of the group was formed so that functional male support was lacking there. Note that the question «Did you feel ...» also had an answer option «female support», but it was not chosen by anyone. So, not only can it be stated that women were actively involved in the projects, but we’d like to emphasize once again that women sometimes performed typically men’s work as the men in local communities were not willing to take part in such projects. Sou ce: aut o s esea c . As you can see, about 18% of the group was formed so that functional male support was lacking there. Note that the question «Did you feel ...» also had an answer option «female support», but it was not chosen by anyone. So, not only can it be stated that women were actively involved in the projects, but we’d like to emphasize once again that women sometimes performed typically men’s work as the men in local communities were not willing to take part in such projects. Analysis of responses to the question: «Have you noticed that difficult or responsible tasks in the project were avoided by ... (men, women, no one)?» – has Vol. 3, No. 3, 2017 ISSN 2414-584X 12 Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com shown that 100 % of respondents chose the option «no one». At the same time, the analysis of responses to the question: «Did you experience situations in conflicts / disputes on the project, when men had a different position than women?» – has shown that 100 % of respondents chose the answer «no». 13 Despite the significant differences from community to community and variations in the structure of the local labor markets. 12 But also in Donetska and other regions, including the Crimea before the conflic 13 12 But also in Donetska and other regions, including the Crimea before the conflict. 13 Despite the significant differences from community to community and variations in the structure of the local labor markets. Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com the activity of women in the group lies in the fact that in their near-retirement age [10], they have more time and energy than men. the activity of women in the group lies in the fact that in their near-retirement age [10], they have more time and energy than men. Conclusions. As a working hypothesis of the study, it was determined that such features as the ability of mixed community initiative groups of rapid resource mobilization and quick value-added growth in the their social capital – as proved by the program that helped integrate the internally displaced people in southern and eastern Ukraine – could be useful in further implementation of economic development programs in local communities. This hypothesis has partly proven to be true, but has reservations. The following results speak in favor of the hypothesis: the group members are quite responsive to prolonged, regular, intensive external publicity actions; the overall level of remaining sustainability of over 88 % can be considered strong and acceptable; the degree of extra motivation, acquired by the groups as a result of positive successful cooperation, can be rated as high. However, the following factors impede the realization of the potential of community initiative groups for local economic development programs: group members sometimes are either not able to think analytically, or do not want to evaluate the effectiveness of the projects because they fear the consequences regarding further support; which may indicate unfair approach to the study, no significant experience of participants and the absence of comparative base in their minds. Members of groups work under the concept in which the focus of development is strongly given to its technical support, while the element of human development is moved far to the background. Although some lack of jobs is felt in at least a half of the communities, only two groups have proposed to create businesses in agriculture, and only one reminded on the need for investors to deal with unemployment issues. Training has not been a priority for the groups’ cores, despite the effort spent on its organization. The groups felt the lack of men and their roles have not always been adequately distributed. Fig. 6. Distribution of age of respondents, N=34 These responses differ from data obtained in previous studies of gender issues [9] with similar questions, - studies performed in peacetime and in other communities12. This also, against the background of dominance of women’s presence, shows that it is women in host communities and especially – in the initiative groups on adaptation – who are sources of decision-making of final opinion. Answers the following questions measuring value-added public good in communities have been distributed as follows (Fig. 10): Fig. 10. Distribution of answers to question: «Who received greater benefits from the project, meaning both the people who got employed and beneficiaries of project services?», N=34 S th ’ h Fig. 10. Distribution of answers to question: «Who received greater benefits from the project, meaning both the people who got employed and beneficiaries of project services?», N=34 Source: author’s research. Please note that answers to this question also had an option «men», but it was not chosen by any of the respondents. Thus, in projects on IDP adaptation through the development of infrastructure and social tolerance in local communities, there is a clear focus on creating such social initiatives that traditionally create jobs/activities for women. Besides, as these projects are characterized by a common public good, there is a fact that it both genders in a territorial community benefited from them. The analysis of the question «Why do you think so?» the was asked to clarify answers to the previous question showed the following: most respondents are inclined to believe that women received greater benefit from projects on IDP integration because they were more active and were striving to use all the options of the development program. Although, in some communities where jobs have been open mostly for men (such as mining settlements), it was mostly men who benefited from IDP adaptation projects. Over 40 % of respondents have noted that women within initiative groups were more active than men13. Thus it is believed that the reason for Vol. 3, No. 3, 2017 ISSN 2414-584X ISSN 2414-584X 13 Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com In times of crisis, activists, especially women, often took the men's work, especially because of very low social activity of men or the men’s absence in the initiative groups. It appeared that men are not participating more than women in the micro-project or program because in the target region, women traditionally occupy leading roles in such initiatives and sectors of the labor market. Although we admit that the results of this study can be shared to other regions with similar/different conditions (especially in Donbas region), the identification of features and tools for such sharing can be subject to a separate study. References References Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com 4. Rittel, H. W. J. and Webber, M. M. (1973), Dilemmas in a General Theory of Planning. Policy Sciences, vol. 4(2), pp. 155–169. 5. Fredericksen, P. J. (2004), Building Sustainable Communities: Leadership Development along the U.S.-Mexico Border. Public Administration Quarterly, vol. 28, no. 1/2, pp. 148–181. 6. Zavadovska, Y. Y. (2016), Efficiency management in territorial projects of support to forced migrants. Scientific Messenger of the LNUVM BT. Series: economic sciences, vol. 4, pp. 183–188. pp 7. Filyak, M. S. and Zavadovska, Y. Y. (2016), A survey of results of efficiency of integration of internally displaced persons in the social structure of the host communities in the regions of Ukraine. Prychornomorski ekonomichni studii, vol. 7, pp. 197–201. 8. Filyak, M. S. and Dushka, V. I. (2013), Napryamy reformuvannya kooperatyvnykh silskohospodarskykh pidpryyemstv: problemy i perspektyvy [Areas of reform of cooperative agricultural enterprises: problems and prospects] in Development of rural territories. Organizational and legal forms in agriculture, ed P. M. Muzyka, SPOLOM, Lviv, Ukraine. 9. Muzyka, P. and Filyak, M. (2016), Improved policy making through enhanced dialogue and focused education. Agricultural and Resource Economics: International Scientific E-Journal, [Online], vol. 2, no. 3, pp. 37–47, available at: www.are-journal.com. 9. Muzyka, P. and Filyak, M. (2016), Improved policy making through enhanced dialogue and focused education. Agricultural and Resource Economics: International Scientific E-Journal, [Online], vol. 2, no. 3, pp. 37–47, available at: www.are-journal.com. 10. Zavadovska, Y. Y. and Filyak, M. S. (2016), Migratsiyni potoky naselennya u period kryzy: vplyv na sotsialno-ekonomichnyy rozvytok u regionakh Ukrainy [Migration flows of population during the crisis: the impact on social and economic development in the regions of Ukraine], SPOLOM, Lviv, Ukraine. 10. Zavadovska, Y. Y. and Filyak, M. S. (2016), Migratsiyni potoky naselennya u period kryzy: vplyv na sotsialno-ekonomichnyy rozvytok u regionakh Ukrainy [Migration flows of population during the crisis: the impact on social and economic development in the regions of Ukraine], SPOLOM, Lviv, Ukraine. How to cite this article? Як цитувати цю статтю? Стиль – ДСТУ: Стиль – ДСТУ: Muzyka P. Human capital efficiency in initiative groups accepting internally displaced persons in the eastern and southern Ukraine [Electronic resource] / P. Muzyka, M. Filyak // Agricultural and Resource Economics : International Scientific E-Journal. – 2017. – Vol. 3. – No. 3. – Pp. 5–15. – Mode of access : www.are-journal.com. References 1. King, C. A., Ewell Foster, C. and Rogalski, K. (2013), Teen Suicide Risk. A practitioner guide to screening, assessment and care management. The Guilford Press, New York, USA. 1. King, C. A., Ewell Foster, C. and Rogalski, K. (2013), Teen Suicide Risk. A practitioner guide to screening, assessment and care management. The Guilford Press, New York, USA. 2. Rittel, Horst W. J. (1988), Annual Report of Faculty Achievement, The University of California, Berkeley, USA. 2. Rittel, Horst W. J. (1988), Annual Report of Faculty Achievement, The University of California, Berkeley, USA. y y 3. Stivers, C. (2008), Public Administration’s Myth of Sisyphus. Administration & Society, vol. 39, is. 8, pp. 1008–1012. https://doi.org/10.1177/0095399707309814. Vol. 3, No. 3, 2017 ISSN 2414-584X 14 Agricultural and Resource Economics: International Scientific E-Journal www.are-journal.com Style – Harvard: Muzyka, P. and Filyak, M. (2016), Human capital efficiency in initiative groups accepting internally displaced persons in the eastern and southern Ukraine. Agricultural and Resource Economics: International Scientific E-Journal, [Online], vol. 2, no. 3, pp. 5–15, available at: www.are-journal.com. Vol. 3, No. 3, 2017 15 ISSN 2414-584X
https://openalex.org/W2947913598
https://europepmc.org/articles/pmc6600172?pdf=render
English
null
Targeting Angiogenesis in Prostate Cancer
International journal of molecular sciences
2,019
cc-by
11,116
Received: 7 May 2019; Accepted: 29 May 2019; Published: 31 May 2019 Abstract: Prostate cancer is the most commonly diagnosed cancer among men in the Western world. Although localized disease can be effectively treated with established surgical and radiopharmaceutical treatments options, the prognosis of castration-resistant advanced prostate cancer is still disappointing. The objective of this study was to review the role of angiogenesis in prostate cancer and to investigate the effectiveness of anti-angiogenic therapies. A literature search of clinical trials testing the efficacy of anti-angiogenic therapy in prostate cancer was performed using Pubmed. Surrogate markers of angiogenic activity (microvessel density and vascular endothelial growth factor A (VEGF-A) expression) were found to be associated with tumor grade, metastasis, and prognosis. Six randomizedstudies were included in this review: two phase II trials on localized and hormone-sensitive disease (n = 60 and 99 patients) and four phase III trials on castration-resistant refractory disease (n = 873 to 1224 patients). Although the phase II trials showed improved relapse-free survival and stabilisation of the disease, the phase III trials found increased toxicity and no significant improvement in overall survival. Although angiogenesis appears to have an important role in prostate cancer, the results of anti-angiogenic therapy in castration-resistant refractory disease have hitherto been disappointing. There are various possible explanations for this lack of efficacy in castration-resistant refractory disease: redundancy of angiogenic pathways, molecular heterogeneity of the disease, loss of tumor suppressor protein phosphatase and tensin homolog (PTEN) expression as well as various VEGF-A splicing isoforms with pro- and anti-angiogenic activity. A better understanding of the molecular mechanisms of angiogenesis may help to develop effective anti-angiogenic therapy in prostate cancer. Keywords: prostate cancer; angiogenesis; VEGF-A; splicing isoforms Keywords: prostate cancer; angiogenesis; VEGF-A; splicing isoforms International Journal of Molecular Sciences Review Zsombor Melegh 1 and Sebastian Oltean 2,* Zsombor Melegh 1 and Sebastian Oltean 2,* 1 Department of Cellular Pathology, Southmead Hospital, Bristol BS10 5NB, UK; zsombor.melegh@nbt.nhs.uk 2 Institute of Biomedical and Clinical Sciences, Medical School, College of Medicine and Health, University of Exeter, Exeter EX12LU, UK * Correspondence: s.oltean@exeter.ac.uk 1 Department of Cellular Pathology, Southmead Hospital, Bristol BS10 5NB, UK; zsombor.melegh@nb 2 Institute of Biomedical and Clinical Sciences, Medical School, College of Medicine and Health, University of Exeter, Exeter EX12LU, UK 1 Department of Cellular Pathology, Southmead Hospital, Bristol BS10 5NB, UK; zsombor.melegh@nbt.nh 2 Institute of Biomedical and Clinical Sciences, Medical School, College of Medicine and Health, University of Exeter, Exeter EX12LU, UK * Correspondence: s.oltean@exeter.ac.uk 2.2. Treatment Options in Prostate Cancer Prostate cancer staging is divided into four stages. Stage 1 and 2 cancers are localized to the prostate whilst stage 3 cancers extend into the periprostatic tissue or the seminal vesicle, without involvement of a nearby organ or lymph node and with no distant metastasis [8]. Stage 4 tumors represent those that have spread to nearby or distant organs or lymph nodes [8]. Stage 1 tumors and stage 2 tumors of low and intermediate risk (Table 1) can be followed up by ‘watchful waiting’ or active surveillance and monitoring [9,10]. Watchful waiting has no curative intent, whilst active surveillance and monitoring defers treatment with curative intent to a time when it is needed [9]. Therefore, in active surveillance and monitoring therapy is reserved for tumor progression, with a 1–10% mortality rate [9]. Table 1. Risk stratification of localized prostate cancer according to NICE guidance, UK [10]. Gleason score: histological pattern of the tumor. Stage T1–T2a: tumor involving <50% of one lobe. Stage T2b: tumor involving ≥50% of one lobe. Stage T2c: tumor involving both lobes. NICE stands for the National Institute for Health and Care Excellence. PSA stands for Prostate-Specific Antigen. Table 1. Risk stratification of localized prostate cancer according to NICE guidance, UK [10]. Gleason score: histological pattern of the tumor. Stage T1–T2a: tumor involving <50% of one lobe. Stage T2b: tumor involving ≥50% of one lobe. Stage T2c: tumor involving both lobes. NICE stands for the National Institute for Health and Care Excellence. PSA stands for Prostate-Specific Antigen. Table 1. Risk stratification of localized prostate cancer according to NICE guidance, UK [10]. Gleason score: histological pattern of the tumor. Stage T1–T2a: tumor involving <50% of one lobe. Stage T2b: tumor involving ≥50% of one lobe. Stage T2c: tumor involving both lobes. NICE stands for the National Institute for Health and Care Excellence. PSA stands for Prostate-Specific Antigen. Level of Risk PSA Level (ng/mL) Gleason Score Clinical Stage Low risk <10 and ≤6 and T1–T2a Intermediate risk 10–20 or 7 or T2b High risk >20 or 8–10 or ≥T2c Level of Risk PSA Level (ng/mL) Gleason Score Clinical Stage Low risk <10 and ≤6 and T1–T2a Intermediate risk 10–20 or 7 or T2b High risk >20 or 8–10 or ≥T2c Radical prostatectomy is a treatment option for localized tumors in patients with few comorbidities. 2.1. Prostate Cancer Prostate cancer is characterized by slow to moderate growth. Consequently, many cases are indolent and in up to 70% of incidentally diagnosed cases over 60 years death is due to an unrelated cause [4]. The five-year relative survival rate for men diagnosed in the USA between 2001 and 2007 with local or regional disease was 100%, whilst the rate for distant disease was 28.7% [5]. UK statistics show similar results: the five-year relative survival for prostate cancer was 100% in localized disease and 30% in distant disease for patients diagnosed during 2002–2006 in the former Anglia Cancer Network [6]. Most cases of prostate cancer are diagnosed by prostate specific antigen (PSA) testing or rarely by rectal examination. Prostate cancer can present with decreased urinary stream, urgency, hesitancy, nocturia, or incomplete bladder emptying, but these symptoms are non-specific and are infrequent at diagnosis [7]. 1. Introduction Prostate cancer is the most commonly diagnosed cancer in men in the Western world, with a median age at diagnosis of 66 years [1]. There will be an estimated 160,000 new cases and 30,000 deaths in 2018 in the USA, representing 19% of all new cancer diagnoses and 9% of all cancer related deaths, respectively [2]. In the United Kingdom, over 47,000 men are diagnosed with prostate cancer every year, with over 330,000 men currently living with the disease [3]. The purpose of this literature review is to assess whether angiogenesis is important in prostate cancer and, if so, whether anti-angiogenic therapies are effective in the treatment of prostate cancer. To begin with, the current treatment options in prostate cancer will be discussed, along with a summary of what is already known in relation to angiogenesis in cancer. This will be followed by the literature review on angiogenesis and anti-angiogenic therapies in prostate cancer, specifically. Finally, the discussion will consider any treatment difficulties that have emerged in such studies. Int. J. Mol. Sci. 2019, 20, 2676; doi:10.3390/ijms20112676 www.mdpi.com/journal/ijms www.mdpi.com/journal/ijms Int. J. Mol. Sci. 2019, 20, 2676 2 of 16 2.2. Treatment Options in Prostate Cancer Although this provides an improvement in disease progression compared to active surveillance and monitoring, it does not translate into a statistical difference in mortality: 10-year cancer-specific survival rates were 98.8% with active surveillance and monitoring compared to 99% with radical prostatectomy [9]. Complications of radical prostatectomy include the mortality and morbidity associated with major surgery and anaesthesia, penile shortening, impotence, urinary and faecal incontinence, and inguinal hernia [8]. Radiation and radiopharmaceutical treatment options include external-beam radiation therapy (EBRT), interstitial implantation of radioisotopes into the prostate and hormonal manipulation [9]. EBRT is used with curative intent in all stages of prostate cancer, with or without adjuvant hormonal therapy. Interstitial implantation of radioisotopes is used in patient with stage 1 and 2 tumors. Short term results are similar to those seen with EBRT or radical prostatectomy, but the maintenance of sexual potency is significantly higher (86–96%) when compared to radical prostatectomy or EBRT (10–40% and 40–60%, respectively) [11]. Int. J. Mol. Sci. 2019, 20, 2676 3 of 16 Hormonal manipulation options include surgical castration (orchidectomy) or medical castration (LH-RH antagonists) [12]. These may be used in stage 3 or 4 cancers and can be enhanced by the addition of anti-androgenic therapy and adjuvant treatment with bisphosphonates [13]. Recently approved anti-androgen agents include abiraterone acetate, an inhibitor of cytochrome P450c17, a critical enzyme in androgen synthesis and enzalutamide, a second generation androgen-receptor–signaling inhibitor [13–15]. Int. J. Mol. Sci. 2019, 20, x FOR PEER REVIEW 3 of 16 Treatment options for high stage metastatic hormone-refractory prostate cancer include active cellular immunotherapy with sipuleucel-T, which has resulted in increased overall survival in metastatic castration-resistant prostate cancer, in a double-blind, placebo-controlled, multicenter phase 3 trial [16]. This lead to its approval for the treatment of asymptomatic or minimally symptomatic patients with nonvisceral metastatic castration-resistant prostate cancer in 2010. Radium-223 dichloride is used in symptomatic patients with bone metastases and no known visceral metastases [17]. Cabazitaxel, a derivative of docetaxel, is approved as a second line chemotherapy agent [18]. Further possible treatment options to prevent bone metastases include denosumab (a monoclonal antibody that inhibits osteoclast function) [19] and bone-seeking radionucleotides (strontium chloride Sr 89) [20]. Treatment options for high stage metastatic hormone-refractory prostate cancer include active cellular immunotherapy with sipuleucel-T, which has resulted in increased overall survival in metastatic castration-resistant prostate cancer, in a double-blind, placebo-controlled, multicenter phase 3 trial [16]. 2.3. Angiogenesis in Cancer angiogenesis. Angiogenesis is defined as the development of new vascular vessels from pre-existing blood vessels. It has a critical role in wound healing and embryonic development and also provides collateral formation for improved organ perfusion in ischaemia [22]. It is a multi-step process triggered by an angiogenic stimulus (Figure 1). The first step of the process is the production of proteases which degrade the basement membrane. This is followed by migration and proliferation of the endothelium, resulting in the formation of a new vascular channel [23]. 2.3. Angiogenesis in Cancer Angiogenesis is defined as the development of new vascular vessels from pre-existing blood vessels. It has a critical role in wound healing and embryonic development and also provides collateral formation for improved organ perfusion in ischaemia [22]. It is a multi-step process triggered by an angiogenic stimulus (Figure 1). The first step of the process is the production of proteases which degrade the basement membrane. This is followed by migration and proliferation of th d th li lti i th f ti f l h l [23] Figure 1. Angiogenesis in cancer. Hypoxia within the tumor induces the release of pro-angiogenic factors and results in degradation of the basement membrane by matrix metalloproteinases (MMP). The endothelial cells start to differentiate and proliferate, forming new blood vessels. The newly formed blood vessels allow further tumor growth. Figure 1. Angiogenesis in cancer. Hypoxia within the tumor induces the release of pro-angiogenic factors and results in degradation of the basement membrane by matrix metalloproteinases (MMP). The endothelial cells start to differentiate and proliferate, forming new blood vessels. The newly formed blood vessels allow further tumor growth. Figure 1. Angiogenesis in cancer. Hypoxia within the tumor induces the release of pro-angiogenic factors and results in degradation of the basement membrane by matrix metalloproteinases (MMP). The endothelial cells start to differentiate and proliferate, forming new blood vessels. The newly formed blood vessels allow further tumor growth. Figure 1. Angiogenesis in cancer. Hypoxia within the tumor induces the release of pro-angiogenic factors and results in degradation of the basement membrane by matrix metalloproteinases (MMP). The endothelial cells start to differentiate and proliferate, forming new blood vessels. The newly formed blood vessels allow further tumor growth. 2.2. Treatment Options in Prostate Cancer This lead to its approval for the treatment of asymptomatic or minimally symptomatic patients with nonvisceral metastatic castration-resistant prostate cancer in 2010. Radium-223 dichloride is used in symptomatic patients with bone metastases and no known visceral metastases [17]. Cabazitaxel, a derivative of docetaxel, is approved as a second line chemotherapy agent [18]. Further possible treatment options to prevent bone metastases include denosumab (a monoclonal antibody that inhibits osteoclast function) [19] and bone-seeking radionucleotides (strontium chloride Sr 89) [20]. Despite a widening arsenal of new treatment options, a cure is rarely achieved in stage 4 prostate cancer, although there is astriking difference in treatment response between individual patients [21]. Such outcomes emphasize the need for research into further treatment options in hormone-refractory advanced prostate cancer. One such emerging therapeutic option is inhibition of tumor-related angiogenesis. (strontium chloride Sr 89) [20]. Despite a widening arsenal of new treatment options, a cure is rarely achieved in stage 4 prostate cancer, although there is astriking difference in treatment response between individual patients [21]. Such outcomes emphasize the need for research into further treatment options in hormone-refractory advanced prostate cancer. One such emerging therapeutic option is inhibition of tumor-related 2.3. Angiogenesis in Cancer angiogenesis. Although angiogenesis is not entirely necessary for tumor initialization (some tumors of the brain, lung, and liver can grow along pre-existing vessels) [23], once a tumor reaches a size of more than a few millimeters, formation of new blood vessels is necessary to provide an appropriate blood supply to support tumor cell viability and proliferation. Hence, angiogenesis plays an important role in tumor progression and is now recognized as one of the hallmarks of cancer [24]. Angiogenesis is controlled by a delicate balance between angiogenesis inducers and Although angiogenesis is not entirely necessary for tumor initialization (some tumors of the brain, lung, and liver can grow along pre-existing vessels) [23], once a tumor reaches a size of more than a few millimeters, formation of new blood vessels is necessary to provide an appropriate blood supply to support tumor cell viability and proliferation. Hence, angiogenesis plays an important role in tumor progression and is now recognized as one of the hallmarks of cancer [24]. Int. J. Mol. Sci. 2019, 20, 2676 4 of 16 Angiogenesis is controlled by a delicate balance between angiogenesis inducers and angiogenesis inhibitors. In a growing cancer there is a constant production of angiogenesis inducers, including vascular endothelial growth factor (VEGF)-A, basic fibroblast growth factor (bFGF, also known as FGF), angiogenin, tumor necrosis factor (TNF)-α, granulocyte colony-stimulating factor (G-CSF), platelet-derived endothelial growth factor (PDGF), placental growth factor (PGF), transforming growth factor (TGF)-α, TGF-β, interleukin-8 (IL-8), hepatocyte growth factor (HGF), and epidermal growth factor (EGF) [22]. This constant production of angiogenesis inducers results in increased activity of endothelial cells, as long as the production of anti-angiogenic factors is correspondingly reduced [25]. Among the angiogenesis activators, VEGF-A and bFGF are particularly important in tumor angiogenesis. The abundance and redundant activities of different angiogenesis inducers may explain the resistance or suboptimal effectiveness of anti-angiogenic therapies, when inhibitors acting only on a single angiogenesis activator are being used [25]. Under normal conditions, angiogenesis inducers are balanced by naturally occurring angiogenesis inhibitors, such as endostatin, angiostatin, IL-1, IL-12, interferons, metalloproteinase inhibitors, and retinoic acid [25,26]. These inhibitors can either disrupt new vessel formations or can help to remove already formed vascular channels. Shifting the balance towards angiogenesis inhibition can interfere with important physiological roles of angiogenesis, such as in embryo development, wound healing, and renal function. 2.3. Angiogenesis in Cancer angiogenesis. Interference with wound healing is a particularly important concern in cancer treatment, for example resulting in delayed post-operative healing [27]. Another example involves the inhibition of VEGF-A, resulting in vasoconstriction by means of elevated NO production, consequently elevating blood pressure [28], and increasing the risk of thrombogenesis, resulting in stroke or myocardial infarction. These factors can potentially limit the use of angiogenesis inhibition in cancer, on account of their potential side effects. 2.4. Angiogenesis Inhibition in Cancer Although angiogenesis is an essential factor in tumor progression, by means of new vessel formation, this also means that angiogenesis inhibition may only result in inhibition of further tumor growth and may not actively eliminate the tumor. This, and the redundancy of the numerous angiogenesis inducers as listed above, explain why the utilization of angiogenesis inhibitors as a monotherapy has not proved to be as effective as initially expected [29]. Hence, angiogenesis inhibitor therapeutic regimes may require a combination of several anti-angiogenic strategies or may need to be complemented by other non-angiogenesis related chemotherapeutic agents in order to achieve an optimal therapeutic effect [30]. Based on the target of the therapeutic agent, angiogenesis inhibition can be divided into two main groups: direct and indirect inhibition [31]. Direct inhibitors target growing endothelial cells, whilst indirect inhibitors target the tumor cells or tumor-associated stromal cells. Small molecular fragments (e.g., arrestin, tumstatin, canstatin, endostatin, and angiostatin) are the products of proteolytic degradation of the extracellular matrix, and act as direct inhibitors by means of inhibition of the endothelial cell proliferation and migration induced by VEGF-A, bFGF, PDGF, and interleukins [32]. The direct anti-angiogenic effect of targeting integrins (cellular adhesion receptors), has also been demonstrated [32]; an integrin inhibitor—cilentigide—has been shown to inhibit tumor cell invasion [33]. Unfortunately, even though cilentigide acts both on tumor cells and endothelial cells and could be a prime example of multifactorial treatment, results of clinical trials have proved disappointing so far [34]. The most extensively clinically used direct anti-angiogenic strategy targets VEGF-A or its receptors. VEGF-A binds to its receptors to stimulate the proliferation of endothelial cells via the RAS–RAF–MAPK (mitogen-activated protein kinase) signalling pathway [35]. Bevacizumab is a humanised IgG1 monoclonal antibody against VEGF-A. It selectively binds to circulating VEGF-A, preventing its interaction with its receptor, VEGF-receptor 2, expressed on the surface of endothelial cells. Initial studies showed clinical improvement when bevacizumab was used in combination with chemotherapy in a number of cancers, without a marked increase in toxicity [36]. Subsequently it has been approved as part of a combination therapy in the treatment of various cancers, including metastatic lung, Int. J. Mol. Sci. 2019, 20, 2676 5 of 16 colorectal, and renal cell carcinoma, and as a single agent treatment in adult glioblastoma [37]. However, subsequent studies have revealed adverse effects, including gastrointestinal perforation, nephrotic syndrome, thromboembolism, surgical wound healing complications and hypertension [37,38]. 2.4. Angiogenesis Inhibition in Cancer In contrast, indirect angiogenesis inhibition involves an interplay between tumor or stromal cells and angiogenesis. One example involves the inhibition of epidermal growth factor receptor (EGFR), a tyrosine kinase receptor. Tumor cell expression and activation of EGFR induces interleukin production, which is demonstrated to promote intratumoral angiogenesis. Thus, blocking the expression and/or activity of EGFR can result in indirect inhibition of angiogenesis [39]. To summarize, a number of anti-angiogenesis drugs have already been approved and are currently used in cancer treatment. This prompts the question whether angiogenesis plays any role in prostate cancer progression and, if so, whether anti-angiogenic therapy would be effective in refractory castration-resistant prostate cancer, for which the current treatment options are limited. 3.1. Angiogenesis in Prostate Cancer Currently there are no direct markers to assess angiogenic activity in prostate cancer, but it is reasonable to assume that vascular density is an indicator of intratumoral angiogenic activity. Microvessel density (MVD) is considered a good surrogate marker of angiogenic activity and has been demonstrated as a prognostic factor in various tumors, including breast and colon cancers as well as malignant melanoma [40]. MVD can be assessed by histological examination of the vasculature, either by assessing the most vascularised area of the tumor (‘hot spot’) or a random representative area. Preliminary data suggested that MVD is associated with higher tumor grade and stage, and worse outcome in prostate cancer [41,42]. Moreover, ultrasound imaging studies of haemodynamic indices have shown a higher peak intensity in high-grade tumors [43]. Later studies, however, have failed to confirm that MVD is an independent prognostic factor in untreated tumors, and no correlation has yet been established between MVD and effectiveness of anti-angiogenic treatment in prostate cancer [44]. Reasons for these conflicting results potentially include different counting methods, diferences in antibodies used, different population sizes, personal experience and pathological background [45]. A further limiting factor is the complex geometrical structure of the newly fromed vascular system, which is difficult to analyse on a two dimensional histological section [46]. Fractal geometry to estimate the surface dimension, computer aided automated image analysis, 3D models or magnetic resonance imaging could potentially be used to overcome these shortcomings, [46,47]. Another possible surrogate marker for tumor angiogenesis is by an assessment of the level of angiogenic regulators in the tumor. Both physiological and pathological angiogenesis is predominantly regulated by VEGF, which has various protein isoforms, each acting on their specific tyrosine kinase receptor at the cell surface [48]. Among the VEGF isoforms, VEGF-A has been extensively studied, and it has been demonstrated to play an important role in prostate cancer angiogenesis [49]. In addition, VEGF-A has been found to be overexpressed in prostate cancer and a high level of VEGF-A is associated with distant metastasis and a poorer prognosis [50–52]. Furthermore, in prostate cancer a high-level VEGF-A expression has been found not only in endothelial cells, but also in tumor cells [53]. p y These findings suggest that angiogenesis is important in prostate cancer, prompting subsequent clinical studies to assess whether anti-angiogenesis therapy is effective in the treatment of prostate cancer. 3.2. Anti-Angiogenesis Clinical Studies in Prostate Cancer An unfiltered Pubmed search for the keywords “angiogenesis” and “prostate” revealed a steady increase in published papers between 2000 and 2013 (from 70 per year in 2000 to 213 per year in 2013) followed by a slow decline (down to 115 in 2018). This appears to reflect the fact that, despite the promising findings of initial studies, suggesting an important role of angiogenesis in prostate cancer, phase III clinical trials, mainly conducted after 2010, have proved disappointing so far. Int. J. Mol. Sci. 2019, 20, 2676 6 of 16 Since VEGF-A was demonstrated to be overexpressed in prostate cancer and associated with poor prognosis and metastasis, most anti-angiogenic clinical studies in prostate cancer have targeted VEGF-A. A randomizedphase II trial on bevacizumab involving 99 patients with hormone-sensitive prostate cancer showed improved relapse-free survival when bevacizumab was used alongside hormone-deprivation therapy (Table 2) [54]. A randomized, double-blind, placebo-controlled phase III clinical study of 1050 patients with prostate cancer showed some improvement in progression-free survival, but found no significant improvement in overall survival in metastatic, castration-resistant prostate cancer, when bevacizumab was used together with docetaxel chemotherapy and prednisone hormonal therapy [55]. Furthermore, bevacizumab resulted in increased toxicity and a greater incidence of treatment-related deaths [55]. This suggests that bevacizumab has some positive effect, especially on hormone-sensitive recurrent prostate cancer, but in hormone-resistant refractory tumors, in which the conventional treatment options are particularly prone to failure, adding bevacizumab treatment does not have any clinical benefit (Table 2). Table 2. Anti-angiogenesis clinical studies in treatment of prostate cancer. Drug Mechanism of Action Phase of the Clinical Trial Number of Patients Outcome Bevacizumab Recombinant humanized monoclonal antibody that blocks VEGF-A II 99 Improved relapse-free survival [54] III 1050 No improvement in overall survival [55] Aflibercept Binds to circulating VEGF-A III 1224 No improvement in overall survival [56] Sunitinib Receptor tyrosine kinase inhibitor III 873 No improvement in overall survival [57] Lenalidomide Multiple mechanisms, including inhibition of VEGF-induced PI3K-Akt pathway signalling I/II 60 Disease stabilisation, decrease in PSA [58] III 1059 Worse overall survival [59] Table 2. Anti-angiogenesis clinical studies in treatment of prostate cancer. Aflibercept (a hybrid protein composed of various domains of VEGF-receptors 1 and 2, fused to human immunoglobulin G1) also targets the VEGF-A pathway, by acting as a decoy receptor for VEGF-A. 4. Discussion Clinical trials that showed an association between high VEGF-A expression and tumor progression assessed VEGF-A protein levels by immunohistochemistry, ELISA methods, or mRNA levels by reverse-transcription-polymerase chain reaction (RT-PCR). Despite high VEGF-A expression in advanced prostate cancer using these methods, anti-angiogenic therapies targeting the VEGF-A pathway have failed to provide significant treatment benefits [63,64]. There are various possible explanations for resistance to anti-angiogenic therapy in prostate cancer. Redundancy of angiogenic pathways means that targeting a single pathway may result in upregulation of alternative pathways. For example, with long-term bevacizumab treatment, which blocks VEGF-A, there is upregulation of EGF, HGF, and PDGF [65]. Lindholm et al. demonstrated in breast cancer xenografts that targeting these pathways can be effective in anti-angiogenic therapy [66]. A combination of different anti-angiogenic therapies in prostate cancer has also showed some promising results: a phase II study of combined bevacizumab and lenalidomide therapy, added to docetaxel and prednisone chemotherapy and hormonal therapy in 63 patients with metastatic castration-resistant prostate cancer found that combined anti-angiogenic therapy can be safely administered, but further randomizedtrials are required to confirm clinical benefit [67]. Another reason for treatment resistance is due to the fact that prostate cancer is a molecularly heterogeneous disease,= and there is currently a lack of biomarkers that can help select those patients who are likely to benefit from anti-angiogenic therapy or that can assess response to anti-angiogenic treatment [48]. The genetic signature of the VEGF-A pathway or variations in VEGF-A or its receptors could be possible markers to predict therapy response, but these have as yet not been validated [68,69]. It is hoped that further stage III trials will be able to identify subgroups of patients who could benefit from anti-angiogenic treatment. g g Resistance to sunitinib tyrosine-kinase-inhibitor has been shown to be associated with loss of the tumor suppressor protein phosphatase and tensin homolog (PTEN). PTEN is a gatekeeper protein that negatively regulates intracellular levels of PI3K and consequently suppresses the PI3K-Akt pathway, which normally promotes cell survival and growth [70]. Reinstating PTEN activity, by suppression of the PI3K-Akt pathway in in vitro studies, has been shown to restore sensitivity to sunitinib in cancer cells [70]. Loss of PTEN activity is considered a key event in prostate carcinogenesis, and reinstating PTEN activity in prostate cancer seems to be a promising tool in overcoming sunitinib resistance. 3.2. Anti-Angiogenesis Clinical Studies in Prostate Cancer Unfortunately, similar to bevacizumab, in a phase III multicentre, randomizeddouble-blind placebo-controlled parallel group study in 1224 men with castration-resistant refractory tumors, aflibercept therapy combined with docetaxel chemotherapy and hormonal therapy did not show any improvement in overall survival [56]. Sunitinib and cediranib are small multireceptor molecule tyrosine kinase inhibitors, with a demonstrated activity against VEGF-receptors 1 and 2. Sunitininb is approved for the treatment of gastrointestinal stromal tumor, renal cell carcinoma and pancreatic neuroendocrine tumors. However, in a randomized, placebo-controlled, phase III trial of sunitinib therapy combined with hormonal therapy in 873 patients with refractory castration-resistant prostate cancer, there was no improvement in overall survival compared to placebo [57]. Furthermore, these anti-VEGF-A therapies have been associated with an increased rate of toxicity and adverse effects, resulting in the discontinuation of treatment (27% vs. 7%) [57]. These toxic and adverse effects included fatigue, asthenia, hand-foot syndrome, hypertension, bowel perforation, pulmonary thromboembolism, and gastrointestinal bleeding, seen in both pre-clinical and clinical studies [60,61]. In addition, treatment-related haematological problems also emerged in up to 20% of the patients, including lymphopenia, neutropenia, and anaemia [57]. Thalidomide is an immune-modulatory drug, which also has anti-angiogenic effects. Lenalidomide is a more potent analogue of thalidomide, with less prominent side effects. The mechanism of the anti-angiogenic effect of lenalidomide is not entirely elucidated, but appears to be through multiple mechanisms, including inhibition of VEGF-induced phosphatidylinositol-3,4,5-trisphosphate (PI3K)-Akt Int. J. Mol. Sci. 2019, 20, 2676 7 of 16 pathway signalling [62]. Lenalidomide therapy in non-metastatic prostate cancer in a phase I/II double-blinded, randomized study of 60 patients resulted in stabilization of the disease and a decline in PSA, with minimal toxicity [58]. A randomized, double-blind, placebo-controlled phase III trial in 1059 patients with castration-resistant refractory prostate cancer, however showed worse overall survival when lenalidomide was added to prednisone, hormonal, and docetaxel chemotherapy, compared to the placebo group [59]. There was also a 25% increase in adverse events, which included haematological side effects (34% vs. 20%), diarrhoea (7% vs. 2%), pulmonary embolism (6% vs. 1%), and asthenia (5% vs. 3%) [59]. To summarize, these findings suggest that anti-angiogenic therapy has no clinical benefit when added to chemotherapy or hormonal therapy in refractory, castration-resistant prostate cancer. 4. Discussion In addition, activation of the PI3K-Akt pathway in tumors with PTEN deletion has been shown to be associated with repressed androgen signalling in prostate cancer, while suppression of the PI3K-Akt pathway was demonstrated to activate androgen receptor signalling [71,72]. In a similar way, suppression of the androgen signaling pathway resulted in activation of the PI3K-Akt pathway [71]. This suggests that there is a cross-talk between the androgen receptor and PI3K-Akt pathways, which would at least in part explain the castration-resistant phenotype observed in tumors with PTEN deletion. Since activation of the PI3-Akt pathway appears to play an important role in resistance to both sunatininb and anti-androgenic therapy, suppression of the PI3K-Akt pathway could help overcome difficulties in anti-angiogenic and anti-androgenic therapy. Recent preclinical studies Int. J. Mol. Sci. 2019, 20, 2676 Int. J. Mol. Sci. 2019, 20, x FOR 8 of 16 8 of 16 on mouse models have shown that targeted inhibition of the PI3K-Akt pathway in castration-resistant prostate cancer resulted in both inhibited cancer cell proliferation and MVD [73,74]. Suboptimal results with bevacizumab treatment may also relate to the interaction between the androgen receptor (AR) signalling and angiogenic pathways. It has been long established that androgens upregulate VEGF-A expression [75], although the mechanism of this is not entirely understood [76]. Most recently, an interaction between epigenetic factors (Lysine specific demethylase 1 (LSD1), protein arginine methyltransferase 5 (PRMT5)) [77,78], zinc-finger transcription factors (specificity protein 1 (Sp1), Wilms tumor gene 1 (WT1), and early growth factor 1 (EGR1)) [76,79], different AR splice variants [80] and hypoxia mediated by the hypoxia-inducable factor 1 α (HIF-1α) [81] have emerged as potential mechanisms for androgen-dependent VEGF-A regulation. Furthermore, AR has been shown to regulate EGFR expression in prostate cancer cells. [82,83] In addition to the role of EGFR in indirect angiogenesis promotion through interleukin production, [39] it has also been demonstrated to upregulate VEGF-A directly and through induction of HIF-1α [84,85] (Figure 2). py p g Akt pathway in castration-resistant prostate cancer resulted in both inhibited cancer cell proliferation and MVD [73,74]. Suboptimal results with bevacizumab treatment may also relate to the interaction between the androgen receptor (AR) signalling and angiogenic pathways. It has been long established that androgens upregulate VEGF-A expression [75], although the mechanism of this is not entirely understood [76]. 4. Discussion Most recently, an interaction between epigenetic factors (Lysine specific demethylase 1 (LSD1), protein arginine methyltransferase 5 (PRMT5)) [77,78], zinc-finger transcription factors (specificity protein 1 (Sp1), Wilms tumor gene 1 (WT1), and early growth factor 1 (EGR1)) [76,79], different AR splice variants [80] and hypoxia mediated by the hypoxia-inducable factor 1 α (HIF-1α) [81] have emerged as potential mechanisms for androgen-dependent VEGF-A regulation. Furthermore, AR has been shown to regulate EGFR expression in prostate cancer cells. [82,83] In addition to the role of EGFR in indirect angiogenesis promotion through interleukin production, [39] it has also been demonstrated to upregulate VEGF-A directly and through induction of HIF-1α [84,85] (Figure 2). Figure 2. Interaction between angiogenic and androgen receptor pathways in prostate cancer cells. Castration results in androgen depletion which causes hypoxia Hypoxia enhances the transcriptional activity of androgen receptor (AR) at low androgen levels, as seen in castration-resistant prostate cancer. The activated androgen receptor promotes the overexpression of vascular endothelial growth factor A (VEGF-A) through hypoxia-inducable factor 1 α (HIF-1α) and (specificity protein 1 (Sp1) related mechanisms and also via regulation of epidermal growth factor receptor (EGFR) expression Figure 2. Interaction between angiogenic and androgen receptor pathways in prostate cancer cells. Castration results in androgen depletion which causes hypoxia Hypoxia enhances the transcriptional activity of androgen receptor (AR) at low androgen levels, as seen in castration-resistant prostate cancer. The activated androgen receptor promotes the overexpression of vascular endothelial growth factor A (VEGF-A) through hypoxia-inducable factor 1 α (HIF-1α) and (specificity protein 1 (Sp1) related mechanisms and also via regulation of epidermal growth factor receptor (EGFR) expression and upregulation of cytokins, mainly interleukin (IL)-6 [86]. Figure 2. Interaction between angiogenic and androgen receptor pathways in prostate cancer cells. Castration results in androgen depletion which causes hypoxia Hypoxia enhances the transcriptional activity of androgen receptor (AR) at low androgen levels, as seen in castration-resistant prostate cancer. The activated androgen receptor promotes the overexpression of vascular endothelial growth factor A (VEGF-A) through hypoxia-inducable factor 1 α (HIF-1α) and (specificity protein 1 (Sp1) related mechanisms and also via regulation of epidermal growth factor receptor (EGFR) expression Figure 2. Interaction between angiogenic and androgen receptor pathways in prostate cancer cells. Castration results in androgen depletion which causes hypoxia Hypoxia enhances the transcriptional activity of androgen receptor (AR) at low androgen levels, as seen in castration-resistant prostate cancer. 4. Discussion The activated androgen receptor promotes the overexpression of vascular endothelial growth factor A (VEGF-A) through hypoxia-inducable factor 1 α (HIF-1α) and (specificity protein 1 (Sp1) related mechanisms and also via regulation of epidermal growth factor receptor (EGFR) expression and upregulation of cytokins, mainly interleukin (IL)-6 [86]. and upregulation of cytokins, mainly interleukin (IL)-6. [86]. The interaction and the importance of angiogenesis and hormonal therapy in tumor progression have initiated a clinical trial implementing dual targeting of angiogenesis and androgen signalling in hormone-sensitive tumors [54]. As discussed above, this phase II clinical trial, which combined short- course androgen deprivation therapy with bevacizumab, improved relapse free survival in recurrent, hormone-sensitive tumors. In addition, it has been demonstrated that androgen deprivation by castration, causes hypoxia in prostatic tumor cells [87,88]. Hypoxia consequently enhances the The interaction and the importance of angiogenesis and hormonal therapy in tumor progression have initiated a clinical trial implementing dual targeting of angiogenesis and androgen signalling in hormone-sensitive tumors [54]. As discussed above, this phase II clinical trial, which combined short-course androgen deprivation therapy with bevacizumab, improved relapse free survival in recurrent, hormone-sensitive tumors. In addition, it has been demonstrated that androgen deprivation by castration, causes hypoxia in prostatic tumor cells [87,88]. Hypoxia consequently enhances the transcriptional activity of AR in prostatic tumor cells at low androgen levels, such as seen Int. J. Mol. Sci. 2019, 20, 2676 9 of 16 in castration-resistant prostate cancer [89]. It has been suggested that the activation of AR in hypoxic conditions is HIF-1α mediated [90], hence targeting HIF-1α could influence the AR stimulatory effect of hypoxia in castration-resistant prostate cancer. Recently, dual targeting of HIF-1α and AR pathways by HIF-1α inhibitors and enzalutamide, a second generation AR inhibitor, showed synergistic effect in castration-resistant prostate cancer cell lines, also resulting in decreased VEGF-A levels [81]. In addition, suppression of Sp1 binding to VEGF-A promoter resulted in significant reduction of VEGF-A level in castration-resistant prostate cancer cells [79]. However, a better understanding of the mechanism of the interaction between VEGF-A and AR is still needed to identify those patients who may benefit from dual targeting therapy [79,86]. g g py [ , ] Targeting VEGF-A also raises a further question: does inhibition of VEGF-A result in a pure anti-angiogenetic effect? Interestingly, it has been shown that VEGF-A has different splice isoforms and these different isoforms can show pro- or anti-angiogenic functions [91]. 4. Discussion In the terminal exon of the VEGF-A gene, there are two alternative splice sites. Splicing at the proximal splice site results in the canonical angiogenic VEGF165a isoform. Splicing at the distal splice site results in an alternative splicing isoform VEGF165b, which has been found to have anti-angiogenic effect by inhibiting vasodilation and reducing permeability [92,93]. The level of the anti-angiogenic VEGF165b splice variant has also been found to be decreased in cancer cells, compared to normal tissue cells [93]. This means that, in cancer cells, there appears to be a shift towards the pro-angiogenic VEGF165a splice variant at the expense of the anti-angiogenic VEGF165b splice variant. The cause of this shift has not been entirely elucidated, but nuclear receptor-coregulator complexes have been shown to regulate splicing events, therefore aberrant recruitment of nuclear receptor-coregulator complexes to the VEGF promoter to promote VEGF165a splicing has been suggested as a possible explanation [48,94]. Current anti-VEGF-A therapies lack isoform specificity, as the epitope of bevacizumab binds the N-terminal region of VEGF-A, which is present in all splice isoforms [95]. Thus, current anti-angiogenic therapies targeting VEGF-A function may result in both inhibition and promotion of tumor angiogenesis. However, the fact that the two isoforms appear to have different splice sites and post-translational regulation offers the possibility of selectively targeting specific isoforms. Serine-arginine protein kinase 1 (SRPK1), a kinase that phosphorylates SR-protein, appears to stimulate VEGF165a splicing, whilst VEGF165b splicing has been shown to be stimulated by Clk1/4, a dual specific protein kinase [96–98]. Investigation with SRPK1 knocked-down cell lines showed a shift towards the anti-angiogenic VEGF165b isoform, while xenografts showed decreased tumor growth and decreased MVD in tumors [99]. In addition, specific inhibition of SRPK1 in a mouse tumor model has been shown to be associated with reduced tumor growth [100] (Figure 3). Most current mainstream anti-angiogenic treatment therapies focus on direct angiogenesis inhibition. A further possible treatment option is indirect inhibition of angiogenesis, targeting an interplay between tumor or stromal cells and angiogenesis. The galectin family of proteins have emerged as playing an important role in this interplay, facilitating tumor progression. Galectins are β-galactoside-binding lectin proteins, which are overexpressed in various cancers and have been associated with poor prognosis and tumor progression in prostate cancer [101]. In addition to their intracellular function of promoting cell transformation and survival, galectins are also secreted into the extracellular space. 5. Materials and Methods The literature review was conducted by a Pubmed literature search engine using a collection of keywords with no restriction on publication date. The following word strings were used as keywords: “angiogenesis”[All Fields]] AND [“prostatic neoplasms”[MeSH Terms] OR [“prostatic”[All Fields] AND “neoplasms”[All Fields]] OR “prostatic neoplasms”[All Fields] OR [“prostate”[All Fields] AND “cancer”[All Fields]] OR “prostate cancer”[All Fields]. The search results were subsequently filtered by article type, specifically clinical trials and review articles. Abstracts were assessed for relevance with subsequent review of full text versions. Only phase II or III studies were included. Studies cited by these articles, but not included in the algorithm, were also manually scoped and were also subject of the review. 6. Conclusions The association of MVD and overexpression of VEGF-A with tumor prognosis in prostate cancer suggested that angiogenesis has an important role in prostate cancer progression. Supplementation of hormonal manipulation and chemotherapy with anti-angiogenesis therapy in hormone-sensitive prostate cancer showed some positive effect, further supporting the hypothesis that angiogenesis is an important factor in prostate cancer. Despite this, clinical trials in refractory castration-resistant prostate cancer hitherto have shown increased toxicity with no clinical benefit. A better understanding of the mechanism of angiogenesis may help to understand the failure of trials, possibly leading to targeted anti-angiogenic therapies in prostate cancer. These could include identification of specific subgroups of patients who might benefit from therapies, targeting tumor-suppressor genes that play a role in treatment resistance, or by identifying and selectively targeting splice variants of VEGF-A. Funding: Funding for this study was supported by grants from British Heart Foundation to SO (PG/15/53/31371), Diabetes UK to SO (17/0005668). Acknowledgments: We wish to acknowledge Cornelia Szecsei for her critical reading of the manuscript. Acknowledgments: We wish to acknowledge Cornelia Szecsei for her critical reading of the manuscript. Conflicts of Interest: The authors declare no conflict of interest Conflicts of Interest: The authors declare no conflict of interest 4. Discussion Here they interact with cell surface receptors, resulting in suppression of the immune response and promotion of angiogenesis, likely by means of interaction with VEGF-receptor2 [102,103]. Rabinovich and colleagues identified that prostate cancer shows a unique galectin expression profile during cancer progression, and showed that galectin-1 is uniquely expressed at high levels in advanced prostate cancer [104]. This makes galectin-1 a potential target of angiogenesis therapy in advanced prostate cancer [105]. Int. J. Mol. Sci. 2019, 20, 2676 10 of 16 [ ] g angiogenic VEGF165b isoform, while xenografts showed decreased tumor growth and decreased MVD in tumors [99]. In addition, specific inhibition of SRPK1 in a mouse tumor model has been shown to be associated with reduced tumor growth [100] (Figure 3). Figure 3. Alternative splicing of VEGF-A. Splicing at the proximal splicing site (PSS) is stimulated by serine-arginine protein kinase 1 (SRPK1), and results in the pro-angiogenic VEGF165a splice variant. Clk1/4 stimulates splicing at the distal splicing site (DSS), which results in the anti-angiogenic VEGF165b isoform. Figure 3. Alternative splicing of VEGF-A. Splicing at the proximal splicing site (PSS) is stimulated by serine-arginine protein kinase 1 (SRPK1), and results in the pro-angiogenic VEGF165a splice variant. Clk1/4 stimulates splicing at the distal splicing site (DSS), which results in the anti-angiogenic VEGF165b isoform. Int. J. Mol. Sci. 2019, 20, 2676 angiogenic VEGF165b isof in tumors [99]. In additio 10 of 16 d MVD hown to Figure 3. Alternative splicing of VEGF-A. Splicing at the proximal splicing site (PSS) is stimulated by serine-arginine protein kinase 1 (SRPK1), and results in the pro-angiogenic VEGF165a splice variant. Clk1/4 stimulates splicing at the distal splicing site (DSS), which results in the anti-angiogenic VEGF165b isoform Figure 3. Alternative splicing of VEGF-A. Splicing at the proximal splicing site (PSS) is stimulated by serine-arginine protein kinase 1 (SRPK1), and results in the pro-angiogenic VEGF165a splice variant. Clk1/4 stimulates splicing at the distal splicing site (DSS), which results in the anti-angiogenic VEGF165b isoform. 1. National Cancer Institute. SEER Stat Fact Sheets: Prostate; National Cancer Institute: Bethesda, MD, USA. Available online: https://seer.cancer.gov/statfacts/html/prost.html#prevalence (accessed on 10 March 2018). References 1. National Cancer Institute. SEER Stat Fact Sheets: Prostate; National Cancer Institute: Bethesda, MD, USA. Available online: https://seer.cancer.gov/statfacts/html/prost.html#prevalence (accessed on 10 March 2018). Int. J. Mol. Sci. 2019, 20, 2676 11 of 16 11 of 16 2. American Cancer Society. Cancer Facts and Figures; American Cancer Society: Atlanta, GA, USA, 2018; Available online: https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer- facts-and-figures/2018/cancer-facts-and-figures-2018.pdf (accessed on 10 March 2018). Cancer Research UK. Prostate Cancer Incidence Statistics [Internet]. 2014. Available online: http://www cancerresearchuk.org/cancer-info/cancerstats/types/prostate/incidence/#age (accessed on 14 August 2018). 4. Zlotta, A.R.; Egawa, S.; Pushkar, D.; Govorov, A.; Kimura, T.; Kido, M.; Takahashi, H.; Kuk, C.; Kovylina, M.; Aldaoud, N.; et al. Prevalence of prostate cancer on autopsy: Cross-sectional study on unscreened Caucasian and Asian men. J. Natl. Cancer Inst. 2013, 105, 1050–1058. [CrossRef] [PubMed] 5. American Cancer Society. Cancer Facts and Figures; American Cancer Society: Atlanta, GA, USA, 2012; Available online: https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/ annual-cancer-facts-and-figures/2012/estimated-number-of-new-cancer-cases-and-deaths-by-sex-2012. pdf (accessed on 19 August 2018). 6. The National Cancer Registration Service, Eastern Office [Internet]. Available online: http://www.ncras.nhs. uk/ncrs-east/ (accessed on 14 August 2018). 7. Zelefsky, M.J.; Eastham, J.A.; Sartor, A.O. Cancer of the prostate. In Cancer: Principles and Practice of Oncology, 9th ed.; De Vita, V.T., Jr., Lawrence, T.S., Rosenberg, S.A., Eds.; Lippincott Williams & Wilkins: Philadelphia, PA, USA, 2011; pp. 1220–7121. 8. PDQ Adult Treatment Editorial Board. Prostate Cancer Treatment (PDQ®): Patient Version. 30 April 2018. In PDQ Cancer Information Summaries [Internet]; National Cancer Institute (US): Bethesda, MD, USA, 2002. Available online: https://www.ncbi.nlm.nih.gov/books/NBK65915/ (accessed on 19 August 2018). Q ( Q ) p In PDQ Cancer Information Summaries [Internet]; National Cancer Institute (US): Bethesda, MD, USA, 2002. Available online: https://www ncbi nlm nih gov/books/NBK65915/ (accessed on 19 August 2018) 9. Hamdy, F.C.; Donovan, J.L.; Lane, J.A.; Mason, M.; Metcalfe, C.; Holding, P.; Davis, M.; Peters, T.J.; Turner, E.L.; Martin, R.M.; et al. 10-Year Outcomes after Monitoring, Surgery, or Radiotherapy for Localized Prostate Cancer. N. Engl. J. Med. 2016, 375, 1415–1424. [CrossRef] [PubMed] 10. Graham, J.; Kirkbride, P.; Cann, K.; Hasler, E.; Prettyjohns, M. Prostate cancer:summary of updated NICE guidance. BMJ 2014, 8, 348. [CrossRef] 11. Ragde, H.; Blasko, J.C.; Grimm, P.D.; Kenny, G.M.; Sylvester, J.E.; Hoak, D.C.; Landin, K.; Cavanagh, W. Interstitial iodine-125 radiation without adjuvant therapy in the treatment of clinically localized prostate carcinoma. Cancer 1997, 80, 442–453. [CrossRef] 12. The Medical Research Council Prostate Cancer Working Party Investigators Group. References Immediate versus deferred treatment for advanced prostatic cancer: Initial results of the Medical Research Council Trial. Br. J. Urol. 1997, 79, 235–426. 13. Dearnaley, D.P.; Mason, M.D.; Parmar, M.K.; Sanders, K.; Sydes, M.R. Adjuvant therapy with oral sodium clodronate in locally advanced and metastatic prostate cancer: Long-term overall survival results from the MRC PR04 and PR05 randomizedcontrolled trials. Lancet Oncol. 2009, 10, 872–876. [CrossRef] 14. James, N.D.; de Bono, J.S.; Spears, M.R.; Clarke, N.W.; Mason, M.D.; Dearnaley, D.P.; Ritchie, A.W.; Amos, C.L.; Gilson, C.; Jones, R.J. Abiraterone for Prostate Cancer Not Previously Treated with Hormone Therapy. N. Engl. J. Med. 2017, 377, 338–351. [CrossRef] 15. Scher, H.I.; Fizazi, K.; Saad, F.; Taplin, M.E.; Sternberg, C.N.; Miller, K.; de Wit, R.; Mulders, P.; Chi, K.N.; Shore, N.D.; et al. Increased survival with enzalutamide in prostate cancer after chemotherapy. N. Engl. J. Med. 2012, 367, 1187–1197. [CrossRef] 16. Kantoff, P.W.; Higano, C.S.; Shore, N.D.; Berger, E.R.; Small, E.J.; Penson, D.F.; Redfern, C.H.; Ferrari, A.C.; Dreicer, R.; Sims, R.B.; et al. Sipuleucel-T immunotherapy for castration-resistant prostate cancer. N. Engl. J. Med. 2010, 363, 411–422. [CrossRef] 17. Parker, C.; Nilsson, S.; Heinrich, D.; Helle, S.I.; O’sullivan, J.M.; Fosså, S.D.; Chodacki, A.; Wiechno, P.; Logue, J.; Seke, M.; et al. Alpha emitter radium-223 and survival in metastatic prostate cancer. N. Engl. J. Med. 2013, 369, 213–223. [CrossRef] 18. De Bono, J.S.; Oudard, S.; Ozguroglu, M.; Hansen, S.; Machiels, J.P.; Kocak, I.; Gravis, G.; Bodrogi, I.; Mackenzie, M.J.; Shen, L.; et al. Prednisone plus cabazitaxel or mitoxantrone for metastatic castration-resistant prostate cancer progressing after docetaxel treatment: A randomizedopen-label trial. Lancet 2010, 376, 1147–1154. [CrossRef] 19. Fizazi, K.; Carducci, M.; Smith, M.; Damião, R.; Brown, J.; Karsh, L.; Milecki, P.; Shore, N.; Rader, M.; Wang, H.; et al. Denosumab versus zoledronic acid for treatment of bone metastases in men with castration-resistant prostate cancer: A randomized, double-blind study. Lancet 2011, 377, 813–822. [CrossRef] Int. J. Mol. Sci. 2019, 20, 2676 12 of 16 20. Oosterhof, G.O.N.; Roberts, J.T.; de Reijke, T.M.; Engelholm, S.A.; Horenblas, S.; von der Maase, H.; Neymark, N.; Debois, M. ColletteL. Strontium (89) chloride versus palliative local field radiotherapy in patients with hormonal escaped prostate cancer: A phase III study of the European Organisation for Research and Treatment of Cancer, Genitourinary Group. Eur. Urol. 2003, 44, 519–526. [CrossRef] 21. References Kurozumi, K.; Ichikawa, T.; Onishi, M.; Fujii, K.; Date, I. Cilengitide treatment for malignant glioma: Current status and future direction. Neurol. Med. Chir. 2012, 52, 539–547. [CrossRef] 34. Su, J.; Cai, M.; Li, W.; Hou, B.; He, H.; Ling, C.; Huang, T.; Liu, H.; Guo, Y. Molecularly Targeted Drugs Plus Radiotherapy and Temozolomide Treatment for Newly Diagnosed Glioblastoma: A Meta-Analysis and Systematic Review. Oncol. Res. 2016, 24, 117–128. [CrossRef] [PubMed] 35. Herbert, S.P.; Stainier, D.Y. Molecular control of endothelial cell behaviour during blood vessel morphogenesis. Nat. Rev. Mol. Cell. Biol. 2011, 12, 551–564. [CrossRef] [PubMed] 36. Margolin, K.; Gordon, M.S.; Holmgren, E.; Gaudreault, J.; Novotny, W.; Fyfe, G.; Adelman, D.; Stalter, S.; Breed, J. Phase Ib trial of intravenous recombinant humanized monoclonal antibody to vascular endothelial growth factor in combination with chemotherapy in patients with advanced cancer: Pharmacologic and long-term safety data. J. Clin. Oncol. 2011, 19, 851–856. [CrossRef] 37. Ferrara, N.; Adamis, A.P. Ten years of anti-vascular endothelial growth factor therapy. Nat. Rev. Drug Discov. 2016, 15, 385–403. [CrossRef] 38. Li, M.; Kroetz, D.L. Bevacizumab-induced hypertension: Clinical presentation and molecular understanding. Pharmacol. Ther. 2018, 182, 152–160. [CrossRef] 39. Minder, P.; Zajac, E.; Quigley, J.P.; Deryugina, E.I. EGFR Regulates the Development and Microarchitecture of Intratumoral Angiogenic Vasculature Capable of Sustaining Cancer Cell Intravasation. Neoplasia 2015, 17, 634–649. [CrossRef] 40. Sharma, S.; Sharma, M.C.; Sarkar, C. Morphology of angiogenesis in human cancer: A conceptual overview, histoprognostic perspective and significance of neoangiogenesis. Histopathology 2005, 46, 481–489. [CrossRef] 40. Sharma, S.; Sharma, M.C.; Sarkar, C. Morphology of angiogenesis in human cancer: A conceptual overview, histoprognostic perspective and significance of neoangiogenesis. Histopathology 2005, 46, 481–489. [CrossRef] 41. Bono, A.V.; Celato, N.; Cova, V.; Salvadore, M.; Chinetti, S.; Novario, R. Microvessel density in prostate histoprognostic perspective and significance of neoangiogenesis. Histopathology 2005, 46, 481–489. [CrossRef] 41. Bono, A.V.; Celato, N.; Cova, V.; Salvadore, M.; Chinetti, S.; Novario, R. Microvessel density in prostate carcinoma. Prostate Cancer Prostatic Dis. 2002, 5, 123–127. [CrossRef] 41. Bono, A.V.; Celato, N.; Cova, V.; Salvadore, M.; Chinetti, S.; Novario, R. Microvessel density in prostate carcinoma. Prostate Cancer Prostatic Dis. 2002, 5, 123–127. [CrossRef] 42. Borre, M.; Offersen, B.V.; Nerstrom, B.; Overgaard, J. Microvessel density predicts survival in prostate cancer patients subjected to watchful waiting. Br. J. Cancer 1998, 78, 940–944. [CrossRef] 43. Jiang, J.; Chen, Y.; Zhu, Y.; Yao, X.; Qi, J. References Fizazi, K.; Tran, N.; Fein, L.; Matsubara, N.; Rodriguez-Antolin, A.; Alekseev, B.Y.; Özgüro˘glu, M.; Ye, D.; Feyerabend, S.; Protheroe, A.; et al. Abiraterone plus Prednisone in Metastatic, Castration-Sensitive Prostate Cancer. N. Engl. J. Med. 2017, 377, 352–360. [CrossRef] 22. Rajabi, M.; Mousa, S.A. The Role of Angiogenesis in Cancer Treatment. Biomedicines 2017, 21, 34. [Cr 22. Rajabi, M.; Mousa, S.A. The Role of Angiogenesis in Cancer Treatment. Biomedicines 2017, 21, 34. [CrossRef] 23. Winkler, F. Hostile takeover: How tumors hijack pre-existing vascular environments to thrive. J. Pathol. 2017, 22. Rajabi, M.; Mousa, S.A. The Role of Angiogenesis in Cancer Treatment. Biomedicines 2017, 21, 34. [CrossRef] 23. Winkler, F. Hostile takeover: How tumors hijack pre-existing vascular environments to thrive. J. Pathol. 2017, 242, 267–272. [CrossRef] Hanahan, D.; Weinberg, R.A. Hallmarks of Cancer: The Next Generation. Cell 2011, 144, 646–674. [CrossRef 4. Hanahan, D.; Weinberg, R.A. Hallmarks of Cancer: 25. Pavlakovic, H.; Havers, W.; Schweigerer, L. Multiple angiogenesis stimulators in a single malignancy: Implications for anti-angiogenic tumor therapy. Angiogenesis 2001, 4, 259–262. [CrossRef] 26. Kerbel, R.S. Tumor angiogenesis. N. Engl. J. Med. 2008, 358, 2039–2049. [CrossRef] 27. Gressett, M.; Shah, S.R. Intricacies of bevacizumab-induced toxicities and their management. Ann. Pharmacother. 2009, 43, 490–501. [CrossRef] 27. Gressett, M.; Shah, S.R. Intricacies of bevacizumab-induced toxicities and their management. Ann. Pharmacother. 2009, 43, 490–501. [CrossRef] 28. Kamba, T.; McDonald, D.M. Mechanisms of adverse effects of anti-VEGF therapy for cancer. Br. J. Cancer 2009, 43, 490–501. [CrossRef] 28. Kamba, T.; McDonald, D.M. Mechanisms of adverse effects of anti-VEGF therapy for cancer. Br. J. Cancer 2007 96 1788–1795 [CrossRef] Kamba, T.; McDonald, D.M. Mechanisms of adverse effects of anti-VEGF therapy for cancer. Br. J. Cancer 2007, 96, 1788–1795. [CrossRef] 29. Ferrara, N. VEGF as a therapeutic target in cancer. Oncology 2005, 69 (Suppl. 3), 11–16. [CrossRef] [PubMed] 29. Ferrara, N. VEGF as a therapeutic target in cancer. Oncology 2005, 69 (Suppl. 3), 11–16. [CrossRef] [PubMed] 30. Carmeliet, P.; Jain, R.K. Molecular mechanisms and clinical applications of angiogenesis. Nature 2011, 473, 298–307. [CrossRef] 30. Carmeliet, P.; Jain, R.K. Molecular mechanisms and clinical applications of angiogenesis. Nature 2011, 473, 298–307. [CrossRef] 31. El-Kenawi, A.E.; El-Remessy, A.B. Angiogenesis inhibitors in cancer therapy: Mechanistic perspective on classification and treatment rationales. Br. J. Pharmacol. 2013, 170, 712–729. [CrossRef] 32. Mundel, T.M.; Kalluri, R. Type IV collagen-derived angiogenesis inhibitors. Microvasc. Res. 2007, 74, 85–89. [CrossRef] 33. References Contrast-enhanced ultrasonography for the detection and characterization of prostate cancer: Correlation with microvessel density and Gleason score. Clin. Radiol. 2011, 66, 732–737. [CrossRef] Int. J. Mol. Sci. 2019, 20, 2676 13 of 16 13 of 16 44. Tretiakova, M.; Antic, T.; Binder, D.; Kocherginsky, M.; Liao, C.; Taxy, J.B.; Oto, A. Microvessel density is not increased in prostate cancer: Digital imaging of routine sections and tissue microarrays. Hum. Pathol. 2013, 44, 495–502. [CrossRef] [PubMed] 45. Miyata, Y.; Saka, H. Reconsideration of the clinical and histopathological significance of angiogenesis in prostate cancer: Usefulness and limitations of microvessel density measurement. Int. J. Urol. 2015, 22, 806–815. [CrossRef] [PubMed] 46. Taverna, G.; Grizzi, F.; Colombo, P.; Seveso, M.; Giusti, G.; Proietti, S.; Fiorini, G.; Lughezzani, G.; Casale, P.; Buffi, N.; et al. Two-dimensional neovascular complexity is significantly higher in nontumor prostate tissue than in low-risk prostate cancer. Korean J. Urol. 2015, 56, 435–442. [CrossRef] [PubMed] 47. Taverna, G.; Grizzi, F.; Colombo, P.; Graziotti, P. Is angiogenesis a hallmark of prostate cancer? Front. Oncol. 2013, 3, 15. [CrossRef] [PubMed] 48. De Brot, S.; Ntekim, A.; Cardenas, R.; James, V.; Allegrucci, C.; Heery, D.M.; Bates, D.O.; Ødum, N.; Persson, J.L.; Mongan, N.P. Regulation of vascular endothelial growth factor in prostate cancer. Endocr. Relat. Cancer 2015, 22, 107–123. [CrossRef] 49. Wong, S.Y.; Haack, H.; Crowley, D.; Barry, M.; Bronson, R.T.; Hynes, R.O. Tumor-secreted vascular endothelial growth factor-C is necessary for prostate cancer lymphangiogenesis, but lymphangiogenesis is unnecessary for lymph node metastasis. Cancer Res. 2005, 65, 9789–9798. [CrossRef] 50. Wegiel, B.; Bjartell, A.; Ekberg, J.; Gadaleanu, V.; Brunhoff, C.; Persson, J.L. A role for cyclin A1 in mediating the autocrine expression of vascular endothelial growth factor in prostate cancer. Oncogene 2005, 24, 6385–6393. [CrossRef] 51. Green, M.M.; Hiley, C.T.; Shanks, J.H.; Bottomley, I.C.; West, C.M.; Cowan, R.A.; Stratford, I.J. Expression of vascular endothelial growth factor (VEGF) in locally invasive prostate cancer is prognostic for radiotherapy outcome. Int. J. Radiat. Oncol. Biol. Phys. 2007, 67, 84–90. [CrossRef] 52. Duque, J.L.; Loughlin, K.R.; Adam, R.M.; Kantoff, P.W.; Zurakowski, D.; Freeman, M.R. Plasma levels of vascular endothelial growth factor are increased in patients with metastatic prostate cancer. Urology 1999, 54, 523–527. [CrossRef] 53. Hrouda, D.; Nicol, D.L.; Gardiner, R.A. The role of angiogenesis in prostate development and the pathogenesis of prostate cancer. Urol. Res. 2003, 30, 347–355. 54. References McKay, R.R.; Zurita, A.J.; Werner, L.; Bruce, J.Y.; Carducci, M.A.; Stein, M.N.; Heath, E.I.; Hussain, A.; Tran, H.T.; Sweeney, C.J.; et al. Randomized Phase II Trial of Short-Course Androgen Deprivation Therapy With or Without Bevacizumab for Patients With Recurrent Prostate Cancer After Definitive Local Therapy. J. Clin. Oncol. 2016, 34, 1913–1920. [CrossRef] 55. Kelly, W.K.; Halabi, S.; Carducci, M.; George, D.; Mahoney, J.F.; Stadler, W.M.; Morris, M.; Kantoff, P.; Monk, J.P.; Kaplan, E.; et al. Randomized, double-blind, placebo-controlled phase III trial comparing docetaxel and prednisone with or without bevacizumab in men with metastatic castration-resistant prostate cancer: CALGB 90401. J. Clin. Oncol. 2012, 30, 1534–1540. [CrossRef] 56. Tannock, I.F.; Fizazi, K.; Ivanov, S.; Karlsson, C.T.; Fléchon, A.; Skoneczna, I.; Orlandi, F.; Gravis, G.; Matveev, V.; Bavbek, S.; et al. Aflibercept versus placebo in combination with docetaxel and prednisone for treatment of men with metastatic castration-resistant prostate cancer (VENICE): A phase 3, double-blind randomizedtrial. Lancet Oncol. 2013, 14, 760–768. [CrossRef] 57. Michaelson, M.D.; Oudard, S.; Ou, Y.C.; Sengeløv, L.; Saad, F.; Houede, N.; Ostler, P.; Stenzl, A.; Daugaard, G.; Jones, R.; et al. Randomized, placebo-controlled, phase III trial of sunitinib plus prednisone versus prednisone alone in progressive, metastatic, castration-resistant prostate cancer. J. Clin. Oncol. 2014, 32, 76–82. [CrossRef] 58. Keizman, D.; Zahurak, M.; Sinibaldi, V.; Carducci, M.; Denmeade, S.; Drake, C.; Pili, R.; Antonarakis, E.S.; Hudock, S.; Eisenberger, M. Lenalidomide in nonmetastatic biochemically relapsed prostate cancer: Results of a phase I/II double-blinded, randomized study. Clin. Cancer Res. 2010, 16, 5269–5276. [CrossRef] 59. Petrylak, D.P.; Vogelzang, N.J.; Budnik, N.; Wiechno, P.J.; Sternberg, C.N.; Doner, K.; Bellmunt, J.; Burke, J.M.; de Olza, M.O.; Choudhury, A.; et al. Docetaxel and prednisone with or without lenalidomide in chemotherapy-naivepatients with metastatic castration-resistant prostate cancer (MAINSAIL): Arandomized, double-blind, placebo-controlled phase 3 trial. Lancet Oncol. 2015, 16, 417–425. [CrossRef] 60. Mangoni, M.; Vozenin, M.C.; Biti, G.; Deutsch, E. Normal tissues toxicities triggered by combined anti-angiogenic and radiation therapies: Hurdles might be ahead. Br. J. Cancer 2012, 107, 308–314. [CrossRef] [PubMed] Int. J. Mol. Sci. 2019, 20, 2676 14 of 16 61. Ogita, S.; Tejwani, S.; Heilbrun, L.; Fontana, J.; Heath, E.; Freeman, S.; Smith, D.; Baranowski, K.; Vaishampayan, U. Pilot Phase II Trial of Bevacizumab Monotherapy in Nonmetastatic Castrate-Resistant Prostate Cancer. ISRN Oncol. 2012, 2012, 242850. [CrossRef] [PubMed] 2. Ribatti, D.; Vacca, A. New Insights in Anti-Angiogenesis in Multiple Myeloma. Int. J. Mol. Sci. References 2018, 19, 2 [CrossRef] [PubMed] 63. Liu, Z.-Q.; Fang, J.-M.; Xiao, Y.-Y.; Zhao, Y.; Cui, R.; Hu, F.; Xu, Q. Prognostic role of vascular endothelial growth factor in prostate cancer: A systematic review and meta-analysis. Int. J. Clin. Exp. Med. 2015, 8, 2289–2298. [PubMed] 64. Wang, K.; Peng, H.L.; Li, L.K. Prognostic value of vascular endothelial growth factorexpression in patients with prostate cancer: A systematic review withmeta-analysis. Asian Pac. J. Cancer Prev. 2012, 13, 5665–5669. [CrossRef] [PubMed] 65. Scholz, A.; Harter, P.N.; Cremer, S.; Yalcin, B.H.; Gurnik, S.; Yamaji, M.; Di Tacchio, M.; Sommer, K.; Baumgarten, P.; Bähr, O.; et al. Endothelial cell-derived angiopoietin-2 is a therapeutic target in treatment-naive and bevacizumab-resistant glioblastoma. EMBO Mol. Med. 2016, 8, 39–57. [CrossRef] 66. Lindholm, E.M.; Krohn, M.; Iadevaia, S.; Kristian, A.; Mills, G.B.; Mælandsmo, G.M.; Engebraaten, O. Proteomic characterization of breast cancer xenografts identifies early and late bevacizumab-induced responses and predicts effective drug combinations. Clin. Cancer Res. 2014, 20, 404–412. [CrossRef] 67. Madan, R.A.; Karzai, F.H.; Ning, Y.-M.; Adesunloye, B.A.; Huang, X.; Harold, N.; Couvillon, A.; Chun, G.; Cordes, L.; Sissung, T.; et al. Phase II trial of docetaxel, bevacizumab, lenalidomide and prednisone in patients with metastatic castration-resistant prostate cancer. BJU Int. 2016, 118, 590–597. [CrossRef] 68. Brauer, M.J.; Zhuang, G.; Schmidt, M.; Yao, J.; Wu, X.; Kaminker, J.S.; Jurinka, S.S.; Kolumam, G.; Chung, A.S.; Jubb, A.; et al. Identification and analysis of in vivo VEGF downstream markers link VEGF pathway activity with efficacy of anti-VEGF therapies. Clin. Cancer Res. 2013, 19, 3681–3692. [CrossRef] 69. De Haas, S.; Delmar, P.; Bansal, A.T.; Moisse, M.; Miles, D.W.; Leighl, N.; Escudier, B.; Van Cutsem, E.; Carmeliet, P.; Scherer, S.J.; et al. Genetic variability of VEGF pathway genes in six randomized Phase III trials assessing the addition of bevacizumab to standard therapy. Angiogenesis 2014, 17, 909–920. [CrossRef] 70. Golovine, K.; Kutikov, A.; Teper, E.; Simhan, J.; Makhov, P.B.; Canter, D.J.; Uzzo, R.G.; Kolenko, V.M. Modulation of Akt/mTOR signalling overcomes sunitinib resistance in renal and prostate cancer cells. Mol. Cancer Ther. 2012, 11, 1510–1517. 71. Carver, B.S.; Chapinski, C.; Wongvipat, J.; Hieronymus, H.; Chen, Y.; Chandarlapaty, S.; Arora, V.K.; Le, C.; Koutcher, J.; Scher, H.; et al. Reciprocal feedback regulation of PI3K and androgen receptor signaling in PTEN-deficient prostate cancer. Cancer Cell 2011, 19, 575–586. [CrossRef] 72. Wang, Y.; Kreisberg, J.I.; Ghosh, P.M. Cross-talk between the androgen receptor and the phosphatidylinositol 3-kinase/Akt pathway in prostate cancer. References [CrossRef] 84. Tabernero, J. The role of VEGF and EGFR inhibition: Implications for combining anti-VEGF and anti-EGFR agents. Mol. Cancer Res. 2007, 5, 203–220. [CrossRef] 85. Mabjeesh, N.J.; Willard, M.T.; Frederickson, C.E.; Zhong, H.; Simons, J.W. Androgens stimulate hypoxia-inducible factor 1 activation via autocrine loop of tyrosine kinase receptor/phosphatidylinositol 3′-kinase/protein kinase B in prostate cancer cells. Clin. Cancer Res. 2003, 9, 2416–2425. 6. Cereda, V.; Formica, V.; Roselli, M. Issues and promises of bevacizumab in prostate cancer treatm Exp. Opin. Biol. Ther. 2018, 18, 707–717. [CrossRef] 87. Shabsigh, A.; Ghafar, M.A.; De La Taille, A.; Burchardt, M.; Kaplan, S.A.; Anastasiadis, A.G.; Buttyan, R. Biomarker analysis demonstrates a hypoxic environment in the castrated rat ventral prostate gland. J. Cell Biochem. 2001, 81, 437–444. [CrossRef] 88. Halin, S.; Hammarsten, P.; Wikström, P.; Bergh, A. Androgen-insensitive prostate cancer cells transiently respond to castration treatment when growing in an androgen-dependent prostate environment. Prostate 2007, 67, 370–377. [CrossRef] 89. Mitani, T.; Harada, N.; Nakano, Y.; Inui, H.; Yamaji, R. Coordinated action of hypoxia-inducible factor-1α and β-catenin in androgen receptor signaling. J. Biol. Chem. 2012, 287, 33594–33606. [CrossRef] 90. Horii, K.; Suzuki, Y.; Kondo, Y.; Akimoto, M.; Nishimura, T.; Yamabe, Y.; Sakaue, M.; Sano, T.; Kitagawa, T.; Himeno, S.; et al. Androgen-dependent gene expression of prostate-specific antigen is enhanced synergistically by hypoxia in human prostate cancer cells. Mol. Cancer Res. 2007, 5, 383–391. [CrossRef] 91. Bates, D.; Cui, T.-G.; Doughty, J.M.; Winkler, M.; Sugiono, M.; Shields, J.D.; Peat, D.; Gillatt, D.; Harper, S.J. VEGF165b, an inhibitory splice variant of vascular endothelial growth factor, is down-regulated in renal cell carcinoma. Cancer Res. 2002, 62, 4123–4131. g y g p VEGF165b, an inhibitory splice variant of vascular endothelial growth factor, is down-regulated in renal cell carcinoma. Cancer Res. 2002, 62, 4123–4131. 92. Woolard, J.; Wang, W.Y.; Bevan, H.S.; Qiu, Y.; Morbidelli, L.; Pritchard-Jones, R.O.; Cui, T.G.; Sugiono, M.; Waine, E.; Perrin, R.; et al. VEGF165b, an inhibitory vascular endothelial growth factor splice variant: Mechanism of action, in vivo effect on angiogenesis and endogenous protein expression. Cancer Res. 2004, 64, 7822–7835. [CrossRef] 93. Oltean, S.; Gammons, M.; Hulse, R.; Hamdollah-Zadeh, M.; Mavrou, A.; Donaldson, L.; Salmon, A.H.; Harper, S.J.; Ladomery, M.R.; Bates, D.O. SRPK1 inhibition in vivo: Modulation of VEGF splicing and potential treatment for multiple diseases. Biochem. Soc. Trans. 2012, 40, 831–835. [CrossRef] 94. Auboeuf, D.; Dowhan, D.H.; Kang, Y.K.; Larkin, K.; Lee, J.W.; Berget, S.M.; O’Malley, B.W. References Curr. Cancer Drug Targets 2007, 7, 591–604. [CrossRef] 73. Yamamoto, Y.; A De Velasco, M.; Kura, Y.; Nozawa, M.; Hatanaka, Y.; Oki, T.; Ozeki, T.; Shimizu, N.; Minami, T.; Yoshimura, K.; et al. Evaluation of in vivo responses of sorafenib therapy in a preclinical mouse model of PTEN-deficient of prostate cancer. J. Transl. Med. 2015, 13, 150. [CrossRef] 74. De Velasco, M.A.; Kura, Y.; Yoshikawa, K.; Nishio, K.; Davies, B.R.; Uemura, H. Efficacy of targeted AKT inhibition in genetically engineered mouse models of PTEN-deficient prostate cancer. Oncotarget 2016, 7, 15959–15976. [CrossRef] 75. Sordello, S.; Bertrand, N.; Plouet, J. Vascular endothelial growth factor is up-regulated in vitro and in v by androgens. Biochem. Biophys. Res. Commun. 1998, 251, 287–290. [CrossRef] 76. Eisermann, K.; Fraizer, G. The Androgen Receptor and VEGF: Mechanisms of Androgen-Regulated Angiogenesis in Prostate Cancer. Cancers 2017, 9, 32. [CrossRef] 77. Kashyap, V.; Ahmad, S.; Nilsson, E.M.; Helczynski, L.; Kenna, S.; Persson, J.L.; Gudas, L.J.; Mongan, N.P. The lysine specific demethylase-1 (LSD1/KDM1A) regulates VEGF-A expression in prostate cancer. Mol. Oncol. 2013, 7, 555–566. [CrossRef] 78. Deng, X.; Shao, G.; Zhang, H.; Li, C.; Zhang, D.; Cheng, L.; Elzey, B.; Pili, R.; Ratliff, T.; Huang, J. Proteinarginine methyltransferase 5 functions as an epigenetic activator of the androgen receptor to promote prostate cancer cell growth. Oncogene 2016, 36, 1223–1231. [CrossRef] 79. Eisermann, K.; Broderick, C.J.; Bazarov, A.; Moazam, M.M.; Fraizer, G.C. Androgen up-regulates vascular endothelial growth factor expression in prostate cancer cells via an Sp1 binding site. Mol. Cancer 2013, 12, 7. [CrossRef] Int. J. Mol. Sci. 2019, 20, 2676 15 of 16 15 of 16 80. Antonarakis, E.; Armstrong, A.; Dehm, S.; Luo, J. Androgen receptor variant-driven prostate cancer: Clinical implications and therapeutic targeting. Prostate Cancer Prostatic Dis. 2016, 19, 231–241. [CrossRef] 81. Fernandez, E.V.; Reece, K.M.; Ley, A.M.; Troutman, S.M.; Sissung, T.M.; Price, D.K.; Chau, C.H.; Figg, W.D. Dual targeting of the androgen receptor and hypoxia-inducible factor 1α pathways synergistically inhibits castration-resistant prostate cancer cells. Mol. Pharmacol. 2015, 87, 1006–1012. [CrossRef] 82. Pignon, J.C.; Koopmansch, B.; Nolens, G.; Delacroix, L.; Waltregny, D.; Winkler, R. Androgen receptor controls EGFR and ERBB2 gene expression at different levels in prostate cancer cell lines. Cancer Res. 2009, 69, 2941–2949. [CrossRef] 83. Zheng, Y.; Izumi, K.; Yao, J.L.; Miyamoto, H. Dihydrotestosterone upregulates the expression of epidermal growth factor receptor and ERBB2 in androgen receptor-positive bladder cancer cells. Endocr. Relat. Cancer 2011, 18, 451–464. © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). References Differential recruitment of nuclear receptor coactivators may determine alternative RNA splice site choice in target genes. Proc. Natl. Acad. Sci. USA 2004, 101, 2270–2274. [CrossRef] 95. Peach, C.J.; Mignone, V.W.; Arruda, M.A.; Alcobia, D.C.; Hill, S.J.; Kilpatrick, L.E.; Woolard, J. Molecular Pharmacology of VEGF-A Isoforms: Binding and Signalling at VEGFR2. Int. J. Mol. Sci. 2018, 19, 1264. [CrossRef] 96. Amin, E.M.; Oltean, S.; Hua, J.; Gammons, M.V.; Hamdollah-Zadeh, M.; Welsh, G.I.; Cheung, M.-K.; Ni, L.; Kase, S.; Rennel, E.S.; et al. WT1 mutants reveal SRPK1 to be a downstream angiogenesis target by altering VEGF splicing. Cancer Cell 2011, 20, 768–780. [CrossRef] 97. Nowak, D.G.; Woolard, J.; Amin, E.M.; Konopatskaya, O.; Saleem, M.A.; Churchill, A.J.; Ladomery, M.R.; Harper, S.J.; Bates, D.O. Expression of pro- and anti-angiogenic isoforms of VEGF is differentially regulated by splicing and growth factors. J. Cell Sci. 2008, 121, 3487–3495. [CrossRef] Int. J. Mol. Sci. 2019, 20, 2676 16 of 16 16 of 16 98. Nowak, D.G.; Amin, E.M.; Rennel, E.S.; Hoareau-Aveilla, C.; Gammons, M.; Damodoran, G.; Hagiwara, M.; Harper, S.J.; Woolard, J.; Ladomery, M.R.; et al. Regulation of vascular endothelial growth factor (VEGF) splicing from pro-angiogenic to anti-angiogenic isoforms: A novel therapeutic strategy for angiogenesis. J. Biol. Chem. 2010, 285, 5532–5540. [CrossRef] 99. Mavrou, A.; Brakspear, K.; Hamdollah-Zadeh, M.; Damodaran, G.; Babaei-Jadidi, R.; Oxley, J.; Gillatt, D.A.; Ladomery, M.R.; Harper, S.J.; Bates, D.O.; Oltean, S. Serine-arginine protein kinase 1 (SRPK1) inhibition as a potential novel targeted therapeutic strategy in prostate cancer. Oncogene 2015, 34, 4311–4319. [CrossRef] [PubMed] 100. Mavrou, A.; Oltean, S. SRPK1 inhibition in prostate cancer: A novel anti-angiogenic treatment through modulation of VEGF alternative splicing. Pharmacol. Res. 2016, 107, 276–281. [CrossRef] 101. Van den Brûle, F.A.; Waltregny, D.; Castronovo, V. Increased expression of galectin-1 in carcinoma-associated stroma predicts poor outcome in prostate carcinoma patients. J. Pathol. 2001, 193, 80–87. [CrossRef] 102. Stanley, P. Galectin-1 Pulls the Strings on VEGFR2. Cell 2014, 156, 625–626. [CrossRef] [PubMed] 103. Jaworski, F.M.; Gentilini, L.D.; Gueron, G.; Meiss, R.P.; Ortiz, E.G.; Berguer, P.M.; Ahmed, A.; Navone, N.; Rabinovich, G.A.; Compagno, D.; et al. In Vivo Hemin Conditioning Targets the Vascular and Immunologic Compartments and Restrains Prostate Tumor Development. Clin. Cancer Res. 2017, 23, 5135–5148. [CrossRef] [PubMed] 104. Laderach, D.J.; Gentilini, L.D.; Giribaldi, L.; Delgado, V.C.; Nugnes, L.; Croci, D.O.; Al Nakouzi, N.; Sacca, P.; Casas, G.; Mazza, O.; et al. References A Unique Galectin Signature in Human Prostate Cancer Progression Suggests Galectin-1 as a Key Target for Treatment of Advanced Disease. Cancer Res. 2013, 73, 86–96. [CrossRef] [PubMed] 105. Goud, N.S.; Soukya, P.S.L.; Ghouse, M.; Komal, D.; Alvala, R.; Alvala, M. Human Galectin-1 and its inhibitors: Privileged target for cancer and HIV Mini Rev Med Chem 2019 [CrossRef] [PubMed] 104. Laderach, D.J.; Gentilini, L.D.; Giribaldi, L.; Delgado, V.C.; Nugnes, L.; Croci, D.O.; Al Nakouzi, N.; Sacca, P.; Casas, G.; Mazza, O.; et al. A Unique Galectin Signature in Human Prostate Cancer Progression Suggests Galectin-1 as a Key Target for Treatment of Advanced Disease. Cancer Res. 2013, 73, 86–96. [CrossRef] [PubMed] Casas, G.; Mazza, O.; et al. A Unique Galectin Signature in Human Prostate Cancer Progression Suggests Galectin-1 as a Key Target for Treatment of Advanced Disease. Cancer Res. 2013, 73, 86–96. [CrossRef] [PubMed] 105. Goud, N.S.; Soukya, P.S.L.; Ghouse, M.; Komal, D.; Alvala, R.; Alvala, M. Human Galectin-1 and its inhibitors: Privileged target for cancer and HIV. Mini Rev. Med. Chem. 2019. [CrossRef] [PubMed] 105. Goud, N.S.; Soukya, P.S.L.; Ghouse, M.; Komal, D.; Alvala, R.; Alvala, M. Human Galectin-1 and its inhibitors: Privileged target for cancer and HIV. Mini Rev. Med. Chem. 2019. [CrossRef] [PubMed] © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
https://openalex.org/W1570146727
https://www.intechopen.com/citation-pdf-url/29106
English
null
A Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors
InTech eBooks
2,012
cc-by
8,975
A Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors Xuye Zhuang1, Pinghua Li2 and Jun Yao1 1State Key Laboratory of Optical Technologies for Microfabrication, Institute of Optics and Electronics, Chinese Academy of Sciences 2Department of Electronic Information Technology, Sichuan Modern Vocational College China Xuye Zhuang1, Pinghua Li2 and Jun Yao1 1State Key Laboratory of Optical Technologies for Microfabrication, Institute of Optics and Electronics, Chinese Academy of Sciences 2Department of Electronic Information Technology, Sichuan Modern Vocational College China Selection of our books indexed in the Book Citation Index in Web of Science™ Core Collection (BKCI) Interested in publishing with us? Contact book.department@intechopen.com Numbers displayed above are based on latest data collected. For more information visit www.intechopen.com Open access books available Countries delivered to Contributors from top 500 universities International authors and editors Our authors are among the most cited scientists Downloads We are IntechOpen, the world’s leading publisher of Open Access books Built by scientists, for scientists 14% 191,000 210M TOP 1% 154 7,200 7 1. Introduction Optical fiber evanescent field sensors(OFEFS) are playing more and more important roles in detecting chemical, bacilli, toxin, and environmental pollutants for their high efficiency, good accuracy, low cost, and convenience (Maria et al., 2007; Wolfbeis, 2006; Angela et al., 2007). In general, these sensors exploit the interactions between evanescent field of the sensing fibers and the surrounding analyte under investigation. Concentrations of analyte can be related to the power attenuation caused by these interactions, and the more energy interacted with the analyte, the higher the sensitivities of the sensors. In order to expose the evanescent filed of the fiber to the analyte, the fiber cladding is often removed and the fiber core is surrounded by the detecting material. To make clear the operation principle of the evanescent field interacting with the analyte and to estimate the sensitivity according to this principle are extremely important to the sensor’s designers. This field has attracted a lot of research groups extraordinarily and been widely discussed both based on geometric optics and optical waveguide theory (Yu et al., 2006; Messica et al.,1996; Gupta & Singh, 1994; Guo & Albin, 2006). However a big difference between the theoretical and experimental values is often observed especially when the sensor’s absorbency is low (Payne & Hale, 1993; Wu et al., 2007; Deng, et al., 2006). In this chapter, a thoroughly theoretical study of the OFEFS is presented. The reason why the sensor’s absorbency, A, shows nonlinear increase with the sensing fiber’s length, l, is given and analyzed. Also, a new method to estimate the sensitivity of the sensor is proposed and confirmed with experimental results, which shows a good agreement with the experimental results and is more accurate than the methods used before. The fabrication technologies of the sensing fibers are introduced. The practical importance of this study lies in helping for understanding, design and construction of optical fiber evanescent field sensors. This chapter is organized as follows. In section 2, the theory basis of the optical fiber evanescent field sensor is introduced and analyzed. The nonlinear relationship between A and l is discussed theoretically. The new method to estimate the sensitivity of the sensor is proposed in section 2.3. The fabrication method of the sensing fiber with acicular www.intechopen.com 166 Fiber Optic Sensors encapsulation is described in section 3. 1. Introduction Also, the experiments used to confirm the new method and the nonlinear relationship between A and l are implemented and the results are analyzed. Finally, the contents of the chapter are summarized briefly in section 4. encapsulation is described in section 3. Also, the experiments used to confirm the new method and the nonlinear relationship between A and l are implemented and the results are analyzed. Finally, the contents of the chapter are summarized briefly in section 4. 2.1 Evanescent field of the optical fiber / 0 p x d x E E e   (4) (4) Where x is the distance from the core-cladding interface, E0 is the electric field magnitude of the field at the interface, and p d represents the penetration depth, which is the distance where the evanescent field decreases to 1/e of its value at the core-cladding interface and is mathematically given by (Zhuang et al., 2009a) 0 2 2 2 1/2 2 2 ( sin ) co cl p n n d      (5) (5) where nj0 is the wavelength of the light source in the vacuum. Because of the non-absorbing cladding, no energy loss is measured in the fiber. When an absorbing media substitutes for the cladding, the intensity of the evanescent field is attenuated and the total transmitted energy in the fiber is reduced. These losses are caused by the interactions between the analyte and the evanescent field. A bigger p d indicates a wider scope covered by the field, more chances of the energy interacts with the analyte, a bigger loss of the energy and a higher sensitivity of the sensor. 2.1 Evanescent field of the optical fiber Optical fiber consists of a cylindrical core and a surrounding cladding, both made of silica, as illustrated in Fig. 1. The core is generally doped with germanium to make its refractive index co n slightly higher than the refractive index of the cladding cl n . Fig. 1. The structure of step-index fiber Core Jacket cl n Cladding co n Fig. 1. The structure of step-index fiber If a ray is launched into the fiber and its propagation angle 2 is greater than the critical angle c , which is defined by the Eq.(1), the light will propagate along the fiber by total internal reflection (TIR). (1) arcsin( / ) c cl co n n  (1) Fig. 2 shows a hypothetical ray of light propagating along the fiber. 0 n is the refractive index of the air. 0 is the incident angle of the light at the core-air interface, which must obey the relationship described in Eq.(2) in order that the incident light can propagate along the fiber by TIR. Fig. 2. The schematic of the light rays transmitting in the evanescent field sensing fiber X Y Z Cladding Core Evanescent field 1  cl n 0  co n 2  0 n Cladding Fig. 2. The schematic of the light rays transmitting in the evanescent field sensing fiber www.intechopen.com A Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors 167 1 2 2 2 0 0 1 sin ( ) co cl n n n   (2) (2) m  is the maximum value of 0 and defined by Eq.(3). m  is the maximum value of 0 and defined by Eq.(3). 1 2 2 2 0 1 2 sin ( ) m n n n NA     (3) (3) If the incident angle of a ray is smaller than m  , that ray of light will propagate along the fiber by TIR. NA is the numerical aperture of the fiber, which is a dimensionless number that characterizes the range of the incident angles over which the light can transmit by TIR in the fiber. Though the light propagates along the fiber by TIR, there is energy penetrating into the cladding. The electric field amplitude of this field decays exponentially from the core- cladding interface and is described as Eq.(4). 2.2 Mathematical mode of the optical fiber evanescent field sensor The structure of the optical fiber evanescent field sensor is shown in Fig.3. One portion of the fiber’s cladding is removed, and its core is exposed to the analyte directly. So the energy of the evanescent field can interact with the analyte, and the concentrations of the analyte can be detected by measuring the loss of the output power of the sensing fiber. The extent of the energy loss can be marked by the absorbency of the sensor, A, which is described as follows. 10 log out in P A P        (6) (6) where out P and in P are the output power of the optical fiber evanescent field sensors with and without an absorptive analyte for sensing. When detecting the same sample with the www.intechopen.com www.intechopen.com 168 Fiber Optic Sensors same concentrations, the bigger the value, the more sensitive the sensor. It shows clearly in Eq.6 that the sensitivity of OFEFS can also be evaluated by the value of / out in P P . When detecting the same sample, the smaller the value, the higher the sensor’s sensitivity. same concentrations, the bigger the value, the more sensitive the sensor. It shows clearly in Eq.6 that the sensitivity of OFEFS can also be evaluated by the value of / out in P P . When detecting the same sample, the smaller the value, the higher the sensor’s sensitivity. Fig. 3. Schematic diagram of the optical fiber evanescent field sensor According to Beer’s law, out P is expressed as (Wu et al., 2007) Cladding Analyte Core l Analyte Cladding Fig. 3. Schematic diagram of the optical fiber evanescent field sensor According to Beer’s law, out P is expressed as (Wu et al., 2007) exp( ) 1 out P Pin N r l j j j      , (7) (7) Subscript j stands for the jth mode optical waveguide transmitting in the sensing fiber. Hence, rj is the fraction of the optical power carried by the jth mode in the sensor. When using incoherent light source, the energy carried by each mode transmitting in the sensing fiber is almost the same (Gloge, (1971). Also, after a long length of transmitting, the energy of each mode is almost equal through energy couples between different modes in the fiber (Zhuang et al., 2009a). 2.2 Mathematical mode of the optical fiber evanescent field sensor The vector zl  indicates that the Z axis of the coordinate is along the fiber’s axis. The particular explanations of each parameter used in Eq.(11) are listed in the reference (Gloge, 1971). For multimode sensing fibers, j can be calculated using Eq.(12). 0.5 (2 2 ) j j N N j   (12) (12) where N is the number of the modes supported by the fiber and defined by where N is the number of the modes supported by the fiber and defined by 2 2 4 V N    (13) (13) V is the normalized frequency of the fiber and expressed as V is the normalized frequency of the fiber and expressed as 1 2 2 2 2 ( ) co cl a V n n     (14) (14) where a is the radius of the core, nj is the wavelength of the light. As to less-mode or single mode optical fibers,of different modes should be calculated carefully based on optical waveguide theory (Zhuang, 2009b). where a is the radius of the core, nj is the wavelength of the light. As to less-mode or single mode optical fibers,of different modes should be calculated carefully based on optical waveguide theory (Zhuang, 2009b). 2.2 Mathematical mode of the optical fiber evanescent field sensor So Eq.(8) can be modified as (Payne & Hale, 1993), Subscript j stands for the jth mode optical waveguide transmitting in the sensing fiber. Hence, rj is the fraction of the optical power carried by the jth mode in the sensor. When using incoherent light source, the energy carried by each mode transmitting in the sensing fiber is almost the same (Gloge, (1971). Also, after a long length of transmitting, the energy of each mode is almost equal through energy couples between different modes in the fiber (Zhuang et al., 2009a). So Eq.(8) can be modified as (Payne & Hale, 1993), 1 exp( ) N in out j j P P l N      (8) (8) where l is the length of the sensing fiber whose cladding is removed, is the absorption coefficient of the analyte and is expressed as 10 log c e   (9) 10 log c e   (9) (9) where and c are molar absorption coefficient and concentration of the analyte, respectively. where and c are molar absorption coefficient and concentration of the analyte, respectively. is the fraction of power transmitting in the fiber cladding that carried by evanescent field f the sensor and is depicted as, is the fraction of power transmitting in the fiber cladding that carried by evanescent field of the sensor and is depicted as, cl cl co P P P   (10) cl cl co P P P   (10) (10) where co P is the energy transmitting in the core; cl P is the energy transmitting in the cladding in the form of evanescent field, which is the only energy interacted with the analyte. j is the energy fraction of the jth mode transmitting in the cladding. can be calculated using Eq.(11). www.intechopen.com www.intechopen.com Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors 169 2 0 0 2 0 0 ( ) 1 1 ( ) a e z co cl co e z R e h l rdrd P P P R e h l rdrd                      (11) (11) The integral part of Eq.(11) is the Poyning Vector Integral in cylindrical coordinates. 2.3 Nonlinear relationship between absorbency and the length of the sensing fiber From Eq.(6) and Eq.(8), we can obtain Eq.(15) which describes the absorbency of the sensing fibers. 10 1 log ( exp( )) N j j l A N       (15) (15) The sensitivity of the optical fiber evanescent field sensors, M, is defined as the instantaneous change of the sensors’ absorbency relative to the analyte. / M dA dC  (16) / M dA dC  (16) dA is the sensitivity of the photoelectric detector, which is the least variance of the absorbency the equipment can distinguish. According to Eq.(15) and dA , the lowest concentrations of the analyte to be detected can be approximately estimated. In experiments, the actual sensitivity of the sensor can be obtained by Eq.(17). A M C    (17) (17) www.intechopen.com www.intechopen.com 170 Fiber Optic Sensors where A  is the difference of the sensors’ absorbency obtained from two different detections, C  is the difference of the analytes’ concentrations. From Eq.(15) and Eq.(16), it is found the absorbency A and the sensitivity M of the sensor linearly increase with l. However, non-linear dependence of A and M on the l is often observed in experimental tests (Zhuang, 2009a, 2009b). So the equations listed above should be modified to obtain a more accurate simulation results. It shows clearly in Eq.(5) that p d is decided by the parameters , co n , cl n and the propagation angle 2 of the ray. As the evanescent field energy transmitting along the fiber, none of those parameters change. So the value of p d keeps unchanged during the process. Because of the interactions between the evanescent field and the analyte, the amplitude of the field decreases quickly which is shown clearly in Fig.4. The portion of the energy transmitting in the cladding is defined by Eq.(11), which indicates the amplitude of the evanescent field of the sensing fiber. For multimode fibers, j is given approximately by Eq.(12), which is the function of N. N is decided by the normalized frequency V of the sensing fiber. As expressed in Eq.(14), V is determined by the characters of the sensing fiber, the wavelength of the light source and the analyte’s refractive index. After an experiment system is set up, V and N are determined, hence j is determined. Fig. 4. 2.3 Nonlinear relationship between absorbency and the length of the sensing fiber Schematic of the evanescent field energy distribution along the sensing fiber Evanescent field Core Analyte l Z O X Y Evanescent field Evanescent field X O Fig. 4. Schematic of the evanescent field energy distribution along the sensing fiber So j  keeps constant along the sensing fiber’s axis. As l grows, the evanescent field energy carried by the sensing fiber of unit length, which interacts with the analyte, decreases. That is to say the contribution per unit length of the sensing fiber to A decreases as l increased. So the linear relationship between A, M and L does not exist. So j  keeps constant along the sensing fiber’s axis. As l grows, the evanescent field energy carried by the sensing fiber of unit length, which interacts with the analyte, decreases. That is to say the contribution per unit length of the sensing fiber to A decreases as l increased. So the linear relationship between A, M and L does not exist. Consider a sensing fiber whose refractive index of the core is 1.4682 and the refractive index of the detecting material is 1.3334. The wavelength of the light source is 632.8nm, the sensing fiber is 14mm in length, 8μm in diameter, and its 120  and 200  are 0.0643 and 0.1104, respectively. Assume the energy carried by these two modes is both 1W, and the energy carried by the evanescent field is totally absorbed by the analyte. The calculated results of Pcl on different locations of the sensing fiber are shown in Fig.5. For η200, the ratio of Pcl on the end of the sensing fiber to that on the beginning is just 19.47%, and it is 39.50% www.intechopen.com 171 A Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors for η120. As l grows, the value of Pcl tends to be small. Pcl decreases much faster, when the order of the waveguide is higher. It indicates that the contribution per unit length of the sensing fiber to A becomes small as l grows, especially the ones close to the end of the sensing fiber. This is the essential reason why A does not increase linearly with l. Fig. 5. 2.3 Nonlinear relationship between absorbency and the length of the sensing fiber cl P on different locations of the sensing fiber 0 2 4 6 8 10 12 14 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 Locations [mm] Energy Pcl\ w Pcl 120 P cl 200 sum Fig. 5. cl P on different locations of the sensing fiber 2.4 New method to estimate the sensitivity of the OFEFS Here does not work as the index of the EXP function as in Eq.(8) but it is multiplied by j in r P to form the power that interacts with the analyte. At the next l , the cladding power ( ) ' ( 1) ( ) ( ) clj k clj k j coj k P P P     is redistributed according to Eq. (10). Then the next calculation cycle begins. Where j in j r P means the power flowing in the cladding i.e. the power interacts with the analyte, and the subscript k means the kth l , hence ( ) clj k P stands for the cladding power in the kth l . Here does not work as the index of the EXP function as in Eq.(8) but it is multiplied by j in r P to form the power that interacts with the analyte. At the next l , the cladding power ( ) ' ( 1) ( ) ( ) clj k clj k j coj k P P P     is redistributed according to Eq. (10). Then the next calculation cycle begins. l  ( 1) clj k P  ( ) clj k P ( ) coj k P ( ) ' clj k P n k+1 k+2 …… …… 0 1 2 k k+3 n-1 ( 1) coj k P  Fig. 6. Schematic diagram of the sensing fiber divided into n parts and the energy l  ( 1) clj k P  ( ) clj k P ( ) coj k P ( ) ' clj k P n k+1 k+2 …… …… 0 1 2 k k+3 n-1 ( 1) coj k P  Fig. 6. Schematic diagram of the sensing fiber divided into n parts and the energy distribution The absorbed energy ( ) clj k P  caused by the analyte can be written by The absorbed energy ( ) clj k P  caused by the analyte can be written by ( ) ' ( ) ( ) ( ) (exp( ) 1) clj k clj k clj k clj k P P P l P        (19) (19) When n , ( ) clj k clj P dP   and l dl  , Eq. 2.4 New method to estimate the sensitivity of the OFEFS Considered that only cl P interacts with the analyte andis constant along the fiber axis, a new method to estimate the output power of OFEFS is proposed. In this method, the sensing fiber is evenly divided into n fractions with each part to be l in length as shown in Fig.6. As Pcl transporting along the sensing fiber, it is attenuating following Beer’s law. Because is constant along the whole sensing fiber, there is power replenishment to cl P from the fiber core simultaneously. For each fraction, l  is very small, so it can be assumed that the energy replenishment occurred at the end of l . The total energy left will be redistributed according toat the beginning of the next l . The process repeats until the calculations on all the fractions have finished. As n trends to be infinite, the calculated result trends to be the real value. In this way the two most important factors, that is only the cladding power interacts with the analyte and is constant along the fiber, are embodied significantly. Now consider the power transmitting in the jth mode between the kth and the ( 1) k th  parts of the sensing fiber. ( ) clj k P is the initial power transmitting in the cladding of the fiber of the kth l , and ( ) coj k P is the initial power in the core. ( ) ' clj k P is the residual energy of ( ) clj k P after passing l . According to Beer’s law (18) ' ( ) ( ) exp( ) ( ) exp( ) clj k clj k j in j k P P l r P l        (18) ' ( ) ( ) exp( ) ( ) exp( ) clj k clj k j in j k P P l r P l        www.intechopen.com www.intechopen.com 172 Fiber Optic Sensors Where j in j r P means the power flowing in the cladding i.e. the power interacts with the analyte, and the subscript k means the kth l , hence ( ) clj k P stands for the cladding power in the kth l . A Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors 173 ( ) 1 1 0 1 totj totj N N n clj k j j k out in N j P P P P P           (22) (22) where totj j in P r P  is the initial energy of the jth mode. where totj j in P r P  is the initial energy of the jth mode. totj j in P r P  is the initial energy of the jth mode. In order to facilitate calculation and obtain an estimated value of good accuracy, the convergence condition of Eq.(22) is set as 1 2 1 2 1 ( ) ( ) 0.1% ( ) 1000 out out n n in in out n in P P P P P P n n           (23) (23) where 1 n and 2 n are the iterative times of the recursion. where 1 n and 2 n are the iterative times of the recursion. where 1 n and 2 n are the iterative times of the recursion. where 1 n and 2 n are the iterative times of the recursion. 2.4 New method to estimate the sensitivity of the OFEFS (19) becomes exp( ) 1 clj clj dP dl P     (20) (20) Together with the initial condition, Eq.(20) and Eq.(10) form the mathematical model of OFEFS. Together with the initial condition, Eq.(20) and Eq.(10) form the mathematical model of OFEFS. (0) (0) exp( ) 1 clj clj clj j clj coj clj coj j in dP dl P P P P P P r P                   (21) (0) (0) exp( ) 1 clj clj clj j clj coj clj coj j in dP dl P P P P P P r P                   (21) (21) Where in P is the initial input power of the OFEFS. (0) clj P and (0) coj P are the initial values of clj P and coj P , respectively. Where in P is the initial input power of the OFEFS. (0) clj P and (0) coj P are the initial values of clj P and coj P , respectively. It is difficult to get an analytic solution of Eq.(21), but more convenient to solve it by numerical integration. Here we prefer to solve this question using recursion. The output power of the sensor after passing the whole sensing fiber can be expressed as www.intechopen.com A Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors A Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors 3.1 Preparation of the sensing fiber Optical fiber evanescent field sensors with acicular encapsulation are fabricated using MEMS silicon photolithography technology and silica wet-etching technology. This type of OFEFS is small, consuming little reagent, suffering from less deformation during the detection process and protecting the sensors from pollution. The sensors’ sample cell consists of a cap and a bottom. The characters of the cap and the bottom are illustrated in Fig. 7. The sizes of the cap and the bottom are both 1mm×20mm. There are two holes fabricated in the cap, which are the channels for the sample flow in and the waster drain out. The fiber slit in the bottom is used to fix the sensing fiber, which will facilitate the process of encapsulation greatly. The slit is 2.5mm in length, 250μm in width and 150μm in depth. The work of the cone that manufactured in the bottom is to guide the sample/de-ionized water into or out of the sample pool. The island stand in the sample pool is used to support the sensing fiber. The function of the slit decorated in the island is to fix the sensing fiber, which can avoid the sensing fiber from shaking. The slit is 140μm in width and 100μm in depth. The slit is 50μm shallower than the fiber slit. The fiber with cladding is thicker than the fiber whose cladding is removed. If these slits are made with the same depth, the sensing fiber will warp, the repeatability of the sensor will be poor and the results will be distorted. So using slits with different depth to support different parts of the fiber can help the sensing fiber keep straight in the sample pool. Sample pool is the place where the analyte interacts with the evanescent field. The width of the sample pool is 200μm, and 150μm in depth. The length of the pool can be chosen discretionary according to experimental requirements. When the length of the pool is 7mm, the total reagent the sensor consumed is only 0.21μl. Both the cap and the bottom are fabricated based on MEMS technologies. In order to obtain high sensitivities, the radius of the sensing fiber is usually very small, such as 4μm. So the strength of the sensing fiber is weak, and the sensing fiber is fragile and www.intechopen.com 174 Fiber Optic Sensors Fiber Optic Sensors 174 Fig. 7. 3.1 Preparation of the sensing fiber The structure of the cap and the bottom easy to break. In order to solve this problem, the fiber is fixed to the bottom first. Then, the cap is bound to the bottom to form the sensor’s cell using glue. The construction of the cell is illustrated in Fig.8. Fig. 8. The schematic structure of the sample cell Cap Bottom Amplify Hole Island Cone Bottom Cap Fiber slit Sensing fiber Island Glue Hole Glue Sample Fiber Fiber slit Fiber Fiber slit Sample pool www.intechopen.com Fig. 7. The structure of the cap and the bottom Cap Bottom Amplify Hole Island Cone Fiber slit Sample pool Sample pool Amplify Fig. 7. The structure of the cap and the bottom easy to break. In order to solve this problem, the fiber is fixed to the bottom first. Then, the cap is bound to the bottom to form the sensor’s cell using glue. The construction of the cell is illustrated in Fig.8. Fig. 8. The schematic structure of the sample cell Bottom Cap Fiber slit Sensing fiber Island Glue Hole Glue Sample Fiber Fiber slit Fiber Fig. 8. The schematic structure of the sample cell www.intechopen.com 175 A Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors The fiber cladding is removed using wet etching, the corrosion solution consists of HF, de- ionized water and CH3COOH. The function of HF is to etch silica with the well-known reactions: 4HF+SiO2→SiF4+2H2O (24) 6HF+SiO2→H2SiF6+2H2O (24) By adding CH3COOH as a buffer, the etching process becomes much more gently and the quality of the core surface would be improved greatly. The velocity of etching is mainly influenced by the parameters list as follows: 1. the concentration of HF. The higher the concentration of the HF in the corrosion solution, the more Freacts with silica, the higher the speed of the etching is; 2. the microstructure of silica. Because the silica used in cladding and core is doped with different elements, the microstructures of them are inconsistent, thus the etching speeds of them are different. A compact structure of silica indicates a low etching speed. p 3. the temperature. The chemical reaction equations shown in Eq.(24) are endothermic reactions. When the temperature is high, the reaction between HF and the silica is exquisite and the etching speed is high. 3.1 Preparation of the sensing fiber As the reaction goes on, the concentration of Fin the corrosion solution decreases gradually, and the etching speed slows down. However, the radius of the fiber becomes small, which indicates the area-volume ratio of the fiber becomes bigger. In this case, the speed of the etching will increase. So it’s really difficult to control the speed of the etching speed carefully. Here, two methods to monitor the fiber’s radius are proposed. 1. by monitoring the output power of the fibers. As shown in Fig.9, a powermeter is used to monitor the transmitted power which is a function of the core diameter. Fig.10 shows the relationship between the output power and the etching time. The output power decreases slightly as the cladding is etched by the HF. When the cladding is eaten up and the core is etched by the etching solution, the strength of the output power decreases dramatically. When the core is eaten up, nothing is left in the sample cell, the relative strength of the output power keeps constant, which is the strength of the background noise. The volume ration among HF, de-ionized water, CH3COOH in the corrosion solution used here is 1.3:1:1. According to the relative strength of the output power the radii of the fibers can be estimated accurately. 2. 2. based on the experimental experience. According to the experimental experience, the etching speeds of corrosion solutions of different proportions can be approximately estimated. First, using corrosion solutions with plentiful HF to etch the cladding. When cladding is to be eaten up, solutions with little HF should be chosen to reduce the etching speed and improve the quality of the sensing fibers’ surface. During this process, the radius of the fiber should be checked using microscope frequently. When appropriate radius is obtained, the etching process is terminated. In room temperature, as the volume ratio among HF, de-ionized water, CH3COOH in the solution is 1:1:1, the etching speed of the cladding is 20μm per hour, and 30μm per hour of the core. www.intechopen.com 176 Fiber Optic Sensors Fig. 9. Experimental set-up of the etching process 0 5000 10000 15000 20000 25000 30000 35000 0 500 1000 1500 2000 2500 Finished Core Cladding Relative strength Times [s] Fig. 10. The relationship between the output power and the etching time Fig. 11 is the sensing fiber fabricated using the method described above. 3.1 Preparation of the sensing fiber A cone is obviously observed in the end of the sensing fiber. As shown in Fig.12, when HF erodes the fibe towards the core along the radial direction, cauterization occurs in the fibers’ axial direction simultaneously. This is the main reason why the sensing fibers’ end is tapered. Light source Fiber Powermeter Sample cell Light source Fiber Powermeter Sample cell Fiber Light source Powermeter Sample cell Fig. 9. Experimental set-up of the etching process Fig. 9. Experimental set-up of the etching process Fig. 9. Experimental set-up of the etching process 0 5000 10000 15000 20000 25000 30000 35000 0 500 1000 1500 2000 2500 Finished Core Cladding Relative strength Times [s] Fig. 10. The relationship between the output power and the etching time Fig. 11 is the sensing fiber fabricated using the method described above. A cone is obviously observed in the end of the sensing fiber. As shown in Fig.12, when HF erodes the fiber towards the core along the radial direction, cauterization occurs in the fibers’ axial direction simultaneously. This is the main reason why the sensing fibers’ end is tapered. 0 5000 10000 15000 20000 25000 30000 35000 0 500 1000 1500 2000 2500 Finished Core Cladding Relative strength Times [s] Fig. 10. The relationship between the output power and the etching time Fig. 11 is the sensing fiber fabricated using the method described above. A cone is obviously observed in the end of the sensing fiber. As shown in Fig.12, when HF erodes the fiber towards the core along the radial direction, cauterization occurs in the fibers’ axial direction simultaneously. This is the main reason why the sensing fibers’ end is tapered. www.intechopen.com 177 A Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors Fig. 11. SEM of the sensing fiber Fig. 12. Schematic of the etching directions of the HF Jacket Fiber Etching direction HF Etching direction www.intechopen.com Fig. 11. SEM of the sensing fiber Fig. 11. SEM of the sensing fiber Fig. 11. SEM of the sensing fiber Fig. 12. Schematic of the etching directions of the HF Jacket Fiber Etching direction HF Etching direction Fig. 12. Schematic of the etching directions of the HF Jacket Fiber Etching direction HF Etching direction Fiber Jacket direction Fig. 12. 3.1 Preparation of the sensing fiber Schematic of the etching directions of the HF www.intechopen.com 178 Fiber Optic Sensors When the etching terminated, the core of the fiber is washed by de-ionized water and baked to release the remaining liquid. Then the sample cell with the sensing fiber can be used as an optical fiber evanescent field sensor directly, as shown in Fig. 13. Fig. 13. The optical fiber evanescent field sensor used in the experiments Fiber Sample Cell Fig. 13. The optical fiber evanescent field sensor used in the experiments 3.2 Experimental set-up The experimental set-up is shown in Fig.14. The optics source used here is He-Ne laser (Type 260A,632.8nm). Its minimum output power is 1.8 mW, the maximum drift of it is 3%  , the beam diameter is 2mm and the beam divergence is 1.5 mrad. As shown in Fig.14, the laser is focused and collimated using a couple of lens, then the light is injected into the fiber and the output power is measured by a spectrometer. After the spectrum is analyzed using a computer, the information of the analytes’ concentrations is obtained. After the detection, the sensing fiber is refreshed by de-ionized water bath, and the sensing fiber can be used repeatedly. Fig. 14. The experimental set-up The absorption medium used for experiments is methylene blue (MB) dissolved in de- ionized water and the absorbing peak is 664 nm. Fig.15 is the absorbency spectrum of the methylene blue in visible region. The concentration of the methylene blue used here is 6 1 10  mol/L. Light source Lens Sample cell Optical fiber Spectrometer Couples Sensing fiber Silicon wafer Computer Couples Sensing fiber Fig. 14. The experimental set-up The absorption medium used for experiments is methylene blue (MB) dissolved in de- ionized water and the absorbing peak is 664 nm. Fig.15 is the absorbency spectrum of the methylene blue in visible region. The concentration of the methylene blue used here is 6 1 10  mol/L. The absorption medium used for experiments is methylene blue (MB) dissolved in de- ionized water and the absorbing peak is 664 nm. Fig.15 is the absorbency spectrum of the methylene blue in visible region. The concentration of the methylene blue used here is 6 1 10  mol/L. www.intechopen.com 179 A Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors 400 500 600 700 800 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 Absorbency wavelength [nm] Methylene blue Fig. 15. Absorption spectrum of methylene blue solution in de-ionized water wavelength [nm] Fig. 15. Absorption spectrum of methylene blue solution in de-ionized water 3.3 Nonlinear relationship between absorbency and the length of the sensing fiber Fig.16 shows the experimental results of A. In the experiments two sensors with different L, 7mm and 14mm, are used. The radii of the sensing fibers are both 4μm, and the refractive indexes are both 1.4682. As shown in Fig.16, the ratio of the sensor’s absorbency with L=14mm to that with L=7mm is smaller than two. It shows clearly the sensing efficiency declines as L increases. The contribution per unit length of the sensing fiber to A drops as L increased. When the concentration of MB grows, the ratio increases. This phenomenon is mainly blamed on the sensing fibers’ blemish. When the concentration of the analyte is high, the effects of the sensing fibers’ disfigurations on A become obvious. The most common defects of the sensing fibers are displayed in Fig.17. When constructing optical fiber evanescent field sensors, it is not advised to use long sensing fibers because the sensing efficiency of the sensing fiber per unit length decreases as the sensing fiber becomes long. Also, long sensing fibers are difficult to fabricate and easy to disfigure and break. 1 2 3 4 5 6 7 8 9 10 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 7mm 14mm Ratio Concentration of MB [10 -5 mol/L] Absorbency 1.4 1.5 1.6 1.7 1.8 1.9 2.0 Ratio 7mm 14mm Fig. 16. The experimental absorbency of the sensors with different L Concentration of MB [10 -5 mol/L] Fig. 16. The experimental absorbency of the sensors with different L www.intechopen.com Fiber Optic Sensors 180 Fig. 17. Defects of the sensing fibers Bend Taperd Granulation Chemical Film Bizarre Point Granulation Fig. 17. Defects of the sensing fibers 3.4 The new method to estimate the sensitivity of the sensor / out in P P versus the concentrations of MB From Fig 20 it is found when / 0 7 i P P  the results obtained using the new method are 2 4 6 8 10 0.86 0.88 0.90 0.92 0.94 0.96 0.98 1.00 1.02 Pout/ Pin [10-6mol/L] Concentrations of MB P n=140 n=1400 experimental Fig. 19. / out in P P versus the concentrations of MB From Fig. 20 it is found when / 0.7 out in P P  the results obtained using the new method are in a good agreement with the experimental results and more accurate than the results obtained from the methods used before. When the concentration of MB is high, the evanescent field energy absorbed by the analyte is huge. So a small dl should be used to get a more accurate emulational result, which indicates a big n should be chosen, as shown in Fig. 20. From Fig. 20 it is found when / 0.7 out in P P  the results obtained using the new method are in a good agreement with the experimental results and more accurate than the results obtained from the methods used before. When the concentration of MB is high, the evanescent field energy absorbed by the analyte is huge. So a small dl should be used to get a more accurate emulational result, which indicates a big n should be chosen, as shown in Fig. 20. From Fig. 20 it is found when / 0.7 out in P P  the results obtained using the new method are in a good agreement with the experimental results and more accurate than the results obtained from the methods used before. When the concentration of MB is high, the evanescent field energy absorbed by the analyte is huge. So a small dl should be used to get a more accurate emulational result, which indicates a big n should be chosen, as shown in Fig. 20. However, when / 0.7 out in P P  , a difference between experimental and theoretical values is found. Various reasons have been assigned to this discrepancy. 3.4 The new method to estimate the sensitivity of the sensor Fig.18a is the picture of the sensor used in the experiments to confirm the accuracy of the novel method proposed here. Fig.18b is the amplificatory image of the sensing fiber. In order to obtain a sensing fiber of high quality and eliminate the deformation caused in the process of encapsulation, the diameter of the sensing fiber used here is 100μm. Sensing fibers with small radii are easy to disfigure and disturb the experimental results. The error of the experimental results can be reduced by using sensing fibers with large radii. The length of the sensing fiber is 14mm, the refractive index of the fiber core is 1.4577. The wavelength of optic source is 632.8nm. In experiment, the analyte is methylene blue, and its refractive index is adjusted to 1.4550 using glycerol with molar absorption coefficient 27200 / L mol cm  . The diameter of the sensing fiber is etched to 100μm using hydrofluoric acid. Fig. 18. Sensing fiber used in the experiments Sample Cell Fiber a b A Fig. 18. Sensing fiber used in the experiments www.intechopen.com 181 A Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors / out in P P against the concentrations of MB obtained from experiments and different calculation schemes are shown in Fig. 19. The curve P represents the method used before. The curves 140 n  and 1400 n  are the results which obtained using the method proposed here with iterative times 140 and 1400. As shown in Fig.19, the values calculated by our method are much closer to the experimental results, especially when / out in P P is high. / out in P P against the concentrations of MB obtained from experiments and different calculation schemes are shown in Fig. 19. The curve P represents the method used before. The curves 140 n  and 1400 n  are the results which obtained using the method proposed here with iterative times 140 and 1400. As shown in Fig.19, the values calculated by our method are much closer to the experimental results, especially when / out in P P is high. Fig. 19. www.intechopen.com 4. Conclusion In this chapter, we have proposed and demonstrated a novel method to estimate the sensitivity of optical fiber evanescent field sensors. In section 1, the importance of constructing mathematical method to estimate the sensitivity of the sensor is described. And the brief introduction of this chapter is also presented in section 1. In section 2, the operation principle of OFEFS is theoretically studied. The effects of the sensing fibers’ length, l, on the sensors’ absorbency, A, are analyzed. The nonlinear relationship between A and l is also explained in section 2.2. It is found that the contribution per unit length of the sensing fiber to A decreases as l grows. So it does not suggest using long sensing fibers to construct OFEFS. The new method to estimate the sensitivity of OFEFS is proposed in section 2.3. The operation principle of OFEFS is embodied significantly by the mathematical model of the method. In section 3, the experimental set-up of the sensor is built. The fabrication of the sensor with acicular encapsulation is introduced, and the factors which effect the preparation of the sensing fibers are discussed. The nonlinear relationship between A and l is confirmed with experiments. The new method is prove to be in a good agreement with the experimental results and is more accurate than the methods used before. The divergence of the theoretically results from the experimental ones is explained. The practical importance of this study lies in helping for understanding, design, and construction of optical fiber evanescent field sensors with high sensitivity. 3.4 The new method to estimate the sensitivity of the sensor It is mainly caused by the deposition of the methylene blue molecules on the sensing fiber’s surface and the disfigurement of the sensing fiber (Ruddy & Maccrait, 1990 ;Potyrailo & Hobbs, 1998; Zhuang et al., 2009b).The effects of the sensing fibers’ disfigurements on the results are listed as follow: (1) the surface of the etched core is not perfect and scattering occurs on the interface between the analyte and the sensing fiber, which will decrease the output power of the sensor in experiment; (2)the fiber diameter is unsymmetrical and there are errors in the measurement, which will introduce mistakes to the simulation; (3) the bending loss increases the energy loss in the sensing region, and the values of / out in P P is depressed; (4) when the unclad optical fiber etched, taper will occur in the two ends of the sensing region as described in section 3.1. When light passes through the taper, energy loss happened because of the discontinuity of the modes supported by these two different parts of the fiber and the experimental results will be enhanced (Ahmad & Hench, 2005). As the concentration of MB is high, more molecules will be deposited on the sensing fibers’ surface, the absorbency of the sensor will be improved and the discrepancy of the theoretical results from the experimental ones will be enlarged as shown in Fig.20. www.intechopen.com 182 Fiber Optic Sensors 1E-7 1E-6 1E-5 1E-4 1E-3 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 p n=140 n=1400 experimental 1E-7 1E-6 1E-5 0.80 0.84 0.88 0.92 0.96 1.00 1.04 [mol/L] Concentrations of MB Pout/ Pin Fig. 20. / out in P P versus the concentrations of MB Amplify 1E-6 [mol/L] Concentrations of MB Fig. 20. / out in P P versus the concentrations of MB 6. References Ahmad M., Hench L. L., (2005). Effect of Taper Geometries and Launch Angle on Evanescent Wave Penetration Depth in Optical Fibers, Biosensors and Bioelectronics, Vol.(20), (2005), pp 1312-1319, ISSN0956-5663 Angela, L., Shankar P. M., Mutharasan R., (2007). A Review of Fiber-optic Biosensors. Sensors and Actuators B: Chemical, Vol.125, No.2,(2007), pp 688-703,ISSN 0925-4005 Deng X. H., Wu Y. H., Zhou L. Q., Xu M., (2006). Parameters Analysis of Few-modes Optical Fiber Evanescent Absorption Sensor, SPIE, Vol.6032, (2006), pp 603208, ISSN 0277- 786X Gloge D., (1971). Weakly Guiding Fibers, Appied Optics, Vol.10, No.10, (1971), pp 2252-2258, ISSN 0003-6935 Guo S., Albin S., (2006). Transmission Property and Evanescent Wave Absorption of Cladded Multimode Fiber Tapers, Opt. Express, Vol.11, No.3, (2006), pp 215-223, ISSN 2156-7085 Gupta B. D., Singh C. D., (1994). Fiber-optic Evanescent Field Absorption Sensor: A Theoretical Evaluation, Fiber and Integrated Optics, Vol.3, No.4, (1994), pp 433-443, ISSN 0146-8030 Maria E. B., Antonio J. R. S., Fuensanta S. R.,Catalina B. O., (2007). Recent Development in Optical Fiber Biosensors. Sensors, Vol.6, No.7,(June 2007), pp 797-859, ISSN 1424- 8220 Messica A., Greenstein A., Katzir A., (1996). Theory of Fiber-optic, Evanescent-wave Spectroscopy and Sensors, Appied Optics, Vol.35, No.13, (1996), pp 2274-2284, ISBN 0003-6935 Payne F. P., Hale Z. M., (1993). Deviation from Beer’s Law in Multimode Optical Fibre Evanescent Field Sensors, International Journal of Optoelectronics, Vol.8, (1993), pp 743-748, ISSN 0952-5432 Potyrailo R. A., Hobbs S. E., (1998). Near-ultraviolet Evanescent-wave Absorption Sensor Based on A Multimode Optical Fiber, Anal. Chem., Vol.70, No.8, (1998), pp 1639- 1645, ISSN 0003-2700 Ruddy V., Maccrait B. D., (1990). Evanescent Wave Absorption Spectroscopy Using Multimode Fibers, J.Appl.Phys. Vol.67, No.10, (1990),pp 6070-6074, ISSN 0021-8979 Ruddy V., Maccrait B. D., (1990). Evanescent Wave Absorption Spectroscopy Using Multimode Fibers, J.Appl.Phys. Vol.67, No.10, (1990),pp 6070-6074, ISSN 0021-8979 Wolfbeis O. S., (2006). Fiber-optic Chemical Sensors and Biosensor, Anal. Chem., Vol.78, N 12 (2006) 3859 3874 ISSN 0003 2700 Wolfbeis O. S., (2006). Fiber-optic Chemical Sensors and Biosensor, Anal. Chem., Vol.78, No.12, (2006), pp 3859-3874, ISSN 0003-2700 Wu Y. H., Deng X. H., Li F., Zhuang X. Y., (2007). Less-mode Optic Fiber Evanescent Wave Absorbing Sensor: Parameter Design for High Sensitivity Liquid Detection, Sens. Actuators B, Vol.122, (2007), pp 127-133,ISSN 0925-4005 Yu X., Cottendena A., Jones N. B., (2006). A Theoretical Evaluation of Fibre-optic Evanescent Wave Absorption in Spectroscopy and Sensors. Optics and Lasers in Engineering, Vol. 44, (2006), pp 93-101, ISBN 0143-8166 Zhuang X. 5. Acknowledgements The authors acknowledge the supports from West Light Foundation of the Chinese Academy of Sciences (A11K011) and National Natural Science Foundation of China www.intechopen.com 183 A Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors (60978051). The experiments were done in the national key lab of applied optics of China. The authors would like to thank Professor Yihui Wu for her benefited discussions and helps. (60978051). The experiments were done in the national key lab of applied optics of China. The authors would like to thank Professor Yihui Wu for her benefited discussions and helps. 6. References Y., Wu Y. H., Wang S. R., Zhang P., Liu S. Y., (2009a). Research on the Fiber-optic Evanescent Field Sensor Based on Microfabrication and the Effect of Fiber Length on Its Properties, Acta Physica Sinca, Vol.58, No.4, (May 2009), pp 2501-2506, ISSN 1000-3290 www.intechopen.com 184 Fiber Optic Sensors Fiber Optic Sensors 184 Zhuang X. Y., (2009b), Study on the Art of Fiber-optic Evanescent Field Sensor with High Sensitivity, (July 2009), PhD paper of Chinese Academy of Sciences, Beijing, China. Zhuang X. Y., (2009b), Study on the Art of Fiber-optic Evanescent Field Sensor with High Sensitivity, (July 2009), PhD paper of Chinese Academy of Sciences, Beijing, China. www.intechopen.com www.intechopen.com www.intechopen.com Fiber Optic Sensors Edited by Dr Moh. Yasin Fiber Optic Sensors Edited by Dr Moh. Yasin Fiber Optic Sensors Edited by Dr Moh. Yasin ISBN 978-953-307-922-6 Hard cover, 518 pages Publisher InTech Published online 22, February, 2012 Published in print edition February, 2012 Published in print edition February, 2012 This book presents a comprehensive account of recent advances and researches in fiber optic sensor technology. It consists of 21 chapters encompassing the recent progress in the subject, basic principles of various sensor types, their applications in structural health monitoring and the measurement of various physical, chemical and biological parameters. It also highlights the development of fiber optic sensors, their applications by providing various new methods for sensing and systems, and describing recent developments in fiber Bragg grating, tapered optical fiber, polymer optical fiber, long period fiber grating, reflectometry and interefometry based sensors. Edited by three scientists with a wide knowledge of the field and the community, the book brings together leading academics and practitioners in a comprehensive and incisive treatment of the subject. This is an essential reference for researchers working and teaching in optical fiber sensor technology, and for industrial users who need to be aware of current developments and new areas in optical fiber sensor devices. How to reference In order to correctly reference this scholarly work, feel free to copy and paste the following: Xuye Zhuang, Pinghua Li and Jun Yao (2012). A Novel Approach to Evaluate the Sensitivities of the Optical Fiber Evanescent Field Sensors, Fiber Optic Sensors, Dr Moh. Yasin (Ed.), ISBN: 978-953-307-922-6, InTech, Available from: http://www.intechopen.com/books/fiber-optic-sensors/a-novel-approach-to-evaluate-the- sensitivities-of-the-optical-fiber-evanescent-field-sensors InTech China Unit 405, Office Block, Hotel Equatorial Shanghai No.65, Yan An Road (West), Shanghai, 200040, China Phone: +86-21-62489820 Fax: +86-21-62489821 InTech China Unit 405, Office Block, Hotel Equatorial Shanghai No.65, Yan An Road (West), Shanghai, 200040, China Phone: +86-21-62489820 Fax: +86-21-62489821 InTech Europe InTech Europe University Campus STeP Ri Slavka Krautzeka 83/A 51000 Rijeka, Croatia Phone: +385 (51) 770 447 Fax: +385 (51) 686 166 www.intechopen.com © 2012 The Author(s). Licensee IntechOpen. This is an open access artic stributed under the terms of the Creative Commons Attribution 3.0 cense, which permits unrestricted use, distribution, and reproduction in ny medium, provided the original work is properly cited. © 2012 The Author(s). Licensee IntechOpen. This is an open access article distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
https://openalex.org/W3094893511
https://www.redalyc.org/journal/3915/391562666036/391562666036.pdf
English
null
Video head impulse test (v-hit) em indivíduos com diabetes mellitus tipo 1
Audiology - Communication Research
2,020
cc-by
5,865
Sistema de Informação Científica Redalyc Rede de Revistas Científicas da América Latina e do Caribe, Espanha e Portugal Sem fins lucrativos acadêmica projeto, desenvolvido no âmbito da iniciativa acesso aberto igo do artigo redalyc.org Sistema de Informação Científica Redalyc Rede de Revistas Científicas da América Latina e do Caribe, Espanha e Portugal Sem fins lucrativos acadêmica projeto, desenvolvido no âmbito da iniciativa acesso aberto Como citar este artigo Número completo Mais informações do artigo Site da revista em redalyc.org RESUMO Purpose: To verify the function of the labyrinth semicircular channels of type 1 diabetes individuals submitted to the Video Head Impulse Test (v-HIT) and to compare them with individuals without diabetes. Methods: Cross-sectional, observational, analytical study conducted with a convenience sample of 35 diabetic and 100 non-diabetic individuals. All participants were submitted to vestibular evaluation using v-HIT. Results: The sample consisted of 135 participants divided into two groups. The study group was composed of individuals with type 1 diabetes, totaling 21 women and 14 men. The age range was between 18 and 71 years, with a mean of 35.37 years and standard deviation of 10.98. The group without diabetes was composed of 77 women and 23 men. The age range was between 20 to 83 years, with a mean of 46.44 and standard deviation of 19.82. The groups were matched for age (p=0.098) and gender (p=0.052). Diabetic patients showed decreased gain in the posterior and left anterior semicircular canals. Velocity showed a significant difference in the left lateral, anterior right and posterior left canals in the group with DM1, however velocity did not show correlation with the gain of the semicircular canals. Conclusion: participants with type 1 diabetes mellitus showed a decreased gain in the posterior semicircular canals and in the left anterior canal when compared to non-diabetic individuals. Objetivo: Verificar a função dos canais semicirculares do labirinto de indivíduos com diabetes tipo 1, submetidos ao Video Head Impulse Test (v-HIT), e compará-los com indivíduos sem diabetes. Métodos: Estudo transversal, observacional, analítico, realizado com uma amostra de conveniência, formada por 35 indivíduos diabéticos e 100 não diabéticos. Todos os participantes foram submetidos à avaliação vestibular por meio do v-HIT. Resultados: A casuística foi composta por 135 participantes, divididos em dois grupos. O grupo de estudo foi composto por indivíduos com diabetes tipo 1, totalizando 21 mulheres e 14 homens. A idade variou entre 18 e 71 anos, com média de 35,37 anos e desvio padrão de 10,98. O grupo sem diabetes foi composto por 77 mulheres e 23 homens. A idade variou entre 20 e 83 anos, com média de 46,44 e desvio padrão de 19,82. Os grupos foram pareados entre si, com relação à idade (p=0,098) e sexo (p=0,052). Os pacientes diabéticos apresentaram ganho diminuído nos canais semicirculares posteriores e anterior esquerdo. Audiology - Communication Research ISSN: 2317-6431 Audiology - Communication Research ISSN: 2317-6431 Ribeiro, Marlon Bruno Nunes; Morganti, Ligia Oliveira Gonçalves; Mancini, Patricia Cotta Video head impulse test (v-hit) em indivíduos com diabetes mellitus tipo 1 Audiology - Communication Research, vol. 25, e2284, 2020 Academia Brasileira de Audiologia Disponível em: http://www.redalyc.org/articulo.oa?id=391562666036 Como citar este artigo Número completo Mais informações do artigo Site da revista em redalyc.org ISSN 2317-6431 Original Article Original Article https://doi.org/10.1590/2317-6431-2019-2284 Video head impulse test (v-hit) em indivíduos com diabetes mellitus tipo 1 Video head impulse test (v-hit) em indivíduos com diabetes mellitus tipo 1 Marlon Bruno Nunes Ribeiro1 , Ligia Oliveira Gonçalves Morganti1 , Patricia Cotta Mancini1  Palavras-chave: Orelha interna; Canais semicirculares; Doenças do labirinto; Diabetes mellitus; Equilíbrio postural Study carried out at Programa de Pós-graduação em Ciências Fonoaudiológicas, Departamento de Fonoaudiologia, Faculdade de Medicina, Universidade Fed- eral de Minas Gerais – UFMG – Belo Horizonte (MG), Brasil. Study carried out at Programa de Pós-graduação em Ciências Fonoaudiológicas, Departamento de Fonoaudiologia, Faculdade de Medicina, Universidade Fed- l d Mi G i UFMG B l H i t (MG) B il METHOD The procedures for this investigation were approved by the Ethics Committee of the Federal University of Minas Gerais State (UFMG), under CAAE nº 56877316.1.0000.5149. The investigation was carried out at the Observatory of Functional Health in the Speech Therapy Department of the School of Medicine, Federal University of Minas Gerais State - UFMG - Minas Gerais (MG), Brazil. There are reports that carbohydrate metabolism disorders can affect the functioning of the vestibular apparatus(10,11). The most frequent vestibulopathies include benign paroxysmal positional vertigo (BPPV), endolymphatic hydrops and vestibulopathies of metabolic origin, which are responsible for 17.1% of labyrinth disorders(12,13). Several metabolic changes in carbohydrates can affect the functioning of the vestibular and auditory systems, most of them due to glucose metabolism disorders(13). The sample consisted of 135 participants answering a questionnaire, reporting no complaints of dizziness, divided into two groups. The study group was composed of individuals with DM1, totaling 21 women and 14 men. Age varied between 18 and 71 years, with a mean of 35.37 years and standard deviation of 10.98. The control group was composed of 77 women and 23 men without diabetes. Age ranged between 20 and 83 years, with a mean age of 46.44 and standard deviation of 19.82. The groups were matched for age (p=0.098) and gender (p=0.052). Glucose metabolism provides the energy necessary for the maintenance of the difference in endolymphatic and perilymphatic potential and the difference in neuronal transmembrane potential, which will allow peripheral information to reach the central nervous system and be properly processed(14). In the vestibular assessment of individuals with glucose metabolism disorder, electronystagmographic changes were found in 27.1% to 43.8% of the individuals(15). One study identified changes in the insulinemic curve in patients with vestibular disorders when compared to healthy volunteers, with a statistically significant difference(16). Other studies have demonstrated vestibular changes in asymptomatic diabetic individuals(10). These findings reveal the importance of performing a peripheral vestibular assessment in individuals with diabetes. g (p ) In the group without diabetes, individuals over 18 years of age who voluntarily agreed to participate in the investigation, who exhibited normal otoscopy, with no history of surgery or otological trauma, without previous self-reported vestibular diseases, with no cervical movement difficulties and who signed the Free and Informed Consent Form were included. In addition to the items mentioned above, participants with DM1, were submitted to auditory assessment (immittance and audiometry). METHOD The individuals in the group without diabetes were recruited in the academic community (students, professors and university staff) and the individuals with diabetes were recruited in the Endocrinology Clinic at Universidade Federal de Minas Gerais (UFMG), where the investigation took place. DM1 participants were being monitored for glycemic control and the duration of the disease ranged from seven months to 46 years, with a mean of 21.9 years and a standard deviation of 10.2. The semicircular canals (SC) detect angular movements of the head, through the vestibulo-ocular reflex (VOR), while the saccule and utricle detect the linear accelerations of the head, in addition to head-tilts in space(17-20). The VOR is responsible for maintaining a clear image on the retina during head movements, triggering compensatory eye movements in the opposite direction(20,21). Previous studies used the caloric test to assess the vestibular function of individuals with diabetes mellitus, but, currently, this analysis can be performed in an objective and detailed way, through the assessment of the vestibulo-ocular reflex using the Video Head Impulse Test (v -HIT)(22-25). The individuals were informed about the investigation objectives, the investigation risks and benefits, and those who voluntarily agreed to participate were then scheduled to come back on the day and time they would be available. Initially, each participant answered a questionnaire covering demographic information (age and gender) and data related to ear and vestibular history. Patients with DM1 answered a specific questionnaire, which contained, in addition to the demographic questions (age and gender), other questions related to otological and vestibular history, besides information about DM1. All the screening exams were performed by the same investigator. The v-HIT is a fast and objective exam, which evaluates the VOR in each semicircular canal, individually, and in physiological frequency of the angular acceleration of the head, by means of fast and short amplitude cephalic impulses. With each impulse, v-HIT records the head movements and the reflex response of the eye. Impulsive tests are fast in triggering VOR without cortical contamination or slow eye systems, assessing the vestibular function at higher frequencies than caloric testing(22-24). Several studies have highlighted the practicality and objectivity of v-HIT, which is able to accurately locate the affected semicircular canal, confirming the clinical usefulness of this exam in the diagnosis and monitoring of the individuals with otoneurological disorders rehabilitation(17-19,22-24). The demographic variables reviewed in this study were age and gender. RESUMO p v-HIT studies evaluating the vestibular function of individuals with DM1 are still scarce in the literature. There are studies in this population using only vectoelectronystagmography(10,15,16). p v-HIT studies evaluating the vestibular function of individuals with DM1 are still scarce in the literature. There are studies in this population using only vectoelectronystagmography(10,15,16). Given the above, the objective of this study was to evaluate the vestibular function of individuals with type 1 diabetes mellitus, using v-HIT, and to compare the results with those obtained in individuals without diabetes. Given the above, the objective of this study was to evaluate the vestibular function of individuals with type 1 diabetes mellitus, using v-HIT, and to compare the results with those obtained in individuals without diabetes. It is estimated that more than 30 thousand Brazilians are affected by DM1 and that Brazil occupies the third position in the prevalence of DM1 in the world, according to the IDF(6,7). Although the disease prevalence is increasing, DM1 corresponds to only 5% to 10% of all cases of DM. The disease is frequently diagnosed in children, adolescents and, in some cases, in young adults, affecting equally men and women(8,9). Audiol Commun Res. 2020;25:e2284 RESUMO A velocidade apresentou diferença significativa nos canais lateral esquerdo, anterior direito e posterior esquerdo no grupo com diabetes mellitus tipo 1, porém não apresentou correlação com o ganho dos canais semicirculares. Conclusão: Os participantes com diabetes mellitus tipo 1 apresentaram um ganho diminuído nos canais semicirculares posteriores e no canal anterior esquerdo quando comparados com indivíduos não diabéticos. Os grupos foram pareados entre si, com relação à idade (p=0,098) e sexo (p=0,052). Os pacientes diabéticos apresentaram ganho diminuído nos canais semicirculares posteriores e anterior esquerdo. A velocidade apresentou diferença significativa nos canais lateral esquerdo, anterior direito e posterior esquerdo no grupo com diabetes mellitus tipo 1, porém não apresentou correlação com o ganho dos canais semicirculares. Conclusão: Os participantes com diabetes mellitus tipo 1 apresentaram um ganho diminuído nos canais semicirculares posteriores e no canal anterior esquerdo quando comparados com indivíduos não diabéticos. Keywords: Inner ear; Semicircular canals; Labyrinth diseases; Diabetes mellitus; Postural balance Palavras-chave: Orelha interna; Canais semicirculares; Doenças do labirinto; Diabetes mellitus; Equilíbrio postural Study carried out at Programa de Pós-graduação em Ciências Fonoaudiológicas, Departamento de Fonoaudiologia, Faculdade de Medicina, Universidade Fed- eral de Minas Gerais – UFMG – Belo Horizonte (MG), Brasil. ( ) 1 Universidade Federal de Minas Gerais – UFMG – Belo Horizonte (MG), Brasil. Conflict of interests: No. Authors’ contribution: MBNR was responsible for conception and design of the study, data collection, analysis and interpretation of data, writing and revision of the manuscript; LOGM was responsible for exam collecting, scientific contribution from the exam experience, review of the article in an intellectually important way and final approval of the version to be published; PCM was responsible for research orientation, review of the article in an intellectually important way and approval of the final version of the article. Funding: None. Corresponding author: Marlon Bruno Nunes Ribeiro. E-mail: marlonfono16@gmail.com Received: July 03, 2019; Accepted: July 28, 2020 Audiol Commun Res. 2020;25:e2284 1 | 8 Ribeiro MBN, Morganti LOG, Mancini PC INTRODUCTION Furthermore, v-HIT is an exam that does not cause discomfort to the patient and does not need any prior preparation for its performance. Type 1 Diabetes Mellitus (DM1) is an autoimmune disease, characterized by the progressive loss of beta-pancreatic cells, which causes the interruption of insulin production and, consequently, a severe metabolic imbalance(1,2). The International Diabetes Federation (IDF) reveals that, every year, more than 70 thousand people develop DM1, in Brazil(3-5). METHOD The v-HIT results were assessed with respect to gain and the presence of corrective saccades. The velocity of the impulses applied was measured as a way to ensure the 2 | 8 v-HIT in individuals with type 1 diabetes mellitus proper execution of the movements. No other otoneurological exam was performed and all participants denied dizziness/ vertigo in their answers to the questionnaire. The data collected was entered in an Excel program worksheet and analyzed statistically, using the Statistical Package for the Social Sciences (SPSS), version 22.0. Initially, the analysis of the frequency of the variables age and gender, the measures of central tendency (mean and median), dispersion (standard deviation) and position (maximum and minimum) of the variables SC gain and cephalic impulses were performed. The normality of the variables age, gain and cephalic impulse velocity was observed using the Kolmogorov-Smirnov test. The comparison of age and gender variables between groups was performed using the Mann-Whitney and Chi-square tests, respectively. The comparison of the groups with and without diabetes was performed using the Mann-Whitney test, with a significance level of 5% (p <0.05) in all analyses. For the auditory assessment of the participants with DM1, meatoscopy and audiometry tests were performed in an acoustically treated room. For tympanometry, the Otoflex 100 Otometrics® equipment was used and the patient was instructed to remain seated, in silence, and a probe was then introduced in the external auditory canal of each ear to capture responses. The audiometry was performed using the Itera II Otometrics® equipment, with the patient sitting with his back to the device and the evaluator, in silence, with the Sennheiser HDA-200 headset, properly positioned. Hearing assessment was performed as a way to rule out hearing loss that could be associated to previous diseases of the inner ear(12). For the v-HIT, the Otometrics® ICS-impulse® equipment was used. The participants remained seated on a chair 120 cm from the target, positioned at eye level, with the goggle device’s straps tight adjusted to the head, in order to minimize possible goggle slips. After calibrating the eye position signal, the subject was instructed to stare at a target located on the wall, while the examiner performed cephalic impulses on the specific stimulation planes of the six SC. At least 20 impulses were obtained in each cephalic movement plane, with a maximum of 10 impulses rejected as inappropriate by the equipment›s software. RESULTS The gain values ​of the six SC can be seen in Table 1. The group with diabetes exhibited a lower gain in the posterior canals, as well as in the left anterior canal As an illustration, Figures 1 and 2 show images of v-HIT exams of two participants, the first being an individual without diabetes, with gain within normal standards (Figure 1) and the second, a participant with DM1, who showed a reduced gain of the posterior and right anterior SC (Figure 2). Corrective saccades were not observed in any of the groups. The velocity values applied in the tests are described in Table 2. In the group with diabetes, lower velocity was applied in the left lateral, right anterior and left posterior SC, in comparison with the group without diabetes. To assess the lateral canals, short and rapid movements to the right and left with the participant’s head were made at random. In the assessment of the vertical canals, the participant’s head was moved 45 ° to the right of the median plane of the head, placing the left anterior and right posterior canals (LARP) to the stimulation plane. In this position, a forward motion of the head activates the left anterior canal and a backward movement activates the right posterior canal. Then, the participant’s head was positioned at this same angle to the left, evaluating the synergistic pair of right anterior and left posterior SC (RALP). In this position, the head forward movement stimulates the right anterior canal and placing the head backwards the left posterior canal is stimulated. Cephalic impulses of unpredictable frequency and direction were generated, characterized by low amplitude (10-20°), high acceleration (1,000-2,500°/s2) and velocity (100-250°/s), according to the parameters suggested by the user equipment’s manual. Other studies have also used these cephalic impulses parameters, as a way to ensure a reliable examination(17-20). The total duration of the exam was approximately 15 minutes. A correlation analysis between the cephalic impulses velocity and the SC gain was performed and it was observed that, only in the right (R-0.357; p-0.001) and left (R-0.26; p-0.010) lateral canal, both in the group without diabetes, the higher the velocity of cephalic impulses, the lower the SC gain. In the group with diabetes, there was no significant correlation between the cephalic impulses velocity and the SC gain. Audiol Commun Res. 2020;25:e2284 RESULTS The association between gender and SC gain in both groups was also analyzed, and statistical significance was found only in the control group for the left anterior SC (p 0.04), with the greatest gain in males, and right posterior SC (p 0,02), with greater gain observed in females. In this study, the results obtained in each semicircular canal assessed were described, comparing these results between the control groups and those with DM1. We chose not to study the variable symmetry between sides. METHOD The v-HIT was repeated when there was hypofunction in any semicircular canal, in order to confirm the result obtained DISCUSSION The equipment features sensors that detect and record head and eyes movement. For each movement performed by the examiner (impulse), a sinusoid is generated on a chart, which results from the movement of the head and eyes. In normal individuals, the sinusoids are expected to be the same, which results in the so-called gain equal to 1. When the movement of the eyes is slower than the head movement, there is a gain below 1 and the compensatory movement of the eyes - corrective saccade - occurs to bring the eyes back on target. The exam was validated and presents specificity values ​of 93% and sensitivity of 74%. A gain greater than or equal to 0.8 for the lateral canals and 0.75 for the vertical canals is considered normal(23,24). The two groups studied were statistically matched with respect to age and gender, with the female gender being present in a greater proportion in both groups. The female gender, even being prevalent in both groups, showed only association with the right posterior canal in the group without diabetes. The group without diabetes showed values within the normal range of gain in all SC, as expected for individuals without vestibular disease(17-22). Most individuals with DM1 had their hearing within the normal range. There was an increase in the occurrence of hearing 3 | 8 Ribeiro MBN, Morganti LOG, Mancini PC Ribeiro MBN, Morganti LOG, Mancini PC Table 1. Analysis of the gain of semicircular canals between the two groups, with and without diabetes Gain Diabetes Absent Present p-value Left Lateral Average 0.96 0.97 Median 0.93 0.95 0.136 Minimum 0.64 0.72 Maximum 1.42 1.20 Standard Deviation 0.13 0.99 Right Lateral Average 1.04 1.05 Median 1.0 1.0 0.307 Minimum 0.76 0.57 Maximum 1.52 1.43 Standard Deviation 0.12 0.14 Left Anterior Average 0.95 0.85 Median 0.93 0.85 <0.001* Minimum 0.71 0.51 Maximum 1.59 1.18 Standard Deviation 0.14 0.14 Right Anterior Average 0.89 0.81 Median 0.89 0.83 0.054 Minimum 0.59 0.43 Maximum 1.34 1.16 Standard Deviation 0.15 0.20 Right Posterior Average 0.86 0.73 Median 0.87 0.73 <0.001* Minimum 0.41 0.42 Maximum 1.46 1.09 Standard Deviation 0.13 0.12 Left Posterior Average 0.85 0.71 Median 0.87 0.76 <0.001* Minimum 0.34 0.12 Maximum 1.31 1.04 Standard Deviation 0.16 0.21 Mann-Whitney Test *p<0.05 Figure 1. DISCUSSION Examination of participant without diabetes Subtitle: LARP = left anterior and right posterior; LA = left anterior; RP = right posterior; RALP = right anterior and left posterior; RA = right anterior; LP = left posterior Table 1. Analysis of the gain of semicircular canals between the two groups, with and without diabetes Gain Diabetes Absent Present p-value Left Lateral Average 0.96 0.97 Median 0.93 0.95 0.136 Minimum 0.64 0.72 Maximum 1.42 1.20 Standard Deviation 0.13 0.99 Right Lateral Average 1.04 1.05 Median 1.0 1.0 0.307 Minimum 0.76 0.57 Maximum 1.52 1.43 Standard Deviation 0.12 0.14 Left Anterior Average 0.95 0.85 Median 0.93 0.85 <0.001* Minimum 0.71 0.51 Maximum 1.59 1.18 Standard Deviation 0.14 0.14 Right Anterior Average 0.89 0.81 Median 0.89 0.83 0.054 Minimum 0.59 0.43 Maximum 1.34 1.16 Standard Deviation 0.15 0.20 Right Posterior Average 0.86 0.73 Median 0.87 0.73 <0.001* Minimum 0.41 0.42 Maximum 1.46 1.09 Standard Deviation 0.13 0.12 Left Posterior Average 0.85 0.71 Median 0.87 0.76 <0.001* Minimum 0.34 0.12 Maximum 1.31 1.04 Standard Deviation 0.16 0.21 Mann-Whitney Test *p<0.05 nalysis of the gain of semicircular canals between the two groups, with and without diabetes Mann-Whitney Test *p<0.05 Figure 1. Examination of participant without diabetes Subtitle: LARP = left anterior and right posterior; LA = left anterior; RP = right posterior; RALP = right anterior and left posterior; RA = right anterior; LP = left posteri Figure 1. Examination of participant without diabetes Subtitle: LARP = left anterior and right posterior; LA = left anterior; RP = right posterior; RALP = right anterior and left posterior; RA = right anterior; LP = left posterior Figure 1. Examination of participant without diabetes without diabetes osterior; LA = left anterior; RP = right posterior; RALP = right anterior and left posterior; RA = right anterior; LP = left posterior Figure 1. Examination of participant without diabetes Subtitle: LARP = left anterior and right posterior; LA = left anterior; RP = right posterior; RALP = right anterior and left posterior; RA = right anterior; LP = left posterior g p p Subtitle: LARP = left anterior and right posterior; LA = left anterior; RP = right posterior; RALP = right anterior and left poste g p p Subtitle: LARP = left anterior and right posterior; LA = left anterior; RP = right posterior; RALP = right anterior and left p Audiol Commun Res. DISCUSSION 2020;25:e2284 4 | 8 v-HIT in individuals with type 1 diabetes mellitus v-HIT in individuals with type 1 diabetes mellitus Figure 2. Examination of participants with type 1 diabetes mellitus Subtitle: LARP = left anterior and right posterior; LA = left anterior; RP = right posterior; RALP = right anterior and left posterior; RA = right anterior; LP = left posterior Figure 2. Examination of participants with type 1 diabetes mellitus Subtitle: LARP = left anterior and right posterior; LA = left anterior; RP = right posterior; RALP = right anterior and left posterior; RA = right anterior; LP = left posterior Table 2. Exam velocity in both groups, with and without diabetes Velocity (100-250º/s) Diabetes p-value Absent Present Left Lateral Average 178 161 Median 180 160 <0.001* Minimum 120 130 Maximum 240 200 Standard Deviation 23.7 15.5 Right Lateral Average 168 158 Median 160 160 0.054 Minimum 120 130 Maximum 240 200 Standard Deviation 23.4 13.9 Left Anterior Average 122 124 Median 120 120 0.416 Minimum 100 110 Maximum 180 140 Standard Deviation 10.6 9.7 Right Anterior Average 124 118 Median 120 120 <0.001* Minimum 110 110 Maximum 160 140 Standard Deviation 10.1 9.0 Right Posterior Average 127 127 Median 120 130 0.715 Minimum 110 110 Maximum 180 150 Standard Deviation 12.9 10.5 Left Posterior Average 129 120 Median 130 120 <0.001* Minimum 110 110 Maximum 160 160 Standard Deviation 12.7 12.6 Mann-Whitney test *p<0.05 Table 2. Exam velocity in both groups, with and without diabetes Table 2. Exam velocity in both groups, with and without diabetes Audiol Commun Res. 2020;25:e2284 5 | 8 Ribeiro MBN, Morganti LOG, Mancini PC potentials, which may cause dizziness(10,13,29,30). Glucose metabolism provides the energy required for maintaining the difference in endolymphatic and perilymphatic potential, and the difference in neuronal transmembrane potential, which will allow peripheral information to reach the central nervous system and be properly processed(10,13,29,30). thresholds changes in these individuals, when considering only high frequencies thresholds. Out of 35 diabetic individuals, only three (8%) had mild and moderate sensorineural hearing loss. Six (16%) participants showed changes in hearing thresholds at frequencies of 6 and 8 KHz, that is, only at high frequencies. All participants with DM1 exhibited type A tympanometry(25). DISCUSSION The group composed of individuals with DM1 also showed values ​​within the normal range of gain for almost all SC, except for the right posterior canal, which average gain was less than the reference value (0.73). However, it showed statistically smaller gains, when compared to the group without diabetes, also in the right and left posterior canals, as well as in the left anterior canal. Participants with DM1 had no complaints of dizziness according to the answers to the questionnaires applied. Another study also found otoneurological changes in individuals with asymptomatic DM1, using the caloric test(10). Although in the group with DM1, lower velocities have been applied for stimulation of the left lateral, right anterior and left posterior SC, in comparison with the control group, for all SC, in both groups, adequate velocity was applied, as recommended in the literature and in the equipment manual for reliable examination - above 120°/s for the lateral canals and 100°/s for the vertical canals(21-24). In addition, for these SC, there was no statistical correlation between the velocity and the value of the VOR gain. The right posterior canal was the only one that showed a gain below the normal range in the group with diabetes. However, no corrective saccades were observed, although expected when a reduction in the vestibulo-ocular reflex gain occurs(20-23). The exams that showed vestibular hypofunction were repeated to confirm the findings. The absence of corrective saccades, in the presence of an altered gain, considering the technique of proper execution of the exam, may correspond to central neurological involvement(20). Further studies are required to assess the potential correlation of this finding in patients with DM1. g Studies on the vestibular function of individuals with DM1 with the use of v-HIT are scarce in the literature. Only one study was found that was carried out with a pediatric population and no statistical difference was found(26). In the other studies, the vestibular assessment was carried out using oculomotor tests and caloric test in this population. A study that evaluated 29 individuals showed alterations in the caloric test in 36.8% (n=7) of the sample, 21.1% (n=4) with altered labyrinth predominance, two to the right and two to the left, and 15.8% (n=3) with altered directional preponderance of nystagmus, one to the right and two to the left(10). DISCUSSION In the group of patients with DM1, 14.3% (n=1) had no complaints, 14.3% (n=1) complained of dizziness due to other causes and 71.4% (n=5) complained about dizziness in specific episodes of hypoglycemia. The results showed that five of these individuals with DM1 (26.3%) exhibited alterations in the vectoelectronystagmography, among who three individuals (15.8%) with deficient peripheral vestibular syndrome and the other two (10.5%) exhibited irritative peripheral vestibular syndrome(10). In view of the results found in this study, it is suggested that greater attention be paid to the vestibular system of individuals with DM1, through otoneurological investigation, since individuals with DM1, without dizziness complaints, may exhibit hypofunction in the SC. The dizziness symptom may appear later, with harmful effects on the quality of life. Thus, we emphasize the importance of detecting vestibular hypofunction early in this population and monitor it, in order to avoid worsening the pathology. This study was limited by the sample size of individuals with DM1, indicating the importance of carrying out studies with a larger number of individuals, so that the data can be confirmed or compared. A study carried out with a sample of 46 patients with DM1 found alterations in the caloric test of electronystagmography in 26.0% (n = 12) of the patients, 4.3% (n = 2) with a predominance of right labyrinth and 21.6% (n = 10) with altered directional preponderance, six to the right and four to the left(27). Sherer & Lobo (2002) found, in a sample of 12 individuals with DM1, that 50.0% (n = 6) exhibited directional preponderance of altered nystagmus and the other 16.7% (n = 2), altered labyrinthine predominance, without specification as to which side(28).i The v-HIT is a fast, useful, non-invasive exam, which does not require preparation or fasting before the exam and allows a detailed assessment of the SC, proving to be a desirable exam for assessing the vestibular function of individuals with DM1. Its usefulness in clinical practice has been increasingly consolidated by studies, due to its practicality and objectivity in diagnosing vestibular disorders(22-24,26). These findings can be explained by the fact that glucose metabolism has a great influence on the inner ear, both in hypoglycemia and in hyperglycemia, which can cause auditory, vestibular or mixed symptoms. It is known that labyrinthine structures, especially the stria vascularis, have intense metabolic activity and depend on the constant supply of oxygen, glucose and adenosine triphosphate (ATP)(29). REFERENCES 17. Janky KL, Patterson J, Shepard N, Thomas M, Barin K, Creutz T, et al. Video Head Impulse Test (vHIT): the role of corrective saccades in identifying patients with vestibular loss. Otol Neurotol. 2018;39(4):467-73. http://dx.doi.org/10.1097/MAO.0000000000001751. PMid:29533335. 1. Mattosinho MMS, Silva DMGV. Itinerário terapêutico do adolescente com diabetes mellitus tipo 1 e seus familiares. Rev Latino-am Enfermagem. 2007 Nov-Dez;15(6):1113-9. 2. Silink M. Childhood diabetes: a global perspective. Horm Res. 2002;57(Supl 1):1-5. PMid:11979014. 18. Sabour S. Diagnostic value of video head impulse test in vestibular neuritis: methodological issues. Otolaryngol Head Neck Surg. 2018;159(2):400-400. http://dx.doi.org/10.1177/0194599818779792. PMid:30066617. 3. Fernandes AP, Pace AE, Zanetti ML, Foss MC, Donadi EA. Fatores imunogenéticos associados ao diabetes mellitus do tipo 1. Rev Lat Am Enfermagem. 2005;13(5):743-9. http://dx.doi.org/10.1590/S0104- 11692005000500020. PMid:16308633. 19. Hougaard DD, Abrahamsen ER. Functional testing of all six semicircular canals with video head impulse test systems. J Vis Exp. 2019;146. http://dx.doi.org/10.3791/59012. PMid:31058885. 4. Knip M, Veijola R, Virtanen SM, Hyöty H, Vaarala O, Åkerblom HK. Environmental triggers and determinants of type 1 diabetes. Diabetes. 2005;54(Supl 2):S125-36. http://dx.doi.org/10.2337/diabetes.54. suppl_2.S125. PMid:16306330. 20. Chen L, Halmagyi GM. Central lesions with selective semicircular canal involvement mimicking bilateral vestibulopathy. Front Neurol. 2018;9:264. http://dx.doi.org/10.3389/fneur.2018.00264. PMid:29740388. 5. Negrato CA, Dias JP, Teixeira MF, Dias A, Salgado MH, Lauris JR, et al. Temporal trends in incidence of type 1 diabetes between 1986 and 2006 in Brazil. J Endocrinol Invest. 2010 Jun;33(6):373-7. http://dx.doi.org/10.1007/BF03346606. PMid:19620822. 21. Alhabib SF, Saliba I. Video head impulse test: a review of the literature. Eur Arch Otorhinolaryngol. 2017;274(3):1215-22. http://dx.doi. org/10.1007/s00405-016-4157-4. PMid:27328962. 22. Ribeiro MBN, Morganti LOG, Mancini PC. Avaliação do efeito da idade sobre a função vestibular por meio do Teste de Impulso Cefálico (v-HIT). Audiol Commun Res. 2019;24:e2209. http://dx.doi. org/10.1590/2317-6431-2019-2209. 6. WHO: World Health Organization. Global report on diabetes [Internet]. Geneva: WHO; 2016 [citado em 2017 Jun 27]. Disponível em: http:// apps.who.int/iris/bitstream/10665/204871/1/9789241565257_eng.pdf 7. Skyler JS, Bakris GL, Bonifacio E, Darsow T, Eckel RH, Groop L, et al. Differentiation of diabetes by pathophysiology, natural history, and prognosis. Diabetes. 2017;66(2):241-55. http://dx.doi.org/10.2337/ db16-0806. PMid:27980006. 23. MacDougall HG, Weber KP, McGarvie LA, Halmagyi GM, Curthoys IS. The video head impulse test: diagnostic accuracy in peripheral vestibulopathy. Neurology. 2009;73(14):1134-41. http://dx.doi. org/10.1212/WNL.0b013e3181bacf85. PMid:19805730. 8. Chiang JL, Kirkman MS, Lael LM, Peters AL. Standards of medical care in diabetes. Diabetes Care. 2017;40(Supl 1):1-131. 24. Tae Hwan K. Min‐BeomHwa K. Effect of aging and direction of impulse in video head impulse test. Laryngoscope. 2018;128:228-33. 9. DISCUSSION Glucose is a fundamental substance for the production of ATP inside the cells and for providing energy for the functioning of the endolymph sodium and potassium pump(28,29). Thus, glucose metabolism disorders alter the ions in the endolymph and perilymph, causing a change in the labyrinthine electrical In some individuals, especially the elderly with eyelid ptosis, there was difficulty in capturing the pupil clearly, through the equipment camera. Thus, to raise the upper eyelid, an adhesive tape was placed across the participant’s eyebrow. Proper pupil capture and precise cephalic movements are essential to properly stimulate SC(17-19,22,26). It is important to note that, although v-HIT is a practical and objective test to evaluate each semicircular canal at physiological frequencies, the tests are complementary tools for vestibular assessment and no single test is able to fully assess all structures of the vestibular system. 6 | 8 Audiol Commun Res. 2020;25:e2284 Audiol Commun Res. 2020;25:e2284 v-HIT in individuals with type 1 diabetes mellitus CONCLUSION Quadros clínicos otoneurológicos mais comuns. 1. ed. São Paulo: Atheneu; 2000. p. 37-45. 12. Kurtaran H, Acar B, Ocak E, Mirici E. The relationship between senile hearing loss and vestibular activity. Rev Bras Otorrinolaringol. 2016;82(6):650-3. http://dx.doi.org/10.1016/j.bjorl.2015.11.016. PMid:26997575. The DM1 group showed less gain in the vestibulo- ocular reflex in the posterior canals and in the left anterior canal, when compared to individuals in the group without diabetes. Corrective saccades were not observed in any of the groups. 13. Murbach VF, Caovilla HH, Munhoz MSL, Ganança MM, Guerrero AI. Distortion product otoacoutic emissions amplitude variations during glucose tolerance test and insulin titration. Acta ORL. 2003;22(4):32- 42. ACKNOWLEDGEMENTS 14. Kaźmierczak H, Doroszewska G. Metabolic disorders in vertigo, tinnitus, and hearing loss. Int Tinnitus J. 2001;7(1):54-8. PMid:14964957. To Professor Milena Guimarães of the Endocrinology Outpatient Clinic of Federal University of Minas Gerais State (UFMG), for the support of this investigation, and to all participants who contributed to the materialization of this study. 15. Charles DA, Barber HO, Hope-Gill HF. Blood glucose and Insulin Levels, thyroid function, and serology in Ménière’s disease, recurrent vestobulopathy, and psychogenic vertigo. J Otolaryngol. 1979;8(4):347- 53. PMid:316014. 16. Kirtane MV, Medikeri SB, Rao P. Blood levels glucose and insulin in Meniere’s disease. Acta Otolaryngol Suppl. 1984;406:42-5. PMid:6382920. 8 | 8 REFERENCES Insel RA, Dunne JL, Atkinson MA, Chiang JL, Dabelea D, Gottlieb PA, et al. Staging presymptomatic type 1 diabetes: a scientific statement of JDRF, the Endocrine Society, and the American Diabetes Association. Diabetes Care. 2015 Out;38(10):1964-74. http://dx.doi.org/10.2337/ dc15-1419. PMid:26404926. 25. Jerger J. Clinical experience with impedance audiometry. Arch Otolaryngol. 1970;92(4):311-24. http://dx.doi.org/10.1001/ archotol.1970.04310040005002. PMid:5455571. 26. Mohammad JM, Robabeh S, Shahin K, Saeed T, Maryam A. Auditory function and motor proficiency in type 1 diabetic children: a case- control study. Int J Pediatr Otorhinolaryngol. 2018;109:7-12. http:// dx.doi.org/10.1016/j.ijporl.2018.03.017. PMid:29728188. 10. Rigon R, Rossi AG, Cóser PL. Achados otoneurológicos em indivíduos portadores de diabetes mellitus tipo 1. Rev Bras Otorrinolaringol. 2007;73(1):106-11. http://dx.doi.org/10.1590/S0034-72992007000100017. 27. Biurrun O, Ferrer JP, Lorente J, De Espana R, Gomis R, Traserra J. Asymptomatic electronystagmographic abnormalities in patients 11. Silva MLG, Munhoz MSL, Ganança MM, Caovilla HH, Ganança CF. In: Silva MLG, Munhoz MSL, Ganança MM, Caovilla HH, editores. Audiol Commun Res. 2020;25:e2284 7 | 8 Ribeiro MBN, Morganti LOG, Mancini PC with type I diabetes mellitus. ORL J Otorhinolaryngol Relat Spec. 1991;53(6):335-8. http://dx.doi.org/10.1159/000276242. PMid:1784472. 29. Serra AP, Lopes KC, Dorigueto RS, Ganança FF. Avaliação da curva glicoinsulinêmica nos pacientes com vestibulopatia periférica. Rev Bras Otorrinolaringol. 2009;75(5):701-5. 28. Scherer LP, Lobo MB. Pesquisa do nistagmo/vertigem de posição e avaliação eletronistagmográfica em um grupo de indivíduos portadores de diabetes mellitus tipo I. Rev Bras Otorrinolaringol. 2002;68(3):355- 60. http://dx.doi.org/10.1590/S0034-72992002000300010. 30. Mangabeira Albernaz PL, Fukuda Y. Glucose, insulin and inner ear pathology. Acta Otolaryngol. 1984;97(5-6):496-501. http://dx.doi. org/10.3109/00016488409132927. PMid:6380207. Audiol Commun Res. 2020;25:e2284
https://openalex.org/W4386994104
https://link.springer.com/content/pdf/10.1007/s10773-023-05440-7.pdf
English
null
Eikonal Quasinormal Modes, Photon Sphere and Shadow of a Charged Black Hole in the 4D Einstein-Gauss-Bonnet Gravity
International journal of theoretical physics
2,023
cc-by
14,570
International Journal of Theoretical Physics (2023) 62:209 https://doi.org/10.1007/s10773-023-05440-7 International Journal of Theoretical Physics (2023) 62:209 https://doi.org/10.1007/s10773-023-05440-7 RESEARCH RESEARCH 1 Universidad Nacional de Colombia. Sede Bogotá. Facultad de Ciencias. Observatorio Astronómico Nacional, Ciudad Universitaria, Bogotá, Colombia Eikonal Quasinormal Modes, Photon Sphere and Shadow of a Charged Black Hole in the 4D Einstein-Gauss-Bonnet Gravity Jose Miguel Ladino1 · Eduard Larrañaga1 Received: 25 May 2023 / Accepted: 2 August 2023 / Published online: 25 September 2023 © The Author(s) 2023 Received: 25 May 2023 / Accepted: 2 August 2023 / Published online: 25 September 2023 © The Author(s) 2023 Eduard Larrañaga ealarranaga@unal.edu.co B Jose Miguel Ladino jmladinom@unal.edu.co Keywords Quasinormal modes · Einstein-gauss-bonnet gravity · Black hole shadow · Photon sphere Abstract In this work, we investigate the relationship between the geometrical properties, the photon sphere, the shadow, and the eikonal quasinormal modes of electrically charged black holes in 4D Einstein-Gauss-Bonnet gravity. Quasinormal modes are complex frequency oscillations that are dependent on the geometry of spacetime and have significant applications in studying black hole properties and testing alternative theories of gravity. Here, we focus on the eikonal limit for high frequency quasinormal modes and their connection to the black holes geometric characteristics. To study the photon sphere, quasinormal modes, and black hole shadow, we employ various techniques such as the Wentzel-Kramers-Brillouin method in various orders of approximation, the Poschl-Teller potential method, and Churilova’s analytical formulas. Our results indicate that the real part of the eikonal quasinormal mode frequencies of test fields are linked to the unstable circular null geodesic and are correlated with the shadow radius for a charged black hole in 4D Einstein-Gauss-Bonnet gravity. Furthermore, we found that the real part of quasinormal modes, the photon sphere and shadow radius have a lower value for charged black holes in 4D Einstein-Gauss-Bonnet gravity compared to black holes without electric charge and those of static black holes in general relativity. Additionally, we explore various analytical formulas for the photon spheres and shadows, and deduce an approximate formula for the shadow radius of charged black holes in 4D Einstein-Gauss-Bonnet gravity, based on Churilova’s method and its connection with the eikonal quasinormal modes. In this work, we investigate the relationship between the geometrical properties, the photon sphere, the shadow, and the eikonal quasinormal modes of electrically charged black holes in 4D Einstein-Gauss-Bonnet gravity. Quasinormal modes are complex frequency oscillations that are dependent on the geometry of spacetime and have significant applications in studying black hole properties and testing alternative theories of gravity. Here, we focus on the eikonal limit for high frequency quasinormal modes and their connection to the black holes geometric characteristics. To study the photon sphere, quasinormal modes, and black hole shadow, we employ various techniques such as the Wentzel-Kramers-Brillouin method in various orders of approximation, the Poschl-Teller potential method, and Churilova’s analytical formulas. Our results indicate that the real part of the eikonal quasinormal mode frequencies of test fields are linked to the unstable circular null geodesic and are correlated with the shadow radius for a charged black hole in 4D Einstein-Gauss-Bonnet gravity. B Jose Miguel Ladino jmladinom@unal.edu.co Eduard Larrañaga ealarranaga@unal.edu.co B Jose Miguel Ladino jmladinom@unal.edu.co Eduard Larrañaga ealarranaga@unal.edu.co 1 Universidad Nacional de Colombia. Sede Bogotá. Facultad de Ciencias. Observatorio Astronómico Nacional, Ciudad Universitaria, Bogotá, Colombia Abstract Furthermore, we found that the real part of quasinormal modes, the photon sphere and shadow radius have a lower value for charged black holes in 4D Einstein-Gauss-Bonnet gravity compared to black holes without electric charge and those of static black holes in general relativity. Additionally, we explore various analytical formulas for the photon spheres and shadows, and deduce an approximate formula for the shadow radius of charged black holes in 4D Einstein-Gauss-Bonnet gravity, based on Churilova’s method and its connection with the eikonal quasinormal modes. Keywords Quasinormal modes · Einstein-gauss-bonnet gravity · Black hole shadow · Photon sphere 123 123 123 209 Page 2 of 26 International Journal of Theoretical Physics (2023) 62:209 1 Introduction Modified gravity theories have gained attention as a potential solution to various unresolved astrophysical mysteries, including the nature of dark matter, the formation of supermassive Black Holes (BHs), the evolution of galaxies, and the behavior of large-scale structures in the universe, as well as the acceleration of its expansion. One of these theories is known as the Einstein-Gauss-Bonnet (EGB) gravity, which introduces the Gauss-Bonnet invariant as an additional term to the Lagrangian. This theory of gravity can be interpreted as an exten- sion of GR with quadratic curvature corrections, yielding interesting implications for BHs, cosmology, and weak-field gravity [1]. Particularly, the BH solutions in EGB gravity have been derived from various modified gravity theories using different approaches. The initial BH solution in EGB theory was found by Boulware and Deser in 1985 [2] for dimensions D ≥5, as the GB term does not affect the gravitational dynamics in D = 4. However, later studies, such as those by Tomozawa in 2011 [3] and Cognola et al. in 2013 [4], discovered that the GB term could have a non-trivial contribution to spacetime when D = 4 through reg- ularization and dimensional reduction techniques. According to Lovelock’s theorem, EGB gravity is only introduced in D ≥5, as the GB term does not contribute dynamically in lower dimensions [5]. This led Glavan and Lin in 2020 [6] to propose a rescaling of the coupling constant to obtain a contribution to gravitational dynamics in D = 4. From this moment, this BH solution in 4D EGB gravity has been studied intensively and is considerably a subject of ongoing research. For example, this BH solution in 4D EGB theory was explored subse- quently in 2020 [7] by Fernandes, who studied its coupling with both BH electric charge and anti-de Sitter space. Despite the fact that the solution proposed by BH in [6] was obtained in a simple way, the model used there was strongly criticized. Several later studies have shown that the method used to find the solution was neither consistent nor well-defined [1, 8–10]. However, several subsequent studies have obtained this same solution and clarified that it was not really new. This and other very similar solutions can be deduced from different well-defined approaches and modified gravity theories [1, 11–17]. On the other hand, remarkable progress in observational astronomy has been achieved in recent years, particularly in the study of BHs. 1 Introduction For instance, the real part of the QNM fre- quency is a monotonically increasing function of the spin of the BH, whereas the imaginary part of the QNM frequency is a monotonically decreasing function of the spin. [20]. There- fore, exploring eikonal QNMs is a valuable approach to studying BHs and their geometrical properties. geodesics of the BH. This relationship is helpful in understanding the connection between QNMs and the geometric properties of the BH. For instance, the real part of the QNM fre- quency is a monotonically increasing function of the spin of the BH, whereas the imaginary part of the QNM frequency is a monotonically decreasing function of the spin. [20]. There- fore, exploring eikonal QNMs is a valuable approach to studying BHs and their geometrical properties. Another very interesting feature of BHs is their shadow, a dark region in their vicinity caused by the bending of light due to the BHs gravity. The exact shape and size of a BHs shadow also depend on the geometrical properties of the BH, as well as the properties of the environment surrounding it, such as the distribution of matter and the presence of other objects. For example, the presence of dark matter can affect the QNMs frequencies and the shadow radius of a BH [21, 22]. The eikonal limit establishes a correlation between these two quantities, indicating that the influence of dark matter on QNMs and the shadow radius is more pronounced for rotating BHs than non-rotating ones [21]. The study of eikonal QNMs in BH solutions of GR and their connection with the photon sphere has been extensively explored in previous research [23]. These studies have also been extended to alternative theories of gravitation, such as Scalar Gauss-Bonnet grav- ity [24], Einstein-dilaton-Gauss-Bonnet BHs [25], dynamical Chern-Simons gravity [26], Rotating Loop Quantum BHs [27], string-corrected D-dimensional BHs [28], and deformed Schwarzschild BHs [29], among others. Additionally, the QNMs of BHs in 4D EGB grav- ity are a topic of ongoing research. Some investigations have focused on the shadows and photon spheres with spherical accretions, the correlation between the shadow of a BH and its eikonal QNMs, as well as the effect of the Gauss-Bonnet (GB) coupling constant α on these properties [30–36]. Moreover, recent research has been conducted on extended and more complex versions of this 4D EGB BH type solution. 1 Introduction One of the most intriguing properties of BHs is their Quasinormal Modes (QNMs), which can be detected by gravitational interfer- ometers. These QNMs are a distinguishing characteristic of BHs that describe their damped oscillations over the spacetime in response to external perturbations [18]. These modes are fundamental to understanding the behavior of BHs and play a crucial role in verifying the theoretical predictions of gravitational wave physics through experimental measurements. On the other hand, remarkable progress in observational astronomy has been achieved in recent years, particularly in the study of BHs. One of the most intriguing properties of BHs is their Quasinormal Modes (QNMs), which can be detected by gravitational interfer- ometers. These QNMs are a distinguishing characteristic of BHs that describe their damped oscillations over the spacetime in response to external perturbations [18]. These modes are fundamental to understanding the behavior of BHs and play a crucial role in verifying the theoretical predictions of gravitational wave physics through experimental measurements. The frequencies of these QNMs of BHs are complex numbers, with the real part correspond- ing to the frequency of the oscillation and the imaginary part corresponding to the rate at which the amplitude of the oscillation decays. QNMs have several important applications in the research of BHs, such as studying their surface gravity and horizon area, stability, the detection of gravitational waves, and their geometrical properties, such as their mass, spin, and electric charge. There are various techniques used to compute and calculate QNMs, including the Wentzel-Kramers-Brillouin (WKB) method, the continued fraction method, the time-domain integration method and much more. In Fact, the knowledge about QNMs could also have potential implications in other fields such as astrophysics, cosmology, and high-energy physics, like testing General Relativiy (GR) and alternative theories of gravity [19]. Eikonal QNMs are a specific type of oscillations that are particularly useful for studying high-frequency QNMs and their applications. These oscillations occur in the eikonal limit, in which the real part of the QNM frequency is directly related to the unstable circular null 123 123 International Journal of Theoretical Physics (2023) 62 :209 209 Page 3 of 26 geodesics of the BH. This relationship is helpful in understanding the connection between QNMs and the geometric properties of the BH. 1 Introduction In this work, we will extend the findings of this study by utilizing additional 123 209 Page 4 of 26 Page 4 of 26 209 International Journal of Theoretical Physics (2023) 62:209 approaches, such as the Poschl-Teller potential and Churilova’s methods, to investigate sev- eral properties that emerge the relationship between the BH shadow, and the eikonal QNMs of scalar and electromagnetic field perturbations for a charged BH in 4D EGB gravity. There- fore, We will show several new analytical formulas for the radius of the photon sphere and the BH shadow, which can be very useful because of its short form and which result from the relationship of these quantities with the eikonal QNMs. approaches, such as the Poschl-Teller potential and Churilova’s methods, to investigate sev- eral properties that emerge the relationship between the BH shadow, and the eikonal QNMs of scalar and electromagnetic field perturbations for a charged BH in 4D EGB gravity. There- fore, We will show several new analytical formulas for the radius of the photon sphere and the BH shadow, which can be very useful because of its short form and which result from the relationship of these quantities with the eikonal QNMs. This paper is organized as follows: In Section 2, we present the electrically charged BH in 4D EGB gravity, briefly introducing the BH metric background, their horizons, and particular limit cases. In Section 3, we show the theory behind the QNMs of scalar and electromagnetic field perturbations, providing the corresponding master wave equations and discussing some of the principal semi-analytical methods to calculate the QNM frequencies, such as the WKB approximation approach and the Poschl-Teller potential method. Then, in Section 4, we discuss some eikonal QNMs approaches, including a recently proposed analytical formulation that approximates the frequencies at this limit. Later, we analyze and apply these methods on the eikonal QNMs of a charged BH in 4D EGB gravity, looking at the effect of the geometric parameters of the BH on these. Afterwards, in Section 5, we study the photon sphere of a charged BH in 4D EGB gravity and its particular limit cases, illustrating the correspondence between eikonal QNMs and null geodesics, and revealing the effect of the geometric parameters of the BH on this. 1 Introduction Thereafter, in Section 6, we investigate the shadow of a charged BH in 4D EGB gravity and its connection with their eikonal QNMs frequencies, sharing an analytic and approximate formula for the shadow and comparing it with all the results given by other methods and again, the effect of the geometric parameters of the BH in their shadow. Finally, in Section 7, we summarize some conclusions. 1 Introduction Investigations have included the study of eikonal QNMs and greybody factors in asymptotically de Sitter spacetime [37], the investigations on the QNMs and the shadow of a BH with confining electric potential in scalar-tensor description of 4D EGB gravity [38], the effects of the magnetic charge on weak deflection angle and greybody bound of 4D EGB BHs [39], the analysis of the shadow of rotating BHs in 4D EGB gravity [40], the study of null geodesics and shadow of 4D EGB BHs surrounded by quintessence [41], the examination of entropy, energy emission, QNMs, and deflection angle of 4D EGB BHs with nonlinear electrodynamics [42], and the inves- tigation of QNMs of a 4D EGB BH in anti-de Sitter space [43]. Similarly, several studies have been conducted on electrically charged BHs in 4D EGB gravity, each focusing on dif- ferent aspects of their behavior. For instance, gravitational lensing is studied in [44], particle motion and plasma behavior are examined in [45], superradiance and stability of the solution are discussed in [46], and the connection between phase transition and QNMs is explored in [47]. Recent research has focused on the properties of rotating charged BHs in 4D EGB gravity, including the examination of photon motion and shadow [48]. Additionally, studies have been conducted on the characteristics of charged BHs in 4D EGB gravity coupled with anti-de Sitter space, such as their shadow, energy emission, deflection angle, and heat engine properties [49]. Furthermore, investigations have been carried out on the instability, quasinor- mal modes, and strong cosmic censorship of charged BHs in 4D EGB gravity coupled with de Sitter space under charged scalar and electromagnetic perturbations [50, 51]. Notably, by merging the findings from previous investigations, a more comprehensive understanding of these variations in modified theories of gravity can be achieved. A recent work in [52] explored the correspondence between the shadow and the QNMs of the scalar field around a charged BH in 4D EGB gravity, using the 6th order of the WKB method. 2.1 The Spacetime Background ThegravitationaltheoryofEGBinD-dimensionalspacetimecoupledwithanelectromagnetic source is described by the action [52] S = 1 16πG  dx D√−g  R −Fμν Fμν + α  R2 −4Rμν Rμν + Rμνβγ Rμνβγ  , (1) (1) where R is the scalar curvature, which corresponds to the well known Einstein-Hilbert con- tribution, Rμν and Rμνβγ are the Ricci and Riemann tensors respectively, α is known as the GB coupling constant and Fμν is the electromagnetic tensor given by Fμν = ∂μ Aν −∂ν Aμ, (2) (2) with Aμ being the quadripotential. α has dimensions of [length2] and some authors take it between −8M2 < α < M2 [30]. Nevertheless, it is usual to consider the simple constrain α > 0 [17], since it has been shown that for α < 0 the BH solution might not be valid for small distances [40]. In this work, we will use the assumption α > 0. EGB gravity describes quadratic corrections to the curvature tensors from Lovelock’s gravitational theory, but is also obtained in the low-energy limit of string theory, in which α can be interpreted as the inverse stress of the string and is defined only with positive values [40]. Actually, the BH solution in EGB theory has already been deduced from various modified gravity theories. It was initially obtained in 1985 by Boulware and Deser in [2] for the cases where D ≥5, since the GB term does not contribute to the gravitational dynamics 123 International Journal of Theoretical Physics (2023) 62 :209 209 Page 5 of 26 when D = 4. Then, Tomozawa in 2011 [3], through a regularization procedure, found that there could be, from a quantum perspective, a non-trivial contribution of the GB term to space-time in the case where D = 4 . Later in 2013, Cognola et al. [4], through another process of regularization to EGB gravity, managed to perform a dimensional reduction under the Lagrangian formulation, finding again the BH type solution for the case in which D = 4. According to Lovelock’s theorem, the gravity of EGB is only introduced in cases where D > 4 because, for smaller dimensions, the term with the GB coupling would not contribute dynamically [5]. In 2020, Glavan and Lin [6] used this formalism to obain the same BH solution in 4D EGB gravity by simply proposing a rescaling of α. However, several studies have shown that this previous proposal is problematic. 2.1 The Spacetime Background This is easily suspected by the fact that the lagrangian action diverges and is not well-defined in the 4-dimensional limit, disregarding Lovelock’s theorem [1, 8–10]. Consequently, it has been clarified that the BH solutions of 4D EGB can be obtained from different approaches and theories of modified gravity that are well-defined. Therefore, it is not an entirely novel solution. To obtain coherent versions of the theory of BH solutions in 4D EGB gravity, alternative regularization processes have been applied. These include scalar-tensor theories from conformal regularizations [14, 15], the Kaluza-Klein regularized reduction [13], and other formalisms related to theories of gravity such as semi-classical or higher dimensional [1, 11, 12, 16, 17]. Taking this into account, we will study the solution of 4D EGB BHs within the context of consistent theories. For example, in [16], the suggested approach have two dynamical degrees of freedom by breaking the temporal diffeomorphism invariance and are explored in the context of EGB gravity in D = d + 1 using the ADM decomposition. This undoubtedly shows that this BH solution has been of great interest in recent years. The spacetime under consideration is assumed to be static and spherically symmetric, and is described by when D = 4. Then, Tomozawa in 2011 [3], through a regularization procedure, found that there could be, from a quantum perspective, a non-trivial contribution of the GB term to space-time in the case where D = 4 . Later in 2013, Cognola et al. [4], through another process of regularization to EGB gravity, managed to perform a dimensional reduction under the Lagrangian formulation, finding again the BH type solution for the case in which D = 4. According to Lovelock’s theorem, the gravity of EGB is only introduced in cases where D > 4 because, for smaller dimensions, the term with the GB coupling would not contribute dynamically [5]. In 2020, Glavan and Lin [6] used this formalism to obain the same BH solution in 4D EGB gravity by simply proposing a rescaling of α. However, several studies have shown that this previous proposal is problematic. This is easily suspected by the fact that the lagrangian action diverges and is not well-defined in the 4-dimensional limit, disregarding Lovelock’s theorem [1, 8–10]. Consequently, it has been clarified that the BH solutions of 4D EGB can be obtained from different approaches and theories of modified gravity that are well-defined. 2.2 Horizons and Particular Cases The CEGB BH solution has two horizons, the internal (Cauchy) horizon, r−, and the event horizon, r+, which are located at r± = M ±  M2 −Q2 −α. (7) (7) The corresponding behavior of r± is shown in Fig. 1 for different values of Q and α. There, the monotonic corrections on r± are evident, at higher values of α and Q, the value of r+ decreases while r−increases. Thus, it is possible to obtain a suitable value of the parameters α and Q for which r−and r+ become a single degenerate horizon (with r−= r+ = M). This particular case is known as the extreme BH type and it is obtained when M = Mext =  Q2 + α. (8) (8) Thus, when M = Mext, the function f (C EGB) has only one real root (corresponding to the degenerate horizon). When M > Mext the usual BHs solutions are obtained, with two real roots representing the two horizon as in (7). Taking M = 1 and M > Mext, α takes values in the range 2 0 < α ≤1 −Q2. (9) (9) From here it is clear that when Q →1, the parameter α →0. On the other hand, when M < Mext we have two complex root and the solution will represent a naked singularity. ext p p g y The BH solution f (C EGB), contains various types of BHs as particular limiting cases. First, the Schwarzschild space-time is reached when Q →0 and α →0, obtaining f (Sch) = 1 −2M r . (10) (10) The Reissner-Nordström (RN) BH is achieved by taking α →0 in the solution f (C EGB), The Reissner-Nordström (RN) BH is achieved by taking α →0 in the solution f (C EG f (RN) = 1 −2M r + Q2 r2 . (11) (11) This metric describes the electrically charged BHs of the theory of GR and the horizons are given by  This metric describes the electrically charged BHs of the theory of GR and the horizons are given by  r± = M ±  M2 −Q2. (12) (12) Fig. 1 Radius of the event horizon r+ and of the inner horizon r−for a CEGB BH. 2.1 The Spacetime Background Therefore, it is not an entirely novel solution. To obtain coherent versions of the theory of BH solutions in 4D EGB gravity, alternative regularization processes have been applied. These include scalar-tensor theories from conformal regularizations [14, 15], the Kaluza-Klein regularized reduction [13], and other formalisms related to theories of gravity such as semi-classical or higher dimensional [1, 11, 12, 16, 17]. Taking this into account, we will study the solution of 4D EGB BHs within the context of consistent theories. For example, in [16], the suggested approach have two dynamical degrees of freedom by breaking the temporal diffeomorphism invariance and are explored in the context of EGB gravity in D = d + 1 using the ADM decomposition. This undoubtedly shows that this BH solution has been of great interest in recent years. The spacetime under consideration is assumed to be static and spherically symmetric, and is described by ds2 = −f (r) dt2 + f (r)−1 dr2 + r2d2 D, (3) (3) where, if D = 4, we have that d2 D ≡dθ2 + sin2 θdφ2 and where, if D = 4, we have that d2 D ≡dθ2 + sin2 θdφ2 and Aμ = −Q r dt, (4) (4) so the solution of an electrically charged BH in 4D EGB gravity will take the form [52] so the solution of an electrically charged BH in 4D EGB gravity will take the form [52] f (C EGB)(r) = 1 + r2 2α ⎡ ⎣1 − 1 + 4α 2M r3 −Q2 r4 ⎤ ⎦. (5) (5) This solution was first introduced in [7], in addition to a coupling with anti-de Sitter space. The asymptotic behavior of this solution is f (C EGB)(r) = 1 −2M r + Q2 r2 + 4M2α r4 −4M Q2α r5 + O 1 r6 . (6) (6) When only the first and second orders are considered in the series expansion, the solutions of GR are clearly revealed. When only the first and second orders are considered in the series expansion, the solutions of GR are clearly revealed. For simplicity, from now on, the spacetime that describes the background geometry of an electrically charged BH in 4D EGB gravity of (5) will be denoted as the CEGB BH solution. 209 Page 6 of 26 International Journal of Theoretical Physics (2023) 62:209 2.2 Horizons and Particular Cases In the left panel it is shown in terms of the electric charge Q/M (using α/M2 = 0.1) and in the right panel in terms of the GB coupling constant α/M2 (with Q/M = 0.1) Fig. 1 Radius of the event horizon r+ and of the inner horizon r−for a CEGB BH. In the left panel it is shown in terms of the electric charge Q/M (using α/M2 = 0.1) and in the right panel in terms of the GB coupling constant α/M2 (with Q/M = 0.1) 123 123 International Journal of Theoretical Physics (2023) 62 :209 Page 7 of 26 209 209 Fig. 2 Dependeces maximum values of GB constant and charge of the BH in 4D EGB gravity(left panel), event horizon to the maximum values of GB constant (middle panel), and event horizon to charge of the BH in 4D EGB gravity (right panel) Fig. 2 Dependeces maximum values of GB constant and charge of the BH in 4D EGB gravity(left panel), event horizon to the maximum values of GB constant (middle panel), and event horizon to charge of the BH in 4D EGB gravity (right panel) The third particular limiting case is the BH solution of 4D EGB gravity, obtained when Q →0, f (EGB) = 1 + r2 2α  1 −  1 + 8Mα r3  . (13) (13) This spacetime has two real roots given by This spacetime has two real roots given by r± = M ±  M2 −α. (14) (14) Furthermore, we can determine the maximum values of the spacetime parameters by analyzing the spacetime to ensure that the BH possesses an event horizon. This can be achieved by solving the equations: f (C EGB)(r) = 0, f (C EGB)′(r) = 0 (15) (15) where ′ denotes the derivative with respect to the radial direction. Figure 2 consists of three panels. The left panel illustrates the dependence of the maximum values of the GB constant and the charge of a black hole in 4D EBG gravity. The gray region represents black holes that possess an event horizon, while the white region corresponds to naked singularities, where there is no black hole at the center of our spacetime. Furthermore, the middle and right panels of Fig. 2 display an intriguing behavior of our event horizon, demonstrating that it remains constant regardless of changes in the parameters. 3.1 Master Wave Equations of Scalar and Electromagnetic Fields QNMs play an important role in investigating gravitational wave astronomy as they describe perturbations near BHs that can be observed through interferometry projects. The study of QNMs using various test fields, such as scalar, electromagnetic, and gravitational, provides valuableinsightsintothegeometricalpropertiesofBHsandhelpsdeterminetheirstabilityand uniqueness. To start the investigation, we propose examining the scalar and electromagnetic fields due to their relatively simple descriptions. Firstly, a massless scalar field, , is described by the Klein-Gordon equation that is written, using the background metric gμν, as 1 √−g ∂μ √−ggμν∂ν  = 0. (16) (16) 123 123 209 Page 8 of 26 209 International Journal of Theoretical Physics (2023) 62:209 On the other hand, the electromagnetic field equation in a curved spacetime is On the other hand, the electromagnetic field equation in a curved spacetime is 1 √−g ∂μ √−gFμν = 0. (17) (17) Using the formalism of perturbation theory and the scalar and vector harmonics to separate the spherical coordinates (t,r, θ, φ), (16) and (17) can be transformed into a single general differential equation that adopts a Schrödinger-like form for stationary backgrounds [19, 53–55], d2 s dr2∗ +  ω2 −Vs(r)  s = 0, (18) (18) where we have introduced the well-known tortoise coordinate, r∗, defined by the relation dr∗= dr f (r) (19) (19) and the effective potential takes de generalized form Vs(r) = f (r) ℓ(ℓ+ 1) r2 + (1 −s) r f ′(r) . (20) (20) In this expression, s = 0 and s = 1 identify the scalar and the electromagnetic perturbations, respectively. Also, the prime denotes differentiation with respect to r, and ℓ= 0, 1, 2, . . . In this expression, s = 0 and s = 1 identify the scalar and the electromagnetic perturbations, respectively. Also, the prime denotes differentiation with respect to r, and ℓ= 0, 1, 2, . . . are the multipole quantum numbers that come from spherical harmonic expansions. In this expression, s = 0 and s = 1 identify the scalar and the electromagnetic perturbations, respectively. Also, the prime denotes differentiation with respect to r, and ℓ= 0, 1, 2, . . . are the multipole quantum numbers that come from spherical harmonic expansions. The QNMs frequencies, denoted by ω in (18), are obtained by requiring purely outgoing waves at infinity and purely incoming waves at the event horizon [30], s ∼±e±iωr∗, r∗→±∞. 3.1 Master Wave Equations of Scalar and Electromagnetic Fields (21) (21) In the case of the CEGB BH, the effective potential is always positive and have the shape of a potential barrier with a single peak. It also fulfills that In the case of the CEGB BH, the effective potential is always positive and have the shape of a potential barrier with a single peak. It also fulfills that V (C EGB) s (r →r+) = V (C EGB) s (r →∞) = 0. (22) (22) This behavior of the effective potential are the necessary boundary conditions to use the semi-analytical methods in the upcoming sections to calculate the QNMs frequencies. This behavior of the effective potential are the necessary boundary conditions to use the semi-analytical methods in the upcoming sections to calculate the QNMs frequencies. 3.2 The WKB Aproximation Method Among the first theoretical approaches developed to calculate these QNMs frequencies in a semi-analytical manner is the well known Wentzel-Kramers-Brillouin (WKB) approximation method [56]. The derivation presented by Schutz and Will [56] begins with a series expansion of the redefined potential (r∗) = ω2 −Vs(r∗). The value of the turtle coordinate at which the maximum point of the effective potential is reached will be denoted by ˜r∗and the potential evaluated at this point would be Vs(˜r∗) = V0. Hence, the series expansion will be  = 0 + 1 2′′ 0 (r∗−˜r∗)2 + O (r∗−˜r∗)3 + ... (23) (23) with 0 = ω2 −V0 and ′′ 0 = −V ′′ 0 . It is clear that the second term of the expansion corresponds to the condition of the maximum point of the potential and therefore it vanishes. Substituting this expansion into the differential (18), the master wave equation reduces to the parabolic cylinder differential equation (usually called the Weber equation), which has 123 123 International Journal of Theoretical Physics (2023) 62 :209 Page 9 of 26 209 209 known solutions. Using the asymptotic behavior described above and imposing the boundary conditions that represent a BH, it is possible to find a simple analytical expression of the frequencies of the QNMs. At first order, it takes the form known solutions. Using the asymptotic behavior described above and imposing the boundary conditions that represent a BH, it is possible to find a simple analytical expression of the frequencies of the QNMs. At first order, it takes the form ω2 = V0 −i  −2V ′′ 0 n + 1 2 . (24) (24) where the expression is labeled with the harmonic or overtone number n. Both, the real part ωR and the imaginary part ωI , as well as the overtone number n, depend only on the maximum potential, V0, and on the second derivative of the potential evaluated in the maximum point, V ′′ 0 . It should be noted that although the WKB formula has been derived analytically, it is not always possible to find the value of ˜r∗explicitly. Therefore, it could be said that the WKB approach is a semi-analytic methodology. When this method was introduced, the QNMs of the gravitational perturbations of the Schwarzschild BH were estimated with an error of approximately 6% [56, 57]. 3.2 The WKB Aproximation Method In 1987, Iyer and Will [58] extended the WKB approximation method up to the 3rd order, improving the precision of the method up to an estimated error of less than 1% for n = 0 [57]. The formula for the frequencies of the QNMs of the 3rd order of the WKB method is ω2 =  V0 +  −2V ′′ 0 ˜1  −i ˜  −2V ′′ 0 [1 + ˜2], (25) (25) where ˜1 and ˜2 (can be consulted in [58]) give additional contributions that depend on n and on higher-order derivatives of the potential evaluated at the radial coordinate of the maximum point. In 2003, Konoplya [59] extended the WKB method to 6th order, giving more accurate results than the previous expressions [57]. In this case, the frequencies are given by the relation 6 i  ω2 −V0   −2V ′′ 0 − 6  j=2  j = n + 1 2, (26) (26) where  j (can be consulted in [59]) represent the higher-order contributions. This equation depends on terms up to V (12) 0 , that is, the twelfth derivative of the potential evaluated at the radial coordinate of the maximum point. Finally, in 2017, Matyjasek and Opala [60] developed the extension of the WKB method up to 13th order. However, it has been shown that convergence in each order is not guaranteed and that the inclusion of more orders in the expansion does not ensure more accurate results [57]. In any case, the equations of the WKB method at 1st, 3rd and 6th order give satisfactory results as long as ℓ> n, with the best results obtained when ℓ≫n and acceptable results when ℓ= n [57]. 3.3 The Pöschl-Teller Potential Method Another of the semi-analytical formalisms developed to calculate the frequencies of the QNMs of a BH was introduced in 1984 by Ferrari and Mashhoon [61]. It consists in an approximation the effective potential included in the (20) to the well known Pöschl-Teller potential, such that the master wave equation could be rewritten as ∂2 ∂r2∗ +  ω2 − V0 cosh2 η (r∗−¯r∗)  = 0, (27) (27) 123 209 Page 10 of 26 International Journal of Theoretical Physics (2023) 62:209 with with η2 = V ′′ 0 2V0 . (28) (28) Making some substitutions and following a similar procedure as that in the WKB approx- imation, it is possible to transform (27) into a differential equation whose solutions are the hypergeometric functions [62]. Analyzing their asymptotic behavior, it is possible to develop a semi-analytic formula for the frequencies of QNMs, ω = ± V0 −η2 4 −iη n + 1 2 . (29) (29) This approach considers both the real and imaginary components of the frequency to be dependent on the potential and its second derivative evaluated at the point of maximum. However, only the imaginary component, ωI , is affected by the overtone number, n. This method can provide more accurate results for ωI compared to those obtained using the WKB formula at 1st order of the (24). Hence, this treatment is not recommended for determining the real component ωR of the perturbation frequencies, except in specific cases such as the eikonal limit (ℓ→∞) or for the fundamental mode (n = 0) [62]. In order to ensure greater precision in our discussions, in the upcoming sections we will keep these restrictions in mind and primarily focus on the eikonal QNMs of the fundamental mode (n = 0). In general, these semi-analytical formulas do not provide precise results when n ≥ℓor when the potential contains divergences, as is the case of perturbations of some massive scalar fields or for asymptotically deSitter and Anti-deSitter spaces. In these situations, the conditions required by the formalisms are not met, since they require the ability to identify the characteristic maximum point of the potential barrier. 3.3 The Pöschl-Teller Potential Method Consequently, other alternative approaches have been proposed for calculating QNM frequencies, including classical and numerical methods such as the Chandrasekhar-Detweiler method, direct integration of the wave equation, the Frobenius series method and its variations, the continued fractions method, and the monodromy technique for highly damped QNMs (for a discussion of these methods see [19, 62]). In recent years, novel and alternative computational methods have also been developed to obtain BH QNM frequencies, such as the Borel summation method [63], the Jansen Mathematica package [64] or the use of Neural Networks Methods [65]. 4.1 Eikonal QNMs Approaches The way in which light travels through space and interacts with matter and energy is one of the most fascinating aspects of the universe. Recently, a strong correlation between null geodesics and QNMs has been established [66]. Specifically, in the eikonal limit (ℓ→∞), the real and imaginary parts of QNMs frequencies for any spherically symmetric, asymptotically flat spacetime can be linked to the frequency and instability timescale of unstable circular null geodesics. This implies a connection between the possible paths of light rays and the response of the BH to external perturbations. Therefore, in the eikonal regime, we can establish a correlation between the radius of the photon sphere Rps of a BH and its QNMs using the 123 International Journal of Theoretical Physics (2023) 62 :209 Page 11 of 26 209 209 following analytical expression [21, 51, 52, 67] following analytical expression [21, 51, 52, 67] following analytical expression [21, 51, 52, 67] ω = ℓ−i n + 1 2 λ. (30) (30) where  is the angular velocity at the photon sphere, where  is the angular velocity at the photon sphere, ere  is the angular velocity at the photon sphere, where  is the angular velocity at the photon sphere,  = f ′(Rps) 2Rps . (31) (31) The symbol λ in (30) represents the Lyapunov exponent, which can be expressed as λ =     f  Rps   2 f  Rps  −R2ps f ′′  Rps  2R2ps . (32) (32) This parameter is associated with the instability time scale of the photon sphere of a BH, indicating how quickly the orbit becomes unstable. This parameter is associated with the instability time scale of the photon sphere of a BH, indicating how quickly the orbit becomes unstable. An interesting approach to the eikonal limit was proposed by M. Churilova [68] by noting that the effective potential Veik in this limit does not usually depend on the spin of the field, except for some exceptions such as the backgrounds of charged BHs coupled to non-linear electromagnetic fields or the gravitational perturbations in some theories with higher cur- vature corrections, like EGB, Einstein-Lovelock or Einstein-dilaton-Gauss-Bonnet theories. Therefore, in most static and spherically symmetric spactimes, the effective potential in the eikonal aproximation for scalar and electromagnetic perturbations can be expressed as [68] Veik(r) = f (r) ℓ(ℓ+ 1) r2 + O(1) . and the Lyapunov exponent takes the form λ(Ch) = 486M4 + 9M2  3Q2 −8α  + 44αQ2 1458 √ 3M5 . (36) (36) In the following sections, we will obtian the radius of the shadow of a CEGB BH from ω(Ch). This approximate expression will not only depend on the geometric parameters of the BH solution, but also on ℓ, so their applicability will be limited to the eikonal regime. 4.1 Eikonal QNMs Approaches (33) (33) This means that the effective potential Veik of the test fields perturbations in the eikonal limit can have the same form as the potential of the electromagnetic field perturbations Vs=1. We will analyze this fact below on the CEGB BH, with the help of our results of the QNMs frequencies of the scalar and electromagnetic field using high values of ℓ. Additionally, in [68] a general approach for eikonal QNMs of asymptotically flat BH solutions is presented. There, an expansion of the first order WKB formula of the (24) is written in powers of small parameters defined by the deviations of a given metric from the Schwarzschild one. These small parameters on the CEGB BH can be identified in the metric expansion of (6). Consequently, applying this Churilova analytical formula, in the eikonal limit, for a CEGB BH we obtain ω(Ch) =  ℓ+ 1 2  3 √ 3M 1 + Q2 6M2 + 2α 27M2 −2Q2α 81M4 (34) −i  n + 1 2  3 √ 3M 1 + Q2 18M2 − 4α 27M2 + 22Q2α 243M4 + O  1 ℓ+ 1 2  . (34) This result reproduces the analytical form of the eikonal QNMs of the 4D EGB BH found in [30], when Q/M = 0. Using (30) and (34) we have that the angular velocity of the photon International Journal of Theoretical Physics (2023) 62:209 209 Page 12 of 26 209 sphere is approximately sphere is approximately sphere is approximately (Ch) = (2ℓ+ 1)  162M4 + 3M2  4α + 9Q2 −4αQ2 972 √ 3ℓM5 , (35) (35) and the Lyapunov exponent takes the form 4.2 Eikonal QNMs of a CEGB BH To calculate and study the eikonal QNMs of the CEGB BH, we use the WKB aproximation formulasat1st,3rd,and6th order,givenby (24),(25),and (26),respectively.Wealsocalculate the eikonal frequencies of the QNMs through the PT potential using (29), the eikonal formula given by the (30), and the Churilova’s analytical formula in (34). We show some of these results in Table 2 for the QNMs of scalar perturbations (s=0), in Table 3 for the QNMs of electromagnetic perturbations (s=1) and in Table 1 for both test fields. In Table 1, we present the QNMs frequencies of the scalar and electromagnetic fields around a CEGB BH for ℓ= 500000 and various values of n. The second column summarize the results obtained from the WKB method in three diferent orders and the PT method, which gave the same results. The third and fourth columns list the values calculated using the eikonal and Churilova formulas, respectively. It is evident that the real part of the frequencies does not depend on n in the eikonal regime. Additionally, it can be seen that the imaginary part of the frequencies obtained from the WKB and PT methods closely match the results calculated using the eikonal limit formula. Although Churilova’s eikonal formula is not as close to the other results, it still agrees well with them. Considering these facts, as depicted in Figs. 3 and 4, the curves representing the frequency behavior overlap in the solid line that summarizes Table 1 QNMs frequencies of the scalar and electromagnetic fields around of a CEGB BH and for various values of n. (with ℓ= 500000, α/M2 = 0.1 and Q/M = 0.1) n WKB 1st, 3rd and 6th order and PT Eikonal Churilova 0 194248.7496-0.1896i 194248.5553-0.1896i 194191.8384-0.1897i 1 194248.7496-0.5687i 194248.5553-0.5687i 194191.8384-0.5692i 2 194248.7496-0.9478i 194248.5553-0.9478i 194191.8384-0.9486i 3 194248.7496-1.3270i 194248.5553-1.3270i 194191.8384-1.3281i 4 194248.7496-1.7061i 194248.5553-1.7061i 194191.8384-1.7075i 5 194248.7496-2.0853i 194248.5553-2.0853i 194191.8384-2.0870i 6 194248.7496-2.4644i 194248.5553-2.4644i 194191.8384-2.4664i 7 194248.7496-2.8435i 194248.5553-2.8435i 194191.8384-2.8458i 8 194248.7496-3.2227i 194248.5553-3.2227i 194191.8384-3.2253i 9 194248.7496-3.6018i 194248.5553-3.6018i 194191.8384-3.6047i le 1 QNMs frequencies of the scalar and electromagnetic fields around of a CEGB BH and for various ues of n. (with ℓ= 500000, α/M2 = 0.1 and Q/M = 0.1) International Journal of Theoretical Physics (2023) 62 :209 Page 13 of 26 209 209 Fig. 3 Eikonal QNMs frecuencies for a CEGB BH depending on the electric charge Q/M. 4.2 Eikonal QNMs of a CEGB BH The left panel corresponds to the behavior of the real part of the frequencies while the right panel illustrates the behavior of the imaginary part. (using n = 0, ℓ= 500000 and α/M2 = 0.1) Fig. 3 Eikonal QNMs frecuencies for a CEGB BH depending on the electric charge Q/M. The left panel corresponds to the behavior of the real part of the frequencies while the right panel illustrates the behavior of the imaginary part. (using n = 0, ℓ= 500000 and α/M2 = 0.1) the behavior of the WKB, PT and the eikonal methods, but differs from the dotted line that displays the results of the Churilova formula. In Tables 2 and 3 we note that increasing ℓimplies that these methods consistently yield similar values. It is also clear that the imaginary part of the frequencies does not depend on ℓ, as is foreseen by the analytical expressions of the eikonal limit and Churilova formulas in (30) and (34), respectively. For a CEGB BH, exactly the same values of the frequencies ω are obtained in all the methods when ℓ> 50000 for the perturbations of both the scalar and the electromagnetic field. For the eikonal and Churilova formulas, this is an obvious result because they do not depend on the field. However, this result for the WKB and PT methods proves the convergence of the eikonal QNMs frequencies. Therefore, the effective potential of these test fields over the CEGB BH effectively behaves like (33) in the eikonal limit. Similarly, our results for the WKB and PT methods when ℓ< 50000 show that the real and imaginary parts of the frequencies ω are, in general, a little smaller for the electromagnetic field than for the scalar field, but they converge for ℓ≈50000, as illustrated in Table 1. Taking ω = ωR −ωI , in Figs. 3 and 4, we show the effect of the geometric parameters Q and α on the real and imaginary components of the eikonal QNMs frequencies for a CEGB BH. Our results show that, as the parameter α increases, the real and imaginary part of the QNMs frequencies ωR and ωI increase monotonically as well. On the other hand, when the electric charge Q grows, the real part ωR also increases but the imaginary part of the frequencies increases up to a maximum peak of growth to decrease after it is reached. Our Fig. 4.2 Eikonal QNMs of a CEGB BH However, our analysis reveals that as Q increases, ωI also increases, until it reaches a value close to Q2 = M2 −α, at which point ωI begins to decrease as depicted in Fig. 3. These same behaviors were observed in [61] for the QNMs of the RN BH due to electric charge, and in [69] for a charged BH in Einstein-Maxwell nonlinear electrodynamics. In the CEGB BH, the effects of electric charge on the QNMs are consistent with those reported in [46]. Furthermore, our results regarding the influence of the GB coupling constant α on the real and imaginary parts of the QNMs of the CEGB BH are in agreement with the findings presented in [30, 34, 37, 46, 52]. Another interesting observation is that the QNMs frequencies calculated by the Churilova formula present a better agreement with other results in the literature when the geometric parameters of the BH are small. This is expected, given the nature of the solution’s expansion [68].Therefore,theChurilovaformula’sfrequenciesdifferfromotherresultsas M approaches Mext. 4.2 Eikonal QNMs of a CEGB BH 4 Eikonal QNMs frecuencies for a CEGB BH depending on the GB coupling constant α/M2. The left panel corresponds to the behavior of the real part of the frequencies while the right panel illustrates the behavior of the imaginary part. (using n = 0, ℓ= 500000 and Q/M = 0.1) Fig. 4 Eikonal QNMs frecuencies for a CEGB BH depending on the GB coupling constant α/M2. The left panel corresponds to the behavior of the real part of the frequencies while the right panel illustrates the behavior of the imaginary part. (using n = 0, ℓ= 500000 and Q/M = 0.1) 209 Page 14 of 26 International Journal of Theoretical Physics (2023) 62:209 Table 2 QNMs frequencies of the scalar field (s=0) around of a CEGB BH and for various high values of ℓ. (with n = 0, α/M2 = 0.1 and Q/M = 0.1) ℓ WKB 1st order WKB 3rd order WKB 6th order PT Eikonal Churilova 5 2.1594-0.1895i 2.1390-0.1898i 2.1391-0.1898i 2.1426-0.1903i 1.9425-0.1896i 2.1361-0.1897i 10 4.0911-0.1896i 4.0804-0.1896i 4.0805-0.1896i 4.0823-0.1898i 3.8850-0.1896i 4.0780-0.1897i 50 19.6216-0.1896i 19.6194-0.1896i 19.6194-0.1896i 19.6197-0.1896i 19.4249-0.1896i 19.6134-0.1897i 100 39.0452-0.1896i 39.0441-0.1896i 39.0441-0.1896i 39.0443-0.1896i 38.8497-0.1896i 39.0325-0.1897i 500 194.4431-0.1896i 194.4428-0.1896i 194.4428-0.1896i 194.4429-0.1896i 194.2486-0.1896i 194.3858-0.1897i 1000 388.6915-0.1896i 388.6914-0.1896i 388.6914-0.1896i 388.6914-0.1896i 388.4971-0.1896i 388.5775-0.1897i 5000 1942.6798-0.1896i 1942.6798-0.1896i 1942.6798-0.1896i 1942.6798-0.1896i 1942.4856-0.1896i 1942.1106-0.1897i 10000 3885.1654-0.1896i 3885.1654-0.1896i 3885.1654-0.1896i 3885.1654-0.1896i 3884.9711-0.1896i 3884.0271-0.1897i 50000 19425.0498-0.1896i 19425.0498-0.1896i 19425.0498-0.1896i 19425.0498-0.1896i 19424.8555-0.1896i 19419.3586-0.1897i 123 Page 15 of 26 209 International Journal of Theoretical Physics (2023) 62 :209 Table 3 QNMs frequencies of the electromagnetic field (s=1) around of a CEGB BH and for various high values of ℓ. (with n = 0, α/M2 = 0.2 and Q/M = 0.2) ℓ WKB 1st order WKB 3rd order WKB 6th order PT Eikonal Churilova 5 2.1646-0.1858i 2.1450-0.1859i 2.1451-0.1859i 2.1486-0.1865i 1.9687-0.1865i 2.1620-0.1873i 10 4.1338-0.1863i 4.1236-0.1863i 4.1236-0.1863i 4.1254-0.1865i 3.9374-0.1865i 4.1275-0.1873i 50 19.8840-0.1865i 19.8819-0.1865i 19.8819-0.1865i 19.8822-0.1865i 19.6872-0.1865i 19.8512-0.1873i 100 39.5713-0.1865i 39.5702-0.1865i 39.5702-0.1865i 39.5704-0.1865i 39.3744-0.1865i 39.5058-0.1873i 500 197.0691-0.1865i 197.0688-0.1865i 197.0688-0.1865i 197.0689-0.1865i 196.8722-0.1865i 196.7427-0.1873i 1000 393.9413-0.1865i 393.9411-0.1865i 393.9411-0.1865i 393.9412-0.1865i 393.7444-0.1865i 393.2889-0.1873i 5000 1968.9188-0.1865i 1968.9188-0.1865i 1968.9188-0.1865i 1968.9188-0.1865i 1968.7219-0.1865i 1965.6584-0.1873i 10000 3937.6407-0.1865i 3937.6407-0.1865i 3937.6407-0.1865i 3937.6407-0.1865i 3937.4439-0.1865i 3931.1203-0.1873i 50000 19687.4161-0.1865i 19687.4161-0.1865i 19687.4161-0.1865i 19687.4161-0.1865i 19687.2193-0.1865i 19654.8153-0.1873i 123 209 Page 16 of 26 Page 16 of 26 International Journal of Theoretical Physics (2023) 62:209 209 findings for the QNMs of the CEGB BH align with those reported in [52], where similar corrections due to Q and α were observed. 5.1 The BH Photon Sphere Radius The photon sphere, also known as the ”light ring” or ”photon orbit”, for a static spherically symmetric BH is recognized as the orbit at which light moves in a unstable circular null geodesic. As mentioned in [21, 52], the Hamilton-Jacobi or Hamiltonian formulations can be used to find the equations of motion for photons around a static and spherically symmetric BH background and subsequently, permit to identify the effective potential that describes the system. From the critical point conditions of this potential, the radius of the photon sphere Rps can be determined by solving the expression 2 −Rps f ′(Rps) f (Rps) = 0. (37) (37) Substituting the Schwarzschild metric on this expression, we obtain that R(Sch) ps = 3M. (38) (38) Using the solution of RN given by (11), we have R(RN) ps = 1 2  9M2 −8Q2 + 3M  (39) (39) It should be noted that this expression for R(RN) ps has the same analytical form given in [70] for the radial coordinate of the maximum of the corresponding effective potential of field perturbations in the eikonal limit. Additionally, the expression for R(RN) ps can be approximated for small values of Q as R(RN) ps = 3M −2Q2 3M −4Q4 27M3 + O  Q5 . (40) (40) Using the 4D EGB BH metric given by (13) in the condition of the (37), we get Using the 4D EGB BH metric given by (13) in the condition of the (37), we get B BH metric given by (13) in the condition of the (37), we get R(EGB) ps =  M √ 16α2 −27M4 −4α 2/3 + 3M2  M √ 16α2 −27M4 −4α 1/3 . (41) 123 123 International Journal of Theoretical Physics (2023) 62 :209 Page 17 of 26 209 age 17 of 26 209 209 In [71], another alternative analytical expression is deduced for the radius of the photon sphere of the 4D EGB BH, with M = 1, R(EGB) ps = 2 √ 3 cos 1 3 cos−1 −4α 3 √ 3 . (42) (42) Although we couldn’t establish an equality between these two expressions, we have tested them numerically and they always gave identical results. However, both expressions lead to the same expansion, R(EGB) ps = 3M −4α 9M −8α2 81M3 + O  α3 , (43) (43) useful for small values of α. 5.1 The BH Photon Sphere Radius Note that the expansions of R(RN) ps and R(EGB) ps show that the first term corresponds to radius of the photon spher for the Schwarzschild BH. useful for small values of α. Note that the expansions of R(RN) ps and R(EGB) ps show that the first term corresponds to radius of the photon spher for the Schwarzschild BH. 5.3 Correspondence Between Eikonal QNMs and Null Geodesics As we stated above, there exist a correlation between null geodesics and eikonal QNMs frequencies for any spherically symmetric, asymptotically flat spacetime [66], which to a large extent can be linked to the fulfillment of the (30). However, with the simple fact that the BH solution is no longer valid for the WKB formula to first order, it is enough to believe that this connection does not hold. For example, the predicted correlation between null geodesics and QNMs is not upheld in the Einstein-Lovelock theory, as reported in [20], where authors showed that the radius of the photon sphere does not match the radial position of the extremum of the effective potential in the eikonal regime, contributing to the breakdown of the proposed correspondence. In the previous section, we found that the effective potential of perturbations of the scalar and electromagnetic fields around the CEGB BH follows (33) in the eikonal limit. However, this is not the case for gravitational perturbations in this background. In fact, in [30], it is shown that there is no correspondence between gravitational eikonal QNMs and null geodesics in the 4D EGB BH because of the form of the effective potential. They also mention that this correspondence does hold true for test fields perturbations when the background metric is considered to be a viable BH solution. Nevertheless, for scalar and electromagneticfieldsintheCEGBBHspacetime,theQNMscalculationsanditsconnections with the null geodesics and with the radius of the BH shadow should be satisfied and valid. With the purpose of analyzing the correspondence in the CEGB BH, we will examine the agreement between the radius of the photon sphere, R(C EGB) ps , and the radial position of the maximum of the effective potential, ˜r, for both scalar and electromagnetic field perturbations in the eikonal limit. By differentiating with respect to the radial coordinate r and equating to zero the (20) of the effective potential, Vs(r), gives a condition that find the radial coordinate ˜r of the maximum point of the potential, as follows 0 = 1 r3  r f ′  ℓ(ℓ+ 1) + r(1 −s2) f ′ −f  2ℓ(ℓ+ 1) + r(1 −s2)  f ′ −r f ′′  r=˜r. (48) 0 = 1 r3  r f ′  ℓ(ℓ+ 1) + r(1 −s2) f ′ −f  2ℓ(ℓ+ 1) + r(1 −s2)  f ′ −r f ′′  r=˜r. 5.2 The Photon Sphere Radius for a CEGB BH Using the expression of (37), an analytical expression for the radius of the photon sphere for a CEGB BH is obtained as R(C EGB) ps = 1 2 −8M  2α + 3Q2 √ X −X + 18M2 + √ X 2 , (44) X = 27M4 −16Q2  α + Q2 31/3Y + Y 32/3 + 6M2 (45) Y =  −243M6 + 72M2  4α2 + 3Q4 + 6αQ2 + Z 1/3 , (46) Z = 1 6  1728  27αM4 + 4Q6  64  α + Q23 −27M4  4α + 3Q2 . (47) (44) (45) (46) (47) The above equations for R(C EGB) ps effectively reproduce the analytic expressions corre- sponding to the radius of the photon spheres of the solutions of the particular limit cases. Taking Q →0 and α →0, we get R(Sch) ps in (38). Doing only α →0 gives R(RN) ps given by (39) and doing only Q →0 recovers R(EGB) ps given by (41). Fig. 5 Photon sphere radius Rps for a CEGB BH using the (47). In the left panel it is shown in terms of the electric charge Q/M (using α/M2 = 0.1) and in the right panel in terms of the GB coupling constant α/M2 (with Q/M = 0.1) Fig. 5 Photon sphere radius Rps for a CEGB BH using the (47). In the left panel it is shown in terms of the electric charge Q/M (using α/M2 = 0.1) and in the right panel in terms of the GB coupling constant α/M2 (with Q/M = 0.1) 209 Page 18 of 26 209 Page 18 of 26 209 International Journal of Theoretical Physics (2023) 62:209 In Fig. 5, we show the effect of the geometric parameters Q and α on R(C EGB) ps . It is clear that as both the electric charge and the GB coupling constant increase, the photon sphere radius becomes smaller. These results agree with those reported in [49, 71]. In Fig. 5, we show the effect of the geometric parameters Q and α on R(C EGB) ps . It is clear that as both the electric charge and the GB coupling constant increase, the photon sphere radius becomes smaller. These results agree with those reported in [49, 71]. Table 4 The effective potential and its radial coordinate of the maximum ˜r for the scalar perturbations around a CEGB BH. We show the convergence for various values of ℓ. (whit α/M2 = 0.1, Q/M = 0.1 and R(C EGB) ps = 2.94761M) 6.1 Connection Between Eikonal QNMs and the Radius of the BH Shadow The BH shadow is a region of darkness that results from the deflection of light by the strong gravitational field in the BH surroundings. Light from background objects that would normally reach an observer is instead absorbed by the BH, resulting in the appearance of a shadow. The shape and size of this shadow is a unique characteristic of each BH and it depends on its geometric properties as well as on the characteristics of the material surrounding it. Assuming a static observer positioned at a radial coordinate rO, far enough from a spher- ically symmetric BH and such that f (rO) ≈1, the radius of the BH shadow, Rsh, as seen by this observer can be approximately calculated by [21, 30, 52, 54, 71] Rsh ≈ Rps  f  Rps . (49) (49) It can be shown that for a Schwarzschild BH, the shadow radius is R(Sch) sh = 3 √ 3M. On the other hand, using the equation for R(C EGB) ps in terms geometric parameters for the CEGB BH solution to obtain the shadow radius is not straightforward. Therefore, in order to find an expression for R(C EGB) sh , we will use the previous calculation of the QNMs as the starting point. Based on the correlations between the distance from the BH and the behavior of eikonal QNMs with the photon sphere, it can be deduced that the real part of QNMs frequencies is inversely proportional to Rsh [21]. This relationship can be simply stated as follows ωR = lim ℓ≫1 ℓ Rsh . (50) (50) In general terms, it is also proposed that the relationship between the QNMs and the shadow radius of spherically symmetrical BHs can be expressed as [52] In general terms, it is also proposed that the relationship between the QNMs and the shadow radius of spherically symmetrical BHs can be expressed as [52] ω = R−1 sh ℓ+ D −3 2 −i n + 1 2 λ (51) (51) where D represents the dimension of spacetime. In the eikonal limit, the term (D −3)/2 can be disregarded. Nevertheless, it can be useful to assess the connection between BH shadows and QNMs at small ℓ, especially in spherically symmetrical spacetimes defined in high or lower dimensions. Moreover, a generalized equation linking eikonal QNMs and shadows of rotating BHs is provided in [72]. 5.3 Correspondence Between Eikonal QNMs and Null Geodesics (4 (48) Table 4 The effective potential and its radial coordinate of the maximum ˜r for the scalar perturbations around a CEGB BH. We show the convergence for various values of ℓ. (whit α/M2 = 0.1, Q/M = 0.1 and R(C EGB) ps = 2.94761M) ℓ M2Vs=0 ˜r/M 5 1.15675 2.93786 10 4.17533 2.94489 50 96.24260 2.94749 100 381.12300 2.94758 500 9452.01630 2.94761 1000 37770.25849 2.94761 5000 943501.21847 2.94761 10000 3773627.47464 2.94761 50000 94333139.77196 2.94761 123 International Journal of Theoretical Physics (2023) 62 :209 Page 19 of 26 209 In Table 4, we present some values of the effective potential Vs for scalar perturbations and the radial position of the maximum ˜r for various values of ℓ, in a CEGB BH background. The results show that as ℓincreases, Vs increases as well, but ˜r becomes closer to the correct value of the radius of the photon sphere that, for the values α/M2 = 0.1 and Q/M = 0.1, is R(C EGB) ps = 2.94761M. On the other hand, in the case of electromagnetic perturbations (s = 1), the value of ˜r can be found analytically and it exactly matches the expression for R(C EGB) ps given in (47). Consequently, this establishes that, in the eikonal limit, the CEGB BH also satisfies the connection between the maximum effective potential of the perturbations and the radius of the photon sphere, at least for scalar and electromagnetic fields. 6.2 CEGB BH Shadow Radius The connection between the shadow and the QNMs of the massless scalar field around a CEGB BH is explored in [52], but they do it using only the 6th order WKB method and from the (51). In this work, we will use the (50), which holds only in the eikonal regime, and we will test several additional methods to study the shadow and QNMs of scalar and electromagnetic perturbations around a CEGB BH. To determine the shadow radius of the CEGB BH, we use the frequencies of the QNMs computed through the WKB method at 1st, 3rd, and 6th order, as specified in (24), (25), and (26), respectively. We also use the frequencies of the QNMs derived from the PT potential method outlined in (29), the eikonal formula that linking QNMs with Rps given by the (30), and the Churilova’s analytical formula presented in (34). By substituting R(C EGB) ps from the (47) into the (49), it is possible to provide a rather complicated analytical expression of the shadow radius of CEGB BH, which is not shared here because it is so extensive. However, from Churilova’s analytical eikonal approach, contrary to all the others studied, it is possible to provide an approximate analytical formula for the CEGB BH shadow radius. Using the (34) and (50), it takes the form R(Ch) sh = 972 √ 3ℓM5 (2ℓ+ 1)  162M4 + 3M2  4α + 9Q2 −4αQ2. (52) (52) This CEGB BH shadow radius formula is related to the eikonal limit and therefore, in addition to the geometric parameters of the solution, it also depends on ℓ. This CEGB BH shadow radius formula is related to the eikonal limit and therefore, in addition to the geometric parameters of the solution, it also depends on ℓ. Using (49), a CEGB BH with α/M2 = 0.1 and Q/M = 0.1 has a shadow with radius Rsh = 5.14804M. In Table 5 we show the results obtained for the shadow radius for the CEGB BH for the fundamental mode (n = 0) and using various values of ℓ. There, R(W K B−PT ) sh represents the shadow of the BH obtained from the WKB and PT potential methods, R(Ei) sh denotes the BH shadow radius obtained by using the eikonal equation and finally, the fourth column shows the results of Churilova’s analytical equation. 6.1 Connection Between Eikonal QNMs and the Radius of the BH Shadow Nonetheless, rotating BHs are not discussed in depth here but they hold significance for future related research projects. 123 209 Page 20 of 26 International Journal of Theoretical Physics (2023) 62:209 6.2 CEGB BH Shadow Radius It should be noted that R(W K B−PT ) sh summarizes all the results of the WKB approximation methods at 1st, 3rd and 6th order and the PT potential because, as discussed in Table 1, these methods return the same values of the frequencies of the QNMs of the scalar and electromagnetic field in the eikonal limit. Therefore, as an initial conclusion of this work we see that all the Table 5 Shadow radius Rsh for a CEGB BH using various values of ℓ. (with n = 0, α/M2 = 0.1, Q/M = 0.1 and Rsh = 5.14804M) ℓ R(W K B−PT ) sh /M R(Ei) sh /M R(Ch) sh /M 5 4.63095 5.14804 4.68141 10 4.88864 5.14804 4.90434 50 5.09643 5.14804 5.09857 100 5.12227 5.14804 5.12393 500 5.14289 5.14804 5.14441 1000 5.14547 5.14804 5.14698 5000 5.14753 5.14804 5.14904 10000 5.14779 5.14804 5.14929 50000 5.14799 5.14804 5.14950 100000 5.14802 5.14804 5.14953 500000 5.14804 5.14804 5.14955 123 International Journal of Theoretical Physics (2023) 62 :209 Page 21 of 26 209 results obtained from the radius of its shadow show verify that the CEGB BH does indeed fulfill the connection between geometrical paramters and the QNMs. The results given by Churilova’s analytical eikonal approach show that R(Ch) sh achieves values that are very close to those obtained by the other approaches. For example, for ℓ= 500000 the deviation error between R(W K B−PT ) sh and R(Ch) sh is less than 1%. results obtained from the radius of its shadow show verify that the CEGB BH does indeed fulfill the connection between geometrical paramters and the QNMs. The results given by Churilova’s analytical eikonal approach show that R(Ch) sh achieves values that are very close to those obtained by the other approaches. For example, for ℓ= 500000 the deviation error between R(W K B−PT ) sh and R(Ch) sh is less than 1%. sh sh For practical purposes, doing ℓ→∞removes the dependency on ℓfrom (52), simplifying the CEGB BH shadow radius to R(C EGB) sh = 486 √ 3M5 162M4 + 3M2  4α + 9Q2 −4αQ2 (53) (53) From this expression, the shadow radius for the limiting paraticular cases of the CEGB BH can be calculated. 7 Conclusion We have studied the relationship between the geometrical properties of a CEGB BH solution and the radius of the photon sphere, shadow radius, and eikonal QNMs. We obtained that the WKB method and PT potential method give the same results for eikonal QNMs for scalar and electromagnetic field perturbations of a CEGB BH. Our findings indicate that the real part of the eikonal QNMs frequencies is linked to the unstable circular null geodesic and shadow radius of a CEGB BH. We have ilustrated how the parameters of electric charge Q and GB constant α affect the QNMs frequencies, photon sphere, and shadow radius. Our results indicate that the real part of QNMs, photon sphere, and shadow radius are lower in CEGB BHs compared to those in 4D EGB, RN, and Schwarzschild BHs. Various equations have been derived for the radius of the photon sphere and shadows of BH solutions. Our inves- tigation has shown that the eikonal approach proposed by Churilova provides a practical and straightforward approximate equation for the CEGB BH shadow radius, which is useful for small values of the geometric parameters. This approach facilitates analytical investigations, such as the study of astrophysical BH shadows, and could aid in observational investigations of QNMs in future gravitational wave projects. There are several topics for future research related to this work. The following projects could be related to extending the analytical approach of the eikonal QNMs realized by Churilova to other BH solutions to test its methodology, including in spacetime arrangements that are not limited to being static, spherically symmetrical, or asymptotically flat. Moreover, the study of the spectrum of QNMs of CEGB BHs excited by an external source, such as an extreme mass ratio inspiral, could be explored. Additionally, the connections between the photon sphere, BH shadow, and eikonal QNMs should be explored for more realistic CEGB BHs or those related to alternative gravity theories. A particularly important BH solution to test these connections is the rotating CEGB BH, as recent theories also suggest connections between photon orbits, shadow radius, and eikonal QNMs in rotating BH solutions [72–74]. In [40], it was shown that the shadow of a rotating 4D EGB BH aligns with the M87* BH shadow observed by the Event Horizon Telescope. 6.2 CEGB BH Shadow Radius For example, taking α →0 gives R(RN) sh = 18 √ 3M3 6M2 + Q2 , (54) (54) while taking Q →0 produces while taking Q →0 produces R(EGB) sh = 81 √ 3M3 27M2 + 2α . (55) (55) Similarly, by choosing Q →0 and α →0 we recover the well-known limit of the Schwarzschild BH shadow radius, R(Sch) sh = 3 √ 3M. Similarly, by choosing Q →0 and α →0 we recover the well-known limit of the Schwarzschild BH shadow radius, R(Sch) sh = 3 √ 3M. In Fig. 6, the solid line summarizes the BH shadow radius calculated using the QNMs given by the WKB-PT method and the eikonal limit formula while the dotted line shows the shadow radius from Churilova’s eikonal approach. It also ilustrates the effects of the electric charge of the BH and the GB coupling constant on the shadow radius of a CEGB BH. As both parameters increase, the shadow radius decreases, which agrees with previous studies [34, 49, 52, 71]. This implies that, based on the range of possible values for the BH geometric parameters as stated in (9), the CEGB BH has a smaller shadow radius compared to the 4D EGB BH and the RN BH, and these BHs have a smaller shadow radius than that of a Schwarzschild BH Figure 6 also show that the curves overlap for small values of α and Q and then, in this region the CEGB BH shadow radius obtained from Churilova’s eikonal approach is very useful due to its analytical simplicity, providing accurate results. Fig. 6 Shadow radius Rsh for a CEGB BH (with ℓ= 500000). In the left panel it is shown in terms of the electric charge Q/M (using α/M2 = 0.1) and in the right panel in terms of the GB coupling constant α/M2 (with Q/M = 0.1) Fig. 6 Shadow radius Rsh for a CEGB BH (with ℓ= 500000). In the left panel it is shown in terms of the electric charge Q/M (using α/M2 = 0.1) and in the right panel in terms of the GB coupling constant α/M2 (with Q/M = 0.1) 209 Page 22 of 26 209 International Journal of Theoretical Physics (2023) 62:209 Ultimately, it is important to say that, in [71], the authors examine a hypothesis regarding a series of inequalities involving multiple parameters associated with the size of an 4D EGB BH. 6.2 CEGB BH Shadow Radius The proposal is that BH. The proposal is that 3 2r+ ≤Rps ≤ 1 √ 3 Rsh ≤3M, (56) (56) keeping in mind the ranges of (9) for the BH geometric parameters. We have evaluated the validity of this hypothesis involving the parameters that describe the size of a CEGB BH and our findings indicate that it satisfies the inequalities. Acknowledgements We would like to thank Farrux Abdulxamidov for the support and the valuable discus- sions. We acknowledge partial financial support from Dirección de Investigación-Sede Bogotá, Universidad Nacional de Colombia (DIB-UNAL) under HERMES Project No. 57057 and Grupo de Astronomía, Astrofísica y Cosmología-Observatorio Astronómico Nacional. Funding Open Access funding provided by Colombia Consortium. 7 Conclusion Here, for a spin parameter of a = 0.1M, the GB coupling constant must be α ≤0.00394M2 (a very small value for α which matches a good approximation of Churilova’s eikonal approach). Therefore, it would be beneficial to also provide an analytical approach to these problems, linking the eikonal QNMs to the geometric properties of rotating CEGB BHs. Acknowledgements We would like to thank Farrux Abdulxamidov for the support and the valuable discus- sions. We acknowledge partial financial support from Dirección de Investigación-Sede Bogotá, Universidad Nacional de Colombia (DIB-UNAL) under HERMES Project No. 57057 and Grupo de Astronomía, Astrofísica y Cosmología-Observatorio Astronómico Nacional. Funding Open Access funding provided by Colombia Consortium. 123 International Journal of Theoretical Physics (2023) 62 :209 209 Page 23 of 26 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. References 1. Fernandes, P.G.S., Carrilho, P., Clifton, T., Mulryne, D.J.: The 4D Einstein-Gauss-Bonnet Theory of Grav- ity: A Review. Class. Quantum Gravity 39, 063001 (2022). https://doi.org/10.1088/1361-6382/ac500a 2. Boulware, D.G., Deser, S.: String-Generated Gravity Models. Phys. Rev. Lett. 55, 2656 (1985). https:// 1. Fernandes, P.G.S., Carrilho, P., Clifton, T., Mulryne, D.J.: The 4D Einstein-Gauss-Bonnet Theory of Grav- ity: A Review. Class. Quantum Gravity 39, 063001 (2022). https://doi.org/10.1088/1361-6382/ac500a ity: A Review. Class. Quantum Gravity 39, 063001 (2022). https://doi.org/10.1088/1361-6382/ac500a 2. Boulware, D.G., Deser, S.: String-Generated Gravity Models. Phys. Rev. Lett. 55, 2656 (1985). https:// doi.org/10.1103/PhysRevLett.55.2656 2. Boulware, D.G., Deser, S.: String-Generated Gravity Models. Phys. Rev. Lett. 55, 2656 (1985). https:// doi.org/10.1103/PhysRevLett.55.2656 3. Tomozawa, Y.: Quantum Corrections to Gravity. (2011). https://doi.org/10.48550/arXiv.1107.1424 4. Cognola, G., Myrzakulov, R., Sebastiani, L., Zerbini, S.: Einstein Gravity with Gauss-Bonnet Entrop Corrections. Phys. Rev. D 88, 024006 (2013). https://doi.org/10.1103/PhysRevD.88.024006 5. Bousder, M., El Bourakadi, K., Bennai, M.: Charged 4D Einstein-Gauss-Bonnet Black Hole: Vacuum Solutions, Cauchy Horizon. Thermodynamics. Phys. Dark Universe 32, 100839 (2021). https://doi.org/ 10.1016/j.dark.2021.100839 6. Glavan, D., Lin, C.: Einstein-Gauss-Bonnet Gravity in Four-Dimensional Spacetime. Phys. Rev. Lett. 124, 81301 (2020). https://doi.org/10.1103/PhysRevLett.124.081301 7. Fernandes, P.G.S.: Charged Black Holes in AdS Spaces in 4D Einstein Gauss-Bonnet Gravity. Phys. L B 805, 135468 (2020). https://doi.org/10.1016/j.physletb.2020.135468 8. Gürses, M., ¸Si¸sman, T.Ç., Tekin, B.: Comment on “Einstein-Gauss-Bonnet Gravity in Four-Dimension Spacetime.” Phys. Rev. Lett. 125,(2020). https://doi.org/10.1103/PhysRevLett.125.149001 8. Gürses, M., ¸Si¸sman, T.Ç., Tekin, B.: Comment on Einstein Gauss Bonnet Gravity in Four Dimensional Spacetime.” Phys. Rev. Lett. 125,(2020). https://doi.org/10.1103/PhysRevLett.125.149001 p y p g y 9. Gürses, M., ¸Si¸sman, T.Ç., Tekin, B.: Is There a Novel Einstein-Gauss-Bonnet Th Eur. Phys. J. C 80,(2020). https://doi.org/10.1140/epjc/s10052-020-8200-7 y ,( ) p g pj 10. Arrechea, J., Delhom, A., Jiménez-Cano, A.: Comment on “Einstein-Gauss-Bonnet Gravity in Four- Dimensional Spacetime ” Phys Rev Lett 125 (2020) https://doi org/10 1103/PhysRevLett 125 149002 10. Arrechea, J., Delhom, A., Jiménez-Cano, A.: Comment on “Einstein-Gauss-Bonnet Gravity in Fo Dimensional Spacetime,” Phys. Rev. Lett. 125,(2020). https://doi.org/10.1103/PhysRevLett.125.1490 11. Cai, R.G., Caob, L.M., Ohtab, N.: Black Holes in Gravity with Conformal Anomaly and Logarithmic Term in Black Hole Entropy. J. High Energy Phys. 2010,(2010). https://doi.org/10.1007/JHEP04(2010)082 12. Cai, R.G.: Thermodynamics of Conformal Anomaly Corrected Black Holes in AdS Space. Phys. Lett. Sect. B Nucl. Elem. Part. High-Energy Phys. 733,(2014). https://doi.org/10.1016/j.physletb.2014.04.044 Sect. B Nucl. Elem. Part. High-Energy Phys. 733,(2014). https://doi.org/10.1016/j.physletb.2014.04.044 13. Lü, H., Pang, Y.: Horndeski Gravity as D →4 Limit of Gauss-Bonnet. Phys. Lett. B 809, 135717 (2020). https://doi.org/10.1016/j.physletb.2020.135717 13. References Glampedakis, K., Silva, H.O.: Eikonal Quasinormal Modes of Black Holes beyond General Relativity. Phys. Rev. D 100, 044040 (2019). https://doi.org/10.1103/PhysRevD.100.044040 27. Liu, C., Zhu, T., Wu, Q., Jusufi, K., Jamil, M., Azreg-Aïnou, M., Wang, A.: Shadow and Quasinormal Modes of a Rotating Loop Quantum Black Hole. Phys. Rev. D 101, 084001 (2020). https://doi.org/10. 1103/PhysRevD.101.084001 y 28. Moura, F., Rodrigues, J.: Eikonal Quasinormal Modes and Shadow of String-Corrected d-Dimensional Black Holes. Phys. Lett. B 819, 136407 (2021). https://doi.org/10.1016/j.physletb.2021.136407 y p g j p y 29. Chen, C.Y., Chiang, H.W., Tsao, J.S.: Eikonal Quasinormal Modes and Photon Orbits of Deformed Schwarzschild Black Holes. Phys. Rev. D 106,(2022). https://doi.org/10.1103/PhysRevD.106.044068 30. Konoplya, R.A., Zinhailo, A.F.: Quasinormal Modes, Stability and Shadows of a Black Hole in the 4D Einstein-Gauss-Bonnet Gravity. Eur. Phys. J. C 80,(2020). https://doi.org/10.1140/epjc/s10052-020- 08639-8 31. Zubair, M., Raza, M.A., Sarikulov, F., Rayimbaev, J.:“4D Einstein-Gauss-Bonnet Black Hole in Power- Yang-Mills Field: A Shadow Study.” [arXiv:2305.16888 [gr-qc]] 32. Zahid, M., Khan, S.U., Ren, J., Rayimbaev, J.: Geodesics and shadow formed by a rotating Gauss-Bonnet black hole in AdS spacetime. Int. J. Mod. Phys. D 31(08), 2250058 (2022). https://doi.org/10.1142/ S0218271822500584 33. Rayimbaev, J., Bardiev, D., Mirzaev, T., Abdujabbarov, A., Khalmirzaev, A.: Shadow and massless parti- cles around regular Bardeen black holes in 4D Einstein Gauss-Bonnet gravity. Int. J. Mod. Phys. D 31(07), 2250055 (2022). https://doi.org/10.1142/S0218271822500559 34. Liu, T.T., Zhang, H.X., Feng, Y.H., Deng, J.B., Hu, X.R.: Double Shadow of a 4D Einstein-Gauss-Bonnet Black Hole and the Connection between Them with Quasinormal Modes. Mod. Phys. Lett. A 37,(2022). https://doi.org/10.1142/S0217732322501541 p g 35. Churilova, M.S.: Quasinormal Modes of the Dirac Field in the Consistent 4D Einstein-Gauss-Bonnet Gravity. Phys. Dark Universe 31, 100748 (2021). https://doi.org/10.1016/j.dark.2020.100748 36. Zeng, X.X., Zhang, H.Q., Zhang, H.: Shadows and Photon Spheres with Spherical Accretions in the Four-Dimensional Gauss-Bonnet Black Hole. Eur. Phys. J. C 80, 1 (2020). https://doi.org/10.1140/epjc/ s10052-020-08449-y 37. Devi, S., Roy, R., Chakrabarti, S.: Quasinormal Modes and Greybody Factors of the Novel Four Dimen- sional Gauss-Bonnet Black Holes in Asymptotically de Sitter Space Time: Scalar, Electromagnetic and Dirac Perturbations. Eur. Phys. J. C 80, (2020). https://doi.org/10.48550/arXiv.2004.14935 Ö 38. Övgün, A.: Black hole with confining electric potential in scalar-tensor description of regularized 4- dimensional Einstein-Gauss-Bonnet gravity. Phys. Lett. B 820, 136517 (2021). https://doi.org/10.1016/ j.physletb.2021.136517 39. Javed, W., Aqib, M., Övgün, A.: Effect of the magnetic charge on weak deflection angle and greybody bound of the black hole in Einstein-Gauss-Bonnet gravity. Phys. Lett. References Lü, H., Pang, Y.: Horndeski Gravity as D →4 Limit of Gauss-Bonnet. Phys. Lett. B 809, 135717 (2020). https://doi.org/10.1016/j.physletb.2020.135717 14. Hennigar,R.A.,Kubizˇnák,D.,Mann,R.B.,Pollack,C.:OnTakingtheD→4LimitofGauss-BonnetGrav- ity: Theory and Solutions. J. High Energy Phys. 2020, (2020). https://doi.org/10.1007/JHEP07(2020)027 14. Hennigar,R.A.,Kubizˇnák,D.,Mann,R.B.,Pollack,C.:OnTakingtheD→4LimitofGauss-BonnetGrav- ity: Theory and Solutions. J. High Energy Phys. 2020, (2020). https://doi.org/10.1007/JHEP07(2020)027 15. Fernandes, P.G.S., Carrilho, P., Clifton, T., Mulryne, D.J.: Derivation of Regularized Field Equations for the Einstein-Gauss-Bonnet Theory in Four Dimensions. Phys. Rev. D 102, 024025 (2020). https://doi. 15. Fernandes, P.G.S., Carrilho, P., Clifton, T., Mulryne, D.J.: Derivation of Regularized Field Equations for the Einstein-Gauss-Bonnet Theory in Four Dimensions. Phys. Rev. D 102, 024025 (2020). https://doi. org/10.1103/PhysRevD.102.024025 16. Aoki, K., Gorji, M.A., Mukohyama, S.: A Consistent Theory of D →4 Einstein-Gauss-Bonnet Gravity. Phys. Lett. B 810, 135843 (2020). https://doi.org/10.1016/j.physletb.2020.135843 17. Ghosh, S.G., Singh, D.V., Kumar, R., Maharaj, S.D.: Phase Transition of AdS Black Holes in 4D EGB Gravity Coupled to Nonlinear Electrodynamics. Ann. Phys. 424, 168347 (2021). https://doi.org/10.1016/ j.aop.2020.168347 j p 18. Kokkotas, K.D., Schmidt, B.G.: Quasi-Normal Modes of Stars and Black Holes. Living Rev. Relativ. 2, (1999). https://doi.org/10.12942/lrr-1999-2 19. Konoplya, R.A., Zhidenko, A.: Quasinormal Modes of Black Holes: From Astrophysics to String Theory. Rev. Mod. Phys. 83, 793 (2011). https://doi.org/10.1103/RevModPhys.83.793 20. Konoplya, R.A., Stuchlík, Z.: Are Eikonal Quasinormal Modes Linked to the Unstable Circula Geodesics? Phys. Lett. B 771, 597 (2017). https://doi.org/10.1016/j.physletb.2017.06.015 21. Jusufi, K.: Quasinormal Modes of Black Holes Surrounded by Dark Matter and Their Connection with the Shadow Radius. Phys. Rev. D 101, 084055 (2020). https://doi.org/10.1103/PhysRevD.101.084055 Ö 22. Liu, D., Yang, Y., Övgün, A., Long, Z.W., Xu, Z.: Gravitational ringing and superradiant instabilities of the Kerr-like black holes in a dark matter halo. Eur. Phys. J. C 83, 565 (2023). https://doi.org/10.1140/ epjc/s10052-023-11739-w 12 3 International Journal of Theoretical Physics (2023) 62:209 209 Page 24 of 26 209 Page 24 of 26 Page 24 of 26 209 23. Li, P.C., Lee, T.C., Guo, M., Chen, B.: Correspondence of Eikonal Quasinormal Modes and Unstable Fundamental Photon Orbits for a Kerr-Newman Black Hole. Phys. Rev. D 104, 084044 (2021). https:// doi.org/10.1103/PhysRevD.104.084044 g y 24. Bryant, A., Silva, H.O., Yagi, K., Glampedakis, K.: Eikonal Quasinormal Modes of Black Holes beyond General Relativity. III. Scalar Gauss-Bonnet Gravity. Phys. Rev. D 104, 044051 (2021). https://doi.org/ 10.1103/PhysRevD.104.044051 25. Konoplya, R.A., Zinhailo, A.F., Stuchlík, Z.: Quasinormal Modes, Scattering, and Hawking Radiation in the Vicinity of an Einstein-Dilaton-Gauss-Bonnet Black Hole. Phys. Rev. D 99, 124042 (2019). https:// doi.org/10.1103/PhysRevD.99.124042 g y 26. References B 829, 137114 (2022). https://doi. org/10.1016/j.physletb.2022.137114 40. Kumar, R., Ghosh, S.G.: Rotating Black Holes in 4D Einstein-Gauss-Bonnet Gravity and Its Shadow. J. Cosmol. Astropart. Phys. 2020, 53 (2020). https://doi.org/10.1088/1475-7516/2020/07/053 41. Heydari-Fard, M., Heydari-Fard, M.: Null Geodesics and Shadow of 4D Einstein-Gauss-Bonnet Black Holes Surrounded by Quintessence. Int. J. Mod. Phys. D 31,(2022). https://doi.org/10.1142/ S0218271822500663 42. Kruglov, S.I.: Einstein-Gauss-Bonnet Gravity with Nonlinear Electrodynamics: Entropy, Energy Emis- sion. Quasinormal Modes and Deflection Angle. Symmetry. 13, 944 (2021). https://doi.org/10.3390/ sym13060944 y 43. Churilova, M.S.: Quasinormal Modes of the Test Fields in the Consistent 4D Einstein-Gauss-Bonnet- (Anti)de Sitter Gravity. Ann. Phys. 427, 168425 (2021). https://doi.org/10.1016/j.aop.2021.168425 44. Kumar, R., Islam, S.U., Ghosh, S.G.: Gravitational Lensing by Charged Black Hole in Regularized 4D Einstein-Gauss-Bonnet Gravity. Eur. Phys. J. C 80(12),(2020). https://doi.org/10.1140/epjc/s10052-020- 08606-3 123 International Journal of Theoretical Physics (2023) 62 :209 Page 25 of 26 209 Page 25 of 26 209 209 45. Atamurotov, F., Shaymatov, S., Sheoran, P., Siwach, S.: Charged Black Hole in 4D Einstein-Gauss-Bonnet Gravity: Particle Motion, Plasma Effect on Weak Gravitational Lensing and Centre-of-Mass Energy. J. Cosmol. Astropart. Phys. 2021, 045 (2021). https://doi.org/10.1088/1475-7516/2021/08/045 46. Zhang, C.Y., Zhang, S.J., Li, P.C., Guo, M.: Superradiance and Stability of the Regularized 4D Charged Einstein-Gauss-Bonnet Black Hole. J. High Energy Phys. 2020,(2020). https://doi.org/10.1007/ JHEP08(2020)105 47. Zhang, M., Zhang, C.M., Zou, D.C., Yue, R.H.: Phase Transition and Quasinormal Modes for Charged Black Holes in 4D Einstein-Gauss-Bonnet Gravity. Chinese Phys. C 45,(2021). https://doi.org/10.1088/ 1674-1137/abe19a 48. Papnoi, U., Atamurotov, F.: Rotating Charged Black Hole in 4D Einstein-Gauss-Bonnet Gravity: Photon Motion and Its Shadow. Phys. Dark Universe 35, 100916 (2022). https://doi.org/10.1016/j.dark.2021. 100916 49. Eslam Panah, B., Jafarzade, Kh., Hendi, S.H.: Charged 4D Einstein-Gauss-Bonnet-AdS Black Holes: Shadow, Energy Emission, Deflection Angle and Heat Engine. Nucl. Phys. B 961, 115269 (2020). https:// doi.org/10.1016/j.nuclphysb.2020.115269 g j p y 50. Liu, P., Niu, C., Zhang, C.Y.: Instability of Regularized 4D Charged Einstein-Gauss-Bonnet de-Sitter Black Holes *. Chinese Phys. C 45, 025104 (2021). https://doi.org/10.1088/1674-1137/abcd2d 51. Mishra, A.K.: Quasinormal Modes and Strong Cosmic Censorship in the Regularised 4D Einstein-Gau Bonnet Gravity. Gen. Relativ. Gravit. 52,(2020). https://doi.org/10.1007/s10714-020-02763-2 52. Chen, D., Gao, C., Liu, X., Yu, C.: The Correspondence between Shadow and Test Field in a Four- Dimensional Charged Einstein-Gauss-Bonnet Black Hole. Eur. Phys. J. C 81, 700 (2021). https://doi.org/ 10.1140/epjc/s10052-021-09510-0 pj 53. Baruah, A., Övgün, A., Deshamukhya, A.: Quasinormal Modes and Bounding Greybody Factors of GUP- corrected Black Holes in Kalb-Ramond Gravity. Ann. Phys. 455, 169393 (2023). References https://doi.org/10.1016/ j.aop.2023.169393 j p 54. Okyay, M., Övgün, A.: Nonlinear electrodynamics effects on the black hole shadow, deflection angle, quasinormal modes and greybody factors. JCAP 01, 009 (2022). https://doi.org/10.1088/1475-7516/ 2022/01/009 55. Yang, Y., Liu, D., Övgün, A., Long, Z.W., Xu, Z.: Probing hairy black holes caused by gravitational decoupling using quasinormal modes and greybody bounds. Phys. Rev. D 107, 064042 (2023). https:// doi.org/10.1103/PhysRevD.107.064042 g y 56. Schutz, B.F., Will, C.M.: Black Hole Normal Modes - A Semianalytic Approach. Astrophys. J. 291, L33 (1985). https://doi.org/10.1086/184453 57. Konoplya, R.A., Zhidenko, A., Zinhailo, A.F.: Higher Order WKB Formula for Quasinormal Modes and Grey-Body Factors: Recipes for Quick and Accurate Calculations. Class. Quantum Gravity 36, 155002 (2019). https://doi.org/10.1088/1361-6382/ab2e25 58. Iyer, S., Will, C.M.: Black-Hole Normal Modes: A WKB Approach. I. Foundations and Application of a Higher-Order WKB Analysis of Potential-Barrier Scattering. Phys. Rev. D 35, 3621 (1987). https://doi. org/10.1103/PhysRevD.35.3621 g y 59. Konoplya, R.A.: Quasinormal Behavior of the D-Dimensional Schwarzschild Black Hole and the Higher Order WKB Approach. Phys. Rev. D 68, 24018 (2003). https://doi.org/10.1103/PhysRevD.68.024018 59. Konoplya, R.A.: Quasinormal Behavior of the D-Dimensional Schwarzschild Black Hole and the Higher Order WKB Approach. Phys. Rev. D 68, 24018 (2003). https://doi.org/10.1103/PhysRevD.68.024018 60. Matyjasek, J., Opala, M.: Quasinormal Modes of Black Holes: The Improved Semianalytic Approach. 60. Matyjasek, J., Opala, M.: Quasinormal Modes of Black Holes: The Improved Semianalytic Approa Phys. Rev. D 96, 24011 (2017). https://doi.org/10.1103/PhysRevD.96.024011 61. Ferrari, V., Mashhoon, B.: New Approach to the Quasinormal Modes of a Black Hole. Phys. Rev. D 30, 295 (1984). https://doi.org/10.1103/PhysRevD.30.295 ( ) p g y 62. Berti, E., Cardoso, V., Starinets, A.O.: Quasinormal Modes of Black Holes and Black Branes. Class. Quantum Gravity 26, 163001 (2009). https://doi.org/10.1088/0264-9381/26/16/163001 63. Hatsuda, Y.: Quasinormal Modes of Black Holes and Borel Summation. Phys. Rev. D 101, 24008 (2020). https://doi.org/10.1103/PhysRevD.101.024008 64. Jansen, A.: Overdamped Modes in Schwarzschild-de Sitter and a Mathematica Package for the Numerical Computation of Quasinormal Modes. Eur. Phys. J. Plus 132, (2017). https://doi.org/10.48550/arXiv.1709. 09178 65. Övgün, A., Sakalli, I., Mutuk, H.: Quasinormal Modes of DS and AdS Black Holes: Feedforward Neu- ral Network Method. Int. J. Geom. Methods Mod. Phys. 18, 2150154 (2021). https://doi.org/10.1142/ S0219887821501541 66. Cardoso, V., Miranda, A.S., Berti, E., Witek, H., Zanchin, V.T.: Geodesic Stability, Lyapunov Exponents, and Quasinormal Modes. Phys. Rev. D 79, 064016 (2009). https://doi.org/10.1103/PhysRevD.79.064016 Ö 66. Cardoso, V., Miranda, A.S., Berti, E., Witek, H., Zanchin, V.T.: Geodesic Stability, Lyapunov Exponents, and Quasinormal Modes. Phys. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References Rev. D 79, 064016 (2009). https://doi.org/10.1103/PhysRevD.79.064016 67. Pantig, R.C., Mastrototaro, L., Lambiase, G., Övgün, A.: Shadow, lensing, quasinormal modes, greybody bounds and neutrino propagation by dyonic ModMax black holes. Eur. Phys. J. C 82, 1155 (2022). https:// doi.org/10.1140/epjc/s10052-022-11125-y 67. Pantig, R.C., Mastrototaro, L., Lambiase, G., Övgün, A.: Shadow, lensing, quasinormal modes, greybody bounds and neutrino propagation by dyonic ModMax black holes. Eur. Phys. J. C 82, 1155 (2022). https:// doi.org/10.1140/epjc/s10052-022-11125-y 123 12 209 Page 26 of 26 209 Page 26 of 26 Page 26 of 26 International Journal of Theoretical Physics (2023) 62:209 209 P 209 68. Churilova, M.S.: Analytical Quasinormal Modes of Spherically Symmetric Black Holes in the Eiko Regime. Eur. Phys. J. C 79, 629 (2019). https://doi.org/10.1140/epjc/s10052-019-7146-0 Á 69. Panotopoulos, G., Rincón, Á.: Quasinormal Modes of Black Holes in Einstein-Power-Maxwell Theory. Int. J. Mod. Phys. D 27, (2018). https://doi.org/10.1142/S0218271818500347 y ( ) p g 70. Konoplya, R.A., Stuchlík, Z., Zhidenko, A.: Massive Nonminimally Coupled Scalar Field in Reissner- Nordström Spacetime: Long-Lived Quasinormal Modes and Instability. Phys. Rev. D 98,(2018). https:// doi.org/10.1103/PhysRevD.98.104033 g y 71. Guo, M., Li, P.C.: Innermost Stable Circular Orbit and Shadow of the 4D Einstein-Gauss-Bonnet Bl Hole. Eur. Phys. J. C 80,(2020). https://doi.org/10.1140/epjc/s10052-020-8164-7 72. Jusufi, K.: Connection between the Shadow Radius and Quasinormal Modes in Rotating Spacetimes. Phys. Rev. D 101, 124063 (2020). https://doi.org/10.1103/PhysRevD.101.124063 y p g y 73. Yang, H.: Relating Black Hole Shadow to Quasinormal Modes for Rotating Black Holes. Phys. Rev. D 103, 084010 (2021). https://doi.org/10.1103/PhysRevD.103.084010 73. Yang, H.: Relating Black Hole Shadow to Quasinormal Modes for Rot 103, 084010 (2021). https://doi.org/10.1103/PhysRevD.103.084010 p g y 74. Li, P.C., Lee, T.C., Guo, M., Chen, B.: Correspondence of Eikonal Quasinormal Modes and Unstable Fundamental Photon Orbits for a Kerr-Newman Black Hole. Phys. Rev. D 104, 084044 (2021). https:// doi.org/10.1103/PhysRevD.104.084044 123
https://openalex.org/W4312329770
http://ejournal.unp.ac.id/students/index.php/fis/article/download/11961/4993
English
null
The Effect of Variation in SiMn/PS Nanocomposite Composition on Hydrophobic Properties
Pillar of Physics Education : Jurnal Berkala Ilmiah Pendidikan Physics/Pillar of Physics Education : Jurnal Berkala Ilmiah Pendidikan Fisika
2,021
cc-by
3,608
ABSTRACT Many researches on hydrophobic synthesis have been carried out on coatings, but there are stillshortcomings, for example, the coating is easily scratched, easily corroded and damaged by contact with other materials, thereby reducing the quality of the coating. This can diminish the use of hydrophobic coatings in industry and others. Therefore, it is necessary to develop a hydrophobic coating that is strong, durable, and not- corrosion so that the quality of a surface can be improved.For this reason, research is carried out by mixinga substrate that hashard properties such as manganese and non-corrosive such as silica to conquer the problems that occurred previously by utilizing the spin coating method. The precursor was prepared by adding 0.5 grams of polystyrene, with varying SiMn compositions. The coating was carried out by utilizing the spin coating method using an oven for 1 hours ata calcination temperature was 60oC. The results of the research from this composition variation shows that the SiMn/PS nanocomposite layer is hydrophobic depending on the contact angle test. The composition of 50%:50% is the largest contact angel with a large contact angle of 104.7°. Keywords : hydrophobic, Silica Oxide (SiO2), Manganese (Mn), polystyrene, contact angle, durability, nanocomposite. This is an open access article distributed under the Creative Commons 4.0 Attribution License, which permits unrestricted use, distribution, and reproductio in any medium, provided the original work is properly cited. ©2021 by author and Universitas Negeri Padang. Sisi Gusti Putri1, Ratnawulan1* 1 Department of Physics,Padang State University, Jalan Prof. Dr. Hamka, Air Tawar Barat, Padang, West Sumatra, 25171. Indonesia Corresponding author. Email:ratnawulan320@fmipa.unp.ac.id Sisi Gusti Putri1, Ratnawulan1* 1 Department of Physics,Padang State University, Jalan Prof. Dr. Hamka, Air Tawar Barat, Padang, West Sumatra, 25171. Indonesia Corresponding author. Email:ratnawulan320@fmipa.unp.ac.id This is an open access article distributed under the Creative Commons 4.0 Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ©2021 by author and Universitas Negeri Padang. There are several steps taken: There are several steps taken: Sample preparation stage, the synthesis of silica and manganese nanoparticles byweighing 8 grams of silica and manganeseand then groundfor 5 hours for silica and 16 hours for manganese using HEM-E3D. The next step is the manufacture of Silica Manganese/Polystyrene precursor by dissolving 0.5 grams of polystyrene in 15 ml of tetrahydrofuran using a magnetic stirrer at a temperature of 500C. Then mix it with SiMn with a varied composition where the composition used is 20%: 80%, 40%: 60%, 50%: 50%, 60%: 40%, 80%:20% with the amount of SiMn 0.4 grams, then stirred for 1 hour using a magnetic stirrer until homogeneous. The next step is sample preparation by preparing glass preparations with a size of 0.5cm x 0.5cm and 1cm x 1cm then washing using an ultrasonic cleaner by soaking the glass in a solution of PEG and aquadest for 2 hours [9]. The next step is to make a thin layer using a spin coating by doing a Spin Coating by placing a glass substrate and then dripping it with a prepared SiMn/PS solution, then rotating it at a speed of 500 rpm for 60 seconds. Furthermore, the manganese silica nanocomposite layer formed was heated in an oven at 60ºC for 1 hour. Thentake photo for contact angle using camera in dark room. Then to measure the contact angle using ImageJ software. Here's how the ImageJ software looks and works [10]. Fig.1. ImageJ Software Display For the contact angle measurement, in the file tool select the picture to be measured, the image will appear then select the angle tool, after that between the water droplet and the surface draw a straight line, then drag the line upwards to form an angle between the droplet and the sample surface [11]. Fig.1. ImageJ Software Display Fig.1. ImageJ Software Display Fig.1. ImageJ Software Display Fig.1. ImageJ Software Display For the contact angle measurement, in the file tool select the picture to be measured, the image will appear then select the angle tool, after that between the water droplet and the surface draw a straight line, then drag the line upwards to form an angle between the droplet and the sample surface [11]. Fig.2. Measuring Contact Angle Fig.2. Measuring Contact Angle Fig.2. Measuring Contact Angle The contact angle is identified by, select Analyze then choose Maesure, the contact angle result will be appeared. 𝐶𝑜𝑛𝑡𝑎𝑐𝑡 𝑎𝑛𝑔𝑙𝑒= 𝑟𝑖𝑔h𝑡 𝑐𝑜𝑛𝑡𝑎𝑐𝑡 𝑎𝑛𝑔𝑒𝑙+ 𝑙𝑒𝑓𝑡 𝑐𝑜𝑛𝑡𝑎𝑐𝑡 𝑎𝑛𝑔𝑒𝑙 2 (1) (1) After that the data is deciphered as a diagram. The impact of temperature on the contact angle can be determined by plotting the data on the X and Y coordinates utilizing the Microsoft Excel program. The general technique used to plot data on an XY graph is that the independent variable is plotted on the X axis and the dependent variable is plotted on the Y axis [13]. I. INTRODUCTION Currently, research on hydrophobic surfaces has been carried out by many other researchers. However, the results obtained still have many shortcomings such as easy to scratch and easy to corrode. Consequently, the advancement of a strong and durable hydrophobic coating and resistance to corrosion in an efficient and easy method is direly required. A surface can be supposed to be hydrophobic if it has specificproperties. The hydrophobic nature has anti- wet properties witha big contact angel of 90ºC [1]. To determine the hydrophobicity of a surface,it can be done by the angle formed between the glass surface coated by the SiMn nanocomposite and the water as well as by measuring the contact angle [2]. A hydrophobic surface has a contact angle between 90°-150°,whereas a contact angle >150° is called superhydrophobic [3]. Silica is a metal oxide compound that is broadly found in nature, silica alsohas anti-corrosion properties [4]. The arrangement of atoms in amorphous silica has a low degree of regularity and occurs randomly. Therefore, the silica sand purification process to remove impurities needs to be carried out [5]. Manganese is an element that has a grayish black color and is one of the plentiful abundant elements found in the earth's crust [6]. Manganese ore has the potential to be developed as an industrial material along with technological advances [7]. Nanocomposite is a matrix with dimensions of 1.0 x 10-9 m. For the production of coatings, polystyrene polymers are used. This polystyrene is impervious to acids, bases and other rusty materials [8]. There are several methods used for this purpose, for examplephase separation,electrochemical reactions, sol- gel,sin coating, dip coating, filler particles and coprecipitation. Spin-couting method is used to make SiMn/PS nanocomposite layers, because this method is easy to do and can make a homogeneous layer. The coating matrix is polystyrene because it is resistant to acids, bases and other rust materials [7] other rust materials [7] Submitted: .2021-8-27 Accepted: 2021-12-20 Published: .2021-12-28 Pillar of Physics, page. | 53 Putri, et al II. METHOD This study examines the effect of variations in the composition of SiMn/PS nanocomposites on hydrophobic properties. This type of research is an experiment conducted at the Materials Physics Laboratory and Biophysics and Chemistry Laboratory, Faculty of Mathematics and Natural Sciences, Padang State University. the materials used are silica, manganese, polystyrene (PS), tetrahydrofuran (THF) and aquadest. The equipment used is a beaker, measuring cup, magnetic stirrer, oven, furnace, spin coating, glass, camera, FTIR and XRD, SEM. There are several steps taken: Then, calculate the average after making repeated measurements [12]. Next, analysis stage the contact angle acquired from the measurement of the composition of the SilicaManganese/Polystyrene (SiMn/PS) nanocomposite layer, the analysis can be calculated by the accompanying equation : Next, analysis stage the contact angle acquired from the measurement of the composition of the nganese/Polystyrene (SiMn/PS) nanocomposite layer, the analysis can be calculated by the accompanying 𝐶𝑜𝑛𝑡𝑎𝑐𝑡 𝑎𝑛𝑔𝑙𝑒= 𝑟𝑖𝑔h𝑡 𝑐𝑜𝑛𝑡𝑎𝑐𝑡 𝑎𝑛𝑔𝑒𝑙+ 𝑙𝑒𝑓𝑡 𝑐𝑜𝑛𝑡𝑎𝑐𝑡 𝑎𝑛𝑔𝑒𝑙 2 (1) III. RESULTS AND DISCUSSION The result of this study is the identification of the contact angle taken from measurements on a thin layer of Silica Manganese/Polystyrene (SiMn/PS) nanocomposite with composition variations of 20%: 80%, 40%: 60%, Pillar of Physics, page. | 54 Putri, et al 50%: 50%, 60%: 40 % and 80%:20%. measuring the contact angle can be done using the image-j application which can be seen in Figure 3 and the results can be seen in Table 1 for composition of nanokomposite SiMn 20%:80% 50%: 50%, 60%: 40 % and 80%:20%. measuring the contact angle can be done using the image-j application which can be seen in Figure 3 and the results can be seen in Table 1 for composition of nanokomposite SiMn 20%:80% Fig.3. Contact Angle Measurement with 20%:80% SiMn composition variation Table 1. Result of contact angle measurement with 20%:80% SiMn composition variation Fig.3. Contact Angle Measurement with 20%:80% SiMn composition variation Table 1. Result of contact angle measurement with 20%:80% SiMn composition variation Fig.3. Contact Angle Measurement with 20%:80% SiMn composition variation Table 1. Result of contact angle measurement with 20%:80% SiMn composition variation Contact Angel Measurement Results The Calculation Results Θright θLeft Θ 92.245 o 92.072 o 92.158 92.726 o 91.513 o 92.119 92.984 o 91.441 o 92.212 92.821 o 91.122 o 91.971 92.153 o 91.214 o 91.686 Average 92.029 In the Table 1 it can be seen that the composition of the 20%:80% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 92.029°. Which can be seen in Figure 4 and the results can be seen in Table 2 For composition of SiMn 40%:60% In the Table 1 it can be seen that the composition of the 20%:80% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 92.029°. Which can be seen in Figure 4 and the results can be seen in Table 2 For composition of SiMn 40%:60% Fig.4. Contact Angle Measurement with 40%:60% SiMn composition variation Table 2. Result of contact angle measurement with 40%:60% SiMn composition variation Fig.4. Contact Angle Measurement with 40%:60% SiMn composition variation Table 2. In the table 2 it can be seen that the composition of the 40%:60% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 97.511°. Which can be seen in Figure 5 and the results can be seen in Table 3 for composition of SiMn 50%:50% III. RESULTS AND DISCUSSION Result of contact angle measurement with 40%:60% SiMn composition variation g p Contact Angel Measurement Results The Calculation Results θRight θLeft Θ 97.063 o 97.326 o 97.194 97.634 o 97.474 o 97.554 97.884 o 97.627 o 97.755 97.462 o 97.608 o 97.746 97.379 o 97.235 o 97.307 Average 97.511 In the table 2 it can be seen that the composition of the 40%:60% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 97.511°. Which can be seen in Figure 5 and the results can be seen in Table 3 for composition of SiMn 50%:50% Contact Angel Measurement Results The Calculation Results θRight θLeft Θ 97.063 o 97.326 o 97.194 97.634 o 97.474 o 97.554 97.884 o 97.627 o 97.755 97.462 o 97.608 o 97.746 97.379 o 97.235 o 97.307 Average 97.511 2 it can be seen that the composition of the 40%:60% SiMn nanocomposite is already hydrophobic Contact Angel Measurement Results The Calculation Results θRight θLeft Θ 97.063 o 97.326 o 97.194 97.634 o 97.474 o 97.554 97.884 o 97.627 o 97.755 97.462 o 97.608 o 97.746 97.379 o 97.235 o 97.307 Average 97.511 In the table 2 it can be seen that the composition of the 40%:60% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 97.511°. Which can be seen in Figure 5 and the results can be seen in Table 3 for composition of SiMn 50%:50% Pillar of Physics, page. | 55 Putri, et al Fi 5 C t t A l M t ith 50% 50% SiM iti i ti Fig.5. Contact Angle Measurement with 50%:50% SiMn composition variation Table 3. Result of contact angle measurement with 50%:50% SiMn composition variation Table 3. Result of contact angle measurement with 50%:50% SiMn composition variation Contact Angel Measurement Results The Calculation Results Θright θLeft Θ 104.986 o 105.457 o 105.221 o 104.484 o 104.339 o 104.411 o 105.287 o 105.097 o 105.197 o 104.706 o 104.925 o 104.817 o 104.321 o 103.389 o 103.855 o Average 104.7 o In the table 3 it can be seen that the composition of the 50%:50% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 104.7°. which can be seen in Figure 6 and the results can be seen in Table 4 for composition of SiMn 60%:40% Fig.6. In the table 4 it can be seen that the composition of the 60%:40% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 95.629°. Which can be seen in Figure 7 and the results can be seen in Table 5 for composition of SiMn 80%:20% III. RESULTS AND DISCUSSION Contact Angle Measurement with 60%:40% SiMn composition variation Fig.6. Contact Angle Measurement with 60%:40% SiMn composition variation Table 4. Result of contact angle measurement with 60%:40% SiMn composition variation Table 4. Result of contact angle measurement with 60%:40% SiMn composition variation Contact Angel Measurement Results The Calculation Results θ Right θLeft Θ 96.459 o 95.811 o 95.635 95.816 o 95.474 o 95.645 96.282 o 94.627 o 95.477 95.711 o 95.608 o 95.659 96.226 o 95.235 o 95.730 Average 95.629 In the table 4 it can be seen that the composition of the 60%:40% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 95.629°. Which can be seen in Figure 7 and the results can be seen in Table 5 for composition of SiMn 80%:20% Contact Angel Measurement Results The Calculation Results θ Right θLeft Θ 96.459 o 95.811 o 95.635 95.816 o 95.474 o 95.645 96.282 o 94.627 o 95.477 95.711 o 95.608 o 95.659 96.226 o 95.235 o 95.730 Average 95.629 In the table 4 it can be seen that the composition of the 60%:40% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 95.629°. Which can be seen in Figure 7 and the results can be seen in Table 5 for composition of SiMn 80%:20% In the table 4 it can be seen that the composition of the 60%:40% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 95.629°. Which can be seen in Figure 7 and the results can be seen in Table 5 for composition of SiMn 80%:20% Pillar of Physics, page. | 56 Putri, et al Fig.7. Contact Angle Measurement with 80%:20% SiMn composition variation Fig.7. Contact Angle Measurement with 80%:20% SiMn composition variation Table 5. Result of contact angle measurement with 80%:20% SiMn composition variation Table 5. Result of contact angle measurement with 80%:20% SiMn composition variation Contact Angel Measurement Results The Calculation Results θ Right θLeft Θ 92.141 o 92.729 o 92.435 92.675 o 91.567 o 92.121 92.102 o 92.775 o 92.438 92.548o 91.546 o 92.047 92.027 o 91.346 o 91.686 Average 92.146 In the table 5 it can be seen that the composition of the 80%:20% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 92.146° which can be seen in Figure 8. III. RESULTS AND DISCUSSION | 57 Putri, et al 4000 3500 3000 2500 2000 1500 1000 500 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 %Tranmitansi cm -1 Komposisi SiMn 80%:20% Komposisi SiMn 60%:40% Komposisi SiMn 50%:50% Komposisi SiMn 40%:60% Komposisi SiMn 20%:80% Fig. 9. FTIR measurement result data Fig. 9. FTIR measurement result data FTIR serves in the Figure 9 to show the infrared spectrum that contains the presence of functional groups in the sample. In testing the surface of the coating with the composition of SiMn 20%:80%, 40%:60%, 50%:50%, 60%:40%, 80%:20%. These results show that the functional groups are present in the composition of SiMn 40%: 60% and SiMn 50%: 50. The absorption peak in the wave number region of 540.51 cm-1 comes from the Mn-O bond stretch (MO: 400-560 cm-1), 767.69 cm-1 comes from the Si-O stretch with a range of 782 - 805 cm -1. Which shows the absorption peak is observed at the wave number 1641.11cm-1 C=C group, in the form of a double carbon bond. Furthermore, the wavelength of 919.53cm-1 indicates the presence of bonds between carbon and hydrogen atoms with the C-H functional group. From the data above, it shows that the group is in the composition of SiMn 50%:50% and SiMn 40%:60%.In the composition of SiMn 40%: 60% and SiMn 50%: 50% there are several very significant main absorption bands located at wave number 547.49 cm-1indicating the Mn-O bond stretch, the CH functional group at wave numbers 919.50 cm-1, 751.58 cm-1comes from the Si-O stretch with a range of 782 - 805 cm-1 IV. CONCLUSION Based on the research that has been done, it can be concluded that the SiMn composition affects the contact angle and has shown a hydrophobic layer where the contact angle exceeds 90°. And the highest contact angle is found in the composition of SiMn 50%:50% with a contact angle of 104.7°. III. RESULTS AND DISCUSSION In the table 5 it can be seen that the composition of the 80%:20% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 92.146° which can be seen in Figure 8. In the table 5 it can be seen that the composition of the 80%:20% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 92.146° which can be seen in Figure 8. In the table 5 it can be seen that the composition of the 80%:20% SiMn nanocomposite is already hydrophobic because the resulting angle is >90° with a large angle of 92.146° which can be seen in Figure 8. Fig.8. Relationship Between Composition Variation and Contact Angle Measurement 85 90 95 100 105 110 20%:80% 40%:60% 50%:50% 60%:40% 80%:20% Sudut Kontak (º) Komposisi SiMn Fig.8. Relationship Between Composition Variation and Contact Angle Measurement Fig.8. Relationship Between Composition Variation and Contact Angle Measurement Based on the data in the Figure 8 obtained from the contact angle of the water droplets with the surface layer, 5 variations of composition were used, according to [4] polymers without the addition of nanoparticles had weak strength. Polymers mixed with nanoparticles will have a stronger and tighter structure. So, to make a hydrophobic coating using polystyrene, the composition of silica and manganese nanoparticles is added to it, here will be seen the effect of variations in the composition of nanoparticles on the contact angle of the hydrophobic layer, where the composition of SiMn nanoparticles used is 20%: 80%, 40%: 60, respectively. %, 50%:50%, 60%:40% and 80%:20%. After going through the tests and measurements, it was found that the contact angles were not too different between the five variations of the silica composition, the contact angles had sizes of 92.029°, 97.511°, 104.7°, 95.629°, 92.146° so that it can be said that the composition of silica and manganese nanoparticles in the SiMn nanocomposite /polystyrene affects the magnitude of the contact angle, and the five variations have been successfully made hydrophobic. Where the highest contact angle is found in the 50%:50% SiMn composition, which is 104.7°. And the lowest is in the composition of SiMn 20%:80% with a contact angle of 92.029° which can be seen in Figure 9. Pillar of Physics, page. REFERENCES D. Feng, Lin, “Super – Hydrophobic Surfaces From Natural to Artifical. Advanced Materials,” vol. 14,. [1] D. Feng, Lin, “Super – Hydrophobic Surfaces From Natural to Artifical. Advanced Materials,” vol. 14,. [2] D. Ensikat, Hans J, Superhydrophobicity in perfection the outstanding properties of the lotus leaf .Beilstein. 2011. [2] D. Ensikat, Hans J, Superhydrophobicity in perfection the outstanding properties of the lotus leaf .Beilstein. 2011. [3] C. H. Lee, K.I., Kim, Y.J., Lee, H.J., and Lee, , Cocoa Has More Phenolic Phytochemical and Higher Antioxidant Capacity than Theas and Red Wine, J. Agric. Food Chem. 2003. [3] C. H. Lee, K.I., Kim, Y.J., Lee, H.J., and Lee, , Cocoa Has More Phenolic Phytochemical and Higher Antioxidant Capacity than Theas and Red Wine, J. Agric. Food Chem. 2003. p y g Y. dkk Hou, “The Association between Self-perceptions of Aging and Anti hypertensive Medicatio Adherence in Older Chinese Adults.AgingClinical and Experimental Research,” pp. 1–8, 2015. [5] Q. Xu, Xianghui, Zhaozhu Zhang, Fang Guo, Jin Yang, Xiaotao Zhu. Xiaoyan Zhou, “FabricationOfBionicSuperhydrophobicManganeseOxide/Polystyrene Nanocomposite Coating.,” J. Bionic Eng., pp. 11–17, 2012. [5] Q. Xu, Xianghui, Zhaozhu Zhang, Fang Guo, Jin Yang, Xiaotao Zhu. Xiaoyan Zhou, “FabricationOfBionicSuperhydrophobicManganeseOxide/Polystyrene Nanocomposite Coating.,” J. Bionic Eng., pp. 11–17, 2012. g pp R. Putri, T. A., Ratnawulan, “Sintesis Lapisan Hydrophobic Nanokomposit Mangan Oksida/Polystyren (MnO2/PS) Untuk Aplikasi Self Cleaning,” J.Pillar ofPhysics, 2018. ( ) p g, f y , [7] A. A. Setiawati, T., Amalia, I. S., Sulistioso, G. S., &Wisnu, “SintesisLapisan Tipis TiO2 danAnalisisSifatFotokatalisnya.,” Jurnalsainsmateriindonesia, pp. 141–146, 2019. [8] D. Hildayati, Sintesis dan Karakterisasi Bahan Komposit Karet Alam Silika. 2009. [9] D. Bhusan, Bharat, Micro-nano-and hierarchica structures for superhydrophobicity, self-cleaning an adhesion. 2009. [10] E. M. Harper, C. A., Petrie, Plastics Materials and Processes: A Concise Encycclopedia. 2003. [11] K. B. dan R. Maheshwari, Lotus-Inspired Nanotechnology Applications. 2008. p gy pp [12] P. J. P. dan Ratnawulan, “Analisis Sifat Fisis Bijih Mangan Hasil Proses Sinteryang Terdapat Di Nagari Kiawai Kecamatan Gunung Tuleh Kabupaten Pasaman Barat,” 2014. [13] R. Szostak, “Mollecular Sieves: Principles of Synthesis and Identification,” Springer, 1998. Pillar of Physics, page. | 58
W4233635266.txt
https://sajp.co.za/index.php/sajp/article/download/990/1195
fr
Book Reviews
South African journal of physiotherapy
1,965
cc-by
1,092
Reproduced by Sabinet Gateway under licence granted by the Publisher (dated 2013.) Page 12 March, 1965 P H Y S I O T H E R A P Y BOOK REVIEWS REHABILITATION MEDICINE. By Howard A. Rusk, M.D., Professor and Chairman of Physical Medicine and Rehabilitation, New York University—Bellvue Medical Center, New York, 2nd Edition, Publishers: Mosby. This new edition of Krusen’s book furnishes an impressive presentation of basic rehabilitation principles and procedures correlated with their clinical application. Comprehensive in scope, it is a well balanced blend of theoretical and clinical information. It serves as a guide through the complexities ot rehabilita­ tion and contains accurate, up-to-date descriptions of the current concepts and practice employed at the renowned Department of Physical Medicine and Rehabilitation at the New York U n i v e r s i t y — Bellvue Medical Center in New York City. It discusses the philosophy and need for re­ habilitation and the principles of therapeutic exercise and muscle re-education. It deals with specific problems such as metabolic diseases, neurological disorders, cancer, pul­ monary problems, musculosceletal problems, paraplegia or quadriplegia. Its discussions of the rehabilitation problems of children and geriatric patients are among the most defini­ tive in print and incorporate the medical, social, vocational and physiological aspects. Obtainable from Medical Distributors, P.O. Box 3378, Johannesburg at a cost of R13.25. CONCEPTS IN REHABILITATION OF THE HANDI­ CAPPED. By Dr. Krusen. Published by Saunders. Here is a brief unique new book written by one of the leading Specialists in the field of Physical Medicine and Rehabilitation which should be of interest to all Physio­ therapists. It describes the challenge of rehabilitation and today’s response. It explains the development of the re­ habilitation team, of modern practice, and of research. The author also outlines the unsolved problems, touching on both immediate and long-range needs. Trends now developing in rehabilitation of the handicapped are described, and a final chapter recommends the broad actions which should be taken promptly—to help the disabled patient. Physiotherapists will find in this book much helptul information on managing their chronically ill and seriously disabled patients. Dr. Krusen’s explanation of the need for increased co­ operation and understanding between physiotherapist, surgeon, psychiatrist, the social worker, and the occupational therapist indicates what comprehensive rehabilitation of a handicapped patient can really mean and accomplish. The book is obtainable from Medical Distributors, P.O. Box 3378, Johannesburg, at a cost of R0.85. VERTEBRAL MANIPULATION. By G. D. Maitland, A.U.A. Published by Butterworth & Co. Ltd., 1964. 146 pages. Price R3.75, plus 15 cents delivery charge. Butterworth & Co. (South Africa) Ltd., 33-35 Beach Grove, Durban, Natal. P.O. Box 792, Durban. Phone 23867 and 62094. Mr. Maitland, who is a member of the Chartered Society of Physiotherapy and of the Australian Physiotherapy Association, has made a thorough study of the techniques of spinal manipulation. He was influenced in this thinking by Mennell, Cyriax and Stoddard, but has retained his own sound, objective and individual approach. He favours the more gentle type of oscillating movement done at the limit of the range, as advocated by Dr. Mennell, particularly as a basis for teaching physiotherapy students and as a starting technique in clinical practice. He prefers to call them techni­ ques of “mobilization” rather than “ manipulation” as he considers the latter to be a more forceful, less localized manoeuvre. In doing so, he supports the welcome recent trend among physiotherapists to regard manipulation as a form of passive movement, carried out with equal gentle­ ness, safety, knowledge and control to those passive move­ ments that have been used by physiotherapists for several decades. He also discusses the place of traction and mani­ pulative techniques in the clinical field. He states that physiotherapists treat only cases referred for manipulation by a medical practitioner who has exam­ ined the patient and diagnosed the disorder as suitable. The techniques selected by the physiotherapist are based upon signs and symptoms, and a reassessment of these is made after each procedure. The manoeuvres are carried out without discomfort to the patient, gently at first; only after a thorough assessment, trial manoeuvre and reassessment calls for a more forceful manipulation is this attempted. By using this approach, he renders manipulation as safe as massage, and in fact safer than some exercises used as a routine in all physiotherapy departments. To quote from the preface: “The text has been planned to lead the reader in logical sequence from the examination of the different inter-vertebral levels, to the techniques of mobilization applicable in each case. The way is then prepred for the further development into the more forceful manipulative procedures and their application. Guiding principles of treatment follow, and are then applied to specific case histories in the final chapter.” The diagrams, and also the tables which illustrate the primary uses of the techniques and the sequence of selection are useful. A comprehensive index concludes a book which must surely be welcomed by all physiotherapists interested in the field of vertebral manipulation. It is the first textbook on the subject written by a physiotherapist. Mr. Maitland is a part-time tutor in physiotherapy at the University of Adelaide, Australia. He has always been very aware of the problems of teaching vertebral manipulations. Teachers of physiotherapy should therefore welcome this reference book, particularly as the new, revised syllabus of training for the Chartered Society of Physiotherapy, and the proposed revised syllabus for the National Diploma in Physiotherapy in South Africa both include manipulative techniques. B.W. BOOKS RECEIVED THE A.B.C.’s OF ATHLETIC INJURIES AND CON­ DITIONING. By Alfred Barnett Ferguson Jr. and Jay Bender. Published by The Williams and Wilkins Company, Baltimore 2, Maryland, U.S.A., 1964. Price $9.25. Review to follow on above publication. Vacancies UNITED CEREBRAL PALSY ASSOCIATION OF SOUTH AFRICA CLINIC IN KLERKSDORP, W. TRANSVAAL Physiotherpist required. Full particulars write to: The Secretary, P.O. Box 1097, Klerksdorp, Western Transvaal. Phone 2-5102. ST. GILES REHABILITATION CENTRE, SALISBURY, RHODESIA Physiotherapist required at St. Giles Rehabilitation Centre, Salisbury, Rhodesia. Experience in Cerebral Palsy essential. Salary according to experience. Write P.O. Box A 224, Avondale, Salisbury, Rhodesia. PHYSIOTHERAPIST Applications are invited for the post of part-time physio­ therapist at the Gold Fields East Native Hospital, Dunnottar. Apply to:— The Senior Medical Officer, P.O. Box 14, Dunnottar, Telephone 734-2135. PRIVATE PRACTICE, EAST LONDON Assistant Physiotherapist (female) required in private practice in East London, to commence 1st May, or later. Good salary, with bonus paid half-yearly, and pleasant working conditions. Partnership offered to suitable applicant. Write to Miss P.. Chatterton, M.C.S.P., 24 St. James’ Road, East London.
https://openalex.org/W4241236285
https://www.qeios.com/read/2S9SYW/pdf
English
null
Estimated Glomerular Filtration Rate
Definitions
2,020
cc-by
81
Qeios · Definition, February 2, 2020 Open Peer Review on Qeios Open Peer Review on Qeios Estimated Glomerular Filtration Rate National Cancer Institute Qeios ID: 2S9SYW · https://doi.org/10.32388/2S9SYW Source National Cancer Institute. Estimated Glomerular Filtration Rate. NCI Thesaurus. Code C110935. A laboratory test that estimates kidney function. It is calculated using an individual's serum creatinine measurement, age, gender, and race. Actual results are reported when the estimated glomerular filtration rate is less than 60 ml/min. Qeios ID: 2S9SYW · https://doi.org/10.32388/2S9SYW 1/1
https://openalex.org/W2050211942
http://dea.lib.unideb.hu/bitstreams/9846d0ab-a076-4d8f-a11e-7152b837e025/download
English
null
PRIMA-1MET induces nucleolar translocation of Epstein-Barr virus-encoded EBNA-5 protein
Molecular cancer
2,009
cc-by
8,431
BioMed Central BioMed Central PRIMA-1MET induces nucleolar translocation of Epstein-Barr virus-encoded EBNA-5 protein Address: 1Department of Microbiology, Tumor and Cell Biology (MTC), Karolinska Institute, S-171 77 Stockholm, Sweden, 2Karolinska Institute Visualization Core Facility (KIVIF), Karolinska Institute, S-171 77 Stockholm, Sweden, 3Center for Integrative Recognition in the Immune System (IRIS), Karolinska Institute, S-171 77 Stockholm, Sweden, 4Swedish Center for Disease Control (SMI), S-171 82 Solna, Sweden and 5Deptarment of Oncology-Pathology, Cancer Center Karolinska (CCK), Karolinska Institute, S-171 76 Stockholm, Sweden Email: György Stuber - Gyorgy.Stuber@ki.se; Emilie Flaberg - Emilie.Flaberg@ki.se; Gabor Petranyi - Gabor.Petranyi@ki.se; Rita Ötvös - rotvos@freemail.hu; Nina Rökaeus - Nina.Rokaeus@ki.se; Elena Kashuba - Elena.Kashuba@ki.se; Klas G Wiman - Klas.Wiman@ki.se; George Klein - Georg.Klein@ki.se; Laszlo Szekely* - Laszlo.Szekely@ki.se * Corresponding author * Corresponding author Received: 10 April 2008 Accepted: 26 March 2009 Published: 26 March 2009 Molecular Cancer 2009, 8:23 doi:10.1186/1476-4598-8-23 This article is available from: http://www.molecular-cancer.com/content/8/1/23 © 2009 Stuber et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Molecular Cancer Open Access Page 1 of 12 (page number not for citation purposes) Introduction The precise role of EBNA-5 in the virus induced transfor- mation has nor yet been established. It binds to p14ARF- hMDM2-p53 complexes. Forced overexpression of p14ARF leads to the formation of extranucleolar inclu- sions with subsequent entrapment of hMDM2, p53 and EBNA-5 [6,12-14]. Epstein-Barr virus (EBV) is the most powerful transform- ing agent of human cells. EBV infected resting B cells undergo blast transformation and develop into immortal lymphoblastoid cell lines (LCLs) in vitro or into immuno- blastic lymphomas in immunocompromised host. Nine latent viral proteins are expressed regularly in the trans- formed cells: the nuclear antigens, EBNA1–6, and three membrane proteins, LMP-1, -2a and -2b. Six of these pro- teins are required for immortalization: EBNA-1, -2, -3 (3A), -5 (LP), -6 (3C) and LMP-1 [1,2] PRIMA-1 has been identified through differential screen- ing of the structural diversity set of the NCI chemical library, as a drug that selectively induces apoptosis in mutant p53 bearing human tumor cells but not in their p53 -/- counterparts [15]. Treatment with PRIMA-1 sup- presses the growth of mutant p53 expressing human tumor xenografts in vivo [16,17]. PRIMA-1 can restore the transcriptional transactivating function of certain p53 mutants and induce p53 dependent apoptosis [15]. EBNA-5 and EBNA-2 are the first two viral proteins expressed in newly infected cells [3]. The co-expression of EBNA-2 and EBNA-5 plays an important role already at the first steps of EBV induced transformation by driving resting B cells into the cell cycle [4]. The co-operation between EBNA-2 and EBNA-5 is needed for the activation of LMP-1 and Cp viral promoters [5]. Recently, we have shown that PRIMA-1MET, a methylated derivative of the original PRIMA with improved pro-apop- totic activity, causes nucleolar translocation of mutant p53 and of PML, CBP and Hsp70. The level of Hsp70 was significantly increased by PRIMA-1MET treatment. The nucleolar accumulation of PML, CBP and Hsp70 was much more efficient in cells with mutant p53 as com- pared to p53-/- cells [18]. PRIMA-Dead, a compound structurally related to PRIMA-1MET but unable to induce mutant p53-dependent apoptosis, failed to induce nucle- olar translocation of mutant p53. These results suggested that redistribution of mutant p53 to nucleoli plays a role in PRIMA-1MET induced apoptosis. EBNA-5 preferentially accumulates in distinct nuclear foci in EBV-transformed lymphoblastoid cell lines. We have previously shown that these foci are inside the PML bod- ies [6]. Introduction We have also shown that the same foci contained the retinoblastoma (Rb) protein and the heat shock pro- tein, Hsp70 [7]. Artificial spreading of the chromatin by exposure to the forces of fluid surface tension disrupted the co-localization gradually. It showed that EBNA-5 is located in the inner core of the bodies whereas PML formed the rigid outer shell [6]. Considering the intimate relationship between EBNA-5 and the p53 pathway as well as the obvious similarities between the proteasome inhibitor and PRIMA-1MET induced nucleolar translocation of p53, PML and Hsp70, we have now investigated the effect of PRIMA-1MET on the subcellular distribution of EBNA-5. Here we show that PRIMA-1MET induces the nucleolar translocation of both virus encoded endogenous and transfected exogenous EBNA5 and its fluorescent derivatives GFP-EBNA5 and DSRed-EBNA-5. Nuclear bodies with prominent PML staining are seen in uninfected resting B lymphocytes. This staining pattern does not change upon EBV infection. In freshly infected cells EBNA-5 is diffusely distributed throughout the nucleoplasm but after a few days gradually relocate to the PML bodies and remains there in established lymphoblas- toid cell lines [8]. The localization of EBNA-5 to PML bod- ies is restricted to EBV- infected human lymphoblasts. Exogenously expressed EBNA-5 in any other cell lines dis- tributes homogeneously in the nucleoplasm [9]. Heat shock or high cell density induced metabolic stress leads to the translocation of EBNA-5 to the nucleoli both from the PML bodies or from the nucleoplasm [10]. Sub- sequently we found that proteasome inhibitors induced also nucleolar translocation of EBNA-5 in both LCLs and transfected cell lines. They also induced nucleolar translo- cation of Hsp70 protein and mutant p53. Translocation of the later was enhanced by the presence of EBNA-5 [9]. In a separate study, we have shown that proteasome inhibi- tors can induce nucleolar translocation of various compo- nents of the PML body and nuclear/nucleolar accumulation of proteasomes [11]. Abstract The low molecular weight compound, PRIMA-1MET restores the transcriptional transactivation function of certain p53 mutants in tumor cells. We have previously shown that PRIMA-1MET induces nucleolar translocation of p53, PML, CBP and Hsp70. The Epstein-Barr virus encoded, latency associated antigen EBNA-5 (also known as EBNA-LP) is required for the efficient transformation of human B lymphocytes by EBV. EBNA-5 associates with p53-hMDM2-p14ARF complexes. EBNA- 5 is a nuclear protein that translocates to the nucleolus upon heat shock or inhibition of proteasomes along with p53, hMDM2, Hsp70, PML and proteasome subunits. Here we show that PRIMA-1MET induces the nucleolar translocation of EBNA-5 in EBV transformed B lymphoblasts and in transfected tumor cells. The PRIMA-1MET induced translocation of EBNA-5 is not dependent on the presence of mutant p53. It also occurs in p53 null cells or in cells that express wild type p53. Both the native and the EGFP or DSRed conjugated EBNA-5 respond to PRIMA-1MET treatment in the same way. Image analysis of DSRed-EBNA-5 expressing cells, using confocal fluorescence time- lapse microscopy showed that the nucleolar translocation requires several hours to complete. FRAP (fluorescence recovery after photobleaching) and FLIP (fluorescence loss in photobleaching) measurements on live cells showed that the nucleolar translocation was accompanied by the formation of EBNA-5 aggregates. The process is reversible since the aggregates are dissolved upon removal of PRIMA-1MET. Our results suggest that mutant p53 is not the sole target of PRIMA-1MET. We propose that PRIMA-1MET may reversibly inhibit cellular chaperons that prevent the aggregation of misfolded proteins, and that EBNA-5 may serve as a surrogate drug target for elucidating the precise molecular action of PRIMA-1MET. Page 1 of 12 (page number not for citation purposes) Page 1 of 12 (page number not for citation purposes) http://www.molecular-cancer.com/content/8/1/23 Molecular Cancer 2009, 8:23 http://www.molecular-cancer.com/content/8/1/23 http://www.molecular-cancer.com/content/8/1/23 Page 2 of 12 (page number not for citation purposes) PRIMA-1MET-treatment and immunofluorescence staining PRIMA-1MET-treatment and immunofluorescence staining The monoclonal mouse antibody JF186 was used against EBNA-5 [19] and the MAb used against B23/nucleophos- min was a gift from P. K. Chan, Baylor College of Medi- cine, Houston, USA. The cells were cultured on cover slips in six-well plates until they have reached a density of 5 × 104 cells/cm2 and incubated for 24 h in the presence of 50 μM PRIMA-1MET dissolved in dimethylsulphoxide (DMSO). Cells treated with DMSO were used as controls. Cells were fixed with methanol-acetone (1:1) at -20°C and then were re-hydrated in phosphate-buffered saline (PBS) for 30 min. Antibodies were diluted in blocking buffer (2% bovine serum albumin, 0.2% Tween-20, 10% glycerol in PBS). The cells were stained with primary MAbs for 1 h at room temperature, followed by three washes in PBS, incubated with secondary FITC or Texas red-conjugated antibodies, washed three times and mounted with 80% glycerol solution in PBS containing 2·5% 1,4-diazabicyclo-(2.2.2)octane (Sigma). Bisbenz- imide (Hoechst 33258) was added at a concentration of 0·4 μg/ml to the secondary antibody for DNA staining. Photokinetic measurements of recombinant EBNA-5 in live cells To measure the intracellular mobility of EBNA-5 in differ- ent intranuclear compartments of treated and control cells we used an Ultraview RS five line laser Nipkow spinning disc confocal system with a CSU22 Yokogawa head (Per- kin Elmer) assembled on a Nikon inverted fluorescence microscope. To achieve pixel precise bleaching of selected areas a galvanometric Photokinesis unit (Perkin Elmer) with separate laser input was installed between the Ultraview unit and the photoport of the microscope. The timelapse 4D imaging with single (FRAP) and repeated (FLIP) bleach cycles was carried out with the Ultraview capture software (Perkin Elmer). The captured images were quantified using the analytic routines of the Ultraview program as well as the program ImageJ (Ras- band, W.S., ImageJ, U. S. National Institutes of Health, Bethesda, Maryland, USA, http://rsb.info.nih.gov/ij/). For FRAP and FLIP studies DSRed-EBNA-5 expressing cells were grown on the bottom glass of a POC Mini chamber. The selected areas were bleached using the 568 nm line of an Argon-Krypton laser. In a typical FRAP recording two prebleach images were followed by 100 bleach cycles (total 300–1000 ms) and the recovery was measured by a series of 500 ms exposition over 1 to 3 minutes (120–360 http://www.molecular-cancer.com/content/8/1/23 http://www.molecular-cancer.com/content/8/1/23 Molecular Cancer 2009, 8:23 toward the oil immersion objective, was prevented by the use of a separate objective heather ring. Both the control- ler block and the heater ring were controlled by a com- mon electric thermostate. The four dimensional image capture was carried out using the custom developed soft- ware "FiveColorMovie" written by us, using the Openlab Automator visual programming environment (Improvi- sion). To ensure the maintenance of proper focal plane during the extended imaging periods we have developed an autofocusing program module that uses recursive min- imum/maximum intensity measurements at 100 separate small squares of a matrix overlayed on the gaussian blurred cental region of interest (ROI) of the raw image. To find the focus, series of short (50 microsecond) expo- sitions are made at different Z axis positions that are clus- tered around the last used focal plane, and extended in height that is twice the length of the imaging stack. The section with the greatest difference between the minimum and maximum intensity values is selected as sharpest. The Z position of the sharpest image then serves as the central point for the consequent capturing of 10 images arranged in a Z stack with exposition times in the range of 500 to 1000 milliseconds. To conveniently capture several hun- dreds of multicolour images along the time axis the indi- vidual Z stacks were collapsed "on-the-fly" using maximum intensity projection algorithm. By saving the images after every 200 time points the program assures that the image capture process is not limited by the RAM but by the available hard disc space. 175), SW480, a colorectal cancer line with mutant p53 (Arg to His 273 and Pro to Ser 309). MCF-7, a breast car- cinoma line bearing wild-type p53. Clones of MCF-7 and SW480 lines (S2 carrying EBNA-5 and P2 vector control), constitutively expressing EBNA-5 from a pBabe-EBNA-5 construct were generated using selection with 1 μg/ml puromycin (Sigma). MCF7 cells constitutively expressing DsRed_EBNA-5 were selected on 1 mg/ml G418 (Sigma). 175), SW480, a colorectal cancer line with mutant p53 (Arg to His 273 and Pro to Ser 309). MCF-7, a breast car- cinoma line bearing wild-type p53. Clones of MCF-7 and SW480 lines (S2 carrying EBNA-5 and P2 vector control), constitutively expressing EBNA-5 from a pBabe-EBNA-5 construct were generated using selection with 1 μg/ml puromycin (Sigma). MCF7 cells constitutively expressing DsRed_EBNA-5 were selected on 1 mg/ml G418 (Sigma). Methods Cell cultures All cell lines were grown in Iscove's cell culture medium supplemented with 10% heat-inactivated FBS, 2 mM L- glutamine, 100 U/ml penicillin and 100 U/ml streptomy- cin. The cells were passaged every fourth day 1:5. Cultures were regularly tested for the absence of mycoplasma with Hoechst 33258 staining. Transfections were done using Lipofectamine Plus reagent (GibcoBRL) according to the manufacturer's instructions. In the present study the fol- lowing cell lines were used: LSsp, EBV transformed lym- phoblastoid B-cell line, H1299 lung adeno carcinoma line (p53 -/-) and its mutant p53 transfected subline (with His Page 2 of 12 (page number not for citation purposes) Page 2 of 12 (page number not for citation purposes) Constructs GFP-EBNA-5 was made by cloning an EBNA-5-encoding BamHI-EcoRI fragment from pBabe-EBNA-5, containing four W repeats and the unique C-terminal region, into BglII-EcoRI-cleaved pEGFP-N1 [13]. To produce red fusion protein EBNA-5 was amplified with primers containing NheI-EcoRI 5'overhangs. The cleaved PCR product was cloned into the corresponding sites of pDsRed1-N1 vector (Clontech). Immunofluorescence staining of EBNA-5 in fixed cells Immunofluorescence staining of EBNA-5 in fixed cells To study the effect of PRIMA-1MET on the subcellular local- ization of EBNA-5, EBV transformed lymphoblastoid cell lines and EBNA-5 transfected tumor cells were treated with various concentrations of the drug for 24 hours. Beside native EBNA-5 we have also used EBNA-5 conju- gated to the C-terminus of the fluorescence protein EGFP or DSRed. Upon completion of the treatment the cells were fixed with methanol:aceton and stained with the monoclonal anti-EBNA-5 antibody JF186. We found that 12–24 hours treatment with 50 uM PRIMA-1MET induced nucleolar translocation of EBNA-5 in all cell lines such as the lymphoblastoid cells LSsp expressing virus encoded endogenous EBNA-5 (Figure 1) and transfected tumor cell lines such as the colon carci- noma line SW480 (endogenous mutant p53; Figure 2), the breast carcinoma line MCF7 (wt p53) and the lung adeno-carcinoma line H1299 (p53 null cells) as well as its transfected variant expressing mutant p53 (His175). The identity of the nucleolus was ascertained by B23 staining and/or phasecontrast imaging in parallel. PRIMA-1MET-induced translocation of exogenous EBNA-5 in mutant p53 carrying SW480 colon carcinoma cells after 24 hours treatment Figure 2 PRIMA-1MET-induced translocation of exogenous EBNA-5 in mutant p53 carrying SW480 colon carci- noma cells after 24 hours treatment. Immunofluores- cence staining of EBNA-5 is green, DNA staining using Hoecsht 33258 is blue. PRIMA-1MET-induced translocation of exogenous EBNA-5 in mutant p53 carrying SW480 colon carcinoma cells after 24 hours treatment Figure 2 PRIMA-1MET-induced translocation of exogenous EBNA-5 in mutant p53 carrying SW480 colon carci- noma cells after 24 hours treatment. Immunofluores- cence staining of EBNA-5 is green, DNA staining using Hoecsht 33258 is blue. Distribution of DSRed-EBNA-5 in the nucleus of a living MCF7 cell that carries wild type p53 Figure 3 Distribution of DSRed-EBNA-5 in the nucleus of a liv- ing MCF7 cell that carries wild type p53. Single confocal section selected from the middle of a series of 21 images. In untreated, transfected cells EBNA-5 localized to the low DNA density areas corresponding to the euchromatin (Figure 3). It was either absent from the nucleolus or if present its level did not exceed the amount in the nucleo- plasm (Additional file 1 and additional file 2). Live cell microscopy Long term live cell fluorescence imaging was carried out in POC Mini chambers. The DSRed-EBNA-5 expressing cells were grown on the round cover glass insert of the POC Mini chamber (Carl Zeiss), The chambers were loaded with 400 ul cell culture medium and were used in fully closed mode. The imaging was carried out on an Ultraview LCI three line laser Nipkow spinning disc con- focal microscope system with a CSU10 Yokogawa head (Perkin Elmer) assembled on a Zeiss Axiovert motorized microscope. During the imaging the temperature was maintained at 37 C with the help of heat controller block covered with a transparent plexi shield. The heat loss, Page 3 of 12 (page number not for citation purposes) Page 3 of 12 (page number not for citation purposes) Molecular Cancer 2009, 8:23 http://www.molecular-cancer.com/content/8/1/23 PRIMA-1MET-induced translocation of exogenous EBNA-5 in mutant p53 carrying SW480 colon carcinoma cells after 24 hours treatment Figure 2 PRIMA-1MET-induced translocation of exogenous EBNA-5 in mutant p53 carrying SW480 colon carci- noma cells after 24 hours treatment. Immunofluores- cence staining of EBNA-5 is green, DNA staining using Hoecsht 33258 is blue. images). In the FLIP experiments the bleach cycles were followed by the capture of ten images and then the bleach cycles were repeated several times. Page 4 of 12 (page number not for citation purposes) Immunofluorescence staining of EBNA-5 in fixed cells In the PRIMA-1MET-induced translocation of virus encoded endog- eneous EBNA-5 in the Epstein-Barr virus transformed human lymphoblastoid cell line LSsp that carries virus encoded EBNA-5 and harbors wild type p53 Figure 1 PRIMA-1MET-induced translocation of virus encoded endogeneous EBNA-5 in the Epstein-Barr virus transformed human lymphoblastoid cell line LSsp that carries virus encoded EBNA-5 and harbors wild type p53. 24 hours treatment with 50 uM PRIMA-1MET leads to the disappearance of EBNA-5 from the PML bodies and to relocation to the nucleolus. PRIMA-1MET-induced translocation of virus encoded endog- eneous EBNA-5 in the Epstein-Barr virus transformed human lymphoblastoid cell line LSsp that carries virus encoded EBNA-5 and harbors wild type p53 Figure 1 PRIMA-1MET-induced translocation of virus encoded endogeneous EBNA-5 in the Epstein-Barr virus transformed human lymphoblastoid cell line LSsp that carries virus encoded EBNA-5 and harbors wild type p53. 24 hours treatment with 50 uM PRIMA-1MET leads to the disappearance of EBNA-5 from the PML bodies and to relocation to the nucleolus. PRIMA-1MET-induced translocation of virus encoded endog- eneous EBNA-5 in the Epstein-Barr virus transformed human lymphoblastoid cell line LSsp that carries virus encoded EBNA-5 and harbors wild type p53 Figure 1 PRIMA-1MET-induced translocation of virus encoded endogeneous EBNA-5 in the Epstein-Barr virus transformed human lymphoblastoid cell line LSsp that carries virus encoded EBNA-5 and harbors wild type p53. 24 hours treatment with 50 uM PRIMA-1MET leads to the disappearance of EBNA-5 from the PML bodies and to relocation to the nucleolus. Distribution of DSRed-EBNA-5 in the nucleus of a living MCF7 cell that carries wild type p53 Figure 3 Distribution of DSRed-EBNA-5 in the nucleus of a liv- ing MCF7 cell that carries wild type p53. Single confocal section selected from the middle of a series of 21 images. Distribution of DSRed-EBNA-5 in the nucleus of a living MCF7 cell that carries wild type p53 Figure 3 Distribution of DSRed-EBNA-5 in the nucleus of a liv- ing MCF7 cell that carries wild type p53. Single confocal section selected from the middle of a series of 21 images. Page 4 of 12 (page number not for citation purposes) Page 4 of 12 (page number not for citation purposes) http://www.molecular-cancer.com/content/8/1/23 Molecular Cancer 2009, 8:23 treated cells there was an overall increase of EBNA-5 levels with a very prominent increase in the nucleolus. Immunofluorescence staining of EBNA-5 in fixed cells After 20 hours of treatment almost all diffuse nucleoplasmic EBNA-5 signal was concentrated in numerous distinct foci evenly distributed throughout the entire nucleus. microscopy method, developed by us, for live cell imaging (see Materials and Methods). The technique permits con- tinuous recording of living cells using a combination of fluorescence and phase contrast illumination over several (6–24) hours. We found that the cells tolerated excellently the combination of 568 nm epifluorescence and 600 nm transmitted phase contrast illumination. On the other hand using shorter wavelengths (405 and 488 nm) always led to visible phototoxic effects during prolonged experi- ments. Imaging cells stably transfected with DSRed- EBNA-5 revealed that EBNA-5 that was originally evenly distributed in the nucleoplasm successively accumulated in the nucleoli between 6 and 10 hours after the PRIMA- 1MET treatment (Figure 4 and Additional file 4). EBNA-5 accumulation was associated with the formation of 15–20 round or ovoid particles of the size of 250–300 nm that showed limited movement inside the nucleolus. The nucleolar accumulation has regularly started from a single focus in a given nucleolus. Different nucleoli started the process at different time. Some nucleoli showed up to four hours delay as compared to the earliest accumulating nucleoli in the same nucleus. After 10 hours treatment with PRIMA-1MET the nucleoli became saturated with To test the possible influence of EBNA-5 on the survival rate of PRIMA-1MET treated cells we have compared wild type and mutant p53 carrying cells stably transfected with EBNA-5 and their vector controls. PRIMA-1MET treatment had no effect on the survival rate of wild type p53 carrying MCF7 breast carcinoma cells with or without EBNA-5 at any PRIMA-1MET concentrations, although the cells showed prominent nucleolar translocation of EBNA-5. Comparing EBNA5 transfected (S2) and vector control transfected (P2) SW480 colon carcinoma cells that express mutant P53 we found that the presence of EBNA-5 slightly sensitized to the PRIMA-1MET effect. (Additional file 3). Page 5 of 12 (page number not for citation purposes) Kinetics of nucleolar translocation of DS-redEBNA5 cells in PRIMA-1MET treated cells To study the dynamics of PRIMA-1MET induced nuclear movements of EBNA-5 we used an automated confocal Time lapse series of PRIMA-1MET-induced translocation of DSRed-EBNA-5 in stably transfected MCF7 cells Figure 4 Time lapse series of PRIMA-1MET-induced translocation of DSRed-EBNA-5 in stably transfected MCF7 cells. Images at 1 hour interval were selected from a series of 720 images recorded in every minutes for 12 hours. p y g Time lapse series of PRIMA-1MET-induced translocation of DSRed-EBNA-5 in stably transfected MCF7 cells. Images at 1 hour interval were selected from a series of 720 images recorded in every minutes for 12 hours. Page 5 of 12 (page number not for citation purposes) Molecular Cancer 2009, 8:23 http://www.molecular-cancer.com/content/8/1/23 http://www.molecular-cancer.com/content/8/1/23 http://www.molecular-cancer.com/content/8/1/23 EBNA-5. At this point some of the brightly fluorescent DSRed-EBNA-5 particles were released from the nucleolus and moved around in the nucleoplasm by rapid Brownian movement (Additional file 5). The nucleolar accumula- tion was also accompanied by an overall increase of DSRed-EBNA-5 fluorescence intensity (Figure 5). Treatment with PRIMA-1MET led to the accumulation of DSRed-EBNA-5 in well-defined granules in the nucleolus with very low molecular mobility. In other words, repeated bleaching of adjacent nucleoplasmic areas, sepa- rate DSRed-EBNA-5 positive foci in the same nucleolus or even part of the same granules failed to induce any signif- icant loss of fluorescence in the non-bleached structures (Figure 7). EBNA-5. At this point some of the brightly fluorescent DSRed-EBNA-5 particles were released from the nucleolus and moved around in the nucleoplasm by rapid Brownian movement (Additional file 5). The nucleolar accumula- tion was also accompanied by an overall increase of DSRed-EBNA-5 fluorescence intensity (Figure 5). Effect of PRIMA-1MET on the mobility of DSRed-EBNA-5 We carried out FRAP and FLIP analysis on untreated and PRIMA-1MET-treated, DSRed-EBNA-5 transfected MCF7 cells to measure the rate of mobility of EBNA-5 in differ- ent nuclear sub-compartments. In the untreated control cells the bulk of DSRed-EBNA-5 was homogenously dis- tributed throughout the nucleoplasm. This fraction showed very high mobility. Using single bleaching FRAP with 2 um spot size the average half recovery time (T 1/2) was 1.5 second that corresponds to a diffusion coefficient of 0.66 um2/s. In comparison the calculated mobility in free solution would be 54.6 um2/s. After 20 hours of treatment DSRed-EBNA-5 in addition to the nucleolar aggregates formed rigid bodies evenly scat- tered in the nucleoplasm. Kinetics of nucleolar translocation of DS-redEBNA5 cells in PRIMA-1MET treated cells FLIP showed that these bodies contained DSRed-EBNA-5 with similar low exchange mobility as the nucleolar aggregates. These bodies showed also relatively rapid translational Brownian movement similarly to the ones released from overfilled nucleoli. An important distinction however from the former was that the nucleoplasmic bodies were somewhat larger (400 nm versus 300 nm) and their movement trajectories were much more restricted (Figure 7 and Additional file 7). Whereas the bodies released from the nucleolus could travel to any area of euchromatin the bodies that were pre- cipitated out at the later time point in the nucleoplasm moved within a well-defined sphere of 800–1200 nm. After 24 hours of treatment the nucleoplasmic bodies increased in size but not in number (Additional file 8). Imaging the fluorescence loss in the non-illuminated areas (FLIP) showed a rapid depletion of the homogene- ous signal from the entire nucleoplasm. The minor popu- lation of nucleolar DSRed-EBNA-5 in the non-treated cells showed a higher resistance to FLIP. The nucleolar DSRed- EBNA-5 was localized to distinct separated areas inside the nucleolus. Using pixel precise bleaching of the indi- vidual areas in FRAP experiments we could identify two levels of recovery one intermediate (T 1/2 21 second) and one very slow (T 1/2 >> 300 s). The presence of the two separate nucleolar subcompartment was also confirmed by FLIP experiments. (Figure 6 and Additional file 6) Reversibility of PRIMA-1MET induced aggregation of DSRed-EBNA-5 PRIMA-1MET regularly induces apoptosis in mutant p53 expressing cells. To explore the possibility whether the protein aggregation phenomenon is a feature advanced stage cellular agony we have treated DSRed-EBNA-5 expressing, p53 -/-, H1299 cells with PRIMA-1MET for 12 hours. These cells are much less sensitive to PRIMA-1MET induced apoptosis than its mutant p53 expressing deriva- tives. The drug treatment induced nucleolar accumulation of the protein in most nucleoli. Removing PRIMA-1MET by repeated washing with drug free medium led to the com- plete dissolution of the aggregates as it could be demon- strated by combined fluorescent/phase contrast time lapse microscopy. No cytopathic effects were detected at any time during the experiment (Figure 8). PRIMA-1MET treatment leads to an overall increase of DSRed- EBNA-5 levels as shown by plotting the average fluorescence intensity against time of the 720 frames shown in Figure 4 after background subtraction Figure 5 PRIMA-1MET treatment leads to an overall increase of DSRed-EBNA-5 levels as shown by plotting the aver- age fluorescence intensity against time of the 720 frames shown in Figure 4 after background subtrac- tion. Page 6 of 12 (page number not for citation purposes) Discussion The most straightforward explanation of the observed effects is that PRIMA-1MET induces a gradual precipitation of EBNA-5. In untreated cells EBNA-5 moves around with high mobility in the nucleoplasm but slows down in the nucleolus. We suggest that this is due to the mechanical sieving effect of the densely arranged chromatin fibers in the zona fibrillaris of the nucleolus (see Additional file 2 for illustration of the density of chromatin fibers in the nucleoplasm and in the nucleolus in a living cell nucleus). In our scenario the drug treatment induces gradual aggre- PRIMA-1MET treatment leads to an overall increase of DSRed- EBNA-5 levels as shown by plotting the average fluorescence intensity against time of the 720 frames shown in Figure 4 after background subtraction Figure 5 PRIMA-1MET treatment leads to an overall increase of DSRed-EBNA-5 levels as shown by plotting the aver- age fluorescence intensity against time of the 720 frames shown in Figure 4 after background subtrac- tion. PRIMA-1MET treatment leads to an overall increase of DSRed- EBNA-5 levels as shown by plotting the average fluorescence intensity against time of the 720 frames shown in Figure 4 after background subtraction Figure 5 PRIMA-1MET treatment leads to an overall increase of DSRed-EBNA-5 levels as shown by plotting the aver- age fluorescence intensity against time of the 720 frames shown in Figure 4 after background subtrac- tion. Page 6 of 12 (page number not for citation purposes) Page 6 of 12 (page number not for citation purposes) Molecular Cancer 2009, 8:23 http://www.molecular-cancer.com/content/8/1/23 Fluorescence loss in photobleaching (FLIP) experiment of untreated DSRed-EBNA-5 expressing MCF7 cells show very high mobility of homogeneously distributed DSRed-EBNA5 Figure 6 Fluorescence loss in photobleaching (FLIP) experiment of untreated DSRed-EBNA-5 expressing MCF7 cells show very high mobility of homogeneously distributed DSRed-EBNA5. Region of interest 1 (ROI 1) was bleached for 300 ms followed by recording of 10 consecutive images at 500 ms intervals. These cycles were repeated for 5 minutes. ROI 1 and 5, representing the total bleached area and a selected bleached subarea, showed rapid recovery of fluorescence. ROI 2, representing a remote non-bleached area in the nucleoplasm showed rapid homogeneous decrease of fluorescence. ROI 6 in adjacent cell showed no changes. ROI 3 and 4 in the nucleolus show two differently equilibrating compartment one faster (ROI 3) and one slower (ROI 4). Fluorescen mobility of Figure 6 The fluorescence images are combined with phase contrast pictures to demonstrate the intact cellular morphol- ogy of the cells during the entire length of the experiment. Conformational change due to mutation or thermal, acid- base or redox change that leads to increased surface expo- sition of otherwise cryptic hydrophobic side chains is the most usual cause of protein precipitation. Exposed hydro- phobic surfaces are potent inducers of cellular heat shock responses. Increased exposition of hydrophobic surfaces lead to increased expression of molecular chaperons that actively counteract the precipitation process, by isolating the misfolded proteins from each other and using the energy of hydrolyzed ATP for actively "massaging" their protein client back to a native conformation that repre- sents the lowest level of folding energy. Importantly mutant p53 was recently found in complex with Hsp90 in PRIMA-1MET treated cells [20]. Hsp90 is a major constitu- ent of the proteome, comprising up to 5% of the total mass of cellular proteins. It remains to be elucidated to what extent mutant p53 is associated with other, less abundant heat shock proteins in the presence and absence of PRIMA-1MET. It is well known however that mutant p53 often com- plexes with Hsp70 [21]. Association of Hsp70 and CHIP (carboxy terminus of Hsp70-interacting protein) is responsible for ubiquitination and degradation of some of the p53 mutants [22]. Our present findings suggest that PRIMA-1MET might act through reversible inhibition of cellular chaperon activity. In this scenario the aggregation of EBNA-5 (or mutant p53) would be prevented by the constitutive activity of Hsp70 type cellular chaperons. Inhibition of chaperon activity by PRIMA-1MET would lead to the accumulation of protein aggregates as well as a reac- tive increase of Hsp70 expression. The PRIMA 1 induced nucleolar translocation of DSRed EBNA 5 is reversible in the p53 / H1299 cells Figure 8 The PRIMA-1MET-induced nucleolar translocation of DSRed-EBNA-5 is reversible in the p53 -/- H1299 cells. The translocation was induced by 12 hours drug treat- ment followed by extensive washing with drug free medium. Time-lapse movie was recorded for 6 hours, one frame per minute. The fluorescence images are combined with phase contrast pictures to demonstrate the intact cellular morphol- ogy of the cells during the entire length of the experiment. Direct interaction with the Hsp70 family of chaperons is also a common denominator of EBNA-5 and mutant p53. Fluorescen mobility of Figure 6 Fluorescence loss in photobleaching (FLIP) experiment of untreated DSRed-EBNA-5 expressing MCF7 cells show very high mobility of homogeneously distributed DSRed-EBNA5 Figure 6 Fluorescence loss in photobleaching (FLIP) experiment of untreated DSRed-EBNA-5 expressing MCF7 cells show very high mobility of homogeneously distributed DSRed-EBNA5. Region of interest 1 (ROI 1) was bleached for 300 ms followed by recording of 10 consecutive images at 500 ms intervals. These cycles were repeated for 5 minutes. ROI 1 and 5, representing the total bleached area and a selected bleached subarea, showed rapid recovery of fluorescence. ROI 2, representing a remote non-bleached area in the nucleoplasm showed rapid homogeneous decrease of fluorescence. ROI 6 in adjacent cell showed no changes. ROI 3 and 4 in the nucleolus show two differently equilibrating compartment one faster (ROI 3) and one slower (ROI 4). Page 7 of 12 (page number not for citation purposes) Page 7 of 12 (page number not for citation purposes) http://www.molecular-cancer.com/content/8/1/23 Molecular Cancer 2009, 8:23 tment with PRIMA-1MET leads to the loss of mobility of DSRed-EBNA-5 in MCF7 cells as show atment with PRIMA-1MET leads to the loss of mobility of DSRed-EBNA-5 in MCF7 c ment. ROI 1 was bleached as above but showed no significant recovery. Adjacent ROI 2 and nificant loss of fluorescence. 20 hours treatment with PRIMA-1MET leads to the loss of mobility of DSRed-EBNA-5 in MCF7 cells as shown by FLIP experi- ment Figure 7 20 hours treatment with PRIMA-1MET leads to the loss of mobility of DSRed-EBNA-5 in MCF7 cells as shown by FLIP experiment. ROI 1 was bleached as above but showed no significant recovery. Adjacent ROI 2 and distant ROI 3 showed no significant loss of fluorescence. y y p g 20 hours treatment with PRIMA-1MET leads to the loss of mobility of DSRed-EBNA-5 in MCF7 cells as shown by FLIP experiment. ROI 1 was bleached as above but showed no significant recovery. Adjacent ROI 2 and distant ROI 3 showed no significant loss of fluorescence. Molecular Cancer 2009, 8:23 http://www.molecular-cancer.com/content/8/1/23 The PRIMA-1MET-induced nucleolar translocation of DSRed- EBNA-5 is reversible in the p53 -/- H1299 cells Figure 8 The PRIMA-1MET-induced nucleolar translocation of DSRed-EBNA-5 is reversible in the p53 -/- H1299 cells. The translocation was induced by 12 hours drug treat- ment followed by extensive washing with drug free medium. Time-lapse movie was recorded for 6 hours, one frame per minute. Additional file 1 Distribution of DSRed-EBNA-5 in the nucleus of MCF7 cell (corre- sponding to Figure3). In stably transfected cells DSRed-EBNA-5 is dis- tributed homogeneously in the euchromatin and in well-defined round spaces in the zona granulosa of the nucleolus. Importantly the fluorescence intensity of the fusion protein is the same in the nucleolar and in the nucleoplasmic fraction. Left side – Animation moving through a series of 21 confocal sections along the Z axis. Rigth side – 3D projection and 360° rotation of the maximum intensity projected images around the Y axis. PRIMA-1MET was identified as a low molecular weight compound that can enhance apoptosis in mutant p53 car- rying cells, compared to the p53 null parental cells. Most p53 mutants are in complex with Hsp70 proteins. We have recently shown that PRIMA-1MET treatment increases Hsp70 expression and nucleolar translocation, in parallel with the induction of nucleolar accumulation of mutant p53 [18]. Numerous experiments indicate that the increased apoptosis induction is accompanied by the acti- vation of p53 target genes [28-32]. Several lines of evi- dence suggest that PRIMA-1MET can also act independently of the p53 status of the cell. It can radiosensitize prostate carcinoma cell lines with mutant or wild type p53 and p53 -/- cells as well [33]. Introduction of mutant p53 (p53ser249 or p53gln248) into p53 -/- hepatocarcinoma cells increases sensitivity to PRIMA-1MET without the induction of p53 target genes [34]. Click here for file Click here for file [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S1.gif] Competing interests The authors declare that they have no competing interests. Additional file 3 PRIMA-1MET is a powerful apoptosis-inducing agent. Iden- tification of its targets is partly hindered by the difficulties to separate its effect from the numerous molecular changes associated with cellular agony subsequent to drug treatment. Here we show that subcellular distribution of EBNA-5 changes in parallel with mutant p53 itself upon PRIMA-1METtreatment. Similar changes in EBNA5 distri- bution occur in cells that lack p53 and are therefore resist- ant for p53 induced apoptosis. We propose that EBNA-5 may serve as a surrogate target that may help to elucidate the molecular action of PRIMA-1MET. Survival rate of PRIMA-1MET treated MCF7 (wtp53) and SW480 (mp53) cells in the presence and absence of EBNA-5. Click here for file [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S3.tiff] Survival rate of PRIMA-1MET treated MCF7 (wtp53) and SW480 (mp53) cells in the presence and absence of EBNA-5. Click here for file [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S3.tiff] Additional file 2 Six minutes time-lapse movie, showing DSRed-EBNA-5 in the nucleus of MCF7 cell. Single confocal section with sampling in every 2 seconds (122 timepoints). The movie shows that in the nucleoplasm DSRed- EBNA-5 fills up the space between the bundles of 300 nm chromatin fibres. The fiber bundles appear as dark shadows over the uniformly bright fluorescence background. The film also shows that the chromatin fibers are more densely packed area that corresponds to the fibrillar compartment of the nucleolus thus providing the structural basis for the postulated molec- ular sieve with small pore size. Click here for file [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S2.gif] Additional file 4 Time-lapse movie of PRIMA-1MET-induced nucleolar accumulation of DSRed-EBNA-5 in stably transfected MCF7 cells (corresponding to Figure4). The nucleolar accumulation starts non-synchronously in differ- ent nuclei between 3–9 hours after exposition to the drug. Click here for file [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S4.gif] Fluorescen mobility of Figure 6 The Hsp70 family members are also among the most potent anti-apoptotic agents that can block both the extrinsic (membrane signalling initiated) and the intrinsic (mitochondrial cytochrome C release initiated) pro-apop- totic signal pathways [23]. gation of EBNA-5 and the aggregates start to clog the nucleolar chromatin fiber meshwork. Heterogeneity in the sieving effect ("effective pore size") of different subnu- cleolar compartments or even between different nucleoli could explain the phenomena of: a.) focal initiation of nucleolar accumulation b.) nucleolar subcompartments with different mobility identified by FLIP c.) asynchro- nous accumulation of EBNA-5 in different nucleoli. Transformation of primary B-cells by EBV is dependent on the EBNA-2 induced activation of numerous viral and cel- lular genes [3,4,24,25]. EBNA-5 enhances this transactiva- tion. Hsp70 is a major complexing partner of EBNA-5 [26]. Elevated expression of Hsp70 increases, and sup- pressed expression of Hsp70 decreases the effect of EBNA- 5 on EBNA-2 mediated transactivation. It has been sug- gested that Hsp70 chaperon activity may help EBNA-5 in shuttling off repressors from EBNA2-enhanced promoters [27]. Along the same lines we also suggest that upon prolonged (20+ hours) treatment with PRIMA-1MET, the in situ fall- ing out of EBNA-5 precipitates in the nucleoplasm is due to the convergence between the size of the precipitated bodies and the sieving dimensions of the 300 nm chroma- tin fibre meshwork of the nucleoplasm. This is also con- sistent with the finding that nucleoplasmic EBNA-5 aggregates show spatially restricted and uniform random walk trajectories (Additional file 7 and Additional file 8). We have previously shown that inhibition of proteasome activity leads to synchronous nucleolar translocation of Page 9 of 12 (page number not for citation purposes) Page 9 of 12 (page number not for citation purposes) Molecular Cancer 2009, 8:23 http://www.molecular-cancer.com/content/8/1/23 Additional material mutant p53, EBNA-5 and Hsp70 in transfected SW480 cells. We have also shown that increased level of EBNA-5 enhanced the nucleolar translocation of mutant p53 [9]. More recently we found that the simultaneous presence of EBNA-5 and mutant p53 sensitizes cells for MG132 and bortezomib induced cytotoxicity (R. Ötvös et al, to be published). These data also suggest there is a close func- tional interplay between mutant p53 and EBNA-5. mutant p53, EBNA-5 and Hsp70 in transfected SW480 cells. We have also shown that increased level of EBNA-5 enhanced the nucleolar translocation of mutant p53 [9]. More recently we found that the simultaneous presence of EBNA-5 and mutant p53 sensitizes cells for MG132 and bortezomib induced cytotoxicity (R. Ötvös et al, to be published). These data also suggest there is a close func- tional interplay between mutant p53 and EBNA-5. References 1. Kieff E: Current perspectives on the molecular pathogenesis of virus-induced cancers in human immunodeficiency virus infection and acquired immunodeficiency syndrome. J Natl Cancer Inst Monogr 1998:7-14. 1. Kieff E: Current perspectives on the molecular pathogenesis of virus-induced cancers in human immunodeficiency virus infection and acquired immunodeficiency syndrome. J Natl Cancer Inst Monogr 1998:7-14. 21. Zylicz M, King FW, Wawrzynow A: Hsp70 interactions with the p53 tumour suppressor protein. Embo J 2001, 20:4634-4638. 22 M ll P H k R C b D L DP V k B Ch 22. Muller P, Hrstka R, Coomber D, Lane DP, Vojtesek B: Chaperone- dependent stabilization and degradation of p53 mutants. Oncogene 2008, 27(24):3371-83. g 2. Rickinson A: Epstein-Barr virus. Virus Res 2002, 82:109-113. g 2. Rickinson A: Epstein-Barr virus. Virus Res 2002, 82:109-113. 3. Alfieri C, Birkenbach M, Kieff E: Early events in Epstein-Barr virus infection of human B lymphocytes. Virology 1991, 181:595-608. g ( ) 23. Nylandsted J, Rohde M, Brand K, Bastholm L, Elling F, Jaattela M: Selective depletion of heat shock protein 70 (Hsp70) acti- vates a tumor-specific death program that is independent of caspases and bypasses Bcl-2. Proc Natl Acad Sci USA 2000, 97:7871-7876. 4. Sinclair AJ, Palmero I, Peters G, Farrell PJ: EBNA-2 and EBNA-LP cooperate to cause G0 to G1 transition during immortaliza- tion of resting human B lymphocytes by Epstein-Barr virus. Embo J 1994, 13:3321-3328. 24. Allan GJ, Inman GJ, Parker BD, Rowe DT, Farrell PJ: Cell growth effects of Epstein-Barr virus leader protein. J Gen Virol 1992, 73(Pt 6):1547-1551. 5. Harada S, Kieff E: Epstein-Barr virus nuclear protein LP stimu- lates EBNA-2 acidic domain-mediated transcriptional acti- vation. J Virol 1997, 71:6611-6618. 25. Mannick JB, Cohen JI, Birkenbach M, Marchini A, Kieff E: The Epstein-Barr virus nuclear protein encoded by the leader of the EBNA RNAs is important in B-lymphocyte transforma- tion. J Virol 1991, 65:6826-6837. J 6. Szekely L, Pokrovskaja K, Jiang WQ, de The H, Ringertz N, Klein G: The Epstein-Barr virus-encoded nuclear antigen EBNA-5 accumulates in PML-containing bodies. J Virol 1996, 70:2562-2568. 26. Mannick JB, Tong X, Hemnes A, Kieff E: The Epstein-Barr virus nuclear antigen leader protein associates with hsp72/hsc73. J Virol 1995, 69:8169-8172. 7. Jiang WQ, Szekely L, Wendel-Hansen V, Ringertz N, Klein G, Rosen A: Co-localization of the retinoblastoma protein and the Epstein-Barr virus-encoded nuclear antigen EBNA-5. Exp Cell Res 1991, 197:314-318. J 27. Additional file 6 Additional file 6 Time lapse movie of the FLIP experiment on non treated cells express- ing DSRed-EBNA-5 as presented in Figure6. Note the rapid loss of nucleoplasmic fluorescence in the non-bleached area of the targeted nucleus and the relative resistance of nucleolar fluorescence to FLIP effect, indicating the lower mobility DSRed-EBNA-5 in the nucleolar subcom- partments. 9. Pokrovskaja K, Mattsson K, Kashuba E, Klein G, Szekely L: Proteas- ome inhibitor induces nucleolar translocation of Epstein- Barr virus-encoded EBNA-5. J Gen Virol 2001, 82:345-358. 10. Szekely L, Jiang WQ, Pokrovskaja K, Wiman KG, Klein G, Ringertz N: Reversible nucleolar translocation of Epstein-Barr virus- encoded EBNA-5 and hsp70 proteins after exposure to heat shock or cell density congestion. J Gen Virol 1995, 76(Pt 10):2423-2432. [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S6.gif] ) 11. Mattsson K, Pokrovskaja K, Kiss C, Klein G, Szekely L: Proteins associated with the promyelocytic leukemia gene product (PML)-containing nuclear body move to the nucleolus upon inhibition of proteasome-dependent protein degradation. Proc Natl Acad Sci USA 2001, 98:1012-1017. Acknowledgements 19. Finke J, Rowe M, Kallin B, Ernberg I, Rosen A, Dillner J, Klein G: Mon- oclonal and polyclonal antibodies against Epstein-Barr virus nuclear antigen 5 (EBNA-5) detect multiple protein species in Burkitt's lymphoma and lymphoblastoid cell lines. J Virol 1987, 61:3870-3878. This work was supported by Cancerfonden, the Swedish Research Council, the Center for Integrative Recognition in the Immune System (IRIS) and the This work was supported by Cancerfonden, the Swedish Research Council, the Center for Integrative Recognition in the Immune System (IRIS) and the Karolinska Institutet (Sweden) as well as the Cancer Research Institute/ This work was supported by Cancerfonden, the Swedish Research Council, the Center for Integrative Recognition in the Immune System (IRIS) and the Karolinska Institutet (Sweden) as well as the Cancer Research Institute/ Cancer Foundation (USA). Cancer Foundation (USA). Cancer Foundation (USA). 20. Rehman A, Chahal MS, Tang X, Bruce JE, Pommier Y, Daoud SS: Pro- teomic identification of heat shock protein 90 as a candidate target for p53 mutation reactivation by PRIMA-1 in breast cancer cells. Breast Cancer Res 2005, 7:R765-774. Click here for file [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S7.gif] 15. Bykov VJ, Issaeva N, Shilov A, Hultcrantz M, Pugacheva E, Chumakov P, Bergman J, Wiman KG, Selivanova G: Restoration of the tumor suppressor function to mutant p53 by a low-molecular- weight compound. Nat Med 2002, 8:282-288. Additional file 8 Time lapse movie of treated cells 24 hours after the administration of PRIMA-1MET. Note the pronounced increase in the size of nucleoplasmic granules. Click here for file [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S8.gif] Time lapse movie of treated cells 24 hours after the administration of PRIMA-1MET. Note the pronounced increase in the size of nucleoplasmic granules. Time lapse movie of treated cells 24 hours after the administration of PRIMA-1MET. Note the pronounced increase in the size of nucleoplasmic granules. Click here for file [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S8.gif] 16. Bykov VJ, Issaeva N, Selivanova G, Wiman KG: Mutant p53- dependent growth suppression distinguishes PRIMA-1 from known anticancer drugs: a statistical analysis of information in the National Cancer Institute database. Carcinogenesis 2002, 23:2011-2018. Click here for file [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S8.gif] 17. Bykov VJ, Selivanova G, Wiman KG: Small molecules that reacti- vate mutant p53. Eur J Cancer 2003, 39:1828-1834. 18. Rokaeus N, Klein G, Wiman KG, Szekely L, Mattsson K: PRIMA- 1(MET) induces nucleolar accumulation of mutant p53 and PML nuclear body-associated proteins. Oncogene 2007, 26:982-992. Authors' contributions High resolution magnified image of a single nucleus from the movie of Additional file3. The movie shows that the accumulation of DSRed- EBNA-5 is starting non-synchronously in different nucleoli initiating from single foci. The movie also illustrates the escape of precipitated DSRed- EBNA-5 particles from the nucleolus and their travelling through the nucleoplasm by random Brownian movement. Click here for file Laboratory work, transfection, cell culturing and immu- nostaining was carried out by GS, PRIMA-1MET treatment was made by GS and NR, microscopic analysis and pro- gramming was performed by EF, GP and GS, viability assay upon MG132 and PRIMA-1MET treatment was per- formed by RÖ, DS-redE5 plasmid and transfection of MCF7 cells with it was made by EK. The experimental plan was conceived by KW GK and LS and it was evaluated by GK and LS. All the authors have read the manuscript and agreed with its content. [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S5.gif] Page 10 of 12 (page number not for citation purposes) Molecular Cancer 2009, 8:23 http://www.molecular-cancer.com/content/8/1/23 Additional file 6 Time lapse movie of the FLIP experiment on non treated cells express- ing DSRed-EBNA-5 as presented in Figure6. Note the rapid loss of nucleoplasmic fluorescence in the non-bleached area of the targeted nucleus and the relative resistance of nucleolar fluorescence to FLIP effect, indicating the lower mobility DSRed-EBNA-5 in the nucleolar subcom- partments. Click here for file [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S6.gif] Additional file 7 Time-lapse movie of the FLIP experiment on PRIMA-1MET- treated cell shown in Figure7. The movie clearly shows that there is no loss of fluo- rescence even in the immediate neighbourhood of the bleached area indi- cating complete immobilisation (precipitation) of DSRed-EBNA-5 upon drug treatment. Also observe the fine granular precipitates in the nucleo- plasm showing random Brownian movement restricted to the dimensions of the average distance between the nucleoplasmic chromatin fibers (as was illustrated in Additional file 2). Click here for file [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S7.gif] Additional file 8 Time lapse movie of treated cells 24 hours after the administration of PRIMA-1MET. Note the pronounced increase in the size of nucleoplasmic granules. Click here for file [http://www.biomedcentral.com/content/supplementary/1476- 4598-8-23-S8.gif] blasts and established lymphoblastoid cell lines differ in their Rb, p53 and EBNA-5 expression patterns. Oncogene 1995, 10:1869-1874. blasts and established lymphoblastoid cell lines differ in their Rb, p53 and EBNA-5 expression patterns. Oncogene 1995, 10:1869-1874. Additional file 7 Time-lapse movie of the FLIP experiment on PRIMA-1MET- treated cell shown in Figure7. The movie clearly shows that there is no loss of fluo- rescence even in the immediate neighbourhood of the bleached area indi- cating complete immobilisation (precipitation) of DSRed-EBNA-5 upon drug treatment. Also observe the fine granular precipitates in the nucleo- plasm showing random Brownian movement restricted to the dimensions of the average distance between the nucleoplasmic chromatin fibers (as was illustrated in Additional file 2). 12. Kashuba E, Mattsson K, Klein G, Szekely L: p14ARF induces the relocation of HDM2 and p53 to extranucleolar sites that are targeted by PML bodies and proteasomes. Mol Cancer 2003, 2:18. 13. Kashuba E, Mattsson K, Pokrovskaja K, Kiss C, Protopopova M, Ehlin- Henriksson B, Klein G, Szekely L: EBV-encoded EBNA-5 associ- ates with P14ARF in extranucleolar inclusions and prolongs the survival of P14ARF-expressing cells. Int J Cancer 2003, 105:644-653. 14. Szekely L, Selivanova G, Magnusson KP, Klein G, Wiman KG: EBNA- 5, an Epstein-Barr virus-encoded nuclear antigen, binds to the retinoblastoma and p53 proteins. Proc Natl Acad Sci USA 1993, 90:5455-5459. Click here for file References Peng CW, Zhao B, Chen HC, Chou ML, Lai CY, Lin SZ, Hsu HY, Kieff E: Hsp72 up-regulates Epstein-Barr virus EBNALP coactiva- tion with EBNA2. Blood 2007, 109:5447-5454. J 27. Peng CW, Zhao B, Chen HC, Chou ML, Lai CY, Lin SZ, Hsu HY, Kieff E: Hsp72 up-regulates Epstein-Barr virus EBNALP coactiva- tion with EBNA2. Blood 2007, 109:5447-5454. 8. Szekely L, Pokrovskaja K, Jiang WQ, Selivanova G, Lowbeer M, Ring- ertz N, Wiman KG, Klein G: Resting B-cells, EBV-infected B- Page 11 of 12 (page number not for citation purposes) Page 11 of 12 (page number not for citation purposes) Molecular Cancer 2009, 8:23 http://www.molecular-cancer.com/content/8/1/23 http://www.molecular-cancer.com/content/8/1/23 http://www.molecular-cancer.com/content/8/1/23 28. Wiman KG: Restoration of Wild-Type p53 Function in Human Tumors: Strategies for Efficient Cancer Therapy. Adv Cancer Res 2007, 97:321-338. 29. Selivanova G, Wiman KG: Reactivation of mutant p53: molecu- lar mechanisms and therapeutic potential. Oncogene 2007, 26:2243-2254. 30. Wiman KG: Strategies for therapeutic targeting of the p53 pathway in cancer. Cell Death Differ 2006, 13:921-926. p y ff 31. Bykov VJ, Wiman KG: Novel cancer therapy by reactivation of the p53 apoptosis pathway. Ann Med 2003, 35:458-465. p y Bykov VJ, Wiman KG: Novel cancer therapy by reacti the p53 apoptosis pathway. Ann Med 2003, 35:458-46 32. Charlot JF, Nicolier M, Pretet JL, Mougin C: Modulation of p53 transcriptional activity by PRIMA-1 and Pifithrin-alpha on staurosporine-induced apoptosis of wild-type and mutated p53 epithelial cells. Apoptosis 2006, 11:813-827. p p p p 33. Supiot S, Zhao H, Wiman K, Hill RP, Bristow RG: PRIMA-1(met) radiosensitizes prostate cancer cells independent of their MTp53-status. Radiother Oncol 2008, 86:407-411. p 34. Shi H, Lambert J, Hautefeuille A, Bykov V, Wiman K, Hainaut P, Caron de Fromentel C: In vitro and in vivo cytotoxic effects of PRIMA-1 on Hepatocellular Carcinoma cells expressing mutant p53ser249. Carcinogenesis 2008, 29(7):1428-34. References Publish with BioMed Central and every scientist can read your work free of charge "BioMed Central will be the most significant development for disseminating the results of biomedical research in our lifetime." Sir Paul Nurse, Cancer Research UK Your research papers will be: available free of charge to the entire biomedical community peer reviewed and published immediately upon acceptance cited in PubMed and archived on PubMed Central yours — you keep the copyright Submit your manuscript here: http://www.biomedcentral.com/info/publishing_adv.asp BioMedcentral Page 12 of 12 (page number not for citation purposes) Publish with BioMed Central and every scientist can read your work free of charge Page 12 of 12 (page number not for citation purposes)
https://openalex.org/W1950391274
https://durham-repository.worktribe.com/preview/1410603/15027.pdf
English
null
Entry Threats and Inefficiency in ‘Efficient Bargaining’
Scottish journal of political economy
2,015
cc-by
12,492
Rupayan Pal† and Bibhas Saha‡ Rupayan Pal† and Bibhas Saha‡ † Indira Gandhi Institute of Development Research (IGIDR), India ‡ Durham University Business School, University of Durham, UK † Indira Gandhi Institute of Development Research (IGIDR), India ‡ Durham University Business School, University of Durham, UK Abstract We study limit pricing in a model of entry with asymmetric information where the incumbent firm’s wage is endogenously determined through ‘efficient bargaining’ with its union. In the presence of entry threat the incumbent firm-union pair may face a conflict between rent sharing and transmitting its cost information. When the wage is not observable to outsiders and employment is the only signalling instrument, over-employment features in all entry deterring contracts. When the wage is also observable, information transmission becomes easier. Then most of the time, but not always, the efficient contract deters (induces) entry against the low (high) cost incumbent. Keywords: Efficient Bargaining, Entry Threat, Signalling, Inefficiency Keywords: Efficient Bargaining, Entry Threat, Signalling, Inefficiency JEL Classifications: J51, L12, D43, J58 JEL Classifications: J51, L12, D43, J58 JEL Classifications: J51, L12, D43, J58 Corresponding author: Rupayan Pal, Indira Gandhi Institute of Development Research (IGIDR), Film City Road, Santosh Nagar, Goregaon (East), Mumbai 400065, India. E-mails: † rupayan@igidr.ac.in, rupayanpal@gmail.com; ‡ b.c.saha@durham.ac.uk. Telephone: +91-22-28416545, Fax: +91-22-28402752. Acknowledgment: We gratefully acknowledge helpful comments from the editor and two anonymous referees. Remaining errors, if any, are our responsibility. Acknowledgment: We gratefully acknowledge helpful comments from the editor and two Abstract We study limit pricing in a model of entry with asymmetric information where the incumbent firm’s wage is endogenously determined through ‘efficient bargaining’ with its union. In the presence of entry threat the incumbent firm-union pair may face a conflict between rent sharing and transmitting its cost information. When the wage is not observable to outsiders and employment is the only signalling instrument, over-employment features in all entry deterring contracts. When the wage is also observable, information transmission becomes easier. Then most of the time, but not always, the efficient contract deters (induces) entry against the low (high) cost incumbent. 1 Introduction In recent years, due to greater integration of product and labour markets, entry of new firms has increased by manifolds in most industries around the world. Empirical studies also suggest that threat of entry significantly affects outcomes of both product and labour markets by influencing investment and/or export (Abraham et al., 2009; Boulhol et al., 2011; Ahsan and Mitra, 2014). Hence, studying the effects of entry threats assumes greater importance in the era of increasing globalization. It is not hard to see that entry threat affects the existing firms’ strategic postures in the product market, and yet at the same time it creates frictions in the process of rent allocation within the firm, particularly with crucial input suppliers, such as the labour unions. Both sides need to cooperate to achieve a common goal of deterring entry in future, but that also requires giving up individual rents at present. Whether they would succeed in achieving their common goal is the central question of this paper. We adapt the classic model of limit pricing due to Milgrom and Roberts (1982) by in- troducing wage bargaining. In the Milgrom-Roberts model, the entrant does not know the true marginal cost of the incumbent, which is either high or low, and entry is prof- itable only if the incumbent’s marginal cost is high. The entrant, however, can infer the incumbent’s marginal cost from the pre-entry price by invoking game-theoretic reasoning. Generally two types of equilibrium are highlighted – separating (i.e. information revealing) and pooling (i.e. information non-revealing). The first equilibrium occurs when the en- 1 1 trant is optimistic about post-entry profit.1 In this case, the low cost incumbent signals his competitiveness by charging a sufficiently low price. The second equilibrium occurs when the entrant is pessimistic about his post-entry profit. The high cost incumbent then can pretend to be the low cost type. For not being to able to extract any new information the entrant would stay away. Thus, there are two alternative scenarios of limit pricing both resulting in entry deterrence. trant is optimistic about post-entry profit.1 In this case, the low cost incumbent signals his competitiveness by charging a sufficiently low price. The second equilibrium occurs when the entrant is pessimistic about his post-entry profit. The high cost incumbent then can pretend to be the low cost type. 1 Introduction But as these papers have used inefficient bargaining protocols, it is difficult to ascertain how much of the production inefficiency is attributable to limit pricing and how much to bargaining frictions.3 By using the efficient bargaining protocol one may gain further insight into inefficiency. Though bargaining and limit pricing are intertwined, conceptually they can be separated. Bargaining frictions are likely to arise when the surplus is to be sacrificed for strategic reasons. On the other hand, the scope for limit pricing depends on what is observable to the entrant and what is not. More specifically, whether the entrant observes the wage in addition to price is crucial. If the wage is observable, the incumbent firm-union pair has an additional instrument of signalling. As such, disclosure of wage agreement may not be mandatory by law.4 Firms may still disclose it voluntarily or strategically. To capture Though bargaining and limit pricing are intertwined, conceptually they can be separated. Bargaining frictions are likely to arise when the surplus is to be sacrificed for strategic reasons. On the other hand, the scope for limit pricing depends on what is observable to the entrant and what is not. More specifically, whether the entrant observes the wage in addition to price is crucial. If the wage is observable, the incumbent firm-union pair has an additional instrument of signalling. As such, disclosure of wage agreement may not be mandatory by law.4 Firms may still disclose it voluntarily or strategically. To capture 3It has been noted that inefficient bargaining protocols can also produce efficient outcomes if profit- sharing is introduced (Anderson and Devereux, 1989; Pohjola, 1987). But the workers’ incomes in that case will be more volatile and even the risk of unemployment may rise (Koskela and Stenbacka, 2006; Schmidt- Sorensen, 1992; Holmlund, 1990). Therefore, simultaneous bargaining over both wage and employment, which is sufficient to generate efficient outcome under complete information, remains a superior protocol than any other. 3It has been noted that inefficient bargaining protocols can also produce efficient outcomes if profit- sharing is introduced (Anderson and Devereux, 1989; Pohjola, 1987). But the workers’ incomes in that case will be more volatile and even the risk of unemployment may rise (Koskela and Stenbacka, 2006; Schmidt- Sorensen, 1992; Holmlund, 1990). Therefore, simultaneous bargaining over both wage and employment, which is sufficient to generate efficient outcome under complete information, remains a superior protocol than any other. 1 Introduction For not being to able to extract any new information the entrant would stay away. Thus, there are two alternative scenarios of limit pricing both resulting in entry deterrence. In this framework, we introduce a labour union in the incumbent firm and allow simulta- neous bargaining over both wage and employment, which is known as efficient bargaining (McDonald and Solow, 1981). The entrant does not know the true reservation wage of the union, which can be high or low; he has some priors about these reservation wages. Introduction of wage bargaining immediately complicates the Milgrom-Roberts model by requiring limit pricing to be jointly incentive compatible for the firm and the union. A second issue concerns decoupling of bargaining from surplus creation. Ordinarily under efficient bargaining this decoupling is achieved seamlessly, because bargaining is shifted only to the surplus part, while the production decision is based on the reservation wage, which is a key requirement for efficiency.2 Under asymmetric information whether that will still be the case is not obvious. We know from the existing literature that when 1Optimism refers to the entrants’ expected profit being positive, where the expected profit is calculated on the basis of his priors about the entrant’s marginal cost. Pessimism refers to negative expected profit. 2Efficiency remains intact even with sequential bargaining, provided that the union’s (and, hence, firm’s) bargaining power at the stage of bargaining over wage does not differ from that at the stage of employment bargaining (Manning, 1987). 2 other bargaining protocols are used such as the right-to-manage bargaining (Nickell and Andrews, 1983), not only is employment distorted, but also bargaining frictions can render signalling difficult (see, for example, Dewatripont, 1987, 1988; Ohnishi, 2001; Pal and Saha, 2006, 2008). But as these papers have used inefficient bargaining protocols, it is difficult to ascertain how much of the production inefficiency is attributable to limit pricing and how much to bargaining frictions.3 By using the efficient bargaining protocol one may gain further insight into inefficiency. other bargaining protocols are used such as the right-to-manage bargaining (Nickell and Andrews, 1983), not only is employment distorted, but also bargaining frictions can render signalling difficult (see, for example, Dewatripont, 1987, 1988; Ohnishi, 2001; Pal and Saha, 2006, 2008). 5Under separating equilibrium entry is deterred only when the reservation wage is low. Under a pooling equilibrium entry is always deterred. 1 Introduction 4Note that in many countries, including continental European countries, Anglo-Saxon countries and developing countries like India, union-firm bargaining is a widespread phenomenon (Flanagan, 1999; Alesina et al., 2006; Pal, 2010). Also, note that disclosure of wage rates is not mandatory by law in most 3 different institutional settings we need to consider two alternative scenarios of unobservable and observable wage, and see to what extent limit pricing is carried out and how it affects wage and employment. In the scenario of unobservable wage, as employment is the only avenue for information transmission, it may need to be sufficiently distorted for the purpose of information rev- elation (as in a separating equilibrium) or information suppression (as in a pooling equi- librium). It turns out that the union’s interest is aligned with the firm’s, so that if it is incentive compatible for the firm to limit price, it is also incentive compatible for the union to limit price. Hence, the standard result of Milgrom and Roberts (1982), as discussed above, go through with the modification that both the firm and the union accept lower payoffs. The limit pricing contracts feature over employment and lower wage, and entry is deterred either via a separating equilibrium or via a pooling equilibrium.5 But the extent of over employment does not depend on the bargaining power of the union. That is to say, over employment is induced by limit pricing and not by bargaining frictions. The entry outcome, however, is efficient under a separating equilibrium, and inefficient under a pooling equilibrium. In the second scenario, where wage is also an instrument of signalling, information transmis- sion becomes easier. Consequently, separation of the types occurs with the first best levels of wage and employment, unless the union’s bargaining power is greater than a critical of the developing countries including India, unlike as in Western countries like the US. 5Under separating equilibrium entry is deterred only when the reservation wage is low. Under a pooling equilibrium entry is always deterred. 4 level. When the union’s bargaining power is greater than a critical level, separation of the low type calls for over employment and lower wage as in the first scenario. Thus, efficiency of employment is preserved most often, despite entry threats. The entry outcome is also efficient. 1 Introduction Equally, information suppression is difficult in this environment and therefore, the pooling equilibrium will not exist, which means that the high cost union will not be able to deter entry, – again a socially efficient outcome. But there is a caveat: information suppression is not optimal as long as the union’s bargaining power is below a critical level. Here bargaining friction comes into play. As long as the union does not expect a large share of the surplus, it does not care much about the effect of entry. So it does not find information suppression optimal, as much as the firm does. Hence, the pooling equilibrium (i.e. the act of information suppression) fails. But if the union is sufficiently powerful, it will see substantial gains from deterring entry and its interest then will be aligned with the firm’s. Consequently, the pooling equilibrium will be feasible, and the high cost union-firm pair will pretend to be low cost type and prevent entry. Their chosen employment level will then be inefficiently large and wage rate will be sufficiently low. Though as before the extent of over employment will not depend on the union’s bargaining power, it can be argued that the bargaining frictions determine when information suppression will be jointly incentive compatible and when it will not. Results of this paper indicate that historical data on wage-employment contracts between union-firm pairs need not necessarily satisfy the condition for Pareto efficiency, even if there was simultaneous bargaining over both wage and employment. In other words, the 5 5 model of simultaneous bargaining over both wage and employment can not be rejected purely on the basis of negative results of tests for Pareto efficiency criteria, as commonly envisaged in the existing empirical literature (see, for example, Brown and Ashenfelter, 1986; Alogoskoufis and Manning, 1991; Vannetelbosch, 1996). Clearly, results of this paper have implications to empirical tests of alternative union-firm bargaining models. model of simultaneous bargaining over both wage and employment can not be rejected purely on the basis of negative results of tests for Pareto efficiency criteria, as commonly envisaged in the existing empirical literature (see, for example, Brown and Ashenfelter, 1986; Alogoskoufis and Manning, 1991; Vannetelbosch, 1996). Clearly, results of this paper have implications to empirical tests of alternative union-firm bargaining models. The remainder of the paper is organized as follows. The next section presents the basic setup of the model. 1 Introduction The main analysis is presented in section 3. Section 4 concludes. 2 The setup The production technology of firm 1 is given by x = l, where x is the output of firm 1. The product market demand curve is linear: p = A−x−y; where p is the price and y is the output of firm 2 in the case of entry. Thus, firm 1’s profit is Π = (p −w)l. The union tries to maximize its net wage bill U = (w −θ)l, where θ is the time-invariant reservation wage of workers. Clearly, higher value of θ would lead to higher marginal cost of firm 1, which is equal to the bargained wage. We consider that θ is drawn by Mother Nature and it could be high (θ2) or low (θ1); θ2 > θ1. The true value of θ is known only to firm 1 and the union, but not to firm 2 until it enters. Firm 2 believes that θ1 occurs with probability ρ and θ2 occurs with probability (1 −ρ). We assume that entry is profitable only if the reservation wage is high (θ = θ2). Both firm 1 and the union technologies (e.g. traditional vis-a-vis modern) and, thus, they differ in terms of skill requirements to produce (almost) homogeneous goods, e.g. cloths (the case of skill mismatch), etc. Nonetheless, it can be shown that qualitative results of this paper will hold true, if we relax this assumption, as long as bargaining is decentralized and marginal costs of firm 1 and firm 2 are weakly correlated. See Pal and Saha (2006) and Pal and Saha (2008) for cost-correlation and entry deterrence under monopoly union and right-to-manage bargaining, respectively. Firm 2’s cost of production is assumed to be exogenously determined: it incurs a fixed cost F in the case of entry and its marginal cost of production is constant, c.7 For simplicity, we consider that firm 2’s marginal cost of production is known to all before it takes entry decision, unlike as in Melitz (2003). The production technology of firm 1 is given by x = l, where x is the output of firm 1. The product market demand curve is linear: p = A−x−y; where p is the price and y is the output of firm 2 in the case of entry. Thus, firm 1’s profit is Π = (p −w)l. 2 The setup There is an incumbent firm (labeled firm 1) and a potential entrant (labeled firm 2) in a market for homogeneous products. Firm 1 simultaneously negotiates both wage (w) and employment (l) with its labour union. The labour union is sufficiently large to meet labour requirements of firm 1, but it does not supply labour to firm 2. The only feasible alternative to the union is to supply workers to the alternative sector. Also, firm 1 cannot hire workers from any other source. In other words, we consider a scenario in which firm 1 and its labour union are locked-in, which is plausible in many real life situations.6 We 6Existing institutional setup often restricts a firm to hire non-union workers. Inability of a firm’s labour union to serve its rival firm(s) can be well justified in the following situations: (a) production units of firms are located in different countries, but they serve the same market (the case of international trade); (b) production units of firms are located in different sates/counties of a country and labour unions operate within a state/county (the case of localized labour unions); (c) firms differ in terms of production 6Existing institutional setup often restricts a firm to hire non-union workers. Inability of a firm’s labour union to serve its rival firm(s) can be well justified in the following situations: (a) production units of firms are located in different countries, but they serve the same market (the case of international trade); (b) production units of firms are located in different sates/counties of a country and labour unions operate within a state/county (the case of localized labour unions); (c) firms differ in terms of production 6 assume that the bargaining power of the union is γ, which is exogenously given, and that of firm 1 is 1 −γ, 0 ≤γ ≤1. For simplicity, we assume that no other payments, covert or overt, outside the wage-employment contract can be made to the union or firm 1. Firm 2’s cost of production is assumed to be exogenously determined: it incurs a fixed cost F in the case of entry and its marginal cost of production is constant, c.7 For simplicity, we consider that firm 2’s marginal cost of production is known to all before it takes entry decision, unlike as in Melitz (2003). 7In other words, we consider a scenario in which firm 2 does not interact with the firm 1’s labour union. 2 The setup The union tries to maximize its net wage bill U = (w −θ)l, where θ is the time-invariant reservation wage of workers. Clearly, higher value of θ would lead to higher marginal cost of firm 1, which is equal to the bargained wage. We consider that θ is drawn by Mother Nature and it could be high (θ2) or low (θ1); θ2 > θ1. The true value of θ is known only to firm 1 and the union, but not to firm 2 until it enters. Firm 2 believes that θ1 occurs with probability ρ and θ2 occurs with probability (1 −ρ). We assume that entry is profitable only if the reservation wage is high (θ = θ2). Both firm 1 and the union technologies (e.g. traditional vis-a-vis modern) and, thus, they differ in terms of skill requirements to produce (almost) homogeneous goods, e.g. cloths (the case of skill mismatch), etc. Nonetheless, it can be shown that qualitative results of this paper will hold true, if we relax this assumption, as long as bargaining is decentralized and marginal costs of firm 1 and firm 2 are weakly correlated. See Pal and Saha (2006) and Pal and Saha (2008) for cost-correlation and entry deterrence under monopoly union and right-to-manage bargaining, respectively. 7 7In other words, we consider a scenario in which firm 2 does not interact with the firm 1’s labour union. 7In other words, we consider a scenario in which firm 2 does not interact with the firm 1’s labour union. 7 7 dislike entry.8 Stages of the game involved are as follows. Stages of the game involved are as follows. 8As the union can not supply workers to firm 2 and firm 2 has no impact on θ or γ, its entry reduces surplus for firm 1 and the union. Period 1 Period 1 Stage 1: Mother Nature chooses the reservation wage, θ ∈{θ1, θ2}. (The same reservation wage prevails in both periods) Stage 2: Simultaneous bargaining over w and l takes place in firm 1. Stage 3: Production takes place. Firm 2, the entrant, observes the incumbent’s price (p), output (x) and employment (l). However, firm 2 may or may not observe the incumbent’s wage (w). Period 2 Stage 1: Firm 2 decides whether to enter or not. If it enters, it must incur a fixed cost F. It also learns the true value of θ. Stage 2: Bargaining over w and l takes place in firm 1. If entry has occurred, Cournot competition takes place; otherwise monopoly prevails. Stage 1: Mother Nature chooses the reservation wage, θ ∈{θ1, θ2}. (The same reservation wage prevails in both periods) g g g p Stage 3: Production takes place. Firm 2, the entrant, observes the incumbent’s price (p), output (x) and employment (l). However, firm 2 may or may not observe the incumbent’s wage (w). Period 2 Stage 1: Firm 2 decides whether to enter or not. If it enters, it must incur a fixed cost F. It also learns the true value of θ. Stage 1: Firm 2 decides whether to enter or not. If it enters, it must incur a fixed cost F. It also learns the true value of θ. Stage 2: Bargaining over w and l takes place in firm 1. If entry has occurred, Cournot competition takes place; otherwise monopoly prevails. Note that, since labour is considered to be the only factor of production and both the production function and the market demand function are deterministic and known to all, observing price (p) is equivalent to observing output (x), which is equivalent to observing employment (l). In other words, price, output and employment carry the same informa- 8 8As the union can not supply workers to firm 2 and firm 2 has no impact on θ or γ, its entry reduces surplus for firm 1 and the union. 8 tion regarding the incumbent firm’s cost.9 In the original Milgrom-Roberts model also, observation of output (in addition to price) does not yield any further information. tion regarding the incumbent firm’s cost.9 In the original Milgrom-Roberts model also, observation of output (in addition to price) does not yield any further information. Since employment, output and price carry the same information, it is sufficient to consider any one of these (either price or employment or output) as the signalling device. This is true regardless of whether wage is observable or not. Without any loss of generality, we consider that in Stage 3 of Period 1 the entrant observes only the price (p) or both price (p) and wage (w). The benchmark cases: We begin by considering two benchmark scenarios of symmetric information – monopoly and duopoly. Under monopoly the bargaining problem between firm 1 and the union, for any θi (i = 1, 2), is as follows. max wi,li Zi = U γ i Π1−γ i = [(wi −θi)li]γ[(A −li −wi)li]1−γ. Solving the above problem we get the monopoly wage and employment as wM i = γ A −θi 2 + θi, lM i = A −θi 2 , i = 1, 2, (1) (1) It is noteworthy that the contract curve is a vertical straight line on the (l, w) plain. 10In contrast, if only wage is determined via bargaining, as in case of standard right-to-manage bargain- 11In the event of zero expected profit, we assume that it will not enter. Period 2 Since it is independent of the bargaining power γ, employment is efficient.10 The payoffs of the It is noteworthy that the contract curve is a vertical straight line on the (l, w) plain. Since it is independent of the bargaining power γ, employment is efficient.10 The payoffs of the 9We mention here that, in the case of multiple factors of production, the observation of output does not necessarily imply the observation of employment unless inputs are perfect complements. In such a scenario, trying to signal through price and wage, or through price alone would require distorting labour and other factors of production. Employment in that case can be informative. We sidestep such possibilities in this paper. 9We mention here that, in the case of multiple factors of production, the observation of output does not necessarily imply the observation of employment unless inputs are perfect complements. In such a scenario, trying to signal through price and wage, or through price alone would require distorting labour and other factors of production. Employment in that case can be informative. We sidestep such possibilities in this paper. 10In contrast, if only wage is determined via bargaining, as in case of standard right-to-manage bargain- 9 union and firm 1 are, respectively, union and firm 1 are, respectively, union and firm 1 are, respectively, U M i = γ (A −θi)2 4 , ΠM i = (1 −γ)(A −θi)2 4 , which are proportional to the (monopoly) surplus. which are proportional to the (monopoly) surplus. In the case of symmetric information duopoly, which would emerge in the post-entry sce- nario, the contract curve will again be vertical, but will correspond to a lower level of efficient output: wD i = γ A −2θi + c 3 + θi, lD i = A −2θi + c 3 , and the consequent payoffs are U D i = γ (A −2θi + c)2 9 , ΠD i = (1 −γ)(A −2θi + c)2 9 Firm 2’s profit is Ri = (A−2c+θi)2 9 −F. We assume entry to be profitable only against θ2, and hence we set R1 < 0 < R2, i.e. (A−2c+θ1)2 9 < F < (A−2c+θ2)2 9 . and hence we set R1 < 0 < R2, i.e. (A−2c+θ1)2 9 < F < (A−2c+θ2)2 9 . is inefficient (Nickell and Andrews, 1983). 3 Asymmetric information Now we analyze the case of asymmetric information. Firm 2 decides on its entry based on whether its expected profit is positive or negative11, where the expected profit is calculated based on its rational belief about true θ. By rational belief we mean the beliefs that are ing, employment is chosen by the firm from its labour demand curve and the resultant bargaining outcome 10 formed using all the available information. The entrant’s prior about θ1 is ρ, which may be revised upward or downward, if he receives a signal about θ to be θ1 or θ2. While allowing such Bayesian updating, we will restrict our attention only to full updating or no updating. That is to say, either his belief about θ1 will be revised to 1 or 0, or it will remain unchanged at ρ. The equilibrium concept we will use is perfect Bayesian equilibrium, which is standard for signalling models. In equilibrium the incumbent firm-union pair will also act with rational expectation that the entrant will update his belief (if he can) and accordingly the pair will decide to reveal information (i.e. send an informative signal) or suppress information (i.e. send no signal or a non-informative signal). Let us first examine their incentive to send an informative signal. If the entrant’s prior is such that ER = ρR1 + (1 −ρ)R2 > 0, he will enter unless there is a signal that θ = θ1. Knowing this, the firm-union pair would indeed like to send an informative signal, if its θ is truly θ1. By doing this they avoid an unnecessary loss of profit (resulting from mistaken entry). This is where the separating equilibrium occurs. On the other hand, if the entrant’s prior is such that ER = ρR1 + (1 −ρ)R2 ≤0, he will stay away, unless he receives an informative signal that θ = θ2. If indeed the true θ is θ2, the firm-union pair would like to send an uninformative signal (or suppress information) so that the entrant cannot update his prior and stays away. This is the idea of pooling equilibrium. Clearly, whether information revelation will be possible or not depends on, among other things, how many instruments are used to transmit information. As discussed earlier, this 11 depends on whether only price is observable, or whether both wage and price are observable to the entrant. We consider these two cases separately. 3.1 The case of unobservable wage We first consider the scenario where the entrant, firm 2, does not observe the wage and it tries to infer the type of the union (i.e., the value of θ) from the observed price, output and employment of Period 1. However, since price, output and employment carry the same information regarding union’s type, without any loss of generality, we can consider the Period 1’s price as the only instrument of signalling in this scenario. We begin with the discussion of separating equilibrium, which is relevant when ER = ρR1 + (1 −ρ)R2 > 0 as discussed above. Separating equilibrium: If the union’s reservation wage is θ1 the firm-union pair would like to let the entrant know that it is truly facing a low cost incumbent and hence it is unwise to enter. The pair can signal its low cost only through price, and their posted price should be such that the θ2 type union could not possibly choose that. This essentially means that the pair would set a sufficiently low price if θ = θ1, and a high price if θ = θ2. These two prices must be optimal for both the firm and the union, which are ensured by 12 the following incentive compatibility conditions: the following incentive compatibility conditions: the following incentive compatibility conditions: Π1(p1; w1) + δΠM 1 ≥ΠM 1 + δΠD 1 , (2) U1(p1; w1) + δU M 1 ≥U M 1 + δU D 1 , (3) Π2(p1; w2) + δΠM 2 ≤ΠM 2 + δΠD 2 , (4) U2(p1; w2) + δU M 2 ≤U M 2 + δU D 2 . (5) (2) (5) Condition (2) states that, for θ = θ1, by setting p1 entry is deterred and firm 1’s profit (discounted and summed over two periods) is greater than what it would have been had the monopoly price pM 1 (= A+θ1 2 ) been set and entry occurred. Condition (4) states that for θ = θ2 by setting p2 = pM 2 (= A+θ2 2 ) entry is accommodated and thereby firm 1’s profit becomes greater than what it would have been, had p1 been set and deterred entry. Conditions (3) and (5) state the same for union of θ1 and θ2 types respectively. These conditions say that setting p1 is incentive compatible only for θ1, but not for θ2. 3.1 The case of unobservable wage Condition (2) states that, for θ = θ1, by setting p1 entry is deterred and firm 1’s profit (discounted and summed over two periods) is greater than what it would have been had the monopoly price pM 1 (= A+θ1 2 ) been set and entry occurred. Condition (4) states that for θ = θ2 by setting p2 = pM 2 (= A+θ2 2 ) entry is accommodated and thereby firm 1’s profit becomes greater than what it would have been, had p1 been set and deterred entry. Conditions (3) and (5) state the same for union of θ1 and θ2 types respectively. These conditions say that setting p1 is incentive compatible only for θ1, but not for θ2. Now it is important to note that since wage is not observed by the entrant, bargaining remains entirely internal to the incumbent firm without any signalling value. Hence, wage bargaining would be merely a rent-sharing arrangement, as is dictated by the efficient bargaining protocol. Once pi is decided for the purpose of information revelation, the joint surplus is determined, and then that is divided between the firm and the union. That is to say, both profit and net wage bill will be proportional to the joint surplus Si = (A−pi)(pi−θi), conditional on pi which satisfies the incentive compatibility conditions stated above. 13 13 In particular when p1 is set, we get wi = γ(p1 −θi)+θi and U(p1, wi) = (wi −θi)(A−p1) = γ(p1 −θi)(A −p1) = γSi(p1), which in turn gives Πi(p1, wi) = (p1 −wi)(A −p1) = (1 − γ)(p1 −θi)(A −p1) = (1 −γ)Si(p1). Similarly, it can be shown that U M i = γSM i = γ (A−θi)2 2 and ΠM i = (1 −γ) (A−θi)2 2 . Similar relation holds for U D i and ΠD i . Because both parties’ payoffs are proportional to the joint surplus, we can compress four incentive compatibility conditions into two as follows. (p1 −θ1)(A −p1) ≥(A −θ1)2 4 −δ[(A −θ1)2 4 −(A −2θ1 + c)2 9 ], (6) (p1 −θ2)(A −p1) ≤(A −θ2)2 4 −δ[(A −θ2)2 4 −(A −2θ2 + c)2 9 ]. (7) (6) (7) Nash bargaining over wi and li must satisfy the constraints (6) and (7), if the resulting prices are to reveal true θ. Formally, in this case, the bargaining problem is: maxwi,li Zi = [(wi −θi)li]γ[(A −wi −li)]1−γ subject to (6) and (7). 3.1 The case of unobservable wage It can be checked that condition (6) is satisfied if It can be checked that condition (6) is satisfied if p1 ∈[p1 = A + θ1 2 − p △1, ¯p1 = A + θ1 2 + p △1] p1 ∈[p1 2 p △1, p1 2 + p △1] and condition (7) is satisfied if and condition (7) is satisfied if and condition (7) is satisfied if p1 ̸∈[pL 1 = A + θ2 2 − p △2, pU 1 = A + θ2 2 + p △2], where △i = δ[ (A−θi)2 4 −(A−2θi+c)2 9 ], i = 1, 2. Clearly, p1 < pL 1 < pM 1 , assuming △1 > △2 > (θ2−θ1)2 4 .12 Therefore, any p1 ∈[p1, pL 1 ] and p2 = pM 2 will satisfy both constraints. where △i = δ[ (A−θi)2 4 −(A−2θi+c)2 9 ], i = 1, 2. Clearly, p1 < pL 1 < pM 1 , assuming △1 > △2 > (θ2−θ1)2 4 .12 Therefore, any p1 ∈[p1, pL 1 ] and p2 = pM 2 will satisfy both constraints. ch holds for a wide range of parametric configurations: △1 > △2 ⇒c < 2A+7θ1+7θ2 16 , and △2 > (θ2−θ1)2 4 ⇒δ > [ (θ2−θ1)2 4 ]/[ (A−θ2)2 4 −(A−2θ2+c)2 9 ]. 14 Figure 1 gives a diagrammatic exposition of the incentive compatibility conditions (6) and (7). The solid curve represents the left hand side (i.e. the joint surplus) of (6), and the solid flat line represents the right hand side of (6). All prices belonging to the interval [p1, ¯p1] are incentive compatible for θ1 type to reveal its type. The broken curve represents the left hand side of (7), while the broken flat line stands for the right hand side of (7). Any price less than (or equal to) pL 1 or greater than pU 1 are not incentive compatible for type θ2 to charge. The interval [p1, pL 1 ] falls in the overlapping region so that any price from this interval can only be charged by the θ1 type. The highest price from this set, pL 1 , gives the largest joint surplus, and hence this is the optimal information revealing price for θ1. The θ2 type then does its best simply by setting pM 2 . 3.1 The case of unobservable wage Thus, pL 1 is the limit price for θ1, which is lower than the monopoly price pM 1 , which implies over employment. To support this proposed (perfect Bayesian) equilibrium we can specify suitable out-of-equilibrium beliefs. Pooling equilibrium: If the entrant’s priors are such that its expected profit is negative (ER < 0), entry will not take place unless the entrant is sure that the incumbent is high cost type. Therefore, by not signalling the true θ the union-firm pair can prevent entry and be better offwhen the true θ is θ2. Formally, both types will quote the same price and it must satisfy the incentive compatibility conditions of the low type, which is given by condition (6), and the following condition for the high type (p1 −θ2)(A −p1) ≥(A −θ2)2 4 −δ[(A −θ2)2 4 −(A −2θ2 + c)2 9 ]. (8) (8) Note that this is just condition (7) with the inequality reversed, so that the untruthful Note that this is just condition (7) with the inequality reversed, so that the untruthful 15 3 ) )( ( 1 1 1 p A p  T ) )( ( 1 2 1 p A p  T . 1 2 1 4 ) ( '  T A 2 2 2 4 ) ( '  T A O 1 p L p1 M p1 M p2 U p1 1p A p Figure 1: Limit pricing behaviour is preferred. In Figure 1 the interval [pL 1 , pU 1 ] is the interval of such prices optimal for the θ2 price. The monopoly price for the low cost type, pM 1 , falls in the range that satisfies both (6) and (8). Therefore, it is optimal to set pM 1 and deter entry, regardless of θ1 or θ2. Proposition 1: When wage is not observable to the entrant, entry threat causes inef- ficiency in the form of over employment, which results in downward distortion of price. Under separating equilibrium the low type is over-employed and entry is deterred only by the low type. Under pooling equilibrium the high type is over-employed, entry is deterred by both types. When price is distorted, wage is also distorted – both downwardly. 3.1 The case of unobservable wage The existing empirical literature has treated efficiency and the efficient bargaining protocol synonymously (see, for example, Brown and Ashenfelter, 1986; Alogoskoufis and Manning, 1991; Vannetelbosch, 1996), which perhaps needs to be reviewed. 3.1 The case of unobservable wage 16 The proof of the Proposition is obvious from the graph.13 The inefficiency results from the fact that without distorting price the low type cannot distinguish itself from the high type, and nor can the high type pretend to be a low type. The limit pricing result and the entry implications are similar to that in Milgrom and Roberts (1982). Efficient bargaining helps to base the incentive constraints on the joint surplus, and this ensures the existence of separating equilibrium. Pal and Saha (2008) have shown that under right-to-manage bargaining entry threat can create frictions in rent-sharing and may render signalling impossible.14 Here that problem is averted, but still the firm-union pair has only one instrument of signalling, which limits information transmission. Consequently inefficiency occurs, despite efficient bargaining. Having said that, we should note that the extent of over employment does not depend on the bargaining power of the union. Recall the expression of pL 1 involving ∆2 which does not depend on γ. Therefore, it is fair to say that bargaining frictions do not worsen inefficiency. er employment can be said entirely due to limit pricing. 13For the wage reduction part, note that under separating equilibrium wL 1 = γ(pL 1 −θ1) + θ1 < wM 1 = γ(pM 1 −θ1) + θ1. Under pooling equilibrium, w2 = wM 1 < wM 2 . 13For the wage reduction part, note that under separating equilibrium wL 1 = γ(pL 1 −θ1) + θ1 < wM 1 = γ(pM 1 −θ1) + θ1. Under pooling equilibrium, w2 = wM 1 < wM 2 . 14Regardless of the bargaining protocol, limit pricing requires the incumbent firm to commit to a high level of employment. However, under right-to-manage bargaining anticipation of such commitment enables the union to bargain for a very high wage and to shift the cost of signalling largely to the firm. This can disrupt the firm’s incentive constraints and separating equilibrium may not exist. Under efficient bargaining such hard bargaining by the union is not possible, because wage and employment are determined simultaneously. 17 For empirical work, our results suggest that inefficient wage-employment contracts can be consistent with the efficient bargaining model. Therefore, even if the null hypothesis ‘bar- gaining model is efficient’ is rejected, the model of simultaneous bargaining over wage and employment can still be valid. 3.2 The case of observable wage We now turn to the scenario where wage is also observed by the entrant. Clearly, there are two distinct signalling instruments, price (via output) and wage, and therefore, information revelation is likely to be easier, while information suppression may be harder. In either case, less distortions may be required in the wage and employment and hence inefficiency should diminish. This will surely benefit the entrant, but may or may not benefit the incumbent union-firm pair. Separating equilibrium: First consider the case of ER > 0. As before, wage and employment must satisfy incentive constraints for the firm-union pair. But, since wage is also observable now, we need to consider individual incentive constraints, rather than the joint surplus. The employment-wage pair (l1, w1) will reveal θ = θ1, if the following two conditions are 18 met: (a) Both firm 1 and the θ1 union find it profitable to choose (l1, w1) and deter entry, instead of choosing (lM 1 , wM 1 ) and induce entry. (b) Either firm 1, or the θ2 union, or both must be worse offby choosing (l1, w1) instead of choosing (lM 2 , wM 2 ). met: (a) Both firm 1 and the θ1 union find it profitable to choose (l1, w1) and deter entry, instead of choosing (lM 1 , wM 1 ) and induce entry. (b) Either firm 1, or the θ2 union, or both must be worse offby choosing (l1, w1) instead of choosing (lM 2 , wM 2 ). met: (a) Both firm 1 and the θ1 union find it profitable to choose (l1, w1) and deter entry, instead of choosing (lM 1 , wM 1 ) and induce entry. (b) Either firm 1, or the θ2 union, or both must be worse offby choosing (l1, w1) instead of choosing (lM 2 , wM 2 ). Note the difference in the second requirement. For separation of the low type, it is necessary that the high type does not mimic the low type. If the high type were to mimic the low type, the entrant must reason that it must be in the interest of both parties; otherwise one party would veto such a proposal. Suppose, the firm benefits from such mimicking, but the union does not; then the only way the firm can make the union agree to this is by making a side-payment. 3.2 The case of observable wage But side-payments are ruled out by assumption.15 Therefore, firm 1 will have no choice but to stick to the status quo corresponding to θ = θ2, which is (lM 2 , wM 2 ). In other words, we are invoking an ‘intuitive rule’ that the entrant will apply in its reasoning about the bargaining. Unless both parties stand to gain, no deviation from the symmetric information contract will be agreed upon. We take the symmetric information contract as a status quo and enforce in the case of a disagreement. The following assumptions are imposed for this part of the analysis. Assumption 1: If any wage and/or employment are distorted from their symmetric in- formation level, it must be agreed upon by both parties. Assumption 2: When a proposed distortion does not benefit both parties, the symmetric 15Side-payments between the union and the firm are ruled out, as has been done in other work (see, for example, Pal and Saha, 2008; Ishiguro and Shirai, 1998). Institutional mechanisms governing industrial relations and trade union agreements commonly bar such side payments in most countries. 19 information wage and employment will be agreed upon. information wage and employment will be agreed upon. information wage and employment will be agreed upon. Formally, the incentive compatibility conditions of firm 1 and the union are given by (9) and (10) respectively, if the union is θ1 type, and by (11) and (12) respectively, if the union is θ2 type. (A −l1 −w1)l1 ≥(1 −γ)[(1 −δ)(A −θ1)2 4 + δ(A −2θ1 + c)2 9 ] ≡¯Π1 (9) (w1 −θ1)l1 ≥γ[(1 −δ)(A −θ1)2 4 + δ(A −2θ1 + c)2 9 ] ≡¯u1 (10) (A −l1 −w1)l1 ≤(1 −γ)[(1 −δ)(A −θ2)2 4 + δ(A −2θ2 + c)2 9 ] ≡¯Π2 (11) (w1 −θ2)l1 ≤γ[(1 −δ)(A −θ2)2 4 + δ(A −2θ2 + c)2 9 ] ≡¯u2 (12) (9) (10) (12) Note that (9) and (11) cannot be satisfied simultaneously, because ¯Π1 > ¯Π2 due to θ2 > θ1. So we can ignore condition (11). But we must satisfy both (10) and (12). That is to say, the θ2 type must not find it optimal to mimic the θ1 type, and the θ1 type must find it optimal to distort the wage if necessary. The union’s incentives are now more critical than the firm’s incentives. 3.2 The case of observable wage Furthermore, two constraints (10) and (12) cannot bind at the same time, because of the following inequality: Note that (9) and (11) cannot be satisfied simultaneously, because ¯Π1 > ¯Π2 due to θ2 > θ1. So we can ignore condition (11). But we must satisfy both (10) and (12). That is to say, the θ2 type must not find it optimal to mimic the θ1 type, and the θ1 type must find it optimal to distort the wage if necessary. The union’s incentives are now more critical than the firm’s incentives. Furthermore, two constraints (10) and (12) cannot bind at the same time, because of the following inequality: (w1 −θ1)l1 ≥¯u1 > ¯u2 ≥(w1 −θ2)l1. Formally, the separating equilibrium pair (l1, w1) solves the following problem: Formally, the separating equilibrium pair (l1, w1) solves the following problem: maxw1,l1 Z1 = U γ 1 Π1−γ 1 = [(w1 −θ1)l1]γ[(A −l1 −w1)l1]1−γ subject to constraints (9), (10) and (12). subject to constraints (9), (10) and (12). 20 w 2 u 1 u B 2  L w1 K E 2 u 1  K/ D 1 u 1  2  O 1l M l A 1 1 2   E l1 1l l Figure 2: Observable wage Consider Figure 2 for a graphical illustration, where we plot the union’s indifference curves and firm’s iso-profit curves. The iso-profit curve ¯Π1 ¯Π1 maps all (l, w) that ensures equality in condition (9). The ¯u1¯u1 curve corresponds to the θ1 union’s utility such that (w1−θ1)l1 = ¯u1 (i.e. constraint (10) binds). The ¯u2¯u2 curve corresponds to the utility of of the θ2 union being exactly equal to ¯u2, when it chooses w1 instead of wM 2 (i.e. constraint (12) binds). Since ¯u2¯u2 is flatter than ¯u1¯u1 on the (l, w) plane, the set of (l, w) satisfying (10) and (12) is non-empty. From the insight of information theory, we can say that if one of the two constraints binds, it must be (12). Moreover, as shown in the figure, l1 will be strictly less than ¯l1 (see Appendix 1 for proof). 3.2 The case of observable wage w 2 u 1 u B 2  L w1 K E 2 u 1  K/ D 1 u 1  2  O 1l M l A 1 1 2   E l1 1l l Figure 2: Observable wage w 2 u 1 u B 2  L w1 K E 2 u 1  K/ D 1 u 1  2  O 1l M l A 1 1 2   E l1 1l l Figure 2: Observable wage Consider Figure 2 for a graphical illustration, where we plot the union’s indifference curves and firm’s iso-profit curves. The iso-profit curve ¯Π1 ¯Π1 maps all (l, w) that ensures equality in condition (9). The ¯u1¯u1 curve corresponds to the θ1 union’s utility such that (w1−θ1)l1 = ¯u1 (i.e. constraint (10) binds). The ¯u2¯u2 curve corresponds to the utility of of the θ2 union being exactly equal to ¯u2, when it chooses w1 instead of wM 2 (i.e. constraint (12) binds). Since ¯u2¯u2 is flatter than ¯u1¯u1 on the (l, w) plane, the set of (l, w) satisfying (10) and (12) is non-empty. From the insight of information theory, we can say that if one of the two constraints binds, it must be (12). Moreover, as shown in the figure, l1 will be strictly less than ¯l1 (see Appendix 1 for proof). 21 Then it is obvious that any (l1, w1) pair that lies above the indifference curve ¯u1¯u1 but below ¯u2¯u2 satisfies both (10) and (12). Hence in Figure 2 any (l1, w1) belonging to the region BKED can credibly signal that the union is θ1 type. Then it is obvious that any (l1, w1) pair that lies above the indifference curve ¯u1¯u1 but below ¯u2¯u2 satisfies both (10) and (12). Hence in Figure 2 any (l1, w1) belonging to the region BKED can credibly signal that the union is θ1 type. Now to solve for optimal (l1, w1) we may invoke the idea of contract curve in the spirit of efficiency bargaining. Due to linear production technology, contract curve in this setup will be vertical. At any given choice of l1, we can draw a vertical line and stretch it all the way up to the zero profit curve, and that would be a contract curve. 3.2 The case of observable wage In Figure 2, the vertical lines at lM 1 , or lE 1 , or l1 are just some contract curves. If there were no incentive constraints, the bargaining would result in the selection of a wage that sets γΠ1(l1) = (1 −γ)u1(l1) to split the pie (conditional on the choice of l1). With the incentive constraints in place that wage, however, may not be feasible. Let us now first see if the standard monopoly wage and employment are feasible. That means, in the pair’s optimization problem none of the constraints binds. Straightforward maximization of Z1 then yields, as shown earlier, lM 1 = A−θ1 2 . The contract curve for lM 1 runs through the region BKED (see Appendix 2 for proof). Now it remains to check if wM 1 = γ (A−θ1)2 4 falls within points K and K′. We can show that if the union’s bargaining power γ is below a critical level, say ˆγ, then indeed wM 1 will lie between K and K′ (see Appendix 3 for proof).16 When γ = ˆγ, wM 1 is exactly equal to wL 1 , where wL 1 is the wage rate at point K. 16wL 1 = θ2 + 2 A−θ1 γ[(1 −δ) (A−θ2)2 4 + δ (A−2θ2+c)2 9 ], ˆγ = (θ2−θ1) A−θ1 2 [ (A−θ1)2 4 −(A−θ2)2 4 ]+δ[ (A−θ2)2 4 −(A−2θ2+c)2 9 ]. 22 Therefore, we can say that at all γ ≤ˆγ, the symmetric information wage and employment (lM 1 , wM 1 ) occurs at the separating equilibrium. This is an interesting and novel finding. This shows that with two signals, the incumbent pair can reveal their type costlessly. When γ > ˆγ, the powerful union’s high wage claim violates the θ2 type’s incentive con- straint. It becomes too attractive for the θ2 type to switch to lM 1 from lM 2 . Therefore, costless signalling is not possible. We have to make the constraint (12) bind. Substituting w1 = θ2 + ¯u2 l1 into U1 and Π1 we write Z1 as Therefore, we can say that at all γ ≤ˆγ, the symmetric information wage and employment (lM 1 , wM 1 ) occurs at the separating equilibrium. This is an interesting and novel finding. This shows that with two signals, the incumbent pair can reveal their type costlessly. 3.2 The case of observable wage When γ > ˆγ, the powerful union’s high wage claim violates the θ2 type’s incentive con- straint. It becomes too attractive for the θ2 type to switch to lM 1 from lM 2 . Therefore, costless signalling is not possible. We have to make the constraint (12) bind. Substituting w1 = θ2 + ¯u2 l1 into U1 and Π1 we write Z1 as Z1 =  θ2 + ¯U2 l1 −θ1 γ  A −l1 −θ2 − ¯U2 l1 1−γ l1. Differentiating this with respect to l1 we get Differentiating this with respect to l1 we get Differentiating this with respect to l1 we get ∂Z1 ∂l1 = 0 ⇐⇒[γΠ1 −(1 −γ)U1] (θ2 −θ1) + (1 −γ)U1(A −θ1 −2l1) = 0. (13) ∂Z1 ∂l1 = 0 ⇐⇒[γΠ1 −(1 −γ)U1] (θ2 −θ1) + (1 −γ)U1(A −θ1 −2l1) = 0. (13) (13) Note that (A −θ1 −2l1) = 0 yields l1 = lM 1 , and we should also have γΠ1 −(1 −γ)U1 = 0 which in turn yields wM 1 ; but we know for γ > ˆγ that is not feasible. So we must have (A −θ1 −2l1) < 0 implying l1 > lM 1 , which in turn requires [γΠ1 −(1 −γ)U1] > 0. That is, l1 must be such that at w1 = wL 1 (l1) and γΠ1(l1) > (1 −γ)U1(l1).17 Note that (A −θ1 −2l1) = 0 yields l1 = lM 1 , and we should also have γΠ1 −(1 −γ)U1 = 0 which in turn yields wM 1 ; but we know for γ > ˆγ that is not feasible. So we must have (A −θ1 −2l1) < 0 implying l1 > lM 1 , which in turn requires [γΠ1 −(1 −γ)U1] > 0. That is, l1 must be such that at w1 = wL 1 (l1) and γΠ1(l1) > (1 −γ)U1(l1).17 Thus, for γ > ˆγ, the separating equilibrium consists of (˜l1, ˜w1) where ˜l1(> lM 1 ) solves (13), and ˜w1 = θ2 + ¯u2 ˜l . Type θ2 union and firm 1 will stick to (lM 2 , wM 2 ). Thus, for γ > ˆγ, the separating equilibrium consists of (˜l1, ˜w1) where ˜l1(> lM 1 ) solves (13), and ˜w1 = θ2 + ¯u2 ˜l . Type θ2 union and firm 1 will stick to (lM 2 , wM 2 ). 3.2 The case of observable wage 17It can be seen that (A−θ1 −2l1) > 0 in conjunction with [γΠ1 −(1−γ)U1] < 0 will not be optimal. If it were so, by lowering the wage, while maintaining the same employment, profit can be raised and union’s utility can be lowered to set γΠ1 = (1 −γ)U1 which will improve the value of the maximand Z1. In that case, the constraint (12) will no longer bind, and that is a contradiction. 23 The general message is that information revelation is not entirely costless. If the union is sufficiently powerful to claim a lion’s share of the surplus, then the rent sharing issue is less important and firm’s role is nearly irrelevant. Signalling then becomes the main objective of the union, and it must bear the cost of doing so. Pooling equilibrium: Now we consider the case of ER < 0. As the θ2 type union would like to mimic a θ1 type union, the firm and the union both must find it optimal to set (wM 1 , lM 1 ) and deter entry, instead of sticking to the status quo (lM 2 , wM 2 ) and induce entry. Therefore, the incentive constraints (11) and (12) must both be reversed as follows. (A −l1 −w1)l1 ≥(1 −γ)[(1 −δ)(A −θ2)2 4 + δ(A −2θ2 + c)2 9 ] ≡¯Π2, (11a) (w1 −θ2)l1 ≥γ[(1 −δ)(A −θ2)2 4 + δ(A −2θ2 + c)2 9 ] ≡¯u2. (12a) (11a) (12a) Other incentive constraints, namely (9) and (10) remain unchanged. Note if (9) is satisfied, then (11a) is automatically satisfied (as ¯Π2 < ¯Π1). So condition (11a) is redundant. Other incentive constraints, namely (9) and (10) remain unchanged. Note if (9) is satisfied, then (11a) is automatically satisfied (as ¯Π2 < ¯Π1). So condition (11a) is redundant. We need to verify if (lM 1 , wM 1 ) satisfy (9), (10) and (12a). Of the three constraints, (9) is generally not a problem; the other two are. In reference to Figure 2, we can say that w1 now must be above point K to satisfy both (10) and (12a), and from our previous discussion we know that this will be so if γ > ˆγ. On the other hand, if γ ≤ˆγ, wM 1 will lie between points K and K′, which means condition (12a) will be violated. So the pooling equilibrium does not exist when γ < ˆγ. 3.2 The case of observable wage (9) With this intuitive reasoning, we can argue that a pooling equilibrium is possible only if the union is sufficiently powerful. The strength of the union matters because a strong 24 union has much more to gain from preventing entry (by suppressing information), while its bargaining partner, a weak firm, does not have much to lose. Once again, over employment occurs for the θ2 type union. In this case also we can suitably specify the out-of-equilibrium beliefs of the entrant to support the proposed equilibrium. Proposition 2: When wage and price are both observable, the following equilibria occur. Proposition 2: When wage and price are both observable, the following equilibria occur. (a) Separating equilibrium: Full information employment and wage (lM 1 , wM 1 ) credibly sig- nals the θ1 type, as long as the union’s bargaining power is below a critical level (i.e. γ ≤ˆγ). When γ > ˆγ, there will be over-employment as well as a wage cut for type θ1; equilibrium employment and wage will be (˜l1, ˜w1). Type θ2 will set (lM 2 , wM 2 ) at all γ. (b) Pooling equilibrium: Pooling equilibrium exists only if the union’s bargaining power exceeds ˆγ, with both types setting (lM 1 , wM 1 ); the θ2 type union will be over-employed. (b) Pooling equilibrium: Pooling equilibrium exists only if the union’s bargaining power exceeds ˆγ, with both types setting (lM 1 , wM 1 ); the θ2 type union will be over-employed. Comparing Proposition 1 and Proposition 2 we can say that the possibility of inefficient employment choice is much less when wage is observable, simply because information revelation becomes easier, or information suppression becomes difficult, barring the case of a very powerful union which manages to fool the entrant. In a nutshell, the availability of an additional signalling device largely mitigates the inefficiency problem endemic to entry threats under asymmetric information. Finally, a brief comment on sequential bargaining is in order. How do our results of si- multaneous bargaining relate to the case of sequential bargaining? There is a well known 25 result due to (Manning, 1987) that under symmetric information the sequentiality of bar- gaining does not matter, as long as the players’ bargaining powers do not change between the stages of bargaining; the outcome is always efficient. Then a natural question to ask is: does asymmetric information force the sequential bargaining to produce a different out- come to the simultaneous bargaining outcome? The answer is ‘no’. It can be shown that, as long as employment is negotiated first and wage next, we will be able to reproduce the same results as Propositions 1 and 2. The reason is, when employment is chosen first, the bargaining pie is determined right away; wage largely then allocates rent, and in addition maintains consistency with the incentive constraints. This replicates the spirit of efficient bargaining. Therefore, signalling through employment alone or through both employment and wage (sequentially) will take the same course as the case of simultaneous bargaining.18 18Further details and proof can be obtained from the authors. 4 Concluding remarks Analysis of this paper suggests that for the purpose of improving efficiency it is not suffi- cient to induce the firms and unions, by appropriate institutional mechanism, to bargain over both employment and wage simultaneously or sequentially. When there are entry threats, the incumbent firms may be required to disclose wage agreements (and similar agreements with other input suppliers). Though the rule of mandatory disclosure of wage agreements will not directly give away the incumbent’s private cost information, it will certainly improve the entrant’s ability to process information, and yet at the same time 18Further details and proof can be obtained from the authors. 26 will save the incumbents from taking costly signalling measures. The society will also be better offby encouraging right level of entry. To what extent this can be done in reality remains an open issue, as it has bearing on both industrial relations regulation and anti- trust policies. Moreover, it can be argued that models of union-firm bargaining over both wage and employment cannot be rejected purely on the basis of negative results of tests for Pareto efficiency criteria. will save the incumbents from taking costly signalling measures. The society will also be better offby encouraging right level of entry. To what extent this can be done in reality remains an open issue, as it has bearing on both industrial relations regulation and anti- trust policies. Moreover, it can be argued that models of union-firm bargaining over both wage and employment cannot be rejected purely on the basis of negative results of tests for Pareto efficiency criteria. References Abraham, F., Konings, J., and Vanormelingen, S. (2009). The effect of gobalization on union bargaining and price-cost margins of firms. Review of World Economics, 145(1):13– 36 union bargaining and price-cost margins of firms. Review of World Economics, 145(1):13– 36. Ahsan, R. and Mitra, D. (2014). Trade liberalisation and labor’s slice of the pie: Evidence from Indian firms. Journal of Development Economics, 108:1–16. Alesina, A. F., Glaeser, E. L., and Sacerdote, B. (2006). Work and leisure in the U.S. and Europe: Why so different? NBER Chapters, in: NBER Macroeconomics Annual 2005, Volume 20, pages 1-100 National Bureau of Economic Research, Inc. . Alogoskoufis, G. and Manning, A. (1991). Tests of alternative wage employment bargaining models with an application to the UK aggregate labour market. European Economic Review, 35(1):23–37. Ahsan, R. and Mitra, D. (2014). Trade liberalisation and labor’s slice of the pie: Evidence from Indian firms. Journal of Development Economics, 108:1–16. Alesina, A. F., Glaeser, E. L., and Sacerdote, B. (2006). Work and leisure in the U.S. and Europe: Why so different? NBER Chapters, in: NBER Macroeconomics Annual 2005, Volume 20, pages 1-100 National Bureau of Economic Research, Inc. . Alogoskoufis, G. and Manning, A. (1991). Tests of alternative wage employment bargaining models with an application to the UK aggregate labour market. European Economic Review, 35(1):23–37. 27 Anderson, S. P. and Devereux, M. (1989). Profit-sharing and optimal labour contracts. Canadian Journal of Economics, 22(2):425–433. Canadian Journal of Economics, 22(2):425–433. Boulhol, H., Dobbelaere, S., and Maioli, S. (2011). Import as product and labour market discipline. British Journal of Labour Relations, 49(2):331–361. Brown, J. N. and Ashenfelter, O. (1986). Testing the efficiency of employment contracts. Journal of Political Economy, 94(Supp.)(3):S40–S87. Dewatripont, M. (1987). Entry deterrence under trade unions. European Economic Review, 31(1/2):149–156. Dewatripont, M. (1988). The impact of trade unions on incentives to deter entry. Rand Journal of Economics, 19(2):191–199. Flanagan, R. (1999). macroeconomic performance and collective bargaining: An interna- tional perspective. Journal of Economic Literature, 37(3):1150–1175. Holmlund, B. (1990). Profit sharing, wage bargaining, and unemployment. Economic Inquiry, 28(2):257–268. Ishiguro, S. and Shirai, Y. (1998). Entry deterrence in a unionized oligopoly. Japanese Economic Review, 49(2):210–221. Koskela, E. and Stenbacka, R. (2006). Flexible and committed profit sharing with wage bar- gaining: Implications for equilibrium unemployment. Journal of Economics, 87(2):159– 180. 28 Manning, A. (1987). An integration of trade union models in a sequential bargaining framework. Economic Journal, 97(385):121–139. McDonald, I. M. and Solow, R. Appendix 1: The point B always lies to the left of point D as shown in Figure 2 Proof: We have, ∂w1 ∂l1 |¯u1¯u1= −w1−θ1 l1 < −w1−θ2 l1 = ∂w1 ∂l1 |¯u2¯u2. That is, the union’s indifference curve ¯u1¯u1 is steeper than ¯u2¯u2 in the l −w plane. Therefore, these two indifference curves intersect only once. Clearly, it is sufficient to prove that the level of employment corresponding to point B (l1) is less than the level of employment corresponding to point D (¯l1): l1 < ¯l1. Solving the equations of ¯u1¯u1 and ¯u2¯u2, we get l1 = ¯u1−¯u2 θ2−θ1 , where ¯u1 = γ[(1 −δ) (A−θ1)2 4 + δ (A−2θ1+c)2 9 ] and ¯u2 = γ[(1 −δ) (A−θ2)2 4 + δ (A−2θ2+c)2 9 ]. And, solving the equations of ¯u1¯u1 and ¯Π1 ¯Π1, we get l1 = 1 2[A−θ1± q (A −θ1)2 −4 γ ¯u1]. We discard the root 1 2[A−θ1− q (A −θ1)2 −4 γ ¯u1], since it corresponds to the point of intersection of ¯u1¯u1 and ¯Π1 ¯Π1 that is closer to the w-axis. Proof: We have, ∂w1 ∂l1 |¯u1¯u1= −w1−θ1 l1 < −w1−θ2 l1 = ∂w1 ∂l1 |¯u2¯u2. That is, the union’s indifference curve ¯u1¯u1 is steeper than ¯u2¯u2 in the l −w plane. Therefore, these two indifference curves intersect only once. Clearly, it is sufficient to prove that the level of employment corresponding to point B (l1) is less than the level of employment corresponding to point D (¯l1): l1 < ¯l1. Solving the equations of ¯u1¯u1 and ¯u2¯u2, we get l1 = ¯u1−¯u2 θ2−θ1 , where ¯u1 = γ[(1 −δ) (A−θ1)2 4 + δ (A−2θ1+c)2 9 ] and ¯u2 = γ[(1 −δ) (A−θ2)2 4 + δ (A−2θ2+c)2 9 ]. And, solving the equations of ¯u1¯u1 and ¯Π1 ¯Π1, we get l1 = 1 2[A−θ1± q (A −θ1)2 −4 γ ¯u1]. We discard the root 1 2[A−θ1− q (A −θ1)2 −4 γ ¯u1], since it corresponds to the point of intersection of ¯u1¯u1 and ¯Π1 ¯Π1 that is closer to the w-axis. Hence, ¯l1 = 1 2[A −θ1 + q (A −θ1)2 −4 γ ¯u1]. References M. (1981). Wage bargaining and employment. American Economic Review, 71(5):896–908. Melitz, M. J. (2003). The impact of trade on intra-industry reallocations and aggregate industry productivity. Econometrica, 71(6):1695–1725. Milgrom, P. and Roberts, J. (1982). Limit pricing and entry under incomplete information: An equilibrium analysis. Econometrica, 50(2):443–459. Milgrom, P. and Roberts, J. (1982). Limit pricing and entry under incomplete information: An equilibrium analysis. Econometrica, 50(2):443–459. Nickell, S. J. and Andrews, M. (1983). Unions, real wages and employment in Britain 1951-79. Oxford Economic Papers, 35(Supplement):183–206. Ohnishi, K. (2001). Lifetime employment contract and strategic entry deterrence: Cournot and Bertrand. Australian Economic Papers, 40(1):30–43. Pal, R. (2010). Impact of communist parties on the individual decision to join a trade union: Evidence from India. The Developing Economies, 48(4):496–528. Pal, R. and Saha, B. (2006). Wage commitment, signalling and entry deterrence or accom- modation. LABOUR:Review of Labour Economics and Industrial Relations,, 20(4):625– 650. Pal, R. and Saha, B. (2008). Union-oligopoly bargaining and entry deterrence: A reasses- ment of limit pricing. Journal of Economics, 95(2):121–147. 29 Pohjola, M. (1987). Profit-sharing, collective bargaining and employment. Journal of Institutional and Theoretical Economics, 143(2):334–342. Pohjola, M. (1987). Profit-sharing, collective bargaining and employment. Journal of Institutional and Theoretical Economics, 143(2):334–342. Schmidt-Sorensen, J. B. (1992). The profit share rate, wages and employment in collective bargaining. European Journal of Political Economy, 8(1):105–113. Schmidt-Sorensen, J. B. (1992). The profit share rate, wages and employment in collective bargaining. European Journal of Political Economy, 8(1):105–113. Vannetelbosch, V. J. (1996). Testing between alternative wage-employment bargaining models using Belgian aggregate data. Labour Economics, 3(1):43–64. 30 Appendix Appendix 1: The point B always lies to the left of point D as shown in Figure 2 Appendix 1: The point B always lies to the left of point D as shown in Figure 2 Now, it is sufficient to check that Now, it is sufficient to check that Now, it is sufficient to check that l1 < ¯l1 ⇒¯u1 −¯u2 θ2 −θ1 < 1 2[A −θ1 + r (A −θ1)2 −4 γ ¯u1] ⇒γ[(1 −δ)2A −θ1 −θ2 4 + 4δ 9 (A −θ1 −θ2 + c) < 1 2[A −θ1 + r δ(A −θ1)2 −4δ 9 (A −2θ1 + c)2], which is obvious for γ = 0. Since the LHS is increasing in γ and the RHS does not depend on γ, it is sufficient to show that the above inequality is true for γ = 1. Now, if γ = 1, the above inequality implies that 2A −θ1 −θ2 4 −δ 36(2A + 7θ1 + 7θ2 −16c) < A −θ1 2 + r δ{(A −θ1)2 4 −(A −2θ1 + c)2 9 }, which is obvious, since 2A−θ1−θ2 4 < A−θ1 2 ⇒θ1 < θ2 and c < 2A+7θ1+7θ2 16 (by construction which is obvious, since 2A−θ1−θ2 4 < A−θ1 2 ⇒θ1 < θ2 and c < 2A+7θ1+7θ2 16 (by construction). QED 31 Appendix 2: The point B always lies to the left, while points E and D always lie to the right of the contract curve of the low state l A−θ1 : Appendix 2: The point B always lies to the left, while points E and D always lie to the Appendix 2: The point B always lies to the left, while points E and D always lie to the right, of the contract curve of the low state l1 = A−θ1 2 : right, of the contract curve of the low state l1 = A−θ1 2 : Proof: We need to prove that l1 < A−θ1 2 < lE 1 < ¯l1, where l1, lE 1 and ¯l1 denote employment levels at points B, E and D, respectively. points B, E and D, respectively. (a) Note that (a) Note that l1 < A −θ1 2 ⇒¯u1 −¯u2 θ2 −θ1 < A −θ1 2 ⇒γ[(1 −δ)2A −θ1 −θ2 4 + 4δ 9 (A −θ1 −θ2 + c)] < A −θ1 2 , which is obvious for γ = 0. If the above is true for γ = 1, then it is true ∀γ. Appendix 1: The point B always lies to the left of point D as shown in Figure 2 l1 < A −θ1 2 ⇒−θ2 −θ1 4 < δ 36[2A + 7θ1 + 7θ2 −16c], Now, if γ = 1, which is true since θ2 > θ1 and c < 2A+7θ1+7θ2 16 (by construction). which is true since θ2 > θ1 and c < 2A+7θ1+7θ2 16 (by construction). (b) Point E is the right most point of intersection of ¯u2 ¯u2 and ¯ Π1 ¯ Π1 curves: (b) Point E is the right most point of intersection of ¯u2 ¯u2 and ¯ Π1 ¯ Π1 curves: ¯u2 ¯u2 :(w1 −θ2)l1 = γ (A −θ2)2 4 −γ∆2, (i) ¯ Π1 ¯ Π1 :(A −l1 −w1)l1 = (1 −γ)(A −θ1)2 4 −(1 −γ)∆1, (ii) where ∆i = δ{(A −θi)2 4 −(A −2θi + c)2 9 }, i = 1, 2. (i) (ii) From (i) and (ii) we get From (i) and (ii) we get (w1 −θ2) = (A −l1 −θ2){γ (A−θ2)2 4 −γ∆2} H , (iii) where H = (1 −γ) (A−θ1)2 4 −(1 −γ)∆1 + γ (A−θ2)2 4 −γ∆2. (w1 −θ2) = (A −l1 −θ2){γ (A−θ2)2 4 −γ∆2} H , (iii) (iii) where H = (1 −γ) (A−θ1)2 4 −(1 −γ)∆1 + γ (A−θ2)2 4 −γ∆2. where H = (1 −γ) (A−θ1)2 4 −(1 −γ)∆1 + γ (A−θ2)2 4 −γ∆2. 32 From (i) and (iii), we get l1 = A−θ2 2 ± q (A−θ2)2 4 −H. We discard the root l1 = A−θ2 2 − From (i) and (iii), we get l1 = A−θ2 2 ± q (A−θ2)2 4 −H. We discard the root l1 = A−θ2 2 − ) and (iii), we get l1 = A−θ2 2 ± q (A−θ2)2 4 −H. We discard the root l1 = A−θ2 2 − q (A−θ2)2 4 −H, since it is closer to the w−axis. Therefore, 2 −H, since it is closer to the w−axis. Therefore, q (A−θ2)2 4 −H, since it is closer to the w−axis. Therefore, lE 1 = A −θ2 2 + r (A −θ2)2 4 −H Now, A −θ1 2 < lE 1 ⇒(θ2 −θ1)2 4 < ∆2 −(1 −γ)[(1 −δ){(A −θ1)2 4 −(A −θ2)2 4 } + δ{(A −2θ1 + c)2 9 −(A −2θ2 + c)2 9 }] ⇒(θ2 −θ1)2 4 < ∆2, which is true by construction. Appendix 1: The point B always lies to the left of point D as shown in Figure 2 lE 1 = A −θ2 2 + r (A −θ2)2 4 −H (c) Note that ¯u1 ¯u1 and ¯u2 ¯u2 are downward sloping curves in the l-w plane, ¯u2 ¯u2 curve lies above the ¯u1 ¯u1 curve on the right of point B, and points E and D are on the downward sloping segment of the ¯ Π1 ¯ Π1 curve. Therefore, it is evident that lE 1 < ¯l1. From (a), (b) and (c) we can write l1 < A−θ1 2 < lE 1 < ¯l1. [QED] From (a), (b) and (c) we can write l1 < A−θ1 2 < lE 1 < ¯l1. [QED] Appendix 3: If γ > ˆγ, wM 1 > wL 1 Appendix 3: If γ > ˆγ, wM 1 > wL 1 Proof: wL 1 is given by the solution of (w1 −θ2)l1 = ¯u2 and l1 = A−θ1 2 , where ¯u2 = γ[(1−δ) (A−θ2)2 4 + δ (A−2θ2+c)2 9 ]. Solving these two equations, we get w1 = θ2 + 2 A−θ1 γ[(1−δ) (A−θ2)2 4 +δ (A−2θ2+c)2 9 ] = wL 1 , say. Now, Proof: w1 is given by the solution of (w1 −θ2)l1 = u2 and l1 = 1 2 , where u2 = γ[(1−δ) ( ) 4 + δ (A−2θ2+c)2 9 ]. Solving these two equations, we get w1 = θ2 + 2 A−θ1 γ[(1−δ) (A−θ2)2 4 +δ (A−2θ2+c)2 9 ] = wL 1 , say. Now, δ (A−2θ2+c)2 9 ]. Solving these two equations, we get w1 = θ2 + 2 A−θ1 γ[(1−δ) (A−θ2)2 4 +δ (A−2θ2+c)2 9 ] = wL say Now δ (A−2θ2+c)2 9 ]. Solving these two equations, we get w1 = θ2 + 2 A−θ1 γ[(1−δ) (A−θ2)2 4 +δ (A−2θ2+c)2 9 ] = wL 1 , say. Now, wL 1 , say. Now, wL 1 , say. Now, wL 1 < wM 1 ⇒θ2 + 2γ A −θ1 [(1 −δ)(A −θ2)2 4 + δ(A −2θ2 + c)2 9 ] < θ1 + γ A −θ1 2 ⇒γ > (θ2 −θ1) A−θ1 2 [ (A−θ1)2 4 −(A−θ2)2 4 ] + δ[ (A−θ2)2 4 −(A−2θ2+c)2 9 ] = ˆγ, say. Therefore, if γ > ˆγ, wM 1 > wL 1 . QED say. Therefore, if γ > ˆγ, wM 1 > wL 1 . QED 33