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fast_asleep/3926054_46_0.txt | THIS STUDY WAS UNDERTAKEN AT
Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), Meibergdreef 47, Amsterdam 1105 BA, The Netherlands. |
fast_asleep/full_27_0.txt | Table 3
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Table 3. Normalized transition probabilities between five behavioral states within the sleep period time in the adaptation and experimental nights. |
fast_asleep/full_10_2.txt | the present study was to investigate the time-course changes in sleep-stage transitions, cortical EEG power, and heart rate variability in the progress of sleep cycles in the adaptation night in comparison with the experimental night in healthy subjects. |
fast_asleep/3926054_48_1.txt | ulen, Josien Visser, Verena Sommer, Oti Kamal, Inger van Steenoven, Brit Giesbertz, Vincent Huson. |
fast_asleep/rsta20140093_49_1.txt | occur with relatively high probability with young normal subjects and with reduced probability in the groups Old/Sleep Disorder. |
fast_asleep/3926054_43_1.txt | them.53,54 Alternatively, the mixed results in the literature may also involve heterogeneous subtypes within ID.55 Interestingly, studies that report alterations in characteristics of spindles or K-complexes in ID during stage N2 usually report no impairments with respect to the conventional PSG sleep parameters,51,52... |
fast_asleep/full_30_0.txt | Quantitative EEG and HRV Analyses
The mean spectral parameters of the first four sleep cycles calculated on the adaptation night and experimental night are shown in Figure 2. The two-way repeated-measures ANOVA (nights: two levels × sleep cycle: four levels) demonstrated a significant interaction [F(3,99) = 3.49, p = 0... |
fast_asleep/3926054_44_0.txt | In conclusion, whole-night sleep stage dynamics reveal a particular stage N2 vulnerability in ID. Quantification of this vulnerability can easily be done using regularly scored PSG recordings. Further investigations of the neurophysiological dynamics during stage N2 may potentially lead to sensitive biomarkers of insom... |
fast_asleep/rsta20140093_40_0.txt | Download figureOpen in new tabDownload PowerPoint
Figure 5.
Figure 5. Distributions of HSE for (a) four groups of subjects (compare transition matrices in figure 2), (b) subjects with and without sleep disorder and (c) old and young subjects. (Online version in colour.) |
fast_asleep/Cellstatetransitions_44_0.txt | Journal of Experimental Biology |
fast_asleep/rsta20140093_19_1.txt | syndrome, periodic leg movements, depression and anxiety disorders. |
fast_asleep/full_36_1.txt | ., 2004) or HRV (Israel et al., 2012; Virtanen et al., 2018) throughout the entire night. Based on the cycle-by-cycle analyses of both nights, the cortical EEG power for each frequency band and HRV of NREM sleep and REM sleep exhibited typical alterations across sleep cycles such as the decrease in delta EEG power and ... |
fast_asleep/rsta20140093_47_1.txt | more often in patients suffering from sleep disorder as can be seen from the dashed lines indicating transition probabilities of both groups Young/Sleep Disorder and Old/Sleep Disorder, respectively. The transition probabilities of Old/Normal subjects equal the total mean, while Young/Normal exhibit a relatively low p... |
fast_asleep/3926054_34_0.txt | Open in new tab
To formally evaluate the added value of quantifying whole-night sleep stage dynamics in addition to conventional sleep parameters for discriminating cases from controls, two nested multiple logistic regression models were compared using a chi-squared likelihood ratio test. The first model included as in... |
fast_asleep/3926054_0_2.txt | PhD, Dieter Riemann, PhD, Eus J W Van Someren, PhD Author Notes
Sleep, Volume 40, Issue 9, September 2017, zsx117, https://doi.org/10.1093/sleep/zsx117
Published: 05 July 2017
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Abstract
Study Objectives
Objective sleep impairments in insomnia disorder... |
fast_asleep/Cellstatetransitions_11_0.txt | Multiscale descriptions
Although molecular descriptions and functional assays are powerful tools to describe cell states, the workshop emphasised that the next technical challenge is to combine different techniques to attain a multiscale description of cell states. The development of multi-omics approaches is now allow... |
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fast_asleep/full_141_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/Cellstatetransitions_35_12.txt | ., Mulas, C., Ibarra-Soria, X., Tyser, R. C. V., Ho, D. L. L. et al. (2019). A single-cell molecular map of mouse gastrulation and early organogenesis. Nature 566, 490-495. https://doi.org/10.1038/s41586-019-0933-9
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Punovuori, K., Migueles, R. P., Malaguti, M., Blin, G., Macleod |
fast_asleep/3926054_38_1.txt | , once they reach this stage. Finally, logistic regression analyses showed not only that people with ID are best distinguishable from healthy controls in terms of the transition probability from stage N2 to stage N1 but also that including this transition probability can significantly improve the goodness of fit of a d... |
fast_asleep/Cellstatetransitions_35_6.txt | Chubb, J. R. (2020). Cell and molecular transitions during efficient dedifferentiation. eLife 9, e55435. https://doi.org/10.7554/eLife.55435
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Nowotschin, S., Setty, M., Kuo, Y.-Y., Liu, V., Garg, V., Sharma, R., Simon, C. S., Saiz, N., Gardner, R., Boutet, S. C. et al. (2019). The emergent lands... |
fast_asleep/full_36_2.txt | HRV can differ among the sleep cycles since cyclic fluctuation within a sleep cycle is modulated by the homeostatic and circadian influences over the night (Åkerstedt et al., 1998). As addressed above, in the first sleep cycle, sleep architecture differed between the adaptation and experimental nights. Delta EEG power... |
fast_asleep/rsta20140093_28_0.txt | Download figureOpen in new tabDownload PowerPoint
Table 2.
p-Values of a Wilcoxon rank-sum test performed for all pairs of distributions shown in figure 3a. |
fast_asleep/3926054_31_4.txt | [1.004, 1.157] .04
Stage R, % 0.995; [0.954, 1.037] .80 0.913; [0.856, 0.973] .005
Transition probability from stage N2 to stage N1, % 3.522; [1.704, 7.281] .0007 1.243; [1.069, 1.444] .005
Transition probability from stage N2 to stage W, % 1 |
fast_asleep/full_35_2.txt | stage REM. However, in this study, the changes in sleep-stage dynamics in the adaptation night had no major impact on sleep architecture in the following sleep cycles. This suggests that the sleep in the first sleep cycle is susceptible to environmental changes in the adaptation night. However, environmental influence... |
fast_asleep/rsta20140093_68_1.txt | ., Philosophical Transactions B, 2011
Inhibiting the inhibitors: Development of the IAP inhibitor xevinapant for the treatment of locally advanced squamous cell carcinoma of the head and neck
Robert L. Ferris et al., Cancer Treatment Reviews, 2023
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fast_asleep/Cellstatetransitions_36_1.txt | , A., Müller, F.-J., Babtie, A., Chan, T. E., Stumpf, M. P. H., Please, C. P., Howison, S. D. et al. (2017). Stem cell differentiation as a non-markov stochastic process. Cell Syst. 5, 268-282.e7. https://doi.org/10.1016/j.cels.2017.08.009
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Wagner, D. E. and Klein, A. M. |
fast_asleep/3926054_31_3.txt | .003] .16
Stage R, minutes 0.997; [0.988, 1.006] .49 0.975; [0.962, 0.988] .0002
WASO, % 1.136; [1.043, 1.238] .003 1.077; [1.033, 1.124] .0005
Stage N1, % 1.263; [1.102, 1.448] .0008 1.078; |
fast_asleep/rsta20140093_22_1.txt | in §3b explicitly cover information about durations. It is also important to point out that the analysis has been performed on a per-dataset basis, where transition matrices are computed for each night of each individual. From these transition matrices of different datasets mean transition matrices are computed by ave... |
fast_asleep/full_112_0.txt | Lorenzo, J.-L., and Barbanoj, M.-J. (2002). Variability of sleep parameters across multiple laboratory sessions in healthy young subjects: the “very first night effect”. Psychophysiology 39, 409–413. |
fast_asleep/rsta20140093_51_0.txt | A Markov chain is a model assuming probabilistic transitions between states with a dependency on a specific number of temporarily previous states. A Markov chain of order k is defined as a probabilistic process where the current transition probability depends on the past k states. A symbolic chain involving n states ca... |
fast_asleep/full_114_0.txt | Malliani, A., Pagani, M., Lombardi, F., and Cerutti, S. (1991). Cardiovascular neural regulation explored in the frequency domain. Circulation 84, 482–492. doi: 10.1161/01.CIR.84.2.482 |
fast_asleep/3926054_41_0.txt | On the other hand, it is worth noting that the overall sleep patterns of people with ID reported here are comparable to previous findings about the aged population. A series of studies have shown that among normal sleepers without sleep complaints, aging is associated with more stage N1 and less SWS,41,42 shorter sleep... |
fast_asleep/rsta20140093_45_0.txt | Download figureOpen in new tabDownload PowerPoint
To investigate the impact of sleep disorders on the transition probabilities, figure 7 shows a comparison of young subjects with and without sleep disorders. Similar to elderly subjects (figure 6), patients suffering from sleep disorders exhibit a higher probability of ... |
fast_asleep/full_167_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/Cellstatetransitions_14_1.txt | methods, such as dimensionality reduction and pseudo-temporal ordering, while powerful visualisation tools, can also bias how we perceive the data. |
fast_asleep/3926054_26_4.txt |
N3 1.35 ± 1.34 0.17 ± 0.32 1.89 ± 1.76 96.36 ± 2.61 0.23 ± 0.57
R 3.77 ± 7.15 2.75 ± 7.56 2.56 ± 2.05 0.01 ± 0.05 90.91 ± 14.28
Bold font highlights significant and trend-level group differences after false discovery rate correction (see text for test statistics). |
fast_asleep/Cellstatetransitions_28_0.txt | Other definitions of cell states and transitions rely on stronger assumptions. We saw how cell states could be modelled as ‘attractors’, or valleys, that become destabilised as gene regulatory networks change or as noise increases, allowing cells to hop over ‘hills’ to the next valley, parameterising a model first prop... |
fast_asleep/full_152_0.txt | Toussaint, M., Luthringer, R., Schaltenbrand, N., Carelli, G., Lainey, E., Jacqmin, A., et al. (1995). First-night effect in normal subjects and psychiatric inpatients. Sleep 18, 463–469. doi: 10.1093/sleep/18.6.463 |
fast_asleep/Cellstatetransitions_10_1.txt | A further benefit of functional assays is that theyprovide powerful readouts for phenotypic screens and thus can be used to identify potential regulators of cell states and transitions. |
fast_asleep/Ventrolateral_preoptic_nucleus_3_2.txt | inputs to the arousal system use this same receptor, these drugs at low doses essentially act by potentiating the VLPO, producing a sleepy state. Animal studies show that VLPO neurons show cFos activation after sedative doses of these drugs, and that VLPO lesions produce resistance to their sedative effects. However,... |
fast_asleep/Cellstatetransitions_36_7.txt | .org/10.1038/s41586-020-2432-4
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Yang, Q., Xue, S.-L., Chan, C. J., Rempfler, M., Vischi, D., Maurer-Gutierrez, F., Hiiragi, T., Hannezo, E. and Liberali, P. (2021). Cell fate coordinates mechano-osmotic forces in intestinal crypt formation. Nat. Cell Biol. 23, 733-744. https://doi.org/10.10 |
fast_asleep/full_4_1.txt | ritsmann and Sylvain Giroud
Body Protein Sparing in Hibernators: A Source for Biomedical Innovation
Fabrice Bertile, Caroline Habold, Yvon Le Maho and Sylvain Giroud
Sleep and Tibialis Anterior Muscle Activity in Mice With Mild Hypoxia and Iron Deficiency: Implications for the Restless Legs Syndrome
Viviana Lo Martire,... |
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fast_asleep/Cellstatetransitions_42_1.txt | Zhe Wei Lee et al., Development, 2022
Inhibiting the inhibitors: Development of the IAP inhibitor xevinapant for the treatment of locally advanced squamous cell carcinoma of the head and neck
Robert L. Ferris et al., Cancer Treatment Reviews, 2023
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fast_asleep/full_174_0.txt | *Correspondence: Takafumi Kato, takafumi@dent.osaka-u.ac.jp |
fast_asleep/rsta20140093_26_1.txt | xon rank-sum test (also known as Wilcoxon–Mann–Whitney test) performed for all pairs of distributions are given, indicating significant differences. These p-values have to be interpreted carefully, because of the relatively high number of individual tests that have been carried out which lead to accumulation of type-1 ... |
fast_asleep/full_131_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/Cellstatetransitions_18_2.txt | . This calls for the development of in toto models that fully recapitulate the context the cell is in. In contrast, a complementary approach is to dissect the singular constituents of the ‘niche’ and then reconstitute the niche using a bottom-up approach. |
fast_asleep/3926054_41_1.txt | ing in a steeper decay of the wake bout survival function29—while we have here observed the opposite pattern in ID, albeit only at a trend level. Consistently, prolonged awakenings in people with ID have been reported in other studies.6,18,19 It should nonetheless be noted that the faster decaying wake bout survival fu... |
fast_asleep/full_170_0.txt | Received: 30 October 2020; Accepted: 12 February 2021;
Published: 24 March 2021. |
fast_asleep/Cellstatetransitions_23_0.txt | THE ROLE OF THE MICROENVIRONMENT IN COORDINATING TRANSITIONS
Tissue mechanics can also be an effective way to coordinate cell state transitions. For example, in several cell types, mechanical stretch can induce DNA methylation, which in turn influences cell state (Maki et al., 2021; Nava et al., 2020). Tissue stretch h... |
fast_asleep/3926054_27_1.txt | occur in at least half of the participants in each group and are not visualized: from stage W to stage N3, from stage N1 to stage N3, from stage R to stage N3, from stage N3 to stage N1, and from stage N3 to stage R. (All p-values are false discovery rate corrected.).
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Markovian state diag... |
fast_asleep/3926054_13_1.txt | the total number of epochs scored as stage
The empirical transition probabilities between all pairs of stages were calculated for each participant separately. |
fast_asleep/full_38_1.txt | fully controlled or monitored. Another limitation is that not all subjects had four sleep cycles in the adaptation and experimental nights. The results of cycle-by-cycle analysis performed on a limited number of subjects with four sleep cycles may be interpreted as the responses to the environmental influences in subj... |
fast_asleep/Cellstatetransitions_30_0.txt | As each model has important implications for the underlying biology, it is necessary to test the extent to which the underlying assumptions are valid. For example, describing a biological process as a phase transition implies cells must go through a critical point, characterised by the appearance of power-law patterns ... |
fast_asleep/Cellstatetransitions_40_0.txt | Read & Publish Open Access publishing: what authors say |
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fast_asleep/Cellstatetransitions_46_0.txt | Biology Open |
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38. Doris ... |
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fast_asleep/Cellstatetransitions_24_1.txt | (Punovuori et al., 2019). Although it is possible to increase the synchrony of differentiating cells by directly modifying the activity of signalling pathways (for example by modulating negative feedback loops; Nett et al., 2018), it is not clear what factors determine the difference in synchronicity between the embry... |
fast_asleep/rsta20140093_62_0.txt | The Hadamard matrix Inline Formula is used to compute the Walsh transform. Inline Formula is an n×n matrix containing only the elements −1 and +1. Furthermore, all rows and columns, respectively, are pairwise orthogonal to each other. |
fast_asleep/rsta20140093_8_0.txt | — sleep onset latency=duration of wakefulness before first occurrence of sleep stages, |
fast_asleep/Cellstatetransitions_0_0.txt | Skip to Main Content
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fast_asleep/3926054_29_1.txt | (CTRL). Data are shown on the semilogarithmic scale. The shaded areas indicate 90% within-group bootstrap confidence intervals. The distributions of sleep bout and stage N2 bout durations significantly differ between ID and CTRL (p =.009 and p =.02, respectively, permutation Mann–Whitney tests). |
fast_asleep/full_4_4.txt | 2Graduate School of Education, The University of Tokyo, Bunkyo-ku, Japan
3Osaka University Hospital, Sleep Medicine Center, Suita, Japan
4Osaka University Health and Counseling Center, Toyonaka, Japan
5Department of Child Development, Osaka University United Graduate School of Child Development, Suita, Japan
Objective:... |
fast_asleep/full_173_1.txt | 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. |
fast_asleep/full_87_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/full_37_2.txt | Jurysta et al., 2009). However, in the healthy subjects of the present study, high beta EEG power and low RR intervals and HF amplitude may have a role for sleep maintenance, rather than sleep disturbance. As sensory alertness remains functional during sleep (Oswald et al., 1960; Kato et al., 2004; Lavigne et al., 200... |
fast_asleep/full_30_1.txt | cycle was significantly higher (p < 0.01) in the adaptation night than in the experimental night. There were no significant differences between the two nights in all other bands in NREM and REM sleep periods. |
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fast_asleep/3926054_16_0.txt | For empirical transition probabilities, no formal statistical tests were performed for rare stage transitions which occurred in fewer than half of the participants in each group (ie, in fewer than 23 people with insomnia and fewer than 21 controls). The remaining values in the transition probability matrices were compa... |
fast_asleep/Cellstatetransitions_29_0.txt | Conversely, defining cell states as discrete entities leads to stepwise transitions through more or less defined macro- and micro-states (Stumpf et al., 2017). The power of discrete definitions of cell states, combined with accurate measurements of population dynamics, can be used to identify a stochastic tissue renewa... |
fast_asleep/Cellstatetransitions_4_0.txt | Defining and identifying cell states
A starting point of discussion was how the definitions of cell states have evolved over time. With limited tools, cell states were initially assigned based on observable and phenotypic features, such as location, morphology and inferred function. Indeed, the phrase ‘cell states’ (Ze... |
fast_asleep/Cellstatetransitions_12_1.txt | . Moreover, thousands of genes and loci, and hundreds of proteins, can change over a short period of time. During the themed discussions, we debated whether cell states were discrete or continuous, and how much the categorisation of cells into states was dependent on the assay used. |
fast_asleep/rsta20140093_36_0.txt | Both quantities are calculated for matrices of size l×l, l=26 for every successive overlapping window [w,w+l−1] of each dataset. This leads to an entropy distribution for each dataset. In order to be able to compare the entropies between groups, we use the mean value of the distribution of each dataset. These mean valu... |
fast_asleep/Cellstatetransitions_13_0.txt | Classical studies of embryonic development and haematopoiesis have supported the notion of discrete states, with cells passing through ‘commitment points’ – points in which cells have irreversibly committed to a fate and lose the ability to revert back and respond to signals in a different way (with the earliest eviden... |
fast_asleep/Cellstatetransitions_35_3.txt | inen, H., Jokitalo, E., Li, X., García Arcos, J. M. et al. (2020). Heterochromatin-driven nuclear softening protects the genome against mechanical stress-induced damage. Cell 181, 800-817.e22. https://doi.org/10.1016/j.cell.2020.03.052
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Negrete, J., Lengyel, I. M., Rohde, L., Desai, R. A., Oates,... |
fast_asleep/3926054_41_3.txt | aging, as confirmed by recent neuroimaging studies. In particular, deficits of the orbitofrontal cortex have been suggested to be involved in self-reported insomnia symptoms44,45 and in sleep fragmentation quantified by actigraphy in aged people.46 The neural mechanisms of age-related changes in sleep patterns from th... |
fast_asleep/Cellstatetransitions_34_12.txt | Crossref
Kinoshita, M. and Smith, A. (2018). Pluripotency deconstructed. Dev. Growth Differ. 60, 44-52. https://doi.org/10.1111/dgd.12419
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Kitadate, Y., Jörg, D. J., Tokue, M., Maruyama, A., Ichikawa, R., Tsuchiya, S., Segi-Nishida, E., Nakagawa, T., Uchida, A., Kimura-Yosh |
fast_asleep/full_128_0.txt | Rotenberg, V. S., Hadjez, J., Kimhi, R., Indurski, P., Sirota, P., Mosheva, T., et al. (1997). First night effect in depression: new data and a new approach. Biol. Psychiatry 42, 267–274. doi: 10.1016/S0006-3223(96)00343-5 |
fast_asleep/3926054_47_0.txt | DISCLOSURE STATEMENT
This was not an industry supported study. Research leading to these results has received funding from the Bial Foundation grant 252/12, the Netherlands Organization of Scientific Research (NWO) grant VICI-453.07.001, and the European Research Council Advanced Grant 671084 INSOMNIA. This project has... |
fast_asleep/full_33_0.txt | Figure 3
www.frontiersin.org
Figure 3. RR intervals and HF amplitude for each sleep cycle. RR intervals and HF amplitude for each sleep cycle are present as mean and standard deviation (red line: adaptation night, blue line: experimental night). Values that significantly differed between nights are indicated by one (p ... |
fast_asleep/Cellstatetransitions_36_3.txt | iuka, S. et al. (2017). Inhibition of cell division and DNA replication impair mouse-naïve pluripotency exit. J. Mol. Biol. 429, 2802-2815. https://doi.org/10.1016/j.jmb.2017.06.020
Google ScholarCrossref
Wang, S.-W. and Klein, A. M. (2021). Learning dynamics by computational integration of single cell genomic and lin... |
fast_asleep/3926054_0_3.txt | ography (PSG) differ between people with ID and matched controls and whether sleep stage dynamic features discriminate them better than conventional sleep parameters. |
fast_asleep/full_100_0.txt | Lanfranchi, P. A., Pépin, J., and Somers, V. K. (2017). “Cardiovascular physiology: autonomic control in health and in sleep disorders,” in Principles and Practice of Sleep Medicine, eds M. Kryger, T. Roth, and B. Dement (Philadelphia, PA: Elsevier Press), 142–154. doi: 10.1016/B978-0-323-24288-2.00179-3 |
fast_asleep/full_121_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/rsta20140093_59_0.txt | With the low number of patients with sleep disorders (n=98) and with the high number of diverse sleep disorders in this set of studies the presented results are to be considered as preliminary providing only weak evidence for differences. Clinically, well-defined datasets with specific sleep disorders should be used wi... |
fast_asleep/rsta20140093_61_0.txt | Appendix A
(a) Hadamard matrix |
fast_asleep/3926054_50_12.txt | osom Res. 2009; 67(2): 117–125. |
fast_asleep/rsta20140093_49_0.txt | Download figureOpen in new tabDownload PowerPoint
The situation is slightly different for two-step transitions including the wake state W. Here transitions N1 Inline Formula W Inline Formula N1 and W Inline Formula N1 Inline Formula W are most probable for old subjects with sleep disorder, followed by the Old/Normal an... |
fast_asleep/3926054_4_2.txt | ST), longer sleep onset latency (SOL) and wake after sleep onset (WASO), lower sleep efficiency (SE), an increased number of awakenings (NWake), and a reduced amount of slow wave sleep (SWS). The duration of rapid eye movement (REM) sleep did not differ significantly between people with ID and controls, when the meta-a... |
fast_asleep/full_66_0.txt | de Zambotti, M., Trinder, J., Silvani, A., Colrain, I. M., and Baker, F. C. (2018). Dynamic coupling between the central and autonomic nervous systems during sleep: a review. Neurosci. Biobehav. Rev. 90, 84–103. doi: 10.1016/j.neubiorev.2018.03.027 |
fast_asleep/3926054_20_0.txt | Validation of Generalizability
Validation of generalizability was pursued using sleep stage data of 100 people with ID and 100 healthy controls from a published investigation35 undertaken at the Freiburg University Medical Center, Freiburg, Germany. Both ID and CTRL groups consisted of 46 males and 54 females and the a... |
fast_asleep/3926054_1_0.txt | Methods
Eighty-eight participants aged 21–70 years, including 46 with ID and 42 age- and sex-matched controls without sleep complaints, were recruited through www.sleepregistry.nl and completed two nights of laboratory PSG. Data of 100 people with ID and 100 age- and sex-matched controls from a previously reported stud... |
fast_asleep/rsta20140093_0_0.txt |
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