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fast_asleep/3926054_50_4.txt | i A Nissen C et al. . Does REM sleep contribute to subjective wake time in primary insomnia? A comparison of polysomnographic and subjective sleep in 100 patients. J Sleep Res. 2008; 17(2): 180–190. Corrigendum J Sleep Res 2012; 21(4):484.
Google ScholarCrossrefPubMedWorldCat
36. Kales A Rechtschaffen A, editors. A Man... |
fast_asleep/3926054_28_1.txt | survival functions with parametric methods and instead tested the between-group differences in bout duration distributions without assumptions using nonparametric procedures. Permutation Mann–Whitney tests33 revealed that, as compared to CTRL, people with ID exhibited a significantly faster decaying sleep bout surviva... |
fast_asleep/Cellstatetransitions_7_0.txt | Molecular characterisation of cell states does not, in principle, require previous knowledge of the system. However, annotation of such datasets often relies on knowledge of marker expression. With single cell assays, we can obtain many parameters describing very complex multicellular systems. However, there is a signi... |
fast_asleep/rsta20140093_7_0.txt | Current evaluations of sleep consider mainly the following periods of time: |
fast_asleep/full_56_0.txt | Borbély, A. A., Daan, S., Wirz-Justice, A., and Deboer, T. (2016). EEG beta power and heart rate variability describe the association between cortical and autonomic arousals across sleep. J. Sleep Res. 25, 131–143. doi: 10.1111/jsr.12371 |
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Theme issue ‘Enhancing dynamical signatures of complex systems through symbolic computation’ compiled and edited by Alberto P... |
fast_asleep/rsta20140093_13_0.txt | In general, we know that healthy middle-aged people spend approximately 5–10% of the night awake, 10% in N1, 50% in N2, 15–20% in N3/N4 and 15–20% in REM sleep. Other quantities which are sometimes considered in publications take the number of awakenings or the number of transitions between sleep stages into account. T... |
fast_asleep/3926054_50_3.txt | event data. Comput Stat Data Anal. 2010; 54(1):78–89.
Google ScholarCrossrefWorldCat
33. Fay MP Shih JH. Permutation tests using estimated distribution functions. J Am Stat Assoc. 1998; 93(441):387–396.
Google ScholarCrossrefWorldCat
34. R Core Team. R: A Language and Environment for Statistical Computing. Vienna: R F... |
fast_asleep/full_28_0.txt | Sleep Variables for Each Sleep Cycle
The percentage of each sleep stage in each sleep cycle is shown in Figure 1. In order to compare the variables for sleep cycles between the adaptation night and the experimental night within a subject, the same number of sleep cycles was analyzed (cycle 1 and cycle 2: n = 74, cycle ... |
fast_asleep/Cellstatetransitions_35_11.txt | and Hannezo, E. (2021). Rigidity percolation uncovers a structural basis for embryonic tissue phase transitions. Cell 184, 1914-1928.E19. https://doi.org/10.1016/j.cell.2021.02.017 S0092867421001677.
Google ScholarCrossref
Pijuan-Sala, B., Griffiths, J. A., Guibentif, C., Hiscock, T. W., Jawaid, W., Calero-Nieto, F. J |
fast_asleep/full_13_0.txt | PSG recordings were performed using surface electroencephalography (EEGs: C3-A2, C4-A1, O1-A2, O2-A1, F3-A2, F4-A1, Fp1-A2, and Fp2-A1), bilateral electrooculography (EOG), lead II electrocardiography (ECG), and chin electromyography (EMG). Signals were amplified, filtered (EEG, EOG, and ECG: 0.3–70 Hz; EMG |
fast_asleep/full_172_0.txt | Alessandro Silvani, University of Bologna, Italy
Reviewed by: |
fast_asleep/rsta20140093_1_0.txt |
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fast_asleep/Cellstatetransitions_34_10.txt | Crossref
Hayashi, K., Ohta, H., Kurimoto, K., Aramaki, S. and Saitou, M. (2011). Reconstitution of the mouse germ cell specification pathway in culture by pluripotent stem cells. Cell 146, 519-532. https://doi.org/10.1016/j.cell.2011.06.052
Google ScholarCrossref
Heasman, J., Snape, A., Smith, J. and Wylie, C. C. (1985... |
fast_asleep/rsta20140093_57_1.txt | figure 3), which might allow for a distinction of healthy subjects and subjects with sleep disorder. By contrast, the spectral entropy distributions (WSE and HSE) which have been presented in figures 4 and 5 indicate a relatively clear distinction between young and old subjects. Furthermore, one-step transitions are vi... |
fast_asleep/Cellstatetransitions_34_8.txt | of distinct hematopoietic differentiation programs in vivo. Cell Stem Cell 1, 218-229. https://doi.org/10.1016/j.stem.2007.05.015
Google ScholarCrossref
Gonzales, K. A. U., Liang, H., Lim, Y.-S., Chan, Y.-S., Yeo, J.-C., Tan, C.-P., Gao, B., Le, B., Tan, Z.-Y., Low, K.-Y. et al. (2015). Deterministic restriction on p... |
fast_asleep/rsta20140093_37_0.txt | Table 3.
p-Values of a Wilcoxon rank-sum test performed for all pairs of WSE distributions shown in figure 4a. |
fast_asleep/rsta20140093_15_1.txt | 8] investigated transitions between wakefulness and sleep during the sleep period in order to derive models for the process of sleep stages (where Lo et al. reduced the transitions to wake–sleep transitions, only, by lumping all sleep stages into one class). To gain further insight into transition patterns including mu... |
fast_asleep/full_58_0.txt | Brandenberger, G., Ehrhart, J., Piquard, F., and Simon, C. (2001). Inverse coupling between ultradian oscillations in delta wave activity and heart rate variability during sleep. Clin. Neurophysiol. 112, 992–996. doi: 10.1016/S1388-2457(01)00507-7 |
fast_asleep/Cellstatetransitions_30_1.txt | 2020) implies the future state (e.g. of a differentiated cell) depends exclusively on the previous state (e.g. of the progenitor), without any previous memory of the states that preceded it. |
fast_asleep/rsta20140093_33_0.txt | Display Formula
3.3
The elements Inline Formula of the l×m matrix Inline Formula are called Walsh/Haar transform coefficients and they are used to compute the corresponding l×m periodogram matrix of the temporal window [w,w+l−1] |
fast_asleep/full_17_1.txt | with a 0.24 s overlap every 10 s, and the data for three units were averaged to obtain a value every 30 s. The limits for band frequencies were as follows: delta, 0.5–4 Hz; theta, 4–8 Hz; alpha, 8–12 Hz; sigma, 12–15 Hz; low beta, 15–23 Hz; high beta, 23–32 Hz. |
fast_asleep/Cellstatetransitions_35_5.txt | e45642. https://doi.org/10.15252/embr.201745642
Google ScholarCrossref
Nichols, J. and Smith, A. (2009). Naive and primed pluripotent states. Cell Stem Cell 4, 487-492. https://doi.org/10.1016/j.stem.2009.05.015
Google ScholarCrossref
Nichols, J. M. E., Antolović, V., Reich, J. D., Brameyer, S., Paschke, P. and |
fast_asleep/3926054_4_4.txt | have demonstrated,12–17 indices of clinical relevance can be derived from these analyses in other sleep-related conditions such as sleep-disordered breathing, providing more sensitive measures of pathological sleep patterns and of responses to interventions than the conventional sleep parameters. |
fast_asleep/3926054_49_9.txt | e293–e294.
Google ScholarCrossrefWorldCat
21. Bastien CH Vallières A Morin CM. Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Med. 2001; 2(4): 297–307.
Google ScholarCrossrefPubMedWorldCat
22. Danker-Hopfe H Anderer P Zeitlhofer J et al. . Interrater reliability for sleep s... |
fast_asleep/full_55_0.txt | CrossRef Full Text | Google Scholar |
fast_asleep/Cellstatetransitions_42_0.txt | Recommended for you by TrendMD
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fast_asleep/3926054_49_5.txt | Ayappa I Walsleben JA Rapoport DM. Sleep continuity measured by survival curve analysis. Sleep. 2006; 29(12): 1625–1631.
Google ScholarCrossrefPubMedWorldCat
13. Swihart BJ Caffo B Bandeen-Roche K Punjabi NM. Characterizing sleep structure using the hypnogram. J Clin Sleep Med. 2008; 4(4): 349–355.
Google ScholarPubMe... |
fast_asleep/full_148_0.txt | Thomas, R. J., Mietus, J. E., Peng, C.-K., Guo, D., Gozal, D., Montgomery-Downs, H., et al. (2014). Relationship between delta power and the electrocardiogram-derived cardiopulmonary spectrogram: possible implications for assessing the effectiveness of sleep. Sleep Med. 15, 125–131. doi: 10.1016/j.sleep.2013.10.002 |
fast_asleep/Cellstatetransitions_2_0.txt | Keywords:Cell state transitions, Definition of cell states, Heterogeneity, Modelling
Introduction
The term ‘cell state transition’ refers to the process by which cells change states over time. Such transitions are an intrinsic part of embryonic development as cells progressively differentiate. They are also crucial dur... |
fast_asleep/full_103_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/rsta20140093_6_1.txt | with a duration of roughly 90 min and it is repeated five to six times during the night. Sleep is often interrupted by very brief awakenings. Usually, they are so short that they are not remembered and good sleep is experienced. The longer the awakenings are the more likely they are realized and memorized which leads ... |
fast_asleep/Cellstatetransitions_34_3.txt | elegans with data-fitted landscape models. PLoS Comput. Biol. 17, e1009034. https://doi.org/10.1371/journal.pcbi.1009034
Google ScholarCrossref
Chaigne, A., Labouesse, C., White, I. J., Agnew, M., Hannezo, E., Chalut, K. J. and Paluch, E. K. (2020). Abscission couples cell division to embryonic stem cell fate. Dev. Ce... |
fast_asleep/3926054_51_2.txt | 1137.
Google ScholarCrossrefPubMedWorldCat
55. Benjamins JS Migliorati F Dekker K et al. . Insomnia heterogeneity: characteristics to consider for data-driven multivariate subtyping. Sleep Med Rev. In press. doi: 10.1016/j.smrv.2016.10.005.
Google ScholarWorldCat
Author notes
Authors Yishul Wei and Michele A. Colombo c... |
fast_asleep/full_50_0.txt | Åkerstedt, T., Hume, K., Minors, D., and Waterhouse, J. (1998). Experimental separation of time of day and homeostatic influences on sleep. Am. J. Physiol. Regul. Integr. Comp. Physiol. 274, 1162–1168. doi: 10.1152/ajpregu.1998.274.4.r1162 |
fast_asleep/full_35_0.txt | Sleep-Stage Dynamics in the Entire Night and Sleep Cycles
The present study revealed that the sleep macrostructure on the adaptation night was characterized by reduced sleep efficiency, less REM sleep, more stage N1, more wakefulness, and more frequent arousal than in the experimental night (Table 1). This study suppor... |
fast_asleep/full_85_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/full_175_0.txt | Disclaimer: 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 guar... |
fast_asleep/full_91_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/3926054_23_4.txt | 43.4 ± 10.6 43.1 ± 12.6 933 –0.27 .79
Stage N3, % 26.5 ± 9.7 23.4 ± 12.2 809.5 –1.30 .19
Stage R, % 25.2 ± 7.0 24.5 ± 12.6 874 –0.76 .44
NWake = number of awakenings; SE = sleep efficiency; SOL = sleep onset latency; SSI = stage shift index; TR |
fast_asleep/3926054_31_6.txt | .051] <.0001
Transition probability from stage W to stage N1, % 0.999; [0.972, 1.026] .92 0.962; [0.941, 0.983] .0004
Mean sleep bout duration, minutes 0.955; [0.921, 0.989] .01 0.964; [0.944, 0.985] .0007
Mean wake bout duration, minutes 1.304; |
fast_asleep/3926054_35_0.txt | The empirical transition probabilities and their comparisons between cases and controls in the Freiburg validation sample are detailed in the Supplementary Material. The two rightmost columns of Table 4 show the age- and sex-adjusted ORs of having ID in the Freiburg validation sample and the corresponding p values. Of ... |
fast_asleep/Cellstatetransitions_35_19.txt | Dalton, S. (2015). Cell-cycle control of bivalent epigenetic domains regulates the exit from pluripotency. Stem Cell Rep. 5, 323-336. https://doi.org/10.1016/j.stemcr.2015.07.005
Google ScholarCrossref
Spemann, H. and Mangold, H. (1924). über Induktion von Embryonalanlagen durch Implantation artfremder Organisatoren. ... |
fast_asleep/full_122_0.txt | Okura, M., Nonoue, S., Tsujisaka, A., Haraki, S., Yokoe, C., Taniike, M., et al. (2020). Polysomnographic analysis of respiratory events during sleep in young nonobese Japanese adults without clinical complaints of sleep apnea. J. Clin. Sleep Med. 16, 1303–1310. doi: 10.5664/jcsm.8498 |
fast_asleep/3926054_50_1.txt | MD et al. . Quantification of the fragmentation of rest-activity patterns in elderly individuals using a state transition analysis. Sleep. 2011; 34(11): 1569–1581.
Google ScholarCrossrefPubMedWorldCat
29. Klerman EB Wang W Duffy JF Dijk DJ Czeisler CA Kronauer RE. Survival analysis indicates that age-related decline i... |
fast_asleep/Cellstatetransitions_20_0.txt | Transitions between states
Reversible transitions, irreversible transitions and plasticity
Throughout the talks and discussions, the issue of ‘spontaneous’ cell state reversibility, as opposed to experimentally induced reprogramming, was also highlighted. Most biological transitions have an intrinsic directionality und... |
fast_asleep/rsta20140093_58_0.txt | In this study, we also analysed transitions between N3 and N4 because we used scorings from a large study which used Rechtschaffen & Kales [2] scorings. We observe a considerable number of transitions between stages N3 and N4 and in this, we also observe differences between normal subjects and patients with sleep disor... |
fast_asleep/full_2_1.txt | IRCCS), Italy |
fast_asleep/full_62_0.txt | Curcio, G., Ferrara, M., Piergianni, A., Fratello, F., and De Gennaro, L. (2004). Paradoxes of the first-night effect: a quantitative analysis of antero-posterior EEG topography. Clin. Neurophysiol. 115, 1178–1188. doi: 10.1016/j.clinph.2003.12.018 |
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fast_asleep/Cellstatetransitions_23_1.txt | to have an influence on the ability of CNS progenitor cells to proliferate and differentiate (Segel et al., 2019). The mechanical properties of cells can regulate cell signalling, for example by influencing ERK signalling, and in turn modify cell states (Boocock et al., 2021; De Belly et al., 2021). Similarly, we saw ... |
fast_asleep/full_90_0.txt | Kishi, A., Haraki, S., Toyota, R., Shiraishi, Y., Kamimura, M., Taniike, M., et al. (2020). Sleep stage dynamics in young patients with sleep bruxism. Sleep 43:zsz202. doi: 10.1093/sleep/zsz202 |
fast_asleep/Cellstatetransitions_29_1.txt | accounting for dynamics and changes in dynamics to address changes in cell states (Negrete et al., 2021). |
fast_asleep/3926054_4_0.txt | insomnia disorder, sleep stage, sleep architecture, polysomnography, sleep fragmentation, non-REM sleep, hypnogram, Markov chain, feature selection, binary classification
Topic: sleep stageswakefulnesssleepinsomniaemotional vulnerability
Issue Section: Insomnia and Psychiatric Disorders
INTRODUCTION
Insomnia disorder (... |
fast_asleep/Cellstatetransitions_35_9.txt | 34-low/negative hematopoietic stem cell. Science 273, 242-245. https://doi.org/10.1126/science.273.5272.242
Google ScholarCrossref
Pagliuca, F. W., Millman, J. R., Gürtler, M., Segel, M., Van Dervort, A., Ryu, J. H., Peterson, Q. P., Greiner, D. and Melton, D. A. (2014). Generation of functional human pancreatic β cell... |
fast_asleep/full_51_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/full_28_1.txt | 82, p = 0.022, ε = 0.38, partial η2 = 0.085]. Post hoc comparisons between the two nights in the first sleep cycle revealed that the percentages of stage Wake and N1 were significantly higher (p < 0.01), and that of stage N3 was significantly lower (p < 0.01) in the adaptation night than in the experimental night. Post... |
fast_asleep/full_140_0.txt | Tamaki, M., Nittono, H., Hayashi, M., and Hori, T. (2005a). Examination of the first-night effect during the sleep-onset period. Sleep 28, 195–202. doi: 10.1093/sleep/28.2.195 |
fast_asleep/3926054_51_4.txt | Cataplexy: A Consensus Statement
Christian R. Baumann et al., Sleep, 2014
Short Daytime Naps Briefly Attenuate Objectively Measured Sleepiness Under Chronic Sleep Restriction
Jared M Saletin et al., Sleep, 2017
0746 Dynamics of Sleep Stage Transitions in Patients with Narcolepsy and Other Hypersomnias
A Kishi et al., ... |
fast_asleep/Cellstatetransitions_35_0.txt | Google ScholarCrossref
McGinn, J., Hallou, A., Han, S., Krizic, K., Ulyanchenko, S., Iglesias-Bartolome, R., England, F. J., Verstreken, C., Chalut, K. J., Jensen, K. B. et al. (2021). A biomechanical switch regulates the transition towards homeostasis in oesophageal epithelium. Nat. Cell Biol. 23, 511-525. https://do... |
fast_asleep/full_10_0.txt | The characteristics of sleep in the adaptation night were previously investigated by conventional analyses of sleep architecture such as the amount of each sleep stage. Recent studies analyzed sleep continuity and characterized the patterns of sleep-stage transitions in order to elucidate the dynamic nature of sleep re... |
fast_asleep/3926054_30_2.txt | N2 to stage N1 over the other sleep parameters in ID–CTRL discrimination. |
fast_asleep/rsta20140093_56_0.txt | These results indicate very clearly that the time series of transitions of sleep stages seems to follow a second-order Markov process. |
fast_asleep/Cellstatetransitions_35_14.txt | org/10.1016/j.endeavour.2007.05.005
Google ScholarCrossref
Saelens, W., Cannoodt, R., Todorov, H. and Saeys, Y. (2019). A comparison of single-cell trajectory inference methods. Nat. Biotechnol. 37, 547-554. https://doi.org/10.1038/s41587-019-0071-9
Google ScholarCrossref
Sáez, M., Blassberg, R., Camacho-Aguilar, |
fast_asleep/full_40_0.txt | Data Availability Statement
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s. |
fast_asleep/rsta20140093_19_0.txt | The sleep recordings for this analysis were recorded from 196 healthy subjects, who were more or less equally distributed over four age classes. An effort was made to include a similar number of male and female subjects. All subjects were recorded in a sleep center for two subsequent nights using cardiorespiratory poly... |
fast_asleep/3926054_26_0.txt |
Table 3Empirical Transition Probabilities Between Sleep Stages, Expressed as Percentage (Mean ± Standard Deviation of the Amsterdam Sample) of Epochs of the Stage Indicated at the Left Side of Each Row That Transition to Epochs of the Stage Indicated at the Top of Each Column.
a. Control (n = 42).
Transition probabili... |
fast_asleep/rsta20140093_23_1.txt | wakefulness or lighter sleep stages which are non-adjacent are more likely. Young healthy subjects have the highest probabilities for transitions in and out of N3 and N4. This corresponds to figure 1, which shows that these subjects have the highest percentage of N3 and N4 in the night and therefore it is likely that ... |
fast_asleep/Cellstatetransitions_18_1.txt | oscillate autonomously but are poorly coordinated, and coordination is only achieved at the population level (Hubaud et al., 2017; Oates, 2020). Several mechanisms have been proposed to allow coordination, including quorum sensing of signalling molecules, adhesion and mechanics-mediated signalling. Here, the cell stat... |
fast_asleep/full_54_0.txt | Bonnet, M. H., and Arand, D. L. (1997). Heart rate variability: sleep stage, time of night, and arousal influences. Electroencephalogr. Clin. Neurophysiol. 102, 390–396. doi: 10.1016/S0921-884X(96)96070-1 |
fast_asleep/3926054_31_2.txt | 14
WASO, minutes 1.027; [1.008, 1.045] .004 1.015; [1.006, 1.025] .0008
Stage N1, minutes 1.052; [1.020, 1.085] .001 1.009; [0.991, 1.027] .32
Stage N3, minutes 0.990; [0.981, 1.000] .06 0.992; [0.981, 1 |
fast_asleep/full_12_0.txt | Polysomnography and Sleep Stages
Polysomnographic recordings were performed on two consecutive nights in a sleep laboratory at Osaka University Graduate School of Dentistry. All subjects completed the Pittsburgh Sleep Quality Index (PSQI) for Japanese (Doi et al., 2000) and Self-rating Depression Scale: SDS (Zung, 1965... |
fast_asleep/3926054_24_0.txt | WASO percentage is relative to TRT–SOL. Sleep stage percentages are relative to TST. Bold font highlights significant group differences. |
fast_asleep/rsta20140093_26_0.txt | Display Formula
3.1
where N=6 is the number of sleep stages W, N1, N2, N3, N4 and REM. The normalization by the entropy Inline Formula of a uniform two-dimensional distribution renders H to lie in the range [0,1]. The normalized joint entropy H is computed for each subject and low values of H indicate less complex tran... |
fast_asleep/Cellstatetransitions_38_0.txt | Journal Meeting: From Stem Cells to Human Development
Promotional banner for Development 2024 Journal Meeting
Register now for the 2024 Development Journal Meeting From Stem Cells to Human Development. Early-bird registration deadline: 3 May. Abstract submission deadline: 21 June. |
fast_asleep/full_160_0.txt | Virtanen, I., Kalleinen, N., Urrila, A. S., and Polo-Kantola, P. (2018). Sleep and cardiovascular function first-night effect on cardiac autonomic function in different female reproductive states. J. Sleep Res. 27, 150–158. doi: 10.1111/jsr.12560 |
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fast_asleep/Cellstatetransitions_10_0.txt | Functional characterisation requires appreciation of the biology of the system and can be challenging at the single cell level. Moreover, in complex and dynamic contexts, it can be difficult to link the functional response to a molecular phenotype. Often, linking function to molecular profiling relies on dividing the c... |
fast_asleep/rsta20140093_42_0.txt | (c) Transition graphs
In this section, the difference of transition probability matrices of different groups of subjects is used to analyse the impact of age and sleep disorder on one-step transition probabilities. These differences are visualized using pruned graphical representations where links between the sleep sta... |
fast_asleep/Cellstatetransitions_36_8.txt | 38/s41556-021-00700-2
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Yao, Y. and Wang, C. (2020). Dedifferentiation: inspiration for devising engineering strategies for regenerative medicine. npj Regen. Med. 5, 14. https://doi.org/10.1038/s41536-020-00099-8
Google ScholarCrossref
Zamir, A., Li, G., Chase, K., Moskovitch, R., Sun, B. and Zarit... |
fast_asleep/3926054_11_1.txt | defined as the number of transitions between distinct stages per hour, was quantified as an index of overall sleep fragmentation.24,25 |
fast_asleep/3926054_42_1.txt | epoch of stage N2) than that used in the current study and also reported no group difference in SOL. Further analyses confirmed that SOL did not differ between groups in either sample, regardless of the definition of sleep onset (results not shown). Finally, the meta-analysis suggested that REM sleep did not differ be... |
fast_asleep/3926054_38_0.txt | DISCUSSION
The current study is, to our knowledge, the first to analyze and compare the whole-night sleep stage dynamics of people with ID and healthy controls. We found that people with ID have a higher probability for stage N2 bouts to terminate early and to transition from stage N2 to stage N1 or wakefulness. Notabl... |
fast_asleep/full_169_0.txt | Citation: Shirota A, Kamimura M, Kishi A, Adachi H, Taniike M and Kato T (2021) Discrepancies in the Time Course of Sleep Stage Dynamics, Electroencephalographic Activity and Heart Rate Variability Over Sleep Cycles in the Adaptation Night in Healthy Young Adults. Front. Physiol. 12:623401. doi: 10.3389/fphys.2021.6234... |
fast_asleep/3926054_23_0.txt | Table 2Conventional Polysomnographic Sleep Parameters (Mean ± Standard Deviation of the Amsterdam Sample).
Sleep parameter Control
(n = 42) Insomnia disorder
(n = 46) Wilcoxon rank-sum statistic W Z p
TRT, minutes 481.4 ± 49.1 479.9 ± 57.3 879 –0.72 .47
TST, minutes 431.0 ± 51.2 408.0 ± 54.5 693 –2.28 .02 |
fast_asleep/full_132_0.txt | Sforza, E., Chapotot, F., Pigeau, R., and Buguet, A. (2008). Time of night and first night effects on arousal response in healthy adults. Clin. Neurophysiol. 119, 1590–1599. doi: 10.1016/j.clinph.2008 |
fast_asleep/3926054_26_2.txt | 0.15 ± 0.28 1.65 ± 1.20 96.76 ± 1.11 0.28 ± 0.37
R 2.99 ± 2.29 1.29 ± 1.09 2.41 ± 1.57 0.01 ± 0.08 93.29 ± 3.01
b. Insomnia disorder (n = 46).
Transition probability Pij, expressed in % to stage …
W N1 N2 N3 R
Transition from stage … W |
fast_asleep/full_13_3.txt | not exhibit signs or symptoms of sleep apnea (Okura et al., 2020). |
fast_asleep/full_108_0.txt | Lee, D., Cho, C., Han, C., Bok, K., and Moon, J. H. (2016). Sleep irregularity in the previous week influences the first-night effect in polysomnographic studies. Psychiatry Investig. 13, 203–209. |
fast_asleep/Cellstatetransitions_3_0.txt | The Company of Biologists virtual workshop on ‘Cell State Transitions: Approaches, Experimental Systems and Models’ brought together experimentalists and theorists from different backgrounds who are studying cell state transitions across various systems. In themed discussions, we tackled three topics: the definition of... |
fast_asleep/full_41_0.txt | Ethics Statement
The studies involving human participants were reviewed and approved by the Research Ethics Committee of Osaka University Graduate School of Dentistry and Osaka University Dental Hospital (H25-E9-5, H29-E48-3). The patients/participants provided their written informed consent to participate in this stud... |
fast_asleep/full_159_0.txt | CrossRef Full Text | Google Scholar |
fast_asleep/Ventrolateral_preoptic_nucleus_3_0.txt | Clinical significance[edit]
Insomnia[edit]
Elderly human patients with more galanin neurons in their intermediate nucleus (the human equivalent of the VLPO galanin neurons in rodents) have better, more continuous sleep. A reduced number of VLPO neurons is associated with more fragmented sleep (more awakenings throughou... |
fast_asleep/Ventrolateral_preoptic_nucleus_3_1.txt | VLPO neurons.
Sedative/hypnotic drugs[edit]
Many sedative/hypnotic drugs act by binding to and potentiating GABA-A receptors. These include older drugs such as ethanol, chloral hydrate and barbiturates, as well as newer benzodiazepines and "non-benzodiazepine" drugs (such as zolpidem, which bind to the same receptor ... |
fast_asleep/3926054_15_0.txt | Statistical Analyses of Group Differences
Group differences in the conventional sleep parameters were evaluated with Wilcoxon rank-sum tests. The rank-sum statistic W (also known as the Mann–Whitney U statistic), is mathematically equal to the product of group sizes
times the area under the receiver operating character... |
fast_asleep/rsta20140093_20_0.txt | Figure 1 shows relative durations of sleep stages for four age quartiles, distinguishing subjects with normal sleep from those with sleep disorder. For all age quartiles the fraction of N1 sleep is larger for patients suffering from sleep disorder compared with normal subjects. The fractions of sleep stages reflect wel... |
fast_asleep/Cellstatetransitions_27_0.txt | Throughout the workshop, it was clear that the definitions of cell states that are employed determine the way we approach and model transitions. Defining cell states transcriptionally leads to largely descriptive analyses of cell state transitions. These analyses often leverage dimensionality reduction techniques to id... |
fast_asleep/full_18_0.txt | Heart rate analysis was performed using complex demodulation (CD) (Shin et al., 1989). The oscillations can be characterized based on the heart rate accelerating or slowing, the wavelength, and/or the amplitude (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiol... |
fast_asleep/Cellstatetransitions_35_1.txt | 38/s41556-021-00679-w
Google ScholarCrossref
Mojtahedi, M., Skupin, A., Zhou, J., Castaño, I. G., Leong-Quong, R. Y. Y., Chang, H., Trachana, K., Giuliani, A. and Huang, S. (2016). Cell fate decision as high-dimensional critical state transition. PLoS Biol. 14, e2000640. https://doi.org/10.1371/journal.pbio.2000640
Goo... |
fast_asleep/full_78_0.txt | Hayano, J., Taylor, J. A., Yamada, A., Mukai, S., Hori, R., Asakawa, T., et al. (1993). Continuous assessment of hemodynamic control by complex demodulation of cardiovascular variability. Am. J. Physiol. Heart Circ. Physiol. 264(4 Pt 2), H1229–H1238. doi: 10.1152/ajpheart.1993.264.4.h1229 |
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