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fast_asleep/full_11_1.txt | paired t-test. All participants completed a written informed consent form approved by the Research Ethics Committee of Osaka University Graduate School of Dentistry and Osaka University Dental Hospital. This study was approved by the ethics committee of the Osaka University Dental Hospital and the Graduate School of D... |
fast_asleep/3926054_31_1.txt | , % 0.935; [0.879, 0.994] .03 0.933; [0.896, 0.971] .0007
NWake 1.046; [1.002, 1.092] .04 1.036; [1.007, 1.066] .02
SSI, 1/hour 1.215; [1.043, 1.416] .01 1.047; [0.985, 1.112] . |
fast_asleep/3926054_5_1.txt | (dis)continuity, we considered that the bout durations of individual sleep stages, as well as the transition probabilities between the stages, could aid to determine the key features of disturbed sleep in ID. In the present study, we therefore systematically investigated the transition probabilities and bout durations... |
fast_asleep/Cellstatetransitions_32_0.txt | Perspectives
Much of the discussion around the concept of cell state was essentially philosophical. How do you define cell state? There are probably as many definitions as there are biological, biochemical and biophysical parameters that can be used to describe a cell. Furthermore, the parameters used to describe cell ... |
fast_asleep/full_136_0.txt | Silvani, A., Calandra-Buonaura, G., Benarroch, E. E., Dampney, R. A. L., and Cortelli, P. (2015). Bidirectional interactions between the baroreceptor reflex and arousal: an update. Sleep Med. 16, 210–216. doi: 10.1016/j.sleep.2014.10.011 |
fast_asleep/rsta20140093_2_1.txt | Changes of sleep-stage transitions due to ageing and sleep disorder
A. Schlemmer, U. Parlitz, S. Luther, N. Wessel and T. Penzel
Published:13 February 2015https://doi.org/10.1098/rsta.2014.0093
Abstract
Transition patterns between different sleep stages are analysed in terms of probability distributions of symbolic seq... |
fast_asleep/full_127_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/3926054_7_0.txt | Table 1Demographics and Self-Reported Sleep (Mean ± Standard Deviation of the Amsterdam Sample).
Characteristic Control (n = 42) Insomnia disorder (n = 46) p
Age, years 46.9 ± 14.6 50.3 ± 13.6 .32
Sex, female/male 32/10 38/8 .60
ISI 1.93 ± 1.91 16.32 ± 4.26 <.0001
Sleep diary
Time in Bed, min 509.3 ± |
fast_asleep/3926054_27_0.txt | Open in new tab
Figure 1
Markovian state diagram for sleep stage transitions. Red arrows indicate transitions with higher probabilities in people with insomnia disorder than in controls: from stage N2 to stage N1 (Wilcoxon W = 1408, Z = 3.70, p =.004) and from stage N2 to stage W (Wilcoxon W = 1276.5, Z = 2.59, p =.096... |
fast_asleep/full_155_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/full_42_0.txt | Author Contributions
AS and TK designed the study and wrote the main manuscript. AS and MK prepared the data sets and analyzed the data. MK and TK contributed to the data collection. AK, HA, and MT revised and commented on the manuscript. All authors reviewed the manuscript and agreed with its content. |
fast_asleep/full_109_0.txt | Google Scholar |
fast_asleep/3926054_30_1.txt | via logistic regression, along with the corresponding p values. A forward stepwise search with sequential chi-squared likelihood ratio tests, starting with age and sex covariates, selected the transition probability from stage N2 to stage N1 in the first step ( χ2(1) = 17.78, p = 2 × 10–5), WASO in the second step (χ2... |
fast_asleep/full_161_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/rsta20140093_46_0.txt | Figure 7.
Figure 7. Same type of diagrams as in figure 6, but for Young/Sleep Disorder versus Young/Normal subjects. (Online version in colour.) |
fast_asleep/rsta20140093_39_0.txt | View inlineView popup
Figure 4.
Figure 4. Distributions of WSE 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_23_2.txt | even greater experimental control (Martínez-Ara et al., 2021 preprint). |
fast_asleep/Cellstatetransitions_34_0.txt | References
Ali, F., Hindley, C., McDowell, G., Deibler, R., Jones, A., Kirschner, M., Guillemot, F. and Philpott, A. (2011). Cell cycle-regulated multi-site phosphorylation of Neurogenin 2 coordinates cell cycling with differentiation during neurogenesis. Development 138, 4267-4277. https://doi.org/10.1242/dev.067900
G... |
fast_asleep/Cellstatetransitions_43_0.txt | Other journals from
The Company of Biologists
Journal of Cell Science |
fast_asleep/rsta20140093_18_0.txt | 2. Data
In order to investigate statistics for sleep stages and sleep transitions, it is important to have high-quality data. This means signals have to be recorded without artefacts and then human sleep scoring using these signals has to be correct and reliable. The latter is done by trained sleep technicians as a typ... |
fast_asleep/full_120_0.txt | Norman, R. G., Scott, M. A., Ayappa, I., Walsleben, J. A., and Rapoport, D. M. (2006). Sleep continuity measured by survival curve analysis. Sleep 29, 1625–1631. doi: 10.1093/sleep/29.12.1625 |
fast_asleep/3926054_12_0.txt | Sleep Stage Transition Probabilities
To quantify sleep stage dynamics, we assessed the empirical probabilities of transitions between the stages including wakefulness, as well as the group-level bout duration distributions for each stage. Sleep stage dynamics were analyzed for the period between sleep onset and the fin... |
fast_asleep/Cellstatetransitions_35_10.txt | Cell. 159, 428-439. https://doi.org/10.1016/j.cell.2014.09.040
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fast_asleep/rsta20140093_5_0.txt | View inlineView popup
Classification of sleep stages (sleep staging) based on EEG signals is obtained by visual inspection by trained technicians. In order to reduce the effort related to visual scoring, sleep stages are scored in 30 s epochs, effectively limiting the temporal resolution of visual classification. Anoth... |
fast_asleep/rsta20140093_25_0.txt | Download figureOpen in new tabDownload PowerPoint
To characterize the transition patterns shown in figure 2, we compute the normalized joint entropies of the corresponding probability distributions {pij} |
fast_asleep/full_19_0.txt | Statistical Analysis
Paired t-tests were used to compare the adaptation and experimental nights, in addition to the mean duration of runs for sleep and each sleep stage. The effect size was presented in Cohen’s d, which was the mean preference index divided by the standard deviation. To individually assess variables th... |
fast_asleep/full_163_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/3926054_48_0.txt | ACKNOWLEDGMENTS
We thank Yvon Sweere for assisting in recruiting and interviewing the participants and the collective efforts of many people who helped with data acquisition and assessment: Frank van Schalkwijk, Rick Wassing, Wisse van der Meijden, Bart te Lindert, Floor van Oosterhout, Jessica Bruyel, Marije Vermeulen... |
fast_asleep/full_46_0.txt | References
Achermann, P., and Borbély, A. A. (2017). “Sleep homeostasis and models of sleep regulation,” in Principles and Practice of Sleep Medicine, eds M. Kryger, T. Roth, and B. Dement (Philadelphia, PA: Elsevier Press), 377–387. doi: 10.1016/B978-0-323-24288-2.00179-3 |
fast_asleep/rsta20140093_66_0.txt | Display Formula
A 3
and
Display Formula
A 4
with Inline Formula being the identity matrix of order n and ⊗ being the Kronecker product defined for n p×q matrix A and a matrix B as follows:
Display Formula
A 5
The Haar matrix has to be normalized if it is used for the Haar transform. |
fast_asleep/Cellstatetransitions_34_18.txt | , K., Yanagida, A., Nishimura, T., Yamaguchi, T., Hirabayashi, M. et al. (2016). Inhibition of apoptosis overcomes stage-related compatibility barriers to chimera formation in mouse embryos. Cell Stem Cell 19, 587-592. https://doi.org/10.1016/j.stem.2016.10.013 |
fast_asleep/Cellstatetransitions_22_0.txt | CLONAL HISTORY
Coordination of cell state transitions can be achieved through cell-intrinsic temporal patterns, such as the cell cycle. Across a number of systems, sister cells have been shown to be highly correlated, undergoing transitions and subsequently dividing at very similar times, as seen in the context of mous... |
fast_asleep/full_158_0.txt | Versace, F., Mozzato, M., De Min Tona, G., Cavallero, C., and Stegagno, L. (2003). Heart rate variability during sleep as a function of the sleep cycle. Biol. Psychol. 63, 149–162. doi: 10.1016/S0301-0511(03)00052-8 |
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fast_asleep/full_26_0.txt | Normalized transition probabilities among the five vigilance states (Wake, N1, N2, N3, and REM) for the two nights are shown in Table 3. The transition from Wake to N1 (Wake → N1) in the adaptation night was significantly higher, whereas that from Wake to N2 (Wake → N2) was significantly lower in the adaptation night t... |
fast_asleep/rsta20140093_69_1.txt | 64-503X
Online ISSN:1471-2962
History:
Published online13/02/2015
Published in print13/02/2015
License:
© 2014 The Author(s) Published by the Royal Society. All rights reserved. |
fast_asleep/3926054_3_0.txt | Conclusions
Quantification of sleep stage dynamics revealed a particular vulnerability of stage N2 in insomnia. The feature characterizes insomnia better than—and independently of—any conventional sleep parameter. |
fast_asleep/rsta20140093_68_0.txt | © 2014 The Author(s) Published by the Royal Society. All rights reserved.
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fast_asleep/full_24_0.txt | Sleep-Stage Continuity and Sleep-Stage Transitions for the Entire Night
The mean continuity time for sleep and each sleep stage is shown in Table 2. The mean duration of sleep runs was significantly shorter in the adaptation night than in the experimental night (p < 0.01). Runs of stage N1 and stage N2 were shorter in ... |
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fast_asleep/3926054_41_2.txt | current protocol does not allow to discriminate possibly different contributions of circadian and homeostatic factors, future studies with more elaborate experimental protocols are needed to disentangle their influences on sleep stage dynamics in ID. The similarity between the sleep patterns in ID and those in aging h... |
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fast_asleep/full_104_0.txt | Lavigne, G. J., Okura, K., Abe, S., Colombo, R., Huynh, N., Montplaisir, J. Y., et al. (2011). Gender specificity of the slow wave sleep lost in chronic widespread musculoskeletal pain. Sleep Med. 12, 179–185. doi: 10.1016/j.sleep.2010.07.015 |
fast_asleep/rsta20140093_63_0.txt | We use the so-called Sylvester construction to build an Hadamard matrix of order n |
fast_asleep/Ventrolateral_preoptic_nucleus_0.txt | The ventrolateral preoptic nucleus (VLPO), also known as the intermediate nucleus of the preoptic area (IPA), is a small cluster of neurons situated in the anterior hypothalamus, sitting just above and to the side of the optic chiasm in the brain of humans and other animals. The brain's sleep-promoting nuclei (e.g., th... |
fast_asleep/Cellstatetransitions_6_0.txt | Global profiling has enabled the identification of a much larger set of defining molecular characteristics. A series of technical advances, in particular in single cell approaches, has allowed us to characterise an ever-greater number of single cells and parameters, tackling systems of increasing complexity and size. T... |
fast_asleep/3926054_6_2.txt | or psychiatric disorders; (2) use of sleep medications within the last 2 months up to and including the recording days; (3) overt shifted or irregular sleep–wake rhythms, assessed using 1 week of actigraphy (Actiwatch AW4, Cambridge Neurotechnology Ltd., Cambridge, United Kingdom or GENEActiv Sleep, Activinsights Ltd.... |
fast_asleep/full_36_0.txt | Quantitative EEG and HRV Variables
Cortical EEG power, such as delta bands, autonomic nervous system function, and sleep-stage distribution fluctuate within a sleep cycle (Brandenberger et al., 2001; Borbély et al., 2016; de Zambotti et al., 2018). Previous studies reported the difference in the sleep architecture betw... |
fast_asleep/Cellstatetransitions_28_1.txt | during pluripotent stem cell differentiation with high predictive power (Sáez et al., 2021). |
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1. Int... |
fast_asleep/3926054_25_1.txt | , p =.096, FDR corrected). Figure 1 illustrates these differences on a Markovian state diagram. |
fast_asleep/full_10_1.txt | the adaptation night. In addition, sleep variables assessed by sleep-stage scoring may not be concordant with those by the quantitative analyses of EEG and heart rate variability (HRV) activities in the adaptation night (Toussaint et al., 1997; Le Bon et al., 2001; Curcio et al., 2004; Israel et al., 2012; Virtanen et... |
fast_asleep/3926054_40_0.txt | The current findings about whole-night sleep stage dynamics in ID differ from those found in other sleep disorders such as sleep-disordered breathing.12–17 Studies on sleep-disordered breathing have reported instability of stage N2, REM sleep, and WASO—inferred from faster decaying bout survival functions for these sta... |
fast_asleep/full_29_0.txt | Figure 1
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Figure 1. Percentage of each sleep stage in each sleep cycle. The percentage of each sleep stage is present as mean and standard deviation (red box: adaptation night, blue box: experimental night). Values that significantly differed between nights are indicated by one (p < 0.05) or two star... |
fast_asleep/Cellstatetransitions_36_0.txt | Google ScholarCrossref
Strawbridge, S. E., Blanchard, G. B., Smith, A., Kugler, H. and Martello, G. (2020). Embryonic stem cells commit to differentiation by symmetric divisions following a variable lag period. bioRxiv 2020.06.17.157578. https://doi.org/10.1101/2020.06.17.157578
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fast_asleep/Cellstatetransitions_34_5.txt | 2021.03.24.436752
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fast_asleep/3926054_27_3.txt | 1, and from stage N3 to stage R. (All p-values are false discovery rate corrected.). |
fast_asleep/Cellstatetransitions_21_0.txt | Coordination of transitions
Most often, cell state transitions occur in a multicellular context. Coordinated transitions ensure that the right number of cells are specified at the correct time and in the correct place. During the workshop, we also discussed the strategies typically employed to achieve such coordination... |
fast_asleep/full_71_0.txt | CrossRef Full Text | Google Scholar |
fast_asleep/Cellstatetransitions_34_11.txt | ogenesis. J. Embryol. Exp. Morphol. 89, 297-316. https://doi.org/10.1242/dev.89.Supplement.297
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Hubaud, A., Regev, I., Mahadevan, L. and Pourquié, O. (2017). Excitable dynamics and yap-dependent mechanical cues drive the segmentation clock. Cell 171, 668-682.e11. https://doi.org/10.1016/j.cell.201... |
fast_asleep/Cellstatetransitions_20_1.txt | exceptions exist, however, as observed in Dictyostelium, in which dedifferentiation occurs rapidly in response to damage, following a trajectory that is remarkably similar to differentiation in reverse (Nichols et al., 2020). In mammalian systems, the most common examples of dedifferentiation occur in response to dama... |
fast_asleep/full_8_1.txt | interactions between the genesis of NREM and REM sleep underlie the stability of sleep cycles overnight (Kishi et al., 2011; Hayashi et al., 2015). Sleep processes and continuity within one sleep cycle are characterized by dynamic phenomena such as transitions among sleep stages (Lo et al., 2004; Kishi et al., 2008, 2... |
fast_asleep/full_118_0.txt | Nonoue, S., Mashita, M., Haraki, S., Mikami, A., Adachi, H., Yatani, H., et al. (2017). Inter-scorer reliability of sleep assessment using EEG and EOG recording system in comparison to polysomnography. Sleep Biol. Rhythms 15, 39–48. doi: 10.1007/s41105-016-0078-2 |
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fast_asleep/3926054_39_0.txt | The main findings of the current study could be replicated in an independent validation sample, confirming their generalizability. There are however a few differences regarding sleep architecture between the samples. In particular, reduced REM sleep and an increased transition probability from stage R to stage W in ID ... |
fast_asleep/3926054_49_8.txt |
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fast_asleep/3926054_4_3.txt | Is the reduced time spent in SWS due to difficulties entering deep sleep or rather because SWS in ID is unstable and rapidly switches to lighter sleep or wakefulness? Several novel methodologies have recently been proposed to extract information about sleep dynamics.11 Among those methods, analyses of the transition p... |
fast_asleep/Cellstatetransitions_35_7.txt | at single-cell resolution. Nature 569, 361-367. https://doi.org/10.1038/s41586-019-1127-1
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Oates, A. C. (2020). Waiting on the Fringe: cell autonomy and signaling delays in segmentation clocks. Curr. Opin. Genet. Dev. 63, 61-70. https://doi.org/10.1016/j.gde.2020.04.008
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fast_asleep/Cellstatetransitions_19_3.txt | enitors 3 days later. Moreover, transplanted bone marrow-derived macrophages fail to completely converge to a microglia phenotype when they graft in the brain and instead retain many molecular characteristics of their cell of origin (Shemer et al., 2018). It therefore appears that, in some cases, the road that cells to... |
fast_asleep/rsta20140093_4_0.txt | Table 1.
Rechtschaffen and Kales classification scheme of sleep stages [2], which is used in this publication. In 2007, stages N3 and N4 were merged into a single class [1,3]. |
fast_asleep/rsta20140093_17_0.txt | This symbolic representation of the sleep process is the starting point of the sleep analysis presented in the following. In §2, the dataset is introduced and an overview of the periods of time spent in different sleep stages is presented. Then in §3a, we focus on an analysis of one-step transition probabilities betwee... |
fast_asleep/Ventrolateral_preoptic_nucleus_1_0.txt | Structure[edit]
At least 80% of neurons in the VLPO that project to the ascending arousal system are GABAergic (neurons that produce GABA).
In vitro studies in rats have shown that many neurons in the VLPO that are inhibited by norepinephrine or acetylcholine are multipolar triangular shaped cells with low threshold sp... |
fast_asleep/rsta20140093_57_0.txt | 6. Conclusion
Typical patterns of sleep-stage transitions of 196 healthy subjects and 98 patients suffering from different sleep disorders have been identified and quantified in terms of transition probabilities. We compared four groups: Young/Normal, Young/Sleep Disorder, Old/Normal and Old/Sleep Disorder. For each su... |
fast_asleep/rsta20140093_21_0.txt | Figure 1.
Figure 1. Fractions of duration of sleep stages awake (W), non-REM1 (N1), non-REM2 (N2), non-REM3 (N3), non-REM4 (N4) and REM (R) in four different age classes (20–37, 38–51, 52–64, 65–95). The left bar in each group gives the average result for the corresponding age quartile, while the bars in the middle (fr... |
fast_asleep/Cellstatetransitions_5_0.txt | Molecular characterisation of cell states
The most common descriptor of cell state relies on the annotation of specific molecules that compose a particular cell. Traditionally, cell states were defined using a small number of parameters or key markers that either showed strong correlation with a functional cell state o... |
fast_asleep/Cellstatetransitions_1_2.txt | the workshop's themed discussions. We also present examples of cell state transitions and describe models and systems that are pushing forward our understanding of how cells rewire their state. |
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fast_asleep/3926054_29_0.txt | Figure 2
Estimated bout survival functions of various bout types in people with insomnia disorder (ID) and controls (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 di... |
fast_asleep/3926054_49_2.txt | MedWorldCat
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fast_asleep/full_36_3.txt | cycles, however, the difference in sleep architecture and EEG power between the two nights disappeared, whereas the RR intervals and HF amplitude, as demonstrated previously (Virtanen et al., 2018), remained lower in the adaptation night than in the experimental night (Figure 2). Previous studies showed that the corre... |
fast_asleep/rsta20140093_14_0.txt | Many sleep disorders, however, also result in changes of sleep transitions. These sleep transitions and the time spent in a specific sleep stage have been analysed previously [7], not only in humans but also in animals and some universal laws have been found and described [8]. It is also known that sleep changes with a... |
fast_asleep/Cellstatetransitions_41_0.txt | We have had great feedback from authors who have benefitted from our Read & Publish agreement with their institution and have been able to publish Open Access with us without paying an APC. Read what they had to say. |
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fast_asleep/rsta20140093_55_0.txt | Download figureOpen in new tabDownload PowerPoint
The distributions show a very similar pattern for all group comparisons exhibiting a very strong increase in the fraction of non-significant cases for Markov order k=2. On the other hand, the null hypothesis assuming a first-order Markov process has to be rejected in mo... |
fast_asleep/rsta20140093_41_0.txt | Download figureOpen in new tabDownload PowerPoint
The results for the WSE and the HSE are very similar, the distributions show a nearly identical shape. Tables 3 and 4 confirm what already can be seen in figures 4 and 5. The age effect on the spectral entropies can be differentiated at a high significance level. Howeve... |
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fast_asleep/full_52_0.txt | Berry, R., Gamaldo, C., Hardig, S., Lloyd, R., Marcus, C., and Vaughn, B. (2014). The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications, Version2.1. Darien, IL: American Academy of Sleep Medicine |
fast_asleep/rsta20140093_14_1.txt | of light sleep (N1 and N2) as well as time spent awake (W) increases with age. This seems to be a normal ageing process. But how does the frequency and the pattern of transitions between sleep stages change during ageing or with sleep disorder? |
fast_asleep/rsta20140093_50_0.txt | 5. Markov order tests
Figure 8 clearly indicates that an investigation of multiple transitions instead of single transitions can reveal subtle information about the sleep process. This raises the question which number of transition can be considered as appropriate for further analysis of symbolic dynamics. We are going... |
fast_asleep/full_162_0.txt | Vyazovskiy, V. V., and Delogu, A. (2014). NREM and REM sleep: complementary roles in recovery after wakefulness. Neuroscientist 20, 203–219. doi: 10.1177/1073858413518152 |
fast_asleep/3926054_10_2.txt | .23 The first night served as an adaption night, and data from the second night were used for analyses. |
fast_asleep/full_149_0.txt | PubMed Abstract | CrossRef Full Text | Google Scholar |
fast_asleep/full_14_0.txt | Sleep Cycles
The sleep cycle was assessed with reference to the method proposed by Feinberg (1974). A sleep cycle was defined as the time from the end of REM sleep to the end of the next REM sleep. The first sleep cycle was defined as the time from sleep onset to the end of the first REM sleep. REM sleep was considered... |
fast_asleep/3926054_49_4.txt | aglioni C Regen W Teghen A et al. . Sleep changes in the disorder of insomnia: a meta-analysis of polysomnographic studies. Sleep Med Rev. 2014; 18(3): 195–213.
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11. Bianchi MT Thomas RJ. Technical advances in the characterization of the complexity of sleep and sleep disorders. Prog ... |
fast_asleep/full_82_0.txt | Hirshkowitz, M., Moore, C. A., Hamilton, C. R. III, Rando, K. C., and Karacan, I. (1992). Polysomnography of adults and elderly: sleep architecture, respiration, and leg movement. J. Clin. Neurophysiol. 9, 56–62. |
fast_asleep/3926054_7_1.txt | 50.2 522.1 ± 66.5 .36
TST, min 436.5 ± 34.5 339.1 ± 65.5 <.0001
SOL, min 13.3 ± 6.9 39.8 ± 42.8 <.0001
SE, % 90.3 ± 4.5 68.8 ± 14.7 <.0001
NWake 1.7 ± 0.9 2.6 ± 1.6 .003
WASO, min 33.1 |
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