A role for sleep disorders in pregnancy complications: challenges and opportunities
Bibliographic record
Abstract
See related article, page 52Sleep and sleeplike states have been identified in all mammalian species, other vertebrates such as birds,1Zepelin H. Rechtschaffen A. Mammalian sleep, longevity, and energy metabolism.Brain Behav Evol. 1974; 10: 425-470Crossref PubMed Scopus (209) Google Scholar, 2Campbell S.S. Tobler I. Animal sleep: a review of sleep duration across phylogeny.Neurosci Biobehav Rev. 1984; 8: 269-300Crossref PubMed Scopus (520) Google Scholar, 3Rechtschaffen A. Current perspectives on the function of sleep.Perspect Biol Med. 1998; 41: 359-390Crossref PubMed Scopus (233) Google Scholar, 4McNamara P. Barton R.A. Nunn C.L. Evolution of sleep. Cambridge University Press, New York, NY2009Google Scholar and invertebrates (eg, fruit fly or Drosophila melanogaster).5Shaw P.J. Cirelli C. Greenspan R.J. Tononi G. 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Preeclampsia and sleep-disordered breathing: a case-control study.Pregnancy Hypertens. 2013; 3: 133-139PubMed Scopus (20) Google Scholar the assessment of sleep quality and quantity during pregnancy and its consequences has not received the attention it deserves. Indeed, assessment of sleep has not been an integral part of prenatal care, even though many sleep disorders that affect pregnant women (eg, obstructive apnea) are amenable to treatment, and therapy can have benefits.24Poyares D. Guilleminault C. Hachul H. et al.Pre-eclampsia and nasal CPAP, part 2: hypertension during pregnancy, chronic snoring, and early nasal CPAP intervention.Sleep Med. 2007; 9: 15-21Abstract Full Text Full Text PDF PubMed Scopus (117) Google Scholar, 25Caughey A.B. Lee K.A. CPAP for the prevention of pre-eclampsia: is this a clinically promising intervention?.Sleep Med. 2007; 9: 1-2Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar, 26Guilleminault C. Palombini L. Poyares D. Takaoka S. 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Neuroscience: garbage truck of the brain.Science. 2013; 340: 1529-1530Crossref PubMed Scopus (354) Google Scholar to be the "garbage truck of the brain" (Figure 2). The breakthrough is that, during natural sleep or anesthesia, there was a 60% increase in the interstitial space, and increased clearance of β-amyloid; hence, the proposal that the purpose of sleep is to remove neurotoxic waste products formed while we are awake63Xie L. Kang H. Xu Q. et al.Sleep drives metabolite clearance from the adult brain.Science. 2013; 342: 373-377Crossref PubMed Scopus (2376) Google Scholar (Figure 3). The potential implications are major: sleep deprivation is a risk factor for neurodegenerative diseases.64Chokroverty S. Sleep and neurodegenerative diseases.Semin Neurol. 2009; 29: 446-467Crossref PubMed Scopus (35) Google Scholar, 65Raggi A. Ferri R. Sleep disorders in neurodegenerative diseases.Eur Neurol. 2010; 17: 1326-1338Google Scholar, 66Osorio R.S. Pirraglia E. Aguera-Ortiz L.F. et al.Greater risk of Alzheimer's disease in older adults with insomnia.J Am Geriatr Soc. 2011; 59: 559-562Crossref PubMed Scopus (112) Google ScholarFigure 2Pathway to clear cellular waste from the brain using the glymphatic systemReproduced with permission from American Association for the Advancement of Science, from Nedergaard.62Nedergaard M. Neuroscience: garbage truck of the brain.Science. 2013; 340: 1529-1530Crossref PubMed Scopus (354) Google ScholarShow full captionCerebrospinal fluid (CSF) passes through the para-arterial space surrounding the arteries (top part of the Figure). This space is bound by the non-luminal surface of the blood vessel and the apical processes of astrocytes. Aquaporin-4 (AQP4) is a that facilitates flow of the para-arterial space into the interstitial CSF with interstitial fluid and a flow that the waste using a fluid in a by Maiken and of of and for of University of was by of of and full of fluid in the brain of a and was to the study of fluid in a using flow in the decreased flow in the in the patterns of sleep in sleep duration of sleep has the in it was in and in D.F. Garfinkel L. and sleep and is increased mortality Gen Psychiatry. 36: PubMed Scopus Google Scholar, Sleep in from the Sleep sleep The Sleep Scholar and of life have been in many to as a that sleep for there is experimental and evidence that the is an T.A. short human sleep is Sleep Res. PubMed Scopus Google Scholar an in which into for hours for a the a of sleep by a for waking for and a for T.A. short human sleep is Sleep Res. PubMed Scopus Google Scholar This is considered the natural for and is with the A.R. and New York, Scholar, C. Cambridge University Press, Scopus Google Scholar to the of the hours the not in The to shift to a sleep of hours in the is to and which the of during studies on as as a of have a high of sleep disturbances during pregnancy, including F.L. Kramer J. Ho K.H. Zee P.C. Grobman W.A. Sleep disturbances in pregnancy.Obstet Gynecol. 2010; 115: 77-83Crossref PubMed Scopus (254) Google Scholar, 31Bourjeily G. Raker C.A. Chalhoub M. Miller M.A. Pregnancy and fetal outcomes of symptoms of sleep-disordered breathing.Eur Respir J. 2010; 36: 849-855Crossref PubMed Scopus (162) Google Scholar, 44Izci B. Riha R.L. Martin S.E. et al.The upper airway in pregnancy and pre-eclampsia.Am J Respir Crit Care Med. 2003; 167: 137-140Crossref PubMed Scopus (151) Google Scholar, 46Izci B. Martin S.E. Dundas K.C. Liston W.A. Calder A.A. Douglas N.J. 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Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".