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Neonatal stress and loss of ovarian hormones: a novel multidisciplinary approach to understand the coincidence of cardiorespiratory and metabolic disorders in females

2022· article· en· W4225398611 on OpenAlexaff
Danuzia A. Marques, Loralie Guay, Xavier Lapointe, Marianne Gagnon, Stéphanie Fournier, Richard Kinkead

Bibliographic record

VenueThe FASEB Journal · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsUniversité de SherbrookeUniversité Laval
Fundersnot available
KeywordsMedicineInternal medicineEndocrinologyHormoneCardiorespiratory fitnessBlood pressurePhysiology

Abstract

fetched live from OpenAlex

Introduction In women, the prevalence of sleep apnea (SA) rises 3‐fold at menopause and most patients also present hypertension and obesity. While the “protective effects” of ovarian hormones are well documented, we do not know why the loss of ovarian hormones leads to SA and related cardiovascular and metabolic disorders only in a subpopulation of women. Because neonatal stress is a major cause of adult diseases, we tested the hypothesis that loss of ovarian function reveals the latent effects of stress on cardiorespiratory and metabolic control. To do so, we subjected female rats to neonatal maternal separation (NMS), a translational model of early life stress. Methodology Rat pups subjected to NMS were placed in a temperature‐controlled incubator 3h/day from postnatal day 3 to 12; controls (CTRL) were undisturbed. The effects of loss of ovarian function were tested using a surgical approach (ovariectomy; OVX, animals with 8 weeks old) and aging (40 weeks old). Measurements of ventilation (by whole body plethysmography), blood pressure (by tail cuff plethysmography), and body composition (by nuclear magnetic resonance) were made. We also harvested brains from 8 weeks old females (SHAM versus OVX). Then, we compared the expression of FosB, a transcription factor that indicates neuronal activity. The number of FosB expressing neurons was counted in the paraventricular nucleus of the hypothalamus (PVH), the main structure regulating the hypothalamic pituitary adrenal (HPA) axis. Results NMS does not affect the incidence of apneic events in all groups. At 8 weeks, mean arterial pressure (MAP) of NMS females was 5% lower than CTRL. In addition, NMS females had 10% more body mass compared to CTRL. At 40 weeks, the MAP of NMS females was 15% higher than CTRL. In both ages, NMS presented 4% more fat, and 4% less lean tissue. OVX did not affect cardiorespiratory function but augmented the number of neurons expressing FosB in the PVH by 55% in NMS, not in CTRL females. Discussion The hypotension observed in young (8 weeks) NMS females was unexpected but is consistent with the fact that hypotension is a common comorbidity of depression. PVH dysfunction contributes to the increase of sympathetic vasomotor activity, characteristic of multiple forms of hypertension. Additionally, the chronic activation of the HPA axis can leads to obesity. The increased expression of FosB in OVX NMS animals indicate that ovarian hormones prevents the stress‐related rise of activity of the HPA axis. At 40 weeks old, the fact that NMS animals were obese and hypertensive indicates that those effects are age dependent. The emergence of dysregulation on the stress neuroaxis is a plausible mechanism to explain those results. Together, these data indicate that neonatal stress may explain why a subpopulation of women are at risk of developing cardiorespiratory and metabolic disturbance at menopause. Ongoing experiments will evaluate the incidence of SA in older animals (60 weeks old) and exploring the underlying mechanisms.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.046
GPT teacher head0.272
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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