Specific Role of Membrane Progesterone Receptors α and β on Ventilation during Sleep in Female Mice.
Bibliographic record
Abstract
We recently showed that deletion of nuclear progesterone receptors disrupts breathing during sleep. Here we tested the hypotheses that deletion of membrane progesterone receptors (mPR) α and β in the medulla‐brain stem regions decreases ventilation and increases breathing instabilities during sleep. Female mice were chronically instrumented and small interfering RNA (siRNA) against mPRαor mPRβ (or a control solution) were infused in the fourth ventricle for 2 weeks. Ventilation (Ve) and CO 2 production (VCO 2 ) were continuously recorded (whole body plethysmography) during 4 h (9:00‐13:00) in normoxia. Respiratory frequency, tidal volume, minute ventilation and the frequency of spontaneous and post‐sigh apneas were determined during sleep, defined as periods of stable breathing pattern lasting at least 10 minutes. Compared to control, deletion of mPRα decreased Ve and Ve/VCO 2 during sleep, but did not affect apnea or sigh frequency. The deletion of mPRβ had no effect on Ve but decreased VCO 2 , increased Ve/VCO 2 and increased the frequency of spontaneous and post‐sigh apneas. Specific deletions of mPRα and mPRβ have been verified by immunohistochemistry on serial brainstem slices. Our results show that mPRα and β play specific role on respiratory control during sleep, and suggest that these receptors mediate some of the respiratory effects of progesterone. Founded by CIHR (MOP‐102715).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".