Contribution of Expiratory Abdominal Muscle Recruitment in the Perinatal Period Across Sleep Wake Cycles
Bibliographic record
Abstract
Breathing and sleeping are homeostatically regulated processes that are necessary for survival. During sleep, specifically rapid eye movement sleep, breathing is more frequently prone to irregularities in both humans and rodents, especially in preterm and full term newborns. Previous work in our laboratory has demonstrated the occurrence of frequent recruitment of abdominal muscle activity in adult rats during REM sleep, despite REM induced postural muscle atonia. This recruitment was also associated with increased tidal volume and increased respiratory stability Little is known about occurrence of expiratory activity in perinatal rats, specifically across sleep states, and how this recruitment contributes to ventilation. In this study our objective is to investigate the occurrence and the significance of expiratory modulated abdominal muscle recruitment across sleep wake cycles in the postnatal period (postnatal day, P0 to P14) of rats. We hypothesize that in the postnatal period, expiratory muscle activity is also recruited across sleep states and its recruitment contributes to stabilize ventilation, specifically during irregular breathing. We instrumented newborn and juvenile rats with EMG electrodes in neck, intercostal and abdominal muscles and recorded breathing parameters and overt behavior inside a whole body plethysmograph. Our results suggest that neonatal rats experience frequent abdominal muscle recruitment events, which occur in both active and quiet sleep. Our results further indicate that respiratory rate is less variable with onset of abdominal muscle recruitment in active sleep. We conclude that occurrence of expiratory activity is associated with stabilization and potentiation of ventilation during sleep in the postnatal period. Support or Funding Information Neuroscience and Mental Health Institute, Women and Childrens Health Research Institute, NSERC, CIHR
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".