State dependent modulation of breathing in rats during urethane anesthesia
Bibliographic record
Abstract
Breathing is an automatic process that is highly influenced by brain state, with abnormalities occurring more frequently during sleep. Although rodents are commonly used for respiratory neurobiology studies, they show irregular sleep patterns and cycles, which make studies of sleep‐dependent breathing challenging. The objective of this study was to determine if sleep‐like brain state alternations apparent under urethane anesthesia are correlated to changes in breathing parameters and respiratory muscle modulation, and to determine if they mimic changes occurring during natural sleep. Rats were anesthetized and respiratory parameters (rate, minute ventilation and EMG activity in diaphragm, genioglossus, abdominal and facial muscles) were recorded across different brain states as assessed by neocortical and hippocampal EEG. Results were compared with recordings in natural sleep. Our data show that brain state alternations under urethane anesthesia are correlated with changes in breathing rate, variability and respiratory muscle modulation and closely reproduce changes observed in natural sleep. Of particular interest is the present demonstration of prominent state dependent modulation of both genioglossus and abdominal muscle activity, which is a robust feature of sleep and sleep‐like brain state transitions. Supported by CIHR (JJG) and NSERC (CTD). SP is a Parker B. Francis fellow.
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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 | 0.001 | 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) | 0.001 | 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".