Costal diaphragm and parasternal intercostal function during CO2 stimulation
Bibliographic record
Abstract
INTRODUCTION: Classically, with increasing CO2 there is a linear increase in minute ventilation (VI) and diaphragm electromyogram (EMG). Although all respiratory muscles would be expected to increase in parallel with VI, given diverse mechanical advantage of individual muscles, there is no a priori reason that all muscles would have equivalent recruitment. QUESTION: Are two primary muscles of inspiration, Costal Diaphragm (COS) and Parasternal Intercostal (PARA), recruited identically during CO2 stimulated ventilation? METHODS: Sonomicrometry transducers and EMG electrodes were implanted in the left COS and PARA. After recovery, the animals were studied awake, breathing through a mask. Airflow, ETCO2, muscle length and Mavg EMG were recorded during room air and CO2 rebreathing. Output included breath-by-breath breathing pattern, muscle shortening and EMG, averaged at 3 levels of ETCO2. ![Figure][1] RESULTS: For N=7 (wgt 31.1 kg) studied 25 days after implant, VI and tidal volume increased significantly with CO2 stimulated breathing. Simultaneously, both SHORT and EMG of COS and PARA exhibited a linear increase. However, changes in action of the two muscles were significantly different, with greater SHORT and EMG of PARA compared to COS per mmHG CO2. SUMMARY: With CO2 stimulation, both shortening and EMG of parasternal increased in lock-step with ventilation. Relative action of costal diaphragm was less than parasternal at equivalent CO2. [1]: pending:yes
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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) | 0.002 | 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".