Brainstem <i>P</i><sub>CO2</sub> modulates phrenic responses to specific carotid body hypoxia in an <i>in situ</i> dual perfused rat preparation
Bibliographic record
Abstract
Inputs from central (brainstem) and peripheral (carotid body) respiratory chemoreceptors are coordinated to protect blood gases against potentially deleterious fluctuations. However, the mathematics of the steady-state interaction between chemoreceptors has been difficult to ascertain. Further, how this interaction affects time-dependent phenomena (in which chemoresponses depend upon previous experience) is largely unknown. To determine how central P(CO2) modulates the response to peripheral chemostimulation in the rat, we utilized an in situ arterially perfused, vagotomized, decerebrate preparation, in which central and peripheral chemoreceptors were perfused separately (i.e. dual perfused preparation (DPP)). We carried out two sets of experiments: in Experiment 1, we alternated steady-state brainstem P(CO2) between 25 and 50 Torr in each preparation, and applied specific carotid body hypoxia (60 Torr P(O2) and 40 Torr P(CO2)) under both conditions; in Experiment 2, we applied four 5 min bouts (separated by 5 min) of specific carotid body hypoxia (60 Torr P(O2) and 40 Torr P(CO2)) while holding the brainstem at either 30 Torr or 50 Torr P(CO2). We demonstrate that the level of brainstem P(CO2) modulates (a) the magnitude of the phrenic responses to a single step of specific carotid body hypoxia and (b) the magnitude of time-dependent phenomena. We report that the interaction between chemoreceptors is negative (i.e. hypo-additive), whereby a lower brainstem P(CO2) augments phrenic responses resulting from specific carotid body hypoxia. A negative interaction may underlie the pathophysiology of central sleep apnoea in populations that are chronically hypocapnic.
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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".