Afferent input modulates the chronic hypercapnia-induced increase in respiratory-related central pH/CO2 chemosensitivity in the cane toad (<i>Bufo marinus</i>)
Bibliographic record
Abstract
The goal of this study was to examine the role of respiratory-related afferent input on the chronic hypercapnia (CHC)-induced increase in central respiratory-related pH/CO2 chemosensitivity in cane toads (Bufo marinus). Toads were exposed to CHC (3.5% CO2) for 10 days, following which in vitro brainstem-spinal cord preparations were used to assess central respiratory-related pH/CO2 chemosensitivity. Motor output from the vagus nerve root was used as an index of breathing (fictive breathing). Olfactory denervation (OD), prior to exposure to CHC, was used to remove the influence of CO2-sensitive olfactory chemoreceptors, which inhibit breathing. Exposure to chronic hyperoxic hypercapnia (CHH) was used to reduce the level of arterial chemoreceptor input compared with CHC alone. In vivo experiments examined the effects of CHC, CHH and OD on the acute hypercapnic ventilatory response of intact animals. In vitro, a reduction in artifical cerebral spinal fluid (aCSF) pH increased fictive breathing in preparations taken from control and CHC animals. CHC caused an increase in fictive breathing compared with controls. OD and CHH abolished the CHC-induced augmentation of fictive breathing. In vivo, CHC did not cause an augmentation of the acute hypercapnic ventilatory response. CHH reduced the in vivo acute hypercapnic ventilatory response compared with animals exposed to CHC. In vivo, OD reduced breathing frequency and increased breath amplitude in both control and CHC animals. The results suggest that afferent input from olfactory and arterial chemoreceptors, during CHC, is involved in triggering the CHC-induced increase in central respiratory-related pH/CO2 chemosensitivity.
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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 | 0.001 |
| 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".