Orexin-A inhibits fictive air breathing responses to respiratory stimuli in the bullfrog tadpole (<i>Lithobates catesbeianus</i>)
Bibliographic record
Abstract
In pre-metamorphic tadpoles, the neural network generating lung ventilation is present but actively inhibited; the mechanisms leading to the onset of air breathing are not well understood. Orexin (ORX) is a hypothalamic neuropeptide that regulates several homeostatic functions, including breathing. While ORX has limited effects on breathing at rest, it potentiates reflexive responses to respiratory stimuli mainly via ORX receptor 1 (OX1R). Here, we tested the hypothesis that OX1Rs facilitate the expression of the motor command associated with air breathing in pre-metamorphic bullfrog tadpoles (Lithobates catesbeianus). To do so, we used an isolated diencephalic brainstem preparation to determine the contributions of OX1Rs to respiratory motor output during baseline breathing, hypercapnia and hypoxia. A selective OX1R antagonist (SB-334867; 5-25 µmol l-1) or agonist (ORX-A; 200 nmol l-1 to 1 µmol l-1) was added to the superfusion media. Experiments were performed under basal conditions (media equilibrated with 98.2% O2 and 1.8% CO2), hypercapnia (5% CO2) or hypoxia (5-7% O2). Under resting conditions gill, but not lung, motor output was enhanced by the OX1R antagonist and ORX-A. Hypercapnia alone did not stimulate respiratory motor output, but its combination with SB-334867 increased lung burst frequency and amplitude, lung burst episodes, and the number of bursts per episode. Hypoxia alone increased lung burst frequency and its combination with SB-334867 enhanced this effect. Inactivation of OX1Rs during hypoxia also increased gill burst amplitude, but not frequency. In contrast with our initial hypothesis, we conclude that ORX neurons provide inhibitory modulation of the CO2 and O2 chemoreflexes in pre-metamorphic tadpoles.
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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".