Orexin‐A and respiration in a rat model of smoke‐induced chronic obstructive pulmonary disease
Bibliographic record
Abstract
1. Orexins are neuropeptides synthesized in the hypothalamus that regulate many physiological functions, including energy homeostasis, stress responses, sleep/wake states etc. It is now emerging that orexins may also regulate breathing, but little is known as to how they do this, particularly in chronic obstructive pulmonary disease (COPD). In the present study, we used a rat model of cigarette smoke-induced COPD to investigate orexin-A expression in the hypothalamus and medulla and its effect on respiration. 2. Sprague-Dawley rats were exposed to cigarette smoke (1 h twice daily) for 12 weeks. Lung function and pathological changes associated with inflammation and emphysema were determined to confirm the validity of the COPD model. 3. Hypothalamic and medullary orexin-A levels, as determined by radioimmunoassay, were higher in smoke-exposed than control rats. Furthermore, the expression of prepro-orexin (PPO) mRNA in the hypothalamus and orexin OX(1) receptor mRNA in the medulla, as determined by real-time quantitative polymerase chain reaction, was higher in smoke-exposed than control rats. 4. The number of orexin-A-positive neurons in the hypothalamus and OX(1) and OX(2) receptor-positive neurons in the ventrolateral medulla was higher in smoke-exposed than control rats. 5. Microinjection of orexin-A (1 μmol/L, 0.1 μL) into the pre-Bötzinger complex enhanced phrenic nerve discharge to a greater extent in smoke-exposed compared with control rats (61% vs 36%, respectively). 6. The findings of the present study demonstrate that the increased respiratory activity in smoke-exposed rats is due to an increase in orexin-A as well as upregulation of orexin receptors in the ventrolateral medulla.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 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".