Adenosine A <sub>1</sub> and A <sub>2A</sub> receptors contribute to enhancement of the hypercapnic ventilatory response following neonatal caffeine treatment in rats
Bibliographic record
Abstract
We recently showed that neonatal treatment with caffeine (NCT), an adenosine receptor antagonist used to treat apnea of prematurity, persistently increases the hypercapnic ventilatory response of juvenile rats. The aim of this study was to determine the relative roles of the adenosine receptor subtypes on the effects of NCT on the hypercapnic (5% of CO2) ventilatory response by administrating specific adenosine receptor antagonists in male juvenile animals treated during the neonatal period from day 3 to 12 with water (control) or caffeine 15 mg/kg (NCT). At postnatal day 20, rats received an injection of vehicle, A1-(DPCPX, 4 mg/kg), or A2A-antagonist (ZM241385, 1 mg/kg) prior to plethysmographic measurements of ventilatory activity under normo- and hypercapnic conditions. While A1 antagonist increased the ventilatory response to hypercapnia in both groups, the respiratory frequency response was stronger in NCT than in control rats; however, the tidal volume response was weaker in NCT rats. A2A antagonist increased the minute ventilation response in control, whereas it remained steady in NCT group. Thus, NCT changed the pattern of the response through A1 receptors, whereas it diminished the influence of A2A receptors. Supported by the Canada Research Chair in Respiratory Neurobiology, and the Jeanne-and-Jean-Louis-Levesque's Chair in Perinatalogy.
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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".