Ampakines alleviate respiratory depression in rats
Bibliographic record
Abstract
Rationale: There is a need for improved therapeutic interventions to treat both drug‐ and sleep‐induced respiratory depression. Activation of AMPA‐type glutamate receptors positively modulates respiratory drive and rhythmogenesis in several brain regions including the preBötzinger complex. Ampakines are a diverse group of small molecules that activate subsets of these receptors. Objective: We determined whether the ampakine CX546 would enhance respiratory drive and rhythmogenesis across various stages of development and whether this ampakine could counter opioid‐ and barbiturate‐induced respiratory depression. Methods: Respiratory frequency and amplitude were measured using the following rat models; perinatal in vitro brainstem‐spinal cord, neonatal in vitro medullary slice, juvenile in situ perfused, working heart‐brainstem preparation and, newborn and adult in vivo. Results: The administration of CX546 stimulated baseline respiratory frequency in perinatal in vitro preparations but not older animals. Pharmacological depression of respiratory frequency and amplitude was countered at all ages studied by CX546 in vitro, in situ and in vivo. Significantly, CX546 countered opioid‐induced breathing depression in all preparations, without altering suppressing analgesia. Conclusions: CX546 effectively reverses opioid‐ and barbiturate‐induced respiratory depression without reversing analgesic response. These studies suggest that ampakines may be useful in preventing or reversing drug‐induced respiratory depression and identify a potential for ampakines for alleviating other forms of respiratory depression. Funded by CIHR, CFI, ASRAP and AHFMR.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".