Relaxin peptides reduce cellular damage in cultured brain slices exposed to transient oxygen–glucose deprivation: an effect mediated by nitric oxide
Bibliographic record
Abstract
The effect of treatment with human relaxins on cell death was studied in oxygen- and glucose-deprived brain slices. In addition, involvement of nitric oxide and the relaxin receptor, RXFP3, was studied. Brain slices ( n = 12–18/group) were cultured under standard conditions for two weeks and then exposed to: ( i) an oxygenated balanced salt solution, ( ii) a deoxygenated, glucose-free balanced salt solution (OGD media), or ( iii) OGD media containing 10−7 mol/L H2 relaxin, 10−7 mol/L H2 relaxin with 50 μmol/L L-NIL, 10−7 mol/L H3 relaxin, or 10−7 mol/L H3 relaxin with 50 μmol/L L-NIL. Cell death was assessed using propidium iodide fluorescence. In a separate experiment, 10−5 mol/L R3 B1-22R (an antagonist of RXFP3) was added to both H2 and H3 relaxin treatments. H2 and H3 relaxin treatment reduced cell damage or death in OGD slices and L-NIL partially attenuated the effect of H3 relaxin. Antagonism of RXFP3 blocked the effect of H3 but not H2 relaxin. These data increase our understanding of the role of relaxin ligands and their receptors in protecting tissues throughout the body from ischemia and reperfusion injury.
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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 | 0.000 | 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) | 0.002 | 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".