Negative Inotropic and Chronotropic Effects of Oxytocin
Bibliographic record
Abstract
We have previously shown that oxytocin receptors are present in the heart and that perfusion of isolated rat hearts with oxytocin results in decreased cardiac flow rate and bradycardia. The mechanisms involved in the negative inotropic and chronotropic effects of oxytocin were investigated in isolated dog right atria in the absence of central mechanisms. Perfusion of atria through the sinus node artery with 10(-6) mol/L oxytocin over 5 minutes (8 mL/min) significantly decreased both beating rate (-14.7+/-4.9% of basal levels, n=5, P<0.004) and force of contraction (-52.4+/-9.1% of basal levels, n=5, P<0.001). Co-perfusion with 10(-6) mol/L oxytocin receptor antagonist (n=3) completely inhibited the effects of oxytocin on frequency (P<0.04) and force of contraction (P<0.004), indicating receptor specificity. The effects of oxytocin were also totally inhibited by co-perfusion with 5x10(-8) mol/L tetrodotoxin (P<0.02) or 10(-6) mol/L atropine (P<0.03) but not by 10(-6) mol/L hexamethonium, which implies that these effects are neurally mediated, primarily by intrinsic parasympathetic postganglionic neurons. Co-perfusion with 10(-6) mol/L NO synthase inhibitor (L-NAME) significantly inhibited oxytocin effects on both beating rate (-1.85+/-1.27% versus -14.7+/-4.9% in oxytocin alone, P<0.05) and force of contraction (-24.9+/-4.4% versus -52.4+/-9.1% in oxytocin alone, n=4, P<0.04). The effect of oxytocin on contractility was further inhibited by L-NAME at 10(-4) mol/L (-8.1+/-1.8%, P<0.01). These studies imply that the negative inotropic and chronotropic effects of oxytocin are mediated by cardiac oxytocin receptors and that intrinsic cardiac cholinergic neurons and NO are involved in these actions.
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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".