Abscisic acid: a novel uterine stimulator in normal and diabetic rats
Bibliographic record
Abstract
Diabetes is usually associated with alterations in myometrial contractility with altered oxytocin responsiveness that increase the incidence of fetal and maternal morbidity and mortality. Pancreatic β-cells release abscisic acid (ABA) in response to glucose, which in turn potentiates insulin secretion. The aim of the study was to find out the effect of ABA on the uterine contractility in normal and diabetic induced rats and tried to detect its possible underlying signaling pathway. Adult non-pregnant female rats were divided into normal nondiabetic group (n = 27) and diabetic group (n = 12). The effect of ABA on the normal and diabetic isolated myometrium was determined alone or after different blockers. Spontaneous diabetic myometrial contraction showed significant decrease and less responsiveness to oxytocin, KCL, and acetylcholine than nondiabetic samples. ABA showed 60% of oxytocin stimulatory effects on myometrial contraction in a dose–response manner in both groups. Meanwhile, this effect was decreased after blocking L-type calcium channels and completely abolished after blocking prostaglandin F (FP) and inositol trisphosphate (IP3) receptors. ABA is found to have an uterotonic effect that is mediated mainly via FP receptor through increasing the level of IP3. So, ABA by its novel effect could be beneficial as pre-labor prescription, especially in diabetic females.
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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 | 0.001 | 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".