Role of the prostaglandins in labour and prostaglandin receptor inhibitors in the prevention of preterm labour
Bibliographic record
Abstract
Parturition is composed of five separate but integrated physiological events: fetal membrane rupture, cervical dilatation, myometrial contractility, placental separation, and uterine involution. Prostaglandins (PGs) have central roles in each of these events, but the most studied is myometrial contraction. Elevated uterine PGs or the enhanced sensitivity of the myometrium to PGs leads to contractions and labour. The primary regulator of PG synthesis is the mRNA expression of PG H Synthase (PGHS-2 or COX-2). Given the central role of PGs in labour, this enzyme becomes an obvious therapeutic target for the prevention of preterm labour, the major cause of perinatal mortality and morbidity. Unfortunately, even though the non-steroidal anti-inflammatory drugs (NSAIDs), which inhibit PGHS, are usually successful in suppressing preterm labour or prolonging pregnancy in animal and human studies, the NSAIDS have had adverse effects on fetal physiology and development. Therefore, other means to suppress PG synthesis or action to arrest preterm labour need to be investigated. The PGF2alpha receptor, FP, may prove to be a reasonable target for tocolysis. FP mRNA increases in the mouse uterus at preterm birth, whereas PGF2alpha concentrations do not increase, suggesting elevated uterine sensitivity to contractile agonists is one mechanism for preterm labour initiation. New data shows that administration of a specific FP antagonist, Theratechnologies (THG) 113.31, delays preterm birth in mice and sheep with no observable maternal or fetal side effects. Hence antagonizing PG action offers new hope for delaying preterm birth.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".