Gestational exposure to Δ<sup>9</sup>-THC impacts ovarian follicular dynamics and angiogenesis in adulthood in Wistar rats
Bibliographic record
Abstract
With the legalization of marijuana (Cannabis sativa) and increasing use during pregnancy, it is important to understand its impact on exposed offspring. Specifically, the effects of Δ-9-tetrahydrocannabinol (Δ9-THC), the major psychoactive component of cannabis, on fetal ovarian development and long-term reproductive health are not fully understood. The aim of this study was to assess the effect of prenatal exposure to Δ9-THC on ovarian health in adult rat offspring. At 6 months of age, Δ9-THC-exposed offspring had accelerated folliculogenesis with apparent follicular development arrest, but no persistent effects on circulating steroid levels. Ovaries from Δ9-THC-exposed offspring had reduced blood vessel density in association with decreased expression of the pro-angiogenic factor VEGF and its receptor VEGFR-2, as well as an increase in the anti-angiogenic factor thrombospondin 1 (TSP-1). Collectively, these data suggest that exposure to Δ9-THC during pregnancy alters follicular dynamics during postnatal life, which may have long-lasting detrimental effects on female reproductive health.
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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 | 0.001 |
| 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".