Seizures and reproductive function: Insights from female rats with epilepsy
Bibliographic record
Abstract
OBJECTIVE: Chronic seizures in women can have adverse effects on reproductive function, such as polycystic ovarian syndrome, but it has been difficult to dissociate the effects of epilepsy from the role of antiepileptic drugs. To distinguish the effects of chronic seizures from medication, we used the laboratory rat, because an epileptic condition can be induced without concomitant anticonvulsant drug treatment. METHODS: Adult female rats were administered the chemoconvulsant pilocarpine to initiate status epilepticus, which was decreased in severity by the anticonvulsant diazepam. These rats developed spontaneous seizures in the ensuing weeks, and are therefore termed epileptic. Controls were saline-treated rats, or animals that were injected with pilocarpine but did not develop status epilepticus. Ovarian cyclicity and weight gain were evaluated for 2 to 3 months. Serum hormone levels were assayed from trunk blood, which was collected at the time of death. Paraformaldehyde-fixed ovaries were evaluated quantitatively. RESULTS: Rats that had pilocarpine-induced seizures had an increased incidence of acyclicity by the end of the study, even if status epilepticus did not occur. Ovarian cysts and weight gain were significantly greater in epileptic than control rats, whether rats maintained cyclicity or not. Serum testosterone was increased in epileptic rats, but estradiol, progesterone, and prolactin were not. INTERPRETATIONS: The results suggest that an epileptic condition in the rat leads to increased body weight, cystic ovaries, and increased testosterone levels. Although caution is required when comparing female rats with women, the data suggest that recurrent seizures have adverse effects, independent of antiepileptic drugs.
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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) | 0.000 | 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".