A Rat Model of Epilepsy in Women: A Tool to Study Physiological Interactions between Endocrine Systems and Seizures
Bibliographic record
Abstract
Epilepsy in women is influenced by endocrine status and antiepileptic drugs, but without an animal model, the effects of endocrine variables and antiepileptic drugs cannot be easily dissociated from the influence of epilepsy itself. Animal models have had limited utility because experimentally induced seizures typically result in reproductive failure. This study was conducted to develop an improved animal model. The muscarinic convulsant pilocarpine was used to elicit status epilepticus (SE) in adult female Sprague Dawley rats. The selective estrogen receptor modulator raloxifene was administered 30 min before pilocarpine. An anticonvulsant barbiturate, pentobarbital, was injected 5-10 min after the onset of SE and at least once thereafter to minimize acute convulsions. Mortality, morbidity, estrous cyclicity, and the ultimate success of the procedure (i.e. induction of recurrent, spontaneous seizures) were monitored. The combination of raloxifene and pentobarbital led to significantly improved estrous cyclicity compared with previous methods. Animals treated with raloxifene and pentobarbital became epileptic, as defined by the recurrence of spontaneous convulsions in the weeks after SE. The results of this study provide an improved animal model to examine the interactions between seizures and ovarian hormone secretion. The results also suggest that treatment of SE with raloxifene may benefit women with SE.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".