The Influence of Gonadal Hormones on Neuronal Excitability, Seizures, and Epilepsy in the Female
Bibliographic record
Abstract
It is clear from both clinical observations of women, and research in laboratory animals, that gonadal hormones exert a profound influence on neuronal excitability, seizures, and epilepsy. These studies have led to a focus on two of the primary ovarian steroid hormones, estrogen and progesterone, to clarify how gonadal hormones influence seizures in women with epilepsy. The prevailing view is that estrogen is proconvulsant, whereas progesterone is anticonvulsant. However, estrogen and progesterone may not be the only reproductive hormones to consider in evaluating excitability, seizures, or epilepsy in the female. It seems unlikely that estrogen and progesterone would exert single, uniform actions given our current understanding of their complex pharmacological and physiological relationships. Their modulatory effects are likely to depend on endocrine state, relative concentration, metabolism, and many other factors. Despite the challenges these issues raise to future research, some recent advances have helped clarify past confusion in the literature. In addition, testable hypotheses have developed for complex clinical problems such as "catamenial epilepsy." Clinical and animal research, designed with the relevant endocrinological and neurobiological issues in mind, will help advance this field in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".