Hormonal regulation of atypical absence seizures
Bibliographic record
Abstract
A time course study that examined the effects of the female estrous cycle on the chronic slow spike-and-wave discharges (SSWDs), gamma-aminobutyric B receptor (GABA(B)R) binding, and GABA(B)R protein expression was conducted in Long Evans hooded rats treated during development with a cholesterol synthesis inhibitor AY9944 (AY). In addition, a pharmacological study using the hormones progesterone, 17 beta-estradiol, mifepristone (intracellular progesterone receptor antagonist), tamoxifen (intracellular estrogen receptor antagonist), and allopregnanolone (progesterone metabolite) was performed to determine their effects on AY-induced seizures. The data indicate that there is a significant increase in both the duration of SSWD and GABA(B)R binding in the AY model, during the proestrus stage of the estrous cycle, the stage during which the levels of progesterone are at their highest. No changes in GABA(B)R1a or R2 protein levels were observed. In addition, the administration of both progesterone and allopregnanolone exacerbated seizures in the AY model, whereas 17 beta-estradiol attenuated the SSWD duration. Neither mifepristone nor tamoxifen blocked the effects of progesterone and 17 beta-estradiol, respectively, on SSWD duration in the AY model, suggesting that these two sex hormones are working in a manner independent of their intracellular receptors. These data suggest an important role for steroid hormones in the regulation and maintenance of AY-induced atypical absence seizures.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".