Sex influences on hippocampal kindling-induced seizures in middle-aged mice
Bibliographic record
Abstract
Epilepsy is a chronic neurological disorder, and its prevalence presents a bimodal distribution with high incidences in children and older adults. The incidence of epilepsy does not generally differ between men and women; however, whether this holds true for new-onset epilepsy in older adults is unclear. While studies in animal models of epilepsy may help explore the biological mechanisms relevant to the influences of sex on epileptogenesis, relatively little information is available regarding sex differences in the genesis of epileptic seizures in middle-aged animals. In this study, we addressed this knowledge gap using a mouse model of extended hippocampal kindling. C57 black mice aged between the ages of 12 and 13 months underwent hippocampal kindling as this age roughly corresponds to middle age in humans (∼50 years). Relative to male mice, female mice showed faster-progressing and more severe evoked seizures, a higher tendency to experience spontaneous seizures in the early stage of extended kindling, less frequent expression of hippocampal interictal spikes, and insignificant decreases in hippocampal theta rhythm. Collectively, these results demonstrated the existence of sex-specific differences in hippocampal kindling-induced seizures and suggested that middle-aged female mice have greater but variable susceptibility to hippocampal kindling-induced epileptogenesis compared with male mice of similar age.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".