IMPACT OF PREVENTING PROLONGED FEBRILE SEIZURES IN THE PREDISPOSED BRAIN
Bibliographic record
Abstract
Objectives: We have shown that pups with a focal cortical dysplasia develop prolonged hyperthermia-induced seizures (a model of febrile seizures) and temporal lobe epilepsy. The goal of this study was to demonstrate that preventing prolonged seizures in our model of temporal lobe epilepsy would improve long-term outcome, even in the predisposed individuals. Methods: We studied 4 groups of pups. The first had the dysplastic lesion and hyperthermia (LH=17), the second LH plus diazepam (LHD=10), the third hyperthermia alone (H=10) and the fourth hyperthermia plus diazepam (HD=10). Animals were monitored for the severity and duration of the acute seizure at P10 and their brain removed 2 weeks later to assess the histological damage induced by the seizure. Results: The LH group had the most severe seizures, lasting up to 34.68±7.4 versus 25.37±4.9 minutes in the H group. Diazepam reduced seizure duration to 7.26±0.88 (LHD) versus 8.43±2.81 (HD). Intra-peritoneal diazepam proved to be effective in every animal. At 2 weeks post hyperthermia, hippocampal asymmetry was seen only in LH rats. Moreover, 30% (5/17) of the LH rats had severe hippocampal atrophy, more than 2SD reduction, a condition not seen in the other groups. Conclusion: Diazepam therapy can prevent hippocampal damage associated with prolonged hyperthermia-induced seizures in the predisposed brain. Studies are ongoing to assess its impact on the long-term risk of developing temporal lobe epilepsy and hippocampal dysfunction.
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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) | 0.000 | 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 | 0.001 |
| 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".