Strain differences affect the induction of status epilepticus and seizure‐induced morphological changes
Bibliographic record
Abstract
Genetic deficits have been discovered in human epilepsy, which lead to alteration of the balance between excitation and inhibition, and ultimately result in seizures. Rodents show similar genetic determinants of seizure induction. To test whether seizure-prone phenotypes exhibit increased seizure-related morphological changes, we compared two standard rat strains (Long-Evans hooded and Wistar) and two specially bred strains following status epilepticus. The special strains, namely the kindling-prone (FAST) and kindling-resistant (SLOW) strains, were selectively bred based on their amygdala kindling rate. Although the Wistar and Long-Evans hooded strains experienced similar amounts of seizure activity, Wistar rats showed greater mossy fiber sprouting and hilar neuronal loss than Long-Evans hooded rats. The mossy fiber system was affected differently in FAST and SLOW rats. FAST animals showed more mossy fiber granules in the naïve state, but were more resistant to seizure-induced mossy fiber sprouting than SLOW rats. These properties of the FAST strain are consistent with those observed in juvenile animals, further supporting the hypothesis that the FAST strain shares circuit properties similar to those seen in immature animals. Furthermore, the extent of mossy fiber sprouting was not well correlated with sensitivity to status epilepticus, but was positively correlated with the frequency of spontaneous recurrent seizures in the FAST rats only, suggesting a possible role for axonal sprouting in the development of spontaneous seizures in these animals. We conclude that genetic factors clearly affect seizure development and related morphological changes in both standard laboratory strains and the selectively bred seizure-prone and seizure-resistant strains.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".