Enhancement of Progenitor Cell Division in the Dentate Gyrus Triggered by Initial Limbic Seizures in Rat Models of Epilepsy
Bibliographic record
Abstract
PURPOSE: Mitogenic effects of seizures on granule cell progenitors in the dentate gyrus were studied in two rat models of epilepsy. We investigated which stage of epileptogenesis is critical for eliciting progenitor cell division and whether seizure-induced neuronal degeneration is responsible for the enhancement of progenitor cell division. METHODS: Seizures were induced by either kainic acid (KA) administration or electrical kindling. Neurogenesis of dentate granule cells was evaluated using the bromodeoxyuridine (BrdU) labeling method, and neuronal degeneration was assessed by in situ DNA fragmentation analysis. RESULTS: After injection of KA, the number of BrdU-positive granule cells began to increase at day 3 after the treatment, peaked at day 5, and returned to baseline at day 10. By day 13, the values were lower than control. After kindling, the number of BrdU-positive cells began to increase after five consecutive experiences of stage I seizures. The increase occurred from day 1 to day 3 after the last electrical stimulation, but returned to baseline by day 7. After generalized seizures were well established, repeated stimulation did not facilitate division of granule cell progenitors. DNA fragmentation was noted in pyramidal neurons in the CA1, CA3, and hilus regions at 18 h after KA injection, but not in the kindling model. CONCLUSIONS: These observations indicate that a mechanism in epileptogenesis boosts dentate progenitor cell division, but progenitor cells may become unreactive to prolonged generalized seizures. Pyramidal neuronal degeneration is not necessary for triggering the upregulation. It is suggested that newly born granule cells may play a role in the network reorganization that occurs during epileptogenesis.
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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) | 0.001 | 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 | 0.001 |
| 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".