Diverse Effects of an Acetylcholinesterase Inhibitor, Donepezil, on Hippocampal Neuronal Death after Pilocarpine-Induced Seizure
Bibliographic record
Abstract
Epileptic seizures are short episodes of abnormal brain electrical activity. Many survivors of severe epilepsy display delayed neuronal death and permanent cognitive impairment. Donepezil is an acetylcholinesterase inhibitor and is an effective treatment agent for Alzheimer's disease. However, the role of donepezil in seizure-induced hippocampal injury remains untested. Temporal lobe epilepsy (TLE) was induced by intraperitoneal injection of pilocarpine (25 mg/kg). Donepezil (2.5 mg/kg/day) was administered by gavage in three different settings: (1) pretreatment for three days before the seizure; (2) for one week immediately after the seizure; and (3) for three weeks from three weeks after the seizure. We found that donepezil showed mixed effects on seizure-induced brain injury, which were dependent on the treatment schedule. Pretreatment with donepezil aggravated neuronal death, oxidative injury, and microglia activation. Early treatment with donepezil for one week showed neither adverse nor beneficial effects; however, a treatment duration of three weeks starting three weeks after the seizure showed a significant reduction in neuronal death, oxidative injury, and microglia activation. In conclusion, donepezil has therapeutic effects when injected for three weeks after seizure activity subsides. Therefore, the present study suggests that the therapeutic use of donepezil for epilepsy patients requires a well-conceived strategy for administration.
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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 | 0.000 | 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".