Bilateral Anterior Thalamic Nucleus Lesions and High-frequency Stimulation Are Protective against Pilocarpine-induced Seizures and Status Epilepticus
Bibliographic record
Abstract
OBJECTIVE: The thalamus is thought to play an important role in secondary generalization of seizures. The aim of the present study was to investigate the influence of anterior thalamic nucleus lesions and high-frequency stimulation in the pilocarpine model of secondarily generalized seizures in rats. METHODS: Adult Wistar rats underwent unilateral (n = 7) or bilateral anterior nucleus thalamotomies (n = 10), or unilateral (n = 4) or bilateral (n = 9) anterior thalamic nucleus stimulation through implanted electrodes. Control animals (n = 9) received bilateral implants but no stimulation. Seven days after these procedures, animals were provided pilocarpine (320 mg/kg intraperitoneally) to induce seizures and status epilepticus (SE). Electrographic recordings from hippocampal and cortical electrodes were evaluated, and ictal behavior was assessed. RESULTS: In the control group, 67% of the animals developed SE 15.3 +/- 8.8 minutes after pilocarpine administration. Neither unilateral anterior nucleus lesions nor stimulation significantly reduced the propensity or latency for developing seizures and SE. Bilateral thalamic stimulation did not prevent SE (observed in 56% of the animals), but it significantly prolonged the latency to its development (48.4 +/- 17.7 min, P = 0.02). Strikingly, no animal with bilateral anterior nucleus thalamotomies developed seizures or SE with pilocarpine. CONCLUSION: Bilateral anterior thalamic nuclear complex stimulation and thalamotomies were protective against SE induced by pilocarpine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".