Clavulanic acid does not affect convulsions in acute seizure tests in mice
Bibliographic record
Abstract
Clavulanic acid (CLAV) inhibits bacterial β-lactamases and is commonly used to aid antibiotic therapy. Prompted by the initial evidence suggestive of the potential anticonvulsant and neuroprotective properties of CLAV, the present study was undertaken to systematically evaluate its acute effects on seizure thresholds in seizure tests typically used in primary screening of potential antiepileptic drugs (AEDs). In the present study, 6-Hz seizure threshold, maximal electroshock seizure threshold (MEST) test, and intravenous pentylenetetrazole (i.v. PTZ) seizure tests were used to determine anticonvulsant effects of intraperitoneally (i.p.) administered CLAV in mice. Acute effects on motor coordination and muscle strength were assessed in the chimney and grip-strength tests, respectively. Doses of CLAV studied in the present study were either comparable or extended the doses reported in the literature to be effective against kainic acid-induced convulsions in mice or behaviorally active in rodents and monkeys. CLAV had no effect on seizure thresholds in the 6-Hz (64 ng/kg to 1 mg/kg) and MEST (64 ng/kg to 5 mg/kg) seizure tests. Similarly, CLAV had no effect on seizure thresholds for i.v. PTZ-induced myoclonic twitch, clonic convulsions, and tonic convulsions (64 ng/kg to 5 mg/kg). Finally, CLAV (64 ng/kg to 5 mg/kg) had no effect on the motor performance and muscle strength in the chimney and grip-strength tests, respectively. In summary, CLAV failed to affect seizure thresholds in three seizure tests in mice. Although the results of the present study do not support further development of CLAV as an AED, its beneficial effects in chronic epilepsy models warrant further evaluation owing to its, for example, potential neuroprotective properties.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".