Anticonvulsant mechanisms of piperine, a piperidine alkaloid
Bibliographic record
Abstract
Piperine, a natural compound isolated from the fruits of Piper, is known to modulate several neurotransmitter systems such as serotonin, norepinephrine, and GABA, all of which have been linked to the development of convulsions. Fruits of Piper species have been suggested as means for managing seizure disorders. The present study was designed to elucidate the anticonvulsant effect of piperine and its mechanisms of action using in-silico, in-vivo and in-vitro techniques.PASS software was used to determine its possible activity and mechanisms. Furthermore the latency for development of convulsions and mortality rate was recorded in different experimental mouse models of epilepsy (pentylenetetrazole, maximal electroshock, NMDA, picrotoxin, bicuculline, BAYK-8644, strychnine-induced convulsions) after administration of various doses of piperine (5, 10 and 20 mg/kg, i.p.). Finally, the effect of piperine on Na(+) and Ca(2+) channels were evaluated using the whole cell patch clamp techniqueOur results revealed that piperine decreased mortality in the MES-induced seizure model. Moreover, piperine (10 mg/kg) delayed the onset of tonic clonic convulsions in the pentylenetetrazole test and reduced associated mortality. Furthermore, an anticonvulsant dose of piperine also delayed the onset of tonic clonic seizures in strychnine, picrotoxin and BAY K-8644. Complete protection against mortality was observed in BAYK-8644 induced convulsions. Finally, whole cell patch clamp analysis suggested an inhibitory effect of piperine on Na(+) channels. Together, our data suggest Na(+) channel antagonist activity as a contributor to the complex anticonvulsant mechanisms of piperine.
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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) | 0.000 | 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".