Possible involvement of ATP-sensitive potassium channels in the antidepressant-like effects of gabapentin in mouse forced swimming test
Bibliographic record
Abstract
Gabapentin as an anticonvulsant drug also has beneficial effects in treatment of depression. Previously, we showed that acute administration of gabapentin produced an antidepressant-like effect in the mouse forced swimming test (FST) by a mechanism that involves the inhibition of nitric oxide (NO). Considering the involvement of NO in adenosine triphosphate (ATP)-sensitive potassium channels (KATP), in the present study we investigated the involvement of KATP channels in antidepressant-like effect of gabapentin. Gabapentin at different doses (5–10 mg/kg) and fluoxetine (20 mg/kg) were administrated by intraperitoneal route, 60 and 30 min, respectively, before the test. To clarify the probable involvement of KATP channels, mice were pretreated with KATP channel inhibitor or opener. Gabapentin at dose 10 mg/kg significantly decreased the immobility behavior of mice similar to fluoxetine (20 mg/kg). Co-administration of subeffective dose (1 mg/kg) of glibenclamide (inhibitor of KATP channels) with gabapentin (3 mg/kg) showed a synergistic antidepressant-like effect. Also, subeffective dose of cromakalim (opener of KATP channels, 0.1 mg/kg) inhibited the antidepressant-like effect of gabapentin (10 mg/kg). None of the treatments had any impact on the locomotor movement. Our study, for the first time, revealed that antidepressant-like effect of gabapentin in mice is mediated by blocking the KATP channels.
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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) | 0.001 | 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 | 0.001 | 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".