A Possible Potentiating Antidepressant Effect of Venlafaxine by Recombinant Rat Leptin in a Rat Model of Chronic Mild Stress
Bibliographic record
Abstract
The present study was designed to investigate the possible changes in forced swimming test (FST), prefrontal cortical glutamate and gamma amino-butyric acid (GABA) contents by leptin and/or venlafaxine in chronic mild stress (CMS)-induced anhedonia in male albino rats.They were divided into 5 groups: the first group was not exposed to CMS, the second group received normal saline with exposure to CMS, the third group received leptin 1 mg/kg/day intraperitoneally (ip) for 3 weeks after CMS induced anhedonia was assesed by sucrose consumption test, the fourth group received venlafaxine 8 mg/kg/day ip for 3 weeks after CMS protocol, and the fifth group was received both medications for 3 weeks.Leptin and/or venlafaxine restored the changes in sucrose consumption test, behavioural assessment by forced swimming test (FST) as well as prefrontal cortical GABA and glutamate contents in the control stressed group.Furthermore, combination of both treatments seems to be more efficacious than venlafaxine alone in these parameters.In conclusion,these results showed a potential antidepressant role of leptin and beneficial therapeutic interaction with venlafaxine by affecting the GABA and glutamate level in prefrontal cortex.These actions could make leptin a potentially valuable drug for the treatment of depression.
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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 | 0.001 |
| 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".