Leptin Prevents Lipopolysaccharide-Induced Depressive-Like Behaviors in Mice: Involvement of Dopamine Receptors
Bibliographic record
Abstract
Depression is a chronic and recurrent disorder, associated with high morbidity and risk of suicide. Leptin was firstly described as an anti-obesity hormone, but several actions of leptin in CNS have been reported. In fact, leptin regulates dopaminergic neurotransmission in mesolimbic areas and has antidepressant-like properties in stress-based models. In the present study, we investigated, for the first time, putative antidepressant-like effects of leptin in an animal model of depressive-like behaviors induced by lipopolysaccharide (LPS), and the potential involvement of dopamine receptors as mediators of those behavioral effects. Mice were injected leptin (1.5 mg/kg, IP) or imipramine prior to LPS administration. To evaluate the involvement of dopamine receptors, different experimental groups were pretreated with either the dopaminergic antagonist SCH23390, for D1 receptors or raclopride, for D2/D3 receptors, prior to leptin injection. Twenty-four hours post-LPS, mice were submitted to the forced swimming and sucrose preference tests. In addition, IL-1β levels were determined in the prefrontal cortex (PFC), hippocampus and striatum. BDNF levels were measured in the hippocampus. Our results showed that leptin, similarly to imipramine, prevented the core behavioral alterations induced by LPS (despair-like behavior and anhedonia), without altering locomotion. In neurochemical analysis, leptin restored LPS-induced changes in IL-1β levels in the PFC and striatum, and increased BDNF levels in the hippocampus. The blockade of dopamine D1 and D2/D3 receptors inhibited leptin's antidepressant-like effects, whilst only the blockade of D1-like receptors blunted leptin-induced increments in prefrontal IL-1β levels. Our results indicate that leptin has antidepressant-like effects in an inflammatory model of depression with the contribution, at least partial, of dopamine receptors.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".