Locomotor and peripheral effects of sibutramine modulated by 5-HT<sub>2</sub>receptors
Bibliographic record
Abstract
Sibutramine has been described as an anti-obesity drug with the ability to inhibit serotonin (5-HT), noradrenaline, and dopamine re-uptake, but without affinity to histamine and muscarinic receptors. On the other hand, cyproheptadine antagonizes serotonin 5-HT(2A), 5-HT(2B), and 5-HT(2C), histamine H1, and muscarinic (M) receptors. There are many reports concerning the influence of sibutramine on central serotoninergic pathways. In this study, we suggest that peripheral pathways may also be involved in the serotoninergic effects of sibutramine. In vivo experiments were undertaken to investigate the serotoninergic effects of sibutramine on body mass, the glycogen concentration in the diaphragm of rats, and locomotor behaviour. Rats were submitted to oral treatment with sibutramine, cyproheptadine, or sibutramine applied in combination with cyproheptadine, for a period of 2 months to investigate the 5-HT2 effects of sibutramine on these parameters. As the results demonstrated, the lower increase in body mass and the increased glycogen levels in the diaphragm muscle of rats treated with sibutramine seem to be modulated by 5-HT2 receptors, since these effects were completely antagonized by cyproheptadine in the group treated with the 2 drugs co-applied. Furthermore, the behavioural results also suggest that mechanisms modulated by 5-HT2 receptors are involved in the increase of locomotion in the rats treated with sibutramine, since the effect did not occur in the rats treated with sibutramine co-applied with the 5-HT2 receptor antagonist, cyproheptadine. The results suggest that sibutramine modifies energy-related parameters such as body mass, diaphragm glycogen, and locomotor behaviour in rats via 5-HT2 serotoninergic pathways.
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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) | 0.002 | 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".