Fluoxetine oral treatment discloses 5-HT<sub>1D</sub> receptor as vagoinhibitor of the cardiac cholinergic neurotransmission in rat
Bibliographic record
Abstract
Although depression and cardiovascular diseases are related, the role of antidepressants such as fluoxetine (increasing serotonin levels) within cardiac regulation remains unclear. We aimed to determine whether fluoxetine modifies the pharmacological profile of serotonergic influence on vagal cardiac outflow. Rats were treated with fluoxetine (10 mg/kg per day; p.o.) for 14 days or equivalent volumes of drinking water (control group); then, they were pithed and prepared for vagal stimulation. Bradycardic responses were obtained by electrical stimulation of the vagal fibers (3, 6, and 9 Hz) or i.v. acetylcholine (ACh; 1, 5, and 10 μg/kg). The i.v. administration of 5-hydroxytryptamine (5-HT; 10 and 50 μg/kg) inhibited the vagally induced bradycardia. 5-CT (5-HT1/7 agonist) and L-694,247 (5-HT1D agonist) mimicked the serotonin inhibitory effect while α-methyl-5-HT (5-HT2 agonist) was devoid of any action. SB269970 (5-HT7 antagonist) did not abolish 5-CT inhibitory action on the electrically induced bradycardia. Pretreatment with LY310762 (5-HT1D antagonist) blocked the effects induced by L-694,247 and 5-CT. 5-HT and 5-CT failed to modify the bradycardia induced by exogenous ACh. Our outcomes suggest that fluoxetine treatment modifies 5-HT modulation on heart parasympathetic neurotransmission in rats, evoking inhibition of the bradycardia via prejunctional 5-HT1D in pithed rats.
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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 | 0.000 | 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) | 0.003 | 0.001 |
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".