Short-term effects of melatonin and pinealectomy on serotonergic neuronal activity across the light–dark cycle
Bibliographic record
Abstract
Melatonin (MLT) and serotonin (5-HT) are two biosynthetically related compounds implicated in several common physiological functions and the etiology of mood disorders. How they interact, though, is not yet fully understood. In this study, single-unit extracellular recordings were used to monitor dorsal raphe nucleus (DR) 5-HT neuronal activity in anesthetized rats, under basal conditions (CTRL), in response to MLT administration, and after pinealectomy (PX) across the light-dark cycle. Under basal conditions, the number of spontaneously active 5-HT neurons and their firing rate were both significantly lower in the dark phase. In the light phase, administration of MLT at low doses (0.5-1 mg/kg, i.v.) decreased 5-HT firing activity. This inhibitory effect of MLT was completely blocked by the MT₁/MT₂ receptor antagonist luzindole, but not by the selective MT(2) receptor antagonist 4P-PDOT, the selective 5-HT(1A) receptor antagonist WAY100635, or by the α₂ adrenoceptor antagonist idazoxan. In the opposite experiment, PX increased 5-HT firing activity in the dark phase, and this was reversed by MLT administration (1 mg/kg, i.v.). Finally, in a forced swim test, MLT (1 mg/kg, i.p.) increased immobility time and decreased swimming behavior. Together, these results suggest that nocturnal MLT secretion imposes tonic inhibitory control over a sub-population of DR 5-HT neurons. This MLT-induced decrease in 5-HT neurotransmission may represent a biological mechanism underlying mood disorders characterized by increased MLT secretion, such as seasonal affective disorder.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".