Nucleus raphe magnus serotonin neurons bidirectionally control spinal mechanical pain transmission
Bibliographic record
Abstract
ABSTRACT Background Noxious stimuli are conveyed to and integrated in the dorsal horn of the spinal cord (DHSC) before being transmitted to supraspinal centers, where pain perception is generated. Descending pathways from the brainstem dynamically modulate this integration, either facilitating or inhibiting nociceptive information based on physiological, emotional, genetic and environmental factors. Serotonergic neurons in the nucleus raphe magnus (NRM), activating different spinal 5-HT receptors, exert bidirectional control, both facilitatory and inhibitory, but the underlying mechanisms of this control remain unclear. Methods We investigated in adult mice, the NRM serotonergic modulation of nociception using imaging, behavioral, pharmacological, electrophysiological, chemogenetic and optogenetic approaches. Results We have demonstrated that the action of serotonergic neurons in the NRM on spinal nociceptive transmission depends on their activation pattern, which targets different spinal 5-HT receptors likely associated with different spinal microcircuits. Serotonergic neurons of the NRM exert a tonic analgesic effect mediated by 5-HT 2c receptor. Low increase in 5-HT activity leads to an increased analgesia through spinal inhibitory interneurons expressing 5-HT 2c and 5-HT 2A receptors. Finally, prolonged stimulation of serotonergic neurons led to hyperalgesia mediated by 5-HT 3 receptor. Comparison of 5-HT receptors in spinal tissue from mice and human shows that 5-HT 2c receptor has a very high expression level, comparable between both species. Conclusions These results propose a model of bidirectional action of serotonin neurons on nociceptive transmission depending on their level of activity and show that 5-HT 2c receptor is the main mediator of serotonin-induced analgesia.
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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 | 0.000 |
| 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".