Endogenous extracellular serotonin modulates the spinal locomotor network of the neonatal mouse
Bibliographic record
Abstract
Serotonin (5-HT) can potently activate and modulate spinal locomotor circuits in a variety of species. Many of these findings have been obtained by applying serotonin exogenously to the isolated spinal cord of in vitro preparations, which has the drawback of indiscriminately activating extrasynaptic receptors and neurons. To investigate the role of endogenously released serotonin in modulating locomotor networks, the selective serotonin reuptake inhibitor citalopram was used. Fictive locomotion was elicited by either electrical stimulation of the brainstem or the sacral 4 (S4) dorsal root. The addition of 20 microm of citalopram caudal to thoracic segment 5 (T5) had an overall inhibitory effect on the lumbar central pattern generator (CPG). Left-right and flexor-extensor coupling were significantly decreased, and there was also a phase shift in the flexor-extensor relationship. In addition, there was a significant decrease in burst amplitude. These effects were observed during both afferent and brainstem evoked fictive locomotion. When citalopram was added in the presence of 5-HT(1A) and 5-HT(1B) antagonists, the inhibitory effects were largely reversed. The remaining excitatory effects were mediated by 5-HT(7) and 5-HT(2) receptors. These results suggest that endogenous 5-HT release can modulate locomotor-like activity early in neonatal development.
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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) | 0.001 | 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".