Trafficking of neurokinin‐1 receptors in serotonin neurons is controlled by substance P within the rat dorsal raphe nucleus
Bibliographic record
Abstract
Substance P (SP) modulates serotonin neurotransmission via neurokinin-1 receptors (NK1rs), and exerts regulatory effects on mood through habenular afferents to the dorsal raphe nucleus (DRN). We have previously demonstrated that, in the caudal DRN of rat, some serotonin neurons are endowed with NK1rs that are mostly cytoplasmic, whereas these receptors are mostly membrane bound in non-serotonin neurons. Here, we first examined by double-labeling immunocytochemistry the relationships between SP axon terminals and these two categories of DRN neurons. Almost half of the SP terminals were synaptic and many were in close contact with serotonin dendrites, but never with non-serotonin dendrites. In additional double-immunolabeling experiments, most if not all dendrites bearing membranous NK1rs appeared to be GABAergic. Treatment with the selective neurokinin-1 antagonist RP67580 modified the subcellular distribution of NK1rs in serotonin neurons. At 1 h after administration of a single dose, the receptor distribution was unchanged in both dendritic types but, after daily administration for 7 or 21 days, the plasma membrane and cytoplasmic density of NK1rs were increased in serotonin dendrites, without any change in non-serotonin dendrites. These treatments also increased NK1r gene expression in the caudal DRN. Lastly, a marked increase in the membrane (but not cytoplasmic) density of NK1rs was measured in serotonin dendrites after bilateral habenular lesion. These results suggest that the trafficking of NK1rs represents a cellular mechanism in control of the modulation of serotonin neuron activity by SP in DRN.
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".