Neuropeptide W has Cell Phenotype‐Specific Effects on the Excitability of Different Subpopulations of Paraventricular Nucleus Neurones
Bibliographic record
Abstract
The administration of the neuropeptide W (NPW) and neuropeptide B (NPB) in rodents has been shown to influence the activity of a variety of autonomic and neuroendocrine systems. The paraventricular nucleus (PVN) is a major autonomic and neuroendocrine integration site in the hypothalamus, and neurones within this nucleus express the receptor for these ligands, NPB/W receptor 1 (NPBWR1). In the present study, we used whole cell patch clamp recordings coupled with single-cell reverse transcriptase-polymerase chain reaction to examine the effects of neuropeptide W-23 (NPW-23) on the excitability of identified PVN neurones. Oxytocin, vasopressin and thyrotrophin-releasing hormone neurones were all found to be responsive to 10 nm NPW-23, although both depolarising and hyperpolarising effects were observed in each of these cell groups. By contrast, corticotrophin-releasing hormone cells were unaffected. Further subdivision of chemically phenotyped cell groups into magnocellular, neuroendocrine or pre-autonomic neurones, using their electrophysiological fingerprints, revealed that neurones projecting to medullary and spinal targets were predominantly inhibited by NPW-23, whereas those that projected to median eminence or neural lobe showed almost equivalent numbers of depolarising and hyperpolarising cells. The demonstration of particular phenotypic populations of PVN neurones showing NPW-induced effects on excitability reinforces the importance of the NPB/NPW neuropeptide system as a regulator of autonomic function.
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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".