Dehydration-Induced Cross-Regulation of Apelin and Vasopressin Immunoreactivity Levels in Magnocellular Hypothalamic Neurons
Bibliographic record
Abstract
Apelin, a neuropeptide recently identified as the endogenous ligand for the G protein-coupled receptor APJ, is highly concentrated in brain structures involved in the control of body fluid homeostasis including the supraoptic (SON) and paraventricular (PVN) hypothalamic nuclei. To clarify the implication of apelin in the regulation of water balance, we sought to determine whether apelin colocalized with arginine vasopressin (AVP) in the rat SON and PVN. We also investigated the effects of water deprivation on the levels of apelin within these two nuclei by comparison with those of AVP. Using dual immunolabeling confocal microscopy, we found that a large proportion of apelin-immunoreactive neurons colocalized AVP within both the SON and PVN, but that the two peptides were segregated within distinct subcellular compartments inside these cells. Both the number and labeling intensity of magnocellular apelin-immunoreactive cells increased significantly after 24- or 48-h dehydration, whereas the number and labeling density of AVP-immunoreactive neurons significantly decreased. The dehydration-induced increase in apelin immunoreactivity was markedly diminished by central injection of a selective vasopressin-1 receptor antagonist. Conversely, the effect of dehydration was mimicked by a 16-min intracerebroventricular infusion of AVP, again in a vasopressin-1 receptor antagonist-reversible manner. These results provide additional evidence for the involvement of the neuropeptide apelin in the control of body fluid homeostasis. They further suggest that the dehydration-induced release of AVP from magnocellular hypothalamic neurons may be responsible for the observed increase in immunoreactive apelin levels within the same neurons and thus that the release of one peptide may block that of another peptide synthesized in the same cells.
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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".