L’apéline, un inhibiteur naturel de l’effet antidiurétique de la vasopressine
Bibliographic record
Abstract
Apelin is a peptide that was recently isolated as the endogenous ligand for the human orphan APJ receptor, a G protein-coupled receptor which shares 31 % amino-acid sequence identity with the angiotensin type 1 receptor. Apelin naturally occurs in the brain and plasma as 13 (pE13F) and 17 amino-acid (K17F) fragments of a single pro-peptide precursor. In transfected CHO cells, K17F and pE13F bind with high affinity to the rat APJ receptor, promote receptor internalization, and inhibit forskolin-induced cAMP formation. In the same cells, pE13F activates MAP kinase and PI3 kinase pathways. Apelin and APJ receptors are both widely distributed in the brain but are particularly highly expressed in the supraoptic (SON) and paraventricular (PVN) hypothalamic nuclei. Dual labeling studies demonstrate that within these two nuclei, apelin and its receptor are colocalized with vasopressin (AVP) in a subset of magnocellular neurons. In lactating rats, characterized by increases in both synthesis and release of AVP, central injection of apelin inhibits the phasic electrical activity of AVP neurons, reduces plasma AVP levels, and increases aqueous diuresis. Moreover, water deprivation, while increasing the activity of AVP neurons, reduces plasma apelin concentrations and induces an intra-neuronal pile up of the peptide, thereby decreasing the inhibitory effect of apelin on AVP release and preventing additional water loss at the kidney level. Taken together, these data demonstrate that apelin counteracts the effects of AVP in the maintenance of body fluid homeostasis. In addition, apelin and its receptor are present in the cardiovascular system, i.e. heart, kidney and vessels. Systemically administered apelin reduces arterial blood pressure, increases cardiac contractility and reduces cardiac loading. The development of non peptidic analogs of apelin may therefore offer new therapeutic avenues for the treatment of cardiovascular disorders.
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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) | 0.002 | 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".