Dendritic Vasopressin Release: Reducing the Flow Makes Blood Vessels Grow
Bibliographic record
Abstract
The hypothalamic supraoptic and paraventricular magnocellular neurons have long been favored for investigations of neuronal function due to their accessibility, defined neuronal cell types, and well known functional outputs. Here, the “neuronal” identity of endocrine-type cells was first identified within the central nervous system, their peptides were the first hormones to be structurally identified, and principles of both axonal and dendritic peptide release were first established. In addition, both astrocytes and neurons of the magnocellular nuclei display morphological and neurochemical features of plasticity that are associated with dynamic regulation of synaptic and secretory functions of the magnocellular neurons (reviewed in (Refs. 1 and 2). A paper in this issue of Endocrinology by Alonso et al. (3) reports novel data that adds yet another fascinating aspect to the physiology of these nuclei. It has been recognized for over 30 yr that high levels of activity in these nuclei were associated with cell proliferation (4). In a recent paper (5), Alonso et al. investigated this further and reported that osmotic stimulation that highly activated the vasopressin neurons in the supraoptic nucleus (SON) caused proliferation mainly of endothelial cells, resulting in angiogenesis and increased capillary density. This was driven by an increase in the expression and action of vascular endothelial growth factor (VEGF). Alonso et al. (3) have now followed up on this intriguing finding by identifying the stimulus for the increased VEGF and resulting angiogenesis. They report that intense activation of the magnocellular neurons by an osmotic stimulus was associated with tissue hypoxia, as revealed by appearance of pimonidazole adducts that occur under hypoxic conditions. In association with this apparent tissue hypoxia, they found that expression of the transcription factor, hypoxia-inducible factor 1α, was increased in the nucleus.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.018 | 0.016 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".