Physiological Regulation of Magnocellular Neurosecretory Cell Activity: Integration of Intrinsic, Local and Afferent Mechanisms
Bibliographic record
Abstract
The hypothalamic supraoptic and paraventricular nuclei contain magnocellular neurosecretory cells (MNCs) that project to the posterior pituitary gland where they secrete either oxytocin or vasopressin (the antidiuretic hormone) into the circulation. Oxytocin is important for delivery at birth and is essential for milk ejection during suckling. Vasopressin primarily promotes water reabsorption in the kidney to maintain body fluid balance, but also increases vasoconstriction. The profile of oxytocin and vasopressin secretion is principally determined by the pattern of action potentials initiated at the cell bodies. Although it has long been known that the activity of MNCs depends upon afferent inputs that relay information on reproductive, osmotic and cardiovascular status, it has recently become clear that activity depends critically on local regulation by glial cells, as well as intrinsic regulation by the MNCs themselves. Here, we provide an overview of recent advances in our understanding of how intrinsic and local extrinsic mechanisms integrate with afferent inputs to generate appropriate physiological regulation of oxytocin and vasopressin MNC activity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".