Involvement of non-neuronal brain cells in AVP-mediated regulation of water space at the cellular, organ, and whole-body level
Bibliographic record
Abstract
Vasopressin (AVP) influences non-neuronal brain cells in cell-type specific manners: (1) it regulates water balance at the cellular level of brain parenchyma by adjusting astrocytic water permeability; (2) it contributes to the control of extracellular K(+) concentration ([K(+)](e)) in brain by stimulation of K(+) transfer from blood to brain, due to activation of an inwardly directed Na(+),K(+),Cl(-) cotransporter at the luminal membrane of capillary endothelial cells and opening of K(+) channels at their abluminal membrane; (3) it decreases formation of cerebrospinal fluid (CSF) by decreasing Cl(-) secretion into CSF by epithelial cells of the choroid plexus, probably by inhibition of Cl(-)/HCO(-)(3) exchange at their basolateral membrane; (4) it contributes to regulation of intracellular volume within the brain by regulation of water permeability in ependymal cells and subpial astrocytes; and (5) it exerts effects on specialized astrocytes in circumventricular organs, their adjacent glia limitans, and the neural pituitary, which regulate AVP release to the systemic circulation by altering the spatial relationship between neurons and their adjacent glial cells. A unified mechanism is proposed, which integrates most of the effects of AVP and may be of considerable importance for neuronal excitability and, thus, for behavior.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".