Activation of organum vasculosum neurones and water intake in mice by vasopressin neurones in the suprachiasmatic nucleus
Bibliographic record
Abstract
Previous studies have shown that mice housed under 12:12 h light-dark conditions display a pronounced increase in water intake during a 2-hour anticipatory period (AP) near the end of their active period (Zeitgeber Time ZT; ZT21.5-ZT23.5) compared to the preceding basal period (BP, ZT19.5-ZT21.5). This increased water intake during the AP is not associated with physiological stimuli for thirst, such as food intake, hyperosmolality, hyperthermia, or hypovolemia. Denying mice the water intake supplement during the AP causes them to be dehydrated at wake time. These observations suggest that this form of thirst may be driven by the circadian clock and serve to mitigate the dehydrating effect of absence of water intake during sleep. Here we review recent findings showing that this behavior is mediated by vasopressin (VP) containing neurons in the suprachiasmatic nucleus (SCN). SCN VP neurons project to the organum vasculosum lamina terminalis (OVLT) where the activity dependent release of VP causes excitation of thirst-promoting neurons. SCN VP neurons increase their electrical activity during the AP and the resultant release of VP causes an increase in the action potential firing rate of OVLT neurons. Experiments involving optogenetic control of VP release from the axon terminals of SCN neurons indicate that this network mechanism is necessary and sufficient to mediate pre-sleep water intake in mice. These findings provide insight into the output mechanisms that are used by the central clock to generate circadian rhythms, and reveal that the regulation of water intake contributes to osmoregulatory homeostasis during sleep. This article is protected by copyright. All rights reserved.
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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 | 0.000 |
| 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".