Sex-Specific Vasopressin Signaling Buffers Stress-Dependent Synaptic Changes in Female Mice
Bibliographic record
Abstract
In many species, social networks provide benefit for both the individual and the collective. In addition to transmitting information to others, social networks provide an emotional buffer for distressed individuals. Our understanding about the cellular mechanisms that contribute to buffering is poor. Stress has consequences for the entire organism, including a robust change in synaptic plasticity at glutamate synapses onto corticotropin-releasing hormone (CRH) neurons in the paraventricular nucleus of the hypothalamus (PVN). In females, however, this stress-induced metaplasticity is buffered by the presence of a naive partner. This buffering may be because of discrete behavioral interactions, signals in the context in which the interaction occurs (i.e., olfactory cues), or it may be influenced by local signaling events in the PVN. Here, we show that local vasopressin (VP) signaling in PVN buffers the short-term potentiation (STP) at glutamate synapses after stress. This social buffering of metaplasticity, which requires the presence of another individual, was prevented by pharmacological inhibition of the VP 1a receptor (V1aR) in female mice. Exogenous VP mimicked the effects of social buffering and reduced STP in CRH PVN neurons from females but not males. These findings implicate VP as a potential mediator of social buffering in female mice. SIGNIFICANCE STATEMENT In many organisms, including rodents and humans, social groups are beneficial to overall health and well-being. Moreover, it is through these social interactions that the harmful effects of stress can be mitigated, a phenomenon known as social buffering. In the present study, we describe a critical role for the neuropeptide vasopressin (VP) in social buffering of synaptic metaplasticity in stress-responsive corticotropin-releasing hormone (CRH) neurons in female mice. These effects of VP do not extend to social buffering of stress behaviors, suggesting this is a very precise and local form of sex-specific neuropeptide signaling.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".