Bridging the gap: Ghrelin and the female stress response to acute non-discriminatory social defeat
Bibliographic record
Abstract
Mouse models of social stress are critical for understanding the impact of social stress on affective state. Nevertheless, these models have focused on male social defeat and dominance hierarchies, making the data only relevant to males. The non-discriminatory social defeat (NDSD) paradigm was developed to study social stress effects in male and female mice. Here, we used NDSD to study the effects of this social stressor on neuroendocrine parameters associated with the stress response in growth hormone secretagogue receptor knock out (GHSR KO) or WT male and female mice. Male/female GHSR KO or WT pairs were added to the cage of a male CD-1 mouse for 10 min. Mice were sacrificed 30 or 60 min later to collect blood or to collect brains for cFos Immunocytochemistry. Acute NDSD led to increased plasma corticosterone and ghrelin compared to non-stress controls. Additionally, we saw lowered LEAP-2 levels in stressed mice, as compared to controls.. We also found stress increased cFos expression in the paraventricular nucleus (PVN) in stressed mice, with stressed female GHSR KO mice sacrificed in the pre-ovulatory phase of the estrous cycle showing more cFos in the PVN than stressed WT counterparts. These data highlight a differential response to acute NDSD in males and females, suggesting that stress-induced activation in the female PVN is moderated by the GHSR and by fluctuating levels of estrogen.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".