Fasting Increases Aggression and Differentially Modulates Local And Systemic Steroid Levels in Male Zebra Finches
Bibliographic record
Abstract
Aggression enables individuals to obtain and retain limited resources. Studies of the neuroendocrine regulation of aggression have focused on territorial and reproductive contexts. By contrast, little is understood concerning the neuroendocrine regulation of aggression over other resources, such as food. Here, we developed a paradigm to examine the role of steroids in food-related aggression. In groups of male zebra finches, a 6-hour fast decreased body mass and increased aggressive interactions among subjects that competed for a point source feeder. Fasting also dramatically altered circulating steroid levels by decreasing plasma testosterone but not estradiol (E2). By contrast, both plasma corticosterone and dehydroepiandrosterone (DHEA) concentrations were elevated with fasting. Interestingly, short-term access to food (15 minutes) after fasting normalized circulating steroid levels. Fasting increased corticosterone levels in a wide range of peripheral tissues but increased DHEA levels specifically in adrenal glands and liver; these effects were quickly normalized with refeeding. DHEA can be metabolized within specific brain regions to testosterone and E2, which promote the expression of aggression. We measured E2 in microdissected brain regions and found that fasting specifically increased local E2 levels in 3 regions: the periaqueductal gray, ventral tegmental area, and ventromedial nucleus of the hypothalamus. These regions are part of the vertebrate social behavior network and regulate the expression of aggression. Together, these data suggest that fasting stimulates secretion of DHEA from the adrenals and liver and subsequent conversion of DHEA to E2 within specific brain regions, to enable individuals to compete for limited food resources.
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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 | 0.001 |
| 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".