An Aggressive Interaction Rapidly Increases Brain Androgens in a Male Songbird during the Non-breeding Season
Bibliographic record
Abstract
Aggression is a crucial behavior that impacts access to limited resources in different environmental contexts. Androgens synthesized by the gonads promote aggression during the breeding season. However, aggression can be expressed during the non-breeding season, despite low androgen synthesis by the gonads. The brain can also synthesize steroids (neurosteroids), including androgens, which might promote aggression during the non-breeding season. Male song sparrows, Melospiza melodia , are territorial year-round and allow the study of seasonal changes in the steroid modulation of aggression. Here, we quantified steroids following a simulated territorial intrusion (STI) for 10 min in wild adult male song sparrows during the breeding and non-breeding seasons. Using liquid chromatography-tandem mass spectrometry (LC-MS/MS), we examined 11 steroids: pregnenolone, progesterone, corticosterone, dehydroepiandrosterone, androstenedione, testosterone, 5a-dihydrotestosterone, 17-estradiol, 17a-estradiol, estriol, and estrone. Steroids were measured in blood and 10 microdissected brain regions that regulate social behavior. In both seasons, STI increased corticosterone in the blood and brain. In the breeding season, STI had no rapid effects on androgens or estrogens. Intriguingly, in the non-breeding season, STI increased testosterone and androstenedione in several behaviorally relevant regions, but not in the blood, where androgens remained non-detectable. Also in the non-breeding season, STI increased progesterone in the blood and specific brain regions. Overall, rapid socially modulated changes in brain steroid levels are more prominent during the non-breeding season. Brain steroid levels vary with season and social context in a region-specific manner and suggest a role for neuroandrogens in aggression during the non-breeding season.
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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".