Social rank influences relationships between hormones and oxidative stress in a cichlid fish
Bibliographic record
Abstract
Abstract An individual’s social environment can have widespread effects on their physiology, including effects on oxidative stress and hormone levels. Many studies have posited that variation in oxidative stress experienced by individuals of different social ranks might be due to endocrine differences, however, few studies have evaluated this hypothesis. Here, we assessed whether a suite of markers associated with oxidative stress in different tissues (blood, plasma, liver, or gonads) had social rank-specific relationships with circulating testosterone or cortisol levels in males of a cichlid fish, Astatotilapia burtoni . Across all fish, blood DNA damage (a global marker of oxidative stress) and gonadal synthesis of reactive oxygen species (as indicated by NADPH-oxidase (NOX) activity) were lower when testosterone was high. High DNA damage in both the blood and gonads was associated with high cortisol in subordinates, but low cortisol in dominants. Additionally, high cortisol was associated with greater production of reactive oxygen species (greater NOX activity) in both the gonads (dominants only) and liver (dominants and subordinates). In general, high testosterone was associated with lower oxidative stress across both social ranks, whereas high cortisol was associated with lower oxidative stress in dominants and higher oxidative stress in subordinates. Taken together, our results show that differences in the social environment can lead to contrasting relationships between hormones and oxidative stress.
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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".