Fecal glucocorticoid metabolites reflect hypothalamic–pituitary–adrenal axis activity in muskoxen (Ovibos moschatus)
Bibliographic record
Abstract
Muskoxen (Ovibos moschatus), a taxonomically unique Arctic species, are increasingly exposed to climate and other anthropogenic changes. It is critical to develop and validate reliable tools to monitor their physiological stress response in order to assess the impacts of these changes. Here, we measured fecal glucocorticoid metabolite (FGM) levels in response to the administration of adrenocorticotropic hormone (ACTH) in the winter (1 IU/kg) and summer (2 IU/kg) using two enzyme immunoassays, one targeting primarily cortisol and the other targeting primarily corticosterone. Fecal cortisol levels varied substantially within and among individuals, and none of the animals in either challenge showed an increase in fecal cortisol following the injection of ACTH. By contrast, two of six (winter) and two of five (summer) muskoxen showed a clear response in fecal corticosterone levels (i.e., maximal percentage increase as compared to time 0 levels > 100%). Increases in fecal corticosterone post-ACTH injection occurred earlier and were of shorter duration in the summer than in the winter and fecal corticosterone levels were, in general, lower during the summer. These seasonal differences in FGM responses may be related to the use of different individuals (i.e., influence of sex, age, social status, etc.) and to seasonal variations in the metabolism and excretion of glucocorticoids, intestinal transit time, voluntary food intake, and fecal output and moisture content. Results from this study support using FGMs as a biomarker of hypothalamic-pituitary-adrenal axis activity in muskoxen, advance our understanding of the physiological adaptations of mammals living in highly seasonal and extreme environments such as the Arctic, and emphasize the importance of considering seasonality in other species when interpreting FGM levels.
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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".