First Look into the Use of Fish Scales as a Medium for Multi-Hormone Stress Analyses
Bibliographic record
Abstract
Recent efforts have provided convincing evidence for the use of fish scale cortisol concentration in the assessment of long-term stress in fishes. However, cortisol alone is not sufficient to fully describe this state of long-term stress. Dehydroepiandrosterone (DHEA) is an androgen with actions that oppose those of cortisol. The means by which DHEA negates the effects of cortisol occurs in part via changes in the metabolism of cortisol to cortisone. The quantitation of cortisol, DHEA and cortisone could therefore provide a more comprehensive assessment of the overall status of physiological stress. As DHEA and cortisone have yet to be quantified within the fish scale, our first objective was to ensure our sample processing protocol for cortisol was applicable to cortisone and DHEA. Following this, we induced a state of long-term stress in goldfish (Carassius auratus). Some degree of elevation in all hormones was observed in the stressed fish scales. Additionally, cortisol and cortisone were significantly elevated in the stressed fish serum in comparison to controls while DHEA was undetectable in either group. Overall, these results suggest that fish scales provide an appropriate medium for the assessment of long-term stress in fishes via the quantitation of relevant steroid hormones.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".