Behavioural responses to acute warming precede critical shifts in the cellular and physiological thermal stress responses in a salmonid fish (brook trout, <i>Salvelinus fontinalis</i>)
Bibliographic record
Abstract
From a conservation perspective, it is important to identify when sub-lethal temperatures begin to adversely impact an organism. However, it is unclear whether, during acute exposures, sub-lethal cellular thresholds occur at similar temperatures to other physiological or behavioural changes, or at temperatures associated with common physiological endpoints measured in fishes to estimate thermal tolerance. To test this, we estimated temperature preference (15.1±1.1°C, mean±s.d.) using a shuttle box, agitation temperature (22.0±1.4°C), defined as the point where a fish exhibits a behavioural avoidance response, and the upper thermal limit (CTmax, 28.2±0.4°C) for 1 year old brook trout (Salvelinus fontinalis) acclimated to 10°C. We then acutely exposed a different subset of fish to the mean temperatures associated with the pre-determined physiological endpoints and sampled tissues when they reached the target temperature or after 60 min of recovery at 10°C for transcriptomic analysis. We used qPCR to estimate mRNA transcript levels of genes associated with heat shock proteins, oxidative stress, apoptosis and inducible transcription factors. A major shift in the transcriptome response occurred once the agitation temperature was reached, which may identify a possible link between the cellular stress response and the behavioural avoidance response.
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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) | 0.002 | 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".