COMPARATIVE STUDY ON THE IMPACT OF DIFFERENT IMMOBILIZATION METHODS ON MUSCLE INTEGRITY AND STRESS INDICATORS IN BROOK TROUT (SALVELINUS FONTINALIS)
Bibliographic record
Abstract
Chemical sedation of fish is often used during scientific research to reduce stress and risk of injury. Electric fish handling gloves (EFHG) have been proposed as a no-residue alternative to chemical immobilization. However, the impact of handling fish with EFHG on their physiology remains relatively poorly studied. Stress markers (plasma cortisol and lactate) and the impact on muscular integrity (plasma creatine kinase and histopathology of skeletal muscles) were assessed in brook trout (Salvelinus fontinalis) subjected to one of three immobilization methods (manual restraint, EFHG [10–16 mV], and buffered 60 mg/L tricaine methanesulfonate [MS-222] immersion anesthesia) for 1- and 5-min restraints. Plasma lactate levels were significantly higher 2 h postrestraint for all experimental groups (+242%; P < 0.001), but the magnitude of these increases was significantly lower in the MS-222 groups (P ≤ 0.0002). Plasma creatine kinase concentrations significantly increased 2 h postrestraint for the EFHG groups (+92%, P ≤ 0.0061), and this increase was significantly higher than in the MS-222 group for the 1-min restraint (P = 0.0031). Although there was no significant difference between the restraining methods tested at all time points for plasma cortisol, the EFHG and manual restraint groups showed a linear and statistically significant increase after the initial 5-min restraint, whereas all other groups presented an expected bell-shaped profile with a plasma peak 1 h after the initial restraint. One fish in the manual restraint group died during the 5-min restraint, and two fish from the EFHG group were euthanized at the end of this protocol because of buoyancy anomalies. All other fish from the 5-min restraint group developed cutaneous saprolegniasis 3 wk after the experiments. The evaluation of the safety of EFHG in brook trout showed similar impacts on the variables tested compared with manual restraint for 1- and 5-min immobilizations.
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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".