Acute temperature elevation in tap and Rhine water affects skin and gill epithelia, hydromineral balance, and gill Na<sup>+</sup>/K<sup>+</sup>-ATPase activity of brown trout (<i>Salmo trutta</i>) smolts
Bibliographic record
Abstract
The effects of a 3-h temperature elevation of 7°C were studied for 29 days on the brown trout (Salmo trutta) smolt in tap water and in water from the lower Rhine. The effects in the skin were apparent at 3 h and included depletion of electron-dense vesicles and increased numbers of heavily stained desmosomes in the filament cells of the upper epidermis. Increased levels of apoptosis and necrosis occurred and were associated with leukocyte infiltration of the epidermis. Similar effects in the gill epithelium were mainly confined to the chloride cells. Highest levels of necrosis in skin and gill epithelia occurred in fish that were temperature shocked in Rhine water. Effects of exposure to Rhine water alone were intermediate between those of temperature shock in tap water and in Rhine water. At 29 days, recovery was good in tap water, partial in Rhine water, and poor for the fish temperature shocked in Rhine water. Although disruption of hydromineral balance was not indicated in plasma electrolytes, specific Na+/K+-ATPase activities in the gill were higher for all treatments at 24 h and for the groups temperature shocked in Rhine water at 8 days. Overall, temperature shock in Rhine water gives additive stress effects and poor recovery at 29 days.
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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) | 0.001 | 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".