Temperature impacts Atlantic salmon's (Salmo salar) immunological response to infectious salmon anemia virus (ISAv).
Bibliographic record
Abstract
Ocean temperatures continue to rise annually due to the ever-growing consequences of global climate change. These temperature changes can have an impact on the immunological robustness of cultured fish, especially cold-water species such as Atlantic salmon. The salmon farming industry already loses hundreds of millions of dollars each year to infectious and non-infectious diseases. One particularly important and WOAH reportable disease is infectious salmon anemia caused by the orthomyxovirus ISAv. Considering the changing environment, it is necessary to find ways to mitigate the effect of diseases on the industry. For this study, 20 Atlantic salmon families were housed in each of 38 different tanks at the AVC, with half of the fish being kept at 10 °C and half being kept at 20 °C. Donor Atlantic salmon IP- injected with a highly virulent ISAv isolate (HPR4; TCID50 of 1 × 105/mL) were added to each tank as the source of co-habitation infection. Both temperatures were sampled at onset of mortality in co-habited fish and at resolution of mortality. Family background and temperature significantly impacted ISAv load, as assessed by qPCR, time to mortality and overall mortality. Mortality was more acute at 20 °C, but overall mortality was higher at 10 °C. Based on percent mortality calculated over the course of the study, different families demonstrated different levels of survival. The three families that demonstrated the highest percent mortality, and the three families with the lowest percent mortality were then assessed for their antiviral responses using relative gene expression. Genes significantly upregulated between the unexposed fish and ISAv exposed fish included mx1, il4/13a, il12rb2, and trim25, and these were further impacted by temperature. Understanding how ISAv resistance is impacted by temperature can help identify seasonal risks of ISAv outbreaks as well as ideal responses to be targeted through immunopotentiation.
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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) | 0.002 | 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".