Vegetable omega-3 and omega-6 fatty acids differentially modulate the antiviral and antibacterial immune responses of Atlantic salmon
Bibliographic record
Abstract
The immunomodulatory effects of omega-3 and omega-6 fatty acids are a crucial subject of investigation for sustainable fish aquaculture, as fish oil is increasingly replaced by terrestrial vegetable oils in aquafeeds. Unlike previous research focusing on fish oil replacement with vegetable alternatives, our study explored how the omega-6 to omega-3 polyunsaturated fatty acid (PUFA) ratio in low-fish oil aquafeeds influences Atlantic salmon's antiviral and antibacterial immune responses. Atlantic salmon were fed aquafeeds rich in soy oil (high in omega-6) or linseed oil (high in omega-3) for 12 weeks and then challenged with bacterial (formalin-killed Aeromonas salmonicida) or viral-like (polyriboinosinic polyribocytidylic acid) antigens. The head kidneys of salmon fed high dietary omega-3 levels exhibited a more anti-inflammatory fatty acid profile and a restrained induction of pro-inflammatory and neutrophil-related genes during the immune challenges. The high-omega-3 diet also promoted a higher expression of genes associated with the interferon-mediated signaling pathway, potentially enhancing antiviral immunity. This research highlights the capacity of vegetable oils with different omega-6 to omega-3 PUFA ratios to modulate specific components of fish immune responses, offering insights for future research on the intricate lipid nutrition-immunity interplay and the development of novel sustainable low-fish oil clinical aquaculture feeds.
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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".