Inactivated <i>Aeromonas salmonicida</i> impairs adaptive immunity in lumpfish (<i>Cyclopterus lumpus</i>)
Bibliographic record
Abstract
Abstract Aeromonas salmonicida , a widely distributed aquatic pathogen causing furunculosis in fish, exhibits varied virulence, posing challenges in infectious disease and immunity studies, notably in vaccine efficacy assessment. Lumpfish ( Cyclopterus lumpus ) has become a valuable model for marine pathogenesis studies. This study evaluated several antigen preparations against A. salmonicida J223, a hypervirulent strain of teleost fish, including lumpfish. The potential immune protective effect of A. salmonicida bacterins in the presence and absence of the A‐layer and extracellular products was tested in lumpfish. Also, we evaluated the impact of A. salmonicida outer membrane proteins (OMPs) and iron‐regulated outer membrane proteins (IROMPs) on lumpfish immunity. The immunized lumpfish were intraperitoneally (i.p.) challenged with 10 4 A. salmonicida cells/dose at 8 weeks‐post immunization (wpi). Immunized and non‐immunized fish died within 2 weeks post‐challenge. Our analyses showed that immunization with A. salmonicida J223 bacterins and antigen preparations did not increase IgM titres. In addition, adaptive immunity biomarker genes (e.g., igm , mhc‐ii and cd4 ) were down‐regulated. These findings suggest that A. salmonicida J223 antigen preparations hinder lumpfish immunity. Notably, many fish vaccines are bacterin‐based, often lacking efficacy evaluation. This study offers crucial insights for finfish vaccine approval and regulations.
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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".