Atlantic salmon challenged with extracellular products from Moritella viscosa
Bibliographic record
Abstract
Skin ulcers in Atlantic salmon Salmo salar in the Canadian east coast salmon aquaculture industry lead to high mortality rates. This condition is clinically similar to winter ulcer disease in Norway with the exception that it occurs at temperatures above 10°C. Moritella viscosa is thought to be the causative agent for winter ulcer disease in Norway, and it is occasionally also isolated from skin ulcer cases in Atlantic Canada. This bacterium is known to produce cytotoxins. The objective of this study was to determine if extracellular products (ECP) from an Atlantic Canadian strain of M. viscosa could induce a tissue response similar to what is observed with M. viscosa infections in Atlantic salmon in eastern Canada. We injected fish subcutaneously with ECP and monitored the development of skin lesions. We sampled fish with early skin lesions and ulcers to describe the pathology associated with the condition. Samples were taken for histopathology, bacterial culture, and quantitative PCR (qPCR). All experimental fish expressed early skin lesions, with 5 fish (8.3%) developing deep skin ulcers after 12 d post-exposure. Our results suggest the ECP of M. viscosa from the east coast of Canada induces a similar tissue response to what is described in ulcer disease in Atlantic salmon. These extracelluar products may partially explain the pathology associated with M. viscosa.
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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".