Haemato-Immunological Response of Immunized Atlantic Salmon (Salmo salar) to Moritella viscosa Challenge and Antigens
Bibliographic record
Abstract
Winter ulcer disease is a health issue in the Atlantic salmonid aquaculture industry, mainly caused by Moritella viscosa. Although vaccination is one of the effective ways to prevent bacterial outbreaks in the salmon farming industry, ulcer disease related to bacterial infections is being reported on Canada’s Atlantic coast. Here, we studied the immune response of farmed immunized Atlantic salmon to bath and intraperitoneal (ip) M. viscosa challenges and evaluated the immunogenicity of M. viscosa cell components. IgM titers were determined after infection, post boost immunization, and post challenge with M. viscosa. IgM+ (B cell) in the spleen and blood cell populations were also identified and quantified by 3,3 dihexyloxacarbocyanine (DiOC6) and IgM-Texas red using confocal microscopy and flow cytometry. At 14 days post challenge, IgM was detected in the serum and spleen. There was a significant increase in circulating neutrophils 3 days after ip and bath challenges in the M. viscosa outer membrane vesicles (OMVs) boosted group compared to non-boosted. Lymphocytes increased in the blood at 7 and 14 days after the ip and bath challenges, respectively, in OMVs boosted group. Furthermore, a rise in IgM titers was detected in the OMVs boosted group. We determined that a commercial vaccine is effective against M. viscosa strain, and OMVs are the most immunogenic component of M. viscosa cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.001 |
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 teacher head, 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".