Susceptibility to columnaris disease in Chinook salmon Oncorhynchus tshawytscha offspring from thiamine-deficient and thiamine-replete females
Bibliographic record
Abstract
Nutrient deficiency can cause increased susceptibility to infectious diseases in fish, thus leading to high rates of morbidity and mortality. Thiamine deficiency complex (TDC) in fish can lead to low reproductive success and high mortality rates. Columnaris disease in salmonids, caused by Flavobacterium columnare, has resulted in devastating losses in aquaculture production and wild populations of Pacific salmon particularly associated with climate change and high water temperatures. There is growing awareness that both TDC and columnaris are emerging diseases of salmonids on the west coast of North America; however, it is unknown whether fish that survive from low/intermediate thiamine level eggs will experience latent mortality due to susceptibility to infectious diseases like columnaris. To investigate the interaction of TDC survivors and columnaris, Chinook salmon Oncorhynchus tshawytscha fry reared from either thiamine-deficient (n = 120) or thiamine-replete (n = 120) eggs were challenged with F. columnare using an immersion challenge model of infection, and morbidity/mortality, immune responses, and bacterial load were evaluated. The cumulative mortalities between the treatment groups were significantly different, with the thiamine-deficient, F. columnare-exposed fry ending the challenge with an 80.3% survival rate and the thiamine-replete, F. columnare-exposed fry ending with a 29.03% survival rate (p < 0.0001). Different transcript abundance was detected in gills and spleen of thiamine-deficient and thiamine-replete fry exposed to F. columnare. This study demonstrated that fry reared from eggs low in thiamine have an altered immune response and warrants further studies to better understand interaction with potential pathogens at different life stages.
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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".