Serum Biomarkers in Atlantic Salmon for Differential Diagnosis of Cardiomyopathy Syndrome and Pancreas Disease: Proteomic Identification of Serum Fibrinogen to Enhance Troponin Immunoassay as Optimal Diagnostic Approach
Bibliographic record
Abstract
Cardiac viral diseases are among the major causes of economic losses in Atlantic salmon (Salmo salar L.) aquaculture. These include cardiomyopathy syndrome (CMS) caused by piscine myocarditis virus (PMCV) and pancreas disease (PD) caused by Atlantic salmonid alphavirus (SAV). The resulting cardiomyopathies impact fish stock in terms of mortality, quality, growth performance and economic loss. Diagnosis of these diseases is currently based on clinical signs, histopathology and RT-qPCR. To identify putative biomarkers for use in the health assessment of Atlantic salmon, a quantitative proteomics investigation was undertaken with the aim of differentiating fish with CMS from healthy fish and fish with PD. Serum samples (n = 9/group) were collected during health assessment from pens where clinical CMS or PD were present and compared to serum from healthy Atlantic salmon. There were 34 differentially abundant proteins (DAPs) in CMS compared to healthy, 66 comparing CMS to PD, and 81 comparing PD to healthy. In relation to healthy samples, most DAPs were shared between CMS and PD, with higher relative abundances observed in PD. An exception to this was serum fibrinogen, which was identified as a putative biomarker for CMS, whereas differentiation of Atlantic salmon with CMS from those with PD was enhanced by the calculation of the ratio of fibrinogen to skeletal troponin C.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
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 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".