Denaturing Gradient Gel Electrophoresis (DGGE) as a Powerful Novel Alternative for Differentiation of Epizootic ISA Virus Variants
Bibliographic record
Abstract
Infectious Salmon Anemia is a devastating disease critically affecting world-wide salmon production. Chile has been particularly stricken by this disease which in all cases has been directly related with its causative agent, a novel orthomyxovirus which presents specific and distinctive infective features. Among these, two molecular markers have been directly associated with pathogenicity in two of the eight RNA sub genomic coding units of the virus: an insertion hot spot region present in viral segment 5 and a Highly Polymorphic Region (HPR) located in viral segment 6. Here we report the successful adaptation of a PCR-dependent denaturing gel electrophoresis technique (DGGE), which enables differentiation of selected reported HPR epizootic variants detected in Chile. At the same time, the technique allows us to distinguish one nucleotide differences in sequences associated with the intriguing, and still not well-understood, insertion events which tend to occur on RNA Segment 5. Thus, the versatility of the technique opens new opportunities for improved understanding of the complex biology of all ISA variants as well as possible applications to other highly variable pathogens.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".