Ex vivo analysis of the impact of dsRNA complexed to cationic phytoglycogen nanoparticles on the innate immune response in rainbow trout
Bibliographic record
Abstract
As aquaculture intensifies to satisfy the rising global demand for food, viral disease pressure is increasing in farmed fish. The variable efficacy of existing vaccines underscores the need for prophylactic strategies that confer broad antiviral protection. Long double-stranded RNA is a potent inducer of the type I interferon response in rainbow trout that can protect against a broad range of virus families. The current work investigates the effect of a commercially available viral dsRNA mimic, high molecular weight polyinosinic: polycytidylic acid (HMW poly I:C), complexed to a phytoglycogen nanoparticle (Nanodendrix, NDx), on primary gut sac preparations and peripheral blood leukocytes (PBLs). PBLs treated with NDx alone or HMW poly I:C + NDx induced significant increases in metabolism, which is an indicator of phagocyte proliferation and activation. The HMW poly I:C + NDx complex was able to enhance overall phagocytosis in adherent and non-adherent PBL populations while upregulating expression of the antiviral genes mx1 and vig-3 after 24hs while HMW poly I:C alone induced some phagocytosis and mx1 expression at 24h. Using a gut perfusion model, NDx suppressed vig-3 expression in the middle intestine and upregulated its expression in the distal intestine after 2hrs, while HMW poly I:C + NDx upregulated vig-3 expression in the middle intestine after 6hrs and HMW poly I:C alone had no effect. Overall, this preliminary translation of antiviral prophylactic dsRNA therapeutics to an ex vivo study of rainbow trout tissues demonstrates the potential for HMW poly I:C + NDx to be analyzed in vivo for the ability to protect rainbow trout against viral infection.
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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".