An in vitro study of type I interferon and inflammatory markers induced by dsRNA and dsRNA-phytoglycogen in rainbow trout
Bibliographic record
Abstract
Understanding the induction patterns for rainbow trout type I interferon and inflammatory markers is essential for the development of new antipathogenic therapeutics and vaccines as well as enhancing aquaculture productivity and biosecurity. Type I interferons (ex. ifn1) and interferon stimulated genes (ex. vig-3) as well as inflammatory markers such as interferon gamma (ifn-γ) and interleukin 1beta (il-1β) all play a crucial role in protecting rainbow trout against pathogen infection. One strategy to better understand how fish defend themselves is by studying the effects of synthetic viral dsRNA analogues such as polyinosinic:polycytidylic acid (poly IC) on the fish innate immune response. The current work utilizes a phytoglycogen-based nanoparticle (Nanodendrix; NDx) to enhance the immunostimulatory effects of poly IC in three rainbow trout cell lines derived from monocyte/macrophages (RTS11), gonads (RTG-2) and gill (RTgill-W1). Variations in innate immune responses were observed between cell lines, between poly IC and poly IC + NDx treatment groups and between transcript, protein and antiviral response levels of study. The poly IC + NDx complex demonstrated prolonged immune stimulation up to 96h post-treatment and exhibited significant inhibition of infectious pancreatic necrosis virus (IPNV) replication. These findings highlight the potential of poly IC + NDx complexes as a novel antiviral therapeutic approach for future in vitro and in vivo studies.
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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) | 0.001 | 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".