Antiviral response elicited against avian influenza virus infection following activation of toll-like receptor (TLR)7 signaling pathway is attributable to interleukin (IL)-1β production
Bibliographic record
Abstract
OBJECTIVE: Single stranded ribonucleic acid (ssRNA) binds to toll-like receptor (TLR)7 leading to recruitment of immune cells and production of pro-inflammatory cytokines, which has been shown in mammals. In chickens, ssRNA has been shown to elicit antiviral response against infectious bursal disease virus infection. The objectives of this study were to determine the pro-inflammatory mediators that are activated downstream of TLR7 signaling pathway in avian macrophages and their roles in antiviral response against avian influenza virus (AIV) infection. RESULTS: In this study, first, we stimulated avian macrophages with the analog of ssRNA, resiquimod, and found that the ssRNA was capable of increasing nitric oxide (NO) and interleukin (IL-1β) production in avian macrophages. Second, we observed when the avian macrophages were stimulated with ssRNA, it elicits an antiviral response against AIV. Finally, we demonstrated that when we blocked the IL-1β response using IL-1 receptor antagonist (IL-1Ra) and the NO production using a selective inhibitor of inducible nitric oxide synthase (iNOS), N-([3-(aminomethyl)phenyl]methyl)ethanimidamide dihydrochloride (1400 W), the antiviral response against AIV is attributable to IL-1β production and not to the NO production. This study provides insights into the mechanisms of antiviral response mediated by ssRNA, particularly against AIV infection.
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 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".