Multiple Porcine Innate Immune Signaling Pathways Are Involved in the Anti-PEDV Response
Bibliographic record
Abstract
Porcine epidemic diarrhea virus (PEDV) has caused great damage to the global pig industry. Innate immunity plays a significant role in resisting viral infection; however, the exact role of innate immunity in the anti-PEDV response has not been fully elucidated. In this study, we observed that various porcine innate immune signaling adaptors are involved in anti-PEDV (AJ1102-like strain) activity in transfected Vero cells. Among these, TRIF and MAVS showed the strongest anti-PEDV activity. The endogenous TRIF, MAVS, and STING were selected for further examination of anti-PEDV activity. Agonist stimulation experiments showed that TRIF, MAVS, and STING signaling all have obvious anti-PEDV activity. The siRNA knockdown assay showed that TRIF, MAVS, and STING are also all involved in anti-PEDV response, and their remarkable effects on PEDV replication were confirmed in TRIF−/−, MAVS−/− and STING−/− Vero cells via the CRISPR approach. For further verification, the anti-PEDV activity of TRIF, MAVS, and STING could be reproduced in porcine IPEC-DQ cells treated with siRNAs. In summary, this study reveals that multiple pattern-recognition receptor (PRR) signaling pathways of porcine innate immunity play an important role in the anti-PEDV infection, providing new and useful antiviral knowledge for prevention and control of PEDV spreading.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".