PCBP1 Deficient Pigs Hold the Potential to Inhibit CSFV Infection
Bibliographic record
Abstract
Abstract Classical swine fever virus (CSFV), pathogen of classic swine fever, has caused severe economic losses worldwide. Poly (rC)-binding protein 1 (PCBP1), interacting with N pro of CSFV, plays a vital role in CSFV growth. Here, our research is the first report to generate PCBP1 knockout pigs via gene editing technology. The PCBP1 knockout pigs exhibited normal birth weight, reproductive-performance traits, and developed normally. Viral challenge results indicated that primary cells isolated from F 0 and F 1 generation pigs could significantly reduce CSFV infection. Additional mechanism exploration further confirmed that PCBP1 KO mediated antiviral effect is related with the activation of type I interferon. Beyond showing that gene editing strategy can be used to generate PCBP1 KO pigs, our study introduces a valuable animal model for further investigating infection mechanisms of CSFV that help to develop better antiviral solution. Importance As a negative regulator in immune modulation, the effects of PCBP1 on viral replication have been found to be valuable. Here, this study was the first report to generate PCBP1 knockout pigs with normal pregnancy rate and viability. Primary cells isolated from F 0 and F 1 generation PCBP1 knockout pigs could significantly reduce CSFV infection. The PCBP1 knockout pigs could be used as a natural host models for investigating the effects of PCBP1-mediating critical interactions on viral replication and helping to develop better antiviral solution.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".