How Does African Swine Fever Virus Evade the cGAS-STING Pathway?
Bibliographic record
Abstract
African swine fever (ASF), a highly infectious and devastating disease affecting both domestic pigs and wild boars, is caused by the African swine fever virus (ASFV). ASF has resulted in rapid global spread of the disease, leading to significant economic losses within the swine industry. A significant obstacle to the creation of safe and effective ASF vaccines is the existing knowledge gap regarding the pathogenesis of ASFV and its mechanisms of immune evasion. The cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway is a major pathway mediating type I interferon (IFN) antiviral immune response against infections by diverse classes of pathogens that contain DNA or generate DNA in their life cycles. To evade the host's innate immune response, ASFV encodes many proteins that inhibit the production of type I IFN by antagonizing the cGAS-STING signaling pathway. Multiple proteins of ASFV are involved in promoting viral replication by protein-protein interaction during ASFV infection. The protein QP383R could impair the function of cGAS. The proteins EP364R, C129R and B175L could disturb the function of cyclic guanosine monophosphate-adenosine monophosphate (cGAMP). The proteins E248R, L83L, MGF505-11L, MGF505-7R, H240R, CD2v, E184L, B175L and p17 could interfere with the function of STING. The proteins MGF360-11L, MGF505-7R, I215L, DP96R, A151R and S273R could affect the function of TANK Binding Kinase 1 (TBK1) and IκB kinase ε (IKKε). The proteins MGF360-14L, M1249L, E120R, S273R, D129L, E301R, DP96R, MGF505-7R and I226R could inhibit the function of Interferon Regulatory Factor 3 (IRF3). The proteins MGF360-12L, MGF505-7R/A528R, UBCv1 and A238L could inhibit the function of nuclear factor kappa B (NF-Κb).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".