VSVΔG MARV GP and VSVΔG ZEBOV GP induce strong and rapid anti-viral state in mouse peritoneal macrophages through type I interferon stimulation (128.11)
Bibliographic record
Abstract
Abstract Replacement of Vesicular Stomatitis Virus (VSV) G protein with the Marburg (MARV) and Ebola (ZEBOV) viruses’ glycoproteins (GP) led to the most effective experimental post-exposure therapeutics available against filoviruses. We hypothesize that the therapeutic effect is partly dependent on activation of innate immune mechanisms, as animals die before the adaptive immune response is activated. Macrophages are primary target cells of MARV, ZEBOV and the recombinant VSVs. Thus, we investigated the innate anti-viral mechanisms that are activated in J774A.1 murine macrophages by VSVΔG MARV GP and VSVΔG ZEBOV GP. The infections result in rapid induction of anti-viral state, as measured by resistance to challenge with a high MOI of a VSV expressing GFP. There is a significant induction of anti-viral state by 6 hours post-infection and by 24 hours post-infection the cells are almost completely resistant to subsequent infections, which correlates with phosphorylation of IRF-3 and IFN-α and IFN-β production. Blockage of the IFN-α/β Receptor, neutralizes 70%-90% of the anti-viral effects suggesting that the anti-viral state induced after VSVΔG MARV GP or VSVΔG ZEBOV GP infections are type I interferon-dependent. In conclusion, the post-exposure protection may be dependent on type I interferon induction and subsequent activation of anti-viral pathways, which may inhibit filovirus replication in target cells.
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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) | 0.000 | 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 | 0.001 |
| 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".