Both TRIF and IPS-1 Adaptor Proteins Contribute to the Cerebral Innate Immune Response against Herpes Simplex Virus 1 Infection
Bibliographic record
Abstract
Toll-like receptors (TLRs) and RNA helicases (RLHs) are important cell sensors involved in the immunological control of viral infections through production of type I interferon (IFN). The impact of a deficiency in the TRIF and IPS-1 adaptor proteins, respectively, implicated in TLR3 and RLH signaling pathways, was investigated during herpes simplex virus 1 (HSV-1) encephalitis. TRIF(-/-), IPS-1(-/-), and C57BL/6 wild-type (WT) mice were infected intranasally with 7.5 × 10(5) PFU of HSV-1. Mice were monitored for neurological signs and survival over 20 days. Groups of mice were sacrificed on days 3, 5, 7, 9, and 11 postinfection for determination of brain viral replication by quantitative PCR (qPCR), plaque assay, and immunohistochemistry and for alpha/beta interferon (IFN-α/β) levels and phosphorylation of interferon regulatory factors 3 and 7 (IRF-3 and -7) in brain homogenates by enzyme-linked immunosorbent assay (ELISA) and Western blotting, respectively. TRIF(-/-) and IPS-1(-/-) mice had higher mortality rates than WT mice (P = 0.02 and P = 0.09, respectively). Viral antigens were more disseminated throughout the brain, correlating with a significant increase in brain viral load for TRIF(-/-) (days 5 to 9) and IPS-1(-/-) (days 7 and 9) mice compared to results for the WT. IFN-β production was reduced in brain homogenates of TRIF(-/-) and IPS-1(-/-) mice on day 5 compared to results for the WT, whereas IFN-α levels were increased on day 7 in TRIF(-/-) mice. Phosphorylation levels of IRF-3 and IRF-7 were decreased in TRIF(-/-) and IPS-1(-/-) mice, respectively. These data suggest that both the TRIF and IPS-1 signaling pathways are important for the control of HSV replication in the brain and survival through IFN-β production.
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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 | 0.000 | 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".