Toll-Like Receptor 3 Signaling on Macrophages is Required for Survival Following Coxsackievirus B4 Infection (134.77)
Bibliographic record
Abstract
Abstract Toll-like receptor 3 (TLR3) has been proposed to play a critical role in the innate detection of viruses. However, as several reports have demonstrated that TLR3 signaling is either dispensable or even harmful following certain viral infections, the role of TLR3 in anti-viral immunity remains controversial. Here, we asked whether TLR3 is required for the immune response to coxsackievirus B4 (CB4), a common human pathogen associated with pancreatitis, myocarditis and diabetes. We demonstrate that TLR3 signaling is required for survival following CB4 infection. TLR3 deficient mice produce lower levels pro-inflammatory mediators and are unable to control viral replication resulting in severe cardiac damage and increased mortality. We further demonstrate that the MyD88-dependent signaling pathways are dispensable in the response to this RNA virus and are unable to compensate for the loss of TLR3. Finally, we demonstrate that adoptive transfer of WT macrophages is sufficient to reestablish protection in a TLR3 deficient host by reducing cardiac pathology suggesting that TLR3 signaling on macrophages is critical for survival following CB4 infection. Our results demonstrate that TLR3 is not simply part of a redundant system of viral recognition, but rather TLR3 plays an essential role in recognizing the molecular signatures associated with specific viruses including CB4. This work was supported by a CIHR grant to MSH.
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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) | 0.002 | 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".