Innate Immune Interleukin-1 Receptor–Associated Kinase 4 Exacerbates Viral Myocarditis by Reducing CCR5 <sup>+</sup> CD11b <sup>+</sup> Monocyte Migration and Impairing Interferon Production
Bibliographic record
Abstract
BACKGROUND: Viral myocarditis follows a fatal course in ≈30% of patients. Interleukin-1 receptor-associated kinase 4 (IRAK4), a major nodal signal transducer in innate immunity, can play a pivotal role in host inflammatory response. We sought to determine how IRAK4 modulates inflammation and outcome in a mouse model of viral myocarditis. METHODS AND RESULTS: Myocarditis was induced after intraperitoneal inoculation of coxsackievirus B3 into C57Bl/6 IRAK4-deficient mice and their littermate controls. Mortality and viral proliferation were markedly reduced in IRAK4(-/-) mice compared with their IRAK4(+/+) littermates. Disease resistance of IRAK4(-/-) mice paralleled increased amounts of protective heart-infiltrating CCR5(+) monocytes/macrophages and enhanced interferon-α and interferon-γ production 2 days after infection. Competitive bone marrow chimera demonstrated that intact IRAK4 function inhibited heart-specific migration of bone marrow-derived CCR5(+) cells. Mechanistically, lack of IRAK4 resulted in interferon regulatory factor 5 homodimerization via reduced melanoma differentiation-associated protein 5 degradation and enhanced Stat1 and Stat5 phosphorylation. Consequently, antiviral interferon-α and interferon-γ production, as well as CCR5(+) cell recruitment, increased, whereas the overall proinflammatory response was drastically reduced in the absence of IRAK4. CONCLUSIONS: Innate immunity signal transducer IRAK4 exacerbates viral myocarditis through inhibition of interferon production and reduced mobilization of protective CCR5(+) monocytes/macrophages to the heart. The combination of IRAK4 inhibitors and antiviral adjuvants may become an attractive therapeutic approach against viral myocarditis in the future.
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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 | 0.000 |
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".