IRAK‐4 kinase activity is required for IRAK‐4‐dependent innate and adaptive immune responses
Bibliographic record
Abstract
Interleukin-1 receptor-associated kinase (IRAK)-4 is a serine-threonine kinase that plays an important role in innate and adaptive immune responses. While the requirement of IRAK-4 kinase activity has been studied in the context of IL-1R signaling, it is not clear whether IRAK-4 requires its kinase function for all of its roles in the immune system. IRAK-4 kinase-dead knock-in (IRAK-4KD/KD) mice were generated to further elucidate whether IRAK-4 kinase activity is required for IRAK-4 to induce cytokine production. IRAK-4KD/KD mice were impaired in their ability to produce cytokines in response to in vivo challenge with lipopolysaccharide (LPS), a potent TLR4 ligand. Cytokine production was also reduced in macrophages and dendritic cells from IRAK-4KD/KD mice in response to LPS and other TLR ligands. In addition, adaptive immune responses were impaired in IRAK-4KD/KD mice. Although in vitro T cell proliferation in response to TCR activation was unaffected in IRAK-4-deficient mice, in vivo T cell responses to lymphocytic choriomeningitits virus infection were significantly impaired in IRAK-4-knockout mice or mice expressing the kinase-dead mutant of IRAK-4. Collectively, these results indicate that IRAK-4 kinase activity is required for IRAK-4-dependent signaling in innate and adaptive immunity.
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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) | 0.002 | 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".