A novel <scp>TLR</scp>2‐triggered signalling crosstalk synergistically intensifies <scp>TNF</scp>‐mediated <scp>IL</scp>‐6 induction
Bibliographic record
Abstract
Toll-like receptors (TLR) recognize pathogens and trigger the production of vigorous pro-inflammatory cytokines [such as tumour necrosis factor (TNF)] that induce systemic damages associated with sepsis and chronic inflammation. Cooperation between signals of TLR and TNF receptor has been demonstrated through the participation of TNF receptor 1 (TNFR) adaptors in endotoxin tolerance. Here, we identify a TLR2-mediated synergy, through a MyD88-independent crosstalk, which enhances subsequent TNF-mediated nuclear factor-kappa B activation and interleukin-6 induction. Membrane-associated adaptor MAL conduces the link between TNF receptor-associated factor 6 (TRAF6) and TNFR-associated death domain, leading to a distinctive K63-ubiquitinylated TRAF6 recruitment into TNFR complex. In summary, our results reveal a novel route of TLR signal that synergistically amplifies TNF-mediated responses, indicating an innovative target for inflammation manipulation.
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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".