Fas (CD95) induces rapid, TLR4/IRAK4-dependent release of pro-inflammatory HMGB1 from macrophages
Bibliographic record
Abstract
Although Fas (CD95) is recognized as a death receptor that induces apoptosis, recent studies indicate that the Fas/FasL system can induce pro-inflammatory cytokine production by macrophages independent of conventional caspase-mediated apoptotic signaling. The precise mechanism(s) by which Fas activates macrophage inflammation is unknown. We hypothesized that Fas stimulates rapid release of high mobility group box 1 (HMGB1) that acts in an autocrine and/or paracrine manner to stimulate pro-inflammatory cytokine production via a Toll-like receptor-4 (TLR4)/Interleukin-1 receptor associated kinase-4 (IRAK4)-dependent mechanism. Following Fas activation, HMGB1 was released within 1 hr from viable RAW267.4 cells and primary murine peritoneal macrophages. HMGB1 release was more rapid following Fas activation compared to LPS stimulation. Neutralization of HMGB1 with an inhibitory anti-HMGB1 monoclonal antibody strongly inhibited Fas-induced production of tumor necrosis factor (TNF) and macrophage inflammatory protein-2 (MIP-2). Both Fas-induced HMGB1 release and associated pro-inflammatory cytokine production were significantly decreased from Tlr4-/- and Irak4-/- macrophages, but not Tlr2-/- macrophages. These findings reveal a novel mechanism underlying Fas-mediated pro-inflammatory physiological responses in macrophages. We conclude that Fas activation induces rapid, TLR4/IRAK4-dependent release of HMGB1 that contributes to Fas-mediated pro-inflammatory cytokine production by viable macrophages.
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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 | 0.000 |
| 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".