Bacterial endotoxin stimulates macrophages to release HMGB1 partly through CD14- and TNF-dependent mechanisms
Bibliographic record
Abstract
Bacterial endotoxin [lipopolysaccharide (LPS)] stimulates macrophages to sequentially release early [tumor necrosis factor (TNF)] and late [high mobility group box 1 (HMGB1)] proinflammatory cytokines. The requirement of CD14 and mitogen-activated protein kinases [MAPK; e.g., p38 and extracellular signal-regulated kinase (ERK)1/2] for endotoxin-induced TNF production has been demonstrated previously, but little is known about their involvement in endotoxin-mediated HMGB1 release. Here, we demonstrated that genetic disruption of CD14 expression abrogated LPS-induced TNF production but only partially attenuated LPS-induced HMGB1 release in cultures of primary murine peritoneal macrophages. Pharmacological suppression of p38 or ERK1/2 MAPK with specific inhibitors (SB203580, SB202190, U0126, or PD98059) significantly attenuated LPS-induced TNF production but failed to inhibit LPS-induced HMGB1 release. Consistently, an endogenous, immunosuppressive molecule, spermine, failed to inhibit LPS-induced activation of p38 MAPK and yet, still significantly attenuated LPS-mediated HMGB1 release. Direct suppression of TNF activity with neutralizing antibodies or genetic disruption of TNF expression partially attenuated HMGB1 release from macrophages induced by LPS at lower concentrations (e.g., 10 ng/ml). Taken together, these data suggest that LPS stimulates macrophages to release HMGB1 partly through CD14- and TNF-dependent mechanisms.
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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 | 0.001 |
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".