Oxidative Stress Increases Surface Toll-Like Receptor 4 Expression in Murine Macrophages Via Ceramide Generation
Bibliographic record
Abstract
Multiorgan failure is a major cause of late mortality following trauma. Oxidative stress generated during shock/resuscitation contributes to tissue injury by priming the immune system for an exaggerated response to subsequent inflammatory stimuli, such as lipopolysaccharide (LPS). We recently reported that oxidative stress causes rapid recruitment of the LPS receptor Toll-like receptor 4 (TLR4) to membrane lipid rafts, thus increasing LPS responsiveness and cellular priming. We hypothesized that activation of Src family kinases by oxidants might contribute to these events. We utilized microscopy, flow cytometry, Western blotting, and thin-layer chromatography methods. Using hydrogen peroxide in vitro and hemorrhagic shock/resuscitation in vivo, oxidant-induced TLR4 translocation in macrophages occurred in an Src-dependent manner. Approaches supporting this conclusion included pharmacologic inhibition of the Src family kinases by PP2, Src inhibition by a molecular approach of cell transfection with Csk, and genetic inhibition of all Src kinases relevant to the monocyte/macrophage lineage in hckfgrlyn triple knockout mice. To evaluate the upstream molecules involved in Src activation, we evaluated the ability of oxidative stress to activate the bioactive lipid molecule ceramide. Oxidants induced ceramide generation in macrophages both in vitro and in vivo, an effect that appears to be due to activation of the acid sphingomyelinase. Using pharmacological approaches, ceramide was shown to be both necessary and sufficient to mediate TLR4 translocation to the plasma membrane in an Src-dependent manner. This study identifies a hierarchy of signaling molecules following oxidative stress that might represent novel targets for therapy in critical illness and organ injury.
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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) | 0.001 | 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".