Lipopolysaccharide Binds Platelet Toll-Like Receptor 4 and Mediates the Activation of Phagocytes in the Reticuloendothelial System (RES): A Novel Mechanism of Host Immunity.
Bibliographic record
Abstract
Abstract Toll-like receptors (TLR) comprise a family of transmembrane proteins characterized by multiple copies of leucine-rich repeats in the extracellular domain and an IL-1 receptor motif in their cytoplasmic domain. The TLR family is a phylogenetically conserved mediator of innate immunity that is essential for microbial recognition and the stimulation of adaptive immune responses. Recently, our laboratory demonstrated that TLR4 expression on platelets was responsible for lipopolysaccharide (LPS)-mediated thrombocytopenia and tumour necrosis factor-α production in vivo (Aslam et al. Blood107:637, 2006). To understand the mechanism of how platelet TLR4 may mediate RES activation, platelets from wild type (WT) and TLR4 knockout mice were incubated with various concentrations of LPS in vitro, washed extensively and transfused into WT mice. Results suggest that only the WT platelets could significantly stimulate TNF-α production in vivo. In vitro flow cytometric analysis of phagocytosis by the monocytic cell line THP-1 demonstrated that platelet TLR4 could efficiently present LPS to THP-1 cells and stimulated them to engulf the LPS-coated platelets. The phagocytosis of the platelets was correlated to elevated levels of intracellular TNF-α production in the THP-1 cells. These results suggest that platelets, via TLR4 expression, can act as initial sentinels of the innate immune system by presenting bacterial products such as LPS to phagocytes of the RES.
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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 | 0.001 |
| Research integrity | 0.001 | 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".