Dual Role of Lipopolysaccharide (LPS)-Binding Protein in Neutralization of LPS and Enhancement of LPS-Induced Activation of Mononuclear Cells
Bibliographic record
Abstract
The lipopolysaccharide (LPS)-binding protein (LBP) has a concentration-dependent dual role in the pathogenesis of gram-negative sepsis: low concentrations of LBP enhance the LPS-induced activation of mononuclear cells (MNC), whereas the acute-phase rise in LBP concentrations inhibits LPS-induced cellular stimulation. In stimulation experiments, we have found that LBP mediates the LPS-induced cytokine release from MNC even under serum-free conditions. In biophysical experiments we demonstrated that LBP binds and intercalates into lipid membranes, amplified by negative charges of the latter, and that intercalated LBP can mediate the CD14-independent intercalation of LPS into membranes in a lipid-specific and temperature-dependent manner. In contrast, prior complexation of LBP and LPS inhibited binding of these complexes to membranes due to different binding of LBP to LPS or phospholipids. This results in a neutralization of LPS and, therefore, to a reduced production of tumor necrosis factor by MNC. We propose that LBP is not only present as a soluble protein in the serum but may also be incorporated as a transmembrane protein in the cytoplasmic membrane of MNC and that the interaction of LPS with membrane-associated LBP may be an important step in LBP-mediated activation of MNC, whereas LBP-LPS complexation in the serum leads to a neutralization of LPS.
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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 | 0.001 | 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 | 0.000 |
| 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".