Deactivation of the lipopolysaccharide antagonist eritoran (E5564) by high-density lipoprotein-associated apolipoproteins
Bibliographic record
Abstract
Lipid A, the active moiety of LPS, exerts its effects through interaction with TLR4, triggering a signalling cascade that results in the release of pro-inflammatory cytokines. Eritoran is a lipid A analogue that competes with LPS for binding to TLR4; however, after intravenous administration, it undergoes a time-dependent deactivation as a consequence of binding to high-density lipoproteins (HDLs). The site of eritoran association with HDL remains unknown. Therefore the aim of this study was to determine if HDL-associated apolipoproteins A1, A2, serum amyloid A (SAA) and C1, inhibit the ability of eritoran to block LPS-induced TNF-α release from whole blood. Eritoran activity after LPS stimulation in human whole blood was assessed in the presence of reconstituted HDL (rHDL) containing different apos. In rHDL, the major apolipoproteins in both the healthy and septic state, A1 and SAA, caused a significant reduction in eritoran antagonistic activity and had a greater effect than minor apolipoproteins A2 and C1. Apolipoproteins associated with HDL are likely to facilitate eritoran deactivation. Apolipoproteins A1 and SAA should be of particular focus as they are the major apos found on HDL in both the healthy and septic state. Further evaluation of the physical association between apolipoproteins and eritoran should be explored.
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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".