Synthesis and immunostimulatory activity of diethanolamine-containing lipid A mimics
Bibliographic record
Abstract
Toll-like receptor (TLR) 4 plays important roles in the innate immunity and the development of adaptive immune responses. TLR4 ligands that can modulate the TLR4-mediated signalling pathways therefore have great potential for therapeutic applications. In this paper, we describe the synthesis of three lipid A mimics (2–4) as potential TLR4 ligands, in which a diethanolamine moiety is employed to replace the reducing end (D-glucosamine) of the archetypical lipid A disaccharide structure. Biological studies indicate that the lipid A mimic with six acyl chains (2) exhibits potent immune stimulatory activity in that it induces a significant increase in the ICAM-1 expression of human pre-monocytic THP-1 cells, as well as significant production of the cytokines TNF-α, IL-6, and IL-1β. The mimic with eight acyl chains (3) is inactive towards both the induction of ICAM-1 expression, and the cytokines TNF-α, and IL-6, yet induces significant production of IL-1β when tested at higher concentration. Finally, the lipid A mimic 4, a derivative of 2, that contains an additional 1-hydroxybutyl group as a result of an unexpected ring opening reaction of a tetrahydrofuran molecule, is active in all respects tested, albeit with reduced potency. These data suggest that diethanolamine-containing lipid A mimics can be potent immune stimulating agents.
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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".