Design of a potent CD1d-binding NKT cell ligand as a vaccine adjuvant
Bibliographic record
Abstract
The glycolipid alpha-galactosylceramide (alpha-GalCer) has been shown to bind CD1d molecules to activate invariant natural killer T (iNKT) cells, and subsequently induce activation of various immune-competent cells, including dendritic cells, thereby providing a significant adjuvant effect for various vaccines. However, in phase I clinical trials, alpha-GalCer was shown to display only marginal biological activity. In our search for a glycolipid that can exert more potent stimulatory activity against iNKT cells and dendritic cells and produce an adjuvant effect superior to alpha-GalCer, we performed step-wise screening assays on a focused library of 25 alpha-GalCer analogues. Assays included quantification of the magnitude of stimulatory activity against human iNKT cells in vitro, binding affinity to human and murine CD1d molecules, and binding affinity to the invariant t cell receptor of human iNKT cells. Through this rigorous and iterative screening process, we have identified a lead candidate glycolipid, 7DW8-5, that exhibits a superior adjuvant effect than alpha-GalCer on HIV and malaria vaccines in mice.
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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".