The Total Synthesis of Proposed Immunoactive Glycolipids from S. Pneumoniae and a Re-evaluation of Their Immunological Activity
Bibliographic record
Abstract
Invariant natural killer T cells (iNKT), a subclass of white blood cells, are responsible for the production of pro-inflammatory cytokines which induce a systemic immune response. They are distinctive in having an invariant T-cell receptor that recognizes glycolipid antigens presented by the class I major histocompatibility complex-related protein CD1d, which is conserved across multiple mammalian species in a class of proteins well-renowned for their high degree of polymorphism. This receptor’s first identified antigen is the potent KRN7000, a glycosphingolipid isolated from bacteria that were found on a Japanese marine sponge. The corresponding terrestrial antigen remained unidentified until quite recently, when diacylglycerol-containing glycolipids, reported to activate iNKT cells, were isolated from Streptococcus pneumoniae . We report the total synthesis and immunological re-evaluation of these two glycolipids. The compounds are unable to activate iNKT cells. Computational modelling shows that these ligands, while being capable of interacting with the CD1d receptor, create a different surface for the binary complex that makes formation of the ternary complex with the iNKT T-cell receptor difficult. Together these results suggest that the reported activity might have been due to an impurity in the original isolated sample, and highlights the importance of taking care when reporting biological activity from isolated natural products.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".