TLR9-mediated dendritic cell activation uncovers mammalian ganglioside species with specific ceramide backbones that activate invariant natural killer T cells
Bibliographic record
Abstract
CD1d-restricted invariant natural killer T (iNKT) cells represent a heterogeneous population of lipid-reactive T cells that are involved in many immune responses, mediated through T-cell receptor (TCR)-dependent and/or independent activation. Although numerous microbial lipid antigens (Ags) have been identified, several lines of evidence have suggested the existence of relevant Ags of endogenous origin. However, the identification of their precise nature as well as the molecular mechanisms involved in their generation are still highly controversial and ill defined. Here, we identified two mammalian gangliosides-namely monosialoganglioside GM3 and disialoganglioside GD3-as endogenous activators for mouse iNKT cells. These glycosphingolipids are found in Toll-like receptor-stimulated dendritic cells (DC) as several species varying in their N-acyl fatty chain composition. Interestingly, their ability to activate iNKT cells is highly dependent on the ceramide backbone structure. Thus, both synthetic GM3 and GD3 comprising a d18:1-C24:1 ceramide backbone were able to activate iNKT cells in a CD1d-dependent manner. GM3 and GD3 are not directly recognized by the iNKT TCR and required the Ag presenting cell intracellular machinery to reveal their antigenicity. We propose a new concept in which iNKT cells can rapidly respond to pre-existing self-molecules after stress-induced structural changes in CD1d-expressing cells. Moreover, these gangliosides conferred partial protection in the context of bacterial infection. Thus, this report identified new biologically relevant lipid self-Ags for iNKT cells.
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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".