Invariant NKT Cell Activation Is Potentiated by Homotypic <i>trans</i>-Ly108 Interactions
Bibliographic record
Abstract
Abstract Invariant NKT (iNKT) cells are innate lymphocytes that respond to glycolipids presented by the MHC class Ib molecule CD1d and are rapidly activated to produce large quantities of cytokines and chemokines. iNKT cell development uniquely depends on interactions between double-positive thymocytes that provide key homotypic interactions between signaling lymphocyte activation molecule (SLAM) family members. However, the role of SLAM receptors in the differentiation of iNKT cell effector subsets and activation has not been explored. In this article, we show that C57BL/6 mice containing the New Zealand Black Slam locus have profound alterations in Ly108, CD150, and Ly9 expression that is associated with iNKT cell hyporesponsiveness. This loss of function was only apparent when dendritic cells and iNKT cells had a loss of SLAM receptor expression. Using small interfering RNA knockdowns and peptide-blocking strategies, we demonstrated that trans-Ly108 interactions between dendritic cells and iNKT cells are critical for robust activation. LY108 costimulation similarly increased human iNKT cell activation. Thus, in addition to its established role in iNKT cell ontogeny, Ly108 regulates iNKT cell function in mice and humans.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".