An α-galactosylceramide C20:2 N-acyl variant enhances anti-inflammatory and regulatory T cell-independent responses that prevent type 1 diabetes
Bibliographic record
Abstract
Protection from type 1 diabetes (T1D), a T helper type 1 (Th1)-mediated disease, is achievable in non-obese diabetic (NOD) mice by treatment with alpha-galactosylceramide (alpha-GalCer) glycolipids that stimulate CD1d-restricted invariant natural killer T (iNK T) cells. While we have reported previously that the C20:2 N-acyl variant of alpha-GalCer elicits a Th2-biased cytokine response and protects NOD mice from T1D more effectively than a form of alpha-GalCer that induces mixed Th1 and Th2 responses, it remained to determine whether this protection is accompanied by heightened anti-inflammatory responses. We show that treatment of NOD mice with C20:2 diminished the activation of 'inflammatory' interleukin (IL)-12 producing CD11c(high)CD8+ myeloid dendritic cells (mDCs) and augmented the function of 'tolerogenic' DCs more effectively than treatment with the prototypical iNKT cell activator KRN7000 (alpha-GalCer C26:0) that induces Th1- and Th2-type responses. These findings correlate with a reduced capacity of C20:2 to sustain the early transactivation of T, B and NK cells. They may also explain our observation that C20:2 activated iNK T cells depend less than KRN7000 activated iNK T cells upon regulation by regulatory T cells for cytokine secretion and protection from T1D. The enhanced anti-inflammatory properties of C20:2 relative to KRN7000 suggest that C20:2 should be evaluated further as a drug to induce iNK T cell-mediated protection from T1D in 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) | 0.001 | 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".