Acidification‐dependent activation of CD1d‐restricted natural killer T cells is intact in cystic fibrosis
Bibliographic record
Abstract
CD1d-restricted natural killer T (NKT) cells are emerging as critical regulators of the immune response to infectious agents, including Pseudomonas aeruginosa; and therapies to augment NKT-cell activation may represent a novel approach to treat chronic, antibiotic-resistant bacterial infections. We examined the capacity of dendritic cells (DCs) from people with cystic fibrosis (CF) to activate NKT cells. Our study was motivated by three lines of evidence: (i) NKT cells play a critical role in clearing P. aeruginosa infection; (ii) activation of NKT cells requires acidification-dependent processing of glycolipid antigens within the endolysosomal compartment; and (iii) endolysosomal acidification may be reduced in CF. We demonstrated that NKT-cell activation was dependent upon intact organelle acidification as inhibitors of the vacuolar (H(+))-ATPases prevented DCs from activating NKT cells with two glycolipid antigens, alpha-galactosylceramide and galactose-galactosylceramide. In contrast, cystic fibrosis transmembrane conductance regulator (CFTR) chloride channel dysfunction had no significant biological impact on the capacity of DCs to activate NKT cells. Dendritic cells from subjects with CF and DCs treated with the thiazolidinone CFTR(inh)-172 inhibitor showed no reduction in their ability to activate NKT cells. Based on these data, we find no evidence for an inherent defect in glycolipid antigen presentation to NKT cells in CF subjects.
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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 | 0.001 |
| 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) | 0.002 | 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".