IL-17A produced by invariant natural killer T cells and CD3+CD56+αGalcer-CD1d tetramer– T cells promote liver fibrosis in patients with primary biliary cholangitis
Bibliographic record
Abstract
Abstract Primary biliary cholangitis (PBC) is characterized as interlobular bile duct injury and fibrosis, which results from the loss of tolerance to self-antigens. However, the exact pathologic mechanism leading to injury and fibrosis in PBC patients is not fully understood. Therefore, in this study, we examined the role of the T cell subsets in PBC patients and healthy controls (HCs). A higher number of invariant Natual killer T (iNKT) cells as well as CD3+CD56+ αGalcer-CD1d tetramer– T cells were found in patients with PBC compared with HCs. Moreover, these 2 T subpopulations produced significantly higher levels of Interleukin (IL)-17A in PBC patients than those in in HCs, which has also been positively correlated with the disease severity. Furthermore, the level of IL-17A produced by these 2 subpopulations was increased after stimulation of the autoantibodies in patients with PBC. Also, the elevated IL-17A levels promoted the PBC-related fibrosis, thus presenting a change in frequencies and functions of these cell phenotypes in the deterioration of the duct damage-related fibrosis. This study clarified PBC patients’ distinct T subpopulations characteristics, providing evidence-based diagnostic and therapies for these patients. The correlation between unclassical T subsets and IL-17A may provide a novel target for the immunotherapy of PBC.
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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) | 0.002 | 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".