Inflammatory Effects of Ex Vivo Human Th17 Cells Are Suppressed by Regulatory T Cells
Bibliographic record
Abstract
Th17 cells are proinflammatory cells associated with many immune-mediated diseases. Major factors limiting the study of human Th17 cells are the lack of an accepted method for their in vitro differentiation or for isolation of a homogenous population of Th17 cells that do not cosecrete IFN-gamma. To overcome these hurdles, we established a novel method to isolate in vivo differentiated Th17 cells from peripheral blood by sorting CD161(+)CCR4(+)CCR6(+)CXCR3(-)CD4(+) T cells. The resulting cells produce high levels of IL-17 but not IFN-gamma, express high levels of retinoic acid-related orphan receptor variant 2, and maintain this phenotype upon expansion. Ex vivo Th17 cells exhibit a low cytotoxic potential and are hyporesponsive to polyclonal anti-CD3/anti-CD28 stimulation. Importantly, ex vivo Th17 cells were susceptible to suppression by both naive and memory regulatory T cells (Tregs), which inhibited production of IL-17, IL-22, and CXCL8. Moreover, Tregs suppressed the antifibrotic effects of Th17 cells in a wound-healing model. These findings provide new tools for the study of normal and pathological functions of bona fide Th17 cells in humans. They also provide new insight into the cross-talk between Th17 cells and immune and nonimmune cells, and they establish the paradigm that adoptive Treg-based therapies may effectively limit Th17-mediated inflammation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 teacher head, 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".