CD3<sup>bright</sup> signals on γδ T cells identify IL‐17A‐producing Vγ6Vδ1<sup>+</sup> T cells
Bibliographic record
Abstract
Interleukin-17A (IL-17A) is a pro-inflammatory cytokine that has an important role at mucosal sites in a wide range of immune responses including infection, allergy and auto-immunity. γδ T cells are recognized as IL-17 producers, but based on the level of CD3 expression, we now define the remarkable ability of a CD3(bright) γδ T-cell subset with an effector memory phenotype to rapidly produce IL-17A, but not interferon-γ. CD3(bright) γδ T cells uniformly express the canonical germline encoded Vγ6/Vδ1(+) T-cell receptor. They are widely distributed with a preferential representation in the lungs and skin are negatively impacted in the absence of retinoic acid receptor-related orphan receptor gammat expression or endogenous flora. This population responded rapidly to various stimuli in a mechanism involving IL-23 and NOD-like receptor family, pyrin domain containing 3 (NLRP3)-inflammasome-dependent IL-1β. Finally, we demonstrated that IL-17-producing CD3(bright) γδ T cells responded promptly and strongly to pneumococcal infection and during skin inflammation. Here, we propose a new way to specifically analyze IL-17-producing Vγ6/Vδ1(+) T cells based on the level of CD3 signals. Using this gating strategy, our data reinforce the crucial role of this γδ T-cell subset in respiratory and skin disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".