IFN-γ+ cytotoxic CD4+ T lymphocytes are involved in the pathogenesis of colitis induced by IL-23 and the food colorant Red 40
Bibliographic record
Abstract
Abstract The food colorant Red 40 is an environmental risk factor for colitis development in mice with increased expression of interleukin (IL)-23. This immune response is mediated by CD4+ T cells, but mechanistic insights into how these CD4+ T cells trigger and perpetuate colitis have remained elusive. Here, using single-cell transcriptomic analysis, we found that several CD4+ T-cell subsets are present in the intestines of colitic mice, including an interferon (IFN)-γ-producing subset. In vivo challenge of primed mice with Red 40 promoted rapid activation of CD4+ T cells and caused marked intestinal epithelial cell (IEC) apoptosis that was attenuated by depletion of CD4+ cells and blockade of IFN-γ. Ex vivo experiments showed that intestinal CD4+ T cells from colitic mice directly promoted apoptosis of IECs and intestinal enteroids. CD4+ T cell-mediated cytotoxicity was contact-dependent and required FasL, which promoted caspase-dependent cell death in target IECs. Genetic ablation of IFN-γ constrained IL-23- and Red 40-induced colitis development, and blockade of IFN-γ inhibited epithelial cell death in vivo. These results advance the understanding of the mechanisms regulating colitis development caused by IL-23 and food colorants and identify IFN-γ+ cytotoxic CD4+ T cells as a new potential therapeutic target for colitis.
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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 | 0.001 |
| 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".