Differential roles of human CD4+ and CD8+ regulatory T cells in controlling self-reactive immune responses
Bibliographic record
Abstract
Abstract Here we analyzed the relative contributions of CD4 + regulatory T cells expressing Forkhead box protein P3 (FOXP3) and CD8 + regulatory T cells expressing killer cell immunoglobulin-like receptors to the control of autoreactive T and B lymphocytes in human tonsil-derived immune organoids. FOXP3 and GZMB respectively encode proteins FOXP3 and granzyme B, which are critical to the suppressive functions of CD4 + and CD8 + regulatory T cells. Using CRISPR–Cas9 gene editing, we were able to achieve a reduction of ~90–95% in the expression of these genes. FOXP3 knockout in tonsil T cells led to production of antibodies against a variety of autoantigens and increased the affinity of influenza-specific antibodies. By contrast, GZMB knockout resulted in an increase in follicular helper T cells, consistent with the ablation of CD8 + regulatory T cells observed in mouse models, and a marked expansion of autoreactive CD8 + and CD4 + T cells. These findings highlight the distinct yet complementary roles of CD8 + and CD4 + regulatory T cells in regulating cellular and humoral responses to prevent autoimmunity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".