Infusion of<i>ex-vivo</i>expanded human TCR-αβ+ double-negative regulatory T cells delays onset of xenogeneic graft-<i>versus</i>-host disease
Bibliographic record
Abstract
Summary Despite the demonstration of potent immunosuppressive function of T cell receptor (TCR)-αβ+ double-negative regulatory T cells (DN Tregs), scarce numbers and lack of effective expansion method limit their clinical applications. Here we describe an approach that allows for ∼3500-fold ex-vivo expansion of human DN Tregs within 3 weeks with &gt; 97% purity. Ex-vivo-expanded DN Tregs suppress proliferation of polyclonally stimulated autologous T and B cells in vitro through direct cell-to-cell contact. In vivo, we demonstrate for the first time that infusion of human DN Tregs delayed an onset of xenogeneic graft-versus-host disease (GVHD) significantly in a humanized mouse model. Furthermore, preincubation of ex-vivo-expanded DN Tregs with a mechanistic target of rapamycin (mTOR) inhibitor rapamycin enhanced their immune regulatory function further. Taken together, this study demonstrates that human DN Tregs can be expanded ex vivo to therapeutic numbers. The expanded DN Tregs can suppress proliferation of T and B cells and attenuate GVHD, highlighting the potential clinical use of DN Tregs to mitigate GVHD.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".