Tunable differentiation of human CD4+ and CD8+ T cells from pluripotent stem cells
Bibliographic record
Abstract
Allogeneic T cell therapies are a highly desirable option to circumvent the cost and complexity of using autologous T cells to treat diseases. Allogeneic CD8+ T cells can be made from pluripotent stem cells (PSCs), but deriving CD4+ T cells from PSCs remained a significant challenge. Using feeder- and serum-free conditions, we found that CD4+ versus CD8+ T cell commitment from PSCs can be controlled by fine-tuning the dynamics of Notch and T cell receptor signaling delivered to CD4+CD8+ double positive T cells. Notch signaling negatively impacts CD4+ T cell commitment, and its timed removal allows generation of clonally-diverse and expandable CD4+ T cells from PSCs. The resulting CD4+ T cells respond to cytokine-mediated polarization by differentiating into Th1, Th2, or Th17 cells, recapitulating canonical helper cell function. These findings represent a significant step towards using PSC-derived CD4+ T cells as a low cost, off-the-shelf, cell therapy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".