Characterization in vitro and engraftment potential in vivo of human progenitor T cells generated from hematopoietic stem cells
Bibliographic record
Abstract
T-cell development follows a defined set of stage-specific differentiation steps. However, molecular and cellular events occurring at early stages of human T-cell development remain to be fully elucidated. To address this, human umbilical cord blood (UCB) hematopoietic stem cells (HSCs) were induced to differentiate to the T lineage in OP9-DL1 cocultures. A developmental program involving a sequential and temporally discrete expression of key differentiation markers was revealed. Quantitative clonal analyses demonstrated that CD34(+)CD38(-) and CD34(+)CD38(lo) subsets of UCB contain a similarly high T-lineage progenitor frequency, whereas the frequency in CD34(+)CD38(+/hi) cells was 5-fold lower. Delta-like/Notch-induced signals increased the T-cell progenitor frequency of CD34(+)CD38(-/lo) cells differentiated on OP9-DL1, and 2 distinct progenitor subsets, CD34(+)CD45RA(+)CD7(++)CD5(-)CD1a(-) (proT1) and CD34(+)CD45RA(+)CD7(++)CD5(+)CD1a(-) (proT2), were identified and their thymus engrafting capacity was examined, with proT2 cells showing a 3-fold enhanced reconstituting capacity compared with the proT1 subset. Furthermore, in vitro-generated CD34(+)CD7(++) progenitors effectively engrafted the thymus of immunodeficient mice, which was enhanced by the addition of an IL-7/IL-7 antibody complex. Taken together, the identification of T-progenitor subsets readily generated in vitro may offer important avenues to improve cellular-based immune-reconstitution approaches.
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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) | 0.001 | 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".