Previously undetected human hematopoietic cell populations with short-term repopulating activity selectively engraft NOD/SCID-β2 microglobulin–null mice
Bibliographic record
Abstract
Increasing use of purified or cultured human hematopoietic cells as transplants has revealed an urgent need for better methods to predict the speed and durability of their engraftment potential. We now show that NOD/SCID-beta2 microglobulin-null (NOD/SCID-beta2m-/-) mice are sequentially engrafted by two distinct and previously unrecognized populations of transplantable human short-term repopulating hematopoietic cells (STRCs), neither of which efficiently engraft NOD/SCID mice. One is predominantly CD34+CD38+ and is myeloid-restricted; the other is predominantly CD34+CD38- and has broader lymphomyeloid differentiation potential. In contrast, the long-term repopulating human cells that generate lymphoid and myeloid progeny in NOD/SCID mice engraft and self-renew in NOD/SCID-beta2m-/- mice equally efficiently. In short-term expansion cultures of adult bone marrow cells, myeloid-restricted STRCs were preferentially amplified (greater than tenfold) and, interestingly, both types of STRC were found to be selectively elevated in mobilized peripheral blood harvests. These results suggest an enhanced sensitivity of STRCs to natural killer cell-mediated rejection. They also provide new in vivo assays for different types of human STRC that may help to predict the engraftment potential of clinical transplants and facilitate future investigation of early stages of human hematopoietic stem cell differentiation.
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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 | 0.001 |
| 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".