Human short-term repopulating stem cells are efficiently detected following intrafemoral transplantation into NOD/SCID recipients depleted of CD122+ cells
Bibliographic record
Abstract
The nonobese diabetic/severe combined immune deficiency (NOD/SCID) xenotransplantation model has emerged as a widely used assay for human hematopoietic stem cells; however, barriers still exist that limit engraftment. We previously identified a short-term SCID-repopulating cell (SRC) following direct intrafemoral injection into NOD/SCID mice, whereas others characterized similar SRCs using NOD/SCID mice depleted of natural killer (NK) cell activity. To determine the model that most efficiently detects short-term SRCs, we compared human engraftment in 6 different xenotransplantation models: NOD/SCID-beta2-microglobulin-null mice, anti-CD122 (interleukin-2 receptor beta [IL-2Rbeta])-treated or unmanipulated NOD/SCID mice, each given transplants by intravenous or intrafemoral injection. Human cell engraftment was highest in intrafemorally injected anti-CD122-treated NOD/SCID mice compared to all other groups at 2 and 6 weeks after transplantation. These modifications to the SRC assay provide improved detection of human stem cells and demonstrate that CD122+ cells provide barriers to stem cell engraftment, a finding with potential clinical relevance.
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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 | 0.000 |
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".