Analysis of parameters that affect human hematopoietic cell outputs in mutant c-kit-immunodeficient mice
Bibliographic record
Abstract
Xenograft models are transforming our understanding of the output capabilities of primitive human hematopoietic cells in vivo . However, many variables that affect posttransplantation reconstitution dynamics remain poorly understood. Here, we show that an equivalent level of human chimerism can be regenerated from human CD34 + cord blood cells transplanted intravenously either with or without additional radiation-inactivated cells into 2- to 6-month-old NOD-Rag1 –/– -IL2Rγc –/– (NRG) mice given a more radioprotective conditioning regimen than is possible in conventionally used, repair-deficient NOD- Prkdc scid/scid - IL2Rγc –/– (NSG) hosts. Comparison of sublethally irradiated and non-irradiated NRG mice and W 41 /W 41 derivatives showed superior chimerism in the W 41 -deficient recipients, with some differential effects on different lineage outputs. Consistently superior outputs were observed in female recipients regardless of their genotype, age, or pretransplantation conditioning, with greater differences apparent later after transplantation. These results define key parameters for optimizing the sensitivity and minimizing the intraexperimental variability of human hematopoietic xenografts generated in increasingly supportive immunodeficient host mice.
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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) | 0.001 | 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".