Model Characterization: Total Body Irradiation or Busulfan for Conditioning in Human Cell Therapy Toxicology and Tumorigenicity Studies using NOD/SCID/IL2Rγnull (NSG) Mice
Bibliographic record
Abstract
The NOD/SCID/IL2Rγnull (NSG) mouse is a relevant model for toxicology and tumorigenicity studies evaluating human cell therapies. Data was compiled from toxicology study control NSG mice exposed to gamma irradiation (0 or 200 cGy) or busulfan. Retrospective data evaluation included mortality, clinical observations, body weights, hematology, and external and internal macroscopic observations. There was no mortality in any of the 129 toxicology control (irradiated and non-irradiated) mice up to the 20-week observation period. Mortalities occurred between Days 1 and 25 among animals given busulfan ≥25 mg/kg/day at 1 or 2 doses via intraperitoneal (i.p.) injection. There were 4/10, 6/10 and 4/10 deaths at 25, 30 and 35 mg/kg/day busulfan, respectively. Busulfan-treated mice presented with dose-dependent clinical signs including signs of anemia in some individuals. Hematology, including white blood cell (WBC) and neutrophil (NEUT) counts, from irradiated mice at Weeks 12 and 20 revealed comparable values to non-irradiated animals. In contrast, irradiated mice treated with a positive control (HL-60) were euthanized prior to Week 12. There were no irradiation-related differences in macroscopic observations with lymphoid atrophy identified comparably in irradiated and non-irradiated groups. These results suggest that irradiation was suitable for conditioning to enable cell engraftment in NSG mice in the context of regulatory toxicology and tumorigenicity studies. Busulfan administered at 20 mg/kg/day for 2 days, i.p. was also well-tolerated, and it could be considered for toxicology studies of genetically modified human cells.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".