uPA+/+-SCID Mouse with Humanized Liver as a Model for In Vivo Metabolism of Exogenous Steroids: Methandienone as a Case Study
Bibliographic record
Abstract
BACKGROUND: Adequate detection of designer steroids in the urine of athletes is still a challenge in doping control analysis and requires knowledge of steroid metabolism. In this study we investigated whether uPA(+/+)-SCID mice carrying functional primary human hepatocytes in their liver would provide a suitable alternative small animal model for the investigation of human steroid metabolism in vivo. METHODS: A quantitative method based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed and validated for the urinary detection of 7 known methandienone metabolites. Application of this method to urine samples from humanized mice after methandienone administration allowed for comparison with data from in vivo human samples and with reported methandienone data from in vitro hepatocyte cultures. RESULTS: The LC-MS/MS method validation in mouse and human urine indicated good linearity, precision, and recovery. Using this method we quantified 6 of 7 known human methandienone metabolites in the urine of chimeric mice, whereas in control nonchimeric mice we detected only 2 metabolites. These results correlated very well with methandienone metabolism in humans. In addition, we detected 4 isomers of methandienone metabolites in both human and chimeric mouse urine. One of these isomers has never been reported before. CONCLUSIONS: The results of this proof-of-concept study indicate that the human liver-uPA(+/+)-SCID mouse appears to be a suitable small animal model for the investigation of human-type metabolism of anabolic steroids and possibly also for other types of drugs and medications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".