MASTR: A Technique for Mosaic Mutant Analysis with Spatial and Temporal Control of Recombination Using Conditional Floxed Alleles in Mice
Why this work is in the frame
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Bibliographic record
Abstract
Mosaic mutant analysis, the study of cellular defects in scattered mutant cells in a wild-type environment, is a powerful approach for identifying critical functions of genes and has been applied extensively to invertebrate model organisms. A highly versatile technique has been developed in mouse: MASTR (mosaic mutant analysis with spatial and temporal control of recombination), which utilizes the increasing number of floxed alleles and simultaneously combines conditional gene mutagenesis and cell marking for fate analysis. A targeted allele (R26(MASTR)) was engineered; the allele expresses a GFPcre fusion protein following FLP-mediated recombination, which serves the dual function of deleting floxed alleles and marking mutant cells with GFP. Within 24 hr of tamoxifen administration to R26(MASTR) mice carrying an inducible FlpoER transgene and a floxed allele, nearly all GFP-expressing cells have a mutant allele. The fate of single cells lacking FGF8 or SHH signaling in the developing hindbrain was analyzed using MASTR, and it was revealed that there is only a short time window when neural progenitors require FGFR1 for viability and that granule cell precursors differentiate rapidly when SMO is lost. MASTR is a powerful tool that provides cell-type-specific (spatial) and temporal marking of mosaic mutant cells and is broadly applicable to developmental, cancer, and adult stem cell studies.
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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 | 0.000 | 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) | 0.000 | 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 it