Reprogramming Mouse Glioma Stem Cells with Defined Factors
Bibliographic record
Abstract
This thesis shows that p53-deficient mouse glioma brain tumour stem cells (BTSCs), which fail to express pluripotency factors, can be reprogrammed with specific transcription factors to generate iPS cell lines (GNS-iPS) expressing endogenous pluripotency factors (Nanog, Oct4, and Rex1). GNS-iPS cell lines formed embryoid bodies (EBs) in vitro and undifferentiated growths in vivo that phenotypically did not resemble tumours derived from non-reprogrammed BTSCs. EBs formed from one GNS-iPS cell line expressed markers of mesoderm, endoderm, and ectoderm. Tumours produced from GNS-iPS cells had reduced astrocytic marker (GFAP) expression compared to those generated from control iPS cell lines or non-reprogrammed BTSCs. Preliminary results suggest that the reprogrammed cells can be re-differentiated into cells that show neural precursor phenotype. These findings suggest that BTSCs can acquire aspects of the pluripotent state with a defined set of transcription factors, opening the door for further exploration of reprogramming strategies to attenuate the cancer phenotype.
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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) | 0.001 | 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".