Human Neural Stem Cells Overexpressing a Carboxylesterase Inhibit Bladder Tumor Growth
Bibliographic record
Abstract
Bladder cancer is a significant clinical and economic problem. Despite intravesical chemotherapy and immunotherapy, up to 80% of patients with non-muscle-invasive bladder cancer develop recurrent tumors, of which 20% to 30% evolve into more aggressive, potentially lethal tumors. Recently, bladder cancer cells are considered to be mediators of resistance to current therapies and therefore represent strong candidates as biologic targets. No effective chemotherapy has yet been developed for advanced bladder cancer. It is desirable that a drug can be delivered directly and specifically to bladder cancer cells. Stem cells have selective migration ability toward cancer cells, and therapeutic genes can be easily transduced into stem cells. In suicide gene therapy for cancer, stem cells carry a gene encoding a carboxylesterase (CE) enzyme that transforms an inert CPT-11 prodrug into a toxic SN-38 product, a topoisomerase 1 inhibitor. In immunodeficient mice, systemically transplanted HB1.F3.CE stem cells migrated toward the tumor implanted by the TCCSUP bladder cancer cell line, and, in combination with CPT-11, the volume of tumors was significantly reduced. These findings may contribute to the development of a new selective chemotherapeutic strategy against bladder cancer. Mol Cancer Ther; 15(6); 1201-7. ©2016 AACR.
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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) | 0.002 | 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".