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Record W2310704577 · doi:10.1158/1535-7163.mct-15-0636

Human Neural Stem Cells Overexpressing a Carboxylesterase Inhibit Bladder Tumor Growth

2016· article· en· W2310704577 on OpenAlexaff
Sung Sik Choi, Byung Hoon, In Ho Chang, Kyung Do Kim, Sang‐Rae Lee, Seung Up Kim, Hong J. Lee

Bibliographic record

VenueMolecular Cancer Therapeutics · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer, Stress, Anesthesia, and Immune Response
Canadian institutionsUniversity of British Columbia Hospital
FundersKorea Research Institute of Bioscience and Biotechnology
KeywordsBladder cancerCancer researchSuicide geneCancer stem cellCancerStem cellCancer cellMedicineChemotherapyGenetic enhancementImmunotherapyBiologyInternal medicineGeneCell biology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.278
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2016
Admission routes1
Has abstractyes

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