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Record W2016693473 · doi:10.1016/j.ymthe.2006.08.029

18. Comparison of Antitumor Activity of Cytosine Deaminase::Uracil Phosphoribosyl Transferase (CD::UPRT) and Purine Nucleoside Phosphorylase (PNP) Suicide Genes Using Replicative but Non-Disseminative Adenovirus Vectors

2006· article· en· W2016693473 on OpenAlexaff
Jaïro Jaime, Nadine Jabbour, William B. Parker, Eric J. Sorscher, Joséphine Nalbantoglu, Bernard Massie

Bibliographic record

VenueMolecular Therapy · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsUniversité de MontréalInstitut National de la Recherche ScientifiqueUniversité du Québec à MontréalMcGill UniversityMontreal Neurological Institute and HospitalBiotechnology Research Institute
Fundersnot available
KeywordsCytosine deaminaseSuicide geneBiologyExpression cassetteOncolytic virusOncolytic adenovirusViral vectorGeneGenetic enhancementVirologyMolecular biologyInternal ribosome entry siteAdenoviridaeVector (molecular biology)VirusGeneticsRNARecombinant DNA

Abstract

fetched live from OpenAlex

Cancer gene therapy using suicide genes has shown great potential in tumor models. To improve efficacy, recent attention has focused on the use of oncolytic vectors. To date this strategy has not resulted in vectors with anti-tumor activities sufficiently potent to sustain complete tumor regression. In this study, we pursued a modified approach that makes use of viral DNA replication but not of oncolysis. This approach is based on the protease-deleted adenovirus vector (AdV) (Oualikene et al. 2000).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.328
Teacher spread0.302 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2006
Admission routes1
Has abstractyes

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