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Record W2014641713 · doi:10.1089/cbr.2008.0461

Inhibition of Pancreatic Carcinoma Growth by Adenovirus-Mediated Human Interleukin-24 Expression in Animal Model

2008· article· en· W2014641713 on OpenAlexaff
Xinting Pan, Weihua Sheng, Qingyun Zhu, Yufeng Xie, Zhenmin Ye, Jim Xiang, Dechun Li, Jicheng Yang

Bibliographic record

VenueCancer Biotherapy and Radiopharmaceuticals · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCancer researchGenetic enhancementAngiogenesisVascular endothelial growth factorTumor suppressor geneBiologyCarcinomaPancreatic cancerPancreatic tumorPancreatic diseasePancreasPathologyMedicineCarcinogenesisEndocrinologyGeneCancerVEGF receptors

Abstract

fetched live from OpenAlex

Interleukin-24 (IL-24) has been shown to be a tumor-suppressor gene and the protein product found to be constitutively expressed by melanocytes, nerve cells, and some primary melanomas. The potential effect of adenovirus (AdV)-mediated IL-24 gene therapy was explored on human pancreatic carcinoma by using a pancreatic carcinoma cell line, patu8988. A recombinant adenovirus, AdVGFP/IL-24, expressing the marker, green fluorescent protein (GFP), and the tumor-suppressor gene, IL-24, was constructed. AdVGFP/IL-24 treatment of pancreatic carcinoma cells in vitro significantly induced pancreatic carcinoma cell cytotoxicity and apoptosis, compared with AdVGFP without IL-24 expression. In nude mice bearing patu8988 tumors, intratumoral injections of AdVGFP/IL-24 significantly inhibited pancreatic carcinoma growth. In addition, the molecular mechanism of tumor suppression was elucidated by downregulating the expression of vascular endothelial growth factor, CD34, and Bcl-2, as well as inhibiting tumor angiogenesis. Therefore, AdVGFP/IL-24 has the potential to serve as a novel tool for pancreatic carcinoma gene therapy.

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 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 score0.007
Threshold uncertainty score0.797

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 head0.039
GPT teacher head0.347
Teacher spread0.307 · 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.

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

Citations15
Published2008
Admission routes1
Has abstractyes

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