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Record W2135736160 · doi:10.1126/scitranslmed.3003960

DNAzyme Targeting c- <i>jun</i> Suppresses Skin Cancer Growth

2012· article· en· W2135736160 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience Translational Medicine · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsDeoxyribozymec-junCancer researchCancerMedicineBiologyInternal medicineGeneticsDNAGeneTranscription factor

Abstract

fetched live from OpenAlex

Worldwide, one in three cancers is skin-related, with increasing incidence in many populations. Here, we demonstrate the capacity of a DNAzyme-targeting c-jun mRNA, Dz13, to inhibit growth of two common skin cancer types-basal cell and squamous cell carcinomas-in a therapeutic setting with established tumors. Dz13 inhibited tumor growth in both immunodeficient and immunocompetent syngeneic mice and reduced lung nodule formation in a model of metastasis. In addition, Dz13 suppressed neovascularization in tumor-bearing mice and zebrafish and increased apoptosis of tumor cells. Dz13 inhibition of tumor growth, which required an intact catalytic domain, was due in part to the induction of tumor immunity. In a series of good laboratory practice-compliant toxicology studies in cynomolgus monkeys, minipigs, and rodents, the DNAzyme was found to be safe and well tolerated. It also did not interfere in more than 70 physiologically relevant in vitro bioassays, suggesting a reduced propensity for off-target effects. If these findings hold true in clinical trials, Dz13 may provide a safe, effective therapy for human skin cancer.

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.

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 score0.053
Threshold uncertainty score0.335

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 studies0.0000.001
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 head0.016
GPT teacher head0.299
Teacher spread0.283 · 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