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Record W2049639704 · doi:10.1159/000353854

Vaccinia Virus Outperforms a Panel of Other Poxviruses as a Potent Oncolytic Agent for the Control of Head and Neck Squamous Cell Carcinoma Cell Lines

2013· article· en· W2049639704 on OpenAlexaff
Anthony C. Nichols, John Yoo, Sung Um, Neil Mundi, David A. Palma, Kevin Fung, S. Danielle MacNeil, James Koropatnick, Joe S. Mymryk, John W. Barrett

Bibliographic record

VenueIntervirology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsOncolytic virusVacciniaCancer researchHead and neck squamous-cell carcinomaVirusVirologyMyxoma virusMedicineCancerBiologyHead and neck cancerInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is the fifth most common cancer worldwide. Existing therapies for advanced tumors have high failure rates and can have severe consequences in terms of pain, disfigurement, and poor speech and swallowing function. New treatment strategies are needed to improve outcomes for patients suffering with this disease and oncolytic viruses represent a promising approach. METHODS: We infected six well-characterized HNSCC cell lines (Cal27, Detroit562, FaDu, SCC4, SCC15, SCC25), with increasing doses of a panel of poxviruses (including myxoma, vaccinia, raccoonpox and tanapox viruses) modified to express green fluorescence protein to determine which virus was the most effective oncolytic agent in cell-based assays. RESULTS: While myxoma, raccoonpox and tanapox displayed differing efficacy in the panel of cell lines, vaccinia virus was the most potent of the tested poxviruses and was highly effective in controlling cell growth in all cell lines. CONCLUSION: Oncolytic poxviruses, particularly vaccinia virus, were effective in killing HNSCC in vitro and hold promise as potential treatments for patients with HNSCC.

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 score0.018
Threshold uncertainty score0.567

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 head0.027
GPT teacher head0.290
Teacher spread0.263 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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