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Record W2032466740 · doi:10.1155/2011/632948

Oncolytic Virotherapy for Multiple Myeloma: Past, Present, and Future

2011· article· en· W2032466740 on OpenAlexaff
Chandini M. Thirukkumaran, Don Morris

Bibliographic record

VenueBone Marrow Research · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsOccupational Cancer Research Centre
Fundersnot available
KeywordsOncolytic virusMedicineVirotherapyClinical trialMultiple myelomaLenalidomideDiseaseCancerCancer researchOncologyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Multiple myeloma (MM) is a B-cell malignancy that is currently felt to be incurable. Despite recently approved novel targeted treatments such as lenalidomide and bortezomib, most MM patients' relapse is emphasizing the need for effective and well-tolerated therapies for this deadly disease. The use of oncolytic viruses has garnered significant interest as cancer therapeutics in recent years, and are currently under intense clinical investigation. Both naturally occurring and engineered DNA and RNA viruses have been investigated preclinically as treatment modalities for several solid and hematological malignancies. Presently, only a genetically modified measles virus is in human clinical trials for MM. The information obtained from this and other future clinical trials will guide clinical application of oncolytic viruses as anticancer agents for MM. This paper provides a timely overview of the history of oncolytic viruses for the treatment of MM and future strategies for the optimization of viral therapy for this disease.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.065
GPT teacher head0.351
Teacher spread0.286 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations14
Published2011
Admission routes1
Has abstractyes

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