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Record W1972122842 · doi:10.1517/14712590903307370

Modification of mammalian reoviruses for use as oncolytic agents

2009· review· en· W1972122842 on OpenAlexaboutno aff
Diana J.M. van den Wollenberg, S K van den Hengel, Iris J. C. Dautzenberg, Onno Kranenburg, Rob C. Hoeben

Bibliographic record

VenueExpert Opinion on Biological Therapy · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsnot available
FundersKom op tegen Kanker
KeywordsOncolytic virusReoviridaeBiologyVirologyGenomeRNAGeneCapsidReverse geneticsVirusRNA virusGenetic enhancementGeneticsRotavirus

Abstract

fetched live from OpenAlex

The Reoviridae are a family of viruses with a non-enveloped icosahedral capsid and a segmented double-stranded RNA genome. Prototypes of the mammalian Orthoreoviruses have been isolated from human respiratory and enteric tracts and are not associated with human disease. One of these, human reovirus type 3 Dearing (T3D), usually serves as a model for the family. In the last decade the mammalian Orthoreoviruses, especially T3D, have been evaluated as oncolytic agents in experimental cancer therapy. This is based on the observation that reoviruses induce cell death and apoptosis in tumor cells, but not in healthy non-transformed cells. Several clinical trials have been initiated in Canada, the USA, and the UK, to study the feasibility and safety of this approach. Due to the segmented structure of their double-stranded RNA genomes genetic modification of Reoviridae has been notoriously difficult. Several techniques have been described recently that facilitate the genetic modification of reovirus genomes. The basis for reverse genetics of reovirus is the discovery in 1990 that reovirus RNA is infectious. Subsequently, it took ten years before a foreign gene was introduced into the reovirus genome. Here we review the methods for reovirus modification and their use for generating new reovirus-derived oncolytic agents.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.343
GPT teacher head0.484
Teacher spread0.142 · 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.

Study designOther design
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

Citations21
Published2009
Admission routes1
Has abstractyes

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