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Record W2059146777 · doi:10.1089/hum.2010.227

Strategies to Enhance Viral Penetration of Solid Tumors

2011· review· en· W2059146777 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

VenueHuman Gene Therapy · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsMcMaster UniversityMcMaster University Medical Centre
Fundersnot available
KeywordsOncolytic virusPenetration (warfare)Bystander effectStromal cellVirusExtracellular matrixCancer researchBiologyVirologyImmunologyCell biology

Abstract

fetched live from OpenAlex

The efficient delivery of viral vectors to tumors is an active area of investigation. A number of barriers exist that must be overcome to achieve good penetration of vectors into tumors and distribution of their effects throughout the tumor mass. Replicating oncolytic viruses have the advantage of being able to amplify the initial dose, but progeny virus are prevented from spreading because of a dense mass of tightly packed cells with a dense extracellular matrix, admixed normal stromal cells, and high interstitial pressure. Although intratumoral injection may ensure initial delivery the distribution achieved by intravenous administration may be superior and come with beneficial bystander damage to the tumor vasculature. Strategies to enhance intravenous delivery and subsequent spread of these vectors within tumors are being developed by a number of groups. Achieving the goal of efficient penetration and spread of viruses within solid tumors is a necessary prerequisite to significant improvements in virus-vectored therapy of solid tumors.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.555
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.069
GPT teacher head0.411
Teacher spread0.343 · 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