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Record W3095532130 · doi:10.1016/j.cytogfr.2020.10.007

Cytokines in oncolytic virotherapy

2020· review· en· W3095532130 on OpenAlexaff
Jonathan Pol, Samuel T. Workenhe, Prathyusha Konda, Shashi Gujar, Guido Kroemer

Bibliographic record

VenueCytokine & Growth Factor Reviews · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsBeatrice Hunter Cancer Research InstituteDalhousie UniversityUniversity of Guelph
FundersLabex Immuno-OncologyHigh-end Foreign Experts Recruitment Plan of ChinaEuropean Research Area Network on Cardiovascular DiseasesChancellerie des Universités de ParisCancéropôle Ile de FranceInstitut National de la Santé et de la Recherche MédicaleInstitut National Du CancerInstitut Universitaire de FranceLigue Contre le CancerFondation pour la Recherche MédicaleSeerave FoundationAssociation pour la Recherche sur le CancerFondation LeducqAgence Nationale de la Recherche
KeywordsOncolytic virusImmunosurveillanceVirotherapyTumor microenvironmentImmune systemCancer researchCytotoxic T cellChemokineBiologyStromal cellAntigenImmunologyImmunotherapyLymphokine

Abstract

fetched live from OpenAlex

Tumors represent a hostile environment for the effector cells of cancer immunosurveillance. Immunosuppressive receptors and soluble or membrane-bound ligands are abundantly exposed and released by malignant entities and their stromal accomplices. As a consequence, executioners of antitumor immunity inefficiently navigate across cancer tissues and fail to eliminate malignant targets. By inducing immunogenic cancer cell death, oncolytic viruses profoundly reshape the tumor microenvironment. They trigger the local spread of danger signals and tumor-associated (as well as viral) antigens, thus attracting antigen-presenting cells, promoting the activation and expansion of lymphocytic populations, facilitating their infiltration in the tumor bed, and reinvigorating cytotoxic immune activity. The present review recapitulates key chemokines, growth factors and other cytokines that orchestrate this ballet of antitumoral leukocytes upon oncolytic virotherapy.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.075
GPT teacher head0.379
Teacher spread0.304 · 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

Citations70
Published2020
Admission routes1
Has abstractyes

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