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Record W2891038428 · doi:10.1158/2326-6066.cir-18-0309

Antibody-Neutralized Reovirus Is Effective in Oncolytic Virotherapy

2018· article· en· W2891038428 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

VenueCancer Immunology Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsOncolytics Biotech (Canada)
FundersNational Cancer InstituteCancer Research UK
KeywordsOncolytic virusVirotherapyAntibodyImmune systemImmunotherapyImmunologyVirologyNeutralizing antibodyInternalizationMedicineBiologyReceptor

Abstract

fetched live from OpenAlex

Abstract Immunotherapy is showing promise for otherwise incurable cancers. Oncolytic viruses (OVs), developed as direct cytotoxic agents, mediate their antitumor effects via activation of the immune system. However, OVs also stimulate antiviral immune responses, including the induction of OV-neutralizing antibodies. Current dogma suggests that the presence of preexisting antiviral neutralizing antibodies in patients, or their development during viral therapy, is a barrier to systemic OV delivery, rendering repeat systemic treatments ineffective. However, we have found that human monocytes loaded with preformed reovirus–antibody complexes, in which the reovirus is fully neutralized, deliver functional replicative reovirus to tumor cells, resulting in tumor cell infection and lysis. This delivery mechanism is mediated, at least in part, by antibody receptors (in particular FcγRIII) that mediate uptake and internalization of the reovirus/antibody complexes by the monocytes. This finding has implications for oncolytic virotherapy and for the design of clinical OV treatment strategies. Cancer Immunol Res; 6(10); 1161–73. ©2018 AACR.

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)0.002
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 score0.046
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.451
Teacher spread0.406 · 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