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Record W4319294019 · doi:10.1128/jvi.00009-23

p38 Mitogen-Activated Protein Kinase Signaling Enhances Reovirus Replication by Facilitating Efficient Virus Entry, Capsid Uncoating, and Postuncoating Steps

2023· article· en· W4319294019 on OpenAlexafffund
Adil Mohamed, Qi Lin, Heather E. Eaton, Maya Shmulevitz

Bibliographic record

VenueJournal of Virology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsUniversity of Alberta
FundersFaculty of Medicine and Dentistry, University of AlbertaCanada Research ChairsCanada Foundation for InnovationUniversity of AlbertaCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchAlberta Cancer FoundationCancer Research SocietyGovernment of CanadaAlberta Health Services
KeywordsOncolytic virusBiologyMAPK/ERK pathwayViral replicationKRASViral entryHRASVirologyCancer researchSignal transductionVirusCancerCell biologyColorectal cancer

Abstract

fetched live from OpenAlex

The use of Pelareorep (mammalian orthoreovirus) as a therapy for metastatic breast cancer has shown promising results in recent clinical trials. However, the selection of prognostic markers to stratify patients has had limited success due to the fact that these markers are upstream receptors and signaling pathways that are present in a high percentage of cancers. This study demonstrates that the mechanism of action of p38 MAPK signaling plays a key role in establishment of reovirus infection at both early entry and late replication steps. Using a panel of breast cancer cell lines, we found that the expression levels of the MAPK11 (p38β) isoform are a strong determinant of reovirus uncoating and infection establishment. Our findings suggest that selecting prognostic markers that target key steps in reovirus replication may improve patient stratification during oncolytic reovirus therapy.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.306
Teacher spread0.288 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations5
Published2023
Admission routes2
Has abstractyes

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