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Record W3094317173 · doi:10.1080/15384101.2020.1836441

The adenoviral protein E4orf4: a probing tool to decipher mechanical stress-induced nuclear envelope remodeling in tumor cells

2020· article· en· W3094317173 on OpenAlexafffund
Kévin Jacquet, Marc‐Antoine Rodrigue, Darren E. Richard, Josée N. Lavoie

Bibliographic record

VenueCell Cycle · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsUniversité LavalCentre hospitalier de l'Université Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyCell biologyCellNuclear proteinGeneticsGeneTranscription factor

Abstract

fetched live from OpenAlex

The human adenovirus (Ad) type 2/5 early region 4 (E4) ORF4 protein (E4orf4) exerts a remarkable tumor cell-selective killing activity in mammalian cells. This indicates that E4orf4 can target tumor cell-defining features and is a unique tool to probe cancer cell vulnerabilities. Recently, we found that E4orf4, through an interaction with the polarity protein PAR3, subverts nuclear envelope (NE) remodeling processes in a tumor cell-selective manner. In this Perspective, we outline mechanical signals that modify nuclear dynamics and tumor cell behavior to highlight potential mechanisms for E4orf4's tumoricidal activity. Through an analysis of E4orf4's cellular targets, we define a protein subnetwork that comprises phosphatase systems interconnected to polarity protein hubs, which could contribute to enhanced NE plasticity. We infer that elucidating E4orf4's protein network at a functional level could uncover key mechanisms of NE remodeling that define the tumor cell phenotype.

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 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 score0.034
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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.

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

Citations0
Published2020
Admission routes2
Has abstractyes

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