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Record W2801167282 · doi:10.3389/fonc.2018.00111

Epstein–Barr Virus and Human Papillomaviruses Interactions and Their Roles in the Initiation of Epithelial–Mesenchymal Transition and Cancer Progression

2018· review· en· W2801167282 on OpenAlexaff
Farhan Cyprian, Halema F. Al-Farsi, Semir Vranić, Saghir Akhtar, Ala‐Eddin Al Moustafa

Bibliographic record

VenueFrontiers in Oncology · 2018
Typereview
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsMcGill University
FundersQatar University
KeywordsEpithelial–mesenchymal transitionCancer researchCancerPI3K/AKT/mTOR pathwayProtein kinase BEpstein–Barr virusMetastasisTumor progressionBiologySignal transductionMedicineVirusVirologyCell biologyGenetics

Abstract

fetched live from OpenAlex

Oncoviruses are implicated in around 20% of all human cancers including both solid and non-solid malignancies. Epstein-Barr virus (EBV) and human papillomaviruses (HPVs) are the most common oncoviruses worldwide. Currently, it is well established that onco-proteins of EBV (LMP1, LMP2A and EBNA1) and high-risk HPVs (E5 and E6/E7) play an important role in the initiation and/or progression of several human carcinomas including cervical, oral and breast. More significantly, it has been recently pointed out that viral onco-proteins of EBV and high-risk HPVs can be co-present and consequently cooperate to initiate and/or amplify epithelial-mesenchymal transition (EMT), which is the hallmark of cancer progression and metastasis. This could occur by -catenin, JAK/STAT/SRC, PI3k/Akt/mTOR and/or RAS/MEK/ERK signaling pathways, which onco-proteins of EBV and HPVs share. This review presents the most recent advances related to EBV and high-risk HPVs onco-proteins interactions and their roles in the progression of human carcinomas especially oral and breast via the initiation of EMT.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.037
GPT teacher head0.384
Teacher spread0.347 · 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 designOther design
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

Citations61
Published2018
Admission routes1
Has abstractyes

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