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Record W2943838533 · doi:10.2217/fvl-2019-0015

Epstein–Barr Virus: Overcoming the DNA Damage Response

2019· article· en· W2943838533 on OpenAlexaff
Lori Frappier

Bibliographic record

VenueFuture Virology · 2019
Typearticle
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologyDNA damageVirusAPOBECVirologyDNAEpstein–Barr virusGeneticsGeneGenome

Abstract

fetched live from OpenAlex

Infections by DNA viruses including, Epstein–Barr virus (EBV), typically induce cellular DNA damage responses (DDR), in particular double-stranded break signaling. To avoid apoptosis associated with constitutive DDR signaling, downstream steps of this pathway must be inactivated. EBV has developed multiple ways of disabling the DDR using several different viral proteins expressed at various stages of EBV infection. Here the interplay between EBV and host DDRs is discussed at each stage of EBV infection, along with the EBV proteins and miRNAs that are known to interfere with DDR signaling. The newly discovered APOBEC editing of EBV DNA and protection from this mutation is also discussed.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score1.000

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)0.0010.001

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 head0.007
GPT teacher head0.248
Teacher spread0.242 · 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.

Study designNot applicable
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
Published2019
Admission routes1
Has abstractyes

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