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Record W3163120500 · doi:10.1111/febs.16025

APOBEC3G rescues cells from the deleterious effects of DNA damage

2021· article· en· W3163120500 on OpenAlexfundno aff
Alexander Botvinnik, Pushkar Shivam, Yoav Smith, Gunjan Sharma, Udy Olshevsky, Ofra Moshel, Zakhariya Manevitch, Núria Climent, Harold Oliva, Elena Britan‐Rosich, Moshe Kotler

Bibliographic record

VenueFEBS Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchIsrael Science FoundationInternational Development Research Centre
KeywordsAPOBEC3GDNA damageDNA repairBiologyHomologous recombinationDNANucleotide excision repairCancer researchCell biologyAPOBECMolecular biologyCytidine deaminaseGeneticsGeneGenome

Abstract

fetched live from OpenAlex

Human apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3G (hA3G), a member of the APOBEC family, was described as an anti-HIV-1 restriction factor, deaminating reverse transcripts of the HIV-1 genome. Several types of cancer cells that express high levels of A3G, such as diffuse large B-cell lymphoma cells and glioblastomas, show enhanced cell survival after ionizing radiation and chemotherapy treatments. Previously, we showed that hA3G promotes (DNA) double-strand breaks repair in cultured cells and rescues transgenic mice from a lethal dose of ionizing radiation. Here, we show that A3G rescues cells from the detrimental effects of DNA damage induced by ultraviolet irradiation and by combined bromodeoxyuridine and ultraviolet treatments. The combined treatments stimulate the synthesis of cellular proteins, which are exclusively associated with A3G expression. These proteins participate mainly in nucleotide excision repair and homologous recombination DNA repair pathways. Our results implicate A3G inhibition as a potential strategy for increasing tumor cell sensitivity to genotoxic treatments.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
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 integrity0.0000.001
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 head0.019
GPT teacher head0.294
Teacher spread0.275 · 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 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

Citations12
Published2021
Admission routes1
Has abstractyes

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