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Record W4285395415 · doi:10.3389/fcell.2022.910440

Chromatin and the Cellular Response to Particle Radiation-Induced Oxidative and Clustered DNA Damage

2022· review· en· W4285395415 on OpenAlexaff
John M. Danforth, Luc Provencher, Aaron A. Goodarzi

Bibliographic record

VenueFrontiers in Cell and Developmental Biology · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsChromatinDNA damageContext (archaeology)DNAIonizing radiationLinear energy transferDNA repairBiophysicsCell biologyBiologyPhysicsGeneticsChemistryRadiationIrradiationOptics

Abstract

fetched live from OpenAlex

the radioactive decay of radon gas in indoor air. Particle radiation is highly genotoxic, inducing DNA damage including oxidative base lesions and DNA double strand breaks. Due to the ionization density of high-LET radiation, the consequent damage is highly clustered wherein ≥2 distinct DNA lesions occur within 1-2 helical turns of one another. These multiply-damaged sites are difficult for eukaryotic cells to resolve either quickly or accurately, resulting in the persistence of DNA damage and/or the accumulation of mutations at a greater rate per absorbed dose, relative to lower LET radiation types. The proximity of the same and different types of DNA lesions to one another is challenging for DNA repair processes, with diverse pathways often confounding or interplaying with one another in complex ways. In this context, understanding the state of the higher order chromatin compaction and arrangements is essential, as it influences the density of damage produced by high-LET radiation and regulates the recruitment and activity of DNA repair factors. This review will summarize the latest research exploring the processes by which clustered DNA damage sites are induced, detected, and repaired in the context of chromatin.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.956
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.001
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 head0.015
GPT teacher head0.253
Teacher spread0.237 · 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 designNot applicable
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

Citations44
Published2022
Admission routes1
Has abstractyes

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