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UVA-induced damage to DNA and proteins: direct<i>versus</i>indirect photochemical processes

2011· article· en· W2026356336 on OpenAlexafffund
Pierre‐Marie Girard, Stefania Francesconi, Mariaelena Pozzebon, Dany Graindorge, Patrick J. Rochette, Régen Drouin, Évelyne Sage

Bibliographic record

VenueJournal of Physics Conference Series · 2011
Typearticle
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsUniversité de SherbrookeUniversité Laval
FundersNational Cancer InstituteCentre National de la Recherche ScientifiqueCanada Research ChairsAgence Nationale de la Recherche
KeywordsDNA damageDNAChemistryBiophysicsOxidative stressIn vitroMechanism (biology)Oxidative damageCell biologyPhotochemistryBiochemistryBiologyPhysics

Abstract

fetched live from OpenAlex

UVA has long been known for generating an oxidative stress in cells. In this paper we review the different types of DNA damage induced by UVA, i.e. strand breaks, bipyrimidine photoproducts, and oxidatively damaged bases. Emphasis is given to the mechanism of formation that is further illustrated by the presentation of new in vitro data. Examples of oxidation of proteins involved in DNA metabolism are also given.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.076
GPT teacher head0.282
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), 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

Citations62
Published2011
Admission routes2
Has abstractyes

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