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Role for DNA repair signaling in coronary artery stenosis (1071.9)

2014· article· en· W1501218729 on OpenAlexafffund
Jolyane Meloche, Aude Pflieger, Steeve Provencher, Sébastien Bonnet

Bibliographic record

VenueThe FASEB Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsDNA damageDNA repairApoptosisArteryPoly ADP ribose polymeraseCancer researchCoronary arteriesStenosisCoronary artery diseaseOxidative stressCell biologyInternal medicineMedicineBiologyDNABiochemistryPolymerase

Abstract

fetched live from OpenAlex

Coronary artery stenosis is a vascular disease characterized by sustained inflammation and oxidative stress, leading to DNA damage. Despite these detrimental conditions, coronary artery smooth muscle cells (CoASMC) show increased proliferation and suppressed apoptosis leading to luminal narrowing. PARP‐1 is a critical enzyme acting as DNA damage sensor by promoting either DNA repair or apoptosis depending on the amount of damage. Recent studies demonstrated the implication of the glycogen synthase 3 (GSK3) enzyme, which when inhibited, favors DNA repair (promoting cell survival and proliferation) and resistance to apoptosis (by promoting mitochondrial hyperpolarization). Thus, we hypothesized that increased DNA damage in coronary artery of patients with stenosis promotes PARP‐1 activation and GSK3 inhibition. In freshly isolated human CoASMC issued from control or stenosed arteries, we measured DNA damage, PARP‐1 expression and phosphorylated GSK3 protein levels. We demonstrated that CoASMC from stenosed arteries exhibit increased DNA damage, enhanced PARP‐1 expression and GSK3 inhibition. These cells also present mitochondrial membrane hyperpolarization and consequently show increased proliferation and suppressed apoptosis. Our study suggests an important role of DNA damage signaling and metabolism dysfunction in coronary stenosis and opens the door to new avenues of investigation and treatment. Grant Funding Source : Supported by CIHR grants

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: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.028
GPT teacher head0.284
Teacher spread0.256 · 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

Citations0
Published2014
Admission routes2
Has abstractyes

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