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Record W1912023046 · doi:10.1139/cjpp-2012-0251

Oxidative-stress-induced epigenetic changes in chronic diabetic complications

2012· review· en· W1912023046 on OpenAlexafffundvenue
Biao Feng, Michael Ruiz, Subrata Chakrabarti

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsOxidative stressBiologyCell biologyDNA repairEpigeneticsEndocrinologyBiochemistry

Abstract

fetched live from OpenAlex

Oxidative stress plays an important role in the development and progression of chronic diabetic complications. Diabetes causes mitochondrial superoxide overproduction in the endothelial cells of both large and small vessels. This increased superoxide production causes the activation of several signal pathways involved in the pathogenesis of chronic complications. In particular, endothelial cells are major targets of glucose-induced oxidative damage in the target organs. Oxidative stress activates cellular signaling pathways and transcription factors in endothelial cells including protein kinase C (PKC), c-Jun-N-terminal kinase (JNK), p38 mitogen-activated protein kinase (MAPK), forkhead box O (FOXO), and nuclear factor kappa-B (NF-κB). Oxidative stress also causes DNA damage and activates DNA nucleotide excision repair enzymes including the excision repair cross complimenting 1(ERCC1), ERCC4, and poly(ADP-ribose) polymerase (PARP). Augmented production of histone acetyltransferase p300, and alterations of histone deacetylases, including class III deacetylases sirtuins, are also involved in this process. Recent research has found that small noncoding RNAs, like microRNA, are a new kind of regulator associated with chronic diabetic complications. There are extensive and complicated interactions and among these molecules. The purpose of this review is to demonstrate the role of oxidative stress in the development of diabetic complications in relation to epigenetic changes such as acetylation and microRNA alterations.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.042
GPT teacher head0.331
Teacher spread0.289 · 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
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

Citations59
Published2012
Admission routes3
Has abstractyes

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