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Record W2894023914 · doi:10.1016/j.ijcha.2018.09.006

Molecular mechanisms and genetic regulation in atherosclerosis

2018· review· en· W2894023914 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIJC Heart & Vasculature · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCircular RNAs in diseases
Canadian institutionsWestern University
FundersUniversity of South ChinaNational Natural Science Foundation of China
KeywordsmicroRNAHistoneRNAExtracellular matrixBiologyMutationCell biologyMedicineGeneticsBioinformaticsCancer researchDNAGene

Abstract

fetched live from OpenAlex

Atherosclerosis (AS) manifested by lipid accumulation, extracellular matrix protein deposition, and calcification in the intima and media of the large to medium size arteries promoting arterial stiffness and reduction of elasticity. It has been accepted that AS leads to increased morbidity and mortality worldwide. Recent studies indicated that genetic abnormalities play an important role in the development of AS. Specific genetic mutation and histone modification have been found to induce AS formation. Furthermore, specific RNAs such as microRNAs and circular RNAs have been identified to play a crucial role in the progression of AS. Nevertheless, the mechanisms by which genetic mutation, DNA and histone modification, microRNAs and circular RNA induce AS still remain elusive. This review describes specific mechanisms and pathways through which genetic mutation, DNA and histone modification, microRNAs and circular RNA instigate AS. This review further provides a therapeutic strategic direction for the treatment of AS targeting genetic mechanisms.

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.

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 score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.016
GPT teacher head0.284
Teacher spread0.267 · 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