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Record W2801710951 · doi:10.1186/s10020-018-0012-y

MicroRNA-296: a promising target in the pathogenesis of atherosclerosis?

2018· review· en· W2801710951 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

VenueMolecular Medicine · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
FundersNational Natural Science Foundation of China
KeywordsmicroRNAAngiogenesisPathogenesisBiologyTranslation (biology)Gene expressionDiseaseMolecular medicineBioinformaticsLipid metabolismNon-coding RNARegulation of gene expressionComputational biologyApoptosisGeneCancer researchCell biologyImmunologyMessenger RNAMedicineGeneticsPathologyEndocrinologyCell cycle

Abstract

fetched live from OpenAlex

Atherosclerosis has been recognized as an inflammatory disease involving the vascular wall. MicroRNAs are a group of small noncoding RNAs to regulate gene expression at the transcriptional level through mRNA degradation or translation repression. Recent studies suggest that miR-296 may play crucial roles in the regulation of angiogenesis, inflammatory response, cholesterol metabolism, hypertension, cellular proliferation and apoptosis. In this review, we primarily discussed the molecular targets of miR-296 involved in the development of atherosclerosis, which may provide a basis for future investigation and a better understanding of the biological functions of miR-296 in atherosclerosis.

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)0.001
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 score0.980
Threshold uncertainty score1.000

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 science0.0010.000
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 head0.028
GPT teacher head0.307
Teacher spread0.279 · 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