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Record W2770838661 · doi:10.1159/000485351

The Dual Regulatory Role of MiR-181a in Breast Cancer

2017· review· en· W2770838661 on OpenAlexaff
Yang Chun, Seyed Nasrollah Tabatabaei, Xiangyan Ruan, Pierre Hardy

Bibliographic record

VenueCellular Physiology and Biochemistry · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsCancerBreast cancerCancer researchMedicinemicroRNAInternal medicineBiologyGeneticsGene

Abstract

fetched live from OpenAlex

MicroRNAs (miRNAs) are a family of highly conserved noncoding single-stranded RNA molecules of 21 to 25 nucleotides. miRNAs silence their cognate target genes at the post-transcriptional level and have been shown to have important roles in oncogenesis, invasion, and metastasis via epigenetic post-transcriptional gene regulation. Recent evidence indicates that the expression of miR-181a is altered in breast tumor tissue and in the serum of patients with breast cancer. However, there are several contradicting findings that challenge the biological significance of miR-181a in tumor development and metastasis. In fact, some studies have implicated miR-181a in regulating breast cancer gene expression. Here we summarize the current literature demonstrating established links between miR-181a and human breast cancer with a focus on recently identified mechanisms of action. This review also aims to explore the potential of miR-181a as a diagnostic and/or prognostic biomarker for breast cancer and to discuss the contradicting data regarding its targeting therapeutics and the associated challenges.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.278
Teacher spread0.265 · 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 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

Citations91
Published2017
Admission routes1
Has abstractyes

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