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Record W4293526306 · doi:10.3390/biomedicines10092121

The Role of miR-29s in Human Cancers—An Update

2022· review· en· W4293526306 on OpenAlexaff
Thuy T. P. Nguyen, Kamrul Hassan Suman, Thong Ba Nguyen, Há Thi Nguyen, Duy Ngoc

Bibliographic record

VenueBiomedicines · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsDalhousie University
Fundersnot available
KeywordsComputational biologymicroRNABiologyGeneticsGene

Abstract

fetched live from OpenAlex

MicroRNAs (miRNAs) are small non-coding RNAs that directly bind to the 3' untranslated region (3'-UTR) of the target mRNAs to inhibit their expression. The miRNA-29s (miR-29s) are suggested to be either tumor suppressors or oncogenic miRNAs that are strongly dysregulated in various types of cancer. Their dysregulation alters the expression of their target genes, thereby exerting influence on different cellular pathways including cell proliferation, apoptosis, migration, and invasion, thereby contributing to carcinogenesis. In the present review, we aimed to provide an overview of the current knowledge on the miR-29s biological network and its functions in cancer, as well as its current and potential applications as a diagnostic and prognostic biomarker and/or a therapeutic target in major types of human cancer.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.021
GPT teacher head0.328
Teacher spread0.307 · 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

Citations37
Published2022
Admission routes1
Has abstractyes

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