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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 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

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.

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 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 score0.997
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.021
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