MétaCan
Menu
Back to cohort
Record W2056491567 · doi:10.1136/jcp.2009.064717

MicroRNAs in clinical oncology: at the crossroads between promises and problems

2009· review· en· W2056491567 on OpenAlexaff
Shereen Metias, Evi Lianidou, George M. Yousef

Bibliographic record

VenueJournal of Clinical Pathology · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsmicroRNACancerRNA interferenceBioinformaticsBiologyComputational biologyFunction (biology)Cancer researchMedicineGeneGeneticsRNA

Abstract

fetched live from OpenAlex

MicroRNAs (miRNAs) are small RNAs that do not code for proteins, but function by controlling protein expression of other genes. miRNAs have been shown to control cell growth, differentiation and apoptosis. Shortly after their discovery, miRNAs have been found to be associated with cancer. Earlier reports have shown that human cancers frequently show a distorted expression profile of miRNAs. In this review, the biogenesis of miRNAs and potential mechanisms of their dysregulation and involvement in cancer pathogenesis are discussed. The current literature on potential applications of miRNAs in the field of clinical oncology from diagnostic to prognostic and predictive applications at the tissue, and more recently, serum levels, is reviewed. The potential therapeutic applications of miRNAs and RNAi in the field of cancer are summarised. Finally, some of the potential challenges that face the transition of miRNAs from a research setting into a clinical application are highlighted, with a future prospective of the incorporation of miRNAs in cancer patient management.

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 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)0.008
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.002
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 head0.149
GPT teacher head0.487
Teacher spread0.338 · 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 teacher head, not a consensus.

Study designOther design
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

Citations82
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical PathologySame topicMicroRNA in disease regulationFrench-language works237,207