MétaCan
Menu
Back to cohort
Record W1971624340 · doi:10.4161/rna.5.3.6558

The emerging role of miR-200 family of MicroRNAs in epithelial-mesenchymal transition and cancer metastasis

2008· review· en· W1971624340 on OpenAlexfundno aff
Manav Korpal, Yibin Kang

Bibliographic record

VenueRNA Biology · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsnot available
FundersNational Cancer InstituteNatural Sciences and Engineering Research Council of CanadaAmerican Cancer Society
KeywordsmicroRNABiologyEpithelial–mesenchymal transitionMetastasisCarcinogenesisSuppressorPhenotypeCancer researchCancerRegulation of gene expressionCell biologyGeneticsGene

Abstract

fetched live from OpenAlex

MicroRNAs (miRNAs) play essential roles in many physiological and pathological processes, including tumor development, by regulating the expression of a plethora of mRNAs. Although the importance of miRNAs in tumorigenesis is well established, only recently have reports elucidated miRNAs as promoters or suppressors of metastasis. The miR-200 family has been shown to inhibit the initiating step of metastasis, epithelial-mesenchymal transition (EMT), by maintaining the epithelial phenotype through direct targeting of transcriptional repressors of E-cadherin, ZEB1 and ZEB2. These findings shed light into a miRNA-mediated regulatory pathway that influences EMT in a developmentally and pathologically relevant setting.

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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.017
GPT teacher head0.302
Teacher spread0.286 · 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

Citations380
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueRNA BiologySame topicMicroRNA in disease regulationFrench-language works237,207