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Record W3120274954 · doi:10.1186/s12935-020-01716-8

MicroRNA regulation of cancer stem cells in the pathogenesis of breast cancer

2021· review· en· W3120274954 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

VenueCancer Cell International · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversity of Saskatchewan
FundersNational Natural Science Foundation of China
KeywordsmicroRNAWnt signaling pathwayBreast cancerCancer stem cellCancer researchStem cellCancerPI3K/AKT/mTOR pathwayMedicineBioinformaticsBiologySignal transductionInternal medicineGeneCell biologyGenetics

Abstract

fetched live from OpenAlex

Breast cancer is the most common cancer among women and accounts for 30% of all female malignancies worldwide. Breast cancer stem cells (BCSCs) are a small population of breast cancer cells that exhibit multiple characteristics including differentiation capacity, self-renewal and therapeutic resistance. Recently, BCSCs have attracted attention due to their modulation of breast tumor behaviors and drug resistance. miRNAs are small noncoding mRNAs involved in virtually all biological processes, including stem cell development, maintenance and differentiation. In breast cancer, miRNAs appear to be multi-faceted since they can act as either suppressors or oncogenes to regulate breast cancer progression. This review summarizes the critical roles of miRNAs in regulating multiple signaling pathways such as Wnt/β-catenin, Notch, PI3K/AKT/mTOR, BMI-1 and STAT3 that are important for the BCSC maintenance.

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 score0.920
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.309
Teacher spread0.288 · 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