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Record W1977342490 · doi:10.1038/aps.2013.35

Friend or foe: the role of microRNA in chemotherapy resistance

2013· review· en· W1977342490 on OpenAlexafffund
Haoran Li, Burton B. Yang

Bibliographic record

VenueActa Pharmacologica Sinica · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversity of TorontoHealth Sciences CentreSunnybrook Health Science Centre
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaHeart and Stroke Foundation of Canada
KeywordsmicroRNADrug resistanceChemotherapyMechanism (biology)CancerApoptosisFunction (biology)DrugCancer researchBiologyMedicineBioinformaticsGenePharmacologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

Chemotherapy has been widely used in treating cancer patients. Despite the tremendous progress in cancer treatment achieved during the last decades, drug resistance still accounts for most of the tumor relapses in chemotherapy-treated patients. Emerging evidence shows that microRNAs play an important role in regulating the drug sensitivity of tumor cells. However, the mechanism of microRNA-mediated drug resistance is not fully understood. Current data suggest that microRNAs can be categorized as oncogenic or tumor-suppressive based on their functions and targets. In tumor cells undergoing drug treatment, microRNAs can function either by decreasing expression of genes associated with multiple drug resistance or by promoting escape from apoptosis and inducing tumor stem cell development. This review aims to provide an updated understanding of the role of microRNAs in regulating chemotherapy resistance and a discussion of potential therapeutic applications.

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)0.000
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 score0.922
Threshold uncertainty score0.915

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 head0.033
GPT teacher head0.350
Teacher spread0.317 · 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.

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

Citations115
Published2013
Admission routes2
Has abstractyes

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