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Record W2014424859 · doi:10.1371/journal.pone.0039621

A Daphnane Diterpenoid Isolated from Wikstroemia polyantha Induces an Inflammatory Response and Modulates miRNA Activity

2012· article· en· W2014424859 on OpenAlexafffund
Anthony Khong, Roberto Forestieri, David E. Williams, Brian O. Patrick, Andrea D. Olmstead, Victoria Svinti, Emily K. Schaeffer, François Jean, Michel Roberge, Raymond J. Andersen, Eric Jan

Bibliographic record

VenuePLoS ONE · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioactive Natural Diterpenoids Research
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsmicroRNASmall interfering RNABiologyRNA interferenceUntranslated regionMolecular biologyRNACell biologyGene silencingGeneBiochemistry

Abstract

fetched live from OpenAlex

MicroRNAs (miRNAs) are endogenously expressed single-stranded ~21-23 nucleotide RNAs that inhibit gene expression post-transcriptionally by binding imperfectly to elements usually within the 3'untranslated region (3'UTR) of mRNAs. Small interfering RNAs (siRNAs) mediate site-specific cleavage by binding with perfect complementarity to RNA. Here, a cell-based miRNA reporter system was developed to screen for compounds from marine and plant extracts that inhibit miRNA or siRNA activity. The daphnane diterpenoid genkwanine M (GENK) isolated from the plant Wikstroemia polyantha induces an early inflammatory response and can moderately inhibit miR-122 activity in the liver Huh-7 cell line. GENK does not alter miR-122 levels nor does it directly inhibit siRNA activity in an in vitro cleavage assay. Finally, we demonstrate that GENK can inhibit HCV infection in Huh-7 cells. In summary, the development of the cell-based miRNA sensor system should prove useful in identifying compounds that affect miRNA/siRNA activity.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.031
GPT teacher head0.270
Teacher spread0.238 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations11
Published2012
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONESame topicBioactive Natural Diterpenoids ResearchFrench-language works237,207