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Record W2133803355 · doi:10.1158/1535-7163.mct-08-1152

Silibinin inhibits translation initiation: implications for anticancer therapy

2009· article· en· W2133803355 on OpenAlexafffund
Chen‐Ju Lin, Rami Sukarieh, Jerry Pelletier

Bibliographic record

VenueMolecular Cancer Therapeutics · 2009
Typearticle
Languageen
FieldMedicine
TopicSilymarin and Mushroom Poisoning
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchCanadian Breast Cancer Research AllianceFaculty of Medicine, McGill UniversityMcGill University
KeywordsSilibininTranslation (biology)MedicinePharmacologyCancer researchOncologyBioinformaticsBiologyGeneticsMessenger RNA

Abstract

fetched live from OpenAlex

Silibinin is a nontoxic flavonoid reported to have anticancer properties. In this study, we show that silibinin exhibits antiproliferative activity on MCF-7 breast cancer cells. Exposure to silibinin leads to a concentration-dependent decrease in global protein synthesis associated with reduced levels of eukaryotic initiation factor 4F complex. Moreover, polysome profile analysis of silibinin-treated cells shows a decrease in polysome content and translation of cyclin D1 mRNA. Silibinin exerts its effects on translation initiation by inhibiting the mammalian target of rapamycin signaling pathway by acting upstream of TSC2. Our results show that silibinin blocks mammalian target of rapamycin signaling with a concomitant reduction in translation initiation, thus providing a possible molecular mechanism of how silibinin can inhibit growth of transformed cells.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.088
GPT teacher head0.375
Teacher spread0.287 · 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

Citations40
Published2009
Admission routes2
Has abstractyes

Explore more

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