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Record W2079472804 · doi:10.1002/mnfr.200400053

Dietary factors and the regulation of 3-hydroxy-3-methylglutaryl coenzyme A reductase: Implications for breast cancer development

2004· review· en· W2079472804 on OpenAlexaff
Robin E. Duncan, Ahmed El‐Sohemy, Michael C. Archer

Bibliographic record

VenueMolecular Nutrition & Food Research · 2004
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant biochemistry and biosynthesis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMevalonate pathwayReductaseHMG-CoA reductaseCoenzyme ABreast cancerMevalonic acidCell growthDNA synthesisCancerCholesterolFatty acid synthesisSterol regulatory element-binding proteinBiologyHydroxymethylglutaryl-CoA reductaseBiochemistryCancer cellCancer researchEndocrinologyInternal medicineEnzymeMedicineSterolIn vitro

Abstract

fetched live from OpenAlex

A role for mevalonate in cancer development has long been suggested by findings that 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase activity is elevated in malignant cells. Increased synthesis mevalonate and mevalonate-derived nonsterol isoprenoids supports increased cell proliferation through the activation of growth-regulatory proteins and oncoproteins, and by promoting DNA synthesis. We have recently shown that mevalonate promotes the growth of human breast cancer cells both in culture and as tumors grown in nude mice. Inhibition mevalonate synthesis, therefore, may be an effective strategy to impair the growth of malignant breast cells. Several dietary compounds with known anti-cancer effects are also reported to inhibit HMG-CoA reductase activity. Here, we review evidence suggesting that inhibition of mevalonate synthesis may mediate the protective effects of cholesterol, plant isoprenoids, genistein, and long-chain n-3 polyunsaturated fatty acids (PUFAs) on experimental breast cancer.

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
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.083
GPT teacher head0.375
Teacher spread0.293 · 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

Citations14
Published2004
Admission routes1
Has abstractyes

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