Evidence map›Paper›PMID 22439629›Full record

ArticleChinese medicine2012

NMR evaluation of total statin content and HMG-CoA reductase inhibition in red yeast rice (Monascus spp.) food supplements.

Dirk W Lachenmeier, Yulia B Monakhova, Thomas Kuballa, Sigrid Löbell-Behrends, Sibylle Maixner, Matthias Kohl-Himmelseher, Asja Waldner, Christian Steffen

Open access · goldAbstract read
In one paragraph

Article in Chinese medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.1field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 42 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 3 countries.

Dirk W LachenmeierChemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, 76187 Karlsruhe, Germany. lachenmeier@web.de.
Yulia B Monakhova
Thomas Kuballa
Sigrid Löbell-Behrends
Sibylle Maixner
Matthias Kohl-Himmelseher
Asja Waldner
Christian Steffen
Chemisches und Veterinäruntersuchungsamt Karlsruhe · DERegierungspräsidium Stuttgart · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRed yeast rice (i.e., rice fermented with Monascus spp.), as a food supplement, is claimed to be blood cholesterol-lowering. The red yeast rice constituent monacolin K, also known as lovastatin, is an inhibitor of the hydroxymethylglutaryl-CoA (HMG-CoA) reductase. This article aims to develop a sensitive nuclear magnetic resonance (NMR) method to determine the total statin content of red yeast rice products.

methodsThe total statin content was determined by a 400 MHz 1H NMR spectroscopic method, based on the integration of the multiplet at δ 5.37-5.32 ppm of a hydrogen at the hexahydronaphthalene moiety in comparison to an external calibration with lovastatin. The activity of HMG-CoA reductase was measured by a commercial spectrophotometric assay kit.

resultsThe NMR detection limit for total statins was 6 mg/L (equivalent to 0.3 mg/capsule, if two capsules are dissolved in 50 mL ethanol). The relative standard deviations were consistently lower than 11%. The total statin concentrations of five red yeast rice supplements were between 1.5 and 25.2 mg per specified daily dose. A dose-dependent inhibition of the HMG-CoA reductase enzyme activity by the red yeast rice products was demonstrated.

conclusionA simple and direct NMR assay was developed to determine the total statin content in red yeast rice. The assay can be applied for the determination of statin content for the regulatory control of red yeast rice products.

Identifiers

PMID22439629
PMCPMC3337221
OpenAlexW2135375412

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.