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Authentication of the Bilberry Extracts by an HPLC Fingerprint Method Combining Reference Standard Extracts.

ABSTRACT: A simple and fast high-performance liquid chromatography (HPLC) fingerprint method combining reference standard extract for the identification of bilberry extract was developed and validated. Six batches of bilberry extract collected from different manufactures were used to establish the HPLC fingerprint. Other berry extracts-such as blueberry extracts, mulberry extracts, cranberry extracts, and black rice extracts-were also analyzed for their HPLC chromatograms. The fingerprints of five batches of bilberry extract showed high similarities, while one batch was distinguished from others. Additionally, the content of anthocyanin Cyanidin-3-O-glucoside (Cy-3-glc) in each berry extract was analyzed and compared. The results indicate that this HPLC fingerprint method, combining reference standard extracts, could be used for the authentication and quality control of bilberry extracts.

SUBMITTER: Liu B

PROVIDER: S-EPMC7321295 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Authentication of the Bilberry Extracts by an HPLC Fingerprint Method Combining Reference Standard Extracts.

Liu Bingbing B Hu Tiantian T Yan Weidong W

Molecules (Basel, Switzerland) 20200528 11

A simple and fast high-performance liquid chromatography (HPLC) fingerprint method combining reference standard extract for the identification of bilberry extract was developed and validated. Six batches of bilberry extract collected from different manufactures were used to establish the HPLC fingerprint. Other berry extracts-such as blueberry extracts, mulberry extracts, cranberry extracts, and black rice extracts-were also analyzed for their HPLC chromatograms. The fingerprints of five batches ...[more]

PMID: 32481617

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Project description:BackgroundObesity and metabolic syndrome are important public concerns, and there is increasing demand for effective therapeutic strategies. Flavonoids are expected to improve the risk factors associated with metabolic syndrome. Anthocyanidins are a kind of flavonoids; well known for their anti-oxidative, anti-inflammatory and anti-tumor properties. However, their effects on adipocytes and molecular systems are not well defined. In this study, we examined the effects of anthocyanidins-enriched bilberry extracts on adipocyte differentiation.MethodsUtilizing 3T3-L1 cell line, we investigated that bilberry extracts and anthocyanidins induced inhibition of lipid accumulation during adipogenesis. To identify what is the most important bilberry mediated-effect, we analyzed the expressions of key transcriptional factors associated with adipocyte differentiation by Real Time (RT)-PCR. From the results of RT-PCR, we hypothesized that bilberry extracts and anthocyanidins blocks insulin signal, we determined the phosphorylation of tyrosine residues of insulin receptor substrate 1 (IRS1) protein by western blotting analysis. In addition, we compared the whole-genome expression profiles of early stage of adipocyte differentiation under four different growth conditions (DMSO, bilberry, two anthocyanidins) by microarray analyses and Gene Set Enrichment Analysis (GSEA).ResultsExposure to bilberry extracts and anthocyanidins during adipocyte differentiation inhibited 3T3-L1 differentiation. During this period, bilberry extracts and anthocyanidin significantly decreased a key adipocyte differentiation-associated marker, peroxisome proliferator-activated receptor- γ (Ppar γ ) and sterol regulatory element-binding protein 1c (Srebp1c). Western blotting analysis showed that bilberry extracts and anthocyanidin decreased the phosphorylation of tyrosine residues of IRS1. In addition, microarray experiments and GSEA data revealed significantly altered expression of the known genes of the insulin pathway in cells treated with bilberry extracts or anthocyanidins in the early differentiation stages.ConclusionsOur data demonstrate that anthocyanidin enriched bilberry extracts strongly inhibit the adipocyte differentiation via the insulin pathway. Furthermore, bilberry extracts might be used as a potential complementary treatment for the obese patients with metabolic syndrome.

Project description:BackgroundMany problems in bioinformatics involve classification based on features such as sequence, structure or morphology. Given multiple classifiers, two crucial questions arise: how does their performance compare, and how can they best be combined to produce a better classifier? A classifier can be evaluated in terms of sensitivity and specificity using benchmark, or gold standard, data, that is, data for which the true classification is known. However, a gold standard is not always available. Here we demonstrate that a Bayesian model for comparing medical diagnostics without a gold standard can be successfully applied in the bioinformatics domain, to genomic scale data sets. We present a new implementation, which unlike previous implementations is applicable to any number of classifiers. We apply this model, for the first time, to the problem of finding the globally optimal logical combination of classifiers.ResultsWe compared three classifiers of protein subcellular localisation, and evaluated our estimates of sensitivity and specificity against estimates obtained using a gold standard. The method overestimated sensitivity and specificity with only a small discrepancy, and correctly ranked the classifiers. Diagnostic tests for swine flu were then compared on a small data set. Lastly, classifiers for a genome-wide association study of macular degeneration with 541094 SNPs were analysed. In all cases, run times were feasible, and results precise. The optimal logical combination of classifiers was also determined for all three data sets. Code and data are available from http://bioinformatics.monash.edu.au/downloads/.ConclusionsThe examples demonstrate the methods are suitable for both small and large data sets, applicable to the wide range of bioinformatics classification problems, and robust to dependence between classifiers. In all three test cases, the globally optimal logical combination of the classifiers was found to be their union, according to three out of four ranking criteria. We propose as a general rule of thumb that the union of classifiers will be close to optimal.

Dataset Information

Authentication of the Bilberry Extracts by an HPLC Fingerprint Method Combining Reference Standard Extracts.

Publications

Authentication of the Bilberry Extracts by an HPLC Fingerprint Method Combining Reference Standard Extracts.

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