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Extraction and Quantification of Azelaic Acid from Different Wheat Samples () and Evaluation of Their Antimicrobial and Antioxidant Activities. | LitMetric

AI Article Synopsis

  • Azelaic Acid (AzA) is a dicarboxylic acid with anti-inflammatory and antimicrobial properties, making it effective for skin conditions like rosacea and acne.
  • * The study explores extracting AzA from whole grains using eco-friendly methods, analyzing 17 different extracts for their AzA levels and biological activities.
  • * Results showed that whole grain extracts have a broader range of activity compared to flour, with one extract (Naviglio) having higher AzA content and another (hydroalcoholic ultrasound-assisted) demonstrating better antimicrobial and antioxidant effects.

Article Abstract

Azelaic Acid (AzA) is a 9-carbon atom dicarboxylic acid, with numerous pharmacological uses in dermatology. Its effectiveness in papulopustular rosacea and acne vulgaris, among other dermatological disorders such as keratinization and hyper-pigmentation, is thought to be related to its anti-inflammatory and antimicrobial properties. It is a by-product of fungal mycelia metabolism but also it is found in different cereals such as barley, wheat, and rye. Diverse topical formulations of AzA exist in commerce, and it is mainly produced via chemical synthesis. In this study we describe the extraction of AzA from whole grains and whole-grain flour () through green methods. Seventeen different extracts were prepared and analyzed for their AzA content by HPLC-MS methods and then screened for their antioxidant activity using spectrophotometric assays (ABTS, DPPH, and Folin-Ciocalteu). Minimum-inhibitory-concentration (MIC) assays against several bacterial and fungal pathogens were performed, to validate their antimicrobial activity. The obtained results indicate that whole grain extracts provide a wider spectrum of activity than the flour matrix; in particular, the Naviglio extract showed higher AzA content, while the hydroalcoholic ultrasound-assisted extract provided better antimicrobial and antioxidant activity. The data analysis was performed using principal component analysis (PCA), as an unsupervised-pattern-recognition technique, to extract useful analytical and biological information.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10003986PMC
http://dx.doi.org/10.3390/molecules28052134DOI Listing

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