Inhibitory effects of mung bean (Vigna radiata L.) seed and sprout extracts on melanogenesis

Jeong, Yoo Min; Ha, Ji Hoon; Noh, Geun Young; Park, Soo Nam

doi:10.1007/s10068-016-0079-6

Cited by 13 publications

(8 citation statements)

References 25 publications

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“…In this study, two pure compounds separated from the ethyl acetate extract fraction were identified as vitexin and isovitexin. In another study, an ethyl acetate extract of mung bean seeds and its sprouts was also investigated for inhibitory effects against melanogenesis using B16F1 melanoma cells [79]. The results showed that inhibitory effects against melanogenesis were especially apparent for 10 μg/mL ethyl acetate fractions of mung bean sprouts (germinated for 1 day), with values of 56.5% in B16F1 melanoma cells treated with a 200 nM α-melanocyte-stimulating hormone.…”

Section: Health Benefitsmentioning

confidence: 99%

Mung Bean (Vigna radiata L.): Bioactive Polyphenols, Polysaccharides, Peptides, and Health Benefits

et al. 2019

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Mung bean (Vigna radiata L.) is an important pulse consumed all over the world, especially in Asian countries, and has a long history of usage as traditional medicine. It has been known to be an excellent source of protein, dietary fiber, minerals, vitamins, and significant amounts of bioactive compounds, including polyphenols, polysaccharides, and peptides, therefore, becoming a popular functional food in promoting good health. The mung bean has been documented to ameliorate hyperglycemia, hyperlipemia, and hypertension, and prevent cancer and melanogenesis, as well as possess hepatoprotective and immunomodulatory activities. These health benefits derive primarily from the concentration and properties of those active compounds present in the mung bean. Vitexin and isovitexin are identified as the major polyphenols, and peptides containing hydrophobic amino acid residues with small molecular weight show higher bioactivity in the mung bean. Considering the recent surge in interest in the use of grain legumes, we hope this review will provide a blueprint to better utilize the mung bean in food products to improve human nutrition and further encourage advancement in this field.

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Section: Health Benefitsmentioning

confidence: 99%

Mung Bean (Vigna radiata L.): Bioactive Polyphenols, Polysaccharides, Peptides, and Health Benefits

et al. 2019

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“…The tyrosinase inhibition was first reported in Vigna mungo (Zia-Ul-Haq 2014). The increase in the tyrosinase inhibition was also reported in Vigna radiata upon sprouting (Jeong 2016). Yao et al (2011) studied the tyrosinase inhibition activity in 16 legumes and found maximum tyrosinase inhibition activity in mung bean with inhibition percentage of 81.24%.…”

Section: Resultsmentioning

confidence: 62%

Antityrosinase activity and photosynthetic pigments in seaweed treated sprouts of Vigna aconitifolia

Verma¹,

Sehrawat

Kumari

et al. 2019

Indian J Agri Sci

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The seaweed, Ascophyullum nodosum is the focus of the research these days and is looked upon as an important alternative bio-fertilizer. For this purpose the interaction of the seaweed with different plants including legumes is important to understand. We previously noticed lesser pigmented nodules in legume plant Vigna aconitifolia, when grown in presence of A. nodosum Extract (ANE). We therefore studied the effect of the ANE on the tyrosinase inhibition activity, an enzyme known to produce melanin pigment. In addition, the effect of the treatment of ANE on the photosynthetic pigments was also recorded. The seeds of Vigna aconitifolia were treated with 0%, 0.01%, 0.05%, 0.10%, 0.50% and 1.0% of A. nodosum extract for different time periods from 0â€“24 hours. It was observed that with the increased exposure to the seaweed (ANE), the tyrosinase inhibition activity also increased up to 0.05% of the seaweed concentration at 24 h of soaking and decreased after increasing the concentration of ANE from 0.1â€“1.0% at the same time period. Seed treatment with 0.05% seaweed was found to be the most effective concentration showing highest tyrosinase inhibition.

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“…Across the world, many cosmetic companies have tried to create products that include a cosmeceutical ingredient to address these aging factors. 46–48 However, the aging process can vary because of the exposome (external and lifestyle factors). 1 , 9 , 10 , 49 Although skin health and aging are affected by both the genome and exposome, an individual’s intrinsic genes do not change.…”

Section: Discussionmentioning

confidence: 99%

A Genome-Wide Association Study and Machine-Learning Algorithm Analysis on the Prediction of Facial Phenotypes by Genotypes in Korean Women

Yoo¹,

Lee

Woo³

et al. 2022

CCID

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Purpose Changes in facial appearance are affected by various intrinsic and extrinsic factors, which vary from person to person. Therefore, each person needs to determine their skin condition accurately to care for their skin accordingly. Recently, genetic identification by skin-related phenotypes has become possible using genome-wide association studies (GWAS) and machine-learning algorithms. However, because most GWAS have focused on populations with American or European skin pigmentation, large-scale GWAS are needed for Asian populations. This study aimed to evaluate the correlation of facial phenotypes with candidate single-nucleotide polymorphisms (SNPs) to predict phenotype from genotype using machine learning. Materials and Methods A total of 749 Korean women aged 30–50 years were enrolled in this study and evaluated for five facial phenotypes (melanin, gloss, hydration, wrinkle, and elasticity). To find highly related SNPs with each phenotype, GWAS analysis was used. In addition, phenotype prediction was performed using three machine-learning algorithms (linear, ridge, and linear support vector regressions) using five-fold cross-validation. Results Using GWAS analysis, we found 46 novel highly associated SNPs (p < 1×10 −05 ): 3, 20, 12, 6, and 5 SNPs for melanin, gloss, hydration, wrinkle, and elasticity, respectively. On comparing the performance of each model based on phenotypes using five-fold cross-validation, the ridge regression model showed the highest accuracy (r 2 = 0.6422–0.7266) in all skin traits. Therefore, the optimal solution for personal skin diagnosis using GWAS was with the ridge regression model. Conclusion The proposed facial phenotype prediction model in this study provided the optimal solution for accurately predicting the skin condition of an individual by identifying genotype information of target characteristics and machine-learning methods. This model has potential utility for the development of customized cosmetics.

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Inhibitory effects of mung bean (Vigna radiata L.) seed and sprout extracts on melanogenesis

Cited by 13 publications

References 25 publications

Mung Bean (Vigna radiata L.): Bioactive Polyphenols, Polysaccharides, Peptides, and Health Benefits

Mung Bean (Vigna radiata L.): Bioactive Polyphenols, Polysaccharides, Peptides, and Health Benefits

Antityrosinase activity and photosynthetic pigments in seaweed treated sprouts of Vigna aconitifolia

A Genome-Wide Association Study and Machine-Learning Algorithm Analysis on the Prediction of Facial Phenotypes by Genotypes in Korean Women

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