Antioxidant and anti‐inflammatory effects of Peanut (Arachishypogaea L.) skin extracts of various cultivars in oxidative‐damaged HepG2 cells and LPS‐induced raw 264.7 macrophages

Abstract

This study was performed to investigate the distribution of phenolic compounds in the peanut skins of various cultivars, as well as their antioxidant and anti‐inflammatory effect (Arachishypogaea L. cv. K‐Ol, cv. Sinpalkwang, cv. Daan, cv. Heuksaeng) and extraction solvent. The major components of red peanut cultivars (K‐Ol, Sinpalkwang, and Daan) were identified as proanthocyanidin, catechin, gallic acid, coumaric acid, and hesperidine, whereas the major components of black peanut cultivar (Heuksaeng) were identified as anthocyanin, ferulic acid, and quercetin. The DPPH and ABTS radical scavenging activities, and FRAP values were the highest in Daan followed by Sinpalkwng, K‐Ol, and Heuksang. Furthermore, the skin extracts of red peanuts effectively improved cell viability, reactive oxygen species generation, MDA concentration, and antioxidant enzyme activity (GR, GPx, CAT, and superoxide dismutase) in oxidative stress‐induced HepG2 cells, and reduced the expression of pro‐inflammatory factors (NO, TNF‐α, IL‐6, and IL‐1β) in LPS‐stimulated RAW 264.7 macrophages. These results suggest that red peanut skin extracts could effectively mediate physiological activity and provide valuable information for the use of peanut byproducts as functional food materials.

Role ofSemisulcospira gottscheiextract as medicinal food on reflux esophagitis in rats

“…LPS, a major component in outer membrane of Gram‐negative bacteria, is generally used to induce inflammation for in vivo and in vitro models (Bhardwaj et al., 2020), (Kim et al., 2020; Deng et al, 2021). LPS activates macrophages and involves the expression of pro‐inflammatory cytokines and mediators including iNOS (Nicholas et al., 2007).…”

Comprehensive review of composition distribution and advances in profiling of phenolic compounds in oilseeds

“…Peanut is a critical oilseed crop widely cultivated in many countries and it is an important food material consumed worldwide ( 28 ). The content of soluble phenolic compounds, insoluble phenolic compounds, soluble flavonoids, and total anthocyanin in peanuts ranged from 706 to 1,458, from 1,071 to 1,262, from 58 to 133, and from 3.36 to 11.49 mg/100 g, respectively ( 29 ).…”

“…The content of soluble phenolic compounds, insoluble phenolic compounds, soluble flavonoids, and total anthocyanin in peanuts ranged from 706 to 1,458, from 1,071 to 1,262, from 58 to 133, and from 3.36 to 11.49 mg/100 g, respectively ( 29 ). Although peanut skin accounts for only a small portion of peanut fruit, it was discarded 7.5 × 10 5 tons a year as a by-product ( 28 ). Peanut skin has high antioxidant activity for its abundant phenolic compounds, such as phenolic acids, stilbenes, flavonoids, anthocyanins and procyanidins, thereby it can be used as natural antioxidant with a wide range of clinical applications ( 8 , 28 ).…”

“…Although peanut skin accounts for only a small portion of peanut fruit, it was discarded 7.5 × 10 5 tons a year as a by-product ( 28 ). Peanut skin has high antioxidant activity for its abundant phenolic compounds, such as phenolic acids, stilbenes, flavonoids, anthocyanins and procyanidins, thereby it can be used as natural antioxidant with a wide range of clinical applications ( 8 , 28 ). Furthermore, peanut shells, as the by-product of peanut industry, contain polyphenols, flavonoids, luteolin and functional compounds for human consumption ( 30 ).…”

“…For multivariate analysis, principal component analysis (PCA) and hierarchical clustering analysis are the frequently used explorative multivariate methods. Miho et al used PCA of phenolic concentrations to distinguish between virgin olive oils and found that virgin olive oils obtained in three consecutive crop seasons could be effectively distinguished by PCA ( 28 ). In addition, linear discriminant analysis, such as partial least squares discriminant analysis, orthogonal partial least square discriminant analysis (OPLS-DA), and multiple linear regression, partial least squares, orthogonal partial least squares etc., are the widely used statistical analysis approaches for classification and regression analysis.…”