Black goji berry anthocyanins extend lifespan and enhance the antioxidant defenses in Caenorhabditis elegans via the JNK-1 and DAF-16/FOXO pathways.

BACKGROUND: The black goji berry (Lycium ruthenicum Murr.) is known for its abundance of high-quality natural antioxidants, particularly anthocyanins. Black goji berry anthocyanins (BGA) are receiving increasing attention because of their high safety and beneficial biological activities. Studies have shown that oxidative stress is a key factor affecting aging, whereas antioxidants are critical preventive and delaying strategies. RESULTS: In the present study, we investigated the potential anti-aging effects and mechanism of BGA using the Caenorhabditis elegans model. We found that BGA prolonged the mean lifespan of nematodes and improve their healthspan, including locomotion, pharyngeal pumping rate and stress resistance. Subsequently, we observed a significant decrease in reactive oxygen species and malondialdehyde levels in nematodes after administering BGA. Moreover, BGA enhanced the activities of the antioxidant enzymes superoxide dismutase and catalase, and elevated the glutathione disulfide/glutathione ratio. We confirmed that BGA exerted excellent antioxidative stress activity in nematodes, which may contribute substantially to its anti-aging effects. The health benefits of BGA in C. elegans might be closely related to petunidin-3-O-glucoside, the most abundant anthocyanin in BGA. Further mechanistic investigation revealed that the JNK-1 and DAF-16/FOXO pathways, rather than the calorie restriction pathway, were responsible for the antioxidant stress and life-prolonging effects of BGA in nematodes. CONCLUSION: Our research provides a theoretical foundation for studying the anti-aging effect of BGA and a basis for developing black goji berry and its anthocyanins as functional foods with anti-aging and antioxidative stress benefits. © 2024 Society of Chemical Industry.

Black Goji Berry (Lycium ruthenicum) Juice Fermented with Lactobacillus rhamnosus GG Enhances Inhibitory Activity against Dipeptidyl Peptidase-IV and Key Steps of Lipid Digestion and Absorption.

With the global increase in hyperglycemia and hyperlipidemia, there is an urgent need to explore dietary interventions targeting the inhibition of dipeptidyl peptidase-IV (DPP-IV) and lipid digestion and absorption. This study investigated how Lactobacillus rhamnosus GG (LGG) affects various aspects of black goji berry (BGB) (Lycium ruthenicum Murr.) juice, including changes in physicochemical and functional properties, as well as microbiological and sensory attributes. Throughout the fermentation process with 2.5-10% (w/v) BGB, significantly improved probiotic viability, lactic acid production, and decreased sugar content. While total flavonoids increase, anthocyanins decrease, with no discernible change in antioxidant activities. Metabolite profiling reveals elevated phenolic compounds post-fermentation. Regarding the inhibition of lipid digestion and absorption, fermented BGB exhibits improved bile acid binding, and disrupted cholesterol micellization by approximately threefold compared to non-fermented BGB, while also increasing pancreatic lipase inhibitory activity. Furthermore, a decrease in cholesterol uptake was observed in Caco-2 cells treated with fermented BGB (0.5 mg/mL), with a maximum reduction of 16.94%. Fermented BGB also shows more potent DPP-IV inhibition. Sensory attributes are significantly improved in fermented BGB samples. These findings highlight the potential of BGB as a bioactive resource and a promising non-dairy carrier for LGG, enhancing its anti-hyperglycemic and anti-hyperlipidemic properties.

Black Goji Berry (Lycium ruthenicum Murray): A Review of Its Pharmacological Activity.

Lycium ruthenicum Murray (LRM; commonly known as black goji berry or black wolfberry), a plant in the Solanaceae family, grows in the deserts of China's Qinghai-Tibet plateau. LRM is widely consumed in traditional Chinese medicine, and its fruits are frequently used as herbal remedies to treat heart disease, fatigue, inflammation, and other conditions. Many studies have reported that LRM is rich in functional phytochemicals, such as anthocyanins and polysaccharides, and has various pharmacological actions. This article reviews research on the biological and pharmacological effects of the constituents of LRM fruits. LRM has various pharmacological properties, such as antioxidant, anti-inflammatory, anti-radiation, immune-enhancing, anti-tumor, and protective effects. LRM has much promise as a dietary supplement for preventing many types of chronic metabolic disease.

Novel color stability and colorimetry-enhanced intelligent CO2 indicators by metal complexation of anthocyanins for monitoring chicken freshness.

This study aims to improve the color stability of anthocyanins and develop a CO2-sensitive indicator based on black goji anthocyanin (BGA) extract. Although the BGA extracts showed distinct color changes, such as red-purple-blue, their intrinsic color diminished after 24 h. A metal complexation method was used for the high color stability of BGA. BGA extracts were chelated with various concentrations of Al3+ [0 - 20% (w/w)]. It showed high color stability and strong intensity in a dose-dependent manner. A CO2-sensitive indicator sachet was developed using hydroxypropyl methylcellulose hydrogel, based on 5% (w/w) Al3+-BGA complexes. The indicator was applied to the chicken breast and detected its spoilage after 3 days with its changing color to greyish blue, due to the microbial growth to 7.00 log CFU/g. These results demonstrated the possibility of chelated anthocyanin complexes as indicating dyes and the ability to monitor the food quality changes through noticeable color changes.

Developing deep learning based regression approaches for determination of chemical compositions in dry black goji berries (Lycium ruthenicum Murr.) using near-infrared hyperspectral imaging.

Black goji berry (Lycium ruthenicum Murr.) has great commercial and nutritional values. Near-infrared hyperspectral imaging (NIR-HSI) was used to determine total phenolics, total flavonoids and total anthocyanins in dry black goji berries. Convolutional neural networks (CNN) were designed and developed to predict the chemical compositions. These CNN models and deep autoencoder were used as supervised and unsupervised feature extraction methods, respectively. Partial least squares (PLS) and least-squares support vector machine (LS-SVM) as modelling methods, successive projections algorithm and competitive adaptive reweighted sampling (CARS) as wavelength selection methods, and principal component analysis (PCA) and wavelet transform (WT) as feature extraction methods were studied as conventional approaches for comparison. Deep learning approaches as modelling methods and feature extraction methods obtained good and equivalent performances to the conventional methods. The results illustrated that deep learning had great potential as modelling and feature extraction methods for chemical compositions determination in NIR-HSI.