EGCG-based nanoparticles: synthesis, properties, and applications.

(-)-Epigallocatechin-3-gallate (EGCG) is a natural phenolic substance found in foods and beverages (especially tea) that exhibits a broad spectrum of biological activities, including antioxidant, antimicrobial, anti-obesity, anti-inflammatory, and anti-cancer properties. Its potential in cardiovascular and brain health has garnered significant attention. However, its clinical application remains limited due to its poor physicochemical stability and low oral bioavailability. Nanotechnology can be used to improve the stability, efficacy, and pharmacokinetic profile of EGCG by encapsulating it within nanoparticles. This article reviews the interactions of EGCG with various compounds, the synthesis of EGCG-based nanoparticles, the functional attributes of these nanoparticles, and their prospective applications in drug delivery, diagnosis, and therapy. The potential application of nanoencapsulated EGCG in functional foods and beverages is also emphasized. Top-down and bottom-up approaches can be used to construct EGCG-based nanoparticles. EGCG-based nanoparticles exhibit enhanced stability and bioavailability compared to free EGCG, making them promising candidates for biomedical and food applications. Notably, the non-covalent and covalent interactions of EGCG with other substances significantly contribute to the improved properties of these nanoparticles. EGCG-based nanoparticles appear to have a wide range of applications in different industries, but further research is required to enhance their efficacy and ensure their safety.

Neural network in food analytics.

Neural network (i.e. deep learning, NN)-based data analysis techniques have been listed as a pivotal opportunity to protect the integrity and safety of the global food supply chain and forecast $11.2 billion in agriculture markets. As a general-purpose data analytic tool, NN has been applied in several areas of food science, such as food recognition, food supply chain security and omics analysis, and so on. Therefore, given the rapid emergence of NN applications in food safety, this review aims to provide a comprehensive overview of the NN application in food analysis for the first time, focusing on domain-specific applications in food analysis by introducing fundamental methodology, reviewing recent and notable progress, and discussing challenges and potential pitfalls. NN demonstrated that it has a bright future through effective collaboration between food specialist and the broader community in the food field, for example, superiority in food recognition, sensory evaluation, pattern recognition of spectroscopy and chromatography. However, major challenges impeded NN extension including void in the food scientist-friendly interface software package, incomprehensible model behavior, multi-source heterogeneous data, and so on. The breakthrough from other fields proved NN has the potential to offer a revolution in the immediate future.

Preparation of enzymatically cross-linked α-lactalbumin nanoparticles and their application for encapsulating lycopene.

High internal phase Pickering emulsions (HIPPEs) stabilized by protein nanoparticles have been widely reported, but the use of enzymatic methods for preparing these nanoparticles remains underexplored. Our hypothesis is that enzymatically crosslinked α-lactalbumin (ALA) nanoparticles (ALATGs) prepared using transglutaminase will demonstrate improved properties as stabilizers for HIPPEs. In this study, we investigated the physicochemical properties and microstructures of ALATGs, finding that enzymatic crosslinking could be enhanced by removing Ca2+ ions from ALA and preheating the proteins (85 °C, 15 min). The electrical charge, secondary structure, and surface hydrophobicity of ALATGs were found to depend on crosslinking conditions. HIPPEs formed with an ALA concentration of 10 mg/mL and an enzyme activity of 120 U/g exhibited the highest apparent viscosity and mechanical strength, as well as significantly improved loading capacity and photostability for the encapsulated lycopene. Overall, our results support the hypothesis that ALATG-nanoparticles show superior performance as emulsifiers compared to ALA-nanoparticles.

Caffeoyl substitution decreased the binding and inhibitory activity of quinic acid against α-amylase: The reason why chlorogenic acid is a relatively weak enzyme inhibitor.

α-Amylase inhibition of chlorogenic acid (CHA) and its component moieties including quinic acid (QA) and caffeic acid (CA) were characterized by IC50, inhibition kinetics, fluorescence quenching, isothermal titration calorimetry, differential scanning calorimetry and molecular docking. QA was found with the highest inhibitory activity in a competitive-mode, and caffeoyl substitution significantly decreased its inhibition but maintained inhibition type. Interestingly, QA hardly quenched α-amylase fluorescence, while CA quenched that significantly without inhibitory activity. This resulted from lack of aromatic ring in QA that can form π-conjugation with α-amylase fluorescent residues. Besides, the binding constant of QA with α-amylase was higher than CHA. Additionally, QA and CA decreased but CHA remained α-amylase thermal stability, indicating that change in α-amylase spatial structure was related with enzyme residue sites involved in interactions with inhibitors, instead of with inhibition effect. Conclusively, caffeoyl substitution decreased α-amylase inhibition of QA through reducing its binding affinity to the enzyme.