Publications by authors named "Xiaoke Peng"

Background: Repetitive transcranial magnetic stimulation (rTMS) and median nerve electrical stimulation (MNES) are two non-invasive neuromodulation techniques that have demonstrated potential in facilitating the recovery of consciousness in patients with impaired consciousness. However, existing studies on awakening interventions for patients with prolonged disorders of consciousness (pDoC) following intracerebral hemorrhage remains limited. In particular, systematic comparisons of the efficacy of rTMS versus MNES in this specific patient population are lacking.

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This study aims to investigate the effects of interfacial layer composition and structure on the formation, physicochemical properties and stability of Pickering emulsions. Interfacial layers were formed using pea protein isolate (PPI), PPI microgel particles (PPIMP), a mixture of PPIMP and sodium alginate (PPIMP-SA), or PPIMP-SA conjugate. The encapsulation and protective effects on different hydrophobic bioactives were then evaluated within these Pickering emulsions.

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(-)-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.

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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 Ca ions from ALA and preheating the proteins (85 °C, 15 min).

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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.

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α-Amylase inhibition of chlorogenic acid (CHA) and its component moieties including quinic acid (QA) and caffeic acid (CA) were characterized by IC, 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.

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