Nutrition & Food Science

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Subject: search.filters.subject.Pickering emulsion

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    Curcumin-Loaded Pickering Emulsion Formed by Ultrasound and Stabilized by Metal Organic Framework Optimization
    (MDPI, 2021-03-03) Ma, Peihua; Zhang, Zhi; Tsai, Shawn; Zhang, Hongchao; Li, Yuan; Yuan, Fang; Wang, Qin
    The ultrasound-assisted preparation of a curcumin-loaded metal organic framework (MOF) UiO-66-NH2 stabilized Pickering emulsion system was carried out in this study. A 3-level-4-factor Box–Behnken design (BBD) and response surface methodology (RSM) analysis were employed to systematically evaluate the effect of different experimental parameters (i.e., ultrasonic power, ultrasonic time, oil content, and MOF content) on curcumin loading capacity (LC) and encapsulation efficiency (EE). The results indicated that ultrasonic power and MOF content significantly affected LC and EE, whereas ultrasonic time and oil content had little effect. A mathematical model for optimizing the preparation of emulsion systems was established. Based on the ridge max analysis, an optimal condition for the newly developed curcumin-loaded MOF-Pickering emulsion was identified, i.e., ultrasonic power 150 W, ultrasonic time 11.17 min, oil content 20.0%, and MOF content 1.10%. At this condition, the LC and EE of curcumin obtained from the experiment reached 7.33% ± 0.54% and 56.18% ± 3.03%, respectively, which were within the prediction range of LC (7.35% ± 0.29%) and EE (54.34% ± 2.45%). The emulsion systems created in this study may find new applications for the delivery of bioactive compounds in food and pharmaceutical areas.
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    Development of Stable Pickering Emulsions with TEMPO-Oxidized Chitin Nanocrystals for Encapsulation of Quercetin
    (MDPI, 2023-01-12) Jia, Xiaoxue; Ma, Peihua; Taylor, Kim Shi-Yun; Tarwa, Kevin; Mao, Yimin; Wang, Qin
    Pickering emulsions stabilized by TEMPO-oxidized chitin nanocrystals (T-ChNCs) were developed for quercetin delivery. T-ChNCs were synthesized by TEMPO oxidation chitin and systematically characterized in terms of their physicochemical properties. T-ChNCs were rod-like with a length of 279.7 ± 11.5 nm and zeta potential around −56.1 ± 1.6 mV. The Pickering emulsions were analyzed through an optical microscope and CLSM. The results showed that the emulsion had a small droplet size (972.9 ± 86.0 to 1322.3 ± 447.7 nm), a high absolute zeta potential value (−48.2 ± 0.8 to −52.9 ± 1.9 mV) and a high encapsulation efficiency (quercetin: 79.6%). The emulsion stability was measured at different levels of T-ChNCs and pH values. The droplet size and zeta potential decreased with longer storage periods. The emulsions formed by T-ChNCs retarded the release of quercetin at half rate of that of the quercetin ethanol solution. These findings indicated that T-ChNCs are a promising candidate for effectively stabilizing Pickering emulsions and controlling release of quercetin.
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    DEVELOPMENT OF ARTIFICIAL INTELLIGENCE AUGMENTED METAL-ORGANIC FRAMEWORK-BASED SYSTEMS AND THEIR APPLICATIONS IN FOOD SECTORS
    (2022) ma, peihua; Wang, Qin Q. W.; Food Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Metal-organic frameworks (MOFs), a type of cutting-edge designable porous scaffolding materials attracted attention in reticular chemistry, which satisfied fundamental demands for delivery research in the past years. In this research, UiO-66 MOF family with different modifications was applied in the food delivery system and freshness monitoring.First, zirconium (IV) chloride and benzene-1,4-dicarboxylic acid were used to make the Zr-based MOF UiO-66. Then, using a post-synthesis loading process, curcumin was encapsulated in it. The system attained a high loading capacity of 3.45 percent w/w, according to both spectroscopic and thermogravimetric measurements. X-ray diffraction (XRD), physisorption analyzer, scanning electron microscopy (SEM), and energy-dispersive X-ray spectrometer (EDS) were used to characterize the crystal structure, porosity, and morphology of the curcumin delivery system, respectively. Curcumin was shown to be released in a controlled manner in simulated intestinal fluids using an in vitro digestion test. After 180 minutes of digestion, almost 60% of the curcumin was released. Second, two types of curcumin-loaded UiO-66 (representative high biocompatibility and water-stable metal-organic framework) deliver systems, curcumin-loaded UiO-66 Pickering emulsion and curcumin loaded UiO-66 high internal-phase Pickering emulsions (HIPPE) were prepared, named curcmin@UiO-66 PE and curcumin@UiO-66 HIPPE, respectively. The loading capacity for the two delivery systems was reached 7.33, and 26.18% w/w respectively. All systems were characterized using X-ray diffraction (XRD), physisorption analyzer, scanning electron microscopy (SEM), and energy-dispersive X-ray spectrometer (EDS), for crystallography, morphology, physicochemical properties, with computer assistant optimization with DFT and GCMC simulation for maximum loading capacity. The result showed that these systems both exhibited extremely high surface area and porosity, as well as strong chemical and thermal stability, which demonstrated their great potential for application as a food delivery system. On this basis, the emulsion system was further optimized using the response surface method. These novel MOF nanoparticle stabilized delivery systems could be practically utilized for other bioactive components and antimicrobial agents, which would find applications in functional food, food safety, and biomedical areas in the future. Third, incorporating or positioning multi-functional MOFs into the smart package is one of the next steps toward reticular chemistry for commercial application. Here, a cheap and versatile method to incorporate MOFs into smart food packages via generic patterning was developed. Meanwhile, deep convolutional neural networks (DCNN) were combined to form a system for monitoring food freshness that provided scent fingerprint recognition. The ice-template-based UiO-66-Br/chitosan sensor array and MOF-MMM-based UiO-66-OH/PVA sensor array comprising 6 different dyes absorbed at MOF matrix formed scent fingerprints that were identifiable by DCNN. Several state-of-art DCNN models were trained for shrimp freshness monitoring by using 31584 labeled images and 13537 images for testing. The highest accuracy achieved was up to 99.94% by the Wide-Slice Residual Network 50 (WISeR50). MOF-MMM-based sensor array showed a similar result where chicken freshness estimation achieved up to 98.95%. These platforms are intuitive, fast, accurate, and non-destructive, enabling consumers to monitor food freshness.