In this study, we developed a fluorescence method to quantify oxygen barrier properties for wall materials used in microencapsulation of oxygen-sensitive compounds. We used a reversible, oxygen quenching dye, tris (4,7-diphenyl-1, 10-phenanthroline) ruthenium(II) dichloride complex, as a marker to monitor oxygen transport across spray-dried and freeze-dried Hi-cap100 and maltodextrin microspheres. We fit the rate of oxygen transport to Fick's second law and extrapolated an effective oxygen diffusion coefficient Deff. Results show that the Deff for spray-dried maltodextrin and Hi-cap100 formulations were in the range of 6.46 × 10 to 7.45 × 10 m /s and 16.0 × 10 to 22.4 × 10 m /s, respectively. Results also show an increasing trend in thiobarbituric acid reactive substances reaction rate constants, with an increasing D for each formulation. Additionally, freeze-dried maltodextrin formulations had significantly higher D (31.1 × 10 to 36.0 × 10 m /s) compared to spray-dried matrices due to a more porous morphology. This new method provides a framework for the in situ estimation of D for wall materials in microspheres. Potential applications include the design and selection of wall materials for maximum oxidative stability of encapsulated ingredients. PRACTICAL APPLICATION: Currently, the selection of wall materials used in microencapsulation of lipids takes a trial-and-error approach, which can be time consuming and prone to error. In this study, we developed a new methodology to directly assess the oxygen barrier properties of wall materials in microspheres. This method can be used by food scientists to screen wall materials in order to optimize the oxidative stability of encapsulated lipids.
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http://dx.doi.org/10.1111/1750-3841.14453 | DOI Listing |
Iran J Basic Med Sci
January 2025
Graduate school, Shenyang Medical College, Shenyang. No. 146, Huanghe North Street, Shenyang, People's Republic of China.
Objectives: Particulate matter 2.5 (PM2.5), particles with an aerodynamic diameter less than 2.
View Article and Find Full Text PDFArch Endocrinol Metab
January 2025
Universidade Federal de São Paulo São PauloSP Brasil Universidade Federal de São Paulo, São Paulo, SP, Brasil.
Objective: Nitrate is ubiquitously found in the environment and is one of the main components of nitrogen fertilizers. Previous studies have shown that nitrate disrupts the reproductive system in aquatic animals, but no study has evaluated the impact of nitrate exposure on the uterus in mammals. This study aimed to evaluate the impact of maternal exposure to nitrate during the prenatal period on uterine morphology and gene expression in adult female F1 rats.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
Centre for Computational Science, University College London, 20 Gordon Street, London WC1H 0AJ, U.K.
For the computational design of new polymeric materials, accurate methods for determining the glass transition temperature () are required. We apply an ensemble approach in molecular dynamics (MD) and examine its predictions of and their associated uncertainty. We separate the uncertainty into the aleatoric contributions arising from dynamical chaos and that due to the computational scenarios chosen to compute .
View Article and Find Full Text PDFJ Comput Assist Tomogr
January 2025
Department of Radiology, George Washington University Hospital, Washington, DC.
The next step in the evolution of static 3-dimensionally (3D) printed models may be the creation of "smart" models, where subcomponents can be seamlessly interacted with through a feedback mechanism, with potential applications in trainee education and patient counseling. Considering the complexity of the ventricular and cisternal systems, they were chosen for segmentation, using Materialize InPrint with outward hollowing using 2.5-mm wall thickness.
View Article and Find Full Text PDFWorld J Surg Oncol
January 2025
Department of Hepatobiliary and Pancreas, Affiliated Hospital of Qingdao University, NO.1677 Wutaishan Road, Qingdao, Shandong Province, 266555, China.
Background: With the rising diagnostic rate of gallbladder polypoid lesions (GPLs), differentiating benign cholesterol polyps from gallbladder adenomas with a higher preoperative malignancy risk is crucial. This study aimed to establish a preoperative prediction model capable of accurately distinguishing between gallbladder adenomas and cholesterol polyps using machine learning algorithms.
Materials And Methods: We retrospectively analysed the patients' clinical baseline data, serological indicators, and ultrasound imaging data.
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