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Oleosomes, naturally occurring in plants, mammals, and microorganisms, are highly valued in both food and non-food industries due to their unique composition, inherent emulsifying properties, and straightforward extraction processes. Despite advancements in twin-screw pressing and ultrasound-assisted methods, this review emphasizes the need to systematically explore aqueous-based method-including aqueous, aqueous enzymatic, salt-solution extraction, and alkali-solution extraction method-that have been underrepresented. For the first time, it highlights how factors such as polyphenols, polysaccharides, pH, temperature, and ionic conditions influence oleosome stability and digestion, which are critical for lipid release, absorption, and nutritional improvement-key aspects aligned with the development of functional foods. This review examines oleosome composition, extraction methods, and factors influencing their stability and digestibility, highlighting their broad application potential.
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http://dx.doi.org/10.1111/1750-3841.70413 | DOI Listing |
Int J Audiol
September 2025
Department of Otolaryngology-Head & Neck Surgery, University of California San Francisco, San Francisco, California, USA.
Objective: To develop and pilot test a combined-learning intervention for Tanzanian primary healthcare workers on ear and hearing care (EHC), comprising five self-led smartphone-based modules and in-person workshops.
Design: The intervention was piloted with primary healthcare workers in Tanzania. Pre- and post-training surveys assessed knowledge, confidence, and attitudes towards EHC via Likert scales.
PLoS One
September 2025
School of Medical Engineering, Xinxiang Medical University, Xinxiang, China.
Computer-aided diagnostic (CAD) systems for color fundus images play a critical role in the early detection of fundus diseases, including diabetes, hypertension, and cerebrovascular disorders. Although deep learning has substantially advanced automatic segmentation techniques in this field, several challenges persist, such as limited labeled datasets, significant structural variations in blood vessels, and persistent dataset discrepancies, which continue to hinder progress. These challenges lead to inconsistent segmentation performance, particularly for small vessels and branch regions.
View Article and Find Full Text PDFJ Craniofac Surg
September 2025
University of Miami Miller School of Medicine, Miami, FL.
Outcomes were to compare the accuracy of 2 large-language models-GPT-4o and o3-Mini-against medical-student performance on otolaryngology-focused, USMLE-style multiple-choice questions. With permission from AMBOSS, we extracted 146 Step 2 CK questions tagged "Otolaryngology" and stratified them by AMBOSS difficulty (levels 1-5). Each item was presented verbatim to GPT-4o and o3-Mini through their official APIs; outputs were scored correct/incorrect.
View Article and Find Full Text PDFMed Sci Sports Exerc
September 2025
Department of Engineering Mechanics, Tsinghua University, Beijing, CHINA.
Purpose: Develop a musculoskeletal-environment interaction model to reconstruct the dynamic-interaction process in skiing.
Methods: This study established a skier-ski-snow interaction (SSSI) model that integrated a 3D full-body musculoskeletal model, a flexible ski model, a ski boot model, a ski-snow contact model, and an air resistance model. An experimental method was developed to collect kinematic and kinetic data using IMUs, GPS, and plantar pressure measurement insoles, which were cost-effective and capable of capturing motion in large-scale field conditions.
PLoS One
September 2025
Department of Pathology, Hospital Tuanku Fauziah, Jalan Tun Abdul Razak, Kangar, Perlis, Malaysia.
Cervical cancer remains a significant cause of female mortality worldwide, primarily due to abnormal cell growth in the cervix. This study proposes an automated classification method to enhance detection accuracy and efficiency, addressing contrast and noise issues in traditional diagnostic approaches. The impact of image enhancement on classification performance is evaluated by comparing transfer learning-based Convolutional Neural Network (CNN) models trained on both original and enhanced images.
View Article and Find Full Text PDF