This research focuses on the overall extraction process of alkylresorcinols (ARs) from uncooked grains and baked products that have been processed with wheat, corn, rice, and white flour. Previously established extraction methods developed by Ross and colleagues, as well as a semiautomated method involving accelerated solvent extraction (ASE), were applied to extract ARs within freshly ground samples. For extraction of alkylresorcinols, nonpolar solvents such as ethyl acetate have been recommended for the extraction of uncooked foods, and polar solvents such as 1-propanol:water (3:1 v/v) have been recommended for the extraction of baked foods that contain rye, wheat, or other starch-rich grains. A comparison of AR extraction methods has been investigated with the application of gas chromatography and a flame ionization detector (GC-FID) to quantify the AR content. The goal of this research was to compare the rapid accelerated solvent extraction of the alkylresorcinols (ASE-AR) method to the previous manual AR extraction methods. Results for this study as well as the investigation of the overall efficiency of ASE-AR extraction with the use of a spiking study indicated that it can be comparable to current extraction methods but with less time required. Furthermore, the extraction time for ASE (approximately 40 min) is much more convenient and less tedious and time-consuming than previously established methods, which range from 5 h for processed foods to 24 h for raw grains.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1021/jf3001422 | DOI Listing |
Clin Orthop Relat Res
January 2025
Division of Orthopaedic Surgery, University of Toronto, Toronto, ON, Canada.
Background: There is debate as to whether kinematic TKA or mechanical alignment TKA is superior. Recent systematic reviews have suggested that kinematically aligned TKAs may be the preferred option. However, the observed differences in alignment favoring kinematic alignment may not improve outcomes (performance or durability) in ways that patients can perceive, and likewise, statistical differences in outcome scores sometimes observed in clinical trials may be too small for patients to notice.
View Article and Find Full Text PDFJMIR Hum Factors
January 2025
Department of Value Improvement, St. Antonius Hospital, Nieuwegein, Netherlands.
Background: Patients with cerebrovascular accident (CVA) should be involved in setting their rehabilitation goals. A personalized prediction of CVA outcomes would allow care professionals to better inform patients and informal caregivers. Several accurate prediction models have been created, but acceptance and proper implementation of the models are prerequisites for model adoption.
View Article and Find Full Text PDFJMIR Form Res
January 2025
Department of Psychology, The University of Texas at San Antonio, San Antonio, TX, United States.
Background: Perception-related errors comprise most diagnostic mistakes in radiology. To mitigate this problem, radiologists use personalized and high-dimensional visual search strategies, otherwise known as search patterns. Qualitative descriptions of these search patterns, which involve the physician verbalizing or annotating the order he or she analyzes the image, can be unreliable due to discrepancies in what is reported versus the actual visual patterns.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Univ Rennes, CHU Rennes, INSERM, LTSI - UMR 1099, F-35000 Rennes, France.
Background: To reduce the mortality related to bladder cancer, efforts need to be concentrated on early detection of the disease for more effective therapeutic intervention. Strong risk factors (eg, smoking status, age, professional exposure) have been identified, and some diagnostic tools (eg, by way of cystoscopy) have been proposed. However, to date, no fully satisfactory (noninvasive, inexpensive, high-performance) solution for widespread deployment has been proposed.
View Article and Find Full Text PDFJMIR Pediatr Parent
January 2025
Department of Health and Physical Education, Mount Royal University, Calgary, AB, Canada.
Background: Early childhood is a critical period for shaping lifelong health behaviors, making early childhood education and care (ECEC) environments ideal for implementing nutrition and physical activity interventions. eHealth tools are increasingly utilized in ECEC settings due to their accessibility, scalability, and cost-effectiveness, demonstrating promise in enhancing educators' practices. Despite the potential effectiveness of these eHealth approaches, a comprehensive collection of available evidence on eHealth tools designed to assess or support best practices for nutrition or physical activity in ECECs is currently lacking.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!