We describe an integrated and straightforward new analytical protocol that identifies plant gums from various sample sources including cultural heritage. Our approach is based on the identification of saccharidic fingerprints using mass spectrometry following controlled enzymatic hydrolysis. We developed an enzyme cocktail suitable for plant gums of unknown composition. Distinctive MS profiles of gums such as arabic, cherry and locust-bean gums were successfully identified. A wide range of oligosaccharidic combinations of pentose, hexose, deoxyhexose and hexuronic acid were accurately identified in gum arabic whereas cherry and locust bean gums showed respectively PentHex and Hex profiles. Optimized for low sample quantities, the analytical protocol was successfully applied to contemporary and historic samples including 'Colour Box Charles Roberson &Co' dating 1870s and drawings from the American painter Arthur Dove (1880-1946). This is the first time that a gum is accurately identified in a cultural heritage sample using structural information. Furthermore, this methodology is applicable to other domains (food, cosmetic, pharmaceutical, biomedical).
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http://dx.doi.org/10.1038/srep44538 | DOI Listing |
J Nanobiotechnology
January 2025
Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology; Basic Medicine Research and Innovation Center of Ministry of Education, Medical School of Southeast University, 87 Dingjiaqiao, Nanjing, 210009, China.
Early diagnosis is critical for providing a timely window for effective therapy in pulmonary fibrosis (PF); however, achieving this remains a significant challenge. The distinct honeycombing patterns observed in computed tomography (CT) for the primary diagnosis of PF are typically only visible in patients with moderate to severe disease, often leading to missed opportunities for early intervention. In this study, we developed a nanoprobe designed to accumulate at fibroblastic foci and loaded with the CT sensitizer iodide to enable effective early diagnosis of PF.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Ave, Silver Spring, MD, 20993, USA.
Continuous and consistent access to quality medical imaging data stimulates innovations in artificial intelligence (AI) technologies for patient care. Breakthrough innovations in data-driven AI technologies are founded on seamless communication between data providers, data managers, data users and regulators or other evaluators to determine the standards for quality data. However, the complexity in imaging data quality and heterogeneous nature of AI-enabled medical devices and their intended uses presents several challenges limiting the clinical translation of novel AI technologies.
View Article and Find Full Text PDFIntroduction: Understanding causal risk factors that contribute to the development of multimorbidity is essential for designing and targeting effective preventive strategies. Despite a large body of research in this field, there has been little critical discussion about the appropriateness of the various analytical approaches used. This proposed scoping review aims to summarise and appraise the analytical approaches used in the published literature that evaluated risk factors of multimorbidity and to provide guidance for researchers conducting analyses in this field.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
College of Nursing, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
Background: TheKeep.Ca was built to facilitate engagement with those experiencing cancer in Manitoba, Canada. Constructed between 2020 and 2024 with a group of patient advisors, the website includes information on engagement activities including research participation, the patient advisor role, and how those experiencing cancer can access these Manitoba activities.
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