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http://dx.doi.org/10.3389/fnut.2024.1481810 | DOI Listing |
Surg Obes Relat Dis
December 2024
Dietetic Department, Leeds Teaching Hospitals NHS Trust, St James's University Hospital, Leeds, United Kingdom.
Inflamm Bowel Dis
December 2024
Division of Gastroenterology, Hepatology & Nutrition, Allegheny Health Network, Pittsburgh, PA, USA.
J Fungi (Basel)
December 2024
Laboratoire de Chimie et Biotechnologie des Produits Naturels-CHEMBIOPRO, Université de la Réunion, 15 Avenue René Cassin, CEDEX 9, CS 92003, F-97744 Saint-Denis, Ile de la Réunion, France.
Fungi: 1, 2, 3, [...
View Article and Find Full Text PDFFront Microbiol
December 2024
Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, United States.
Symbiotic interactions drive species evolution, with nutritional symbioses playing vital roles across ecosystems. Chemosynthetic symbioses are globally distributed and ecologically significant, yet the lack of model systems has hindered research progress. The giant ciliate and its sulfur-oxidizing symbionts represent the only known chemosynthetic symbiosis with a short life span that has been transiently cultivated in the laboratory.
View Article and Find Full Text PDFFront Nutr
December 2024
Department of Systems Biology and Bioinformatics, Institute of Computer Science, University of Rostock, Rostock, Germany.
Introduction: Disease-related malnutrition is common but often underdiagnosed in patients with chronic gastrointestinal diseases, such as liver cirrhosis, short bowel and intestinal insufficiency, and chronic pancreatitis. To improve malnutrition diagnosis in these patients, an evaluation of the current Global Leadership Initiative on Malnutrition (GLIM) diagnostic criteria, and possibly the implementation of additional criteria, is needed.
Aim: This study aimed to identify previously unknown and potentially specific features of malnutrition in patients with different chronic gastrointestinal diseases and to validate the relevance of the GLIM criteria for clinical practice using machine learning (ML).
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