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Guizellini Filipe Corrêa Franzin Bruno Trevizan da Silva Matheus Antonio Abra Luciana Mazotti Hojo Ossamu Pastre Iêda Aparecida Ribeiro Clóvis Augusto Paiva-Santos Carlos de Oliveira Fertonani Fernando Luis 《Journal of Thermal Analysis and Calorimetry》2021,143(1):47-60
Journal of Thermal Analysis and Calorimetry - The aim of this work is to synthesize and characterize a new structured silver–clay dried, calcined or sintered at different temperatures... 相似文献
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Algebras and Representation Theory - We introduce and study the category of twisted modules over a triangular differential graded bocs. We show that in this category idempotents split, that it... 相似文献
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Vieira Renata Leia Demario Gaglieri Caroline de Oliveira Cristina Soltovski Ferreira Laura Teófilo Schnitzler Egon Bannach Gilbert 《Journal of Thermal Analysis and Calorimetry》2021,144(3):689-697
Journal of Thermal Analysis and Calorimetry - Buckwheat starch is an alternative source to supply the high global demand for starch. The properties of starch can be modified through chemical and... 相似文献
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Karen Beatriz Méndez-Rodríguez Nicté Figueroa-Vega César Arturo Ilizaliturri-Hernandez Mónica Cardona-Alvarado Jaime Antonio Borjas-García Carlos Kornhauser Juan Manuel Malacara Rogelio Flores-Ramírez Francisco Javier Pérez-Vázquez 《Biomedical chromatography : BMC》2020,34(12):e4956
Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra-fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross-sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty-one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty-eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2-propenal, 2-propanol, butane- 2,3-dione and 2-methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice. 相似文献