Synthesis and Anticancer Activity of Certain Selenophene Derivatives

Russian Journal of Organic Chemistry - Selenopheno[2,3-d]pyrimidine- and selenopheno[2,3-d][1,2,3]triazine-containing compounds were synthesized starting from...     

A novel synthesis route for brookite rich titanium dioxide photocatalyst involving organic intermediate

Journal of Sol-Gel Science and Technology - High temperature stable brookite rich titanium dioxide of average crystallite size 20&;nbsp;nm has been prepared by a novel aqueous sol–gel...     

Optimized spacer layer thickness for plasmonic-induced enhancement of photocurrent in a-Si:H

Journal of Nanoparticle Research - Plasmonic interfaces consisting of silver nanoparticles of different sizes (50–100&;nbsp;nm) have been processed by the self-assembled dewetting...     

Investigation of Plasma Oscillations in Glasslike Dielectrics by Means of Total External Reflection of X Rays

Technical Physics - Glasslike dielectrics are investigated by methods of plasmon dispersion and asymmetry of the number of localized electrons in the region in which total external reflection of...     

Identification of metabolic markers in patients with type 2 Diabetes by Ultrafast gas chromatography coupled to electronic nose. A pilot study

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.