Superquantiles at Work: Machine Learning Applications and Efficient Subgradient Computation

Set-Valued and Variational Analysis - R. Tyrell Rockafellar and his collaborators introduced, in a series of works, new regression modeling methods based on the notion of superquantile (or...     

Thermal,morphostructural and spectrometric characterization of an antibacterial kaolinite-based filter modified with silver for water treatment

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...     

Topology optimization of composite hyperelastic material using SPIMFO-method

Meccanica - Fiber reinforced materials are used in assorted engineering application and for this reason, new additive manufacturing technologies have been developed for this type of materials. With...     

Application of TiO2-nanotubes/PbO2 as an anode for the electrochemical elimination of Acid Red 1 dye

Journal of Solid State Electrochemistry - In this study, galvanostatic electrolysis, through the use of the platinum supported on Ti (Ti/Pt) and Ti/TiO2-nanotubes/PbO2 anodes, was conducted in an...     

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.     

Elemental distribution by synchrotron X-ray microfluorescence of prostate 3D cell culture

Prostate cancer is a highly prevalent disease and ranks second among malignant neoplasms that affect men around the world, behind lung cancer alone. Trace elements are very important and are involved in many cellular processes. The X-ray microfluorescence technique is an advanced tool of high spatial resolution, sensitivity, multielemental analysis, and nondestructiveness for trace element study. This study aimed to investigate the elemental distribution in spheroids obtained through the following human prostate cell lines using synchrotron X-ray microfluorescence: tumor cell line androgen independent (DU145), tumor cell line androgen dependent (LNCaP), and normal cell line (RWPE-1). The measurements were performed with a standard geometry of 45° of incidence, excited by a white beam using a pixel of 25 μm and an acquisition time of 300 ms/pixel at the X-ray fluorescence beamline at the Synchrotron Light National Laboratory (Campinas, Brazil). The synchrotron X-ray microfluorescence results showed differences between groups in all elements analyzed and suggested that further studies should be performed to understand the relationship of these trace elements with the progression and development of the disease.