Skin complications of diabetes mellitus revealed by polarized hyperspectral imaging and machine learning

Aging and diabetes lead to protein glycation and cause dysfunction of collagen-containing tissues. The accompanying structural and functional changes of collagen significantly contribute to the development of various pathological malformations affecting the skin, blood vessels, and nerves, causing a number of complications, increasing disability risks and threat to life. In fact, no methods of non-invasive assessment of glycation and associated metabolic processes in biotissues or prediction of possible skin complications, e.g., ulcers, currently exist for endocrinologists and clinical diagnosis. In this publication, utilizing emerging photonics-based technology, innovative solutions in machine learning, and definitive physiological characteristics, we introduce a diagnostic approach capable of evaluating the skin complications of diabetes mellitus at the very earlier stage. The results of the feasibility studies, as well as the actual tests on patients with diabetes and healthy volunteers, clearly show the ability of the approach to differentiate diabetic and control groups. Furthermore, the developed in-house polarization-based hyperspectral imaging technique accomplished with the implementation of the artificial neural network provides new horizons in the study and diagnosis of age-related diseases

Single nucleotide polymorphisms in the intergenic region between metformin transporter OCT2 and OCT3 coding genes are associated with short-Term response to metformin monotherapy in type 2 diabetes mellitus patients

Publisher Copyright: © 2016 The authors Published by Bioscientifica Ltd. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.Objective(s): High variability in clinical response to metformin is often observed in type 2 diabetes (T2D) patients, and it highlights the need for identification of genetic components affecting the efficiency of metformin therapy. Aim of this observational study is to evaluate the role of tagSNPs (tagging single nucleotide polymorphisms) from genomic regions coding for six metformin transporter genes with respect to the short-Term efficiency. Design: 102 tagSNPs in 6 genes coding for metformin transporters were genotyped in the group of 102 T2D patients treated with metformin for 3 months. Methods: Most significant hits were analyzed in the group of 131 T2D patients from Slovakia. Pharmacokinetic study in 25 healthy nondiabetic volunteers was conducted to investigate the effects of identified polymorphisms. Results: In the discovery group of 102 patients, minor alleles of rs3119309, rs7757336 and rs2481030 were significantly nominally associated with metformin inefficiency (P = 1.9 × 106 to 8.1 × 106). Effects of rs2481030 and rs7757336 did not replicate in the group of 131 T2DM patients from Slovakia alone, whereas rs7757336 was significantly associated with a reduced metformin response in combined group. In pharmacokinetic study, group of individuals harboring risk alleles of rs7757336 and rs2481030 displayed significantly reduced AUC∞ of metformin in plasma. Conclusions: For the first time, we have identified an association between the lack of metformin response and SNPs rs3119309 and rs7757336 located in the 5 flanking region of the genes coding for Organic cation transporter 2 and rs2481030 located in the 5 flanking region of Organic cation transporter 3 that was supported by the results of a pharmacokinetic study on 25 healthy volunteers.publishersversionPeer reviewe