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Myotonic dystrophy type 1 (DM1) is a hereditary disease characterized by progressive distal muscle weakness and myotonia. Patients with DM1 have abnormal lipid metabolism and a high propensity to develop a metabolic syndrome in comparison to the general population. It follows that metabolome evaluation in these patients is crucial and may contribute to a better characterization and discrimination between DM1 disease phenotypes and severities. Several experimental approaches are possible to carry out such an analysis; among them is Fourier-transform infrared spectroscopy (FTIR) which evaluates metabolic profiles by categorizing samples through their biochemical composition. In this study, FTIR spectra were acquired and analyzed using multivariate analysis (Principal Component Analysis) using skin DM1 patient-derived fibroblasts and controls. The results obtained showed a clear discrimination between both DM1-derived fibroblasts with different CTG repeat length and with the age of disease onset; this was evident given the distinct metabolic profiles obtained for the two groups. Discrimination could be attributed mainly to the altered lipid metabolism and proteins in the 1800-1500 cm-1 region. These results suggest that FTIR spectroscopy is a valuable tool to discriminate both DM1-derived fibroblasts with different CTG length and age of onset and to study the metabolomic profile of patients with DM1.Diabetes incidence has been a problem, because according with the World Health Organization and the International Diabetes Federation, the number of people with this disease is increasing very fast all over the world. Diabetic treatment is important to prevent the development of several complications, also lipid profile monitoring is important. For that reason the aim of this work is the implementation of machine learning algorithms that are able to classify cases, that corresponds to patients diagnosed with diabetes that have diabetes treatment, and controls that refers to subjects who do not have diabetes treatment but some of them have diabetes, bases on lipids profile levels. Logistic regression, K-nearest neighbor, decision trees and random forest were implemented, all of them were evaluated with accuracy, sensitivity, specificity and AUC-ROC curve metrics. Artificial neural network obtain an acurracy of 0.685 and an AUC value of 0.750, logistic regression achieve an accuracy of 0.729 and an AUC value of 0.795, K-nearest neighbor gets an accuracy of 0.669 and an AUC value of 0.709, on the other hand, decision tree reached an accuracy pg 0.691 and a AUC value of 0.683, finally random forest achieve an accuracy of 0.704 and an AUC curve of 0.776. The performance of all models was statistically significant, but the best performance model for this problem corresponds to logistic regression.CYP2C19 polymorphisms are important factors for proton pump inhibitor-based therapy. We examined the CYP2C19 genotypes and analyzed the distribution among ethnicities and clinical outcomes in Indonesia. We employed the polymerase chain reaction-restriction fragment length polymorphism method to determine the CYP2C19 genotypes and evaluated inflammation severity with the updated Sydney system. For CYP2C19*2, 46.4% were the homozygous wild-type allele, 14.5% were the homozygous mutated allele, and 39.2% were the heterozygous allele. For CYP2C19*3, 88.6% were the homozygous wild-type allele, 2.4% were the homozygous mutated allele, and 9.0% were the heterozygous allele. Overall, the prevalence of rapid, intermediate, and poor metabolizers in Indonesia was 38.5, 41.6, and 19.9%, respectively. [https://www.selleckchem.com/products/wnt-c59-c59.html C59] In the poor metabolizer group, the frequency of allele *2 (78.8%) was higher than the frequency of allele *3 (21.2%). The Papuan had a significantly higher likelihood of possessing poor metabolizers than the Balinese (OR 11.0; P = 0.002). The prevalence of poor metabolizers was lower compared with the rapid and intermediate metabolizers among patients with gastritis and gastroesophageal reflux disease. Intermediate metabolizers had the highest prevalence, followed by rapid metabolizers and poor metabolizers. Dosage adjustment should therefore be considered when administering proton pump inhibitor-based therapy in Indonesia.Concomitant with the ever-expanding use of electrical appliances and mobile communication systems, public and occupational exposure to electromagnetic fields (EMF) in the extremely-low-frequency and radiofrequency range has become a widely debated environmental risk factor for health. Radiofrequency (RF) EMF and extremely-low-frequency (ELF) MF have been classified as possibly carcinogenic to humans (Group 2B) by the International Agency for Research on Cancer (IARC). The production of reactive oxygen species (ROS), potentially leading to cellular or systemic oxidative stress, was frequently found to be influenced by EMF exposure in animals and cells. In this review, we summarize key experimental findings on oxidative stress related to EMF exposure from animal and cell studies of the last decade. The observations are discussed in the context of molecular mechanisms and functionalities relevant to health such as neurological function, genome stability, immune response, and reproduction. Most animal and many cell studies showed increased oxidative stress caused by RF-EMF and ELF-MF. In order to estimate the risk for human health by manmade exposure, experimental studies in humans and epidemiological studies need to be considered as well.Energy drinks containing significant quantities of caffeine, taurine and sugar are increasingly consumed, particularly by adolescents and young adults. The putative effects of chronic ingestion of either standard energy drink, MotherTM (ED), or its sugar-free formulation (sfED) on metabolic syndrome were determined in wild-type C57BL/6J mice, in comparison to a soft drink, Coca-Cola (SD), a Western-styled diet enriched in saturated fatty acids (SFA), and a combination of SFA + ED. Following 13 weeks of intervention, mice treated with ED were hyperglycaemic and hypertriglyceridaemic, indicating higher triglyceride glucose index, which was similar to the mice maintained on SD. Surprisingly, the mice maintained on sfED also showed signs of insulin resistance with hyperglycaemia, hypertriglyceridaemia, and greater triglyceride glucose index, comparable to the ED group mice. In addition, the ED mice had greater adiposity primarily due to the increase in white adipose tissue, although the body weight was comparable to the control mice receiving only water.