Metabolomics approach: Interpretation of changes in rat plasma metabolites after solifenacin treatment

Abstract Changes in metabolite levels of patients using the long-term drug can be comprehensively demonstrated by pharmacometabolomic studies. In this study, biological alterations induced by the administration of solifenacin succinate were investigated with a pharmacometabolomics approach on rat metabolism. Plasma samples obtained from rats were analyzed by LC-Q- TOF/MS/MS. METLIN and HMDB databases were used to identify metabolites. Data were processed and classified with MATLAB 2017b. 53 m/z values were found to be significantly different between the drug and control groups (p ≤ 0.01 and fold analysis > 1.5) and identified by comparing METLIN and HMDB databases. According to multivariate data analysis, changes in arachidonic acid, thromboxane A2, palmitic acid, choline, calcitriol, histamine phosphate, retinyl ester, l-cysteine, l-leucine, beta-alanine, l-histidine levels were found to be statistically significant compare to the control group. Differences in the biosynthesis of phenylalanine, aminoacyl-tRNA, tyrosine, tryptophan, metabolism of glycerophospholipid, cysteine, methionine, histidine, arachidonic metabolism have been successfully demonstrated by the metabolomics approach. Our study provides important information to explain the efficacy and toxicity of chronic administration of solifenacin succinate

Chemometrics Assisted Raman Spectroscopy: A Non-Invasive Approach in Diagnosis and Monitoring of Colorectal Cancer

Objective: Colorectal cancer is a commonly encountered cancer worldwide about 1.4 million new cases diagnosed and 693,900 deaths occurred per year. Colorectal cancer could be stopped and highly curable if diagnosed early. In this proposed study, the main goal is to develop accurate, sensitive and rapid Raman spectroscopy method in colorectal cancer diagnosis of formalin-fixed paraffin embedded tissue samples. Methods: In the proposed method, samples were deparaffinized and prepared as 20 microns of dimension that was located on a coverslip. The instrument produces a continuum laser at 785 nm that were applied to both healthy and cancer tissues. Wavenumber of 50-1800 cm-1 was scanned to get information about the metabolic variation in each group. Results: Accuracy of the method was calculated by comparing the results regarding the histopathological evaluation. Healthy and cancer tissues formed two unique clusters via chemometrics algorithm. The rapid, easy and precise diagnosis was achieved for colorectal cancer diagnosis. By this method, some beneficial information regarding the variation in several metabolites was also obtained from the spectrum. Conclusion: It is reported that the optimized method represents an important opportunity for clustering and separating cancer tissues from healthy ones. This novel, rapid, precise and numerical approach may be an effective alternative for the conventional methods.