The Blood Plasma Lipidomic Profile in Atherosclerosis of the Brachiocephalic Arteries.

According to the World Health Organization, ischemic stroke is the second leading cause of death in the world. Frequently, it is caused by brachiocephalic artery (BCA) atherosclerosis. Timely detection of atherosclerosis and its unstable course can allow for a timely response to potentially dangerous changes and reduce the risk of vascular complications. Omics technologies allow us to identify new biomarkers that we can use in diagnosing diseases. This research included 90 blood plasma samples. The study group comprised 52 patients with severe atherosclerotic lesions BCA, and the control group comprised 38 patients with no BCA atherosclerosis. Targeted and panoramic lipidomic profiling of their blood plasma was carried out. There was a statistically significant difference (p < 0.05) in the values of the indices saturated fatty acids (FAs), unsaturated FAs, monounsaturated FAs, omega-3, and omega-6. Based on the results on the blood plasma lipidome, we formed models that have a fairly good ability to determine atherosclerotic lesions of the brachiocephalic arteries, as well as a model for identifying unstable atherosclerotic plaques. According only to the panoramic lipidome data, divided into groups according to stable and unstable atherosclerotic plaques, a significant difference was taken into account: p value < 0.05 and abs (fold change) > 2. Unfortunately, we did not observe significant differences according to the established plasma panoramic lipidome criteria between patients with stable and unstable plaques. Omics technologies allow us to obtain data about any changes in the body. According to our data, statistically significant differences in lipidomic profiling were obtained when comparing groups with or without BCA atherosclerosis.

UniqPy: A tool for estimation of short-chain fatty acids composition by gas-chromatography/mass-spectrometry with headspace extraction.

Short-chain fatty acids are metabolites widely presented in many natural sources, including human feces and blood. Estimation of their composition is a common procedure, usually performed using nuclear magnetic resonance or gas chromatography with a flame ionization detector. However, the commonly used methods often depend on specific sample preparation, such as filtration and homogenization. The gas-chromatography/mass-spectrometry (GC/MS) method with headspace extraction allows sample preparation to be kept to a minimum regardless of the physical state of the sample, which can be potentially useful in metabolomics research of complex natural samples such as blood or feces. In this work, we have demonstrated the applicability of Headspace GC-MS for estimating short chain fatty acid (SCFA) composition. The main problem here is the complex, non-linear dependence between the composition of the compounds in the source phase and the relative pressures in the vapor phase, which are directly measured by this method. We have implemented a thermodynamic model that performs the reverse transformation of relative abundances in the vapor phase to relative concentrations in the liquid phase, and have tested it on some synthetic SCFA mixtures. The developed method is available as a pip package called UniqPy and can be used to describe liquid-vapor equilibrium for any multicomponent system if a sufficient amount of training data is provided. The gas chromatography method with headspace extraction in conjunction with the UniqPy data transformation showed satisfactory quantification accuracy for propionic acid, butyric acid, isobutyric acid, and valeric acid (R-squared > 0.96). The applicability of the method was additionally demonstrated on a series of fecal samples.

Estimating population-level of alcohol, tobacco and morphine use in a small Russian region using wastewater-based epidemiology.

INTRODUCTION: Alcohol, tobacco and illicit drug use combined are the largest modifiable health risk factors. Wastewater-based epidemiology (WBE) is a complementary approach for monitoring substance use in the population. In this study we applied WBE technique to a community in the Moscow region to estimate population-level consumption of alcohol, tobacco and morphine. METHODS: Wastewater sampling was carried out over 47 days, in 2018 and 2019, including the New Year period. Analysis of the samples for consumption biomarkers (ethyl sulphate, cotinine and morphine) were undertaken using liquid chromatography tandem mass spectrometry (LC-MS/MS). Daily consumption estimates were then compared with sales/production/prescription data and between different days of the week using Mann-Whitney U test. RESULTS: Alcohol consumption was significantly higher on Sundays and during the New Year and Russian Christmas period compared to weekdays and Saturdays. Tobacco consumption estimates were largely consistent throughout the week. Morphine was detected by WBE during the monitoring period but was inconsistent with prescription record data. DISCUSSION AND CONCLUSIONS: This study provides evidence for the feasibility of conducting WBE in Russia. Estimates of alcohol consumption derived from WBE were higher than average alcohol sales data for the country. The estimated consumption of nicotine is generally consistent with the production data, with estimates higher than in most other countries. Our results also suggest potential illegal use of opioids (morphine-based) in the population. Given the considerable health and economic costs of substance use in Russia, more extensive WBE testing is recommended to inform and evaluate public health policies.

Proteomic dataset: Profiling of membrane fraction of Escherichia coli isolated from Crohn's disease patients after adhesion and invasion experiments.

Crohn's disease (CD) is a type of inflammatory bowel disease (IDB). The endoscopic picture of Crohn's disease includes thickened submucosa, transmural inflammation, fissuring ulceration, and non-caseating granulomas. Intestinal microbiome dysbiosis has been described systematically in patients with IBD. In recent decades it was detailed that Escherichia coli, especially adherent-invasive E. coli (AIEC) pathotype, has been implicated in the pathogenesis of IBD, including Crohn's disease (Palmela, et al., 2018). In comparison with commensal strains of E. coli, AIEC strains have a large adhesive-invasive potential therefore its surface composition is of great interest. We presented a dataset of the membrane proteins of strains isolated from patients with Crohn's disease. From the set of Escherichia coli isolated from Crohn's disease patients [2] we chose three isolates with strongest AIEC pathotype. We performed proteome-wide LC-MS analysis of membrane fraction of this isolates after invasion or adhesion-invasion to human intestinal CaCo-2 cell line and prior to this (control). The data including LC-MS/MS raw files and exported MaxQuant search results with fasta files were deposited to the PRIDE repository project accession PXD014250.