Hidden Stochastic Nature of a Single Bacterial Motor

The rotary flagellar motor of Escherichia coli bacterium switches stochastically between the clockwise (CW) and counterclockwise (CCW) direction. We found that the CW and CCW intervals could be described by a gamma distribution, suggesting the existence of hidden Markov steps preceding each motor switch. Power spectra of time series of switching events exhibited a peaking frequency instead of the Lorentzian profile expected from standard kinetic two-state models. Our analysis indicates that the number of hidden steps may be a key dynamical parameter underlying the switching process in a single bacterial motor as well as in large cooperative molecular systems.Molecular and Cellular BiologyPhysic

Review Paper Flavonoids and mechanisms of their anticancer action

Abstract: Numerous studies collected over the last decade indicate the beneficial health effects of flavonoids. The diseases that could be potentially cured with flavonoids include cancer, cardiovascular disease, diabetes, and neurodegenerative diseases. Flavonoids are natural compounds found in fruits, vegetables, tea, and plant leaves.They are present in every day diets. All flavonoids possess a similar core structure that consists of benzo-γ-pyrone with an attached benzene ring. The position at which the benzene ring is attached andthe presence of hydroxyl and methyl groups define the structural diversity of the flavonoids and a variety of the exerted biochemical effects. A π-conjugated structure of flavonoids along with a number of benzene ring substituents defines the active participation of flavonoids in redoxreactions and, as a result, the exhibition of antioxidant and pro-oxidant properties. While antioxidant properties appear to be favorable in maintaining good health, it is the pro-oxidant activity of flavonoids that forms the basis of numerous reactions leading to cancer preventive effects. The reactions of flavonoids with metal cations or peroxidases may result in the formation of polyphenol radicals that damage DNA and proteins, thus stimulating apoptosis. Flavonoids may also modify the activity of various enzymes, therefore modulating metabolism and affecting the dynamics of apoptotic cellular death. The aim of the present review is to summarize recent advances in understanding (1) the biochemical basis of the pro-oxidant properties of flavonoids brought about by metal cations and peroxidases, (2) the interactions of flavonoids with enzymes metabolizing xenobiotics, specifically carcinogens, and (3) the influence of flavonoids on the activity of drug efflux transporters. A special attention is devoted to the relationship between flavonoid structure and its potential pro-oxidant and anticancer activity

Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults

Metabolomics is a promising technology for the application of translational medicine to cardiovascular risk. Here, we applied a liquid chromatography/tandem mass spectrometry approach to explore the associations between plasma concentrations of amino acids, methylarginines, acylcarnitines, and tryptophan catabolism metabolites and cardiometabolic risk factors in patients diagnosed with arterial hypertension (HTA) (n = 61), coronary artery disease (CAD) (n = 48), and non-cardiovascular disease (CVD) individuals (n = 27). In total, almost all significantly different acylcarnitines, amino acids, methylarginines, and intermediates of the kynurenic and indolic tryptophan conversion pathways presented increased (p< 0.05) in concentration levels during the progression of CVD, indicating an association of inflammation, mitochondrial imbalance, and oxidative stress with early stages of CVD. Additionally, the random forest algorithm was found to have the highest prediction power in multiclass and binary classification patients with CAD, HTA, and non-CVD individuals and globally between CVD and non-CVD individuals (accuracy equal to 0.80 and 0.91, respectively). Thus, the present study provided a complex approach for the risk stratification of patients with CAD, patients with HTA, and non-CVD individuals using targeted metabolomics profiling