Disruption of homeostasis can increase the amount of free radicals formed during metabolic processes. This phenomenon known as oxidative stress can have numerous negative outcomes. The role of dietary antioxidants is to help the prevention of oxidative stress. We investigated free radical scavenging capacity of six structurally similar anthraquinones (alizarin, purpurin, chrysophanol, emodin, aloe-emodin and 1,3,8-trihydroxyanthraquinone) for inactivating a set of ten hydroxy and peroxy free radicals. The antioxidant capacity of anthraquinones was estimated by considering Gibbs free energy of three studied reaction mechanisms: hydrogen atom transfer (HAT), single-electron transfer followed by proton transfer (SET-PT) and sequential proton loss electron transfer (SPLET). The geometry of all participants in chemical reactions was optimized using the M06-2X/6-311++G(d,p) level of theory. Benzene, pentyl ethanoate, dimethyl sulfoxide and water were used to investigate the impact of solvent polarity on the thermodynamic feasibility of antiradical reactions. It was found that HAT and SPLET mechanisms are operative and competitive, while the SET-PT mechanism is not thermodynamically plausible. Among the studied anthraquinones, AL and PU showed the highest scavenging capacity. Their reactivity toward free radicals decreases as follows:˙OH > (CH₃)₃C–O˙ ≈ ˙OCH₃ > CCl₃–O–O˙ > PhO˙ > ˙OOH ≈ CH₂ CH–O–O˙ ≈ CH₃–O–O˙ ≈ CH₂ CH–CH₂–O–O˙ ≫ O₂˙⁻. Inhibition activity of anions of the selected six anthraquinones toward P-glycoproteins was estimated using docking analysis. The obtained results suggest that all the investigated compounds are potential inhibitors of P-glycoproteins under physiological conditions, indicating them as potential protectors against patient resistance toward various anticancer drugs.

As apoptosis and genome instability in children with autoimmune diseases (AIDs) are insufficiently investigated, we aimed to analyse them in peripheral blood lymphocytes (PBLs) of children and adolescents with Hashimoto's thyroiditis (HT), Graves' disease (GD) and type 1 diabetes mellitus (T1DM), including possible factors that could affect their occurrence. The study population included 24 patients and 19 healthy controls. Apoptotic cells were detected using an Annexin V-FITC/7-AAD kit. Genome instability was measured as micronuclei (MNs) frequency using the cytokinesis-block MN assay. In addition, comet assay was performed for determination of genome instability as genome damage index (GDI) in new subpopulation of patients with T1DM. The percentage of apoptotic PBLs in patients with AID was significantly lower than in control subjects. There was a positive correlation between thyroid-stimulating homone (TSH) concentration and the proportion of cells in late stage apoptosis in patients with autoimmune thyroid diseases (AITDs). The MN frequency in patients was significantly higher than in controls. Individuals with HT or T1DM had a significantly higher MN frequency than those with GD. Similarly, the value of GDI in patients with T1DM was significantly higher than in controls. The level of apoptosis was positively correlated with MN frequency as well as with GDI in patients with AID. In conclusion, children with AITD (HT and GD) and T1DM have a significantly lower level of apoptosis in PBLs and significantly higher MN frequency as GDI than healthy subjects. Apoptosis and the level of genome instability in these patients with AID are positively correlated.

THE ASSOCIATION OF CIRCULATING SCLEROSTIN LEVEL WITH MARKERS OF BONE METABOLISM IN PATIENTS WITH THYROID DYSFUNCTION

Cardiovascular diseases (CVDs) are a leading cause of death. If not treated in a timely manner, cardiovascular diseases can cause a plethora of major life complications that can include disability and a loss of the ability to work. Globally, acute myocardial infarction (AMI) is responsible for about 3 million deaths a year. The development of strategies for prevention, but also the early detection of cardiovascular risks, is of great importance. The fractional flow reserve (FFR) is a measurement used for an assessment of the severity of coronary artery stenosis. The goal of this research was to develop a technique that can be used for patient fractional flow reserve evaluation, as well as for the assessment of the risk of death via gathered demographic and clinical data. A classification ensemble model was built using the random forest machine learning algorithm for the purposes of risk prediction. Referent patient classes were identified by the observed fractional flow reserve value, where patients with an FFR higher than 0.8 were viewed as low risk, while those with an FFR lower than 0.8 were identified as high risk. The final classification ensemble achieved a 76.21% value of estimated prediction accuracy, thus achieving a mean prediction accuracy of 74.1%, 77.3%, 78.1% and 83.6% over the models tested with 5%, 10%, 15% and 20% of the test samples, respectively. Along with the machine learning approach, a numerical approach was implemented through a 3D reconstruction of the coronary arteries for the purposes of stenosis monitoring. Even with a small number of available data points, the proposed methodology achieved satisfying results. However, these results can be improved in the future through the introduction of additional data, which will, in turn, allow for the utilization of different machine learning algorithms.