Effect of Mesenchimal Stem Cells on Apoptosis Indices in Renal Parenchyma during Experimental Stress

Background. Kidneys are extremely sensitive to various environmental factors. Stress disturbs prooxidant-antioxidant balance, causes hyperproduction of reactive oxygen species, changes activity of the nitroxidergic system components, regulating apoptosis. The use of mesenchymal stem cells can normalize functioning of damaged organs in the pathological process.Aim: to assess the effectiveness of mesenchymal stem cells in a single 24-hour immobilization according to the dynamics of apoptosis indices in renal tissue – nitric oxide (NO) and fragmented DNA.Materials and methods. The study included male nonlinear white rats aged 3 to 4 months and weighing 225 ± 25 grams. Experimental stress was modeled by the immobilization of animals in the fixation chambers within 24 hours. The efficacy of cell therapy was determined by the change in the concentration of the tested substances at 1, 3, 7, 14, 21 and 30 days of the experiment.Results. There was a sharp increase in the total amount of nitrates / nitrites and the level of DNA fragmentation in the homogenates of the renal parenchyma after the action of an acute stressor, which may indicate the induction of apoptosis. It was proved that in animals, receiving mesenchymal stem cells as a treatment, the restoration of the studied parameters in the kidney tissue was significantly accelerated in comparison with the controls values.Conclusion. Mesenchymal stem cells protect cells from self-destruction and activate reparation, which makes them promising for further study

Phase Composition and Microstructure of Ti-Nb Alloy Produced by Selective Laser Melting

The phase composition and microstructure of Ti-Nb alloy produced from composite titanium and niobium powder by selective laser melting (SLM) was studied. Produced monolayered Ti-Nb alloy enhanced the formation of fine-grained and medium-grained zones with homogeneous element composition of 36-38% Nb mass interval. Alloy phase composition responded to [beta]-alloy substrate phase (grain size was 5-7 pm) and non-equilibrium martensite [alpha]"- phase (grain size was 0.1-0.7 [mu]m). [alpha]"-phase grains were found along [beta]-phase grain boundaries and inside grains, including decreased niobium content. Alloy microhardness varied within 4200-5500 MPa

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Elucidating the Beneficial Role of PPAR Agonists in Cardiac Diseases

Peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors that bind to DNA and regulate transcription of genes involved in lipid and glucose metabolism. A growing number of studies provide strong evidence that PPARs are the promising pharmacological targets for therapeutic intervention in various diseases including cardiovascular disorders caused by compromised energy metabolism. PPAR agonists have been widely used for decades as lipid-lowering and anti-inflammatory drugs. Existing studies are mainly focused on the anti-atherosclerotic effects of PPAR agonists; however, their role in the maintenance of cellular bioenergetics remains unclear. Recent studies on animal models and patients suggest that PPAR agonists can normalize lipid metabolism by stimulating fatty acid oxidation. These studies indicate the importance of elucidation of PPAR agonists as potential pharmacological agents for protection of the heart from energy deprivation. Here, we summarize and provide a comprehensive analysis of previous studies on the role of PPARs in the heart under normal and pathological conditions. In addition, the review discusses the PPARs as a therapeutic target and the beneficial effects of PPAR agonists, particularly bezafibrate, to attenuate cardiomyopathy and heart failure in patients and animal models

Identification of Novel Epigenetic Markers of Prostate Cancer by NotI-Microarray Analysis

A significant need for reliable and accurate cancer diagnostics and prognosis compels the search for novel biomarkers that would be able to discriminate between indolent and aggressive tumors at the early stages of disease. The aim of this work was identification of potential diagnostic biomarkers for characterization of different types of prostate tumors. NotI-microarrays with 180 clones associated with chromosome 3 genes/loci were applied to determine genetic and epigenetic alterations in 33 prostate tumors. For 88 clones, aberrations were detected in more than 10% of tumors. The major types of alterations were DNA methylation and/or deletions. Frequent methylation of the discovered loci was confirmed by bisulfite sequencing on selective sampling of genes: FGF12, GATA2, and LMCD1. Three genes (BHLHE40, BCL6, and ITGA9) were tested for expression level alterations using qPCR, and downregulation associated with hypermethylation was shown in the majority of tumors. Based on these data, we proposed the set of potential biomarkers for detection of prostate cancer and discrimination between prostate tumors with different malignancy and aggressiveness: BHLHE40, FOXP1, LOC285205, ITGA9, CTDSPL, FGF12, LOC440944/SETD5, VHL, CLCN2, OSBPL10/ZNF860, LMCD1, FAM19A4, CAND2, MAP4, KY, and LRRC58. Moreover, we probabilistically estimated putative functional relations between the genes within each set using the network enrichment analysis