Publications by authors named "K U Klyshnikov"

Unlabelled: is to assess protective capabilities of the polymer coating made of polyvinyl alcohol to prevent leukocyte adhesion to epoxy-treated bovine pericardium, which is used in production of bioprosthetic heart valves.

Materials And Methods: Fragments of unmodified (control) and modified with polyvinyl alcohol epoxy-treated bovine pericardium were incubated in the dedicated chambers connected to a pulsatile flow system (Ibidi GmbH, Germany). During 48 h incubation was conducted in whole donor plasma containing 310 of mononuclear fraction cells.

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Percutaneous coronary intervention, a common treatment for atherosclerotic coronary artery lesions, occasionally results in perforations associated with increased mortality rates. Stents coated with a bioresorbable polymer membrane may offer an effective solution for sealing coronary artery perforations. Additionally, such coatings could be effective in mitigating neointimal hyperplasia within the vascular lumen and correcting symptomatic aneurysms.

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Introduction: The development of next-generation tissue-engineered medical devices such as tissue-engineered vascular grafts (TEVGs) is a leading trend in translational medicine. Microscopic examination is an indispensable part of animal experimentation, and histopathological analysis of regenerated tissue is crucial for assessing the outcomes of implanted medical devices. However, the objective quantification of regenerated tissues can be challenging due to their unusual and complex architecture.

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Background: Decellularized xenogenic scaffolds represent a promising substrate for tissue-engineered vascular prostheses, particularly those with smaller diameters (<6 mm). Despite their benefits, a notable limitation presents itself during decellularization, namely, the diminished mechanical strength that introduces the risk of aneurysmal dilations in the early post-implantation period. This study introduces a strategy for modification the mechanical properties of these biological scaffolds through the forming of an external polymeric reinforcement via thermal extrusion.

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Majority of modern techniques for creating and optimizing the geometry of medical devices are based on a combination of computer-aided designs and the utility of the finite element method This approach, however, is limited by the number of geometries that can be investigated and by the time required for design optimization. To address this issue, we propose a generative design approach that combines machine learning (ML) methods and optimization algorithms. We evaluate eight different machine learning methods, including decision tree-based and boosting algorithms, neural networks, and ensembles.

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