The processes of globalization and integration, as well as technologies and computerization, occurring in public life cause significant changes in all its spheres, especially in medicine. Nowadays, computerization of health-care facilities has become the norm of their development. However, rapid technological change requires the modernization of medical education system, revising the approaches to the training of competitive medical professionals who will able to adapt quickly to changes in the field of health care. The research issue concerns the processes of future medical professionals’ training. The importance of telemedicine in health-care systems of Ukraine and Poland is justified. It is suggested that the problem of telemedicine and e-health usage in the process of medical professionals’ training in Ukraine is not studied sufficiently and does not have practical consolidation. The didactic methodology of medical specialties students training for the use of telemedicine technologies in future professional activities is developed.
The aim of this article was to show an Electronic Health Record for elderly patients that was prepared for tablets with Android system. The program can be used in case of collecting patient data that comes from the Comprehensive Geriatric Assessment – the multidisciplinary diagnostic tool which is performed among older adults in hospital and outpatient settings. The application was designed for devices with Android system using JellyBean, Kitkat or Lollipop system version. The app allowed to perform, save, edit, view and send survey results. Additionally, it had an option of creating an account with different permission levels. The program was created to facilitate and accelerate the work of a physician who is obliged to complete a Comprehensive Geriatric Assessment card with the patient. It was intended to replace the filling out of a paper questionnaire, in which the doctor must personally sum up all the results, with a tool that will be available on tablets and which enables to complete and evaluate the results of medical examination faster than during performing the questionnaire in a traditional way.
Among still comparatively few G protein-coupled receptors, the adenosine A 2A receptor has been co-crystallized with several ligands, agonists as well as antagonists. It can thus serve as a template with a well-described orthosteric ligand binding region for adenosine receptors. As not all subtypes have been crystallized yet, and in order to investigate the usability of homology models in this context, multiple adenosine A 1 receptor (A 1 AR) homology models had been previously obtained and a library of lead-like compounds had been docked. As a result, a number of potent and one selective ligand toward the intended target have been identified. However, in in vitro experimental verification studies, many ligands also bound to the A 2A AR and the A 3 AR subtypes. In this work we asked the question whether a classification of the ligands according to their selectivity was possible based on docking scores. Therefore, we built an A 3 AR homology model and docked all previously found ligands to all three receptor subtypes. As a metric, we employed an in vitro/in silico selectivity ranking system based on taxicab geometry and obtained a classification model with reasonable separation. In the next step, the method was validated with an external library of, selective ligands with similarly good performance. This classification system might also be useful in further screens.
The GPR18 receptor, often referred to as the N-arachidonylglycine receptor, although assigned (along with GPR55 and GPR119) to the new class A GPCR subfamily-lipid receptors, officially still has the status of a class A GPCR orphan. While its signaling pathways and biological significance have not yet been fully elucidated, increasing evidence points to the therapeutic potential of GPR18 in relation to immune, neurodegenerative, and cancer processes to name a few. Therefore, it is necessary to understand the interactions of potential ligands with the receptor and the influence of particular structural elements on their activity. Thus, given the lack of an experimentally solved structure, the goal of the present study was to obtain a homology model of the GPR18 receptor in the inactive state, meeting all requirements in terms of protein structure quality and recognition of active ligands. To increase the reliability and precision of the predictions, different contemporary protein structure prediction methods and software were used and compared herein. To test the usability of the resulting models, we optimized and compared the selected structures followed by the assessment of the ability to recognize known, active ligands. The stability of the predicted poses was then evaluated by means of molecular dynamics simulations. On the other hand, most of the best-ranking contemporary CADD software/platforms for its full usability require rather expensive licenses. To overcome this down-to-earth obstacle, the overarching goal of these studies was to test whether it is possible to perform the thorough CADD experiments with high scientific confidence while using only license-free/academic software and online platforms. The obtained results indicate that a wide range of freely available software and/or academic licenses allow us to carry out meaningful molecular modelling/docking studies.
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