No abstract

No abstract

Computational machine learning, especially selfenhancing algorithms, prove remarkable effectiveness in applications, including cardiovascular medicine. This review summarizes and cross-compares the current machine learning algorithms applied to electrocardiogram interpretation. In practice, continuous real-time monitoring of electrocardiograms is still difficult to realize. Furthermore, automated ECG interpretation by implementing specific artificial intelligence algorithms is even more challenging. By collecting large datasets from one individual, computational approaches can assure an efficient personalized treatment strategy, such as a correct prediction on patient-specific disease progression, therapeutic success rate and limitations of certain interventions, thus reducing the hospitalization costs and physicians' workload. Clearly such aims can be achieved by a perfect symbiosis of a multidisciplinary team involving clinicians, researchers and computer scientists. Summarizing, continuous cross-examination between machine intelligence and human intelligence is a combination of precision, rationale and highthroughput scientific engine integrated into a challenging framework of big data science.

Atomic force microscopy (AFM) is a pioneer imaging technique commonly employed by biological researchers in detection of the properties of biological membranes over the last decade. The AFM findings distinguish its applicability from the conventional methods, such as: confocal, multiphotons, electron microscopy, etc. as well as from the mechanical methods (compression and indentation test, extensiometry, etc.). With its high resolution (below 10 nm), AFM has emerged as a powerful tool in obtaining the nanostructural details and biomechanical properties of heart tissue. The composition of extracellular matrix is essential for heart compliance and its mechanical function. Here, we illustrate the surface morphology, its structural assembling and the mechanical properties of a myocardial infarction scar section aquired via AFM, in dry conditions. The cross section through the mature myocardial scar of mice after myocardial infarction shows that the embedded fibrils into the tissue matrix of a mature scar overlap at some sites, and form network-like structures. The nano-fibrils surface shows defined structural periodicity. A cross-section along the axial fibrilar direction gives an average D-periodic banding pattern of approximately 50,3 nm (± 6,2 nm std.). As future perspective, yet uncovered morphological and mechanical investigations, correlated with functional studies, open a new window for understanding pathological mechanisms.

Белорусская медицинская академия последипломного образования, г. Минск, Республика Беларусь История статуэтки «Женщина с болезнью Паркинсона» Резюме. Представлена история создания гипсовой статуэтки «Женщина с болезнью Паркинсона».