Publications by authors named "M Zima"

Objectives: Non-communicable diseases are estimated to account for 90 % of total deaths and 19 % of premature deaths in Slovakia. Major preventable risk factors of premature mortality are overweight, obesity and alcohol consumption.

Background: Screening of risk factors related to alcoholic and nonalcoholic fatty liver diseases (AFLD and NAFLD, respectively) in Slovak outpatients with liver disease.

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Numerous conditions, including cancer, diabetes, aging, and atherosclerosis, are thought to be associated with oxidative stress. Oxidative stress is defined as a persistent imbalance between oxidation and antioxidation, resulting in the damage of cellular macromolecules and is often considered to be involved in wide variety of human diseases. However, the current literature is very heterogeneous making it rather difficult to draw general conclusions.

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Metformin is widely prescribed as a first-choice antihyperglycemic drug for treatment of type 2 diabetes mellitus, and recent epidemiological studies showed its utility also in cancer therapy. Although it is in use since the 1970s, its molecular target, either for antihyperglycemic or antineoplastic action, remains elusive. However, the body of the research on metformin effect oscillates around mitochondrial metabolism, including the function of oxidative phosphorylation (OXPHOS) apparatus.

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In the clinical diagnostic laboratories of Chelyabinsk and St. Petersburg evaluation of detection rate of Mycoplasma hominis and Ureaplasma spp. was implemented using technique of polymerase chain reaction and cultural method.

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The goal of this paper is to describe a robust artifact removal (RAR) method, an automatic sequential procedure which is capable of removing short-duration, high-amplitude artifacts from long-term neonatal EEG recordings. Such artifacts are mainly caused by movement activity, and have an adverse effect on the automatic processing of long-term sleep recordings. The artifacts are removed sequentially in short-term signals using independent component analysis (ICA) transformation and wavelet denoising.

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