Species delineation based on bacterial genomes is an essential part of the research of prokaryotes. In silico genome-to-genome comparison methods are computationally demanding, but much less tedious and error prone than the wet-lab methods. In this paper, we present a novel method for the delineation of bacterial genomes based on genomic signal processing. The proposed method uses numerical representations of whole bacterial genomes, phase signal and cumulated phase signal, from which four parameters are derived for each genome. The parameters characterize a genome and their calculation is independent of the other genomes comprising a delineation dataset. The delineation itself is processed as a calculation of the parameters' average similarity. The method was statistically verified on 1826 bacterial genomes. A similarity threshold of 96% was set based on the receiver operating characteristic curve that featured sensitivity of 99.78% and specificity of 97.25%. Additionally, comparative analysis on another 33 bacterial genomes was conducted using standard delineation tools as these tools were not able to process the dataset of 1826 genomes using desktop computer. The proposed method achieved comparable or better delineation results in comparison with the standard tools. Besides the excellent delineation results, another great advantage of the method is its small computational demands, which enables the delineation of thousands of genomes on a desktop computer. The calculation of the parameters takes tens of minutes for thousands of genomes. Moreover, they can be calculated in advance by creating a database, meaning the delineation itself is then completed in a matter of seconds.

• Publikační typ
• časopisecké články MeSH

The citizens of German nationality within the interwar period in the Czechoslovakia were integrated in the political, economical and cultural affairs. The German nationality athletes were gathered in DHfL (Der Deutsche Hauptausschuss für Leibesübungen) where one of the main members was HDW (Hauptverband Deutscher Wintersportvereine). This association united almost 16,000 winter outdoor sport followers of German nationality living in the Czechoslovakia out of which the skiers were the most numerous branch. After the year 1927, having stepped out of DHfL, the DTV (Deutscher Turnverband) became the second head office of German sports in The Czechoslovak Republic. However efficient their members were, they still did not appear in the Czechoslovak national team. The biggest problem turned out to be the participation in international competitions where only members of associations included in international organisations could enter. The members of such organisations were almost exclusively “Czechoslovak” associations. For some period only HDW was represented in FIS. An agreement between HDW and SLRČR (Association of Czechoslovak Skiers) was not reached earlier than in 1922 when the competitors of German nationality proved extraordinary performance. They soon became the elite of Czechoslovak representatives. Unfortunately due to the atmosphere after the WWII the results of the German nationality skiers were forgotten or even crossed out from the score sheet. The aim of this article is to outline the delicate dilemma of the German nationality skiers and also to bring out their results in selected important competitions during the interwar period.

• MeSH
• asociace (psychologie) MeSH
• dějiny 20. století MeSH
• lidé MeSH
• lyžování dějiny   MeSH
• menšiny dějiny   psychologie   zákonodárství a právo   MeSH
• mezinárodní spolupráce dějiny   MeSH
• společenskoinstitucionální vztahy zákonodárství a právo   MeSH
• sporty dějiny   MeSH
• Check Tag
• dějiny 20. století MeSH
• lidé MeSH
• Geografické názvy
• Československo MeSH
• Německo MeSH

The dysbiosis of oral microbiome (OM) precedes the clinical signs of periodontal disease. Its simple measure thus could indicate individuals at risk of periodontitis development; however, such a tool is still missing. Up to now, numerous microbial taxa were associated with periodontal health or periodontitis. The outputs of most studies could, nevertheless, be slightly biased from following two reasons: First, the healthy group is often characterized only by the absence of the disease, but the individuals could already suffer from dysbiosis without any visible signs. Second, the healthy/diseased OM characteristics are frequently determined based on average data obtained for whole groups of periodontally healthy persons versus patients. Especially in smaller sets of tested individuals the typical individual variability can thus complicate the unambiguous assignment of oral taxa to respective state of health. In this work the taxonomic composition of OM was evaluated for 20 periodontally healthy individuals and 15 patients with chronic periodontitis. The narrowed selection set of the most diseased patients (confirmed by clinical parameters) and the most distant group of healthy individuals with the lowest probability of dysbiosis was determined by clustering analysis and used for identification of marker taxa. Based on their representation in each individual oral cavity we proposed the numeric index of periodontal health called R/G value. Its diagnostic potential was further confirmed using independent set of 20 periodontally healthy individuals and 20 patients with periodontitis with 95 percent of samples assigned correctly. We also assessed the individual temporal OM dynamics in periodontal health and we compared it to periodontitis. We revealed that the taxonomic composition of the system changes dynamically but generally it ranges within values typical for periodontal health or transient state, but far from values typical for periodontitis. R/G value tool, formulated from individually evaluated data, allowed us to arrange individual OMs into a continuous series, instead of two distinct groups, thus mimicking the gradual transformation of a virtual person from periodontal health to disease. The application of R/G value index thus represents a very promising diagnostic tool for early prediction of persons at risk of developing periodontal disease.

• MeSH
• chronická parodontitida * MeSH
• dysbióza MeSH
• lidé MeSH
• mikrobiota * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Rychlý rozvoj strojového učení (zejména hlubokého) podporuje jeho využití ke zpřesnění screeningu nádorových onemocnění. Hodnocení screeningové mamografie je v Česku prováděno nezávisle dvěma radiology. Zapojení umělé inteligence do algoritmu druhého čtení mamografických snímků přispívá ke zvýšení specifity a senzitivity mamografického vyhodnocování. Neuronová síť dokáže zachytit vstupní obraz a na základě natrénovaných číselných parametrů (vah), kterým je přirazena konkrétní hodnota, definuje vlastnosti, které se ve snímcích hledají, což ovlivňuje konečný výsledek mamografického vyšetření. Cílem zavedení umělé inteligence je lepší záchyt maligních nádorů v časném stadiu a zároveň snížení falešně negativních nebo pozitivních mamografických nálezů s následnou redukcí doplňujících vyšetření, což povede k ekonomickému zefektivnění screeningového procesu.

The rapid development of machine learning, especially deep learning, is fueling radiology's interest in using the technology to improve the accuracy and efficiency of cancer screening . In the Czech Republic, full-scale, organized, and audited mammography screening has been ongoing since September 2002 . The screening interval is set at two years for the group of women over 45 years of age . Evaluation of screening mammography in the Czech Republic is performed inde- pendently by two radiologists . While comparing the level of specific- ity and sensitivity of one radiologist versus one radiologist and AI, previous studies concluded that the overall level was improved . Thus, the inclusion of artificial intelligence in the algorithm of the second reading of mammography images contributes to the increase in the specificity and sensitivity of mammography screening based on the research papers from England, the USA and South Korea . The architecture of the Convolutional Neural Network (ConvNet) is very similar to the conventional neural networks, reflecting the biological behaviour of the brain . The neural network processes an input image and based on trained numerical parameters (weights) with an assigned value, define the features to look for in the images, which enables to evaluate the mammography screening . The goal of introducing AI into practice is that, in combination with humans in the evaluation process, it may lead to a higher level of detection of early-stage malignant tumors and to a reduction in false negative or positive mammographic findings . Additionally, it is expected to reduce follow-up examinations after the screening mammography making the screening process more cost effective.

• MeSH
• lidé MeSH
• mamografie MeSH
• nádory prsu * diagnostické zobrazování   epidemiologie   prevence a kontrola   MeSH
• nervová síť abnormality   diagnostické zobrazování   ultrastruktura   MeSH
• plošný screening MeSH
• umělá inteligence * dějiny   MeSH
• Check Tag
• lidé MeSH
• ženské pohlaví MeSH

Artificial intelligence (AI) has significantly impacted numerous industries, including health care, dentistry, and specifically prosthodontics. This review focuses on AI's role in prosthodontics, detailing its use in diagnosis, design, and manufacturing. AI-driven systems analyze intraoral scans, improve prosthetic planning, and aid in robotic procedures. Emerging technologies, such as generative AI for prosthetic design and AI-driven material innovation, are discussed alongside the ethical and regulatory challenges facing broader adoption. The review highlights AI's potential to transform prosthodontic workflows, facilitating more accurate, efficient, and personalized care, while also pointing to future developments such as real-time monitoring and enhanced collaboration platforms.

• MeSH
• design s pomocí počítače MeSH
• lidé MeSH
• stomatologická protetika * metody   MeSH
• umělá inteligence * MeSH
• zubní protéza - design metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

V článku je popsán vliv psychické zátěže na psychosomatické veličiny (srdeční frekvence, tlak krve, elektromyografické potenciály, kožní odpor). Psychologická zátěž byla vyvolána dvěma testy. První zátěžový test je zaměřen na zjištění úrovně verbální, percepční a numerické logiky, prostorové představivosti, technické a analytické schopnosti (testl). Jako druhý je použit tzv. sedmičkový test (test 2), který ovlivňuje pozornostní a paměťovou funkci při stresových podnětech. Klasifikace respondentů byla provedena: a) z psychologických dotazníků, b) z výsledků měření. Pro zpracování výsledků měření bylo použito logistické regresní analýzy, expertního systému, strojového učení a kombinace expertního systému se strojovým učením. Tato práce je úvodní, v následujících pracích budou jednotlivé metody podrobně rozpracovány.

The infiuence of a psychical load on psychosomatic quantities (heart beat frequency, blood pressure, electromyographic potentials, skin resistance) are described. The psychologie load is represented by two tests. The first one is intended for determination of verbal, perception a numerical logic level, 3D space imagination, and technical and analytical abilities (test 1). The second one is presented by the so-called sevens-test (test 2), which has an infiuence on the attention and memory functions during the time of stress. The classification was performed: a) using the psychological questionnaires, b) using the measurements results. Logistic regression analysis, expert system, machine learning and the combination of an expert systém and machine learning were used for the measurement results evaluation. This is an introductory the article, the individual methods will be explained in details in the following article.

• MeSH
• expertní systémy MeSH
• fyziologický stres MeSH
• klasifikace MeSH
• lidé MeSH
• psychofyziologie MeSH
• psychologické testy metody   MeSH
• regresní analýza MeSH
• umělá inteligence MeSH
• Check Tag
• lidé MeSH

Pathophysiological recordings of patients measured from various testing methods are frequently used in the medical field for determining symptoms as well as for probability prediction for selected diseases. There are numerous symptoms among the Parkinson's disease (PD) population, however changes in speech and articulation – is potentially the most significant biomarker. This article is focused on PD diagnosis classification based on their speech signals using pattern recognition methods (AdaBoost, Bagged trees, Quadratic SVM and k-NN). The dataset investigated in the article consists of 30 PD and 30 HC individuals' voice measurements, with each individual being represented with 2 recordings within the dataset. Training signals for PD and HC underwent an extraction of relatively well-discriminating features relating to energy and spectral speech properties. Model implementations included a 5-fold cross validation. The accuracy of the values obtained employing the models was calculated using the confusion matrix. The average value of the overall accuracy = 82.3 % and averaged AUC = 0.88 (min. AUC = 0.86) on the available data.

• MeSH
• algoritmy MeSH
• analýza dat MeSH
• hlas MeSH
• lidé MeSH
• Parkinsonova nemoc * diagnóza   MeSH
• řízené strojové učení MeSH
• strojové učení * MeSH
• umělá inteligence * MeSH
• Check Tag
• lidé MeSH

The paper describes a software tool created to inspect the anatomical structures of any segmented voxel model of the human body for use in numerical analyses of the interaction of non-ionizing electromagnetic radiation with a metallic implant. A voxel model is a three-dimensional representation of the human body model in the form of a numerical array of indices that identify each element as belonging to a particular tissue, organ, or anatomical part. The process of virtual implant placement within these models while maintaining their anatomical limitations is complex and time-consuming. We have created a software tool in the MATLAB environment to simplify and speed up this process. As a representative case, we used the developed tool to identify three implantation sites of pacing electrodes within the cardiovascular system of the available AustinMan and AustinWoman models.

• MeSH
• anatomické modely MeSH
• biomedicínský výzkum MeSH
• digitální technologie metody   přístrojové vybavení   MeSH
• kardiostimulace umělá metody   MeSH
• kardiovaskulární nemoci diagnostické zobrazování   prevence a kontrola   MeSH
• lidské tělo * MeSH
• počítačová simulace MeSH
• software * trendy   MeSH
• Publikační typ
• práce podpořená grantem MeSH
• přehledy MeSH

Biomechanics is one of the branches of science contributing significantly not only to increasing our knowledge of the development of living systems but also to our understanding of the relevant laws of mechanics and their mechanical functions. Important anatomical and biomechanical data as related to the individual functions of the organism and their biomechanical significance are focussed on in this publication. The locomotor and circulatory apparatus and the identification of the mechanical properties of living tissue and materials used in osteosynthesis and alloarthroplasty are among the fields covered. The phenomena observed in the cardiovascular system are described using the basic equation of motion of viscous fluids. Suitable hydraulic models are proposed for investigation and testing of vascular grafts, artificial cardiac valves and artificial heart. Important research data are presented about biomechanical structures of the locomotoric apparatus, and joint rheology. A section is included presenting the fundamentals of the biomechanical analysis in criminology and in bioballistics.

• Klíčová slova
• systém kardiovaskulární - biomechanika - texty učební postgraduální,

• Konspekt
• Biochemie. Molekulární biologie. Biofyzika
• NLK Obory
• fyzika, biofyzika
• fyziologie
• kardiologie
• angiologie

Infection in apple leaves is typically brought on by unanticipated weather conditions such as rain, hailstorms, draughts, and fog. As a direct consequence of this, the farmers suffer a significant loss of productivity. It is essential to be able to identify apple leaf diseases in advance in order to prevent the occurrence of this disease and minimise losses to productivity caused by it. The research offers a bibliometric analysis of the effectiveness of artificial intelligence in diagnosing diseases affecting apple leaves. The study provides a bibliometric evaluation of apple leaf disease detection using artificial intelligence. Through an analysis of broad current developments, publication and citation structures, ownership and cooperation patterns, bibliographic coupling, productivity patterns, and other characteristics, this scientometric study seeks to discover apple diseases. Nevertheless, numerous exploratory, conceptual, and empirical studies have concentrated on the identification of apple illnesses. However, given that disease detection is not confined to a single field of study, there have been very few attempts to create an extensive science map of transdisciplinary studies. In bibliometric assessments, it is important to take into account the growing amount of research on this subject. The study synthesises knowledge structures to determine the trend in the research topic. A scientometric analysis was performed on a sample of 214 documents in the subject of identifying apple leaf disease using a scientific search technique on the Scopus database for the years 2011-2022. In order to conduct the study, the Bibliometrix suite's VOSviewer and the web-based Biblioshiny software were also utilised. Important journals, authors, nations, articles, and subjects were chosen using the automated workflow of the software. Furthermore, citation and co-citation checks were performed along with social network analysis. In addition to the intellectual and social organisation of the meadow, this investigation reveals the conceptual structure of the area. It contributes to the body of literature by giving academics and practitioners a strong conceptual framework on which to base their search for solutions and by making perceptive recommendations for potential future research areas.

• MeSH
• bibliometrie MeSH
• databáze faktografické MeSH
• Fabaceae * MeSH
• lidé MeSH
• Malus * MeSH
• software MeSH
• umělá inteligence MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH