Warburg micro syndrome type 1 associated with peripheral neuropathy and cardiomyopathy

The Warburg micro syndrome (WARBM) is a genetically heterogeneous syndrome linked to at least 4 loci. At the clinical level, WARBM is characterized by microcephaly, microphthalmia, microcornea, congenital cataracts, corpus callosum hypoplasia, severe mental retardation, and hypogonadism. In some families additional clinical features have been reported. The presence of uncommon clinical features (peripheral neuropathy, cardiomyopathy) may result in misdirected molecular diagnostics. Using the next generation sequencing approach (NGS), we were able to diagnose WARBM1 syndrome by detection of a new mutation within the RAB3GAP1 gene. We have detected some DNA variants which may be responsible for cardiomyopathy. We did not find any obvious pathogenic mutation within a set of genes known to be responsible for hereditary motor and sensory neuropathy (HMSN). We conclude that: (i) in clinically delineated syndromes, a classical single-gene oriented approach may be not conclusive especially in the presence of rare clinical features, (ii) peripheral neuropathy and cardiomyopathy are rare additional symptoms coexisting with WARBM1, (iii) a pleiotropic effect of a single point mutation is sufficient to be causative for WARBM1 and (iv) more WARBM-affected patients should be reported to delineate a complete phenotype

Metabolic and thermogenic properties of the subcutaneous white adipose tissue of wild and laboratory rodents

For the first time biochemical analysis of inguinal adipose tissue of korean mouse (Apodemus peninsulae) and short-tailed vole (Microtus agrestis) have performed. Expression of uncoupling protein UCP1 in inguinal fat was combined with high metabolic and oxidative activity of this fat depot in wild rodents, in comparison with laboratory mice. Studies of the adipose tissues in animals from natural populations can be useful for the elucidating of the physiological norm of their functioning and for the development of regimes for the prevention and correction of metabolic disorders

Program for sound generation based on image color spectrum with using the recurrent neural network

This work is devoted to development and approbation of the program for sound generation based on image color spectrum with using the recurrent neural network. The work contains a description of the transition between color and music characteristics, the rationale for choosing and the description of a recurrent neural network. The choices of the neural network implementation technology as well as the results of the experiment are described

Evaluation of Business Model Innovation towards Industry 4.0 via Cross-industry

Innovation is one of the key drivers of growth, development, and profitability, which increases competitive advantages and has recently been moving towards industry 4.0 technologically. This motivates companies to update their business models (BM) towards industry 4.0. Moreover, there is a technique with the primary characteristics for achieving this motivation called "cross-industry innovation". Cross-industry innovation is a new method of innovation that concerns the creative translation and imitation of existing solutions from other industries for responding to the needs of the current market, sectors, areas, or domains. The challenge is to find out how far managers can rely on that to innovate their BM towards Industry 4.0. The aim of this study was to investigate the application of cross-industry innovation for designing industry 4.0 BM and explore the extent to which companies can rely on it as it has not been used for this purpose previously. This study utilized a database analysis to compare cross-industry innovation practices with industry 4.0 BM's characteristics in terms of value proposition, value creation, and value capture levels. In addition, some interviews were conducted with companies that had previously implemented cross-industry innovation to validate and generalize the results. The results indicated that cross-industry innovation practices can better fulfill flexible and dynamic networks, connected information flows, high efficiency, high scalability, and high availability in terms of value creation as well as variabilization of prices and costs in terms of value capture. Therefore, it demonstrated that cross-industry innovation was a more dependable and applicable strategy for designing the BM of Industry 4.0 than current practices

Demands and challenges for SME regarding the human-centred implementation of innovative technologies and AI

Digitization is constantly affecting the working world and is of enormous interest in many fields of science. But to what extent are innovative technologies actually being applied in regional SMEs and what are the obstacles to their introduction? From a psychological point of view, it is essential to consider the employee's health and the effects of innovative technologies on their everyday work. The aim of using innovative technologies should not be to completely replace human labor or to dequalify employees, but to relieve the workforce and free up working time for more meaningful activities. One concept that should be included in the human-centered design of human-machine interaction in artificial intelligence is the HAI-MMI concept (Huchler, 2020), which offers starting points for high-quality collaboration at various levels. To reduce the gap between science and industry, this paper focuses on the actual demands of SME in the Aachen region in Germany referring to a requirements analysis within the research project AKzentE4.0 (N = 50 SME) and discusses how appropriate innovative technologies of the Industry 4.0 and AI can be implemented and deployed in a human-centred way. Moreover, the establishment of a Human Factors Competence Center for Employment in Industry 4.0 is outlined, which is meant to be used for the dissemination of research results from the project and should narrow the gap between science and industry in the long run

Conceptualization of an AI-based Skills Forecasting Model for Small and Medium-Sized Enterprises (SMEs)

Forecasting-based skills management, which is oriented to the respective corporate goals, is gaining enormous importance as a central management tool. The aim is to predict future skills requirements and match them with existing interorganizational skills. Companies are required to anticipate changes in markets, industries, and technologies at an early stage as well as to identify changes in job profiles within an occupational profile by tapping into and evaluating various data sources. Based on these findings, they can then make informed decisions regarding skill gaps, for example, to implement targeted further training measures. Forecasting-based skills management offers the opportunity to optimally qualify employees for constantly changing tasks. At the same time, however, the targeted development of such skills requires a high level of time, financial and personnel resources, which small and medium-sized enterprises (SMEs) generally do not have at their disposal. In addition, many SMEs are not yet aware of the importance of this issue. Within the framework of research and industrial projects of the Smart Work department at the FIR (Institute for Industrial Management) at the RWTH Aachen University, an AI-based skills forecasting tool will be developed. The goal of the paper is to conceptualize the future machine learning method, that is able to generate individualized skills forecasts and recommendations for SMEs. This is achieved by linking societal forecasts and sector trends with company-specific conditions and skills. In order to generate a corresponding database, the derivation system is made available to various companies (large companies and SMEs) in order to obtain as many data sets as possible. The data sets obtained via the derivation system are then used as training data sets for the machine learning method, with the help of which an automatic derivation of competencies depending on new trends is to be made possible

Patofizjologiczne mechanizmy migotania przedsionków (AF) jako podstawa skutecznego leczenia w dążeniu do polepszenia jakości życia chorych w świetle aktualnych wytycznych ESC (European Society of Cardiology)

Migotanie przedsionków (atrial fibrillation, AF) należy do najczęstszych przyczyn nagłych zgonów, udarów mózgu i niewydolności serca, a zapadalność na AF w najbliższych latach jeszcze wzrośnie. Przyczynami choroby są: predyspozycje genetyczne, cukrzyca, niewydolność serca, otyłość, choroba wieńcowa, nadciśnienie tętnicze i starzenie się. Zmiany patofizjologiczne AF obejmują przebudowę przedsionków i naczyń wieńcowych, odczyn zapalny, niedokrwienie oraz zaburzenia gospodarki wapniowej kardiomiocytów. Jakość życia chorych z AF jest istotnie gorsza niż u osób zdrowych. Dzieje się tak wskutek osłabienia, kołatania serca, duszności, ucisku w klatce piersiowej i zaburzeń snu. Chorobie towarzyszy także stres psychospołeczny. Zintegrowane leczenie AF obejmuje 4 filary: zaangażowanych chorych, zespoły wielodyscyplinarne, narzędzia technologiczne i dostęp do wszystkich możliwych terapii. Rozpoznanie oraz kontrola chorób współistniejących, leczenie przeciwzakrzepowe, kontrola rytmu serca i jego częstotliwości, a także edukacja istotnie poprawiają rokowanie i jakość życia chorych. Doraźne przywrócenie rytmu zatokowego i jego utrzymanie pozostaje integralną częścią postępowania. W celu zapobiegania nawrotowi AF, w razie współistniejącej niewydolności serca ze zmniejszoną frakcją wyrzutową, stosuje się leki nieantyarytmiczne (ACEI/ARB, LBA), podobnie jak ma to miejsce w kardiomiopatii nadciśnieniowej (ACEI/ARB). Leczenie zabiegowe w AF ma na celu całkowitą izolację żył płucnych, co przynosi skuteczniejszą kontrolę rytmu serca niż farmakoterapia. Zabieg przezcewnikowy jest leczeniem z wyboru, a gdy jest on nieskuteczny lub przyjmowane leki nie pomagają, przeprowadza się zabieg chirurgiczny. Wiele współistniejących chorób zwiększa ryzyko wystąpienia, nawrotów i powikłań AF. Ich identyfikacja i leczenie odgrywają ważną rolę w zapobieganiu AF oraz w optymalnym prowadzeniu chorych.Atrial fibrillation (AF) is one o f the most common causes o f sudden death, cerebral stroke and heart failure. AF morbidity will increase in the coming years. The disease is precipitated by gene predisposition, diabetes, heart failure, obesity, coronary disease, hypertension and aging. Pathophysiological changes include atrial and coronary arteries remodelling, inflammation, and cardiomyocyte calcium metabolism disorders. Life quality in AF patients is significantly impaired, as compared to healthy people, due to weakness, heart palpitation, dyspnea, chest discomfort and sleep disorders; psychosocial stress occurs as well. Integrated AF management requires 4 areas: patient involvement, multidisciplinary teams, technological tools and access to all currently possible therapies. Diagnosis and control of coexisting diseases, anticoagulant treatment, heart rhythm and heart rate control, as well as education, remarkably improve AF prognosis and life quality. Casual recovery and maintaining the sinus rhythm is important as a part of the integral approach. Prevention of AF recurrence include non-antiarrhythmic medicines (ACEI/ARB, LBA) in heart failure with decreased ejection fraction, as well as in hypertensive cardiomyopathy (ACEI/ ARB). Surgical treatment aims the total isolation of pulmonary veins with more efficient heart rhythm control, as compared to pharmacological management. In paroxysmal AF, percutaneous intervention is a treatment of choice. Surgery can be necessary, if percutaneous intervention either pharmacotherapy is unsuccessful. Coexisting diseases elevate the risk of AF, including AF recurrence and complications. They need to be properly identified and treated in order to optimize the patient management