Novel Noninvasive Paraclinical Study Method for Investigation of Liver Diseases.

Based on a prior university patent, the authors developed a novel type of bioimpedance-based test method to noninvasively detect nonalcoholic fatty liver disease (NAFLD). The development of a new potential NAFLD diagnostic procedure may help to understand the underlying mechanisms between NAFLD and severe liver diseases with a painless and easy-to-use paraclinical examination method, including the additional function to detect even the earlier stages of liver disease. The aim of this study is to present new results and the experiences gathered in relation to NAFLD progress during animal model and human clinical trials.

Novel probiotic treatment of autism spectrum disorder associated social behavioral symptoms in two rodent models.

The prevalence of autism spectrum disorder (ASD) has rapidly increased in the past decades, and several studies report about the escalating use of antibiotics and the consequent disruption of the gastrointestinal microbiome leading to the development of neurobehavioral symptoms resembling to those of ASD. The primary purpose of this study was to investigate whether depletion of the gastrointestinal microbiome via antibiotics treatment could induce ASD-like behavioral symptoms in adulthood. To reliably evaluate that, validated valproic acid (VPA) ASD animal model was introduced. At last, we intended to demonstrate the assessed potential benefits of a probiotic mixture (PM) developed by our research team. Male Wistar rats were used to create antibiotics treated; antibiotics and PM treated; PM treated, VPA treated; VPA and PM treated; and control groups. In all investigations we focused on social behavioral disturbances. Antibiotics-induced microbiome alterations during adulthood triggered severe deficits in social behavior similar to those observed in the VPA model. Furthermore, it is highlighted that our PM proved to attenuate both the antibiotics- and the VPA-generated antisocial behavioral symptoms. The present findings underline potential capacity of our PM to improve social behavioral alterations thus, indicate its promising therapeutic power to attenuate the social-affective disturbances of ASD.

Physical Validation of a Residual Impedance Rejection Method during Ultra-Low Frequency Bio-Impedance Spectral Measurements.

Accurate and reliable measurement of the electrical impedance spectrum is an essential requirement in order to draw relevant conclusions in many fields and a variety of applications; in particular, for biological processes. Even in the state-of-the-art methods developed for this purpose, the accuracy and efficacy of impedance measurements are reduced in biological systems, due to the regular occurrence of parameters causing measurement errors such as residual impedance, parasitic capacitance, generator anomalies, and so on. Recent observations have reported the necessity of decreasing such inaccuracies whenever measurements are performed in the ultra-low frequency range, as the above-mentioned errors are almost entirely absent in such cases. The current research work proposes a method which can reject the anomalies listed above when measuring in the ultra-low frequency range, facilitating data collection at the same time. To demonstrate our hypothesis, originating from the consideration of the determinant role of the measuring frequency, a physical model is proposed to examine the effectiveness of our method by measuring across the commonly used vs. ultra-low frequency ranges. Validation measurements reflect that the range of frequencies and the accuracy is much greater than in state-of-the-art methods. Using the proposed new impedance examination technique, biological system characterization can be carried out more accurately.

Measurement system with real time data converter for conversion of I 2 S data stream to UDP protocol data.

A central goal of systems neuroscience is to simultaneously measure the activities of all achievable neurons in the brain at millisecond resolution in freely moving animals. This paper describes a protocol converter which is part of a measurement acquisition system for multichannel real time recording of brain signals. In practice, in such techniques, a primary consideration of reliability leads to great necessity towards increasing the sampling rate of these signals while simultaneously increasing the resolution of A/D conversion to 24 bits or even to the unprecedented 32 bits per sample. In fact, this was the guiding principle for our team in the present study. By increasing the temporal and amplitude resolution, it is supposed that we get enabled to discover or recognize and identify new signal components which have previously been masked at a "low" temporal and amplitude resolution, and these new signal components, in the future, are likely to contribute to a deeper understanding of the workings of the brain.

A Novel Fuzzy-Adaptive Extended Kalman Filter for Real-Time Attitude Estimation of Mobile Robots.

This paper proposes a novel fuzzy-adaptive extended Kalman filter (FAEKF) for the real-time attitude estimation of agile mobile platforms equipped with magnetic, angular rate, and gravity (MARG) sensor arrays. The filter structure employs both a quaternion-based EKF and an adaptive extension, in which novel measurement methods are used to calculate the magnitudes of system vibrations, external accelerations, and magnetic distortions. These magnitudes, as external disturbances, are incorporated into a sophisticated fuzzy inference machine, which executes fuzzy IF-THEN rules-based adaption laws to consistently modify the noise covariance matrices of the filter, thereby providing accurate and robust attitude results. A six-degrees of freedom (6 DOF) test bench is designed for filter performance evaluation, which executes various dynamic behaviors and enables measurement of the true attitude angles (ground truth) along with the raw MARG sensor data. The tuning of filter parameters is performed with numerical optimization based on the collected measurements from the test environment. A comprehensive analysis highlights that the proposed adaptive strategy significantly improves the attitude estimation quality. Moreover, the filter structure successfully rejects the effects of both slow and fast external perturbations. The FAEKF can be applied to any mobile system in which attitude estimation is necessary for localization and external disturbances greatly influence the filter accuracy.