Structural and functional analysis of human voltage-dependent anion channel isoforms (hVDACs): Combining in-vitro and in-silico approaches

VDACs are a small family of conserved proteins located in the outer mitochondrial membrane. They conduct ions, metabolites and small molecules, among which the energetic nucleotides ATP, ADP and NADH. Three different VDAC isoforms have been characterized in higher eukaryotes, encoded by three separate nuclear genes. VDAC1 is the most abundant isoform in most cells, being ten and hundred times more prevalent than VDAC2 and VDAC3, respectively. It is thus not surprising that VDAC1 is the isoform most extensively characterized. Functionally, VDAC1 is anion selective and exhibits a single-channel conductance of ~3.5-4.0 nS in 1 M KCl at an applied voltage between -20 mV and 10 mV. Raising the applied voltage results in the channel switching to the so-called “closed state”, with a lower conductance and a channel selectivity reversed to cations. In addition to the poreforming function, VDAC1 has been involved in various interactions and cross-talk with other cellular proteins like hexokinase, tubulin, the Ca2+ gate into mitochondria and the Bcl-2 family members that can impact on the activity of the pore itself and vice versa, testimony to the involvement of VDAC to crucial cell fates like in pathways leading to apoptosis, cancer and degeneration The aim of the PhD project was to perform a comparative study on the human VDAC isoforms focusing on both the whole channels and the individuals N-terminal domains. In this sense, both experimental and computational techniques have been used pointing out their complementarity and contribute to the completeness of the study. After a brief introduction, the methods used during the PhD will be presented. In the third chapter, the results together with the discussion will be described. Firstly, focusing on the structural characterization of the N-termini of the three isoforms. Secondly, the results and the discussion will concern the comparative study of the entire channels. Both of these characterization have been performed with either experimental and computational techniques. Finally, in the 4th chapter a brief conclusion and an outlook on a future perspective will be given

Modelling Head Impact Safety Performance of Polymer-based Foam Protective Devices

The aim of this paper is to investigate an iterative statistical procedure, based on a small and censored sample of impact test experiments, useful for interval estimation of head impact safety parameter as critical fall height of protective devices. An adaptive testing routine was developed that was mainly constituted by a series of at least four impact test experiments, followed by the comparison of at least two parameter estimates based on incremental exponential regression fittings and a final confirmation experiment. A total number of 23 protective devices, mainly made of polyethylene foam, were investigated in order to validate the adaptive routine. The routine, applied to critical fall height of protective devices, was 19 times convergent within a maximum of 6 impact test experiments. 4 times the sample was censored because the iterative procedure has exceeded the available number of specimens. Confidence intervals at the 90 % level were always less than 0.18 m. The applicability of the adaptive routine was satisfactory demonstrated with reference to devices made of PE-foam and safety threshold of peak acceleration a-max equal to 200 g. The target of a confidence interval below the state-of-art was achieved

EARLINET Single Calculus Chain – technical – Part 1: Pre-processing of raw lidar data

In this paper we describe an automatic tool for the pre-processing of aerosol lidar data called ELPP (EARLINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of ELPP, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns

EARLINET Single Calculus Chain - technical - Part 1: Pre-processing of raw lidar data

In this paper we describe an automatic tool for the pre-processing of aerosol lidar data called ELPP (EAR-LINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of ELPP, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time preprocessing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns

Outdoor Tests for the Validation of an Inertial System Able to Detect Illegal Steps in Race-walking

Abstract Aim of this study was to validate an inertial system able to detect the loss of ground contact (LOGC) in race-walking through outdoor tests in real training conditions. An inertial sensor was placed at L5/S1 of the vertebral column of a Italian national team athlete to acquire timing measurements of the LOGC. Data were encoded by a well-defined protocol. After a preliminary laboratory study, the athlete performed outdoor-field-tests at different velocities. A specific e-bike with a high-speed camera allowed to acquire a video and to validate sensor measurements. Results indicate that the inertial system can improve the accuracy in detecting the visible LOGC

The 1st Advanced Manufacturing Student Conference (AMSC21) Chemnitz, Germany 15–16 July 2021

The Advanced Manufacturing Student Conference (AMSC) represents an educational format designed to foster the acquisition and application of skills related to Research Methods in Engineering Sciences. Participating students are required to write and submit a conference paper and are given the opportunity to present their findings at the conference. The AMSC provides a tremendous opportunity for participants to practice critical skills associated with scientific publication. Conference Proceedings of the conference will benefit readers by providing updates on critical topics and recent progress in the advanced manufacturing engineering and technologies and, at the same time, will aid the transfer of valuable knowledge to the next generation of academics and practitioners. *** The first AMSC Conference Proceeding (AMSC21) addressed the following topics: Advances in “classical” Manufacturing Technologies, Technology and Application of Additive Manufacturing, Digitalization of Industrial Production (Industry 4.0), Advances in the field of Cyber-Physical Systems, Virtual and Augmented Reality Technologies throughout the entire product Life Cycle, Human-machine-environment interaction and Management and life cycle assessment.:- Advances in “classical” Manufacturing Technologies - Technology and Application of Additive Manufacturing - Digitalization of Industrial Production (Industry 4.0) - Advances in the field of Cyber-Physical Systems - Virtual and Augmented Reality Technologies throughout the entire product Life Cycle - Human-machine-environment interaction - Management and life cycle assessmen

What is the impact of a novel MED12 variant on syndromic conotruncal heart defects? Analysis of case report on two male sibs

Background: Syndromic congenital heart disease accounts for 30% of cases and can be determined by genetic, environmental or multifactorial causes. In many cases the etiology remains uncertain. Many known genes are responsible for specific morphopathogenetic mechanisms during the development of the heart whose alteration can determine specific phenotypes of cardiac malformations. Case presentation: We report on two cases of association of conotruncal heart defect with facial dysmorphisms in sibs. In both cases the malformations' identification occurred by ultrasound in the prenatal period. It was followed by prenatal invasive diagnosis. The genetic analysis revealed no rearrangements in Array-CGH test, while gene panel sequencing identified a new hemizygous variant of uncertain significance (c.887G > A; p.Arg296Gln) in the MED12 gene, located on the X chromosome and inherited from the healthy mother. Conclusion: No other reports about the involvement of MED12 gene in syndromic conotruncal heart defects are actually available from the literature and the international genomic databases. This novel variant is a likely pathogenic variant of uncertain significance and it could broaden the spectrum of genes involved in the development of congenital heart diseases and the phenotypic range of MED12-related disorders

Atmospheric boundary layer height estimation from aerosol lidar: A new approach based on morphological image processing techniques

The atmospheric boundary layer (ABL) represents the lowermost part of the atmosphere directly in contact with the Earth's surface. The estimation of its depth is of crucial importance in meteorology and for anthropogenic pollution studies. ABL height (ABLH) measurements are usually far from being adequate, both spatially and temporally. Thus, different remote sensing sources can be of great help in growing both the spatial and temporal ABLH measurement capabilities. To this aim, aerosol backscatter profiles are widely used as a proxy to retrieve the ABLH. Hence, the scientific community is making remarkable efforts in developing automatic ABLH retrieval algorithms applied to lidar observations. In this paper, we propose a ABLH estimation algorithm based on image processing techniques applied to the composite image of the total attenuated backscatter coefficient. A pre-processing step is applied to the composite total backscatter image based on morphological filters to properly set-up and adjust the image to detect edges. As final step, the detected edges are post-processed through both mathematical morphology and an object-based analysis. The performance of the proposed approach is assessed on real data acquired by two different lidar systems, deployed in Potenza (Italy) and Évora (Portugal), belonging to the European Aerosol Research Lidar Network (EARLINET). The proposed approach has shown higher performance than the benchmark consisting of some state-of-The-Art ABLH estimation methods. © 2021 Copernicus GmbH. All rights reserved.ACTRIS (https://www.actris.eu/, last access: 15 March 2021) has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement nos. 654109 (ACTRIS-2), 759530 (ACTRIS-PPP), 871115 (ACTRIS-IMP) and 824068 (ENVRI-FAIR), and previously from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 262254. The Portuguese lidar station is also supported by national funds through FCT – Foundation for Science and Technology, I. P., within the scope of projects UIDB/04683/2020 and UIDP/04683/2020, and also through project TOMAQAPA (PTDC/CTAMET/29678/2017). Moreover, the authors gratefully acknowledge CloudNET for providing ECMWF and GDAS atmospheric forecasts for all the measurement cases included in this study