Results of a collaborative study on DNA identification of aged bone samples

AimA collaborative exercise with several institutes was organized by the Forensic DNA Service (FDNAS) and the Institute of the Legal Medicine, 2nd Faculty of Medicine, Charles University in Prague, Czech Republic, with the aim to test performance of different laboratories carrying out DNA analysis of relatively old bone samples. MethodsEighteen laboratories participating in the collaborative exercise were asked to perform DNA typing of two samples of bone powder. Two bone samples provided by the National Museum and the Institute of Archaelogy in Prague, Czech Republic, came from archeological excavations and were estimated to be approximately 150 and 400 years old. The methods of genetic characterization including autosomal, gonosomal, and mitochondrial markers was selected solely at the discretion of the participating laboratory. ResultsAlthough the participating laboratories used different extraction and amplification strategies, concordant results were obtained from the relatively intact 150 years old bone sample. Typing was more problematic with the analysis of the 400 years old bone sample due to poorer quality. ConclusionThe laboratories performing identification DNA analysis of bone and teeth samples should regularly test their ability to correctly perform DNA-based identification on bone samples containing degraded DNA and potential inhibitors and demonstrate that risk of contamination is minimized

Edge Machine Learning for the Automated Decision and Visual Computing of the Robots, IoT Embedded Devices or UAV-Drones

This paper presents edge machine learning (ML) technology and the challenges of its implementation into various proof-of-concept solutions developed by the authors. Paper presents the concept of Edge ML from a variety of perspectives, describing different implementations such as: a tech-glove smart device (IoT embedded device) for controlling teleoperated robots or an UAVs (unmanned aerial vehicles/drones) that is processing data locally (at the device level) using machine learning techniques and artificial intelligence neural networks (deep learning algorithms), to make decisions without interrogating the cloud platforms. Implementation challenges used in Edge ML are described and analyzed in comparisons with other solutions. An IoT embedded device integrated into a tech glove, which controls a teleoperated robot, is used to run the AI neural network inference. The neural network was trained in an ML cloud for better control. Implementation developments, behind the UAV device capable of visual computation using machine learning, are presented

The Telocytes in the Subepicardial Niche

A great interest has developed over the last several years in research on interstitial Cajal-like cells (ICLCs), later renamed to telocytes (TCs). Such studies are restricted by diverse limitations. We aimed to critically review (sub)epicardial ICLCs/TCs and to bring forward supplemental immunohistochemical evidence on (sub)epicardial stromal niche inhabitants. We tested the epicardial expressions of CD117/c-kit, CD34, Cytokeratin 7 (CK7), Ki67, Platelet-Derived Growth Factor Receptor (PDGFR)-α and D2-40 in adult human cardiac samples. The mesothelial epicardial cells expressed D2-40, CK7, CD117/c-kit and PDGFR-α. Subepicardial D2-40-positive lymphatic vessels and isolated D2-40-positive and CK7-positive subepicardial cells were also found. Immediate submesothelial spindle-shaped cells expressed Ki-67. Submesothelial stromal cells and endothelial tubes were PDGFR-α-positive and CD34-positive. The expression of CD34 was pan-stromal, so a particular stromal cell type could not be distinguished. The stromal expression of CD117/c-kit was also noted. It seems that epicardial TCs could not be regarded as belonging to a unique cell type until (pre)lymphatic endothelial cells are inadequately excluded. Markers such as CD117/c-kit or CD34 seem to be improper for identifying TCs as a distinctive cell type. Care should be taken when using the immunohistochemical method and histological interpretations, as they may not produce accurate results

Edge Machine Learning for the Automated Decision and Visual Computing of the Robots, IoT Embedded Devices or UAV-Drones

This paper presents edge machine learning (ML) technology and the challenges of its implementation into various proof-of-concept solutions developed by the authors. Paper presents the concept of Edge ML from a variety of perspectives, describing different implementations such as: a tech-glove smart device (IoT embedded device) for controlling teleoperated robots or an UAVs (unmanned aerial vehicles/drones) that is processing data locally (at the device level) using machine learning techniques and artificial intelligence neural networks (deep learning algorithms), to make decisions without interrogating the cloud platforms. Implementation challenges used in Edge ML are described and analyzed in comparisons with other solutions. An IoT embedded device integrated into a tech glove, which controls a teleoperated robot, is used to run the AI neural network inference. The neural network was trained in an ML cloud for better control. Implementation developments, behind the UAV device capable of visual computation using machine learning, are presented

IoT Communication Security Issues for Companies: Challenges, Protocols and The Web of Data

This article analyzes and highlights the security perspective of Internet of Things (IoT) connected devices and their communication challenges, as IoT is considered one of the key emerging fields in Industry 4.0. The IoT architectures can consist of physical systems, virtual ones or even hybrids, combining a collection of different physically active things, sensors, cloud services, specific IoT protocols, communication layers, users and developers. On top of all, it is the business layer, because the scope of the entire IoT environment is to deliver data, to monitor and to facilitate the management of complex processes. In order to facilitate the data exchange between the IoT layers, there have been developed a series of protocols particular to the IoT domain. As in many IT related fields, the solutions are not perfect from the data security and privacy perspectives, many challenges being still open research issues. As the two concepts of IoT and Cloud of Things are connected, bringing real world data into the Cloud to process it, raises Cloud Computing security concerns regarding the privacy and security of data. Although in recent years, many efforts have been made to improve Cloud Computing security, there are risks that need to be taken into consideration. From the Web of Data’s point of view, things are even more prone to security risks. Because privacy is one of the fundamental right of digital users, it is extremely important for new technologies to comply with privacy regulations and policies, such as the new European data protection and privacy frameworks. In this context, companies must take into account standards, challenges and new trends in IoT. In the absence of specific measures, raw or processed data can be easily stolen from the Web of Data. In this paper we analyze and present the main protocols of communication in the IoT field from a data security perspective. Also, we do a review of the main architectures that can improve the security of the communication between IoT devices and the Cloud data storage

Hybrid Lipid Nanoformulations for Hepatoma Therapy: Sorafenib Loaded Nanoliposomes—A Preliminary Study

Sorafenib is a multikinase inhibitor that has received increasing attention due to its high efficacy in hepatocellular carcinoma treatment. However, its poor pharmacokinetic properties (limited water solubility, rapid elimination, and metabolism) still represent major bottlenecks that need to be overcome in order to improve Sorafenib’s clinical application. In this paper, we propose a nanotechnology-based hybrid formulation that has the potential to overcome these challenges: sorafenib-loaded nanoliposomes. Sorafenib molecules have been incorporated into the hydrophobic lipidic bilayer during the synthesis process of nanoliposomes using an original procedure developed in our laboratory and, to the best of our knowledge, this is the first paper reporting this type of analysis. The liposomal hybrid formulations have been characterized by transmission electron microscopy (TEM), dynamic light scattering (DLS), and nanoparticle tracking analysis (NTA) that provided useful information concerning their shape, size, zeta-potential, and concentration. The therapeutic efficacy of the nanohybrids has been evaluated on a normal cell line (LX2) and two hepatocarcinoma cell lines, SK-HEP-1 and HepG2, respectively

Detection of SARS-CoV-2 Viral Genome and Viral Nucleocapsid in Various Organs and Systems

While considerable attention has been devoted to respiratory manifestations, such as pneumonia and acute respiratory distress syndrome (ARDS), emerging evidence underlines the significance of extrapulmonary involvement. In this study, we examined 15 hospitalized patients who succumbed to severe complications following SARS-CoV-2 infection. These patients were admitted to the Sibiu County Clinical Emergency Hospital in Sibiu, Romania, between March and October 2021. All patients were ethnic Romanians. Conducted within a COVID-19-restricted environment and adhering to national safety protocols, autopsies provided a comprehensive understanding of the disease’s multisystemic impact. Detailed macroscopic evaluations and histopathological analyses of myocardial, renal, hepatic, splenic, and gastrointestinal tissues were performed. Additionally, reverse transcription-quantitative polymerase chain reaction (rt-qPCR) assays and immunohistochemical staining were employed to detect the viral genome and nucleocapsid within the tissues. Myocardial lesions, including ischemic microstructural changes and inflammatory infiltrates, were prevalent, indicative of COVID-19’s cardiac implications, while renal pathology revealed the chronic alterations, acute tubular necrosis, and inflammatory infiltrates most evident. Hepatic examination identified hepatocellular necroinflammatory changes and hepatocytic cytopathy, highlighting the hepatic involvement of SARS-CoV-2 infection. Splenic parenchymal disorganization was prominent, indicating systemic immune dysregulation. Furthermore, gastrointestinal examinations unveiled nonspecific changes. Molecular analyses detected viral genes in various organs, with immunohistochemical assays confirming viral presence predominantly in macrophages and fibroblasts. These findings highlighted the systemic nature of SARS-CoV-2 infection, emphasizing the need for comprehensive clinical management strategies and targeted therapeutic approaches beyond respiratory systems