Special Issue on the Internet of Things (ISCC 2020)

Journal of Signal Processing Systems -     

A Role for Human Renal Tubular Epithelial Cells in Direct Allo-Recognition by CD4+ T-Cells and the Effect of Ischemia-Reperfusion

Direct allorecognition is the earliest and most potent immune response against a kidney allograft. Currently, it is thought that passenger donor professional antigen-presenting cells (APCs) are responsible. Further, many studies support that graft ischemia-reperfusion injury increases the probability of acute rejection. We evaluated the possible role of primary human proximal renal tubular epithelial cells (RPTECs) in direct allorecognition by CD4+ T-cells and the effect of anoxia-reoxygenation. In cell culture, we detected that RPTECs express all the required molecules for CD4+ T-cell activation (HLA-DR, CD80, and ICAM-1). Anoxia-reoxygenation decreased HLA-DR and CD80 but increased ICAM-1. Following this, RPTECs were co-cultured with alloreactive CD4+ T-cells. In T-cells, zeta chain phosphorylation and c-Myc increased, indicating activation of T-cell receptor and co-stimulation signal transduction pathways, respectively. T-cell proliferation assessed with bromodeoxyuridine assay and with the marker Ki-67 increased. Previous culture of RPTECs under anoxia raised all the above parameters in T-cells. FOXP3 remained unaffected in all cases, signifying that proliferating T-cells were not differentiated towards a regulatory phenotype. Our results support that direct allorecognition may be mediated by RPTECs even in the absence of donor-derived professional APCs. Also, ischemia-reperfusion injury of the graft may enhance the above capacity of RPTECs, increasing the possibility of acute rejection.     

A Systematic Review and Meta-Analysis of Pharmacogenetic Studies in Patients with Chronic Kidney Disease

Chronic kidney disease (CKD) is an important global public health problem due to its high prevalence and morbidity. Although the treatment of nephrology patients has changed considerably, ineffectiveness and side effects of medications represent a major issue. In an effort to elucidate the contribution of genetic variants located in several genes in the response to treatment of patients with CKD, we performed a systematic review and meta-analysis of all available pharmacogenetics studies. The association between genotype distribution and response to medication was examined using the dominant, recessive, and additive inheritance models. Subgroup analysis based on ethnicity was also performed. In total, 29 studies were included in the meta-analysis, which examined the association of 11 genes (16 polymorphisms) with the response to treatment regarding CKD. Among the 29 studies, 18 studies included patients with renal transplantation, 8 involved patients with nephrotic syndrome, and 3 studies included patients with lupus nephritis. The present meta-analysis provides strong evidence for the contribution of variants harbored in the ABCB1, IL-10, ITPA, MIF, and TNF genes that creates some genetic predisposition that reduces effectiveness or is associated with adverse events of medications used in CKD.     

Editorial: Security and Privacy Protection for Mobile Applications and Platforms

Mobile Networks and Applications -     

A hybrid approach to scheduling real-time IoT workflows in fog and cloud environments

Multimedia Tools and Applications - In this paper, we propose a hybrid fog and cloud-aware heuristic for the dynamic scheduling of multiple real-time Internet of Things (IoT) workflows in a...     

Semi-supervised online structure learning for composite event recognition

Online structure learning approaches, such as those stemming from statistical relational learning, enable the discovery of complex relations in noisy data streams. However, these methods assume the existence of fully-labelled training data, which is unrealistic for most real-world applications. We present a novel approach for completing the supervision of a semi-supervised structure learning task. We incorporate graph-cut minimisation, a technique that derives labels for unlabelled data, based on their distance to their labelled counterparts. In order to adapt graph-cut minimisation to first order logic, we employ a suitable structural distance for measuring the distance between sets of logical atoms. The labelling process is achieved online (single-pass) by means of a caching mechanism and the Hoeffding bound, a statistical tool to approximate globally-optimal decisions from locally-optimal ones. We evaluate our approach on the task of composite event recognition by using a benchmark dataset for human activity recognition, as well as a real dataset for maritime monitoring. The evaluation suggests that our approach can effectively complete the missing labels and eventually, improve the accuracy of the underlying structure learning system.

     

CoopStor: a cooperative reliable and efficient data collection protocol in fault and delay tolerant wireless networks

Wireless Networks - Internet of things consist in the deployment of constrained and battery-powered devices with a radio interface. Most industrial applications require to respect strict...     

The potential of WHR/batch and cullet preheating for energy efficiency in the EU ETS glass industry and the related energy incentives

The European Emissions Trading Scheme (EU ETS) covers approximately 45% of European greenhouse gases (GHGs), 11,000 stationary installations as well as aircraft operators. The EU ETS particularly affects the energy-intensive industries while it imposes a significant risk of “carbon leakage,” i.e., the risk of EU industry departing to countries with weaker restraints on GHG emissions. The EU glass industry, being capital intensive and also requiring long investment cycles, is the world’s largest glass producer with a market share close to one third of global production. Therefore, it is of significant importance to view the position of the EU ETS glass industry in terms of energy conservation possibilities. The present paper utilizes a vertical approach to provide information on both ETS market evolution and specific technical information to support technological innovation to the glass industry. EU ETS glass industry is analyzed regarding the balance between allocated European Union emission allowances (EUAs), verified CO₂ emissions, and potential shortfall in allowances so as to determine the situation of glass industries and the extent of urge for energy-saving activities towards the strengthening of their position within the requirements of the EU ETS phase III. The replication potential of waste heat recovery (WHR) through batch preheating is specifically addressed since it is considered a promising technology according to the latest Best Available Techniques (BAT) reference document for the glass industry under Directive IED 2010/75/EU. A case study for a container glass furnace based on simulation results is presented investigating the impact of different operating and design configurations on specific energy consumption and CO₂ emissions.