Design and synthesis of non-peptide mimetics mapping the immunodominant myelin basic protein (MBP83–96) Epitope to function as T-cell receptor antagonists

Encephalitogenic T cells are heavily implicated in the pathogenesis of multiple sclerosis (MS), an autoimmune demyelinating disease of the central nervous system. Their stimulation is triggered by the formation of a trimolecular complex between the human leukocyte antigen (HLA), an immunodominant myelin basic protein (MBP) epitope, and the T cell receptor (TCR). We detail herein our studies directed towards the rational design and synthesis of non-peptide mimetic molecules, based on the immunodominant MBP83–96 epitope that is recognized by the TCR in complex with HLA. We focused our attention on the inhibition of the trimolecular complex formation and consequently the inhibition of proliferation of activated T cells. A structure-based pharmacophore model was generated, in view of the interactions between the TCR and the HLA-MBP83–96 complex. As a result, new candidate molecules were designed based on lead compounds obtained through the ZINC database. Moreover, semi-empirical and density functional theory methods were applied for the prediction of the binding energy between the proposed non-peptide mimetics and the TCR. We synthesized six molecules that were further evaluated in vitro as TCR antagonists. Analogues 15 and 16 were able to inhibit to some extent the stimulation of T cells by the immunodominant MBP83–99 peptide from immunized mice. Inhibition was followed to a lesser degree by analogues 17 and 18 and then by analogue 19. These studies show that lead compounds 15 and 16 may be used for immunotherapy against MS

A smartwater metering deployment based on the fog computing paradigm

In this paper, we look into smart water metering infrastructures that enable continuous, on-demand and bidirectional data exchange between metering devices, water flow equipment, utilities and end-users. We focus on the design, development and deployment of such infrastructures as part of larger, smart city, infrastructures. Until now, such critical smart city infrastructures have been developed following a cloud-centric paradigm where all the data are collected and processed centrally using cloud services to create real business value. Cloud-centric approaches need to address several performance issues at all levels of the network, as massive metering datasets are transferred to distant machine clouds while respecting issues like security and data privacy. Our solution uses the fog computing paradigm to provide a system where the computational resources already available throughout the network infrastructure are utilized to facilitate greatly the analysis of fine-grained water consumption data collected by the smart meters, thus significantly reducing the overall load to network and cloud resources. Details of the system's design are presented along with a pilot deployment in a real-world environment. The performance of the system is evaluated in terms of network utilization and computational performance. Our findings indicate that the fog computing paradigm can be applied to a smart grid deployment to reduce effectively the data volume exchanged between the different layers of the architecture and provide better overall computational, security and privacy capabilities to the system

End-to-end quality aware optimization for multimedia clouds

This article presents a novel, end-to-end, qualityaware optimization framework for multimedia clouds, where path selection mechanisms are exploited in conjunction with media optimization in order to support multimedia delivery in a quality-aware manner. As wireless data traffic worldwide is characterized by exponential growth, with the most prominent part being multimedia services, consumers get in the challenging position to compete for the limited wireless network resources. Cloud technologies and especially Software-Defined Networking is the perfect candidate technology in order to provide an elastic, dynamic provisioning of network resources that adapt to a highly changing environment, where application requirements and data volumes vary over time. This work combines the selection of the optimum path in the core network with quality-aware media adaptation based on the current conditions of the wireless access network. Thus the proposed framework achieves efficient network resources utilization in an end-to-end fashion

Evaluation of a stable Gonadotropin-Releasing Hormone analog in mice for the treatment of endocrine disorders and prostate cancer

Gonadotropin-releasing hormone (GnRH) receptor agonists have wide clinical applications including the treatment of prostate cancer and endocrine disorders. However, such agonists are characterized by poor pharmacokinetic properties, often requiring repeated administration or special formulations. Therefore, the development of novel peptide analogs with enhanced in vivo stability could potentially provide therapeutic alternatives. The pharmacological evaluation of a bioactive peptide [Des-Gly10,Tyr5(OMe),D-Leu 6,Aze-NHEt9]GnRH, analog 1, is presented herein and compared with leuprolide. Peptide stability was evaluated using mouse kidney membrane preparations, followed by a liquid chromatography-tandem mass spectrometry-based approach that afforded identification and quantification of its major metabolites. The analog was significantly more stable in vitro in comparison with leuprolide. In vitro and in vivo stability results correlated well, encouraging us to develop a clinically relevant pharmacokinetic mouse model, which facilitated efficacy measurements using testosterone as a biomarker. Analog 1, an agonist of the GnRH receptor with a binding affinity in the nanomolar range, caused testosterone release in mice that was acutely dose-dependent, an effect blocked by the GnRH receptor antagonist cetrorelix. Repeated dosing studies in mice demonstrated that analog 1 was well tolerated and had potency similar to that of leuprolide, based on plasma and testis testosterone reduction and histopathological findings. Analog 1 also shared with leuprolide similar significant antiproliferative activity on androgen-dependent prostate cancer (LNCaP) cells. On the basis of pharmacokinetic advantages, we expect that analog 1 or analogs based on this new design will be therapeutically advantageous for the treatment of cancer and endocrine disorders. Copyrigh

An empirical analysis of the determinants of mobile instant messaging appropriation in university learning

Published ArticleResearch on technology adoption often profiles device usability (such as perceived usefulness) and user dispositions (such as perceived ease of use) as the prime determinants of effective technology adoption. Since any process of technology adoption cannot be conceived out of its situated contexts, this paper argues that any pre-occupation with technology acceptance from the perspective of device usability and user dispositions potentially negates enabling contexts that make successful adoption a reality. Contributing to contemporary debates on technology adoption, this study presents flexible mobile learning contexts comprising cost (device cost and communication cost), device capabilities (portability, collaborative capabilities), and learner traits (learner control) as antecedents that enable the sustainable uptake of emerging technologies. To explore the acceptance and capacity of mobile instant messaging systems to improve student performance, the study draws on these antecedents, develops a factor model and empirically tests it on tertiary students at a South African University of Technology. The study involved 223 national diploma and bachelor’s degree students and employed partial least squares for statistical analysis. Overall, the proposed model displayed a good fit with the data and rendered satisfactory explanatory power for students’ acceptance of mobile learning. Findings suggest that device portability, communication cost, collaborative capabilities of device and learner control are the main drivers of flexible learning in mobile environments. Flexible learning context facilitated by learner control was found to have a positive influence on attitude towards mobile learning and exhibited the highest path coefficient of the overall model. The study implication is that educators need to create varied learning opportunities that leverage learner control of learning in mobile learning systems to enhance flexible mobile learning. The study also confirmed the statistical significance of the original Technology Acceptance Model constructs

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease