Plasmodial sugar transporters as anti-malarial drug targets and comparisons with other protozoa

Glucose is the primary source of energy and a key substrate for most cells. Inhibition of cellular glucose uptake (the first step in its utilization) has, therefore, received attention as a potential therapeutic strategy to treat various unrelated diseases including malaria and cancers. For malaria, blood forms of parasites rely almost entirely on glycolysis for energy production and, without energy stores, they are dependent on the constant uptake of glucose. Plasmodium falciparum is the most dangerous human malarial parasite and its hexose transporter has been identified as being the major glucose transporter. In this review, recent progress regarding the validation and development of the P. falciparum hexose transporter as a drug target is described, highlighting the importance of robust target validation through both chemical and genetic methods. Therapeutic targeting potential of hexose transporters of other protozoan pathogens is also reviewed and discussed

Monitoring biological wastewater treatment processes: Recent advances in spectroscopy applications

Biological processes based on aerobic and anaerobic technologies have been continuously developed to wastewater treatment and are currently routinely employed to reduce the contaminants discharge levels in the environment. However, most methodologies commonly applied for monitoring key parameters are labor intensive, time-consuming and just provide a snapshot of the process. Thus, spectroscopy applications in biological processes are, nowadays, considered a rapid and effective alternative technology for real-time monitoring though still lacking implementation in full-scale plants. In this review, the application of spectroscopic techniques to aerobic and anaerobic systems is addressed focusing on UV--Vis, infrared, and fluorescence spectroscopy. Furthermore, chemometric techniques, valuable tools to extract the relevant data, are also referred. To that effect, a detailed analysis is performed for aerobic and anaerobic systems to summarize the findings that have been obtained since 2000. Future prospects for the application of spectroscopic techniques in biological wastewater treatment processes are further discussed.The authors thank the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, COMPETE 2020 (POCI-01-0145-FEDER-006684) and the project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. The authors also acknowledge the financial support to Daniela P. Mesquita and Cristina Quintelas through the postdoctoral Grants (SFRH/BPD/82558/2011 and SFRH/BPD/101338/2014) provided by FCT - Portugal.info:eu-repo/semantics/publishedVersio

Decomposing & mapping neural systems onto general-purpose parallel machines

Simulations of neural systems on sequential computers are computationally expensive. For example, a single experiment for a typical financial application, e.g. exchange rate time series analysis, requires about ten hours of CPU time on a Sun workstation. Neural systems are, however inherently parallel, and would thus benefit from parallel implementations. Therefore, this thesis investigates the problem of decomposing and mapping neural systems onto general-purpose parallel machines. It presents a Mapping System capable of decomposing neural network systems, and mapping them onto a range of general-purpose parallel machines; both MIMD and SIMD. Firstly, taxonomies of neural network systems and parallel machines are provided, as well as descriptions of typical examples of both. Secondly, parallelism in neural systems and machines is analysed. The different types of parallelism exhibited by neural systems are identified. This allows a classification of neural systems on the basis of their parallelism and in accordance with their taxonomy. Parallel machines and the approaches to parallel programming are then analysed to identify the features of parallel machines involved in the mapping process. From this analysis of parallelism in neural systems and machines, the characteristics required for decomposing and mapping neural systems are identified, and a Mapping System for decomposing and mapping neural systems onto general-purpose parallel machines is described. The Mapping System consists of two modules; a machine independent Abstract Decomposition module, and a Machine Dependent Decomposition module. The Abstract Decomposition (AD) module describes a specification for neural systems. The AD specifies a finite set of schemes for decomposing neural systems according to the required exploitation of neural systems' parallelism; e.g. connection, neuron, cluster. The Machine Dependent Decomposition (MDD) analyses the decomposition schemes in conjunction with the features of parallel machines; e.g. processors' features, communications schemes, and specifies the most suitable mapping scheme to implement. To validate the Mapping System, prototype mapping software for MIMD machines has been implemented. The MIMD mapping software is able to automatically map static neural systems onto a 48- processor Parsys SN1000 Transputer machine. This mapping software was developed as part of the CEC-funded Esprit II Pygmalion Neurocomputing Project, and is incorporated in the Pygmalion Neural Network Environment. The Machine Dependent Decomposition (MDD) module is improved by the development of an analytical framework for evaluating the speedup of neural systems' mapping schemes, based on the integration of machine-dependent features with the alternative decomposition schemes. The various mapping schemes for the classical backpropagation neural systems were hand-coded onto a 64x64-processor Distributed Array of Processors (DAP). The analytical framework is then used to evaluate the speedups of the different mapping schemes. This shows that the expected speedups agree with the results obtained when implementing the mapping schemes. A formal specification for neural network systems which uses the Abstract Syntax Notation One (ASN. 1) as the syntactic construct is then presented. The innovative use of ASN. l, previously dedicated to the specification of communication protocols by the Open System Interconnection, provides a formal basis for specifying neural systems and their parallelism. This thesis develops a solution for decomposing and mapping neural systems onto general-purpose parallel machines. Working top down, this thesis makes three major contributions: i) the innovative use of ASN. l as the notational support for specifying neural systems with explicit support for parallelism, ii) an analytical framework for evaluating the speedup of alternative neural system' mappings, and iii) a general-purpose Mapping System for mapping neural systems onto parallel machines

Prevalence

Background: Spontaneous bacterial pleuritis is a high mortality complication in cirrhotic patients with hydrothorax. Aim: To investigate the prevalence and risk factors for spontaneous bacterial pleuritis in cirrhotic patients with hydrothorax. Methods: Adult inpatients with liver cirrhosis and hydrothorax were enrolled. The severity of liver disease was assessed by the Model for End-Stage Liver Disease (MELD) score. Pleural fluid was analyzed [pH, polymorphonuclear (PMN) leucocyte count, total protein level, lactate dehydrogenase (LDH) level, glucose level, bacterial culture and cytology]. Spontaneous bacterial pleuritis was diagnosed by positive pleural fluid culture or, if negative, a pleural fluid PMN count >500 cells/μL without radiographic evidence of pneumonia. Results: Out of 98 cirrhotic patients with hydrothorax enrolled in the study; 14 (14.3%) fullfilled the criteria for the diagnosis of spontaneous bacterial pleuritis. Of those 14 patients; 9 were culture positive and 5 were culture negative. The other 84 did not have evidence of spontaneous bacterial pleuritis and were considered to have uncomplicated hydrothorax. Patients with spontaneous bacterial pleuritis had more severe liver diseases (MELD score), and higher rate of associated spontaneous bacterial peritonitis (SBP) and bacteraemia than patients with uncomplicated hydrothorax. Patients with spontaneous bacterial pleuritis had a significantly higher PMN count and a lower protein level in the pleural fluid. Conclusion: The prevalence of spontaneous bacterial pleuritis in the studied group of patients with hepatic hydrothorax was 14.3%. Patients with advanced liver disease, low pleural fluid protein, or SBP are at risk for spontaneous bacterial pleuritis

Limitations on AES quantitative analyses of plasma deposited ceramics

Difficulties encountered in using AES for quantitative measurements have been evaluated with three plasma deposited materials : amorphous hydrogenated silicon carbide a-Si$_{\rm x}$C$_{1-{\rm x}}$:H; amorphous hydrogenated silicon nitride a-SiN$_{\rm x}$:H; crystallized hydrogenated aluminium nitride Al$_{\rm x}$N$_{\rm y}$:H. For a-Si$_{\rm x}$C$_{1-{\rm x}}$:H, the values of composition $x$ calculated from Peak/Background and Area/Background ratios are not very different for materials near to stoichiometry or rich in silicon. A divergence on results is noticed for a-Si$_{\rm x}$C$_{1-{\rm x}}$:H films with carbon-rich contents and for a-SiN$_{\rm x}$:H films. This is attributed to broadening effects seen on the KVV peak of carbon and on both LVV and KLL peaks of silicon. The most important problem in Al$_{\rm x}$N$_{\rm y}$ thin films quantitative Auger analysis is to find suitable reference samples. Available ones are silicon nitride and pure aluminium. The aluminium KLL Auger spectrum is characterized by surface and bulk plasmon loss peaks. Furthermore, the primary electrons efficiency and the emission yield is modified by changes in the solid matrix