Allelic forms of merozoite surface protein-3 in Plasmodium falciparum isolates from southeast of Iran

Background: Genetic diversity has provided Plasmodium falciparum with the potential capacity of avoiding the immune response, and possibly supported the natural selection of drug or vaccine-resistant parasites. Merozoite surface protein-3 (MSP-3) has been used to develop vaccines and investigate the genetic diversity regarding P. falciparum malaria in Iran. Objectives: The main goal of this study was to analyze the polymorphic antigen MSP-3 genes across southeast of Iran among four different districts, to identify the differences in the allele frequency and genetic diversity. Materials and Methods: Nested polymerase chain reaction amplification was used to determine polymorphisms of N-terminal region of the MSP-3 gene. A total of 85 microscopically positive P. falciparum infected individuals from southeast of Iran were included in this study. Results: Of the 85 confirmed P. falciparum samples obtained from four different districts, 72 were successfully scored for MSP-3.The MSP-3 allele classes (K1 and 3D7 types) showed comparable prevalence in all districts. Overall frequencies of K1 and 3D7 allele classes were 94.5 % for both. Conclusions: Since no study has yet looked at the extent of P. falciparum MSP-3 in this geographic region, these data can be helpful to support development of a vaccine based on MSP-3 against malaria. There should be a comparative analysis in different seasonal peaks to indicate the allelic polymorphism of MSP-3 over a period. © 2014, Ahvaz Jundishapur University of Medical Sciences; Published by Kowsar Corp

Microservices Architecture Enables DevOps: an Experience Report on Migration to a Cloud-Native Architecture

This article reports on experiences and lessons learned during incremental migration and architectural refactoring of a commercial mobile back end as a service to microservices architecture. It explains how the researchers adopted DevOps and how this facilitated a smooth migration

Fuzzy Self-Learning Controllers for Elasticity Management in Dynamic Cloud Architectures

Cloud controllers support the operation and quality management of dynamic cloud architectures by automatically scaling the compute resources to meet performance guarantees and minimize resource costs. Existing cloud controllers often resort to scaling strategies that are codified as a set of architecture adaptation rules. However, for a cloud provider, deployed application architectures are black-boxes, making it difficult at design time to define optimal or pre-emptive adaptation rules. Thus, the burden of taking adaptation decisions often is delegated to the cloud application. We propose the dynamic learning of adaptation rules for deployed application architectures in the cloud. We introduce FQL4KE, a self-learning fuzzy controller that learns and modifies fuzzy rules at runtime. The benefit is that we do not have to rely solely on precise design-time knowledge, which may be difficult to acquire. FQL4KE empowers users to configure cloud controllers by simply adjusting weights representing priorities for architecture quality instead of defining complex rules. FQL4KE has been experimentally validated using the cloud application framework ElasticBench in Azure and OpenStack. The experimental results demonstrate that FQL4KE outperforms both a fuzzy controller without learning and the native Azure auto-scalin

Systems analysis of host-parasite interactions.

Parasitic diseases caused by protozoan pathogens lead to hundreds of thousands of deaths per year in addition to substantial suffering and socioeconomic decline for millions of people worldwide. The lack of effective vaccines coupled with the widespread emergence of drug-resistant parasites necessitates that the research community take an active role in understanding host-parasite infection biology in order to develop improved therapeutics. Recent advances in next-generation sequencing and the rapid development of publicly accessible genomic databases for many human pathogens have facilitated the application of systems biology to the study of host-parasite interactions. Over the past decade, these technologies have led to the discovery of many important biological processes governing parasitic disease. The integration and interpretation of high-throughput -omic data will undoubtedly generate extraordinary insight into host-parasite interaction networks essential to navigate the intricacies of these complex systems. As systems analysis continues to build the foundation for our understanding of host-parasite biology, this will provide the framework necessary to drive drug discovery research forward and accelerate the development of new antiparasitic therapies

Transcriptome-based reconstructions from the murine knockout suggest involvement of the urate transporter, URAT1 (slc22a12), in novel metabolic pathways.

URAT1 (slc22a12) was identified as the transporter responsible for renal reabsorption of the medically important compound, uric acid. However, subsequent studies have indicated that other transporters make contributions to this process, and that URAT1 transports other organic anions besides urate (including several in common with the closely related multi-specific renal organic anion transporters, OAT1 (slc22a6) and OAT3 (slc22a8)). These findings raise the possibility that urate transport is not the sole physiological function of URAT1. We previously characterized mice null for the murine ortholog of URAT1 (mURAT1; previously cloned as RST), finding a relatively modest decrement in urate reabsorptive capacity. Nevertheless, there were shifts in the plasma and urinary concentrations of multiple small molecules, suggesting significant metabolic changes in the knockouts. Although these molecules remain unidentified, here we have computationally delineated the biochemical networks consistent with transcriptomic data from the null mice. These analyses suggest alterations in the handling of not only urate but also other putative URAT1 substrates comprising intermediates in nucleotide, carbohydrate, and steroid metabolism. Moreover, the analyses indicate changes in multiple other pathways, including those relating to the metabolism of glycosaminoglycans, methionine, and coenzyme A, possibly reflecting downstream effects of URAT1 loss. Taken together with the available substrate and metabolomic data for the other OATs, our findings suggest that the transport and biochemical functions of URAT1 overlap those of OAT1 and OAT3, and could contribute to our understanding of the relationship between uric acid and the various metabolic disorders to which it has been linked

Mechanical performance of concrete with partial replacement of sand by sewage sludge ash

The production of sewage sludge from waste water treatment plants is increasing all over the world. Disposal of sewage sludge is a serious environmental problem. If we think of the areas needed for sludge ash disposal, we clearly understand the importance of reusing sewage sludge ash in concrete. This paper presents results related to the replacement of sand by sewage sludge ash. The sludge was characterized for chemical composition (XRF analysis), crystalline phases (XRD analysis) and pozzolanic activity. The effects of incineration on crystal phases of dry sludge were investigated. Two (W/C) ratios (0.55 and 0.45) and three sludge percentages (5%, 10% and 20%) by cement mass were used. The mechanical performance of SSAC at different curing ages (3, 7, 28 and 90 days) was assessed by means of mechanical tests. Results show that sewage sludge ash leads to a reduction in density and mechanical strength. Results also show that concrete with 20% of sewage sludge ash and W/C=0.45 has a 28 day compressive strength of almost 30MPa

Mechanical performance of concrete with partial replacement of sand by sewage sludge ash from incineration

"Advanced Materials Forum VI , vol. 730-732"The production of sewage sludge from waste water treatment plants is increasing all over the world. Disposal of sewage sludge ash is a serious environmental problem. If we think of the areas needed for sludge ash disposal, we clearly understand the importance of reusing sewage sludge ash in concrete. This paper presents results related to the replacement of sand by sewage sludge ash. The sludge was characterized for chemical composition (XRF analysis), crystalline phases (XRD analysis) and pozzolanic activity. The effects of incineration on crystal phases of dry sludge were investigated. Two (W/C) ratios (0.55 and 0.45) and three sludge percentages (5%, 10% and 20%) by cement mass were used. The mechanical performance of SSAC at different curing ages (3, 7, 28 and 90 days) was assessed by means of mechanical tests. Results show that sewage sludge ash leads to a reduction in density and mechanical strength. Results also show that concrete with 20% of sewage sludge ash and W/C=0.45 has a 28 day compressive strength of almost 30MPa

Using Bad Learners to find Good Configurations

Finding the optimally performing configuration of a software system for a given setting is often challenging. Recent approaches address this challenge by learning performance models based on a sample set of configurations. However, building an accurate performance model can be very expensive (and is often infeasible in practice). The central insight of this paper is that exact performance values (e.g. the response time of a software system) are not required to rank configurations and to identify the optimal one. As shown by our experiments, models that are cheap to learn but inaccurate (with respect to the difference between actual and predicted performance) can still be used rank configurations and hence find the optimal configuration. This novel \emph{rank-based approach} allows us to significantly reduce the cost (in terms of number of measurements of sample configuration) as well as the time required to build models. We evaluate our approach with 21 scenarios based on 9 software systems and demonstrate that our approach is beneficial in 16 scenarios; for the remaining 5 scenarios, an accurate model can be built by using very few samples anyway, without the need for a rank-based approach.Comment: 11 pages, 11 figure

Underwater swarm robotics consensus control

The control of a swarm of underwater robots requires more than just a control algorithm, it requires a communications system. Underwater communications is difficult at the best of times and so large time delays and minimal information is a concern. The control system must be able to work on minimal and out of date information. The control system must also be able to control a large number of robots without a master control, a decentralized control approach. This paper describes one such control method

Design of a prototype underwater research platform for swarm robotics

To perform under water robotic research requires specialized equipment. A few pieces of electronics atop a set of wheels are not going to cut it. An underwater research platform must be waterproof, reliable, robust, recoverable and easy to maintain. It must also be able to move in 3 dimensions. Also it must be able to navigate and avoid obstacles. Further if this platform is to be part of a swarm of like platforms then it must be cost effective and relatively small. To purchase such a platform can be very expensive. However, for shallow water, a suitable platform can be built from mostly off the shelf items at little cost. This article describes the design of one such underwater robot including various sensors and communications systems that allow for swarm robotics. Whilst the robotic platform performs well, to explore what many of them would do, that is more than are available, simulation is required. This article continues to study how best to simulate these robots for a swarm, or system of systems, approach