Epidemiology and interactions of Human Immunodeficiency Virus - 1 and Schistosoma mansoni in sub-Saharan Africa.

Human Immunodeficiency Virus-1/AIDS and Schistosoma mansoni are widespread in sub-Saharan Africa and co-infection occurs commonly. Since the early 1990s, it has been suggested that the two infections may interact and potentiate the effects of each other within co-infected human hosts. Indeed, S. mansoni infection has been suggested to be a risk factor for HIV transmission and progression in Africa. If so, it would follow that mass deworming could have beneficial effects on HIV-1 transmission dynamics. The epidemiology of HIV in African countries is changing, shifting from urban to rural areas where the prevalence of Schistosoma mansoni is high and public health services are deficient. On the other side, the consequent pathogenesis of HIV-1/S. mansoni co-infection remains unknown. Here we give an account of the epidemiology of HIV-1 and S. mansoni, discuss co-infection and possible biological causal relationships between the two infections, and the potential impact of praziquantel treatment on HIV-1 viral loads, CD4+ counts and CD4+/CD8+ ratio. Our review of the available literature indicates that there is evidence to support the hypothesis that S. mansoni infections can influence the replication of the HIV-1, cell-to-cell transmission, as well as increase HIV progression as measured by reduced CD4+ T lymphocytes counts. If so, then deworming of HIV positive individuals living in endemic areas may impact on HIV-1 viral loads and CD4+ T lymphocyte counts.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Small animal models to understand pathogenesis of osteoarthritis and use of stem cell in cartilage regeneration

Osteoarthritis (OA) is one of the most common diseases, which affect the correct functionality of synovial joints and is characterized by articular cartilage degradation. Limitation in the treatment of OA is mostly due to the very limited regenerative characteristic of articular cartilage once is damaged. Small animal models are of particular importance for mechanistic analysis to understand the processes that affect cartilage degradation. Combination of joint injury techniques with the use of stem cells has been shown to be an important tool for understanding the processes of cartilage degradation and regeneration. Implementation of stem cells and small animal models are important tools to help researchers to find a solution that could ameliorate and prevent the symptoms of OA

Memristor multiport readout: A closed-form solution for sneak paths

In this paper, we introduce for the first time, a closed-form solution for the memristor-based memory sneak paths without using any gating elements. The introduced technique fully eliminates the effect of sneak paths by reading the stored data using multiple access points and evaluating a simple addition/subtraction on the different readings. The new method requires fewer reading steps compared to previously reported techniques, and has a very small impact on the memory density. To verify the underlying theory, the proposed system is simulated using Synopsys HSPICE showing the ability to achieve a 100% sneak-path error-free memory. In addition, the effect of quantization bits on the system performance is studied. © 2014 IEEE

Memristor multiport readout: A closed-form solution for sneak paths

In this paper, we introduce for the first time, a closed-form solution for the memristor-based memory sneak paths without using any gating elements. The introduced technique fully eliminates the effect of sneak paths by reading the stored data using multiple access points and evaluating a simple addition/subtraction on the different readings. The new method requires fewer reading steps compared to previously reported techniques, and has a very small impact on the memory density. To verify the underlying theory, the proposed system is simulated using Synopsys HSPICE showing the ability to achieve a 100% sneak-path error-free memory. In addition, the effect of quantization bits on the system performance is studied. © 2014 IEEE

High penetration of rooftop photovoltaic cells in low voltage distribution networks: Voltage imbalance and improvement

Installation of domestic rooftop photovoltaic cells (PVs) is increasing due to feed–in tariff and motivation driven by environmental concerns. Even though the increase in the PV installation is gradual, their locations and ratings are often random. Therefore, such single–phase bi–directional power flow caused by the residential customers can have adverse effect on the voltage imbalance of a three–phase distribution network. In this chapter, a voltage imbalance sensitivity analysis and stochastic evaluation are carried out based on the ratings and locations of single–phase grid–connected rooftop PVs in a residential low voltage distribution network. The stochastic evaluation, based on Monte Carlo method, predicts a failure index of non–standard voltage imbalance in the network in presence of PVs. Later, the application of series and parallel custom power devices are investigated to improve voltage imbalance problem in these feeders. In this regard, first, the effectiveness of these two custom power devices is demonstrated vis–à–vis the voltage imbalance reduction in feeders containing rooftop PVs. Their effectiveness is investigated from the installation location and rating points of view. Later, a Monte Carlo based stochastic analysis is utilized to investigate their efficacy for different uncertainties of load and PV rating and location in the network. This is followed by demonstrating the dynamic feasibility and stability issues of applying these devices in the network