Incidence of rotavirus infection in children with gastroenteritis attending Jos university teaching hospital, Nigeria

This study was conducted to determine the incidence of rotavirus infection in children with gastroenteritis attending Jos university teaching hospital, Plateau State. A total of 160 children with acute diarrhea were selected by random sampling. Stool samples were obtained and assayed for rotavirus antigens by enzyme linked immunosorbent assay technique using standard diagnostic BIOLINE Rotavirus kit. Demographic data of parents were also recorded. Rotavirus were detected in faeces of 22(13.8%) children with acute diarrhea, 90.9% of positive cases of rotavirus gastroenteritis were under 2 years of age with highest prevalence in children 7-12 months of age. Males excreted rotavirus at a significant higher rate than females (P < 0.05). Rotavirus excretion was highest when all three symptoms (diarrhea, fever and vomiting) occurred in the same child (7.5%) and lower when 2 symptoms occurred together (diarrhea and vomiting) with 3.8%, diarrhea and fever with 1.3% and lowest when diarrhea occurred alone with 1.3%. Playing with toys, attending day care, distance of source of water from toilet, eating of food not requiring cooking and playing with other children may serve as predisposing factors of rotavirus disease in these children

Building collaboration in multi-agent systems using reinforcement learning

© Springer Nature Switzerland AG 2018. This paper presents a proof-of concept study for demonstrating the viability of building collaboration among multiple agents through standard Q learning algorithm embedded in particle swarm optimisation. Collaboration is formulated to be achieved among the agents via competition, where the agents are expected to balance their action in such a way that none of them drifts away of the team and none intervene any fellow neighbours territory, either. Particles are devised with Q learning for self training to learn how to act as members of a swarm and how to produce collaborative/collective behaviours. The produced experimental results are supportive to the proposed idea suggesting that a substantive collaboration can be build via proposed learning algorithm

RNAi Screening in Drosophila Cells Identifies New Modifiers of Mutant Huntingtin Aggregation

The fruitfly Drosophila melanogaster is well established as a model system in the study of human neurodegenerative diseases. Utilizing RNAi, we have carried out a high-throughput screen for modifiers of aggregate formation in Drosophila larval CNS-derived cells expressing mutant human Huntingtin exon 1 fused to EGFP with an expanded polyglutamine repeat (62Q). 7200 genes, encompassing around 50% of the Drosophila genome, were screened, resulting in the identification of 404 candidates that either suppress or enhance aggregation. These candidates were subjected to secondary screening in normal length (18Q)-expressing cells and pruned to remove dsRNAs with greater than 10 off-target effects (OTEs). De novo RNAi probes were designed and synthesized for the remaining 68 candidates. Following a tertiary round of screening, 21 high confidence candidates were analyzed in vivo for their ability to modify mutant Huntingtin-induced eye degeneration and brain aggregation. We have established useful models for the study of human HD using the fly, and through our RNAi screen, we have identified new modifiers of mutant human Huntingtin aggregation and aggregate formation in the brain. Newly identified modifiers including genes related to nuclear transport, nucleotide processes, and signaling, may be involved in polyglutamine aggregate formation and Huntington disease cascades

Evolution, and functional analysis of Natural Resistance-Associated Macrophage proteins (NRAMPs) from Theobroma cacao and their role in cadmium accumulation

The presence of the toxic metal cadmium (Cd2+) in certain foodstuffs is recognised as a global problem, and there is increasing legislative pressure to reduce the content of Cd in food. The present study was conducted on cacao (Theobroma cacao), the source of chocolate, and one of the crops known to accumulate Cd in certain conditions. There are a range of possible genetic and agronomic methods being tested as a route to such reduction. As part of a gene-based approach, we focused on the Natural Resistance-Associated Macrophage Proteins (NRAMPS), a family of proton/metal transporter proteins that are evolutionarily conserved across all species from bacteria to humans. The plant NRAMP gene family are of particular importance as they are responsible for uptake of the nutritionally vital divalent cations Fe2+, Mn2+, Zn2+, as well as Cd2+. We identified the five NRAMP genes in cacao, sequenced these genes and studied their expression in various organs. We then confirmed the expression patterns in response to variation in nutrient cation availability and addition of Cd2+. Functional analysis by expression in yeast provided evidence that NRAMP5 encoded a protein capable of Cd2+ transport, and suggested this gene as a target for genetic selection/modification

Comparing Artificial Neural Networks, General Linear Models and Support Vector Machines in Building Predictive Models for Small Interfering RNAs

Exogenous short interfering RNAs (siRNAs) induce a gene knockdown effect in cells by interacting with naturally occurring RNA processing machinery. However not all siRNAs induce this effect equally. Several heterogeneous kinds of machine learning techniques and feature sets have been applied to modeling siRNAs and their abilities to induce knockdown. There is some growing agreement to which techniques produce maximally predictive models and yet there is little consensus for methods to compare among predictive models. Also, there are few comparative studies that address what the effect of choosing learning technique, feature set or cross validation approach has on finding and discriminating among predictive models.Three learning techniques were used to develop predictive models for effective siRNA sequences including Artificial Neural Networks (ANNs), General Linear Models (GLMs) and Support Vector Machines (SVMs). Five feature mapping methods were also used to generate models of siRNA activities. The 2 factors of learning technique and feature mapping were evaluated by complete 3x5 factorial ANOVA. Overall, both learning techniques and feature mapping contributed significantly to the observed variance in predictive models, but to differing degrees for precision and accuracy as well as across different kinds and levels of model cross-validation.The methods presented here provide a robust statistical framework to compare among models developed under distinct learning techniques and feature sets for siRNAs. Further comparisons among current or future modeling approaches should apply these or other suitable statistically equivalent methods to critically evaluate the performance of proposed models. ANN and GLM techniques tend to be more sensitive to the inclusion of noisy features, but the SVM technique is more robust under large numbers of features for measures of model precision and accuracy. Features found to result in maximally predictive models are not consistent across learning techniques, suggesting care should be taken in the interpretation of feature relevance. In the models developed here, there are statistically differentiable combinations of learning techniques and feature mapping methods where the SVM technique under a specific combination of features significantly outperforms all the best combinations of features within the ANN and GLM techniques

Effect of Village-wide Use of Long-Lasting Insecticidal Nets on Visceral Leishmaniasis Vectors in India and Nepal: A Cluster Randomized Trial

Visceral leishmaniasis (VL) is a vector-borne disease causing at least 60,000 deaths each year amongst an estimated half million cases, and until recently there have been no significant initiatives to reduce this burden. However, in 2005, the governments of India, Bangladesh and Nepal signed a memorandum of understanding at the World Health Assembly in Geneva for the elimination of the disease by 2015. In the absence of an effective vaccine, the program will rely on the active detection and prompt treatment of cases throughout the endemic region, combined with a recurrent indoor residual spraying (IRS) of all villages at risk. Vector control programs based on IRS are notorious for failing to maintain comprehensive spray coverage over time owing to logistical problems and lack of compliance by householders. Long-lasting insecticidal nets (LNs) have been postulated as an alternative or complement to IRS. Here we describe how comprehensive coverage of LN in trial communities reduced the indoor density of sand flies by 25% compared to communities without LNs. This provides an indication that LNs could be usefully deployed as a component of the VL control program in the Indian subcontinent

Control of bovine mastitis: old and recent therapeutic approaches

Mastitis is defined as the inflammatory response resulting of the infection of the udder tissue and it is reported in numerous species, namely in domestic dairy animals. This pathology is the most frequent disease of dairy cattle and can be potentially fatal. Mastitis is an economically important pathology associated with reduced milk production, changes in milk composition and quality, being considered one of the most costly to dairy industry. Therefore, the majority of research in the field has focused on control of bovine mastitis and many efforts are being made for the development of new and effective anti-mastitis drugs. Antibiotic treatment is an established component of mastitis control programs; however, the continuous search for new therapeutic alternatives, effective in the control and treatment of bovine mastitis, is urgent. This review will provide an overview of some conventional and emerging approaches in the management of bovine mastitis infections.F. Gomes acknowledge the financial support of the Portuguese Foundation for Science and Technology through the Grant SFRH/BPD/84488/2012 and for financial support to the CEB research center

Small RNA interference-mediated gene silencing of heparanase abolishes the invasion, metastasis and angiogenesis of gastric cancer cells

<p>Abstract</p> <p>Background</p> <p>Heparanase facilitates the invasion and metastasis of cancer cells, and is over-expressed in many kinds of malignancies. Our studies indicated that heparanase was frequently expressed in advanced gastric cancers. The aim of this study is to determine whether silencing of heparanase expression can abolish the malignant characteristics of gastric cancer cells.</p> <p>Methods</p> <p>Three heparanase-specific small interfering RNA (siRNAs) were designed, synthesized, and transfected into cultured gastric cancer cell line SGC-7901. Heparanase expression was measured by RT-PCR, real-time quantitative PCR and Western blot. Cell proliferation was detected by MTT colorimetry and colony formation assay. The <it>in vitro </it>invasion and metastasis of cancer cells were measured by cell adhesion assay, scratch assay and matrigel invasion assay. The angiogenesis capabilities of cancer cells were measured by tube formation of endothelial cells.</p> <p>Results</p> <p>Transfection of siRNA against 1496-1514 bp of encoding regions resulted in reduced expression of heparanase, which started at 24 hrs and lasted for 120 hrs post-transfection. The siRNA-mediated silencing of heparanase suppressed the cellular proliferation of SGC-7901 cells. In addition, the <it>in vitro </it>invasion and metastasis of cancer cells were attenuated after knock-down of heparanase. Moreover, transfection of heparanase-specific siRNA attenuated the <it>in vitro </it>angiogenesis of cancer cells in a dose-dependent manner.</p> <p>Conclusions</p> <p>These results demonstrated that gene silencing of heparanase can efficiently abolish the proliferation, invasion, metastasis and angiogenesis of human gastric cancer cells <it>in vitro</it>, suggesting that heparanase-specific siRNA is of potential values as a novel therapeutic agent for human gastric cancer.</p

Sustainable drainage system site assessment method using urban ecosystem services

The United Kingdom's recently updated approach to sustainable drainage enhanced biodiversity and amenity objectives by incorporating the ecosystem approach and the ecosystem services concept. However, cost-effective and reliable methods to appraise the biodiversity and amenity values of potential sustainable drainage system (SuDS)sites and their surrounding areas are still lacking, as is a method to enable designers to distinguish and link the amenity and biodiversity benefits that SuDS schemes can offer. In this paper, therefore, the authors propose two ecosystem services- and disservices-based methods (i.e. vegetation structure cover-abundance examination and cultural ecosystem services and disservices variables appraisal) to aid SuDS designers to distinguish and link amenity and biodiversity benefits, and allow initial site assessments to be performed in a cost-effective and reliable fashion. Forty-nine representative sites within Greater Manchester were selected to test the two methods. Amenity and biodiversity were successfully assessed and habitat for species, carbon sequestration, recreation and education ecosystem services scores were produced,which will support SuDS retrofit design decision-making. Large vegetated SuDS sites with permanent aquatic features were found to be most capable of enhancing biodiversity- and amenity-related ecosystem services. Habitat for species and recreation ecosystem services were also found to be positively linked to each other. Finally, waste bins on site were found to help reduce dog faeces and litter coverage. Overall, the findings presented here enable future SuDS retrofit designs to be more wildlife friendly and socially inclusive