Biological effects of soft denture reline materials on L929 cells in vitro.

Soft denture reline materials have been developed to help patients when their oral mucosa is damaged or affected due to ill-fitting dentures or post-implant surgery. Although reports have indicated that these materials leach monomers and other components that do affect their biocompatibility, there is little information on what cell molecules may be implicated in these material/tissue interactions. The biocompatibility of six soft liners (Ufi Gel P, Sofreliner S, Durabase Soft, Trusoft, Softone and Coe Comfort) was evaluated using a mouse fibroblast cell line, L929. Within 2 h of material disc preparation, each of the materials was exposed by direct contact to L929 cells for periods of 24 and 48 h. The effect of this interaction was assessed by alamarBlue assay (for cell survival). The expression of integrin α5β1 and transforming growth factor β1 was also assessed using plate assays such as enzyme-linked immunosorbent assay. Trusoft, Softone and Coe Comfort showed significantly reduced cell survival compared with the other soft lining materials at each incubation period. Furthermore, there were significant differences with these same materials in the expression of both integrin α5β1 and transforming growth factor β1. Soft liner materials may affect cell viability and cellular proteins that have important roles in wound healing and the preservation of cell viability and function in the presence of environmental challenges and stresses

Network model of immune responses reveals key effectors to single and co-infection dynamics by a respiratory bacterium and a gastrointestinal helminth

Co-infections alter the host immune response but how the systemic and local processes at the site of infection interact is still unclear. The majority of studies on co-infections concentrate on one of the infecting species, an immune function or group of cells and often focus on the initial phase of the infection. Here, we used a combination of experiments and mathematical modelling to investigate the network of immune responses against single and co-infections with the respiratory bacterium Bordetella bronchiseptica and the gastrointestinal helminth Trichostrongylus retortaeformis. Our goal was to identify representative mediators and functions that could capture the essence of the host immune response as a whole, and to assess how their relative contribution dynamically changed over time and between single and co-infected individuals. Network-based discrete dynamic models of single infections were built using current knowledge of bacterial and helminth immunology; the two single infection models were combined into a co-infection model that was then verified by our empirical findings. Simulations showed that a T helper cell mediated antibody and neutrophil response led to phagocytosis and clearance of B. bronchiseptica from the lungs. This was consistent in single and co-infection with no significant delay induced by the helminth. In contrast, T. retortaeformis intensity decreased faster when co-infected with the bacterium. Simulations suggested that the robust recruitment of neutrophils in the co-infection, added to the activation of IgG and eosinophil driven reduction of larvae, which also played an important role in single infection, contributed to this fast clearance. Perturbation analysis of the models, through the knockout of individual nodes (immune cells), identified the cells critical to parasite persistence and clearance both in single and co-infections. Our integrated approach captured the within-host immuno-dynamics of bacteria-helminth infection and identified key components that can be crucial for explaining individual variability between single and co-infections in natural populations

Integração de métodos multicritério na busca da sustentabilidade agrícola para a produção de tomates no município de São José de Ubá-RJ.

Este estudo discute alternativas para os sistemas produtivos da terra no plantio de tomates em São José de Ubá-RJ e as relações de trabalho passíveis de serem colocadas em pratica de forma a promover uma agricultura sustentavel na região, priorizando os aspectos economicos, ambientais e culturais do problema. A introdução da questão cultural aumenta a complexidade da questão, sendo necessário o uso de uma metodologia capaz de lidar com toda a subjetividade envolvida nesse processo de tomada de decisão. O estudo visa contribuir para a conquista de um processo sustentavel na região, estabelecendo um processo de tomada de decisão pautado nas opinioes do agricultor, respeitando principalmente as questões culturais do problema. As características do ambiente de tomada de decisão indicaram o uso de uma combinação de métodos de apoio a decisão multicritério - MACBETH e VIP Analysis - para a seleção da melhor alternativa capaz de possibilitar o alcance dos objetivos propostos

Comparing Models for Early Warning Systems of Neglected Tropical Diseases

Early Warning Systems (EWS) are management tools to predict the occurrence of epidemics. They are based on the dependence of a given infectious disease on environmental variables. Although several neglected tropical diseases are sensitive to the effect of climate, our ability to predict their dynamics has been barely studied. In this paper, we use several models to determine if the relationship between cases and climatic variability is robust—that is, not simply an artifact of model choice. We propose that EWS should be based on results from several models that are to be compared in terms of their ability to predict future number of cases. We use a specific metric for this comparison known as the predictive R2, which measures the accuracy of the predictions. For example, an R2 of 1 indicates perfect accuracy for predictions that perfectly match observed cases. For cutaneous leishmaniasis, R2 values range from 72% to77%, well above predictions using mean seasonal values (64%). We emphasize that predictability should be evaluated with observations that have not been used to fit the model. Finally, we argue that EWS should incorporate climatic variables that are known to have a consistent relationship with the number of observed cases

Salivary characteristics may be associated with burning mouth syndrome?

Burning mouth syndrome (BMS) it is characterized by burning and uncomfortable sensations with no clinical alterations or laboratory findings. The evaluation of the salivary characteristics of people with BMS can help the understanding of the pathogenesi

Boolean network simulations for life scientists

Modern life sciences research increasingly relies on computational solutions, from large scale data analyses to theoretical modeling. Within the theoretical models Boolean networks occupy an increasing role as they are eminently suited at mapping biological observations and hypotheses into a mathematical formalism. The conceptual underpinnings of Boolean modeling are very accessible even without a background in quantitative sciences, yet it allows life scientists to describe and explore a wide range of surprisingly complex phenomena. In this paper we provide a clear overview of the concepts used in Boolean simulations, present a software library that can perform these simulations based on simple text inputs and give three case studies. The large scale simulations in these case studies demonstrate the Boolean paradigms and their applicability as well as the advanced features and complex use cases that our software package allows. Our software is distributed via a liberal Open Source license and is freely accessible fro

Integrating Quantitative Knowledge into a Qualitative Gene Regulatory Network

Despite recent improvements in molecular techniques, biological knowledge remains incomplete. Any theorizing about living systems is therefore necessarily based on the use of heterogeneous and partial information. Much current research has focused successfully on the qualitative behaviors of macromolecular networks. Nonetheless, it is not capable of taking into account available quantitative information such as time-series protein concentration variations. The present work proposes a probabilistic modeling framework that integrates both kinds of information. Average case analysis methods are used in combination with Markov chains to link qualitative information about transcriptional regulations to quantitative information about protein concentrations. The approach is illustrated by modeling the carbon starvation response in Escherichia coli. It accurately predicts the quantitative time-series evolution of several protein concentrations using only knowledge of discrete gene interactions and a small number of quantitative observations on a single protein concentration. From this, the modeling technique also derives a ranking of interactions with respect to their importance during the experiment considered. Such a classification is confirmed by the literature. Therefore, our method is principally novel in that it allows (i) a hybrid model that integrates both qualitative discrete model and quantities to be built, even using a small amount of quantitative information, (ii) new quantitative predictions to be derived, (iii) the robustness and relevance of interactions with respect to phenotypic criteria to be precisely quantified, and (iv) the key features of the model to be extracted that can be used as a guidance to design future experiments

Social Correlates of and Reasons for Primate Meat Consumption in Central Amazonia

Traditionally, humans have consumed nonhuman primates in many places, including throughout the Amazon region. However, primate consumption rates are changing with rising urbanization and market access. We characterize primate consumption in central Amazonia using 192 qualitative interviews with inhabitants in three rural villages and in the city of Tefé. We used a generalized linear model to investigate how individual consumer characteristics, such as age and gender, and livelihoods affected primate consumption. We also used principal coordinate analysis (PCoA), and word clouds and network text analyses, to describe reasons people gave for eating or avoiding primates. Our results show that men were more likely to say that they eat primates than women, and that the probability that a person said that they eat primates correlated positively with the percentage of their life lived in rural areas. People gave sentiment and ethical reasons not to eat primates. Custom influenced whether people said they eat primates both positively and negatively, while taste positively influenced whether people said they eat primates. A preference for other wild meats in rural areas, and for domestic meats in cities negatively influenced whether people said they eat primates. People also cited the perceptions that primates have a human-like appearance and that primate meat is unhealthy as reasons not to eat primates. People in urban areas also cited conservation attitudes as reasons for not eating primates. Our findings provide an understanding of factors influencing primate consumption in our study area and will be useful for designing tailored conservation initiatives by reducing hunting pressure on primates in rural settings and increasing the effectiveness of outreach campaigns in urban centers