Progressive Visceral Leishmaniasis Is Driven by Dominant Parasite-induced STAT6 Activation and STAT6-dependent Host Arginase 1 Expression

The clinicopathological features of the hamster model of visceral leishmaniasis (VL) closely mimic active human disease. Studies in humans and hamsters indicate that the inability to control parasite replication in VL could be related to ineffective classical macrophage activation. Therefore, we hypothesized that the pathogenesis of VL might be driven by a program of alternative macrophage activation. Indeed, the infected hamster spleen showed low NOS2 but high arg1 enzyme activity and protein and mRNA expression (p<0.001) and increased polyamine synthesis (p<0.05). Increased arginase activity was also evident in macrophages isolated from the spleens of infected hamsters (p<0.05), and arg1 expression was induced by L. donovani in primary hamster peritoneal macrophages (p<0.001) and fibroblasts (p<0.01), and in a hamster fibroblast cell line (p<0.05), without synthesis of endogenous IL-4 or IL-13 or exposure to exogenous cytokines. miRNAi-mediated selective knockdown of hamster arginase 1 (arg1) in BHK cells led to increased generation of nitric oxide and reduced parasite burden (p<0.005). Since many of the genes involved in alternative macrophage activation are regulated by Signal Transducer and Activator of Transcription-6 (STAT6), and because the parasite-induced expression of arg1 occurred in the absence of exogenous IL-4, we considered the possibility that L. donovani was directly activating STAT6. Indeed, exposure of hamster fibroblasts or macrophages to L. donovani resulted in dose-dependent STAT6 activation, even without the addition of exogenous cytokines. Knockdown of hamster STAT6 in BHK cells with miRNAi resulted in reduced arg1 mRNA expression and enhanced control of parasite replication (p<0.0001). Collectively these data indicate that L. donovani infection induces macrophage STAT6 activation and STAT6-dependent arg1 expression, which do not require but are amplified by type 2 cytokines, and which contribute to impaired control of infection

Approaches in biotechnological applications of natural polymers

Natural polymers, such as gums and mucilage, are biocompatible, cheap, easily available and non-toxic materials of native origin. These polymers are increasingly preferred over synthetic materials for industrial applications due to their intrinsic properties, as well as they are considered alternative sources of raw materials since they present characteristics of sustainability, biodegradability and biosafety. As definition, gums and mucilages are polysaccharides or complex carbohydrates consisting of one or more monosaccharides or their derivatives linked in bewildering variety of linkages and structures. Natural gums are considered polysaccharides naturally occurring in varieties of plant seeds and exudates, tree or shrub exudates, seaweed extracts, fungi, bacteria, and animal sources. Water-soluble gums, also known as hydrocolloids, are considered exudates and are pathological products; therefore, they do not form a part of cell wall. On the other hand, mucilages are part of cell and physiological products. It is important to highlight that gums represent the largest amounts of polymer materials derived from plants. Gums have enormously large and broad applications in both food and non-food industries, being commonly used as thickening, binding, emulsifying, suspending, stabilizing agents and matrices for drug release in pharmaceutical and cosmetic industries. In the food industry, their gelling properties and the ability to mold edible films and coatings are extensively studied. The use of gums depends on the intrinsic properties that they provide, often at costs below those of synthetic polymers. For upgrading the value of gums, they are being processed into various forms, including the most recent nanomaterials, for various biotechnological applications. Thus, the main natural polymers including galactomannans, cellulose, chitin, agar, carrageenan, alginate, cashew gum, pectin and starch, in addition to the current researches about them are reviewed in this article.. }To the Conselho Nacional de Desenvolvimento Cientfíico e Tecnológico (CNPq) for fellowships (LCBBC and MGCC) and the Coordenação de Aperfeiçoamento de Pessoal de Nvíel Superior (CAPES) (PBSA). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and COMPETE 2020 (POCI-01-0145-FEDER-006684) (JAT)

Political Profiling using Feature Engineering and NLP

Public surveys are predominantly used when forecasting election outcomes. While the approach has had significant successes, the surveys have had their failures as well, especially when it comes to accuracy and reliability. As a result, it becomes challenging for political parties to spend their campaign budgets in a manner that facilitates the growth of a favorable and verifiable public opinion. Consequently, it is critical that a more accurate methodology to predict election outcome is developed. In this paper, we present an evaluation of the impact of utilizing dynamic public data on predicting the outcome of elections. Our model yielded a 0.71 Pearson Correlation between derived features and percentage of votes predicted. Hence, we can conclude that candidates having affiliation with notable organizations and having participation in public events greatly increases their likelihood to win. Also, having Wikipedia presence with some notable key words like ’Congress’, ’Republican’ and ’House’, makes them stand out in their constituencies. Together these features explain 80 percent of the response variable, which in this case is percentage of votes the candidates get in their respective constituencies