Mangiferin: A Promising Anticancer Bioactive

Of late, several biologically active antioxidants from natural products have been investigated by the researchers in order to combat the root cause of carcinogenesis, i.e., oxidative stress. Mangiferin, a therapeutically active C-glucosylated xanthone, is extracted from pulp, peel, seed, bark and leaf of Mangifera indica. These polyphenols of mangiferin exhibit antioxidant properties and tend to decrease the oxygen-free radicals, thereby reducing the DNA damage. Indeed, its capability to modulate several key inflammatory pathways undoubtedly helps in stalling the progression of carcinogenesis. The current review article emphasizes an updated account on the patents published on the chemopreventive action of Mangiferin, apoptosis induction made on various cancer cells, along with proposed antioxidative activities and patent mapping of other important therapeutic properties. Considering it as promising polyphenol, this paper would also summarize the diverse molecular targets of Mangiferin

SIFT: Building an Internet of safe Things

As the number of connected devices explodes, the use scenarios of these devices and data have multiplied. Many of these scenarios, e.g., home automation, require tools beyond data visualizations, to express user intents and to ensure interactions do not cause undesired effects in the physical world. We present SIFT, a safety-centric programming platform for connected devices in IoT environments. First, to simplify programming, users express high-level intents in declarative IoT apps. The system then decides which sensor data and operations should be combined to satisfy the user requirements. Second, to ensure safety and compliance, the system verifies whether conflicts or policy violations can occur within or between apps. Through an office deployment, user studies, and trace analysis using a large-scale dataset from a commercial IoT app authoring platform, we demonstrate the power of SIFT and highlight how it leads to more robust and reliable IoT apps

P20-08. Glycosylation: an important factor in Env diversity

Supported by a CAVD Grant from the Bill and Melinda Gates Foundation

P2X receptors: epithelial ion channels and regulators of salt and water transport.

When the results from electrophysiological studies of renal epithelial cells are combined with data from in vivo tubule microperfusion experiments and immunohistochemical surveys of the nephron, the accumulated evidence suggests that ATP-gated ion channels, P2X receptors, play a specialized role in the regulation of ion and water movement across the renal tubule and are integral to electrolyte and fluid homeostasis. In this short review, we discuss the concept of P2X receptors as regulators of salt and water salvage pathways, as well as acknowledging their accepted role as ATP-gated ion channels

Identification of disease-causing genes using microarray data mining and gene ontology

Background: One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small quantity of samples with respect to the number of genes. This problem reduces the classification accuracy of the methods, so gene selection is essential to improve the predictive accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVMRFE) has become one of the leading methods, but its performance can be reduced because of the small sample size, noisy data and the fact that the method does not remove redundant genes. Methods: We propose a novel framework for gene selection which uses the advantageous features of conventional methods and addresses their weaknesses. In fact, we have combined the Fisher method and SVMRFE to utilize the advantages of a filtering method as well as an embedded method. Furthermore, we have added a redundancy reduction stage to address the weakness of the Fisher method and SVMRFE. In addition to gene expression values, the proposed method uses Gene Ontology which is a reliable source of information on genes. The use of Gene Ontology can compensate, in part, for the limitations of microarrays, such as having a small number of samples and erroneous measurement results. Results: The proposed method has been applied to colon, Diffuse Large B-Cell Lymphoma (DLBCL) and prostate cancer datasets. The empirical results show that our method has improved classification performance in terms of accuracy, sensitivity and specificity. In addition, the study of the molecular function of selected genes strengthened the hypothesis that these genes are involved in the process of cancer growth. Conclusions: The proposed method addresses the weakness of conventional methods by adding a redundancy reduction stage and utilizing Gene Ontology information. It predicts marker genes for colon, DLBCL and prostate cancer with a high accuracy. The predictions made in this study can serve as a list of candidates for subsequent wet-lab verification and might help in the search for a cure for cancers

Enhanced flight performance by genetic manipulation of wing shape in Drosophila

Insect wing shapes are remarkably diverse and the combination of shape and kinematics determines both aerial capabilities and power requirements. However, the contribution of any specific morphological feature to performance is not known. Using targeted RNA interference to modify wing shape far beyond the natural variation found within the population of a single species, we show a direct effect on flight performance that can be explained by physical modelling of the novel wing geometry. Our data show that altering the expression of a single gene can significantly enhance aerial agility and that the Drosophila wing shape is not, therefore, optimized for certain flight performance characteristics that are known to be important. Our technique points in a new direction for experiments on the evolution of performance specialities in animals

Modulation of human macrophage responses to mycobacterium tuberculosis by silver nanoparticles of different size and surface modification

Exposure to silver nanoparticles (AgNP) used in consumer products carries potential health risks including increased susceptibility to infectious pathogens. Systematic assessments of antimicrobial macrophage immune responses in the context of AgNP exposure are important because uptake of AgNP by macrophages may lead to alterations of innate immune cell functions. In this study we examined the effects of exposure to AgNP with different particle sizes (20 and 110 nm diameters) and surface chemistry (citrate or polyvinlypyrrolidone capping) on cellular toxicity and innate immune responses against Mycobacterium tuberculosis (M.tb) by human monocyte-derived macrophages (MDM). Exposures of MDM to AgNP significantly reduced cellular viability, increased IL8 and decreased IL10 mRNA expression. Exposure of M.tb-infected MDM to AgNP suppressed M.tb-induced expression of IL1B, IL10, and TNFA mRNA. Furthermore, M.tb-induced IL-1β, a cytokine critical for host resistance to M.tb, was inhibited by AgNP but not by carbon black particles indicating that the observed immunosuppressive effects of AgNP are particle specific. Suppressive effects of AgNP on the M.tb-induced host immune responses were in part due to AgNP-mediated interferences with the TLR signaling pathways that culminate in the activation of the transcription factor NF-κB. AgNP exposure suppressed M.tb-induced expression of a subset of NF-κB mediated genes (CSF2, CSF3, IFNG, IL1A, IL1B, IL6, IL10, TNFA, NFKB1A). In addition, AgNP exposure increased the expression of HSPA1A mRNA and the corresponding stress-induced Hsp72 protein. Up-regulation of Hsp72 by AgNP can suppress M.tb-induced NF-κB activation and host immune responses. The observed ability of AgNP to modulate infectious pathogen-induced immune responses has important public health implications

Self-rated health in middle-aged and elderly Chinese : distribution, determinants and associations with cardio-metabolic risk factors

Background: Self-rated health (SRH) has been demonstrated to be an accurate reflection of a person's health and a valid predictor of incident mortality and chronic morbidity. We aimed to evaluate the distribution and factors associated with SRH and its association with biomarkers of cardio-metabolic diseases among middle-aged and elderly Chinese. Methods: Survey of 1,458 men and 1,831 women aged 50 to 70 years, conducted in one urban and two rural areas of Beijing and Shanghai in 2005. SRH status was measured and categorized as good (very good and good) vs. not good (fair, poor and very poor). Determinants of SRH and associations with biomarkers of cardio-metabolic diseases were evaluated using logistic regression. Results: Thirty two percent of participants reported good SRH. Males and rural residents tended to report good SRH. After adjusting for potential confounders, residence, physical activity, employment status, sleep quality and presence of diabetes, cardiovascular disease, and depression were the main determinants of SRH. Those free from cardiovascular disease (OR 3.68; 95%CI 2.39; 5.66), rural residents (OR 1.89; 95% CI 1.47; 2.43), non-depressed participants (OR 2.50; 95% CI 1.67; 3.73) and those with good sleep quality (OR 2.95; 95% CI 2.22; 3.91) had almost twice or over the chance of reporting good SRH compared to their counterparts. There were significant associations -and trend- between SRH and levels of inflammatory markers, insulin levels and insulin resistance. Conclusion: Only one third of middle-aged and elderly Chinese assessed their health status as good or very good. Although further longitudinal studies are required to confirm our findings, interventions targeting social inequalities, lifestyle patterns might not only contribute to prevent chronic morbidity but as well to improve populations' perceived health