Compressing web Geodata for real-time environmental applications

The advent of connected mobile devices has caused an unprecedented availability of geo-referenced user-generated content, which can be exploited for environment monitoring. In particular, Augmented Reality (AR) mobile applications can be designed to enable citizens collect observations, by overlaying relevant meta-data on their current view. This class of applications rely on multiple meta-data, which must be properly compressed for transmission and real-time usage. This paper presents a two-stage approach for the compression of Digital Elevation Model (DEM) data and geographic entities for a mountain environment monitoring mobile AR application. The proposed method is generic and could be applied to other types of geographical data

Effects of Health Insurance on Perceived Quality of Care Among Latinos in the United States

There is suggestive evidence that lower rates of health insurance coverage increases the gaps in quality and access to care among Latinos as compared with non-Latino whites. In order to examine these potential disparities, we assessed the effects of insurance coverage and multiple covariates on perceived quality of care. To assess the distribution of perceived quality of care received in a national Latino population sample, and the role of insurance in different patient subgroups. Telephone interviews conducted between 2007 and 2008 using the Pew Hispanic Center/Robert Wood Johnson Foundation Latino Health Surveys (Waves 1 and 2). Randomly selected Latino adults aged ≥18 years living in the United States. Pearson χ2 tests identified associations among various demographic variables by quality of care ratings (poor, fair, good, excellent) for the insured and uninsured (Wave 1: N = 3545). Subgroup analyses were conducted among Wave 2 participants reporting chronic conditions (N = 1067). Bivariate and multivariate analyses were conducted to estimate the effects of insurance, demographic variables and consumer characteristics on quality of care. Insurance availability had an odds ratio of 1.47 (95% CI, 1.22–1.76) net of confounders in predicting perceived quality of care among Latinos. The largest gap in rates of excellent/good ratings occurred among the insured with eight or more doctor visits compared to the uninsured (76.2% vs. 54.6%, P < .05). Future research can gain additional insights by examining the impact of health insurance on processes of care with a refined focus on specific transactions between consumers and providers’ support staff and physicians guided by the principles of patient-centered care

KIDMAP, a web based system for gathering patients' feedback on their doctors

<p>Abstract</p> <p>Background</p> <p>The gathering of feedback on doctors from patients after consultations is an important part of patient involvement and participation. This study first assesses the 23-item Patient Feedback Questionnaire (PFQ) designed by the Picker Institute, Europe, to determine whether these items form a single latent trait. Then, an Internet module with visual representation is developed to gather patient views about their doctors; this program then distributes the individualized results by email.</p> <p>Methods</p> <p>A total of 450 patients were randomly recruited from a 1300-bed-size medical center in Taiwan. The Rasch rating scale model was used to examine the data-fit. Differential item functioning (DIF) analysis was conducted to verify construct equivalence across the groups. An Internet module with visual representation was developed to provide doctors with the patient's online feedback.</p> <p>Results</p> <p>Twenty-one of the 23 items met the model's expectation, namely that they constitute a single construct. The test reliability was 0.94. DIF was found between ages and different kinds of disease, but not between genders and education levels. The visual approach of the KIDMAP module on the WWW seemed to be an effective approach to the assessment of patient feedback in a clinical setting.</p> <p>Conclusion</p> <p>The revised 21-item PFQ measures a single construct. Our work supports the hypothesis that the revised PFQ online version is both valid and reliable, and that the KIDMAP module is good at its designated task. Further research is needed to confirm data congruence for patients with chronic diseases.</p

A genetic ensemble approach for gene-gene interaction identification

<p>Abstract</p> <p>Background</p> <p>It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging.</p> <p>Methods</p> <p>In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA) and an ensemble of classifiers (called genetic ensemble). Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP) subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise <it>double fault </it>is designed to quantify the degree of complementarity.</p> <p>Conclusions</p> <p>Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR) and is slightly better than Polymorphism Interaction Analysis (PIA), which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of combining identification results from different algorithms.</p

Transcriptome Profiling of Bovine Milk Oligosaccharide Metabolism Genes Using RNA-Sequencing

This study examines the genes coding for enzymes involved in bovine milk oligosaccharide metabolism by comparing the oligosaccharide profiles with the expressions of glycosylation-related genes. Fresh milk samples (n = 32) were collected from four Holstein and Jersey cows at days 1, 15, 90 and 250 of lactation and free milk oligosaccharide profiles were analyzed. RNA was extracted from milk somatic cells at days 15 and 250 of lactation (n = 12) and gene expression analysis was conducted by RNA-Sequencing. A list was created of 121 glycosylation-related genes involved in oligosaccharide metabolism pathways in bovine by analyzing the oligosaccharide profiles and performing an extensive literature search. No significant differences were observed in either oligosaccharide profiles or expressions of glycosylation-related genes between Holstein and Jersey cows. The highest concentrations of free oligosaccharides were observed in the colostrum samples and a sharp decrease was observed in the concentration of free oligosaccharides on day 15, followed by progressive decrease on days 90 and 250. Ninety-two glycosylation-related genes were expressed in milk somatic cells. Most of these genes exhibited higher expression in day 250 samples indicating increases in net glycosylation-related metabolism in spite of decreases in free milk oligosaccharides in late lactation milk. Even though fucosylated free oligosaccharides were not identified, gene expression indicated the likely presence of fucosylated oligosaccharides in bovine milk. Fucosidase genes were expressed in milk and a possible explanation for not detecting fucosylated free oligosaccharides is the degradation of large fucosylated free oligosaccharides by the fucosidases. Detailed characterization of enzymes encoded by the 92 glycosylation-related genes identified in this study will provide the basic knowledge for metabolic network analysis of oligosaccharides in mammalian milk. These candidate genes will guide the design of a targeted breeding strategy to optimize the content of beneficial oligosaccharides in bovine milk

Modulation of Neutrophil Function by a Secreted Mucinase of Escherichia coli O157∶H7

Escherichia coli O157∶H7 is a human enteric pathogen that causes hemorrhagic colitis which can progress to hemolytic uremic syndrome, a severe kidney disease with immune involvement. During infection, E. coli O157∶H7 secretes StcE, a metalloprotease that promotes the formation of attaching and effacing lesions and inhibits the complement cascade via cleavage of mucin-type glycoproteins. We found that StcE cleaved the mucin-like, immune cell-restricted glycoproteins CD43 and CD45 on the neutrophil surface and altered neutrophil function. Treatment of human neutrophils with StcE led to increased respiratory burst production and increased cell adhesion. StcE-treated neutrophils exhibited an elongated morphology with defective rear detachment and impaired migration, suggesting that removal of the anti-adhesive capability of CD43 by StcE impairs rear release. Use of zebrafish embryos to model neutrophil migration revealed that StcE induced neutrophil retention in the fin after tissue wounding, suggesting that StcE modulates neutrophil-mediated inflammation in vivo. Neutrophils are crucial innate effectors of the antibacterial immune response and can contribute to severe complications caused by infection with E. coli O157∶H7. Our data suggest that the StcE mucinase can play an immunomodulatory role by directly altering neutrophil function during infection. StcE may contribute to inflammation and tissue destruction by mediating inappropriate neutrophil adhesion and activation

Sweet taste pleasantness is modulated by morphine and naltrexone

Rodent models highlight the key role of µ-opioid receptor (MOR) signaling in palatable food consumption. In humans however, the effects of MOR stimulation on eating and food liking remain unclear. In a bidirectional psychopharmacological cross-over study, 49 healthy men underwent a sweet taste paradigm following double-blind administration of the MOR agonist morphine, placebo, and the opioid antagonist nalt rexone. We hypothesized that behaviors regulated by the endogenous MOR system would be enhanced by MOR agonism, and decreased by antagonism. The strongest drug effects were expected for the sweetest (high-calorie) sucrose solution, as reported in rodents. However, very sweet sucrose-water solutions are considered sickly and aversive by many people (called sweet dislikers). Since both sweet likers and dislikers were tested, we were able to assess whether MOR manipulations affect pleasantness ratings differently depending on both subjective and objective value. As hypothesized, MOR stimulation with morphine increased pleasantness of the sweetest of five sucrose solutions, without enhancing pleasantness of the lower-sucrose solutions. For opioid antagonism, an opposite pattern was observed for the sweetest drink only. This bidirectional effect of agonist and antagonist treatment is consistent with rodent findings that MOR manipulations most strongly affect the highest-calorie foods. Importantly, the observed drug effects on pleasantness of the sweetest drink did not differ between sweet likers and dislikers. We speculate that the MOR system promotes survival in part by increasing concordance between the objective (caloric) and subjective (hedonic) value of food stimuli, so that feeding behaviour becomes more focused on the richest food available