Piggy Bank: Experience the Semantic Web Inside Your Web Browser

The original publication is available at www.springerlink.com http://dx.doi.org/10.1007/11574620_31The Semantic Web Initiative envisions a Web wherein information is offered free of presentation, allowing more effective exchange and mixing across web sites and across web pages. But without substantial Semantic Web content, few tools will be written to consume it; without many such tools, there is little appeal to publish Semantic Web content. To break this chicken-and-egg problem, thus enabling more flexible information access, we have created a web browser extension called Piggy Bankthat lets users make use of Semantic Web content within Web content as users browse the Web. Wherever Semantic Web content is not available, Piggy Bank can invoke screenscrapers to restructure information within web pages into Semantic Web format. Through the use of Semantic Web technologies, Piggy Bank provides direct, immediate benefits to users in their use of the existing Web. Thus, the existence of even just a few Semantic Web-enabled sites or a few scrapers already benefits users. Piggy Bank thereby offers an easy, incremental upgrade path to users without requiring a wholesale adoption of the Semantic Web’s vision. To further improve this Semantic Web experience, we have created Semantic Bank, a web server application that lets Piggy Bank users share the Semantic Web information they have collected, enabling collaborative efforts to build sophisticated Semantic Web information repositories through simple, everyday’s use of Piggy Bank

Germline variation in inflammation-related pathways and risk of Barrett's oesophagus and oesophageal adenocarcinoma

Esophageal adenocarcinoma (EA) incidence has risen sharply in Western countries over recent decades. Local and systemic inflammation, operating downstream of disease-associated exposures, is considered an important contributor to EA pathogenesis. Several risk factors have been identified for EA and its precursor, Barrett’s esophagus (BE), including symptomatic reflux, obesity, and smoking. The role of inherited genetic susceptibility remains an area of active investigation. To explore whether germline variation related to inflammatory processes influences susceptibility to BE/EA, we used data from a genome-wide association study (GWAS) of 2,515 EA cases, 3,295 BE cases, and 3,207 controls. Our analysis included 7,863 single nucleotide polymorphisms (SNPs) in 449 genes assigned to five pathways: cyclooxygenase (COX), cytokine signaling, oxidative stress, human leukocyte antigen, and NFκB. A principal components-based analytic framework was employed to evaluate pathway-level and gene-level associations with disease risk. We identified a significant signal for the COX pathway in relation to BE risk (P=0.0059, FDR q=0.03), and in gene-level analyses found an association with MGST1 (microsomal glutathione-S-transferase 1; P=0.0005, q=0.005). Assessment of 36 MGST1 SNPs identified 14 variants associated with elevated BE risk (q<0.05). Of these, four were subsequently confirmed (P<5.5 × 10−5) in a meta-analysis encompassing an independent set of 1,851 BE cases and 3,496 controls. Three of these SNPs (rs3852575, rs73112090, rs4149204) were associated with similar elevations in EA risk. This study provides the most comprehensive evaluation of inflammation-related germline variation in relation to risk of BE/EA, and suggests that variants in MGST1 influence disease susceptibility

Burden of Uncontrolled Severe Asthma With and Without Elevated Type-2 Inflammatory Biomarkers

Background: Many patients with asthma have type-2 airway inflammation, identified by the presence of biomarkers, including history of allergy, high blood eosinophil (EOS) count, and high fractional exhaled nitric oxide levels. Objective: To assess disease burden in relation to type-2 inflammatory biomarker status (history of allergy, blood EOS count, and fractional exhaled nitric oxide level) in patients with uncontrolled and controlled severe asthma in the NOVEL observational longiTudinal studY (NOVELTY) (NCT02760329). Methods: Asthma diagnosis and severity were physician-reported. Control was defined using Asthma Control Test score (uncontrolled &lt;20, controlled ≥20) and/or 1 or more severe physician-reported exacerbation in the previous year. Biomarker distribution (history of allergy, blood EOS count, and fractional exhaled nitric oxide level), symptom burden (Asthma Control Test score, modified Medical Research Council dyspnea scale), health status (St George's Respiratory Questionnaire score), exacerbations, and health care resource utilization were assessed. Results: Of 647 patients with severe asthma, 446 had uncontrolled and 123 had controlled asthma. Among those with uncontrolled asthma, 196 (44%) had 2 or more positive biomarkers, 187 (42%) had 1 positive biomarker, 325 (73%) had low blood EOS, and 63 (14%) were triple-negative. Disease burden was similarly high across uncontrolled subgroups, irrespective of biomarker status, with poor symptom control (Asthma Control Test score 14.9-16.6), impaired health status (St George's Respiratory Questionnaire total score 46.7-49.4), clinically important breathlessness (modified Medical Research Council grade ≥2 in 47.3%-57.1%), and 1 or more severe exacerbation (70.6%-76.2%). Conclusions: Type-2 inflammatory biomarkers did not differentiate disease burden in patients with severe asthma. Patients with low type-2 inflammatory biomarker levels have few biologic therapy options; their needs should be addressed

Cluster Analyses From the Real-World NOVELTY Study: Six Clusters Across the Asthma-COPD Spectrum

Background: Asthma and chronic obstructive pulmonary disease (COPD) are complex diseases, the definitions of which overlap. Objective: To investigate clustering of clinical/physiological features and readily available biomarkers in patients with physician-assigned diagnoses of asthma and/or COPD in the NOVEL observational longiTudinal studY (NOVELTY; NCT02760329). Methods: Two approaches were taken to variable selection using baseline data: approach A was data-driven, hypothesis-free and used the Pearson dissimilarity matrix; approach B used an unsupervised Random Forest guided by clinical input. Cluster analyses were conducted across 100 random resamples using partitioning around medoids, followed by consensus clustering. Results: Approach A included 3796 individuals (mean age, 59.5 years; 54% female); approach B included 2934 patients (mean age, 60.7 years; 53% female). Each identified 6 mathematically stable clusters, which had overlapping characteristics. Overall, 67% to 75% of patients with asthma were in 3 clusters, and approximately 90% of patients with COPD were in 3 clusters. Although traditional features such as allergies and current/ex-smoking (respectively) were higher in these clusters, there were differences between clusters and approaches in features such as sex, ethnicity, breathlessness, frequent productive cough, and blood cell counts. The strongest predictors of the approach A cluster membership were age, weight, childhood onset, prebronchodilator FEV1, duration of dust/fume exposure, and number of daily medications. Conclusions: Cluster analyses in patients from NOVELTY with asthma and/or COPD yielded identifiable clusters, with several discriminatory features that differed from conventional diagnostic characteristics. The overlap between clusters suggests that they do not reflect discrete underlying mechanisms and points to the need for identification of molecular endotypes and potential treatment targets across asthma and/or COPD

Burden of Uncontrolled Severe Asthma With and Without Elevated Type-2 Inflammatory Biomarkers

Background: Many patients with asthma have type-2 airway inflammation, identified by the presence of biomarkers, including history of allergy, high blood eosinophil (EOS) count, and high fractional exhaled nitric oxide levels. Objective: To assess disease burden in relation to type-2 inflammatory biomarker status (history of allergy, blood EOS count, and fractional exhaled nitric oxide level) in patients with uncontrolled and controlled severe asthma in the NOVEL observational longiTudinal studY (NOVELTY) (NCT02760329). Methods: Asthma diagnosis and severity were physician-reported. Control was defined using Asthma Control Test score (uncontrolled = 20) and/or 1 or more severe physician-reported exacerbation in the previous year. Biomarker distribution (history of allergy, blood EOS count, and fractional exhaled nitric oxide level), symptom burden (Asthma Control Test score, modified Medical Research Council dyspnea scale), health status (St George's Respiratory Questionnaire score), exacerbations, and health care resource utilization were assessed. Results: Of 647 patients with severe asthma, 446 had uncontrolled and 123 had controlled asthma. Among those with uncontrolled asthma, 196 (44%) had 2 or more positive biomarkers, 187 (42%) had 1 positive biomarker, 325 (73%) had low blood EOS, and 63 (14%) were triple-negative. Disease burden was similarly high across uncontrolled subgroups, irrespective of biomarker status, with poor symptom control (Asthma Control Test score 14.9-16.6), impaired health status (St George's Respiratory Questionnaire total score 46.7-49.4), clinically important breathlessness (modified Medical Research Council grade >= 2 in 47.3%-57.1%), and 1 or more severe exacerbation (70.6%-76.2%). Conclusions: Type-2 inflammatory biomarkers did not differentiate disease burden in patients with severe asthma. Patients with low type-2 inflammatory biomarker levels have few biologic therapy options; their needs should be addressed

Prasadiseius incanus Prasad and Guanilo 2011, n. sp.

Prasadiseius incanus Prasad and Guanilo, n. sp. (Figs. 1 – 26)Published as part of Prasad, V., Guanilo, A. D., Grados, J. & Prassad, I., 2011, A New Species Of Prasadiseius Wainstein, 1970 (Acari: Otopheidomenidae) From Hawk Moths (Lepidoptera: Sphingidae) In Peru, pp. 99-125 in Acarologia 51 (1) on page 109, DOI: 10.1051/acarologia/20111999, http://zenodo.org/record/539278