Citizen Science applied to building healthier community environments::advancing the field through shared construct and measurement development

Background Physical inactivity across the lifespan remains a public health issue for many developed countries. Inactivity has contributed considerably to the pervasiveness of lifestyle diseases. Government, national and local agencies and organizations have been unable to systematically, and in a coordinated way, translate behavioral research into practice that makes a difference at a population level. One approach for mobilizing multi-level efforts to improve the environment for physical activity is to engage in a process of citizen science. Citizen Science here is defined as a participatory research approach involving members of the public working closely with research investigators to initiate and advance scientific research projects. However, there are no common measures or protocols to guide citizen science research at the local community setting. Objectives We describe overarching categories of constructs that can be considered when designing citizen science projects expected to yield multi-level interventions, and provide an example of the citizen science approach to promoting PA. We also recommend potential measures across different levels of impact. Discussion Encouraging some consistency in measurement across studies will potentially accelerate the efficiency with which citizen science participatory research provides new insights into and solutions to the behaviorally-based public health issues that drive most of morbidity and mortality. The measures described in this paper abide by four fundamental principles specifically selected for inclusion in citizen science projects: feasibility, accuracy, propriety, and utility. The choice of measures will take into account the potential resources available for outcome and process evaluation. Our intent is to emphasize the importance for all citizen science participatory projects to follow an evidence-based approach and ensure that they incorporate an appropriate assessment protocol. Conclusions We provided the rationale for and a list of contextual factors along with specific examples of measures to encourage consistency among studies that plan to use a citizen science participatory approach. The potential of this approach to promote health and wellbeing in communities is high and we hope that we have provided the tools needed to optimally promote synergistic gains in knowledge across a range of Citizen Science participatory projects

Systematic survey of randomized trials evaluating the impact of alternative diagnostic strategies on patient-important outcomes

Objectives: To provide a perspective on the current practice of randomized clinical trials (RCTs) of diagnostic strategies focusing on patient-important outcomes. Study Design and Setting: We conducted a comprehensive search of MEDLINE and included RCTs published in full-text reports that evaluated alternative diagnostic strategies. Results: Of 56,912 unique citations, we sampled 7,500 and included 103 eligible RCTs, therefore suggesting that MEDLINE includes approximately 781 diagnostic RCTs. The 103 eligible trials reported on: mortality (n = 41; 39.8%); morbidities (n = 63; 61.2%); symptoms/quality of life/functional status (n = 14; 13.6%); and on composite end points (n = 10; 9.7%). Of the studies that reported statistically significant results (n = 12; 11.6%), we judged 7 (58.3%) as at low risk of bias with respect to missing outcome data and 4 (33.3%) as at low risk of bias regarding blinding. Of the 41 RCTs that reported on mortality, only one (2.4%) reported statistically significant results. Of 63 RCTs addressing morbidity outcomes, 11 (17.5%) reported statistically significant results, all of which reported relative effects of greater than 20%. Conclusion: RCTs of diagnostic tests are not uncommon, and sometimes suggest benefits on patient-important outcomes but often suffer from limitations in sample size and conduct. (C) 2017 Elsevier Inc. All rights reserved.Peer reviewe

Genomic epidemiology of a national outbreak of post-surgical Mycobacterium abscessus wound infections in Brazil.

An epidemic of post-surgical wound infections, caused by a non-tuberculous mycobacterium, has been on-going in Brazil. It has been unclear whether one or multiple lineages are responsible and whether their wide geographical distribution across Brazil is due to spread from a single point source or is the result of human-mediated transmission. 188 isolates, collected from nine Brazilian states, were whole genome sequenced and analysed using phylogenetic and comparative genomic approaches. The isolates from Brazil formed a single clade, which was estimated to have emerged in 2003. We observed temporal and geographic structure within the lineage that enabled us to infer the movement of sub-lineages across Brazil. The genome size of the Brazilian lineage was reduced relative to most strains in the three subspecies of Mycobacterium abscessus and contained a novel plasmid, pMAB02, in addition to the previously described pMAB01 plasmid. One lineage, which emerged just prior to the initial outbreak, is responsible for the epidemic of post-surgical wound infections in Brazil. Phylogenetic analysis indicates that multiple transmission events led to its spread. The presence of a novel plasmid and the reduced genome size suggest that the lineage has undergone adaptation to the surgical niche

A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes

dentification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 x 10(-8)) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.Peer reviewe

Electrophysiological characterization of subclinical and overt hypertrophic cardiomyopathy by magnetic resonance imaging-guided electrocardiography

Background: Ventricular arrhythmia in hypertrophic cardiomyopathy (HCM) relates to adverse structural change and genetic status. Cardiovascular magnetic resonance (CMR)–guided electrocardiographic imaging (ECGI) noninvasively maps cardiac structural and electrophysiological (EP) properties. Objectives: The purpose of this study was to establish whether in subclinical HCM (genotype [G]+ left ventricular hypertrophy [LVH]−), ECGI detects early EP abnormality, and in overt HCM, whether the EP substrate relates to genetic status (G+/G−LVH+) and structural phenotype. Methods: This was a prospective 211-participant CMR-ECGI multicenter study of 70 G+LVH−, 104 LVH+ (51 G+/53 G−), and 37 healthy volunteers (HVs). Local activation time (AT), corrected repolarization time, corrected activation-recovery interval, spatial gradients (GAT/GRTc), and signal fractionation were derived from 1,000 epicardial sites per participant. Maximal wall thickness and scar burden were derived from CMR. A support vector machine was built to discriminate G+LVH− from HV and low-risk HCM from those with intermediate/high-risk score or nonsustained ventricular tachycardia. Results: Compared with HV, subclinical HCM showed mean AT prolongation (P = 0.008) even with normal 12-lead electrocardiograms (ECGs) (P = 0.009), and repolarization was more spatially heterogenous (GRTc: P = 0.005) (23% had normal ECGs). Corrected activation-recovery interval was prolonged in overt vs subclinical HCM (P < 0.001). Mean AT was associated with maximal wall thickness; spatial conduction heterogeneity (GAT) and fractionation were associated with scar (all P < 0.05), and G+LVH+ had more fractionation than G−LVH+ (P = 0.002). The support vector machine discriminated subclinical HCM from HV (10-fold cross-validation accuracy 80% [95% CI: 73%-85%]) and identified patients at higher risk of sudden cardiac death (accuracy 82% [95% CI: 78%-86%]). Conclusions: In the absence of LVH or 12-lead ECG abnormalities, HCM sarcomere gene mutation carriers express an aberrant EP phenotype detected by ECGI. In overt HCM, abnormalities occur more severely with adverse structural change and positive genetic status

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis