Mobile applications in government services (mG-App) from user's perspectives: A predictive modelling approach

YesMobile applications are becoming a preferred delivery method for the government sector and contributing to more convenient and timely services to citizens. This study examines the intention to use mobile applications for the government services (mG-App) in Oman. This study extended the Unified Theory of Acceptance and Use of Technology (UTAUT) model by including two constructs namely trust and information quality. Data were collected from 513 mobile application users across Oman. The research model was analysed in two stages. First, structural equation modelling (SEM) was employed to determine significant determinants affecting users’ acceptance of mG-App. In the second stage, a neural network model was used to validate SEM results and determine the relative importance of determinants of acceptance of mG-App. The findings revealed that trust and performance expectancy are the strongest determinants influencing the acceptance of mG-App. The findings of this research have provided theoretical contributions to the existing research on mG-App and practical implications to decision-makers involved in the development and implementation of mG-App in in Oman

Authentication and Discrimination of Green Tea Samples Using UV-Visible, FTIR and HPLC Techniques Coupled with Chemometrics Analysis

Green tea is a popular beverage consumed worldwide. Its quality should be controlled adequately as the quality is influenced by several factors in addition to adulterations. This study aimed to develop a simple method for assessing the quality of green tea samples obtained from the South and the East Asian regions. The UV-Visible, FTIR and HPLC data from 38 samples were subjected to multivariate analyses using the unsupervised recognition techniques comprising Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA). The model for their authentication was constructed and validated by applying the supervised recognition techniques as Soft Independent Modeling of Class Analogy (SIMCA) and Partial Least Square Discriminant Analysis (PLS-DA). The percentages of caffeine in the identified samples were determined using a validated HPLC assay in addition to in vitro determination of their antioxidant activity using DPPH radical-scavenging capacity assay. HCA and PCA based on UV data successfully distributed the tested samples into informative clusters. However, that obtained from visible data could only differentiate samples with respect to their powdered condition. On the contrary, PCA from FTIR and HPLC data could hardly discriminate any of the samples. The models constructed using SIMCA and PLS-DA showed a good class separation between the South and the East Asian samples. The percentages of caffeine in the identified samples and the IC50 in DPPH assay are greatly diverse among all the tested samples. Thus, UV spectroscopy and chemometrics have provided a simple and quick tool for the quality control of commercial green tea samples

Are mice good models for human neuromuscular disease? Comparing muscle excursions in walking between mice and humans

The mouse is one of the most widely used animal models to study neuromuscular diseases and test new therapeutic strategies. However, findings from successful pre-clinical studies using mouse models frequently fail to translate to humans due to various factors. Differences in muscle function between the two species could be crucial but often have been overlooked. The purpose of this study was to evaluate and compare muscle excursions in walking between mice and humans

Association of MC1R Variants and host phenotypes with melanoma risk in CDKN2A mutation carriers: a GenoMEL study

<p><b>Background</b> Carrying the cyclin-dependent kinase inhibitor 2A (CDKN2A) germline mutations is associated with a high risk for melanoma. Penetrance of CDKN2A mutations is modified by pigmentation characteristics, nevus phenotypes, and some variants of the melanocortin-1 receptor gene (MC1R), which is known to have a role in the pigmentation process. However, investigation of the associations of both MC1R variants and host phenotypes with melanoma risk has been limited.</p> <p><b>Methods</b> We included 815 CDKN2A mutation carriers (473 affected, and 342 unaffected, with melanoma) from 186 families from 15 centers in Europe, North America, and Australia who participated in the Melanoma Genetics Consortium. In this family-based study, we assessed the associations of the four most frequent MC1R variants (V60L, V92M, R151C, and R160W) and the number of variants (1, ≥2 variants), alone or jointly with the host phenotypes (hair color, propensity to sunburn, and number of nevi), with melanoma risk in CDKN2A mutation carriers. These associations were estimated and tested using generalized estimating equations. All statistical tests were two-sided.</p> <p><b>Results</b> Carrying any one of the four most frequent MC1R variants (V60L, V92M, R151C, R160W) in CDKN2A mutation carriers was associated with a statistically significantly increased risk for melanoma across all continents (1.24 × 10−6 ≤ P ≤ .0007). A consistent pattern of increase in melanoma risk was also associated with increase in number of MC1R variants. The risk of melanoma associated with at least two MC1R variants was 2.6-fold higher than the risk associated with only one variant (odds ratio = 5.83 [95% confidence interval = 3.60 to 9.46] vs 2.25 [95% confidence interval = 1.44 to 3.52]; Ptrend = 1.86 × 10−8). The joint analysis of MC1R variants and host phenotypes showed statistically significant associations of melanoma risk, together with MC1R variants (.0001 ≤ P ≤ .04), hair color (.006 ≤ P ≤ .06), and number of nevi (6.9 × 10−6 ≤ P ≤ .02).</p> <p><b>Conclusion</b> Results show that MC1R variants, hair color, and number of nevi were jointly associated with melanoma risk in CDKN2A mutation carriers. This joint association may have important consequences for risk assessments in familial settings.</p&gt

Laboratory-based and office-based risk scores and charts to predict 10-year risk of cardiovascular disease in 182 countries: a pooled analysis of prospective cohorts and health surveys

Background: Worldwide implementation of risk-based cardiovascular disease (CVD) prevention requires risk prediction tools that are contemporarily recalibrated for the target country and can be used where laboratory measurements are unavailable. We present two cardiovascular risk scores, with and without laboratory-based measurements, and the corresponding risk charts for 182 countries to predict 10-year risk of fatal and non-fatal CVD in adults aged 40–74 years. Methods: Based on our previous laboratory-based prediction model (Globorisk), we used data from eight prospective studies to estimate coefficients of the risk equations using proportional hazard regressions. The laboratory-based risk score included age, sex, smoking, blood pressure, diabetes, and total cholesterol; in the non-laboratory (office-based) risk score, we replaced diabetes and total cholesterol with BMI. We recalibrated risk scores for each sex and age group in each country using country-specific mean risk factor levels and CVD rates. We used recalibrated risk scores and data from national surveys (using data from adults aged 40–64 years) to estimate the proportion of the population at different levels of CVD risk for ten countries from different world regions as examples of the information the risk scores provide; we applied a risk threshold for high risk of at least 10% for high-income countries (HICs) and at least 20% for low-income and middle-income countries (LMICs) on the basis of national and international guidelines for CVD prevention. We estimated the proportion of men and women who were similarly categorised as high risk or low risk by the two risk scores. Findings: Predicted risks for the same risk factor profile were generally lower in HICs than in LMICs, with the highest risks in countries in central and southeast Asia and eastern Europe, including China and Russia. In HICs, the proportion of people aged 40–64 years at high risk of CVD ranged from 1% for South Korean women to 42% for Czech men (using a ≥10% risk threshold), and in low-income countries ranged from 2% in Uganda (men and women) to 13% in Iranian men (using a ≥20% risk threshold). More than 80% of adults were similarly classified as low or high risk by the laboratory-based and office-based risk scores. However, the office-based model substantially underestimated the risk among patients with diabetes. Interpretation: Our risk charts provide risk assessment tools that are recalibrated for each country and make the estimation of CVD risk possible without using laboratory-based measurements

Dynamics of biofilm formation and the interaction between Candida albicans and methicillin-susceptible (MSSA) and -resistant Staphylococcus aureus (MRSA)

Polymicrobial biofilms are an understudied and a clinically relevant problem. This study evaluates the interaction between C. albicans, and methicillin- susceptible (MSSA) and resistant (MRSA) S. aureus growing in single- and dual-species biofilms. Single and dual species adhesion (90 min) and biofilms (12, 24, and 48 h) were evaluated by complementary methods: counting colony-forming units (CFU mL-1), XTT-reduction, and crystal violet staining (CV). The secretion of hydrolytic enzymes by the 48 h biofilms was also evaluated using fluorimetric kits. Scanning electron microscopy (SEM) was used to assess biofilm structure. The results from quantification assays were compared using two-way ANOVAs with Tukey post-hoc tests, while data from enzymatic activities were analyzed by one-way Welch-ANOVA followed by Games-Howell post hoc test ( = 0.05). C. albicans, MSSA and MRSA were able to adhere and to form biofilm in both single or mixed cultures. In general, all microorganisms in both growth conditions showed a gradual increase in the number of cells and metabolic activity over time, reaching peak values between 12 h and 48 h (<0.05). C. albicans single- and dual-biofilms had significantly higher total biomass values (<0.05) than single biofilms of bacteria. Except for single MRSA biofilms, all microorganisms in both growth conditions secreted proteinase and phospholipase-C. SEM images revealed extensive adherence of bacteria to hyphal elements of C. albicans. C. albicans, MSSA, and MRSA can co-exist in biofilms without antagonism and in an apparent synergistic effect, with bacteria cells preferentially associated to C. albicans hyphal forms.CNPq (Council for Technical and Scientific Development) (Grant 400658/2012-7)Fundação para a Ciência e Tecnologia (FCT), Portugal (SFRH/BPD/71076/2010)CAPES(Coordination for the Improvement of Higher Level Personnel

Gene expression profiling of alveolar soft-part sarcoma (ASPS)

<p>Abstract</p> <p>Background</p> <p>Alveolar soft-part sarcoma (ASPS) is an extremely rare, highly vascular soft tissue sarcoma affecting predominantly adolescents and young adults. In an attempt to gain insight into the pathobiology of this enigmatic tumor, we performed the first genome-wide gene expression profiling study.</p> <p>Methods</p> <p>For seven patients with confirmed primary or metastatic ASPS, RNA samples were isolated immediately following surgery, reverse transcribed to cDNA and each sample hybridized to duplicate high-density human U133 plus 2.0 microarrays. Array data was then analyzed relative to arrays hybridized to universal RNA to generate an unbiased transcriptome. Subsequent gene ontology analysis was used to identify transcripts with therapeutic or diagnostic potential. A subset of the most interesting genes was then validated using quantitative RT-PCR and immunohistochemistry.</p> <p>Results</p> <p>Analysis of patient array data versus universal RNA identified elevated expression of transcripts related to angiogenesis (ANGPTL2, HIF-1 alpha, MDK, c-MET, VEGF, TIMP-2), cell proliferation (PRL, IGFBP1, NTSR2, PCSK1), metastasis (ADAM9, ECM1, POSTN) and steroid biosynthesis (CYP17A1 and STS). A number of muscle-restricted transcripts (ITGB1BP3/MIBP, MYF5, MYF6 and TRIM63) were also identified, strengthening the case for a muscle cell progenitor as the origin of disease. Transcript differentials were validated using real-time PCR and subsequent immunohistochemical analysis confirmed protein expression for several of the most interesting changes (MDK, c-MET, VEGF, POSTN, CYP17A1, ITGB1BP3/MIBP and TRIM63).</p> <p>Conclusion</p> <p>Results from this first comprehensive study of ASPS gene expression identifies several targets involved in angiogenesis, metastasis and myogenic differentiation. These efforts represent the first step towards defining the cellular origin, pathogenesis and effective treatment strategies for this atypical malignancy.</p

Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c

Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29–39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance