Evaluating Factors Affecting the Adoption of Web 2.0 from the Perspective of Isfahan High School Teachers based on Technology Acceptance Model 3

Nowadays students, as digital natives, are attending social networks, social sites, blogging and doing other activities of Web 2.0, while it seems teachers, as digital immigrants, are less likely to use this technology than students. Given the apparent gap between digital natives and immigrants, and the undeniable benefits of using these tools to teach or assist teaching that leads to collaboration, knowledge sharing and knowledge and data transfer, it is necessary to detect factors affecting the acceptance and usage of this technology by teachers, and then policy making in the field of education to be done properly by the authorities, based on these factors. Thus, this research has used the technology acceptance theory 3, which was introduced in 2008 in connection with the information technology to address these factors. This has been carried out through a descriptive study, and the data has been collected by a questionnaire on the sample of 340 high school teachers in Isfahan. Analysis of hypothesis has been done by structural equation modeling and path analysis methods using LISREL software. The results of this research showed convenient and perceived ease of use, has the most influence on the adoption of Web 2.0 technologies by teachers. Peer support, organizational support and computer self-efficacy positively and computer anxiety negatively are factors that affect ease of use

Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels

Survival of patients treated with intra-aortic balloon counterpulsation at a tertiary care center in Pakistan – patient characteristics and predictors of in-hospital mortality

BACKGROUND: Intra-aortic balloon counterpulsation (IABC) has an established role in the treatment of patients presenting with critical cardiac illnesses, including cardiogenic shock, refractory ischemia and for prophylaxis and treatment of complications of percutaneous coronary interventions (PCI). Patients requiring IABC represent a high-risk subset with an expected high mortality. There are virtually no data on usage patterns as well as outcomes of patients in the Indo-Pakistan subcontinent who require IABC. This is the first report on a sizeable experience with IABC from Pakistan. METHODS: Hospital charts of 95 patients (mean age 58.8 (± 10.4) years; 78.9% male) undergoing IABC between 2000–2002 were reviewed. Logistic regression was used to determine univariate and multivariate predictors of in-hospital mortality. RESULTS: The most frequent indications for IABC were cardiogenic shock (48.4%) and refractory ischemia (24.2%). Revascularization (surgical or PCI) was performed in 74 patients (77.9%). The overall in-hospital mortality rate was 34.7%. Univariate predictors of in-hospital mortality included (odds ratio [95% CI]) age (OR 1.06 [1.01–1.11] for every year increase in age); diabetes (OR 3.68 [1.51–8.92]) and cardiogenic shock at presentation (OR 4.85 [1.92–12.2]). Furthermore, prior CABG (OR 0.12 [0.04–0.34]), and in-hospital revascularization (OR 0.05 [0.01–0.189]) was protective against mortality. In the multivariate analysis, independent predictors of in-hospital mortality were age (OR 1.13 [1.05–1.22] for every year increase in age); diabetes (OR 6.35 [1.61–24.97]) and cardiogenic shock at presentation (OR 10.0 [2.33–42.95]). Again, revascularization during hospitalization (OR 0.02 [0.003–0.12]) conferred a protective effect. The overall complication rate was low (8.5%). CONCLUSIONS: Patients requiring IABC represent a high-risk group with substantial in-hospital mortality. Despite this high mortality, over two-thirds of patients do leave the hospital alive, suggesting that IABC is a feasible therapeutic device, even in a developing country

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition

Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche.

Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10(-8)) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.