Computer-Aided-Design of Concert Staging

Concert stages contain many complex geometries and structural components, making their design a difficult task.  Equally difficult is the assembly of a concert stage, since proper construction of it's various components is vital to ensure structural integrity.  Computer-Aided-Design (CAD) is a necessary tool in staging design and analysis.  CAD can be used to show the overall structure of the stage, break the stage down into its various constituent components, and show how the individual stage members are connected.  Using solid modeling, the solid representations of the components and individual members assist in visualizing the complex components and their interconnection.  CAD techniques are essential in envisioning how various members of the stage fit together, and to show the step-by-step process of stage construction.  Also, the use of the CAD model is invaluable in any structural analysis.  After translating the CAD model into an IGES file, the structure can be imported into a finite-element program, which can then be used to evaluate the integrity of the stage by examining existing stresses

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.Peer reviewe

Genome-wide Association Study Identifies Five New Susceptibility Loci For Primary Angle Closure Glaucoma

Primary angle closure glaucoma (PACG) is a major cause of blindness worldwide. We conducted a genome-wide association study (GWAS) followed by replication in a combined total of 10,503 PACG cases and 29,567 controls drawn from 24 countries across Asia, Australia, Europe, North America, and South America. We observed significant evidence of disease association at five new genetic loci upon meta-analysis of all patient collections. These loci are at EPDR1 rs3816415 (odds ratio (OR) = 1.24, P = 5.94 x 10(-15)), CHAT rs1258267 (OR = 1.22, P = 2.85 x 10(-16)), GLIS3 rs736893 (OR = 1.18, P = 1.43 x 10(-14)), FERMT2 rs7494379 (OR = 1.14, P = 3.43 x 10(-11)), and DPM2-FAM102A rs3739821 (OR = 1.15, P = 8.32 x 10(-12)). We also confirmed significant association at three previously described loci (P < 5 x 10(-8) for each sentinel SNP at PLEKHA7, COL11A1, and PCMTD1-ST18)(1), providing new insights into the biology of PACG.485556+Singapore Ministry of Health's National Medical Research Council under its Translational and Clinical Research (TCR) Flagship Programme Grant Stratified Medicine for Primary Angle Closure Glaucoma [NMRC/TCR/008-SERI/2013]Singapore Translational Research (STaR) Investigator Award Singapore Angle Closure Glaucoma Program Characterization, Prevention, and Management [NMRC/STAR/0023/2014]Biomedical Research CouncilAgency for Science, Technology and Research (A-STAR), SingaporeUniversiti Sains Malaysia [RUI 1001/PPSP/812101, RUI 1001/PPSP/812152]Program of Beijing ScholarsLeading Talents-High-Level Talents of the Health System of Beijing [2009-1-05]National Major Scientific and Technological Special Project for 'Significant New Drugs Development' [2011ZX09302-007-05]National Natural Science Foundation of China [81570837

Genome-wide association study identifies five new susceptibility loci for primary angle closure glaucoma.

Primary angle closure glaucoma (PACG) is a major cause of blindness worldwide. We conducted a genome-wide association study (GWAS) followed by replication in a combined total of 10,503 PACG cases and 29,567 controls drawn from 24 countries across Asia, Australia, Europe, North America, and South America. We observed significant evidence of disease association at five new genetic loci upon meta-analysis of all patient collections. These loci are at EPDR1 rs3816415 (odds ratio (OR) = 1.24, P = 5.94 × 10(-15)), CHAT rs1258267 (OR = 1.22, P = 2.85 × 10(-16)), GLIS3 rs736893 (OR = 1.18, P = 1.43 × 10(-14)), FERMT2 rs7494379 (OR = 1.14, P = 3.43 × 10(-11)), and DPM2-FAM102A rs3739821 (OR = 1.15, P = 8.32 × 10(-12)). We also confirmed significant association at three previously described loci (P < 5 × 10(-8) for each sentinel SNP at PLEKHA7, COL11A1, and PCMTD1-ST18), providing new insights into the biology of PACG