Ultrasonic benchmarking with UTdefect

UTDefect is a program for simulation of ultrasonic testing with emphasis on applications within the nuclear power industry. The entire testing process, including the ultrasonic transmitter, the receiver, and scattering from various types of defects of simple shape, is modelled. The basic idea behind UTDefect is to use solutions to the elastodynamic wave equation that are esentially exact. For the 2009 benchmark problems the results obtained from UTDefect are in most cases in fairly good agreement with the experimental data from CEA. © 2010 American Institute of Physics

Ultrasonic wave propagation in an anisotropic cladding with a wavy interface

The propagation of ultrasonic waves in a thick plate with a cladding is investigated in the two-dimensional case. The surfaces of the plate are traction-free except where an ultrasonic probe is attached and emits waves into the plate. The plate is made of two different materials, the base material and the cladding, and these are both allowed to be anisotropic. The interface between the base material and the cladding is assumed to be wavy (sinusoidal) and this is common in practice for welded claddings. The null field approach is used to solve the wave propagation problem. Thus the starting point is the (surface) integral representations in the two materials. The Green’s tensors are chosen as the half space Green’s tensors as only the integrals along the interface then remain. The Green’s functions are expanded in Fourier transforms along the interface and the surface fields are likewise expanded. Applying the periodicity of the interface a discretized set of equations remains. For the sinusoidal interface all integrals can be computed analytically which leads to an efficient numerical scheme. Some numerical results show the influence of the anisotropy and the wavy interface

The SNARE Protein SNAP23 and the SNARE-Interacting Protein Munc18c in Human Skeletal Muscle Are Implicated in Insulin Resistance/Type 2 Diabetes

OBJECTIVE-Our previous studies suggest that the SNARE protein synaptosomal-associated protein of 23 kDa (SNAP23) is involved in the link between increased lipid levels and insulin resistance in cardiomyocytes. The objective was to determine whether SNAP23 may also be involved in the known association between lipid accumulation in skeletal muscle and insulin resistance/type 2 diabetes in humans, as well as to identify a potential regulator of SNAP23. RESEARCH DESIGN AND METHODS-We analyzed skeletal muscle biopsies from patients with type 2 diabetes and healthy, insulin-sensitive control subjects for expression (mRNA and protein) and intracellular localization (subcellular fractionation and immunohistochemistry) of SNAP23, and for expression of proteins known to interact with SNARE proteins. Insulin resistance was determined by a euglycemic hyperinsulinemic clamp Potential mechanisms for regulation of SNAP23 were also investigated in the skeletal muscle cell line L6. RESULTS-We showed increased SNAP23 levels in skeletal muscle from patients with type 2 diabetes compared with that from lean control subjects Moreover, SNAP23 was redistributed from the plasma membrane to the microsomal/cytosolic compartment in the patients with the type 2 diabetes Expression of the SNARE-interacting protein Munc18c was higher in skeletal muscle from patients with type 2 diabetes Studies in L6 cells showed that Munc18c promoted the expression of SNAP23. CONCLUSIONS-We have translated our previous in vitro results into humans by showing that there is a change in the distribution of SNAP23 to the interior of the cell in skeletal muscle from patients with type 2 diabetes. We also showed that Munc18c is a potential regulator of SNAP23. Diabetes 59: 1870-1878, 201

Variant near ADAMTS9 Known to Associate with Type 2 Diabetes Is Related to Insulin Resistance in Offspring of Type 2 Diabetes Patients—EUGENE2 Study

A meta-analysis combining results from three genome-wide association studies and followed by large-scale replication identified six novel type 2 diabetes loci. Subsequent studies of the effect of these variants on estimates of the beta-cell function and insulin sensitivity have been inconclusive. We examined these variants located in or near the JAZF1 (rs864745), THADA (rs7578597), TSPAN8 (rs7961581), ADAMTS9 (rs4607103), NOTCH2 (rs10923931) and the CDC123/CAMK1D (rs12779790) genes for associations with measures of pancreatic beta-cell function and insulin sensitivity.Oral and intravenous glucose stimulated insulin release (n = 849) and insulin sensitivity (n = 596) estimated from a hyperinsulinemic euglycemic clamp were measured in non-diabetic offspring of type 2 diabetic patients from five European populations. Assuming an additive genetic model the diabetes-associated major C-allele of rs4607103 near ADAMTS9 associated with reduced insulin-stimulated glucose uptake (p = 0.002) during a hyperinsulinemic euglycemic clamp. However, following intravenous and oral administration of glucose serum insulin release was increased in individuals with the C-allele (p = 0.003 and p = 0.01, respectively). A meta-analyse combining clamp and IVGTT data from a total of 905 non-diabetic individuals showed that the C-risk allele associated with decreased insulin sensitivity (p = 0.003) and increased insulin release (p = 0.002). The major T-allele of the intronic JAZF1 rs864745 conferring increased diabetes risk was associated with increased 2(nd) phase serum insulin release during an IVGTT (p = 0.03), and an increased fasting serum insulin level (p = 0.001). The remaining variants did not show any associations with insulin response, insulin sensitivity or any other measured quantitative traits.The present studies suggest that the diabetogenic impact of the C-allele of rs4607103 near ADAMTS9 may in part be mediated through decreased insulin sensitivity of peripheral tissues

DNA methylation of loci within ABCG1 and PHOSPHO1 in blood DNA is associated with future type 2 diabetes risk

Identification of subjects with a high risk of developing type 2 diabetes (T2D) is fundamental for prevention of the disease. Consequently, it is essential to search for new biomarkers that can improve the prediction of T2D. The aim of this study was to examine whether 5 DNA methylation loci in blood DNA (ABCG1, PHOSPHO1, SOCS3, SREBF1, and TXNIP), recently reported to be associated with T2D, might predict future T2D in subjects from the Botnia prospective study. We also tested if these CpG sites exhibit altered DNA methylation in human pancreatic islets, liver, adipose tissue, and skeletal muscle from diabetic vs. non-diabetic subjects. DNA methylation at the ABCG1 locus cg06500161 in blood DNA was associated with an increased risk for future T2D (OR = 1.09, 95% CI = 1.02-1.16, P-value = 0.007, Q-value = 0.018), while DNA methylation at the PHOSPHO1 locus cg02650017 in blood DNA was associated with a decreased risk for future T2D (OR = 0.85, 95% CI = 0.75-0.95, P-value = 0.006, Q-value = 0.018) after adjustment for age, gender, fasting glucose, and family relation. Furthermore, the level of DNA methylation at the ABCG1 locus cg06500161 in blood DNA correlated positively with BMI, HbA1c, fasting insulin, and triglyceride levels, and was increased in adipose tissue and blood from the diabetic twin among monozygotic twin pairs discordant for T2D. DNA methylation at the PHOSPHO1 locus cg02650017 in blood correlated positively with HDL levels, and was decreased in skeletal muscle from diabetic vs. non-diabetic monozygotic twins. DNA methylation of cg18181703 (SOCS3), cg11024682 (SREBF1), and cg19693031 (TXNIP) was not associated with future T2D risk in subjects from the Botnia prospective study.Peer reviewe

Integration of molecular profiles in a longitudinal wellness profiling cohort

An important aspect of precision medicine is to probe the stability in molecular profiles among healthy individuals over time. Here, we sample a longitudinal wellness cohort with 100 healthy individuals and analyze blood molecular profiles including proteomics, transcriptomics, lipidomics, metabolomics, autoantibodies and immune cell profiling, complemented with gut microbiota composition and routine clinical chemistry. Overall, our results show high variation between individuals across different molecular readouts, while the intra-individual baseline variation is low. The analyses show that each individual has a unique and stable plasma protein profile throughout the study period and that many individuals also show distinct profiles with regards to the other omics datasets, with strong underlying connections between the blood proteome and the clinical chemistry parameters. In conclusion, the results support an individual-based definition of health and show that comprehensive omics profiling in a longitudinal manner is a path forward for precision medicine