Investigation of DNA polymorphisms in SMAD genes for genetic predisposition to diabetic nephropathy in patients with type 1 diabetes mellitus

Aims/hypothesis: SMAD proteins are involved in multiple signalling pathways and are key modulators of gene expression. We hypothesised that genetic variation in selected SMAD genes contributes to susceptibility to diabetic nephropathy. Methods: We selected 13 haplotype tag (ht) single nucleotide polymorphisms (SNPs) from 67 variants identified by resequencing the SMAD2 and SMAD3 genes. For SMAD1, SMAD4 and SMAD5 genes, genotype data were downloaded for 217 SNPs from Phase II of the International HapMap project. Of these, 85 SNPs met our inclusion criteria, resulting in the selection of 13 tag SNPs for further investigation. A case-control approach was employed, using 267 nephropathic patients and 442 controls with type 1 diabetes from Ireland. Two further populations (totalling 1,407 patients, 2,238 controls) were genotyped to validate initial findings. Genotyping was conducted using iPLEX, TaqMan and gel electrophoresis.
Results: The distribution of genotypes was in Hardy-Weinberg equilibrium. Analysis by the ? 2 test of genotype and allele frequencies in patients versus controls in the Irish population (n?=?709) revealed evidence for the association of one allele at 5% level of significance (rs10515478, p uncorrected?=?0.006; p corrected?=?0.04). This finding represents a relatively small difference in allele frequency of 6.4% in the patient group compared with 10.7% in the control group; this difference was not supported in subsequent investigations using DNA from European individuals with similar phenotypic characteristics.
Conclusions/interpretation: We selected an appropriate subset of variants for the investigation of common genetic risk factors and assessed SMAD1 to SMAD5 genes for association with diabetic nephropathy. We conclude that common polymorphisms in these genes do not strongly influence genetic susceptibility to diabetic nephropathy in white individuals with type 1 diabetes mellitus.

Diagnostic based modeling for determining absolute atomic oxygen densities in atmospheric pressure helium-oxygen plasmas

Absolute atomic oxygen ground state densities in a radio-frequency driven atmospheric pressure plasma jet, operated in a helium-oxygen mixture, are determined using diagnostic based modeling. One-dimensional numerical simulations of the electron dynamics are combined with time integrated optical emission spectroscopy. The population dynamics of the upper O 3p 3P (l=844 nm) atomic oxygen state is governed by direct electron impact excitation, dissociative excitation, radiation losses, and collisional induced quenching. Absolute values for atomic oxygen densities are obtained through comparison with the upper Ar 2p1 (l=750.4 nm) state. Results for spatial profiles and power variations are presented and show excellent quantitative agreement with independent two-photon laser-induced fluorescence measurements.

Antennas for over-body-surface communication at 2.45 GHz

In this paper, the on-body performance of a range of wearable antennas was investigated by measuring vertical bar S-21 vertical bar path gain between two devices mounted on tissue-equivalent numerical and experimental phantoms, representative of human muscle tissue at 2.45 GHz. In particular, the study focused on the performance of a compact higher mode microstrip patch antenna (HMMPA) with a profile as low as lambda/20. The 5- and 10-mm-high HMMPA prototypes had an impedance bandwidth of 6.7% and 8.6%, respectively, sufficient for the operating requirements of the 2.45-GHz industrial, scientific, and medical (ISM) band and both antennas offered 11-dB higher path gain compared to a fundamental-mode microstrip patch antenna. It was also dernonstrated that a 7-dB improvement in path gain can be obtained for a fundamental-mode patch through the addition of a shortening wall. Notably, on-body HMMPA performance was comparable to a quarter wave monopole antenna on the same size of ground-plane, mounted normal to the tissue surface, indicating that the low-profile and physically more robust antenna is a promising solution for bodyworn antenna applications.

Diagnostic based modelling of radio-frequency driven atmospheric pressure plasmas

Diagnostic based modelling (DBM) actively combines complementary advantages of numerical plasma simulations and relatively simple optical emission spectroscopy (OES). DBM is employed to determine absolute atomic oxygen ground state densities in a helium–oxygen radio-frequency driven atmospheric pressure plasma jet. A comparatively simple one-dimensional simulation yields detailed information on electron properties governing the population dynamics of excited states. Important characteristics of the electron dynamics are found to be largely insensitive to details of the chemical composition and to be in very good agreement with space and phase-resolved OES. Benchmarking the time and space resolved simulation allows us to subsequently derive effective excitation rates as the basis for DBM with simple space and time integrated OES. The population dynamics of the upper O 3p 3P (? = 844 nm) atomic oxygen state is governed by direct electron impact excitation, dissociative excitation, radiation losses and collisional induced quenching. Absolute values for atomic oxygen densities are obtained through tracer comparison with the upper Ar 2p1 (? = 750.4 nm) state. The presented results for the atomic oxygen density show excellent quantitative agreement with independent two-photon laser-induced fluorescence measurements.

Diagnostic-based modeling on a micro-scale atmospheric-pressure plasma jet

Diagnostic-based modeling (DBM) actively combines complementary advantages of numerical plasma simulations and relatively simple optical emission spectroscopy (OES). DBM is applied to determine spatial absolute atomic oxygen ground-state density profiles in a micro atmospheric-pressure plasma jet operated in He–O2. A 1D fluid model with semi-kinetic treatment of the electrons yields detailed information on the electron dynamics and the corresponding spatio-temporal electron energy distribution function. Benchmarking this time- and space-resolved simulation with phase-resolved OES (PROES) allows subsequent derivation of effective excitation rates as the basis for DBM. The population dynamics of the upper O(3p3P) oxygen state (? = 844 nm) is governed by direct electron impact excitation, dissociative excitation, radiation losses, and collisional induced quenching. Absolute values for atomic oxygen densities are obtained through tracer comparison with the upper Ar(2p1) state (? = 750.4 nm). The resulting spatial profile for the absolute atomic oxygen density shows an excellent quantitative agreement to a density profile obtained by two-photon absorption laser-induced fluorescence spectroscopy.

Discordant quantitative detection of putative biomarkers in nodal micrometastases of colorectal cancer: biological and clinical implications

Aims: Nodal expression of the carcinoembryonic antigen ( CEA), cytokeratin 20 ( CK20), and guanylyl cyclase C ( GCC) genes was measured in tandem in patients with colorectal cancer ( CRC) to assess whether there would be sufficient agreement between these markers in their ability to detect micrometastasis to qualify one of them as a universal marker, and whether frozen and paraffin wax embedded tissues would yield similar results.

How Porosity and Permeability Vary Spatially With Grain Size, Sorting, Cement Volume, and Mineral Dissolution In Fluvial Triassic Sandstones: The Value of Geostatistics and Local Regression

Although it is well known that sandstone porosity and permeability are controlled by a range of parameters such as grain size and sorting, amount, type, and location of diagenetic cements, extent and type of compaction, and the generation of intergranular and intragranular secondary porosity, it is less constrained how these controlling parameters link up in rock volumes (within and between beds) and how they spatially interact to determine porosity and permeability. To address these unknowns, this study examined Triassic fluvial sandstone outcrops from the UK using field logging, probe permeametry of 200 points, and sampling at 100 points on a gridded rock surface. These field observations were supplemented by laser particle-size analysis, thin-section point-count analysis of primary and diagenetic mineralogy, quantitiative XRD mineral analysis, and SEM/EDAX analysis of all 100 samples. These data were analyzed using global regression, variography, kriging, conditional simulation, and geographically weighted regression to examine the spatial relationships between porosity and permeability and their potential controls. The results of bivariate analysis (global regression) of the entire outcrop dataset indicate only a weak correlation between both permeability porosity and their diagenetic and depositional controls and provide very limited information on the role of primary textural structures such as grain size and sorting. Subdividing the dataset further by bedding unit revealed details of more local controls on porosity and permeability. An alternative geostatistical approach combined with a local modelling technique (geographically weighted regression; GWR) subsequently was used to examine the spatial variability of porosity and permeability and their controls. The use of GWR does not require prior knowledge of divisions between bedding units, but the results from GWR broadly concur with results of regression analysis by bedding unit and provide much greater clarity of how porosity and permeability and their controls vary laterally and vertically. The close relationship between depositional lithofacies in each bed, diagenesis, and permeability, porosity demonstrates that each influences the other, and in turn how understanding of reservoir properties is enhanced by integration of paleoenvironmental reconstruction, stratigraphy, mineralogy, and geostatistics.

Mapping public sector organizations:An agenda for future research

This article summarizes the key findings from the five mapping case studies presented in this special issue and relates them back to the conceptual, definitional, and theoretical issues presented in the opening article (MacCarthaigh & Roness, 2012). In so doing, the article considers the alternative ways in which organizational change can best be captured, mapped, and explained and the key issues to be considered when conducting such exercises. As well as identifying how the case studies have advanced the possibilities for mapping public sector organizational change over time in a cross-national context and the benefits this offers for other aspects of public administration research, the article identifies some impediments to future research and collaboration in the field and suggests ways to overcome them. © Taylor & Francis Group, LLC.