A population-based case-control study on social factors and risk of testicular germ cell tumours

Objectives Incidence rates for testicular cancer have risen over the last few decades. Findings of an association between the risk of testicular cancer and social factors are controversial. The association of testicular cancer and different indicators of social factors were examined in this study.<p></p> Design Case–control study.<p></p> Setting Population-based multicentre study in four German regions (city states Bremen and Hamburg, the Saarland region and the city of Essen).<p></p> Participants The study included 797 control participants and 266 participants newly diagnosed with testicular cancer of which 167 cases were classified as seminoma and 99 as non-seminoma. The age of study participants ranged from 15 to 69 years.<p></p> Methods Social position was classified by educational attainment level, posteducational training, occupational sectors according to Erikson-Goldthorpe-Portocarrero (EGP) and the socioeconomic status (SES) on the basis of the International SocioEconomic Index of occupational status (ISEI). ORs and corresponding 95% CIs (95% CIs) were calculated for the whole study sample and for seminoma and non-seminoma separately.<p></p> Results Testicular cancer risk was modestly increased among participants with an apprenticeship (OR=1.7 (95% CI 1.0 to 2.8)) or a university degree (OR=1.6 (95% CI 0.9 to 2.8)) relative to those whose education was limited to school. Analysis of occupational sectors revealed an excess risk for farmers and farm-related occupations. No clear trend was observed for the analyses according to the ISEI-scale.<p></p> Conclusions Social factors based on occupational measures were not a risk factor for testicular cancer in this study. The elevated risk in farmers and farm-related occupations warrants further research including analysis of occupational exposures.<p></p&gt

Localness of energy cascade in hydrodynamic turbulence, II. Sharp spectral filter

We investigate the scale-locality of subgrid-scale (SGS) energy flux and inter-band energy transfers defined by the sharp spectral filter. We show by rigorous bounds, physical arguments and numerical simulations that the spectral SGS flux is dominated by local triadic interactions in an extended turbulent inertial-range. Inter-band energy transfers are also shown to be dominated by local triads if the spectral bands have constant width on a logarithmic scale. We disprove in particular an alternative picture of ``local transfer by nonlocal triads,'' with the advecting wavenumber mode at the energy peak. Although such triads have the largest transfer rates of all {\it individual} wavenumber triads, we show rigorously that, due to their restricted number, they make an asymptotically negligible contribution to energy flux and log-banded energy transfers at high wavenumbers in the inertial-range. We show that it is only the aggregate effect of a geometrically increasing number of local wavenumber triads which can sustain an energy cascade to small scales. Furthermore, non-local triads are argued to contribute even less to the space-average energy flux than is implied by our rigorous bounds, because of additional cancellations from scale-decorrelation effects. We can thus recover the -4/3 scaling of nonlocal contributions to spectral energy flux predicted by Kraichnan's ALHDIA and TFM closures. We support our results with numerical data from a $512^3$ pseudospectral simulation of isotropic turbulence with phase-shift dealiasing. We conclude that the sharp spectral filter has a firm theoretical basis for use in large-eddy simulation (LES) modeling of turbulent flows.Comment: 42 pages, 9 figure

Multiplication and Composition in Weighted Modulation Spaces

We study the existence of the product of two weighted modulation spaces. For this purpose we discuss two different strategies. The more simple one allows transparent proofs in various situations. However, our second method allows a closer look onto associated norm inequalities under restrictions in the Fourier image. This will give us the opportunity to treat the boundedness of composition operators.Comment: 49 page

Yersinia enteroco/itica prevalence in a French slaughterhouse: first results

Yersinlia enterocolitica is involved in human foodbome infections. Pigs are considered as a major reservoir in many countries. The aim of the study was to contribute to the evaluation of the prevalence of Y. enterocolitica in France in pigs at the slaughterhouse level with optimized detection methods based on ISO 10273-2003. Several samples of tonsils over nine consecutive months were analyzed in a single slaughterhouse. Enumeration and isolation were achieved by using CIN agar and Y eCM chromogenic medium (modified from the Weagant medium, 2008). Two enrichment media were used: a peptone, sorbitol and biliary salts broth (PSB) and the Irgasan, Ticarcillin and potassium chlorate broth (ITC)

Identification of direct residue contacts in protein-protein interaction by message passing

Understanding the molecular determinants of specificity in protein-protein interaction is an outstanding challenge of postgenome biology. The availability of large protein databases generated from sequences of hundreds of bacterial genomes enables various statistical approaches to this problem. In this context covariance-based methods have been used to identify correlation between amino acid positions in interacting proteins. However, these methods have an important shortcoming, in that they cannot distinguish between directly and indirectly correlated residues. We developed a method that combines covariance analysis with global inference analysis, adopted from use in statistical physics. Applied to a set of >2,500 representatives of the bacterial two-component signal transduction system, the combination of covariance with global inference successfully and robustly identified residue pairs that are proximal in space without resorting to ad hoc tuning parameters, both for heterointeractions between sensor kinase (SK) and response regulator (RR) proteins and for homointeractions between RR proteins. The spectacular success of this approach illustrates the effectiveness of the global inference approach in identifying direct interaction based on sequence information alone. We expect this method to be applicable soon to interaction surfaces between proteins present in only 1 copy per genome as the number of sequenced genomes continues to expand. Use of this method could significantly increase the potential targets for therapeutic intervention, shed light on the mechanism of protein-protein interaction, and establish the foundation for the accurate prediction of interacting protein partners.Comment: Supplementary information available on http://www.pnas.org/content/106/1/67.abstrac

Characterization of chemical bonding in low-k dielectric materialsfor interconnect isolation: a xas and eels study

The use of low dielectric constant materials in the on-chipinterconnect process reduces interconnect delay, power dissipation andcrosstalk noise. To achieve the requirements of the ITRS for 2007-2009minimal sidewall damage from etch, ash or cleans is required. In chemicalvapor deposited (CVD) organo-silicate glass (OSG) which are used asintermetal dielectric (IMD) materials the substitution of oxygen in SiO2by methyl groups (-CH3) reduces the permittivity significantly (from 4.0in SiO2 to 2.6-3.3 in the OSG), since the electronic polarizability islower for Si-C bonds than for Si-O bonds. However, plasma processing forresist stripping, trench etching and post-etch cleaning removes C and Hcontaining molecular groups from the near-surface layer of OSG.Therefore, compositional analysis and chemical bonding characterizationof structured IMD films with nanometer resolution is necessary forprocess optimization. OSG thin films as-deposited and after plasmatreatment are studied using X-ray absorption spectroscopy (XAS) andelectron energy loss spectroscopy (EELS). In both techniques, the finestructure near the C1s absorption or energy loss edge, respectively,allows to identify C-H, C-C, and C-O bonds. This gives the opportunity todifferentiate between individual low-k materials and their modifications.The O1s signal is less selective to individual bonds. XAS spectra havebeen recorded for non-patterned films and EELS spectra for patternedstructures. The chemical bonding is compared for as-deposited andplasma-treated low-k materials. The Fluorescence Yield (FY) and the TotalElectron Yield (TEY) recorded while XAS measurement are compared.Examination of the C 1s near-edge structures reveal a modified bonding ofthe remaining C atoms in the plasma-treated sample regions

Nanosized superparamagnetic precipitates in cobalt-doped ZnO

The existence of semiconductors exhibiting long-range ferromagnetic ordering at room temperature still is controversial. One particularly important issue is the presence of secondary magnetic phases such as clusters, segregations, etc... These are often tedious to detect, leading to contradictory interpretations. We show that in our cobalt doped ZnO films grown homoepitaxially on single crystalline ZnO substrates the magnetism unambiguously stems from metallic cobalt nano-inclusions. The magnetic behavior was investigated by SQUID magnetometry, x-ray magnetic circular dichroism, and AC susceptibility measurements. The results were correlated to a detailed microstructural analysis based on high resolution x-ray diffraction, transmission electron microscopy, and electron-spectroscopic imaging. No evidence for carrier mediated ferromagnetic exchange between diluted cobalt moments was found. In contrast, the combined data provide clear evidence that the observed room temperature ferromagnetic-like behavior originates from nanometer sized superparamagnetic metallic cobalt precipitates.Comment: 20 pages, 6 figures; details about background subtraction added to section III. (XMCD

MetaGeneAnnotator: Detecting Species-Specific Patterns of Ribosomal Binding Site for Precise Gene Prediction in Anonymous Prokaryotic and Phage Genomes

Recent advances in DNA sequencers are accelerating genome sequencing, especially in microbes, and complete and draft genomes from various species have been sequenced in rapid succession. Here, we present a comprehensive gene prediction tool, the MetaGeneAnnotator (MGA), which precisely predicts all kinds of prokaryotic genes from a single or a set of anonymous genomic sequences having a variety of lengths. The MGA integrates statistical models of prophage genes, in addition to those of bacterial and archaeal genes, and also uses a self-training model from input sequences for predictions. As a result, the MGA sensitively detects not only typical genes but also atypical genes, such as horizontally transferred and prophage genes in a prokaryotic genome. In this paper, we also propose a novel approach for analyzing the ribosomal binding site (RBS), which enables us to detect species-specific patterns of the RBSs. The MGA has the ingenious RBS model based on this approach, and precisely predicts translation starts of genes. The MGA also succeeds in improving prediction accuracies for short sequences by using the adapted RBS models (96% sensitivity and 93% specificity for 700 bp fragments). These features of the MGA expedite wide ranges of microbial genome studies, such as genome annotations and metagenome analyses