Magnetic nanoparticles as efficient bulk pinning centers in type-II superconductors

Enhancement of flux pinning by magnetic nanoparticles embedded into the bulk of type-2 superconductor is studied both theoretically and experimentally. Magnetic part of the pinning force associated with the interaction between a spherical magnetic inclusion and an Abrikosov vortex was calculated in the London approximation. Calculations are supported by the experimental results obtained on sonochemically modified MgB2 superconductor with embedded magnetic Fe2O3 nanoparticles and compared to MgB2 with nonmagnetic Mo2O5 pinning centers of similar concentration and particle size distribution. It is shown that ferromagnetic nanoparticles result in a considerable enhancement of vortex pinning in large-kappa type-2 superconductors.Comment: PDF, 14 page

Evaluation, contrôle et prévention du risque de transmission du virus influenza aviaire à l'homme

Since mid-december 2003, an epizootic of highly pathogenic avian influenza (type A, sub-type H5N1) occurs in eastern and south-eastern Asia. This epizootic is historically unprecedented in its virulence, geographical spread, and economic consequences for the agricultural sector. Implications for human health were registered in Vietnam and in Thailand. This paper summarizes the current knowledge about the risk evaluation of the transmission of avian influenza virus to humans. The current asian epizootic has highlighted the key role of global health information systems and also the need for exhaustive notification of human and animal cases. It reinforces the concept of veterinary public health

Quantum character varieties and braided module categories

We compute quantum character varieties of arbitrary closed surfaces with boundaries and marked points. These are categorical invariants $\int_S\mathcal A$ of a surface $S$, determined by the choice of a braided tensor category $\mathcal A$, and computed via factorization homology. We identify the algebraic data governing marked points and boundary components with the notion of a {\em braided module category} for $\mathcal A$, and we describe braided module categories with a generator in terms of certain explicit algebra homomorphisms called {\em quantum moment maps}. We then show that the quantum character variety of a decorated surface is obtained from that of the corresponding punctured surface as a quantum Hamiltonian reduction. Characters of braided $\mathcal A$-modules are objects of the torus category $\int_{T^2}\mathcal A$. We initiate a theory of character sheaves for quantum groups by identifying the torus integral of $\mathcal A=\operatorname{Rep_q} G$ with the category $\mathcal D_q(G/G)-\operatorname{mod}$ of equivariant quantum $\mathcal D$-modules. When $G=GL_n$, we relate the mirabolic version of this category to the representations of the spherical double affine Hecke algebra (DAHA) $\mathbb{SH}_{q,t}$.Comment: 33 pages, 5 figures. Final version, to appear in Sel. Math. New Se

Integration of phenotypic metadata and protein similarity in Archaea using a spectral bipartitioning approach

In order to simplify and meaningfully categorize large sets of protein sequence data, it is commonplace to cluster proteins based on the similarity of those sequences. However, it quickly becomes clear that the sequence flexibility allowed a given protein varies significantly among different protein families. The degree to which sequences are conserved not only differs for each protein family, but also is affected by the phylogenetic divergence of the source organisms. Clustering techniques that use similarity thresholds for protein families do not always allow for these variations and thus cannot be confidently used for applications such as automated annotation and phylogenetic profiling. In this work, we applied a spectral bipartitioning technique to all proteins from 53 archaeal genomes. Comparisons between different taxonomic levels allowed us to study the effects of phylogenetic distances on cluster structure. Likewise, by associating functional annotations and phenotypic metadata with each protein, we could compare our protein similarity clusters with both protein function and associated phenotype. Our clusters can be analyzed graphically and interactively online

Sex differences in risk factors for coronary heart disease: a study in a Brazilian population

BACKGROUND: In Brazil coronary heart disease (CHD) constitutes the most important cause of death in both sexes in all the regions of the country and interestingly, the difference between the sexes in the CHD mortality rates is one of the smallest in the world because of high rates among women. Since a question has been raised about whether or how the incidence of several CHD risk factors differs between the sexes in Brazil the prevalence of various risk factors for CHD such as high blood cholesterol, diabetes mellitus, hypertension, obesity, sedentary lifestyle and cigarette smoking was compared between the sexes in a Brazilian population; also the relationships between blood cholesterol and the other risk factors were evaluated. RESULTS: The population presented high frequencies of all the risk factors evaluated. High blood cholesterol (CHOL) and hypertension were more prevalent among women as compared to men. Hypertension, diabetes and smoking showed equal or higher prevalence in women in pre-menopausal ages as compared to men. Obesity and physical inactivity were equally prevalent in both sexes respectively in the postmenopausal age group and at all ages. CHOL was associated with BMI, sex, age, hypertension and physical inactivity. CONCLUSIONS: In this population the high prevalence of the CHD risk factors indicated that there is an urgent need for its control; the higher or equal prevalences of several risk factors in women could in part explain the high rates of mortality from CHD in females as compared to males

Tissue Compartment Analysis for Biomarker Discovery by Gene Expression Profiling

BACKGROUND:Although high throughput technologies for gene profiling are reliable tools, sample/tissue heterogeneity limits their outcomes when applied to identify molecular markers. Indeed, inter-sample differences in cell composition contribute to scatter the data, preventing detection of small but relevant changes in gene expression level. To date, attempts to circumvent this difficulty were based on isolation of the different cell structures constituting biological samples. As an alternate approach, we developed a tissue compartment analysis (TCA) method to assess the cell composition of tissue samples, and applied it to standardize data and to identify biomarkers. METHODOLOGY/PRINCIPAL FINDINGS:TCA is based on the comparison of mRNA expression levels of specific markers of the different constitutive structures in pure isolated structures, on the one hand, and in the whole sample on the other. TCA method was here developed with human kidney samples, as an example of highly heterogeneous organ. It was validated by comparison of the data with those obtained by histo-morphometry. TCA demonstrated the extreme variety of composition of kidney samples, with abundance of specific structures varying from 5 to 95% of the whole sample. TCA permitted to accurately standardize gene expression level amongst >100 kidney biopsies, and to identify otherwise imperceptible molecular disease markers. CONCLUSIONS/SIGNIFICANCE:Because TCA does not require specific preparation of sample, it can be applied to all existing tissue or cDNA libraries or to published data sets, inasmuch specific operational compartments markers are available. In human, where the small size of tissue samples collected in clinical practice accounts for high structural diversity, TCA is well suited for the identification of molecular markers of diseases, and the follow up of identified markers in single patients for diagnosis/prognosis and evaluation of therapy efficiency. In laboratory animals, TCA will interestingly be applied to central nervous system where tissue heterogeneity is a limiting factor