Design and validation of methods searching for risk factors in genotype case-control studies.

Accessibility of high-throughput genotyping technology allows genome-wide association studies for common complex diseases. This paper addresses two challenges commonly facing such studies: (i) searching an enormous amount of possible gene interactions and (ii) finding reproducible associations. These challenges have been traditionally addressed in statistics while here we apply computational approaches--optimization and cross-validation. A complex risk factor is modeled as a subset of single nucleotide polymorphisms (SNPs) with specified alleles and the optimization formulation asks for the one with the maximum odds ratio. To measure and compare ability of search methods to find reproducible risk factors, we propose to apply a cross-validation scheme usually used for prediction validation. We have applied and cross-validated known search methods with proposed enhancements on real case-control studies for several diseases (Crohn's disease, autoimmune disorder, tick-borne encephalitis, lung cancer, and rheumatoid arthritis). Proposed methods are compared favorably to the exhaustive search: they are faster, find more frequently statistically significant risk factors, and have significantly higher leave-half-out cross-validation rate.     

A short-oligonucleotide microarray that allows improved detection of gastrointestinal tract microbial communities

Background  

The human gastrointestinal (GI) tract contains a diverse collection of bacteria, most of which are unculturable by conventional microbiological methods. Increasingly molecular profiling techniques are being employed to examine this complex microbial community. The purpose of this study was to develop a microarray technique based on 16S ribosomal gene sequences for rapidly monitoring the microbial population of the GI tract.     

2SNP: scalable phasing method for trios and unrelated individuals

Emerging microarray technologies allow affordable typing of very long genome sequences. A key challenge in analyzing of such huge amount of data is scalable and accurate computational inferring of haplotypes (i.e., splitting of each genotype into a pair of corresponding haplotypes). In this paper, we first phase genotypes consisting only of two SNPs using genotypes frequencies adjusted to the random mating model and then extend phasing of two-SNP genotypes to phasing of complete genotypes using maximum spanning trees. Runtime of the proposed 2SNP algorithm is O(nm (n + log m), where n and m are the numbers of genotypes and SNPs, respectively, and it can handle genotypes spanning entire chromosomes in a matter of hours.On datasets across 23 chromosomal regions from HapMap[11], 2SNP is several orders of magnitude faster than GERBIL and PHASE while matching them in quality measured by the number of correctly phased genotypes, single-site and switching errors. For example the 2SNP software phases entire chromosome (10(5) SNPs from HapMap) for 30 individuals in 2 hours with average switching error 7.7%.We have also enhanced 2SNP algorithm to phase family trio data and compared it with four other well-known phasing methods on simulated data from [15]. 2SNP is much faster than all of them while loosing in quality only to PHASE. 2SNP software is publicly available at http://alla.cs.gsu.edu/~software/2SNP.     

The effect of thermal treatment on antibacterial properties of nanostructured TiO<Subscript>2</Subscript>(N) films illuminated with visible light

This work focuses on the photocatalytic performances and antibacterial activity of nitrogen doped TiO₂ nanosystems with three and five layers obtained by a sol-gel route, followed by thermal treatment in oxygen or ammonia atmosphere at temperatures between 400 and 1000°C. Subsequently, the antibacterial activity of the obtained nanosystems on the Escherichia coli cells are determined and discussed. The obtained results show a significant dependence of the functional performances on the system’s composition. In particular, the antimicrobial activity of nitrogen-doped TiO₂ films is correlated with the temperature of thermal treatment and illumination time with visible artificial light.     

Stem cells as delivery vehicles for regenerative medicinechallenges and perspectives

The use of stem cells as carriers for therapeutic agents is an appealing modality for targeting tissues or organs of interest. Combined delivery of cells together with various information molecules as therapeutic agents has the potential to enhance, modulate or even initiate local or systemic repair processes, increasing stem cell efficiency for regenerative medicine applications. Stem-cell-mediated delivery of genes, proteins or small molecules takes advantage of the innate capability of stem cells to migrate and home to injury sites. As the native migratory properties are affected by in vitro expansion, the existent methods for enhancing stem cell targeting capabilities(modified culture methods, genetic modification, cell surface engineering) are described. The role of various nanoparticles in eq-uipping stem cells with therapeutic small molecules is revised together with their class-specific advantages and shortcomings. Modalities to circumvent common challenges when designing a stem-cell-mediated targeted delivery system are described as well as future prospects in using this approach for regenerative medicine applications.