Photocatalytic Template Removal by Non-Ozone-Generating UV Irradiation for the Fabrication of Well-Defined Mesoporous Inorganic Coatings

The processing of mesoporous inorganic coatings typically requires a high-temperature calcination step to remove organic precursors that are essential during the material assembly. Lowering the fabrication energy costs and cutting back on the necessary resources would provide a greater scope for the deployment in applications such as architectural glass, optical components, photovoltaic cells, and energy storage, as well as further compatibilize substrates with low temperature stability. Organic removal methods based on UV–ozone treatment are increasing in popularity, but concerns remain regarding large-scale ozone generation and usage of mercury-containing UV lamps. To this end, we present a method that relies on non-ozone-generating UV radiation at 254 nm (UV254) and incorporation of small amounts of photocatalytic material in the formulation, here demonstrated with TiO2 nanocrystals. At concentrations as low as 5 wt % relative to the main inorganic aluminosilicate material, the TiO2 nanocrystals catalyze a “cold combustion” of the organic components under UV254 irradiation to reveal a porous inorganic network. Using block copolymer-based co-assembly in conjunction with photocatalytic template removal, we produce well-defined mesoporous inorganic thin films with controlled porosity and refractive index values, where the required processing time is governed by the amount of TiO2 loading. This approach provides an inexpensive, flexible, and environmentally friendly alternative to traditional organic removal techniques, such as UV–ozone degradation and thermal calcination

A study protocol to evaluate the relationship between outdoor air pollution and pregnancy outcomes

<p>Abstract</p> <p>Background</p> <p>The present study protocol is designed to assess the relationship between outdoor air pollution and low birth weight and preterm births outcomes performing a semi-ecological analysis. Semi-ecological design studies are widely used to assess effects of air pollution in humans. In this type of analysis, health outcomes and covariates are measured in individuals and exposure assignments are usually based on air quality monitor stations. Therefore, estimating individual exposures are one of the major challenges when investigating these relationships with a semi-ecologic design.</p> <p>Methods/Design</p> <p>Semi-ecologic study consisting of a retrospective cohort study with ecologic assignment of exposure is applied. Health outcomes and covariates are collected at Primary Health Care Center. Data from pregnant registry, clinical record and specific questionnaire administered orally to the mothers of children born in period 2007-2010 in Portuguese Alentejo Litoral region, are collected by the research team. Outdoor air pollution data are collected with a lichen diversity biomonitoring program, and individual pregnancy exposures are assessed with spatial geostatistical simulation, which provides the basis for uncertainty analysis of individual exposures. Awareness of outdoor air pollution uncertainty will improve validity of individual exposures assignments for further statistical analysis with multivariate regression models.</p> <p>Discussion</p> <p>Exposure misclassification is an issue of concern in semi-ecological design. In this study, personal exposures are assigned to each pregnant using geocoded addresses data. A stochastic simulation method is applied to lichen diversity values index measured at biomonitoring survey locations, in order to assess spatial uncertainty of lichen diversity value index at each geocoded address. These methods assume a model for spatial autocorrelation of exposure and provide a distribution of exposures in each study location. We believe that variability of simulated exposure values at geocoded addresses will improve knowledge on variability of exposures, improving therefore validity of individual exposures to input in posterior statistical analysis.</p

Quantitative Trait Locus (QTL) Mapping Reveals a Role for Unstudied Genes in Aspergillus Virulence

Infections caused by the fungus Aspergillus are a major cause of morbidity and mortality in immunocompromised populations. To identify genes required for virulence that could be used as targets for novel treatments, we mapped quantitative trait loci (QTL) affecting virulence in the progeny of a cross between two strains of A. nidulans (FGSC strains A4 and A91). We genotyped 61 progeny at 739 single nucleotide polymorphisms (SNP) spread throughout the genome, and constructed a linkage map that was largely consistent with the genomic sequence, with the exception of one potential inversion of ∼527 kb on Chromosome V. The estimated genome size was 3705 cM and the average intermarker spacing was 5.0 cM. The average ratio of physical distance to genetic distance was 8.1 kb/cM, which is similar to previous estimates, and variation in recombination rate was significantly positively correlated with GC content, a pattern seen in other taxa. To map QTL affecting virulence, we measured the ability of each progeny strain to kill model hosts, larvae of the wax moth Galleria mellonella. We detected three QTL affecting in vivo virulence that were distinct from QTL affecting in vitro growth, and mapped the virulence QTL to regions containing 7–24 genes, excluding genes with no sequence variation between the parental strains and genes with only synonymous SNPs. None of the genes in our QTL target regions have been previously associated with virulence in Aspergillus, and almost half of these genes are currently annotated as “hypothetical”. This study is the first to map QTL affecting the virulence of a fungal pathogen in an animal host, and our results illustrate the power of this approach to identify a short list of unknown genes for further investigation