The inventorying of building stone performance-in-use to assess susceptibility to decay

The Natural Stone Database for Northern Ireland was constructed to address the paucity of information available to stone conservation practitioners within the region. Almost 2000 listed buildings and monuments were surveyed over three years to produce an interactive GIS database. This contained information on stone sources, together with details of stone condition and decay processes. This paper uses elements of this GIS to investigate stone decay patterns across Northern Ireland. The results demonstrate that as the level of stone decay increases, so does the proportion of buildings with sandstone as the primary stone type. It appears that a
higher open porosity level combined with Northern Ireland’s wetter climate and maritime location leads to rapid wetting and drying cycles within sandstones. This is coupled with the ingress and crystallisation of marine and other salts within stone pores leading to considerably
higher rates of decay than for any other stone type.

Gene regulatory mechanisms underpinning prostate cancer susceptibility

Molecular characterization of genome-wide association study (GWAS) loci can uncover key genes and biological mechanisms underpinning complex traits and diseases. Here we present deep, high-throughput characterization of gene regulatory mechanisms underlying prostate cancer risk loci. Our methodology integrates data from 295 prostate cancer chromatin immunoprecipitation and sequencing experiments with genotype and gene expression data from 602 prostate tumor samples. The analysis identifies new gene regulatory mechanisms affected by risk locus SNPs, including widespread disruption of ternary androgen receptor (AR)-FOXA1 and AR-HOXB13 complexes and competitive binding mechanisms. We identify 57 expression quantitative trait loci at 35 risk loci, which we validate through analysis of allele-specific expression. We further validate predicted regulatory SNPs and target genes in prostate cancer cell line models. Finally, our integrated analysis can be accessed through an interactive visualization tool. This analysis elucidates how genome sequence variation affects disease predisposition via gene regulatory mechanisms and identifies relevant genes for downstream biomarker and drug development.