Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Primary Care for Sports and Fitness: A Lifespan Approach

Here are the practical knowledge and the clinical skills you need to help your patients prevent common sports-related injuries...and to assess, diagnose, and treat them when they occur—all in a handy, easy-to-use reference.https://digitalcommons.usm.maine.edu/facbooks/1033/thumbnail.jp

Numerical modeling of surface runoff and erosion due to moving rainstorms at the drainage basin scale

A physically-based distributed erosion model (MEFIDIS) was applied to evaluate the consequences of storm movement on runoff and erosion from the Alenquer basin in Portugal. Controlled soil flume laboratory experiments were also used to test the model. Nine synthetic circular storms were used, combining three storm diameters (0.5, 1 and 2 times the Alenquer basin's axial length) with three speeds of storm movement (0.5, 1 and 2 m/s); storm intensities were synthesized in order to maintain a constant rainfall depth of 50 mm. The model was applied to storms moving downstream as well as upstream along the basin's axis. In all tests, downstream-moving storms caused significantly higher peak runoff (56.5%) and net erosion (9.1%) than did upstream-moving storms. The consequences for peak runoff were amplified as the storm intensity increased. The hydrograph shapes were also different: for downstream-moving storms, runoff started later and the rising limb was steeper, whereas for upstream moving storms, runoff started early and the rising limb was less steep. Both laboratory and model simulations on the Alenquer basin showed that the direction of storm movement, especially in case of extreme rainfall events, significantly affected runoff and soil loss.http://www.sciencedirect.com/science/article/B6V6C-4K7WTYF-3/1/05f00859098982a6ae43cfee9cc48fe

Measuring rill erosion at plot scale by a drone-based technology

The traditional direct method (i.e. metric ruler and rillmeter) of monitoring rill erosion at plot scale is time consuming and invasive since it modifies the surface of the rilled area. Measuring rill features using a drone-based technology is considered a non-invasive method allowing a fast field relief. In the experimental Sparacia area a survey by a quadricopter Microdones md4-200 was carried out and this relief allowed the generation of a Digital Elevation Model (DEM), with a mesh size of 1 cm and a resolution elevation equal to 2 mm, for three plots (L, G and C) affected by rill erosion. At first for the experimental L plot, which is 44 m long, the rill features were surveyed by a “manual” method which was carried out by drawing on the PC screen the rill paths obtained by a visual orthophoto interpretation. This manual method was not applicable for the plots in which rills of limited depth occurred and were not detectable. Then, for both L plot and the other experimental plots having a length ranging from 22 to 44 m, an “automatic” extraction method of rills from DEM was applied. Using an appropriate calculation routine, a vector coverage of transects orthogonal to the main flow direction (i.e., the maximum slope steepness path) was generated. The intersection of each plot DEM with the transect coverage allowed to obtain both the cross-sections and the main rill morphological features. For the L plot the comparison between the rill morphological features obtained by the two different methods (manual, automatic) was carried out. Finally, the length-volume relationship and the dimensionless one proposed by Bruno et al. (2008) were tested for all studied experimental plots