Signal Quality Monitoring of GNSS Signals Using a Chip Shape Deformation Metric

The Global Navigation Satellite System continues to become deeply em-bedded within modern civilization, and is depended on for confident, accurate navigation information. High precision position and timing accuracy is typically achieved using differential processing, however these systems provide limited compensation for distortions caused by multi-path or faulty satellite hardware. Signal Quality Monitoring (SQM) aims to provide confidence in a receivers Position, Navigation, and Timing solution and to offer timely warnings in the event that signal conditions degrade to unsafe levels. The methods presented in this document focus on implementing effective SQM using low-cost Commercial Off-the-Shelf equipment, a Software Defined Radio, and a typical software receiver architecture that tracks the Galileo E1C signals and the Global Positioning System L1 Coarse-Acquisition signals. Techniques are centered on acquiring and discriminating signal chip shapes with a goal of identifying both 1) clean and 2) deformed signals. The demonstrated identification method is relevant to the growing significance of SQM for SoL applications while providing benefit for confidently monitoring received GNSS signal integrity without requiring specialized receiver hardware

Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk.

Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression

An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples.

MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed.  Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination

Pf7: an open dataset of Plasmodium falciparum genome variation in 20,000 worldwide samples

We describe the MalariaGEN Pf7 data resource, the seventh release of Plasmodium falciparum genome variation data from the MalariaGEN network.  It comprises over 20,000 samples from 82 partner studies in 33 countries, including several malaria endemic regions that were previously underrepresented.  For the first time we include dried blood spot samples that were sequenced after selective whole genome amplification, necessitating new methods to genotype copy number variations.  We identify a large number of newly emerging crt mutations in parts of Southeast Asia, and show examples of heterogeneities in patterns of drug resistance within Africa and within the Indian subcontinent.  We describe the profile of variations in the C-terminal of the csp gene and relate this to the sequence used in the RTS,S and R21 malaria vaccines.  Pf7 provides high-quality data on genotype calls for 6 million SNPs and short indels, analysis of large deletions that cause failure of rapid diagnostic tests, and systematic characterisation of six major drug resistance loci, all of which can be freely downloaded from the MalariaGEN website

Fast and robust single PCR for Plasmodium sporozoite detection in mosquitoes using the cytochrome oxidase I gene

Abstract Background Molecular tools for detecting malaria-infected mosquitoes with improved practicality, sensitivity and specificity, and high-throughput are required. A common PCR technique used to detect mosquitoes infected with Plasmodium spp. is a nested PCR assay based on the 18s-rRNA gene. However, this technique has several technical limitations, is laborious and time consuming. Methods In this study, a PCR-based on the Plasmodium cytochrome oxidase I (COX-I) gene was compared with the 18s-rRNA nested PCR using serial dilutions (330–0.0012 pg) of DNA from Plasmodium vivax, Plasmodium falciparum and Plasmodium knowlesi and with DNA from 48 positive and negative Kenyan mosquitoes (previously detected by using both ELISA and PCR). This assay for Plasmodium spp. DNA detection using the fast COX-I PCR assay was then performed individually on 2122 field collected mosquitoes (from the Solomon Islands) in which DNA was extracted from head and thorax. Results The fast COX-I PCR assay took 1 h to run and consistently detected as low as to 0.043 pg of parasite DNA (equivalent to two parasites) in a single PCR, while analyses with the 18s-rRNA nested PCR required 4 h to complete with a consistent detection threshold of 1.5 pg of DNA. Both assays produced concordant results when applied to the 48 Kenyan control samples with known Plasmodium spp. infection status. The fast COX-I PCR identified 23/2122 Plasmodium-infected mosquitoes from the Solomon Islands. Conclusions This new COX-I PCR adapted for a single PCR reaction is a faster, simpler, cheaper, more sensitive technique amenable to high-throughput analyses for Plasmodium DNA detection in mosquitoes and is comparable to the 18s-rRNA nested PCR. The improved sensitivity seen with the fast COX-I PCR will improve the accuracy of mosquito infection rate determination