Using VSWIR Microimaging Spectroscopy to Explore the Mineralogical Diversity of HED Meteorites

We use VSWIR microimaging spectroscopy to survey the spectral diversity of HED meteorites at 80-μm/pixel spatial scale. Our goal in this work is both to explore the emerging capabilities of microimaging VSWIR spectroscopy and to contribute to understanding the petrologic diversity of the HED suite and the evolution of Vesta. Using a combination of manual and automated hyperspectral classification techniques, we identify four major classes of materials based on VSWIR absorptions that include pyroxene, olivine, Fe-bearing feldspars, and glass-bearing/featureless materials. Results show microimaging spectroscopy is an effective method for rapidly and non-destructively characterizing small compositional variations of meteorite samples and for locating rare phases for possible follow-up investigation. Future work will include incorporating SEM/EDS results to quantify sources of spectral variability and placing observations within a broader geologic framework of the differentiation and evolution of Vesta

People of the British Isles: preliminary analysis of genotypes and surnames in a UK control population

There is a great deal of interest in fine scale population structure in the UK, both as a signature of historical immigration events and because of the effect population structure may have on disease association studies. Although population structure appears to have a minor impact on the current generation of genome-wide association studies, it is likely to play a significant part in the next generation of studies designed to search for rare variants. A powerful way of detecting such structure is to control and document carefully the provenance of the samples involved. Here we describe the collection of a cohort of rural UK samples (The People of the British Isles), aimed at providing a well-characterised UK control population that can be used as a resource by the research community as well as providing fine scale genetic information on the British population. So far, some 4,000 samples have been collected, the majority of which fit the criteria of coming from a rural area and having all four grandparents from approximately the same area. Analysis of the first 3,865 samples that have been geocoded indicates that 75% have a mean distance between grandparental places of birth of 37.3km, and that about 70% of grandparental places of birth can be classed as rural. Preliminary genotyping of 1,057 samples demonstrates the value of these samples for investigating fine scale population structure within the UK, and shows how this can be enhanced by the use of surnames

CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital.

BACKGROUND: Traditional health information systems are generally devised to support clinical data collection at the point of care. However, as the significance of the modern information economy expands in scope and permeates the healthcare domain, there is an increasing urgency for healthcare organisations to offer information systems that address the expectations of clinicians, researchers and the business intelligence community alike. Amongst other emergent requirements, the principal unmet need might be defined as the 3R principle (right data, right place, right time) to address deficiencies in organisational data flow while retaining the strict information governance policies that apply within the UK National Health Service (NHS). Here, we describe our work on creating and deploying a low cost structured and unstructured information retrieval and extraction architecture within King's College Hospital, the management of governance concerns and the associated use cases and cost saving opportunities that such components present. RESULTS: To date, our CogStack architecture has processed over 300 million lines of clinical data, making it available for internal service improvement projects at King's College London. On generated data designed to simulate real world clinical text, our de-identification algorithm achieved up to 94% precision and up to 96% recall. CONCLUSION: We describe a toolkit which we feel is of huge value to the UK (and beyond) healthcare community. It is the only open source, easily deployable solution designed for the UK healthcare environment, in a landscape populated by expensive proprietary systems. Solutions such as these provide a crucial foundation for the genomic revolution in medicine

A retrospective observational study of the relationship between single nucleotide polymorphisms associated with the risk of developing Colorectal cancer and survival

Background: There is variability in clinical outcome for patients with apparently the same stage colorectal cancer (CRC). Single nucleotide polymorphisms (SNPs) mapping to chromosomes 1q41, 3q26.2, 6p21, 8q23.3, 8q24.21, 10p14, 11q13, 11q23.1, 12q13.13, 14q22, 14q22.2, 15q13.3, 16q22.1, 18q21.1, 19q13.11, 20p12, 20p12.3, 20q13.33 and Xp22 have robustly been shown to be associated with the risk of developing CRC. Since germline variation can also influence patient outcome the relationship between these SNPs and patient survivorship from CRC was examined. Methods: All enrolled into the National Study of Colorectal Cancer Genetics (NSCCG) were genotyped for 1q41, 3q26.2, 6p21, 8q23.3, 8q24.21, 10p14, 11q13, 11q23.1, 12q13.13, 14q22, 14q22.2, 15q13.3, 16q22.1, 18q21.1, 19q13.11, 20p12, 20p12.3, 20q13.33 and xp22 SNPs. Linking this information to the National Cancer Data Repository allowed patient genotype to be related to survival. Results: The linked dataset consisted of 4,327 individuals. 14q22.22 genotype defined by the SNP rs4444235 showed a significant association with overall survival. Specifically, the C allele was associated with poorer observed survival (per allele hazard ratio 1.13, 95% confidence interval 1.05-1.22, P = 0.0015). Conclusion: The CRC susceptibility SNP rs4444235 also appears to exert an influence in modulating patient survival and warrants further evaluation as a potential prognostic marker

Interaction between polymorphisms in aspirin metabolic pathways, regular aspirin use and colorectal cancer risk: A case-control study in unselected white European populations

Regular aspirin use is associated with reduced risk of colorectal cancer (CRC). Variation in aspirin’s chemoprevention efficacy has been attributed to the presence of single nucleotide polymorphisms (SNPs). We conducted a meta-analysis using two large population-based case-control datasets, the UK-Leeds Colorectal Cancer Study Group and the NIH-Colon Cancer Family Registry, having a combined total of 3325 cases and 2262 controls. The aim was to assess 42 candidate SNPs in 15 genes whose association with colorectal cancer risk was putatively modified by aspirin use, in the literature. Log odds ratios (ORs) and standard errors were estimated for each dataset separately using logistic regression adjusting for age, sex and study site, and dataset-specific results were combined using random effects meta-analysis. Meta-analysis showed association between SNPs rs6983267, rs11694911 and rs2302615 with CRC risk reduction (All P<0.05). Association for SNP rs6983267 in the CCAT2 gene only was noteworthy after multiple test correction (P = 0.001). Site-specific analysis showed association between SNPs rs1799853 and rs2302615 with reduced colon cancer risk only (P = 0.01 and P = 0.004, respectively), however neither reached significance threshold following multiple test correction. Meta-analysis of SNPs rs2070959 and rs1105879 in UGT1A6 gene showed interaction between aspirin use and CRC risk (Pinteraction = 0.01 and 0.02, respectively); stratification by aspirin use showed an association for decreased CRC risk for aspirin users having a wild-type genotype (rs2070959 OR = 0.77, 95% CI = 0.68–0.86; rs1105879 OR = 0.77 95% CI = 0.69–0.86) compared to variant allele cariers. The direction of the interaction however is in contrast to that published in studies on colorectal adenomas. Both SNPs showed potential site-specific interaction with aspirin use and colon cancer risk only (Pinteraction = 0.006 and 0.008, respectively), with the direction of association similar to that observed for CRC. Additionally, they showed interaction between any non-steroidal anti-inflammatory drugs (including aspirin) use and CRC risk (Pinteraction = 0.01 for both). All gene x environment (GxE) interactions however were not significant after multiple test correction. Candidate gene investigation indicated no evidence of GxE interaction between genetic variants in genes involved in aspirin pathways, regular aspirin use and colorectal cancer risk

Recurrent Coding Sequence Variation Explains only A Small Fraction of the Genetic Architecture of Colorectal Cancer

Whilst common genetic variation in many non-coding genomic regulatory regions are known to impart risk of colorectal cancer (CRC), much of the heritability of CRC remains unexplained. To examine the role of recurrent coding sequence variation in CRC aetiology, we genotyped 12,638 CRCs cases and 29,045 controls from six European populations. Single-variant analysis identified a coding variant (rs3184504) in SH2B3 (12q24) associated with CRC risk (OR = 1.08, P = 3.9 × 10-7), and novel damaging coding variants in 3 genes previously tagged by GWAS efforts; rs16888728 (8q24) in UTP23 (OR = 1.15, P = 1.4 × 10-7); rs6580742 and rs12303082 (12q13) in FAM186A (OR = 1.11, P = 1.2 × 10-

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible