2,045 research outputs found

    Unsupervised correspondence with combined geometric learning and imaging for radiotherapy applications

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    The aim of this study was to develop a model to accurately identify corresponding points between organ segmentations of different patients for radiotherapy applications. A model for simultaneous correspondence and interpolation estimation in 3D shapes was trained with head and neck organ segmentations from planning CT scans. We then extended the original model to incorporate imaging information using two approaches: 1) extracting features directly from image patches, and 2) including the mean square error between patches as part of the loss function. The correspondence and interpolation performance were evaluated using the geodesic error, chamfer distance and conformal distortion metrics, as well as distances between anatomical landmarks. Each of the models produced significantly better correspondences than the baseline non-rigid registration approach. The original model performed similarly to the model with direct inclusion of image features. The best performing model configuration incorporated imaging information as part of the loss function which produced more anatomically plausible correspondences. We will use the best performing model to identify corresponding anatomical points on organs to improve spatial normalisation, an important step in outcome modelling, or as an initialisation for anatomically informed registrations. All our code is publicly available at https://github.com/rrr-uom-projects/Unsup-RT-Corr-NetComment: Accepted in 3rd Workshop on Shape in Medical Imaging (ShapeMI 2023). This preprint has not undergone peer review or any post-submission improvements or correction

    Complete Genome Sequence and Comparative Metabolic Profiling of the Prototypical Enteroaggregative Escherichia coli Strain 042

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    Background \ud Escherichia coli can experience a multifaceted life, in some cases acting as a commensal while in other cases causing intestinal and/or extraintestinal disease. Several studies suggest enteroaggregative E. coli are the predominant cause of E. coli-mediated diarrhea in the developed world and are second only to Campylobacter sp. as a cause of bacterial-mediated diarrhea. Furthermore, enteroaggregative E. coli are a predominant cause of persistent diarrhea in the developing world where infection has been associated with malnourishment and growth retardation. \ud \ud Methods \ud In this study we determined the complete genomic sequence of E. coli 042, the prototypical member of the enteroaggregative E. coli, which has been shown to cause disease in volunteer studies. We performed genomic and phylogenetic comparisons with other E. coli strains revealing previously uncharacterised virulence factors including a variety of secreted proteins and a capsular polysaccharide biosynthetic locus. In addition, by using Biolog™ Phenotype Microarrays we have provided a full metabolic profiling of E. coli 042 and the non-pathogenic lab strain E. coli K-12. We have highlighted the genetic basis for many of the metabolic differences between E. coli 042 and E. coli K-12. \ud \ud Conclusion \ud This study provides a genetic context for the vast amount of experimental and epidemiological data published thus far and provides a template for future diagnostic and intervention strategies

    Developing and enhancing biodiversity monitoring programmes: a collaborative assessment of priorities

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    1.Biodiversity is changing at unprecedented rates, and it is increasingly important that these changes are quantified through monitoring programmes. Previous recommendations for developing or enhancing these programmes focus either on the end goals, that is the intended use of the data, or on how these goals are achieved, for example through volunteer involvement in citizen science, but not both. These recommendations are rarely prioritized. 2.We used a collaborative approach, involving 52 experts in biodiversity monitoring in the UK, to develop a list of attributes of relevance to any biodiversity monitoring programme and to order these attributes by their priority. We also ranked the attributes according to their importance in monitoring biodiversity in the UK. Experts involved included data users, funders, programme organizers and participants in data collection. They covered expertise in a wide range of taxa. 3.We developed a final list of 25 attributes of biodiversity monitoring schemes, ordered from the most elemental (those essential for monitoring schemes; e.g. articulate the objectives and gain sufficient participants) to the most aspirational (e.g. electronic data capture in the field, reporting change annually). This ordered list is a practical framework which can be used to support the development of monitoring programmes. 4.People's ranking of attributes revealed a difference between those who considered attributes with benefits to end users to be most important (e.g. people from governmental organizations) and those who considered attributes with greatest benefit to participants to be most important (e.g. people involved with volunteer biological recording schemes). This reveals a distinction between focussing on aims and the pragmatism in achieving those aims. 5.Synthesis and applications. The ordered list of attributes developed in this study will assist in prioritizing resources to develop biodiversity monitoring programmes (including citizen science). The potential conflict between end users of data and participants in data collection that we discovered should be addressed by involving the diversity of stakeholders at all stages of programme development. This will maximize the chance of successfully achieving the goals of biodiversity monitoring programmes

    Fine-mapping identifies multiple prostate cancer risk loci at 5p15, one of which associates with TERT expression

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    Associations between single nucleotide polymorphisms (SNPs) at 5p15 and multiple cancer types have been reported. We have previously shown evidence for a strong association between prostate cancer (PrCa) risk and rs2242652 at 5p15, intronic in the telomerase reverse transcriptase (TERT) gene that encodes TERT. To comprehensively evaluate the association between genetic variation across this region and PrCa, we performed a fine-mapping analysis by genotyping 134 SNPs using a custom Illumina iSelect array or Sequenom MassArray iPlex, followed by imputation of 1094 SNPs in 22 301 PrCa cases and 22 320 controls in The PRACTICAL consortium. Multiple stepwise logistic regression analysis identified four signals in the promoter or intronic regions of TERT that independently associated with PrCa risk. Gene expression analysis of normal prostate tissue showed evidence that SNPs within one of these regions also associated with TERT expression, providing a potential mechanism for predisposition to disease

    Scintillation-limited photometry with the 20-cm NGTS telescopes at Paranal Observatory

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    Ground-based photometry of bright stars is expected to be limited by atmospheric scintillation, although in practice observations are often limited by other sources of systematic noise. We analyse 122 nights of bright star (Gmag ≲ 11.5) photometry using the 20-cm telescopes of the Next-Generation Transit Survey (NGTS) at the Paranal Observatory in Chile. We compare the noise properties to theoretical noise models and we demonstrate that NGTS photometry of bright stars is indeed limited by atmospheric scintillation. We determine a median scintillation coefficient at the Paranal Observatory of CY=1.54⁠, which is in good agreement with previous results derived from turbulence profiling measurements at the observatory. We find that separate NGTS telescopes make consistent measurements of scintillation when simultaneously monitoring the same field. Using contemporaneous meteorological data, we find that higher wind speeds at the tropopause correlate with a decrease in long-exposure (t = 10 s) scintillation. Hence, the winter months between June and August provide the best conditions for high-precision photometry of bright stars at the Paranal Observatory. This work demonstrates that NGTS photometric data, collected for searching for exoplanets, contains within it a record of the scintillation conditions at Paranal
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