Image patch analysis and clustering of sunspots: a dimensionality reduction approach

Sunspots, as seen in white light or continuum images, are associated with regions of high magnetic activity on the Sun, visible on magnetogram images. Their complexity is correlated with explosive solar activity and so classifying these active regions is useful for predicting future solar activity. Current classification of sunspot groups is visually based and suffers from bias. Supervised learning methods can reduce human bias but fail to optimally capitalize on the information present in sunspot images. This paper uses two image modalities (continuum and magnetogram) to characterize the spatial and modal interactions of sunspot and magnetic active region images and presents a new approach to cluster the images. Specifically, in the framework of image patch analysis, we estimate the number of intrinsic parameters required to describe the spatial and modal dependencies, the correlation between the two modalities and the corresponding spatial patterns, and examine the phenomena at different scales within the images. To do this, we use linear and nonlinear intrinsic dimension estimators, canonical correlation analysis, and multiresolution analysis of intrinsic dimension.Comment: 5 pages, 7 figures, accepted to ICIP 201

Image patch analysis of sunspots and active regions. II. Clustering via matrix factorization

Separating active regions that are quiet from potentially eruptive ones is a key issue in Space Weather applications. Traditional classification schemes such as Mount Wilson and McIntosh have been effective in relating an active region large scale magnetic configuration to its ability to produce eruptive events. However, their qualitative nature prevents systematic studies of an active region's evolution for example. We introduce a new clustering of active regions that is based on the local geometry observed in Line of Sight magnetogram and continuum images. We use a reduced-dimension representation of an active region that is obtained by factoring the corresponding data matrix comprised of local image patches. Two factorizations can be compared via the definition of appropriate metrics on the resulting factors. The distances obtained from these metrics are then used to cluster the active regions. We find that these metrics result in natural clusterings of active regions. The clusterings are related to large scale descriptors of an active region such as its size, its local magnetic field distribution, and its complexity as measured by the Mount Wilson classification scheme. We also find that including data focused on the neutral line of an active region can result in an increased correspondence between our clustering results and other active region descriptors such as the Mount Wilson classifications and the $R$ value. We provide some recommendations for which metrics, matrix factorization techniques, and regions of interest to use to study active regions.Comment: Accepted for publication in the Journal of Space Weather and Space Climate (SWSC). 33 pages, 12 figure

Image patch analysis of sunspots and active regions. I. Intrinsic dimension and correlation analysis

The flare-productivity of an active region is observed to be related to its spatial complexity. Mount Wilson or McIntosh sunspot classifications measure such complexity but in a categorical way, and may therefore not use all the information present in the observations. Moreover, such categorical schemes hinder a systematic study of an active region's evolution for example. We propose fine-scale quantitative descriptors for an active region's complexity and relate them to the Mount Wilson classification. We analyze the local correlation structure within continuum and magnetogram data, as well as the cross-correlation between continuum and magnetogram data. We compute the intrinsic dimension, partial correlation, and canonical correlation analysis (CCA) of image patches of continuum and magnetogram active region images taken from the SOHO-MDI instrument. We use masks of sunspots derived from continuum as well as larger masks of magnetic active regions derived from the magnetogram to analyze separately the core part of an active region from its surrounding part. We find the relationship between complexity of an active region as measured by Mount Wilson and the intrinsic dimension of its image patches. Partial correlation patterns exhibit approximately a third-order Markov structure. CCA reveals different patterns of correlation between continuum and magnetogram within the sunspots and in the region surrounding the sunspots. These results also pave the way for patch-based dictionary learning with a view towards automatic clustering of active regions.Comment: Accepted for publication in the Journal of Space Weather and Space Climate (SWSC). 23 pages, 11 figure

Comparison of zooplankton data collected by a continuous semi-automatic sampler (CALPS) and a traditional vertical ring net

We compared and evaluated the performance of a Continuous Automatic Litter and Plankton Sampler (CALPS) against the traditional ring net vertical haul. CALPS is a custom-made semi-automatic sampler, which collects water using a pump system at a single depth along a predetermined transect as the ship sails. CALPS underestimated species abundance compared to the ring net by a factor 1.61, but both datasets illustrated a similar species composition, community size structure and good agreement in the spatial distribution of abundance. Our analysis suggests that avoidance of the CALPS is likely to be the main factor responsible for the observed difference in sampling efficiency, but other factors, such as depth, area sampled and zooplankton patchiness, are also likely to play their part. We conclude that whilst the CALPS is not suitable for investigations that require accurate measures of abundance, it is an ideal tool to identify and quantify changes in plankton communities and diversity. A particular advantage over more traditional vertical sampling methods is that it can be integrated within existing multidisciplinary surveys at little extra cost, thus making the CALPS particularly valuable as part of integrated monitoring programmes to underpin policy areas such as the EU Marine Strategy Framework Directive

A radioiodinated rucaparib analogue as an Auger electron emitter for cancer therapy

Introduction: Radioligand therapy (RLT) is an expanding field that has shown great potential in the fight against cancer. Radionuclides that can be carried by selective ligands such as antibodies, peptides, and small molecules targeting cancerous cells have demonstrated a clear improvement in the move towards precision medicine. Poly (ADP-ribose) polymerase (PARP) is a family of enzymes involved in DNA damage repair signalling pathway, with PARP inhibitors olaparib, talazoparib, niraparib, veliparib, and rucaparib having FDA approval for cancer therapy in routine clinical use. Based on our previous work with the radiolabelled PARP inhibitor [18F]rucaparib, we replaced the fluorine-18 moiety, used for PET imaging, with iodine-123, a radionuclide used for SPECT imaging and Auger electron therapy, resulting in 8-[123I]iodo-5-(4-((methylamino)methyl)phenyl)-2,3,4,6-tetrahydro-1H-azepino[5,4,3-cd]indol-1-one, ([123I]GD1), as a potential radiopharmaceutical for RLT.Methods: [123I]GD1 was synthesized via copper-mediated radioiodination from a selected boronic esters precursor. In vitro uptake, retention, blocking, and effects on clonogenic survival with [123I]GD1 treatment were tested in a panel of cancer cell lines. Enzymatic inhibition of PARP by GD1 was also tested in a cell-free system. The biodistribution of [123I]GD1 was investigated by SPECT/CT in mice following intravenous administration.Results: Cell-free enzymatic inhibition and in vitro blocking experiments confirmed a modest ability of GD1 to inhibit PARP-1, IC50 = 239 nM. In vitro uptake of [123I]GD1 in different cell lines was dose dependent, and radiolabelled compound was retained in cells for &gt;2 h. Significantly reduced clonogenic survival was observed in vitro after exposure of cells for 1 h with as low as 50 kBq of [123I]GD1. The biodistribution of [123I]GD1 was further characterized in vivo showing both renal and hepatobiliary clearance pathways with a biphasic blood clearance.Conclusion: We present the development of a new theragnostic agent based on the rucaparib scaffold and its evaluation in in vitro and in vivo models. The data reported show that [123I]GD1 may have potential to be used as a theragnostic agent.</p

Radiofluorination of a highly potent ATM inhibitor as a potential PET imaging agent

PURPOSE: Ataxia telangiectasia mutated (ATM) is a key mediator of the DNA damage response, and several ATM inhibitors (ATMi) are currently undergoing early phase clinical trials for the treatment of cancer. A radiolabelled ATMi to determine drug pharmacokinetics could assist patient selection in a move towards more personalised medicine. The aim of this study was to synthesise and investigate the first 18F-labelled ATM inhibitor [18F]1 for non-invasive imaging of ATM protein and ATMi pharmacokinetics. METHODS: Radiofluorination of a confirmed selective ATM inhibitor (1) was achieved through substitution of a nitro-precursor with [18F]fluoride. Uptake of [18F]1 was assessed in vitro in H1299 lung cancer cells stably transfected with shRNA to reduce expression of ATM. Blocking studies using several non-radioactive ATM inhibitors assessed binding specificity to ATM. In vivo biodistribution studies were performed in wild-type and ATM-knockout C57BL/6 mice using PET/CT and ex vivo analysis. Uptake of [18F]1 in H1299 tumour xenografts was assessed in BALB/c nu/nu mice. RESULTS: Nitro-precursor 2 was synthesised with an overall yield of 12%. Radiofluorination of 2 achieved radiochemically pure [18F]1 in 80 ± 13 min with a radiochemical yield of 20 ± 13% (decay-corrected) and molar activities up to 79.5 GBq/μmol (n = 11). In vitro, cell-associated activity of [18F]1 increased over 1 h, and retention of [18F]1 dropped to 50% over 2 h. [18F]1 uptake did not correlate with ATM expression, but could be reduced significantly with an excess of known ATM inhibitors, demonstrating specific binding of [18F]1 to ATM. In vivo, fast hepatobiliary clearance was observed with tumour uptake ranging 0.13-0.90%ID/g after 1 h. CONCLUSION: Here, we report the first radiofluorination of an ATM inhibitor and its in vitro and in vivo biological evaluations, revealing the benefits but also some limitations of 18F-labelled ATM inhibitors

Local exome sequences facilitate imputation of less common variants and increase power of genome wide association studies

The analysis of less common variants in genome-wide association studies promises to elucidate complex trait genetics but is hampered by low power to reliably detect association. We show that addition of population-specific exome sequence data to global reference data allows more accurate imputation, particularly of less common SNPs (minor allele frequency 1–10%) in two very different European populations. The imputation improvement corresponds to an increase in effective sample size of 28–38%, for SNPs with a minor allele frequency in the range 1–3%

Establishing population-based surveillance of diagnostic timeliness using linked cancer registry and administrative data for patients with colorectal and lung cancer.

BACKGROUND: Diagnostic timeliness in cancer patients is important for clinical outcomes and patient satisfaction but, to-date, continuous monitoring of diagnostic intervals in nationwide incident cohorts has been impossible in England. METHODS: We developed a new methodology for measuring the secondary care diagnostic interval (SCDI - first relevant secondary care contact to diagnosis) using linked cancer registration and healthcare utilisation data. Using this method, we subsequently examined diagnostic timeliness in colorectal and lung cancer patients (2014-15) by socio-demographic characteristics, diagnostic route and stage at diagnosis. RESULTS: The approach assigned SCDIs to 94.4% of all incident colorectal cancer cases [median length (90th centile) of 25 (104) days] and 95.3% of lung cancer cases [36 (144) days]. Advanced stage patients had shorter intervals (median, colorectal: stage 1 vs 4 - 34 vs 19 days; lung stage 1&2 vs 3B&4 - 70 vs 27 days). Routinely referred patients had the longest (colorectal: 61, lung: 69 days) and emergency presenters the shortest intervals (colorectal: 3, lung: 14 days). Comorbidities and additional diagnostic tests were also associated with longer intervals. CONCLUSION: This new method can enable repeatable nationwide measurement of cancer diagnostic timeliness in England and identifies actionable variation to inform early diagnosis interventions and target future research.GL is supported by a Cancer Research UK Advanced Clinician Scientist Fellowship (award C18081/A18180). GL is an associate director (co-investigator) of the multi-institutional CanTest Research Collaborative funded by a Cancer Research UK Population Research Catalyst award (C8640/A23385

BIOFRAG: A new database for analysing BIOdiversity responses to forest FRAGmentation

Habitat fragmentation studies are producing inconsistent and complex results across which it is nearly impossible to synthesise. Consistent analytical techniques can be applied to primary datasets, if stored in a flexible database that allows simple data retrieval for subsequent analyses. Method: We developed a relational database linking data collected in the field to taxonomic nomenclature, spatial and temporal plot attributes and further environmental variables (e.g. information on biogeographic region. Typical field assessments include measures of biological variables (e.g. presence, abundance, ground cover) of one species or a set of species linked to a set of plots in fragments of a forested landscape. Conclusion: The database currently holds records of 5792 unique species sampled in 52 landscapes in six of eight biogeographic regions: mammals 173, birds 1101, herpetofauna 284, insects 2317, other arthropods: 48, plants 1804, snails 65. Most species are found in one or two landscapes, but some are found in four. Using the huge amount of primary data on biodiversity response to fragmentation becomes increasingly important as anthropogenic pressures from high population growth and land demands are increasing. This database can be queried to extract data for subsequent analyses of the biological response to forest fragmentation with new metrics that can integrate across the components of fragmented landscapes. Meta-analyses of findings based on consistent methods and metrics will be able to generalise over studies allowing inter-comparisons for unified answers. The database can thus help researchers in providing findings for analyses of trade-offs between land use benefits and impacts on biodiversity and to track performance of management for biodiversity conservation in human-modified landscapes.Fil: Pfeifer, Marion. Imperial College London; Reino UnidoFil: Lefebvre, Veronique. Imperial College London; Reino UnidoFil: Gardner, Toby A.. Stockholm Environment Institute; SueciaFil: Arroyo Rodríguez, Víctor. Universidad Nacional Autónoma de México; MéxicoFil: Baeten, Lander. University of Ghent; BélgicaFil: Banks Leite, Cristina. Imperial College London; Reino UnidoFil: Barlow, Jos. Lancaster University; Reino UnidoFil: Betts, Matthew G.. State University of Oregon; Estados UnidosFil: Brunet, Joerg. Swedish University of Agricultural Sciences; SueciaFil: Cerezo Blandón, Alexis Mauricio. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; ArgentinaFil: Cisneros, Laura M.. University of Connecticut; Estados UnidosFil: Collard, Stuart. Nature Conservation Society of South Australia; AustraliaFil: D´Cruze, Neil. The World Society for the Protection of Animals; Reino UnidoFil: Da Silva Motta, Catarina. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Duguay, Stephanie. Carleton University; CanadáFil: Eggermont, Hilde. University of Ghent; BélgicaFil: Eigenbrod, Félix. University of Southampton; Reino UnidoFil: Hadley, Adam S.. State University of Oregon; Estados UnidosFil: Hanson, Thor R.. No especifíca;Fil: Hawes, Joseph E.. University of East Anglia; Reino UnidoFil: Heartsill Scalley, Tamara. United State Department of Agriculture. Forestry Service; Puerto RicoFil: Klingbeil, Brian T.. University of Connecticut; Estados UnidosFil: Kolb, Annette. Universitat Bremen; AlemaniaFil: Kormann, Urs. Universität Göttingen; AlemaniaFil: Kumar, Sunil. State University of Colorado - Fort Collins; Estados UnidosFil: Lachat, Thibault. Swiss Federal Institute for Forest; SuizaFil: Lakeman Fraser, Poppy. Imperial College London; Reino UnidoFil: Lantschner, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche; ArgentinaFil: Laurance, William F.. James Cook University; AustraliaFil: Leal, Inara R.. Universidade Federal de Pernambuco; BrasilFil: Lens, Luc. University of Ghent; BélgicaFil: Marsh, Charles J.. University of Leeds; Reino UnidoFil: Medina Rangel, Guido F.. Universidad Nacional de Colombia; ColombiaFil: Melles, Stephanie. University of Toronto; CanadáFil: Mezger, Dirk. Field Museum of Natural History; Estados UnidosFil: Oldekop, Johan A.. University of Sheffield; Reino UnidoFil: Overal , Williams L.. Museu Paraense Emílio Goeldi. Departamento de Entomologia; BrasilFil: Owen, Charlotte. Imperial College London; Reino UnidoFil: Peres, Carlos A.. University of East Anglia; Reino UnidoFil: Phalan, Ben. University of Southampton; Reino UnidoFil: Pidgeon, Anna Michle. University of Wisconsin; Estados UnidosFil: Pilia, Oriana. Imperial College London; Reino UnidoFil: Possingham, Hugh P.. Imperial College London; Reino Unido. The University Of Queensland; AustraliaFil: Possingham, Max L.. No especifíca;Fil: Raheem, Dinarzarde C.. Royal Belgian Institute of Natural Sciences; Bélgica. Natural History Museum; Reino UnidoFil: Ribeiro, Danilo B.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Ribeiro Neto, Jose D.. Universidade Federal de Pernambuco; BrasilFil: Robinson, Douglas W.. State University of Oregon; Estados UnidosFil: Robinson, Richard. Manjimup Research Centre; AustraliaFil: Rytwinski, Trina. Carleton University; CanadáFil: Scherber, Christoph. Universität Göttingen; AlemaniaFil: Slade, Eleanor M.. University of Oxford; Reino UnidoFil: Somarriba, Eduardo. Centro Agronómico Tropical de Investigación y Enseñanza; Costa RicaFil: Stouffer, Philip C.. State University of Louisiana; Estados UnidosFil: Struebig, Matthew J.. University of Kent; Reino UnidoFil: Tylianakis, Jason M.. University College London; Estados Unidos. Imperial College London; Reino UnidoFil: Teja, Tscharntke. Universität Göttingen; AlemaniaFil: Tyre, Andrew J.. Universidad de Nebraska - Lincoln; Estados UnidosFil: Urbina Cardona, Jose N.. Pontificia Universidad Javeriana; ColombiaFil: Vasconcelos, Heraldo L.. Universidade Federal de Uberlandia; BrasilFil: Wearn, Oliver. Imperial College London; Reino Unido. The Zoological Society of London; Reino UnidoFil: Wells, Konstans. University of Adelaide; AustraliaFil: Willig, Michael R.. University of Connecticut; Estados UnidosFil: Wood, Eric. University of Wisconsin; Estados UnidosFil: Young, Richard P.. Durrell Wildlife Conservation Trust; Reino UnidoFil: Bradley, Andrew V.. Imperial College London; Reino UnidoFil: Ewers, Robert M.. Imperial College London; Reino Unid